hypothesis in genes

If you're seeing this message, it means we're having trouble loading external resources on our website.

If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked.

To log in and use all the features of Khan Academy, please enable JavaScript in your browser.

Biology library

Course: biology library > unit 18.

DNA replication and RNA transcription and translation
Alleles and genes
Intro to gene expression (central dogma)
The genetic code

One gene, one enzyme

Nucleic acids
Central dogma

Key points:

The one gene, one enzyme hypothesis is the idea that each gene encodes a single enzyme. Today, we know that this idea is generally (but not exactly) correct.
Sir Archibald Garrod, a British medical doctor, was the first to suggest that genes were connected to enzymes.
Beadle and Tatum confirmed Garrod's hypothesis using genetic and biochemical studies of the bread mold Neurospora .
Beadle and Tatum identified bread mold mutants that were unable to make specific amino acids. In each one, a mutation had "broken" an enzyme needed to build a certain amino acid.

Introduction

Garrod’s "inborn errors of metabolism", beadle and tatum: connecting genes to enzymes, why bread mold is great for experiments, let's make some mutants.

Obtain Neurospora spores.
Expose spores to X-rays. Some spores now have random mutations.
Cross spores to normal (non-irradiated spores) and collect the progeny spores.
Transfer each progeny spore individually to its own tube of complete medium, so that it makes a colony.
Transfer part of each colony to its own tube of minimal medium.
Nutritional mutants may be identified as colonies that grew on complete medium, but did not grow when transferred to minimal medium.

Pinpointing the broken pathway

If a mutant grew on minimal medium with amino acids (but not vitamins), it must be unable to make one or more amino acids.
If a mutant grew on the vitamin medium but not the amino acid medium, it must be unable to make one or more vitamins.
Start with a nutritional mutant. By definition, the nutritional mutant can grow on complete medium, but not on minimal medium.
Now, we are going to find out what in the complete medium it is that the nutritional mutant needs to grown. To do so, we transfer a little bit of the colony into each of two tubes: one with minimal medium + full set of vitamins, the other with minimal medium + all 20 amino acids.
In this example, the mutant is rescued by the mixture of all 20 amino acids, but not by the set of vitamins. This indicates that the mutation makes the mutant unable to synthesize one or more amino acids.
Since the mutant is rescued by the amino acid mix, the next question becomes: what amino acid(s) is it unable to make? To answer this question, we transfer a bit of the mutant colony into each of 20 tubes. Each tube contains minimal medium plus one of the 20 amino acids.
In this example, the mutant can grow in the tube containing minimal medium + arginine, but not in any of the other 19 tubes. (I.e., the mutant is rescued by arginine). This indicates that the mutation in the mutant must disrupt arginine biosynthesis.

"One gene-one enzyme" today

Some genes encode proteins that are not enzymes. Enzymes are just one category of protein. There are many non-enzyme proteins in cells, and these proteins are also encoded by genes.
Some genes encode a subunit of a protein, not a whole protein. In general, a gene encodes one polypeptide, meaning one chain of amino acids. Some proteins consist of several polypeptides from different genes. What about alternative splicing? Alternative splicing is another exception! In eukaryotes only, some genes can encode several similar but non-identical polypeptides through a process called alternative splicing , in which different "chunks" of a gene are chosen for use during gene expression 4 ‍ . Alternative splicing does not take place in bacteria, and not all eukaryotic genes are alternatively spliced.
Some genes don't encode polypeptides. Some genes actually encode functional RNA molecules rather than polypeptides!

Works cited:

Piro, A. Tagarelli, G., Lagonia, P., Quattrone, A., and Tagarelli, A. (2010). Archibald Edward Garrod and alcaptonuria: “Inborn errors of metabolism” revisited. Genetics in Medicine , 12 , 475. http://www.ncbi.nlm.nih.gov/pubmed/20703138 .
Garrod, A. E. (1902). The incidence of alkaptonuria: A study in chemical individuality. Lancet , 2 , 1616-1620. Retrieved from http://www.esp.org/foundations/genetics/classical/ag-02.pdf .
Genome News Network. (2004). 1908: Archibald E. Garrod (1857-1936) postulates that genetic defects cause many inherited diseases. In Genetics and genomics timeline . Retrieved from http://www.genomenewsnetwork.org/resources/timeline/1908_Garrod.php .
Brief forward to ESP reprint of: Garrod, A. E. (1902). The incidence of alkaptonuria: A study in chemical individuality. Lancet , 2 , 1616-1620. Retrieved from http://www.esp.org/foundations/genetics/classical/ag-02.pdf .
Nasrallah, J. B. (2012). Adrian M. Srb. In Biographical memoirs , 5. Retrieved from http://www.nasonline.org/publications/biographical-memoirs/memoir-pdfs/srb-adrian.pdf
Beadle, G. W. and Tatum, E. L. (1941). Genetic control of biochemical reactions in Neurospora . PNAS , 27 , 502. Retrieved from http://www.pnas.org/content/27/11/499.full.pdf .
Beadle, G. W. and Tatum, E. L. (1941). Genetic control of biochemical reactions in Neurospora . PNAS , 27 , 500. Retrieved from http://www.pnas.org/content/27/11/499.full.pdf .
Griffiths, A. J. F., Miller, J. H., Suzuki, D. T., Lewontin, R. C., and Gelbart, W. M. (2000). The procedure used by Beadle and Tatum. In An introduction to genetic analysis (7th ed.). New York, NY: W. H. Freeman. Retrieved from http://www.ncbi.nlm.nih.gov/books/NBK22044/figure/A1616/?report=objectonly .
Beadle, G. W. and Tatum, E. L. (1945). Neurospora. II. Methods of producing and detecting mutations concerned with nutritional requirements. American Journal of Botany , 32 , 679-680. Retrieved from http://www.jstor.org/stable/2437625 .
Beadle, G. W. and Tatum, E. L. (1945). Neurospora. II. Methods of producing and detecting mutations concerned with nutritional requirements. American Journal of Botany , 32 , 681. Retrieved from http://www.jstor.org/stable/2437625 .
Horowitz, N. H., Berg, P., Singer, M., Lederberg, J., Susman, M., Doebley, J., and Crow, J.F. (2004). A Centennial: George W. Beadle, 1903–1989. In J. F. Crow and W. F. Dove (eds.), Perspectives: Anecdotal, historical and critical commentaries on genetics . Genetics , 166 (1), 2. http://dx.doi.org/10.1534/genetics.166.1.1 .
Reece, J. B., Urry, L. A., Cain, M. L., Wasserman, S. A., Minorsky, P. V., and Jackson, R. B. (2011). The products of gene expression: A developing story. In Campbell biology (10th ed., p. 336). San Francisco, CA: Pearson.
Purves, W. K., Sadava, D. E., Orians, G. H., and Heller, H.C. (2004). One gene, one polypeptide. In Life: the science of biology (7th ed., p. 234). Sunderland, MA: Sinauer Associates.

Additional references:

Want to join the conversation.

Upvote Button navigates to signup page
Downvote Button navigates to signup page
Flag Button navigates to signup page

school Campus Bookshelves
menu_book Bookshelves
perm_media Learning Objects
login Login
how_to_reg Request Instructor Account
hub Instructor Commons
Download Page (PDF)
Download Full Book (PDF)
Periodic Table
Physics Constants
Scientific Calculator
Reference & Cite
Tools expand_more
Readability

selected template will load here

This action is not available.

6.1: One Gene - One Enzyme Theory

Last updated
Save as PDF
Page ID 4833

John W. Kimball
Tufts University & Harvard

Neurospora crassa

Neurospora crassa is an ascomycete, the red bread mold. Like all fungi, it reproduces by spores. It produces two kinds of spores:

Conidia are spores produced by asexual reproduction. Mitosis of the haploid nuclei of the active, growing fungus generates the conidia.
Ascospores , on the other hand, are formed following sexual reproduction. If two different mating types ("sexes") are allowed to grow together, they will fuse to form a diploid zygote. Meiosis of this zygote then gives rise to the haploid ascospores.

Neurospora is particularly well suited for genetic studies because

It can be grown quickly on simple culture medium.
It spends most of its life cycle in the haploid condition so any recessive mutations will show up in its phenotype.
Meiosis I, followed by
Meiosis II, followed by
one mitotic division
the zygote nucleus is heterozygous for a gene (shown here as a and A ) and
no crossing over near that locus occurs during meiosis I,

The One Gene - One Enzyme Theory

Sucrose, a few salts, and one vitamin — biotin — provide the nutrients that Neurospora needs to synthesize all the macromolecules of its cells.

Geneticists George W. Beadle and E. L. Tatum exposed some of the conidia of one mating type of Neurospora to ultraviolet rays in order to induce mutations.

Then individual irradiated spores were allowed to germinate on a "complete" medium; that is, one enriched with various vitamins and amino acids.
Once each had developed a mycelium, it was allowed to mate with the other mating type.
The ascospores produced were dissected out individually and each one placed on complete medium.
After growth had occurred, portions of each culture were subcultured on minimal medium .
Sometimes growth continued; sometimes it didn't.
When it did not ("1st" in the figure) , the particular strain was then supplied with a mixture of vitamins, amino acids, etc. until growth did occur ("2nd ").
Eventually each mutated strain was found to have acquired a need for one nutrient; in the example illustrated here, the vitamin thiamine ("3rd").

Beadle and Tatum reasoned that radiation had caused a gene that permits the synthesis of thiamine from the simple ingredients in minimal medium to mutate to an allele that does not. The synthesis of thiamine from sucrose requires a number of chemical reactions, each one catalyzed by a specific enzyme.

By adding, one at a time, the different precursors of thiamine to the medium in which their mutant mold was placed, they were able to narrow down the defect to the absence of a single enzyme.

If they added to the minimal medium any precursor further along in the process, growth occurred.
Any precursor before the blocked step could not support growth.

Thus, in this example, the conversion of precursor C to precursor D was blocked because of the absence of the needed enzyme ( c ).

This led them to postulate the one gene - one enzyme theory: each gene in an organism controls the production of a specific enzyme. It is these enzymes that catalyze the reactions that lead to the phenotype of the organism.

Today, we know that, in fact, not only enzymes, but all the other proteins from which the organism is built are encoded by genes.

Contributors and Attributions

John W. Kimball . This content is distributed under a Creative Commons Attribution 3.0 Unported (CC BY 3.0) license and made possible by funding from The Saylor Foundation.

Subscriber Services
For Authors
Publications
Archaeology
Art & Architecture
Bilingual dictionaries
Classical studies
Encyclopedias
English Dictionaries and Thesauri
Language reference
Linguistics
Media studies
Medicine and health
Names studies
Performing arts
Science and technology
Social sciences
Society and culture
Overview Pages
Subject Reference
English Dictionaries
Bilingual Dictionaries

gene-for-gene hypothesis

Quick reference.

The proposal that during their evolution a host and its parasite develop complementary genetic systems, with each gene that provides the host with resistance matched by a gene in the parasite that confers susceptibility. The interacting genes from the two species are called corresponding genes, since for each gene that conditions resistance in the host there is a corresponding gene that conditions avirulence in the parasite, and the products of the two genes interact. The product of the resistance gene serves as a receptor for a ligand produced by the parasite, directly or indirectly through expression of an avirulence gene. The binding of receptor and ligand is the recognition event that elicits through cellular signal transduction (q.v.), a cascade of defense responses that constitute the resistant phenotype. See Chronology, 1955, Flor; coevolution, Linum usitatissimum, Melampsora lini.

From: gene-for-gene hypothesis in A Dictionary of Genetics »

Subjects: Science and technology — Life Sciences

Retinoblastoma: present scenario and future challenges

Vishnu Vardhan Byroju 1 ,
Aisha Shigna Nadukkandy 2 ,
Marco Cordani ORCID: orcid.org/0000-0001-9342-4862 3 &
Lekha Dinesh Kumar ORCID: orcid.org/0000-0002-1263-7135 2

Cell Communication and Signaling volume 21 , Article number: 226 ( 2023 ) Cite this article

3133 Accesses

3 Citations

10 Altmetric

Metrics details

With an average incidence of 1 in every 18,000 live births, retinoblastoma is a rare type of intraocular tumour found to affect patients during their early childhood. It is curable if diagnosed at earlier stages but can become life-threateningly malignant if not treated timely. With no racial or gender predisposition, or even environmental factors known to have been involved in the incidence of the disease, retinoblastoma is often considered a clinical success story in pediatric oncology. The survival rate in highly developed countries is higher than 95% and they have achieved this because of the advancement in the development of diagnostics and treatment techniques. This includes developing the already existing techniques like chemotherapy and embarking on new strategies like enucleation, thermotherapy, cryotherapy, etc. Early diagnosis, studies on the etiopathogenesis and genetics of the disease are the need of the hour for improving the survival rates. According to the Knudson hypothesis, also known as the two hit hypothesis, two hits on the retinoblastoma susceptibility (RB) gene is often considered as the initiating event in the development of the disease. Studies on the molecular basis of the disease have also led to deciphering the downstream events and thus in the discovery of biomarkers and related targeted therapies. Furthermore, improvements in molecular biology techniques enhanced the development of efficient methods for early diagnosis, genetic counseling, and prevention of the disease. In this review, we discuss the genetic and molecular features of retinoblastoma with a special emphasis on the mutation leading to the dysregulation of key signaling pathways involved in cell proliferation, DNA repair, and cellular plasticity. Also, we describe the classification, clinical and epidemiological relevance of the disease, with an emphasis on both the traditional and innovative treatments to tackle retinoblastoma.

Video Abstract

Introduction

With an ability to convert electromagnetic/ light energy to electrical energy, the retina acts as a transduction screen that enables the visualisation of any object in front of it by transmitting this electrical energy as nerve impulse to the cortical functioning centres [ 1 ]. It layers the innermost part of the eye and hosts various types of cells like rods and cones which are integral for its proper functioning. Various diseases like retinal tear, retinal detachment, diabetic retinopathy, macular degeneration, retinitis pigmentosa etc. have been associated with retina and its impaired functioning. One such disease is retinoblastoma, the most common malignant intraocular tumour in children. Retinoblastoma is theorized to arise from the cones of the retina, which have certain properties that leave them rather susceptible to tumorigenesis [ 2 ]. Globally, 1 in every 16,000 to 20,000 live births is known to be afflicted by retinoblastoma [ 3 ]. Most of the cases are diagnosed before the age of 5 and it accounts for 3% of all childhood cancers [ 4 ]. Of these, 200–300 new cases emerge in the United States alone and this incidence has not changed in over 40 years [ 5 ]. Previous studies indicated that there were significant differences in the incidence of retinoblastoma based on gender, ethnicity, and infections due to poor sanitation [ 6 ]. The newer studies, however, deny significance of such differences and consider retinoblastoma to have similar incidence throughout the world [ 4 ].

Despite being rare, retinoblastoma gained interest within the scientific community since RB1 gene is the first tumour suppressor gene to be discovered [ 7 ]. In its hereditary form, retinoblastoma is associated with de novo mutations resulting in tumours at other foci in the body which are termed ‘second primary tumours’ and is attributed to the role played by phosphorylated Rb protein [ 8 ]. Subjects with hereditary retinoblastomas are at a higher risk of developing other second primary tumours such as osteosarcomas, melanomas etc. [ 9 ]. Every form of retinoblastoma, familial and sporadic has the Rb gene mutated to some extent resulting in the downstream processing of aberrant transcripts [ 10 , 11 ]. RB1 gene is located on the largest acrocentric chromosome, 13 and consists of 27 exons [ 9 , 10 ]. Following transcription, Rb protein is formed and gets involved in the regulation of cell cycle at the G1-S checkpoint. Phosphorylation essentially acts to ‘switch off’ Rb tumour suppressor protein which results in [ 12 ] deregulation of downstream molecular events that eventually results in retinoblastoma [ 13 ].

Cell plasticity is a term usually referred to phenotypic and molecular changes resulting from genetic and epigenetic alterations responsible for cell variability and intra-tumor heterogeneity. Plasticity is a distinctive trait of tumor progression and represents an important evolutionary mechanism by which tumor cells can survive to environmental and energy stresses [ 14 ]. Concerning the functional significance, plasticity confers to cancer cells the ability to dynamically oscillate between different stages of differentiation and stemness with limited or high tumorigenic and metastatic potential [ 15 ]. Cancer cell plasticity is also linked to the epithelial-to-mesenchymal transition (EMT) program and metabolic rewiring from glycolytic metabolism to oxidative phosphorylation and involves a complex interplay between intracellular signaling pathways with environmental cues [ 16 , 17 ]. The major signaling pathways involved in retinoblastoma initiation and development are Rb, p53, Ras/MAPK and Notch pathways [ 18 , 19 ]. These belong to an oncogenic network that promotes phenotypic and molecular changes in cellular state to adapt retinoblastoma to extracellular stress and drug treatment. As described below, such pathways may lead to EMT activation [ 20 ], undifferentiated stem-like cellular state [ 21 ], or glycolytic shift towards OXPHOS to alternate energy fuels and metabolic routes depending on the need of tumor cells [ 22 , 23 ]. The deep understanding of the mechanism underlying cell plasticity in retinoblastoma may provide insights for establishing new therapeutic interventions.

Like many other diseases, economic disparities find their way into dictating presentation and survival rates in cases of retinoblastoma too across the world. Age group of subjects that present with signs of retinoblastoma is higher in middle and low-income countries as compared to affluent nations, suggesting deficit in diagnostic resources [ 24 ]. Survival rates also portray a similar picture with developed nations nearing 90%, middle income countries averaging 70% and low-income countries about 40%. (Income disparities were based on the World Bank classification) [ 25 , 26 ]. Financial constraints act as a major deterrent contributing to the delay in diagnosis and treatment in developing countries. Social stigma in certain cases also played a role in refusal of enucleation and resulted in the cancer metastasis. Availability of a cancer registry, infrastructure, multidisciplinary approach, medications, treatment noncompliance are known to be some of the major determinants of survival disparities [ 26 ].

Classification of retinoblastoma (WHO classification)

Retinoblastoma had major classification overhauls and has finally stabilized with the Reese-Ellsworth and ICRB (International Classification of Retinoblastoma) as the most accepted form as of now. Reese-Ellsworth (R-E) was considered to be the first classification done for intraocular cancer and was developed to predict the chances of saving the eye following external beam radiotherapy (Fig. 1 ; Table 1 ). However, in the 1990’s, when intravenous chemotherapy for intraocular retinoblastoma was introduced, the R-E classification system was no longer appropriate. Therefore, a new classification scheme referred as “International Intraocular Retinoblastoma Classification” (IIRC) was developed [ 27 ]. The IIRC scheme, groups the tumours into A to E classes depending on their size, location, and other features like the presence of small colonies of cancerous cells in the vitreous (retinoblastoma seeds) and the presence of retinal detachment. This staging was further modified to form the Intraocular Classification of Retinoblastoma (ICRB), which differed from the IIRC mainly in the definitions of the advanced groups. Even though well accepted, certain discrepancies have been reported with ICRB affecting 5.2% of the group under study [ 28 ]. While RE and ICRB are 5 stage classification systems, the ICRB provides a better distinction between the severely affected eyes and the eyes that can be salvaged with less effort (Table 2 ).

Pictorial representation for Reese Ellsworth’s Classification of Retinoblastoma. A graphical abstract of the Reese Ellsworth’s classification system prepared using arbitrarily chosen symbols to represent their corresponding groups within the classification system and to understand different demarcations of the eye. The 1a (yellow cloud shape) aims to represent a tumour behind the equator, solitary and less than 4-disc diameters in size; 1b (multiple yellow cloud shapes) aims to represent multiple tumours behind the equator of the retina with the largest tumour not exceeding 4-disc diameters.; 2a (purple diagonal shape) aims to represent a 4-10DD tumour behind the retina; 2b (Multiple purple diagonal shapes) represents multiple tumours between 4-10DD; 3a (Green triangle shape) aims to represent a tumour anterior to the equator of the retina; 3b (Green triangle shape in a different location) aims to represent a > 10DD tumour behind the equator; 4a (multiple shapes of varied colours) aims to represent multiple tumours with some of them larger than ten-disc diameters in size; 4b (yellow slip diagonal shape) aims to represent a tumour that is crossing the ora serrata; 5a (Large, undefined blue shape in the background) aims to represent a large tumour that covers more than half of the retina; 5b (X marked at the border of the figure and in multiple areas marked across the eye figure) aims to represent vitreous seeding of the eye

Furthermore, retinoblastoma has been assigned various stages depending upon the progression of the disease and its potential for metastasis. The system was named International Retinoblastoma Staging System (Table 3 ) where, the stage 0 often shows good prognosis with treatment while stage IV shows poor outcome. During stage IV, the cancer is considered to be extraocular and can lead to bulging out of the eye [ 29 ]. When it comes to differentiating it into various types, the disease can appear as unilateral, bilateral or trilateral. The chance of a patient developing a trilateral retinoblastoma is 6% higher in case of bilateral retinoblastoma as compared to unilateral and can be fatal in 50% of the cases. Another classification of retinoblastoma could be based on direction of progression of the disease; i.e. exophytic if the tumour originates in the retina and spreads in the direction of the brain behind or endophytic if the tissue spreads in an anatomic anterior direction.

Epidemiology

Most of the estimated incidence of retinoblastoma varies by country from 3.4 to 42.6 cases per million live births. In the United States alone, the incidence is 11.8 affected per million live births among children less than 5 years of age. This accounts to a global average of 8200 new cases per year, out of which 60% of cases are unilateral and 40% are bilateral. The unilateral retinoblastoma (most of which are sporadic) is diagnosed at a median age of 2 years while bilateral one is diagnosed earlier, at nearly 1 year of age [ 3 ]. Retinoblastoma has an autosomal dominance pattern with each offspring having a 50% risk of inheriting the RB1 gene mutation that has a 90% penetrance. Family history is positive in only 10% of the individuals, both in case of unilateral and bilateral retinoblastoma and these individuals are considered to have the heritable form. If an individual has heritable retinoblastoma, his or her siblings should be tested for germline mutation, presence or absence of which determines the future risk. If no mutation is found, the risk is very similar to the general population and if a mutation is found, the high risk necessitates periodic surveillance [ 30 ].

The future of survivors of retinoblastoma is tough as they have chances of developing other cancers due to metastasis or germline mutation. Even though there is survival probability of 9 out of 10, most of them turn blind. A stable incidence rate has been observed in the United States for about 40 years from 1973-to 2012 based on a report [ 31 ]. The incidence of retinoblastoma has been increasing in European nations when compared to previous reports. A multinational European study postulates that such an increase is linked to improved survival of familial subjects owing to advancement in the health care sector and the availability of resources [ 32 ]. A retrospective cohort study using the Finnish Cancer Registry (1964–2014) showed an increase in familial retinoblastoma cases while the overall incidence remained the same [ 3 ]. Canadian reports represents a stable incidence of retinoblastoma which is comparable to that of other developed nations [ 4 ]. Poland demonstrates a similar pattern of incidence and management of retinoblastoma to that of western Europe and North America despite being middle-income nations [ 5 ]. The lack of availability of registries has limited our understanding of trends in Africa. A higher incidence of retinoblastoma has been found in white population of South Africa, probably due to better access to diagnosis and management [ 6 ]. Studies from Southeast Asia were insufficient and demonstrated socioeconomic barriers for their access to health care system. Poor awareness, lack of training for health care workers to detect retinoblastoma early, and comorbidities resulted in late diagnosis and complex management [ 33 ]. A study of the incidence of retinoblastoma in Taiwan demonstrated no notable trend from 1998–2011. An initial declining trend from 2005 to 2011 followed by an increase in the incidence of retinoblastoma was noted in Lebanon. An increase in awareness among health care professionals and taking refugee data into consideration are some essential steps for further understanding of disease epidemiology [ 26 ]. Retinoblastoma presenting at later stages is common in developing countries and examination of children during primary care visits is essential to improve diagnosis and survival [ 25 ].

Screening and diagnosis of retinoblastoma

Screening of retinoblastoma involves various tests for detecting the symptoms (Fig. 2 ) of retinoblastoma. Leukocoria (sometimes referred to as the ‘cat’s eye reflex’) can be detected by the presence of a white reflection in photographs or the red reflex test. A simpler approach would be to use mobile phones for the same purpose where, such an application exists in the form of an app called “White eye Detector” developed by Bryan Shaw. Performing cover test detects the presence of strabismus while all other signs can be identified by a systematic visual examination. Screening by an ophthalmologist is a necessity in children with a positive family history of retinoblastoma. Offspring and siblings of affected patients require regular screening examinations in childhood unless genetic testing is done to rule out a gene mutation in which case the risk is similar to that of the general population. Genetic counselling for families with retinoblastoma can help determine the risk to future offspring and whether other family members are at risk of developing the disease [ 34 ].

Symptoms of retinoblastoma. Pie chart representation of the presenting symptoms of retinoblastoma

An ophthalmoscope view shows the optic disk, the physiological cup, the retinal vessels, the macula and the fovea centralis so the tumour is quite easily identified. Non-invasive two dimensional and three-dimensional real-time ultrasound techniques have eased detection significantly. Once the polymerase chain reaction (PCR) was invented, it became easy to identify the batch deletion of exons in chromosome no. 13 of the children whose parents carry the RB1 gene mutation. Quantitative multiplexing is an advanced form of the technique where several primers are used at the same time together to identify batch deletions [ 35 ]. Use of X Ray and Computed Tomography has found its place in detection of retinoblastoma relying on properties such as calcification in the latter technique. Gadolinium contrast enhancement followed by MRI scan has been helpful to detect the tumour. Fat saturation was quite helpful as well wherein the fat was suppressed at one time and was expressed at another time in anticipation of finding the nature of the tumour. T1 weighted imaging with a magnetization of 63% was used for better results [ 36 , 37 ].

Fluorescein Angiography is a technique that requires injection of a small bolus of fluorescent material into the blood stream which finally reaches the ophthalmic artery. A specialized camera takes pictures of the eye once it reaches there through the catheter using the fluorescence of the arteries of the eye as a light source [ 38 , 39 ]. Unsuccessful attempts at detecting retinoblastoma using positron emission tomography (which relied on detecting increased glucose consumption by the tumour) were made using Flourine-18-fluorodeoxyglucose throughout many years. The conclusion that FDG-PET is not currently widely established and does not provide any significant advantage over MRI/CT except in metastasis rendered MRI as the gold standard [ 40 ]. Early detection using an ultrasonogram in-utero to study the face and eyes can help in detection of the cancer, resulting in earlier detection and potential cure [ 41 ].

Treatment and management of the disease

Retinoblastoma is a cancer that can be cured if diagnosed at an appropriate time. The involvement of structures beyond the retina and the vitreous humour should be taken into consideration as they have the potential to progress into metastasis rapidly. The treatment of retinoblastoma is often complex and involves decisions to be made based on a number of factors including but not limited to the size of the tumour in various axes, age of the patient, risk of secondary metastasis, previous attempts made at chemotherapy, toxicity of the chemotherapeutic agent in the subject and laterality of the tumour [ 42 , 43 ].

Enucleation

Complete removal of the eye that is affected by the tumour, or surgical excision is termed as enucleation. It is the least conservative possible management and hence reserved for cases that cannot be helped otherwise. Enucleation should be avoided in cases where salvage is possible with other treatment modalities in an effort to preserve vision and improve conservation. For the first 2 years after surgery, all patients undergoing enucleation must be carefully monitored for the risk of orbital relapse. Hydroxyapatite implants coated with specialized polymers and have attachment sites for the extraocular muscles are being implemented. Overall, enucleation was widely used and continues to be used in cases where other treatment modalities are unhelpful [ 44 ].

Intra-arterial (IAC) chemotherapy

Pierre Gobin et al. have reported their overall experience with intra-arterial chemotherapy to be safe and effective in avoiding enucleation [ 45 ]. Modern microcatheter techniques were used to administer the chemotherapy agents and success was obtained with acceptable levels of toxicity. The choice of the drugs included mephalan, topotecan hydrochloride, carboplatin and methotrexate in this route of administration. The Kaplan Meier curves estimated the event free survival of receivers of the IAC route to be higher than other treatment modalities. Since deleterious after-effects of IVC were observed, IAC could successfully replace IVC route and furthermore it delivered a higher dose of chemo agents to the target site [ 45 ]. Intra-arterial chemotherapy is administered as either primary or secondary treatment interventions and studies reveal no significant difference in post-treatment vascular events. Since post chemotherapeutic toxicity was observed, there is a need for careful surveillance. Although intra-arterial chemotherapy is proving to be a strong treatment modality, its limitations require the implementation of better techniques [ 5 ]. IAC efficacy is decreased in cases of extensive collateral meningeal vascular presence due to dilution of the agent into these vessels. Collateral blood supply to the retina apart from the ophthalmic artery has variations and has implications in the dose delivery. Catheterization of relevant arteries requires skill and the technical difficulties could arise that can reduce the delivery of intra-arterial chemotherapy [ 46 ].

Intravitreal chemotherapy (IVitC)

Focused drug delivery to a vitreal seed hotspot is considered precision intra-vitreal chemotherapy and is an emerging technique [ 32 ]. Often used as an adjunct therapy to IAC, in IVitC, drugs are delivered directly into the vitreous cavity in advanced stages of retinoblastoma where vitreous seeding occurs. A combination of chemodrugs such as melphalan and topotecan [ 33 ] are the preferred mode of treatment when tumour seeds recur in the vitreous and is found to be more effective than the respective individual treatments [ 42 , 43 ]. While the presence of vitreous seeds is an indication for Intra-vitreal chemotherapy, contraindications include diffuse dispersion of the tumour seeds, invasion of the anterior chamber of the eye, hemorrhage into the vitreous humour, and secondary glaucoma [ 6 ]. Acute hemorrhagic retinopathy and heterochromia, the presence of different iris colours has been noted secondary to intra-vitreal melphalan and topotecan administration [ 25 , 26 ]. With the advent of nanoparticle delivery, intra-vitreal chemotherapy has promising prospects in the management of retinoblastoma [ 46 ].

Thermotherapy

This mode of treatment is often engaged for tumours of minor dimensions, not exclusively for the eye. The usual dimension as indicated for thermotherapy alone is of a diameter of maximum 4 mm. Diode system delivers infra-red rays either through the pupil or the sclera to destroy tumour tissue by applying focused heat to induce necrosis. Ideal temperature of thermotherapy ranges from 45–60 C . It is often used in conjunction with other treatment modalities such as chemotherapy [ 47 ]. Complications are seen in some cases which include but are not limited to atrophy of the iris, obstruction of the retinal vein and detachment of the retina. Attempts were made to avoid thermotherapy as a single modality in cases where seeding of the vitreous humour is observed. Lasting regression is seen in 86% of the subjects in selected cases [ 48 ].

Cryotherapy

Much like thermotherapy, cryotherapy is an adjuvant and used in conjunction with other treatments. A retinoblastoma tumour up to 3.5 mm in diameter and 2 mm in thickness could be treated with cryotherapy. This therapy is contraindicated in cases with vitreous seeding and any tumour that has dimensions larger than the norm. The modality involves the application of triple freeze thaw technique using liquid nitrogen [ 49 ].

External beam radiation (EBR)

External beam radiation is in the line of management of treatment for retinoblastoma after enucleation as an attempt to salvage the remaining eye. A high energy photon beam or electrons are delivered at an angle where the tumour has maximum exposure. Complications include cataracts, conjunctivitis, dry eyes and intractable glaucoma. Considering side effects such as new mutations, dry eyes, keratopathy, retinopathy and optic neuropathy, EBR therapy is better restricted to extra ocular tumour extension or if better alternatives are available, this could be completely avoided [ 50 ]. Tumours can sometimes arise secondarily due to radiation exposure, however, development of new modalities of beam radiation reduce such instances [ 51 ].

Tumour regression should be followed up closely and the appearance, size, location, and number of tumours documented during each examination have to be assessed. When a tumour regresses after treatment, it can either appear as a white coloured calcific mass or as translucent piece of flesh. In most of the cases, patients undergo examination under anaesthesia every 4 to 8 weeks until the age of 3, followed by less frequent examinations if the disease is found to be latent. Recurrence of the disease has been found to occur years after treatment and is very common these days. Patients with hereditary retinoblastoma also require long-term follow-up because such patients have an increased lifetime risk of developing secondary malignancies [ 52 ].

Retinoblastoma: the genetics behind the disease

Ascertaining the ‘two-hit’ hypothesis.

Retinoblastoma gene is best known as the tumour suppressor that inspired the ‘two-hit’ hypothesis. The idea that the loss of both the alleles of a tumour suppressor gene is a pre-requisite for tumour initiation occurred to Knudson in the 1970s. Fifteen years later in 1986, retinoblastoma gene (RB1) was localized and cloned for the first time, confirming Knudson’s prediction [ 7 ]. Located on chromosome 13q14, spanning over a length of 190kbp, RB1 is the most important carrier of mutations in the malignant tumour affecting the retina of mostly young children. Present in two distinct clinical forms, retinoblastoma is a genetic disease that is either inherited or occurs sporadically. In hereditary retinoblastoma, an inherited germline mutation in the patient is followed by an acquired mutation in the developing retinal cells, leading to the completion of the ‘two hits’. The sporadic version of the disease is followed by separate mutations on both the alleles in the retinoblastoma gene of the somatic cells [ 53 ]. It was observed that patients with hereditary form of the disease often have their both eyes affected by multiple tumours while in non-hereditary form, patients get affected unilaterally. The unilateral tumours are formed due to the double mutations occurring as a result of the somatic events in the retinal cells after fertilization. This becomes unifocal if only a single retinal cell is affected while, if the mutation occurs during the process of development and in turn multiple cells are affected, the retinoblastoma appears multifocal. But then, not all unilateral tumours are formed as a result of somatic events. Studies suggest that around 15% of the unilateral retinoblastomas are formed in patients with a hereditary mutation in one of the alleles and a constitutive one in the other [ 54 ]. In case of bilateral retinoblastoma, the RB1 gene, in most of the patients, acquires a de novo mutation during spermatogenesis, indicating that it is mostly the paternal chromosome that is vulnerable to mutations [ 55 ]. Furthermore, studies on both hereditary and sporadic retinoblastoma have suggested that the polymorphic markers flanking either sides of the RB1 gene often undergo loss of heterozygosity as a result of the second hit [ 56 ].

The broad spectrum of mutations with respect to retinoblastoma

More than 50% of the mutations found on RB1 have been detected only once, indicating the broad spectrum of RB1 mutations that spread across promoter, most exons, and splicing regions of introns [ 57 , 58 ]. Even though wide varieties of genetic variations like chromosomal rearrangements, large exonic deletions, hypermethylation of the gene promoter region, small length mutations, and single nucleotide substitutions occur in RB1, the majority of familial RBs are formed due to nonsense and frameshift mutations resulting in a loss of function. The premature halting of the translation leads to unstable mRNA mutants, further leading to no detection of functional retinoblastoma protein. Furthermore, comparative genome hybridisation and karyotypic analysis have depicted the loss as well as the gain of regions in the RB gene. Some cancers show a loss at 16q22 position, and others a gain of the region at 1q31, 6p22, 2p24-25, and 13q32-34. While 60% of retinoblastomas show a gain at 6p, a loss of 16q is found in children diagnosed at an older age. Studies on the gain or loss of regions have hastened the process of identifying various oncogenes and tumour suppressors involved in retinoblastoma initiation and progression [ 59 ].

The role of mosaicism is widely getting recognised in retinoblastoma as the genetic analysis of the disease is becoming more advanced [ 62 ]. Mosaicism is that genetic condition where the multicellular organism has more than one genetic line as a result of mutation. Mosaic retinoblastoma mostly occurs as a result of DNA damage during cell division. The adversity of the disease depends on the number of cells that are affected by the mosaicism. Usually the chance of the unilateral proband to have heritable retinoblastoma is precluded by testing for two mutant alleles in RB tumour DNA and then confirming the presence of these mutant alleles in their blood DNA. The absence of RB1 mutant allele in the blood of a parent with an affected child is where mosaicism acts as a causative reason. The chances of this becoming heritable are less as the mosaicism should occur in the embryonic stage [ 58 ].

Most often, the gene inactivation on RB1 is insufficient for the development of the disease. Studies over the past years show that additional genetic and stochastic events leading to the proliferation of retinal precursor cells are necessary to initiate tumorigenesis [ 60 ]. Though thousands of RB1 mutations have been documented, a small fraction of the unilateral retinoblastomas are found to have mutations that are yet to be identified in RB1 gene, indicating that there also exists an alternative mechanism for retinoblastoma genesis. Studies done in the early 2010s showed that these tumours formed in the retina, lacked RB1 mutations and instead showed amplification of MYCN gene. This is just considered to be an initiating event, and studies are still going on the development of MYCN amplified tumours [ 58 ]. Other genes that are inactivated are the leukemic oncogene DEK, Cadherin-11, and the transcriptional factor E2F3 [ 61 ]. With a two-fold increased expression, the kinesin gene KIF14 is overexpressed mainly in patients diagnosed at an older age. KIF14 and E2F3 activation is triggered due to the genomic instability caused by the RB1 mutation in many cases [ 62 ]. The senescence protein p16INK4A, involved in RB progression, is found to be absent in cells that escape from senescence. Similar research on the subsidiary mechanisms involved in the development of the disease through various gene expression studies has pointed out the necessity to decipher the complexity of the disease [ 63 ]. Hence there is an immense need to analyse various signalling pathways that are deregulated as a result of the disease, or vice versa.

Signalling pathways involved in Retinoblastoma

Initiation of any tumour requires a set of genetic aberrations that regulate their basic cellular functions. These genetic and epigenetic changes allow the cells to escape their homeostatic controls further allowing them to proliferate outside their normal niche. This is mainly due to the concomitant dysregulation of various signal transduction pathways like, Rb, p53, Wnt, Ras-ERK, etc. (Fig. 3 ) which may have an impact on the oncogenic properties of retinoblastoma through multiple mechanisms, including the acquisition of stem cell-like phenotype, EMT activation and metabolic rewiring [ 20 , 21 , 22 , 23 ].

Retinoblastoma cancer signalling. Major signalling pathways that undergo concomitant deregulation during retinoblastoma (Created using Biorender) The abbreviations ATM (Ataxia Telangiectasia Mutated), CHK1/2 (Checkpoint Kinase 1/2), HDAC(Histone Deacetylase), BRG (ATP-dependent chromatin remodeler SMARCA4), CDK2(Cyclin Dependent Kinase 2), MEK(Mitogen-activated protein kinase kinase), ERK (Extracellular signal-regulated kinase), ARF (Alternate open reading frame), MDM2 (Murine Double Minute 2), MDM4(Murine Double Minute 4), HDM2(Human Double Minute 2), AKT (Protein kinase B), mTOR(Mammalian Target of Rapamycin)

The transcription of 190kbp RB1 gene leads to the formation of a 110 kDa nuclear phosphoprotein renowned for its role in cell cycle regulation. It suppresses cell division by targeting the E2F family of transcription factors [ 64 ]. When hypo-phosphorylated, Rb binds to E2F and it prevents the transcription of genes necessary for G1 to S phase transition. When in need of cellular replication, the activated cyclin-cyclin dependent kinase (CDK) complex phosphorylates Rb and prevents its interaction with E2F. Mutations on the RB1 gene inhibit the Rb function, thus leading to the activation of E2F mediated transcription and hence, constant cell division leading to the retinoblastoma. Rb also binds to chromatin remodelling proteins like histone deacetylase (HDAC) and protein brahma homolog 1 (BRG) in its dephosphorylated form, causing alteration in chromatin structure and preventing access to transcription sites essential for cell cycle progression [ 64 ].

Studies have shown that inactivation of RB1 enables constitutive expression of E2F protein, causing a halt in the cell cycle control [ 65 ]. A recent study on murine models found that E2F independent CDK2 inhibition is a critical function required for p107 mediated tumour suppression. Inactivating this CDK2 inhibitor or deleting p27 expression was thus found to induce retinoblastoma. CDK2 being a protein known to cause tumour penetrance in all retinoblastoma models, removal of p107 in an Rb knockout model causing activation of CDK2 and post transcriptional induction of S-phase kinase-associated protein 2 (SKP2) further established the crosstalk among these proteins [ 66 ].

A number of studies linked dysregulation of Rb signaling pathway to the acquisition of multiple cellular status, as an undifferentiated “stem-like” phenotype, the activation of EMT program, or metabolic rewiring (Fig. 4 ). This highly dynamic phenotype might contribute to the oncogenic properties of retinoblastoma and lead to therapy resistance and inefficacy. For example, genetic, or functional inactivation of Rb family proteins in tissue stem/progenitor cells, impacts differentiation, sustains self-renewing capabilities thus promoting stem cells expansion and cancer initiation [ 67 ]. On the other hand, loss of Rb in differentiated post-mitotic cells has been observed leading to cell cycle re-entry and dedifferentiation, as well as to tumour initiation. In this regard, both mouse and human fibroblasts with inactivated Rb proteins acquire stem cells-like features, including the ability to form spheres and express inducible pluripotent genes [ 68 , 69 ]. Interestingly, the Rb-E2F1 complex has been reported to counteract the expression of SOX2 and other stem cell-related molecules through the binding of their promoters and regulatory sequences [ 70 ]. Overall, these studies suggested that Rb inactivation not only exclusively leads to tumour formation by cell cycle deregulation but also by favoring the acquisition of self-renewal and stemness properties.

Loss of Rb gene in retinoblastoma. Graphical abstract on how loss of Rb gene can deregulate metabolic pathways, cell cycle and epithelial to mesenchymal transition (EMT) leading to formation of cancer stem cell and in turn enabling the development of the tumor. (Created using Biorender)

Epithelial Mesenchymal transition (EMT) leads to the acquisition of mesenchymal phenotype from epithelial cells and may occur during embryonic development, tissue regeneration or in cancer progression. EMT endows cancer cells of invasive and metastatic potential through highly regulated molecular pathways in which microRNAs, epigenetic and posttranslational regulators participate [ 71 ]. The impact of Rb family proteins in EMT is controversial. For example, Rb depletion in breast cancer cells limit cell-cell adhesion and induces a mesenchymal-like phenotype. In contrast, ectopic expression of Rb resulted in increased E-cadherin, which is required in epithelial cell-cell adhesion [ 72 ]. On the other side, Egger et al. found that Rb dephosphorylation in 3D cultures of invasive fibrosarcoma cells counteracts EMT, suggesting that targeting Rb phosphorylation in mesenchymal cancer cells might attenuate the invasiveness of cancer cells [ 73 ]. Recently, lack of Rb proteins in retinoblastoma tumours and in oncogene-induced senescent cells has been linked to a reduction of glycolytic genes and metabolic rewiring towards glycolysis independent energy production and mitochondrial activity [ 23 ]. On the other hand, loss of Rb1 may also enhance glycolytic metabolism in Kras -driven lung tumours [ 74 ]. Although the role of Rb proteins in metabolism is controversial, their loss may contribute to different metabolic status to alternate fuels and energy production mechanisms.

p53 pathway

The p53 signalling pathway responds to various intrinsic and extrinsic stress signals by monitoring DNA replication, chromosome segregation and cell division [ 75 ]. Studies conducted over the years show that retinoblastoma caused due to RB1 mutations usually bypass the p53 pathway as they are already death resistant [ 63 ]. The activation of E2F in the absence of Rb leads to the overexpression of p14 ARF . The p14 ARF protein further leads to activation of MDM2, an inhibitor of p53. The proteosomal targeting of Rb being a common neoplastic strategy often put forward, the ability of MDM2 to mediate the interaction of the proteasome with Rb enables proteasome-dependent ubiquitin-independent degradation of Rb that is taken into advantage [ 19 ]. The knocking down of MDM2 results in hypo-phosphorylated Rb accumulation and thus DNA synthesis inhibition. A major inhibitor used to do the same is Nutlin-3. Similar to MDM2, MDMX is often found to be upregulated in retinoblastoma. The induction of MDMX in retinoblastoma cell lines like Y79, Weri1 and ML-1 showed increased expression of p53, phospho-p53 [ser-15], and various p53 targets like p21, and MDM2. Retinal cells lacking Rb and p107 also showed cell proliferation and survival when expressed with MDMX [ 19 ].

MDM4 is another protein which along with MDM2 maintains the stability of p53. Mutations and polymorphisms on MDM4 are studied vividly as this protein regulates Rb levels through MDM2 mediated ubiquitination [ 76 ]. Further small molecule inhibitors like CEP134 have shown that MDM4 expressing retinoblastoma cell lines depicted tumour regression by activation of p53 pathway [ 77 ]. Another molecule that acts as an inhibitor of p53 is HDM2. P53 protein auto-regulates itself through the transcription of these inhibitor proteins. Thus, loss of HDM2 leads to the subsequent accumulation of the p53 and thus the apoptosis of these tumour cells. Strategies that try to enhance the expression of HDM2 are thus often tried in retinoblastomas with wild type p53 [ 78 ]. The role of p53 in modulating cell plasticity is well-established. Several studies conferred to p53 a key role in the regulation of EMT mainly through modulating the complex miRNAs network [ 82 , 83 , 84 , 85 ]. On the other hand, p53 has been proposed to be a critical player in the regulation of stemness, differentiation, reprogramming of pluripotent stem cells, and inhibiting cancer stemness [ 79 ]. Interestingly, concomitant inactivating mutations in both p53 and Rb genes results in less differentiated tumours compared to a WT p53 background, suggesting the existence of a functional interrelation [ 80 , 81 ]. In this regard, MEFs lacking Rb function in a genetic context of p53 KO, showed increased sphere formation in 3-D culture, suggesting that double Rb/p53 inactivation fosters the acquisition of a stem-like phenotype [ 82 ]. These studies suggest that genetic interplay between Rb and p53 plays a key role in regulating the undifferentiated state in both normal and tumour cells.

Wnt signalling

The Wnt signaling is one of the major signaling pathways known to maintain the tissue morphogenesis during embryogenesis, stem-like properties, and DNA repair. In the CNS, Wnt signaling is required for cell fate specification, axon guidance, synapse development and the establishment of neuronal circuits [ 83 ]. A number of studies have shown that Wnt signaling pathway controls stem/progenitor cells. In this regard, Wnt3a can regulate the self-renewal of hematopoietic stem cells [ 84 ], the adult neurogenesis in the hippocampus [ 85 ], and the proliferation of retinal stem cells [ 86 ]. In another study it has been reported that canonical β-catenin/Wnt pathway improves retinal pigmented epithelium derivation from human embryonic stem cells [ 87 ]. Due to its ubiquitous presence in various cancers, manipulation of this pathway is often considered as an anti-neoplastic strategy in cancer treatment. During the growth of retinal cells, the Rb and Wnt pathway are supposed to act in opposite manner to control their proliferation and differentiation. Studies on developing chick retina found that inhibition of Wnt signaling caused blockage of premature neuronal differentiation and proliferation of progenitor cells. Overexpression of Wnt2b results in neuronal differentiation indicating that the mutations responsible for the deregulation of this pathway in RB1 knockout retinal progenitor cells could lead to tumorigenesis [ 88 ]. Studies on murine models showed that deletion of Rb homologs like p107 and p130 causes an increment in β-catenin expression, indicating the crosstalk between Rb and Wnt pathway. It has also been shown that cyclin D1, a downstream molecule of the Wnt signaling is a regulator of Rb pathway [ 89 ]. Wnt is negatively controlled by a tumor suppressor MEG3, making it a prognostic factor to detect retinoblastoma progression [ 90 ]. The silencing of PRC1 gene in HXO-RB44 and WERI-Rb-1 cell lines showed downregulation of Wnt signaling leading to a lower expression of PRC1, VEGF, Wnt1, β-catenin, cyclinD1, and GSK-3β phosphorylation, thus decreased proliferation and invasion abilities. This study showed the possibilities of suppressing the proliferation, and angiogenesis by downregulating the Wnt/β-catenin pathway in retinoblastoma cells [ 91 ]. Similar studies done using siRNAs to repress SOST expression indicated the upregulation of various genes like Wnt-1, β-catenin, c-Myc, cyclinD1, MMP-2 and MMP-9, further indicating the promotion of proliferation, invasion, migration, and inhibition of apoptosis in human retinoblastoma cells by the activation of the pathway [ 92 ]. The tumor suppressor role of Apc2 was also observed in retinoblastoma cell lines. Apc2 was found hypermethylated in 70% of tumor samples, and as a result, Wnt is activated in retinoblastoma [ 93 ]. A number of studies reported that Wnt signaling pathway confers plasticity to retinal pigment epithelium by controlling EMT and metabolic rewiring. In this regard, a study led by Tseng et al showed that Wnt induces EMT in ARPE-19 cells upon loss of contact inhibition [ 94 ]. In another study it has been observed that laser photocoagulation fosters Wnt/β-catenin signal transduction pathway, thus sustaining both retinal pigment epithelium (RPE) proliferation and EMT. Wnt/β-catenin signaling also induces the expression of transcription factors required for RPE biogenesis [ 95 ]. Wnt signaling is also linked to Warburg Effect and cancer metabolic rewiring [ 96 ]. In this regard, Wnt may foster the expression and the activity of glycolytic enzyme phosphofructokinase 1 platelet isoform (PFKP) in a β‑catenin‑independent manner. In a study by Vallée et al. conducted in exudative age-related macular degeneration, it has been reported that WNT/beta-catenin pathway stimulates PI3K/Akt and HIF-1α signaling which in turn leads to the activation of glycolytic enzymes [ 97 ].

Ras/MEK/ERK pathway

Considered to be the best characterised signalling pathway in cell biology, Ras/Raf pathway transduces signals from the extracellular area to the nucleus and enables activation of cell growth, differentiation, and migration. Studies have shown that Rb protein is a nuclear target of this signalling. The levels of Rb in turn are known to regulate the Ras expression. Rb deficient cell lines expressed elevated levels of Ras during its G1 phase, but this was found to be reversed in the presence of a defective E2F expression [ 98 ]. Cyclin dependent kinase regulatory subunit 1B (CKS1B) is a protein whose downregulation efficaciously inhibits the proliferation, invasion and angiogenesis of retinoblastoma cell lines through MEK/ERK signalling pathway. Activation of the MEK/ERK signalling enhances the expression of MEK, ERK, BCl2, PCNA, cyclinD1, VEGF and b-FGF, leading to increment in cell proliferation, migration, invasion and apoptotic inhibition [ 99 ]. Inhibition of various kinases in Y79 cell lines like CDK2/6, and cyclinD1 by increasing the expression of their inhibitors p21 and p27 have depicted an enhancement in the phosphorylation of JNK and p38-MAPK, NF-κB leading to activation of both pathways [ 100 ]. Similar results were observed when using curcumin as an anti-cancer therapeutic molecule [ 101 ]. Studies determining the role of BRAF mutations in human retinoblastoma cell found that, the lack of their presence was in accordance with the hypermethylation status of RASSF1 and the presence of CpG island methylator phenotype (CIMP) [ 102 ]. Astrocyte Elevated Gene 1 (AEG1) is another protein which when downregulated using RNA interference showed regression of tumor by inhibiting ERK [ 102 ]. Other than these, various miRNAs have also been observed that can regulate RB cell growth and metastasis by suppressing the insulin like growth factor-1 receptor IGF1R/k-Ras/Raf/MEK/ERK signalling pathway.

Although direct evidence does not exist in retinoblastoma disease, it is widely described that MAPK pathway might participate in the regulation of cancer cell plasticity and EMT in other tumors. For example, p38-MAPK family has been reported to foster EMT and increase CSCs population in glioma and breast cancer [ 103 , 104 ]. Pharmacological inhibition of ERK enhances stemness of NSCLC cells via promoting Slug-mediated EMT [ 105 ]. In breast cancer models ERK2 can sustain EMT plasticity through DOCK10-dependent Rac1/FoxO1 activation [ 106 ] and TNF-α activates EMT program in oral squamous carcinoma by up-regulating P38 and ERK proteins thus enhancing tumor invasion and migratory capabilities [ 104 ].

Notch pathway

Notch is an evolutionarily conserved signalling pathway that promotes proliferative signalling during neurogenesis. In the developing brain, Notch signalling plays a critical role in preserving neural progenitors in an undifferentiated state, by limiting neurogenesis. Notch signalling also controls synaptic plasticity, learning and memory in the adult brain [ 107 ]. In addition, a study by Hitoshi et al. suggested that Notch pathway molecules are essential for the maintenance of neural stem cells [ 108 ]. Usually notch receptors inhibit photoreceptor differentiation during retinal development and help in maintaining its progenitor state. Thus, during retinal development Notch1 and Notch3 are expressed in the central portion, while Notch2 is mostly present in the periphery. Deregulation of their expression is often observed in retinoblastoma cells in both humans and murine, making this pathway a favourite therapeutic target. Jagged1 is a protein that gets expressed distinctly at distinct time intervals during retinal cell development. Studies have shown that Notch1 and Jag2 are highly expressed in the SO-Rb50 cell line [ 109 ]. The overexpression of Jag2 causes an increase in the expression of Hes1, a downstream molecule of the Notch signalling. The suppression of Jag2 expression was also observed to decrease the PI3KC2β mRNA levels, which further promoted AKT expression [ 110 ]. MCL1, another anti-apoptotic molecule is found to be degraded in the presence of small molecule inhibitors that decrease the expression of Spleen Tyrosine Kinase (SYK). The inhibition of Notch pathways in WERI Rb1 and Y79 cell lines detected reduction in the cell viability. The combination of these along with exposure to hypoxia is found to be very effective as a treatment strategy against retinoblastoma [ 111 ].

Studies on various non-coding RNAs have also deciphered their role in proliferation, stemness, migration and invasion of retinoblastoma cells via the regulation of Notch signalling [ 112 ]. Interestingly, Notch signaling pathway has been found to be a critical player of cellular plasticity through the induction of EMT. Niessen et al., showed that Notch-induced expression of Slug plays an important role in the initiation of EMT [ 113 ]. In another study, it has been reported that a complex integration of the hypoxia and Notch signaling pathways are necessary for EMT control [ 114 ]. Indeed, Notch drives hypoxia-inducible factor 1α (HIF-1 α) recruitment to the lysyl oxidase (LOX) regulatory sequences, thus fostering the hypoxia-induced up-regulation of LOX and the stabilization of Snail-1 protein. Moreover, it has been described that Notch signaling pathway plays a key role in proliferative vitreoretinopathy (VR) formation by fostering EMT program of RPE cells [ 115 ]. It has been reported that Notch signaling is an essential player involved in metabolic flexibility and may lead to glycolytic switch through multiple mechanisms. Indeed, hyperactivated Notch signaling induces glycolysis through the activation of AKT whereas hypo-activated Notch limits mitochondrial function and promotes glycolytic metabolism in a p53-dependent way. Intriguingly, it has been observed that only tumours with hyperactivated Notch signaling display an aggressive phenotype since they maintain the ability to revert to mitochondria metabolism [ 116 ].

Conclusion and future perspective

Retinoblastoma is a rare cancer that attracts physicians and scientists because of the potential for its cure and novelty in its treatment modalities. The care for retinoblastoma has been revolutionised by tumour imaging. The similarities observed between the intraocular microenvironment and brain, makes it a possibility to use the paratopic xenograft, since it is a better option when compared to the existing subcutaneous xenografting technique. This can be made possible by the powerful combination of fundus imaging and optical coherence tomography (OCT), and the other uses and advantages of the same need to be further explored. The use of radio-labelled amino acid tracers for molecular imaging using positron emission tomography (PET) and single photon emission computed tomography (SPECT) have shown good results in brain tumour, indicating the possibilities of this being a probable imaging option for retinoblastoma [ 117 ]. Furthermore, imaging studies done on high resolution scale might also reveal other imaging biomarkers leading to proper stratification of retinoblastomas for developing improved prognostication and treatment decisions. This could also be used to analyse and impact identification of MYCN retinoblastoma [ 32 ].

The level of knowledge we have of the clinical behaviour of intracranial tumours in retinoblastoma is inordinate when compared to our understanding of their molecular features. The fact that even after being one of the oldest cancers to be identified, there is no proper molecular targeted therapy for the disease points to all the unknown secondary mutations that are part of retinoblastoma which are still to be deciphered. Yet, significant progress has been made in the knowledge of the retinoblastoma biology, leading to the discovery and development of small molecules for the treatment of the same, like inhibitors of the MDMX–p53 response (nutlin-3a), histone deacetylase (HDAC) inhibitors, spleen tyrosine kinase (SYK) inhibitors etc. Thus, therapeutic strategies against retinoblastoma have rapidly evolved in the recent years, with a paradigm shift in standard treatment protocols toward the targeted delivery of chemotherapeutic agents. The use of nanotechnology as a prominent delivery system to transport these molecules to the tumour sites has shown the potential to reduce the problems faced by these standard techniques [ 118 , 119 , 120 , 121 ]. Yet our understanding on various matters regarding the tumour biology and effective therapies need to progress in order to make sure that retinoblastoma is a curable childhood cancer.

Availability of data and materials

Not applicable.

Snell RS, Lemp MA. Clinical anatomy of the eye. 2nd ed. Malden: Blackwell Science; 1998. p. 423.

Google Scholar

Munier FL, Balmer A, van Melle G, Gailloud C. Radial asymmetry in the topography of retinoblastoma. Clues to the cell of origin. Ophthalmic Genet. 1994;15(3–4):101–6.

Article PubMed CAS Google Scholar

Aerts I, Lumbroso-Le Rouic L, Gauthier-Villars M, Brisse H, Doz F, Desjardins L. Retinoblastoma. Orphanet J Rare Dis. 2006;1:31.

Article PubMed PubMed Central Google Scholar

Fabian ID, Sagoo MS. Understanding retinoblastoma: epidemiology and genetics. Community Eye Health. 2018;31(101):7.

PubMed PubMed Central Google Scholar

Fernandes AG, Pollock BD, Rabito FA. Retinoblastoma in the United States: a 40-year incidence and survival analysis. J Pediatr Ophthalmol Strabismus. 2018;55(3):182–8.

Article PubMed Google Scholar

Wong JR, Tucker MA, Kleinerman RA, Devesa SS. Retinoblastoma incidence patterns in the US Surveillance, Epidemiology, and End Results program. JAMA Ophthalmol. 2014;132(4):478–83.

Friend SH, Bernards R, Rogelj S, Weinberg RA, Rapaport JM, Albert DM, et al. A human DNA segment with properties of the gene that predisposes to retinoblastoma and osteosarcoma. Nature. 1986;323(6089):643–6.

Dommering CJ, Marees T, van der Hout AH, Imhof SM, Meijers-Heijboer H, Ringens PJ, et al. RB1 mutations and second primary malignancies after hereditary retinoblastoma. Fam Cancer. 2012;11(2):225–33.

Moll AC, Imhof SM, Bouter LM, Tan KE. Second primary tumors in patients with retinoblastoma. A review of the literature. Ophthalmic Genet. 1997;18(1):27–34.

Dunham A, Matthews LH, Burton J, Ashurst JL, Howe KL, Ashcroft KJ, et al. The DNA sequence and analysis of human chromosome 13. Nature. 2004;428(6982):522–8.

Article PubMed PubMed Central CAS Google Scholar

Dyson NJ. RB1: a prototype tumor suppressor and an enigma. Genes Dev. 2016;30(13):1492–502.

Johnson DG, Schwarz JK, Cress WD, Nevins JR. Expression of transcription factor E2F1 induces quiescent cells to enter S phase. Nature. 1993;365(6444):349–52.

Balmer A, Zografos L, Munier F. Diagnosis and current management of retinoblastoma. Oncogene. 2006;25(38):5341–9.

da Silva-Diz V, Lorenzo-Sanz L, Bernat-Peguera A, Lopez-Cerda M, Munoz P. Cancer cell plasticity: impact on tumor progression and therapy response. Semin Cancer Biol. 2018;53:48–58.

Fanelli GN, Naccarato AG, Scatena C. Recent advances in cancer plasticity: cellular mechanisms, surveillance strategies, and therapeutic optimization. Front Oncol. 2020;10:569.

Chaffer CL, San Juan BP, Lim E, Weinberg RA. EMT, cell plasticity and metastasis. Cancer Metastasis Rev. 2016;35(4):645–54.

Lehuede C, Dupuy F, Rabinovitch R, Jones RG, Siegel PM. Metabolic plasticity as a determinant of tumor growth and metastasis. Cancer Res. 2016;76(18):5201–8.

Classon M, Harlow E. The retinoblastoma tumour suppressor in development and cancer. Nat Rev Cancer. 2002;2(12):910–7.

Laurie NA, Donovan SL, Shih CS, Zhang J, Mills N, Fuller C, et al. Inactivation of the p53 pathway in retinoblastoma. Nature. 2006;444(7115):61–6.

Suresh Babu V, Bisht A, Mallipatna A, Sa D, Dudeja G, Kannan R, et al. Enhanced epithelial-to-mesenchymal transition and chemoresistance in advanced retinoblastoma tumors is driven by miR-181a. Cancers (Basel). 2022;14(20):5124.

Seigel GM, Campbell LM, Narayan M, Gonzalez-Fernandez F. Cancer stem cell characteristics in retinoblastoma. Mol Vis. 2005;11:729–37.

PubMed CAS Google Scholar

Ciavarra G, Zacksenhaus E. Rescue of myogenic defects in Rb-deficient cells by inhibition of autophagy or by hypoxia-induced glycolytic shift. J Cell Biol. 2010;191(2):291–301.

Takebayashi S, Tanaka H, Hino S, Nakatsu Y, Igata T, Sakamoto A, et al. Retinoblastoma protein promotes oxidative phosphorylation through upregulation of glycolytic genes in oncogene-induced senescent cells. Aging Cell. 2015;14(4):689–97.

Navo E, Teplisky D, Albero R, Fandino AC, Demirdjian G, Chantada GL. Clinical presentation of retinoblastoma in a middle-income country. J Pediatr Hematol Oncol. 2012;34(3):e97-101.

Chantada GL, Qaddoumi I, Canturk S, Khetan V, Ma Z, Kimani K, et al. Strategies to manage retinoblastoma in developing countries. Pediatr Blood Cancer. 2011;56(3):341–8.

Naseripour M. “Retinoblastoma survival disparity”: the expanding horizon in developing countries. Saudi J Ophthalmol. 2012;26(2):157–61.

Linn Murphree A. Intraocular retinoblastoma: the case for a new group classification. Ophthalmol Clin North Am. 2005;18(1):41–53 ( viii ).

Novetsky DE, Abramson DH, Kim JW, Dunkel IJ. Published international classification of retinoblastoma (ICRB) definitions contain inconsistencies–an analysis of impact. Ophthalmic Genet. 2009;30(1):40–4.

Brown BJ, Adeleye AO, Ibeh JN. A prospective study on the causes of delayed diagnosis of childhood cancer in Ibadan, Nigeria. Pediatr Hematol Oncol. 2015;32(6):365–73.

Mallipatna A, Marino M, Singh AD. Genetics of retinoblastoma. Asia Pac J Ophthalmol (Phila). 2016;5(4):260–4.

Snell RS, Lemp MA. Clinical anatomy of the eye. Blackwell Publishing; 2013.

Dimaras H, Kimani K, Dimba EA, Gronsdahl P, White A, Chan HS, et al. Retinoblastoma. Lancet. 2012;379(9824):1436–46.

Stiller CA, Parkin DM. Geographic and ethnic variations in the incidence of childhood cancer. Br Med Bull. 1996;52(4):682–703.

Vempuluru VS, Kaliki S. Screening for retinoblastoma: a systematic review of current strategies. Asia Pac J Ophthalmol (Phila). 2021;10(2):192–9.

Mastrangelo D, Squitieri N, Bruni S, Hadjistilianou T, Frezzotti R. The polymerase chain reaction (PCR) in the routine genetic characterization of retinoblastoma: a tool for the clinical laboratory. Surv Ophthalmol. 1997;41(4):331–40.

Paquette LB, Miller D, Jackson HA, Lee T, Randolph L, Murphree AL, et al. In utero detection of retinoblastoma with fetal magnetic resonance and ultrasound: initial experience. AJP Rep. 2012;2(1):55–62.

de Graaf P, Goricke S, Rodjan F, Galluzzi P, Maeder P, Castelijns JA, et al. Guidelines for imaging retinoblastoma: imaging principles and MRI standardization. Pediatr Radiol. 2012;42(1):2–14.

Hayreh SS. Recent advances in fluorescein fundus angiography. Br J Ophthalmol. 1974;58(4):391–412.

Shields JA, Sanborn GE, Augsburger JJ, Orlock D, Donoso LA. Fluorescein angiography of retinoblastoma. Retina. 1982;2(4):206–14.

Moothedath AW, Chopra KK, Seth R, Meena JP, Gupta AK, Kumar R, et al. Role of 18-fluorodeoxyglucose positron emission tomography-computed tomography in predicting residual disease posttreatment completion in retinoblastoma patients. Indian J Nucl Med. 2022;37(2):142–6.

Manjandavida FP, Xia J, Zhang J, Tang XY, Yi HR. In-utero ultrasonography detection of fetal retinoblastoma and neonatal selective ophthalmic artery chemotherapy. Indian J Ophthalmol. 2019;67(6):958–60.

Shields CL, Manjandavida FP, Arepalli S, Kaliki S, Lally SE, Shields JA. Intravitreal melphalan for persistent or recurrent retinoblastoma vitreous seeds: preliminary results. JAMA Ophthalmol. 2014;132(3):319–25.

Shields CL, Shields JA. Retinoblastoma management: advances in enucleation, intravenous chemoreduction, and intra-arterial chemotherapy. Curr Opin Ophthalmol. 2010;21(3):203–12.

Shields JA, Shields CL, De Potter P. Enucleation technique for children with retinoblastoma. J Pediatr Ophthalmol Strabismus. 1992;29(4):213–5.

Gobin YP, Dunkel IJ, Marr BP, Brodie SE, Abramson DH. Intra-arterial chemotherapy for the management of retinoblastoma: four-year experience. Arch Ophthalmol. 2011;129(6):732–7.

Cooper GM. The cell, a molecular approach. 2nd ed. Sunderland: Sinauer Associates; 2000.

Pandey AN. Retinoblastoma: an overview. Saudi J Ophthalmol. 2014;28(4):310–5.

Shields CL, Santos MC, Diniz W, Gunduz K, Mercado G, Cater JR, et al. Thermotherapy for retinoblastoma. Arch Ophthalmol. 1999;117(7):885–93.

Shields JA, Parsons H, Shields CL, Giblin ME. The role of cryotherapy in the management of retinoblastoma. Am J Ophthalmol. 1989;108(3):260–4.

Ancona-Lezama D, Dalvin LA, Shields CL. Modern treatment of retinoblastoma: a 2020 review. Indian J Ophthalmol. 2020;68(11):2356–65.

Abramson DH, Jereb B, Ellsworth RM. External beam radiation for retinoblastoma. Bull N Y Acad Med. 1981;57(9):787–803.

PubMed PubMed Central CAS Google Scholar

Jonathan W. Kim ALMADS. Retinoblastoma: treatment options. 3rd edn. 2019. p. 119–39.

Griffith AD, Sorsby A. The genetics of retinoblastoma. Br J Ophthalmol. 1944;28(6):279–93.

Harbour JW. Eye cancer: unique insights into oncogenesis: the Cogan Lecture. Invest Ophthalmol Vis Sci. 2006;47(5):1736–45.

Chintagumpala M, Chevez-Barrios P, Paysse EA, Plon SE, Hurwitz R. Retinoblastoma: review of current management. Oncologist. 2007;12(10):1237–46.

Choy KW, Pang CP, Yu CB, Wong HL, Ng JS, Fan DS, et al. Loss of heterozygosity and mutations are the major mechanisms of RB1 gene inactivation in Chinese with sporadic retinoblastoma. Hum Mutat. 2002;20(5):408.

Richter S, Vandezande K, Chen N, Zhang K, Sutherland J, Anderson J, et al. Sensitive and efficient detection of RB1 gene mutations enhances care for families with retinoblastoma. Am J Hum Genet. 2003;72(2):253–69.

Lohmann DR. RB1 gene mutations in retinoblastoma. Hum Mutat. 1999;14(4):283–8.

Squire J, Phillips RA, Boyce S, Godbout R, Rogers B, Gallie BL. Isochromosome 6p, a unique chromosomal abnormality in retinoblastoma: verification by standard staining techniques, new densitometric methods, and somatic cell hybridization. Hum Genet. 1984;66(1):46–53.

Rushlow DE, Mol BM, Kennett JY, Yee S, Pajovic S, Theriault BL, et al. Characterisation of retinoblastomas without RB1 mutations: genomic, gene expression, and clinical studies. Lancet Oncol. 2013;14(4):327–34.

Bowles E, Corson TW, Bayani J, Squire JA, Wong N, Lai PB, et al. Profiling genomic copy number changes in retinoblastoma beyond loss of RB1. Genes Chromosomes Cancer. 2007;46(2):118–29.

Madhavan J, Coral K, Mallikarjuna K, Corson TW, Amit N, Khetan V, et al. High expression of KIF14 in retinoblastoma: association with older age at diagnosis. Invest Ophthalmol Vis Sci. 2007;48(11):4901–6.

DiCiommo D, Gallie BL, Bremner R. Retinoblastoma: the disease, gene and protein provide critical leads to understand cancer. Semin Cancer Biol. 2000;10(4):255–69.

Lee C, Chang JH, Lee HS, Cho Y. Structural basis for the recognition of the E2F transactivation domain by the retinoblastoma tumor suppressor. Genes Dev. 2002;16(24):3199–212.

Sachdeva UM, O’Brien JM. Understanding pRb: toward the necessary development of targeted treatments for retinoblastoma. J Clin Invest. 2012;122(2):425–34.

Sangwan M, McCurdy SR, Livne-Bar I, Ahmad M, Wrana JL, Chen D, Bremner R. Established and new mouse models reveal E2f1 and Cdk2 dependency of retinoblastoma, and expose effective strategies to block tumor initiation. Oncogene. 2012;31(48):5019–28.

Sage J. The retinoblastoma tumor suppressor and stem cell biology. Genes Dev. 2012;26(13):1409–20.

Liu Y, Clem B, Zuba-Surma EK, El-Naggar S, Telang S, Jenson AB, et al. Mouse fibroblasts lacking RB1 function form spheres and undergo reprogramming to a cancer stem cell phenotype. Cell Stem Cell. 2009;4(4):336–47.

Li F, He Z, Shen J, Huang Q, Li W, Liu X, et al. Apoptotic caspases regulate induction of iPSCs from human fibroblasts. Cell Stem Cell. 2010;7(4):508–20.

Kareta MS, Gorges LL, Hafeez S, Benayoun BA, Marro S, Zmoos AF, et al. Inhibition of pluripotency networks by the Rb tumor suppressor restricts reprogramming and tumorigenesis. Cell Stem Cell. 2015;16(1):39–50.

Ribatti D, Tamma R, Annese T. Epithelial-mesenchymal transition in cancer: a historical overview. Transl Oncol. 2020;13(6):100773.

Arima Y, Inoue Y, Shibata T, Hayashi H, Nagano O, Saya H, et al. Rb depletion results in deregulation of E-cadherin and induction of cellular phenotypic changes that are characteristic of the epithelial-to-mesenchymal transition. Cancer Res. 2008;68(13):5104–12.

Egger JV, Lane MV, Antonucci LA, Dedi B, Krucher NA. Dephosphorylation of the Retinoblastoma protein (Rb) inhibits cancer cell EMT via Zeb. Cancer Biol Ther. 2016;17(11):1197–205.

Conroy LR, Dougherty S, Kruer T, Metcalf S, Lorkiewicz P, He L, et al. Loss of Rb1 enhances glycolytic metabolism in Kras-driven lung tumors in vivo. Cancers (Basel). 2020;12(1):237.

Vogelstein B, Lane D, Levine AJ. Surfing the p53 network. Nature. 2000;408(6810):307–10.

Pant V, Xiong S, Iwakuma T, Quintas-Cardama A, Lozano G. Heterodimerization of Mdm2 and Mdm4 is critical for regulating p53 activity during embryogenesis but dispensable for p53 and Mdm2 stability. Proc Natl Acad Sci U S A. 2011;108(29):11995–2000.

Togashi K, Okada M, Suzuki S, Sanomachi T, Seino S, Yamamoto M, et al. Inhibition of retinoblastoma cell growth by CEP1347 through activation of the P53 pathway. Anticancer Res. 2020;40(9):4961–8.

Elison JR, Cobrinik D, Claros N, Abramson DH, Lee TC. Small molecule inhibition of HDM2 leads to p53-mediated cell death in retinoblastoma cells. Arch Ophthalmol. 2006;124(9):1269–75.

Curylova L, Ramos H, Saraiva L, Skoda J. Noncanonical roles of p53 in cancer stemness and their implications in sarcomas. Cancer Lett. 2022;525:131–45.

Choi J, Curtis SJ, Roy DM, Flesken-Nikitin A, Nikitin AY. Local mesenchymal stem/progenitor cells are a preferential target for initiation of adult soft tissue sarcomas associated with p53 and Rb deficiency. Am J Pathol. 2010;177(5):2645–58.

Jiang Z, Deng T, Jones R, Li H, Herschkowitz JI, Liu JC, et al. Rb deletion in mouse mammary progenitors induces luminal-B or basal-like/EMT tumor subtypes depending on p53 status. J Clin Invest. 2010;120(9):3296–309.

Kitajima S, Kohno S, Kondoh A, Sasaki N, Nishimoto Y, Li F, et al. Undifferentiated state induced by Rb-p53 double inactivation in mouse thyroid neuroendocrine cells and embryonic fibroblasts. Stem Cells. 2015;33(5):1657–69.

Salinas PC. Wnt signaling in the vertebrate central nervous system: from axon guidance to synaptic function. Cold Spring Harb Perspect Biol. 2012;4(2):a008003.

Reya T, Duncan AW, Ailles L, Domen J, Scherer DC, Willert K, et al. A role for Wnt signalling in self-renewal of haematopoietic stem cells. Nature. 2003;423(6938):409–14.

Lie DC, Colamarino SA, Song HJ, Desire L, Mira H, Consiglio A, et al. Wnt signalling regulates adult hippocampal neurogenesis. Nature. 2005;437(7063):1370–5.

Inoue T, Kagawa T, Fukushima M, Shimizu T, Yoshinaga Y, Takada S, et al. Activation of canonical Wnt pathway promotes proliferation of retinal stem cells derived from adult mouse ciliary margin. Stem Cells. 2006;24(1):95–104.

Leach LL, Buchholz DE, Nadar VP, Lowenstein SE, Clegg DO. Canonical/beta-catenin Wnt pathway activation improves retinal pigmented epithelium derivation from human embryonic stem cells. Invest Ophthalmol Vis Sci. 2015;56(2):1002–13.

Tell S, Yi H, Jockovich ME, Murray TG, Hackam AS. The Wnt signaling pathway has tumor suppressor properties in retinoblastoma. Biochem Biophys Res Commun. 2006;349(1):261–9.

Tetsu O, McCormick F. Beta-catenin regulates expression of cyclin D1 in colon carcinoma cells. Nature. 1999;398(6726):422–6.

Gao Y, Lu X. Decreased expression of MEG3 contributes to retinoblastoma progression and affects retinoblastoma cell growth by regulating the activity of Wnt/β-catenin pathway. Tumour Biol. 2016;37(2):1461–9.

Liao YJ, Yin XL, Deng Y, Peng XW. PRC1 gene silencing inhibits proliferation, invasion, and angiogenesis of retinoblastoma cells through the inhibition of the Wnt/beta-catenin signaling pathway. J Cell Biochem. 2019;120(10):16840–52.

Wu T, Wang LN, Tang DR, Sun FY. SOST silencing promotes proliferation and invasion and reduces apoptosis of retinoblastoma cells by activating Wnt/beta-catenin signaling pathway. Gene Ther. 2017;24(7):399–407.

Beta M, Chitipothu S, Khetan V, Biswas J, Krishnakumar S. Hypermethylation of adenomatosis polyposis coli-2 and its tumor suppressor role in retinoblastoma. Curr Eye Res. 2015;40(7):719–28.

Chen HC, Zhu YT, Chen SY, Tseng SC. Wnt signaling induces epithelial-mesenchymal transition with proliferation in ARPE-19 cells upon loss of contact inhibition. Lab Invest. 2012;92(5):676–87.

Han JW, Lyu J, Park YJ, Jang SY, Park TK. Wnt/beta-catenin signaling mediates regeneration of retinal pigment epithelium after laser photocoagulation in mouse eye. Invest Ophthalmol Vis Sci. 2015;56(13):8314–24.

El-Sahli S, Xie Y, Wang L, Liu S. Wnt signaling in cancer metabolism and immunity. Cancers (Basel). 2019;11(7):904.

Vallee A, Lecarpentier Y, Guillevin R, Vallee JN. Aerobic glycolysis hypothesis through WNT/beta-catenin pathway in exudative age-related macular degeneration. J Mol Neurosci. 2017;62(3–4):368–79.

Lee KY, Ladha MH, McMahon C, Ewen ME. The retinoblastoma protein is linked to the activation of Ras. Mol Cell Biol. 1999;19(11):7724–32.

Zeng Z, Gao ZL, Zhang ZP, Jiang HB, Yang CQ, Yang J, et al. Downregulation of CKS1B restrains the proliferation, migration, invasion and angiogenesis of retinoblastoma cells through the MEK/ERK signaling pathway. Int J Mol Med. 2019;44(1):103–14.

Liu H, Zhou M. Antitumor effect of Quercetin on Y79 retinoblastoma cells via activation of JNK and p38 MAPK pathways. BMC Complement Altern Med. 2017;17(1):1–8.

Article Google Scholar

Kumar A, Singam A, Swaminathan G, Killi N, Tangudu NK, Jose J, et al. Combinatorial therapy using RNAi and curcumin nano-architectures regresses tumors in breast and colon cancer models. Nanoscale. 2022;14(2):492–505.

Chang Y, Li B, Xu X, Shen L, Bai H, Gao F, et al. Lentivirus-mediated knockdown of astrocyte elevated gene-1 inhibits growth and induces apoptosis through MAPK pathways in human retinoblastoma cells. PLoS One. 2016;11(2):e0148763.

Ling G, Ji Q, Ye W, Ma D, Wang Y. Epithelial-mesenchymal transition regulated by p38/MAPK signaling pathways participates in vasculogenic mimicry formation in SHG44 cells transfected with TGF-beta cDNA loaded lentivirus in vitro and in vivo. Int J Oncol. 2016;49(6):2387–98.

Xu M, Wang S, Wang Y, Wu H, Frank JA, Zhang Z, et al. Role of p38gamma MAPK in regulation of EMT and cancer stem cells. Biochim Biophys Acta Mol Basis Dis. 2018;1864(11):3605–17.

Cai S, Li N, Bai X, Liu L, Banerjee A, Lavudi K, et al. ERK inactivation enhances stemness of NSCLC cells via promoting Slug-mediated epithelial-to-mesenchymal transition. Theranostics. 2022;12(16):7051–66.

Shin S, Buel GR, Nagiec MJ, Han MJ, Roux PP, Blenis J, et al. ERK2 regulates epithelial-to-mesenchymal plasticity through DOCK10-dependent Rac1/FoxO1 activation. Proc Natl Acad Sci U S A. 2019;116(8):2967–76.

Lathia JD, Mattson MP, Cheng A. Notch: from neural development to neurological disorders. J Neurochem. 2008;107(6):1471–81.

Hitoshi S, Alexson T, Tropepe V, Donoviel D, Elia AJ, Nye JS, et al. Notch pathway molecules are essential for the maintenance, but not the generation, of mammalian neural stem cells. Genes Dev. 2002;16(7):846–58.

Xiao W, Chen X, He M. Inhibition of the Jagged/Notch pathway inhibits retinoblastoma cell proliferation via suppressing the PI3K/Akt, Src, p38MAPK and Wnt/betacatenin signaling pathways. Mol Med Rep. 2014;10(1):453–8.

Asnaghi L, Tripathy A, Yang Q, Kaur H, Hanaford A, Yu W, et al. Targeting Notch signaling as a novel therapy for retinoblastoma. Oncotarget. 2016;7(43):70028–44.

Zhang J, Benavente CA, McEvoy J, Flores-Otero J, Ding L, Chen X, et al. A novel retinoblastoma therapy from genomic and epigenetic analyses. Nature. 2012;481(7381):329–34.

Gao Y, Luo X, Zhang J. LincRNA-ROR is activated by H3K27 acetylation and induces EMT in retinoblastoma by acting as a sponge of miR-32 to activate the Notch signaling pathway. Cancer Gene Ther. 2021;28(1–2):42–54.

Niessen K, Fu Y, Chang L, Hoodless PA, McFadden D, Karsan A. Slug is a direct Notch target required for initiation of cardiac cushion cellularization. J Cell Biol. 2008;182(2):315–25.

Sahlgren C, Gustafsson MV, Jin S, Poellinger L, Lendahl U. Notch signaling mediates hypoxia-induced tumor cell migration and invasion. Proc Natl Acad Sci U S A. 2008;105(17):6392–7.

Zhang J, Yuan G, Dong M, Zhang T, Hua G, Zhou Q, et al. Notch signaling modulates proliferative vitreoretinopathy via regulating retinal pigment epithelial-to-mesenchymal transition. Histochem Cell Biol. 2017;147(3):367–75.

Landor SK, Mutvei AP, Mamaeva V, Jin S, Busk M, Borra R, et al. Hypo- and hyperactivated Notch signaling induce a glycolytic switch through distinct mechanisms. Proc Natl Acad Sci U S A. 2011;108(46):18814–9.

Brindle KM, Izquierdo-García JL, Lewis DY, Mair RJ, Wright AJ. Brain tumor imaging. J Clin Oncol. 2017;35(21):2432–8.

Swaminathan G, Shigna A, Kumar A, Byroju VV, Durgempudi VR, Dinesh Kumar L. RNA interference and nanotechnology: a promising alliance for next generation cancer therapeutics. Front Nanotechnol. 2021;3:694838.

Nadukkandy AS, Ganjoo E, Singh A, Dinesh Kumar L. Tracing new landscapes in the arena of nanoparticle-based cancer immunotherapy. Front Nanotechnol. 2022;4:911063.

Garcia-Garrido E, Cordani M, Somoza A. Modified gold nanoparticles to overcome the chemoresistance to gemcitabine in mutant p53 cancer cells. Pharmaceutics. 2021;13(12):2067.

Latorre A, Latorre A, Castellanos M, Lafuente-Gomez N, Diaz CR, Crespo-Barreda A, et al. Albumin-based nanostructures for uveal melanoma treatment. Nanomedicine. 2021;35:102391.

Download references

Acknowledgements

The authors are extremely grateful to V. Dinesh Kumar for his critical evaluation, suggestions, and help in editing the manuscript. Authors thank Aviral Kumar for his valuable help with Biorender. Authors are also extremely grateful to Dr. Vinay K Nancoori, Director of CSIR-Centre for Cellular and Molecular Biology (CCMB), Hyderabad, India for his support. ASN was supported by INSPIRE scholarship for higher education from the Department of Science and Technology (DST), Government of India. MC is supported with a Ramon y Cajal grant (RYC2021-031003-I) from the Spanish Ministry of Science and Innovation, Agencia Estatal de Investigación (MCIN/AEI/10.13039/501100011033), and European UnionNextGeneration (EU/PRTR). MC also acknowledges funding from Spanish Ministry of Universities and Complutense University of Madrid (Maria Zambrano grants for the requalification of the Spanish University System 2021-2023).

Author information

Authors and affiliations.

Department of Biochemistry, American International Medical University, Gros Islet, St. Lucia, USA

Vishnu Vardhan Byroju

CSIR-Centre for Cellular and Molecular Biology, Habsiguda, Uppal Road, Hyderabad, India

Aisha Shigna Nadukkandy & Lekha Dinesh Kumar

Department of Biochemistry and Molecular Biology, Complutense University of Madrid, and Instituto de Investigaciones Sanitarias San Carlos (IdISSC), Madrid, Spain

Marco Cordani

You can also search for this author in PubMed Google Scholar

Contributions

All the authors contributed to writing original draft and revised the manuscript. V.V.B. and A.S.N. prepared the figures. L.D.K. supervised the manuscript.

Corresponding authors

Correspondence to Marco Cordani or Lekha Dinesh Kumar .

Ethics declarations

Ethics approval and consent to participate, consent for publication.

All the authors approved the publication of this manuscript.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Byroju, V.V., Nadukkandy, A.S., Cordani, M. et al. Retinoblastoma: present scenario and future challenges. Cell Commun Signal 21 , 226 (2023). https://doi.org/10.1186/s12964-023-01223-z

Download citation

Received : 24 March 2023

Accepted : 12 July 2023

Published : 04 September 2023

DOI : https://doi.org/10.1186/s12964-023-01223-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Retinoblastoma
Knudson hypothesis
Chemotherapy
Cell plasticity
Signalling pathways
Molecular targeted therapies

Cell Communication and Signaling

ISSN: 1478-811X

General enquiries: [email protected]

The evolution of imprinting in plants: beyond the seed

Open access
Published: 29 April 2021
Volume 34 , pages 373–383, ( 2021 )

Cite this article

You have full access to this open access article

Sean A. Montgomery ORCID: orcid.org/0000-0003-1680-4858 1 &
Frédéric Berger ORCID: orcid.org/0000-0002-3609-8260 1

4183 Accesses

9 Citations

5 Altmetric

Explore all metrics

Genomic imprinting results in the biased expression of alleles depending on if the allele was inherited from the mother or the father. Despite the prevalence of sexual reproduction across eukaryotes, imprinting is only found in placental mammals, flowering plants, and some insects, suggesting independent evolutionary origins. Numerous hypotheses have been proposed to explain the selective pressures that favour the innovation of imprinted gene expression and each differs in their experimental support and predictions. Due to the lack of investigation of imprinting in land plants, other than angiosperms with triploid endosperm, we do not know whether imprinting occurs in species lacking endosperm and with embryos developing on maternal plants. Here, we discuss the potential for uncovering additional examples of imprinting in land plants and how these observations may provide additional support for one or more existing imprinting hypotheses.

Identification and Comparison of Imprinted Genes Across Plant Species

Conserved imprinting associated with unique epigenetic signatures in the Arabidopsis genus

Maja Klosinska, Colette L. Picard & Mary Gehring

DNA Demethylation and Gene Imprinting in Flowering Plants

Avoid common mistakes on your manuscript.

Introduction

The term imprinting was coined by Helen Crouse in 1960 who described a process of parent-of-origin specific chromosome elimination during sex determination in black flies (Sciara), happening in both the soma and the germline, and differing between males and females (Crouse 1960 ). This led to the hypothesis that chromosomes carried a mark, an imprint, of their parental origin, which is carried across cell divisions. Since then, parental genomic imprinting has been discovered and studied in detail in placental mammals and flowering plants where it affects single genes and gene clusters, as opposed to the whole chromosomes of Sciara (Kelsey and Feil 2013 ; McGrath and Solter 1984 ; Surani et al. 1984 ). One exception is the imprinting of the X chromosome, wherein the paternal X chromosome is preferentially inactivated in specific embryonic (Okamoto et al. 2004 ), extraembryonic (Takagi and Sasaki 1975 ) and somatic cells (Deakin 2013 ) of particular mammalian species. The modern definition of imprinting encompasses its molecular phenotype, that is an epigenetic phenomenon in which alleles are expressed in a parent-of-origin specific manner. An epigenetic mark, or “imprint”, is established prior to fertilization that serves to direct the asymmetric silencing of alleles. Most imprinted genes are marked by DNA methylation (Batista and Köhler 2020 ), though studies in plants (Jullien et al. 2006 ; Moreno-Romero et al. 2019 ) and more recently in mouse (Chen et al. 2019 ; Inoue et al. 2018 ) have highlighted a role for the repressive histone modification H3K27me3.

While imprinting may potentially occur in all sexually reproducing organisms, it has only been described in placental mammals, flowering plants and some insect species. From such a sparse distribution it follows that imprinting must have arisen through convergent evolution, and thus raises the question about the selective pressures that favour the evolution of imprinting. A consensus on why imprinting has evolved remains elusive. Given the array of examples that support one or more hypotheses, it is likely that imprinting may arise under different selective pressures. In seed plants, evolutionary selection applies to the fitness of the offspring in terms of seed-proper development, maturation, survival, germination and survival of the seedling, whereas in non-seed plant offspring fitness is primarily a function of embryo survival and spore production.

The hypothesis that has arguably gained the most traction is the parental conflict hypothesis, also known as the kinship theory (Haig and Westoby 1989 ). This hypothesis posits that genomic imprinting is evolutionarily favoured when the interests of parental alleles in offspring differ from each other, resulting in the expression of whichever allele is favoured to be expressed (Haig 2014 ). Coincidently, the hypothesis was originally formulated to cover maternal investment in offspring in flowering plants (Haig and Westoby 1989 ). The differential dosage hypothesis extends the parental conflict hypothesis to a broader range of parental interactions that lead to the differential expression of parental alleles, rather than binary on or off states (Dilkes and Comai 2004 ). Nonetheless, both hypotheses deal with the same selective pressure, that is contrasting optima in gene expression levels between maternal and paternal alleles in offspring. Thus, the parental conflict and differential dosage hypotheses will not be distinguished further in this review.

Another prominent hypothesis relevant to imprinting in land plants is the coadaptation hypothesis (Wolf and Hager 2006 ). The coadaptation hypothesis focuses on maternally expressed imprinted genes and proposes that these alleles are preferentially expressed because it allows for improved coordination of resource transfer and growth between mother and offspring across a range of phenotypes (Wolf and Hager 2006 ).

It has been hypothesized that imprinting functions as a post-zygotic barrier in polyploids due to incompatibilities in gene expression levels of imprinted genes in interploidy crosses (Schatlowski and Köhler 2012 ). However, this hypothesis relies on pre-existing imprinting mechanisms that act as a reproductive barrier. It does not deal with the evolutionary origins of imprinting and will not be discussed here. Likewise, the hypothesis that individual imprinted genes have arisen under weak or relaxed selection (Berger et al. 2012 ; Rodrigues and Zilberman 2015 ) relies on the pre-existence of imprinting mechanisms that inadvertently act on these genes. This idea does not address the origin of imprinting and will also not be discussed here.

An excellent overview of these hypotheses is covered by recent reviews (Patten et al. 2014 ; Rodrigues and Zilberman 2015 ), as is a general overview of the evolution of imprinting in animals and plants (Sazhenova and Lebedev 2021 ). In this review, we examine the observations and theories surrounding the evolution of imprinting in land plants and the predictions resulting from them regarding the prevalence of imprinting in non-angiosperm species.

Imprinting in land plants: a spotlight on angiosperms

Numerous reviews on imprinting in flowering plants comprehensively cover the topic (Armenta-Medina and Gillmor 2019 ; Batista and Köhler 2020 ; Gehring and Satyaki 2017 ) and we will briefly cover the basics here for the purpose of making comparisons to non-angiosperm species.

In flowering plants, seeds are the product of two fertilization events. The pollen tube delivers two sperm cells that fertilize the egg and the central cell. The fertilized egg develops as the embryo, while the fertilized central cell develops as the endosperm. The endosperm is usually triploid, directs the flow of nutrients from mother to embryo, and is surrounded by diploid tissues of maternal origin that differentiate from the ovule integuments. Amongst land plants, the search for imprinted genes has only been pursued in monocots and eudicots (Fig. 1 ). Of those genes identified, the vast majority are expressed in the endosperm (Gehring et al. 2011 ; Hsieh et al. 2011 ; Luo et al. 2011 ; Waters et al. 2011 ). There are around one hundred imprinted genes in maize and Arabidopsis, found in roughly equal proportions from both maternal and paternal genomes (Schon and Nodine 2017 ; Wyder et al. 2019 ). While some genes have been found to be imprinted across species and have strong effects on endosperm function when their imprinting is perturbed (Grossniklaus et al. 1998 ; Ingouff et al. 2005 ; Makarevich et al. 2008 ), there has been a wide debate regarding the conservation of the imprinted status of genes (Chen et al. 2018 ; Hatorangan et al. 2016 ; Klosinska et al. 2016 ; Lafon-Placette et al. 2018 ; Liu et al. 2021 ; Pignatta et al. 2014 ; Rong et al. 2021 ; Roth et al. 2018 ; Tuteja et al. 2019 ; Waters et al. 2013 ; Yang et al. 2018 , 2020 ; Yoshida et al. 2018 ). Yet, a conservation of imprinting targets may exist for molecular complexes or pathways rather than individual genes. Difficulties in comparing the distinct modes of endosperm development amongst angiosperms also hinders establishing the degree of conservation (Kordyum and Mosyakin 2020 ). Regardless of their imprinted status, many imprinted genes have not been connected to obvious phenotypes when knocked out or when their imprinting is removed (Berger et al. 2012 ; Waters et al. 2013 ). The assessment of function might be precluded by redundancy and the lack of in-depth studies.

Schematic of land plant evolution. Schematic of major land plant groups and innovations relevant to imprinting. Major events are denoted with stars, including the terrestrialization of plants, dominance of haploid or diploid stages of the life cycle (also denoted in magenta and green), endosperm tissue resulting from a second fertilization event and where imprinting has thus far been described. Ploidy levels of endosperm and the presence of maternally derived resource storage tissues, the nucellus or perisperm, are also indicated

In contrast to the endosperm, only a small number of genes from both maternal and paternal genomes appear to be imprinted and expressed immediately following fertilization in the embryo (Jahnke and Scholten 2009 ; Nodine and Bartel 2012 ; Raissig et al. 2013 ; Zhao et al. 2019 ). Since the endosperm assumes the role of nutrient transfer and storage in the seed and often serves as the main interface between mother and embryo, imprinting in the embryo may have been attenuated or disappeared. However, the few imprinted genes identified in angiosperm embryos may be a remnant of more prevalent imprinting in the embryos of ancestral angiosperms.

Like the endosperm, the suspensor is a non-embryonic, transient tissue involved in nutrient transfer during early embryogenesis. There are reports of parent-of-origin effects on suspensor development (Bayer et al. 2009 ; Luo et al. 2016 ; Ueda et al. 2017 ; Zhang et al. 2017 ), and an analysis of parent-of-origin expression of suspensor genes has shown several hundred genes with biased expression throughout suspensor development (Zhao et al. 2020 ). Given that the endosperm is an angiosperm-specific tissue, it is conceivable that imprinting of genes in the suspensor or embryo is more likely to be conserved in species lacking endosperm, if imprinting were to be identified in those species.

Mechanistically, both H3K27me3 and DNA methylation are associated with imprinted genes, as observed in mammals. In angiosperms, H3K27me3 predominantly marks maternally imprinted alleles of paternally expressed genes, whereas DNA methylation predominantly marks paternally imprinted alleles of maternally expressed genes (Armenta-Medina and Gillmor 2019 ; Batista and Köhler 2020 ; Gehring and Satyaki 2017 ). Imprinted gene expression in endosperm is a result of the maintenance of an epigenetic asymmetry between parental alleles which has already been established in gametes. H3K27me3 is almost completely lost in sperm (Borg et al. 2020 , 2021 ) and likely maintained in female gametes (Pillot et al. 2010 ), whereas DNA methylation is highly reduced in the female gametes (Jullien Pauline et al., 2012 ) and maintained in sperm (Calarco Joseph et al. 2012 ; Kawashima and Berger 2014 ). Therefore, an early clue to detect imprinting in non-angiosperm species may be the presence of an epigenetic asymmetry of H3K27me3 or DNA methylation in the gametes.

Getting to the origins of imprinting and endosperm: ANA-grade angiosperms

The tight association of imprinting with endosperm in monocots and eudicots raises the question of whether imprinting in land plants is dependent on the existence of endosperm, and if so, whether there is a dependence on triploidy in endosperm. This last point is already questioned by the fact that endosperm ploidy is distinct from the triploid ratio of one paternal to two maternal genomes in some species of monocots and eudicots (Kordyum and Mosyakin 2020 ). Imprinting has not been investigated in land plants outside of monocots and eudicots, but endosperm can be found in ANA-grade angiosperms (Fig. 1 ). Several observations, mostly from interploidy crosses, indicate imprinting may be found in these species.

In the Nymphaeales, interploidy crosses revealed contrasting parent-of-origin phenotypes. Extra paternal genomes cause increased endosperm growth, whereas extra maternal genomes cause decreased endosperm growth (Friedman et al. 2012 ; Povilus et al. 2018 ). These results mirror those in other angiosperms (von Wangenheim and Peterson 2004 ) and suggest the presence of imprinted genes in the endosperm in the Nymphaeales. It is interesting to note that the endosperm is diploid in the Nymphaeales (Geeta 2003 ; Floyd and Friedman, 2000 ), but the main resource storage tissue is the perisperm which derives entirely from the mother plant and develops prior to fertilization (Friedman 2008 ) (Fig. 2 ). Similarly, the Piperaceae and Austrobaileyales utilize a maternally derived perisperm or nucellus to store nutrients for the developing embryo (Losada et al. 2017 ; Madrid and Friedman 2010 ; Tobe et al. 2007 ), while the Piperaceae have a highly reduced polyploid endosperm (Madrid and Friedman 2010 ) and the Austrobaileyales have a large diploid endosperm (Losada et al. 2017 ; Tobe et al. 2007 ).

Embryonic development and intergenerational communication across land plants. Schematic of pre- (left) and post- (right) fertilization tissues relevant for imprinting in a bryophytes, b ferns and lycophytes, c Nymphaeales and Austrobaileyales and d Amborella , monocots and eudicots. Ploidy levels and tissue names are indicated inside the relevant tissues. Pink shapes indicate maternally derived tissues. Green circles indicate tissues where resource acquisition occurs, green boxes indicate tissues where resources are stored, and green lines indicate tissue boundaries across which resources are transferred. Purple arrows illustrate potential axes of communication between generations, with filled arrows denoting unfertilized maternal tissues and open arrows denoting post-fertilization tissues. Purple lines around tissues show the boundary between tissues from different generations. Stars indicate tissue in which imprinted genes are predicted to be found, whereas pentagons indicate imprinting is predicted if multiple embryos have access to the same resource storage tissue

These observations are interesting, but in the absence of a clear demonstration of a parent-of-origin bias in the expression of specific genes, it remains unclear whether the observations reported above would challenge the importance of endosperm triploidy in the evolution and function of imprinting in the endosperm (Baroux et al. 2002 ; Stewart-Cox et al. 2004 ). Amborella has a triploid endosperm that is hypothesized to have originated independently from the triploid endosperm of monocots and eudicots, and this species provides the means to test for the relationship between a triploid endosperm and imprinting. Finding imprinted genes in the endosperm of Amborella , but not in the endosperm of Nymphaeales nor Austrobaileyales, would point to a strong connection between triploid endosperm and imprinting. In contrast, the presence of imprinted genes in the endosperm of all angiosperm groups would not support the correlation between imprinting and ploidy levels in endosperm. In conclusion, a high degree of variability of endosperm development in ANA-grade angiosperms may prove to be fertile ground to examine to what degree the evolution of imprinting is directly connected to the evolution of double-fertilization.

Imprinting without seeds: observations from the past

We have so far covered imprinting in seed plants and would like to now consider what little is known about imprinting in the embryos of seedless land plants. An intriguing report in the aquatic fern Marsilea vestita describes a non-random segregation of paternal autosomes during embryonic mitoses after the 16-cell stage and suggests that an imprinting mark may underlie this unusual phenomenon (Tourte et al. 1980 ). Specifically, paternal chromosomes were labelled prior to fertilization and the label accumulated only in cells that will give rise to all aerial organs, whereas the label of maternal chromosomes was observed evenly throughout the fern embryo (Tourte et al. 1980 ). Similar results were later obtained in another aquatic fern, Marsilea quadrifolia (Bordonneau and Tourte 1994 ). If imprinting is behind these observations, this form of imprinting would more closely resemble imprinting in insects such as Sciara, where whole paternal chromosomes are imprinted (Crouse 1960 ). However, in the case of Marsilea , it is unclear whether paternal chromosomes are heterochromatinized, as in Sciara (de la Filia et al. 2021 ). This form of imprinting is also distinct from the more thoroughly studied imprinting of specific maternal and paternal loci in flowering plants and mammals. Since ferns lack sex chromosomes, this type of imprinting would also be distinct from the imprinting of the mammalian X chromosome. Whether and when a potential parentally biased expression would take place during embryogenesis in the model fern Marsilea remains to be tested by transcriptomic analyses. Likewise, neither immunostaining nor chromatin profiling experiments have been performed to identify an imprinting chromatin mark that may distinguish parental chromosomes, nor is the prevalence of this phenomenon across fern species known.

Imprinting in bryophytes: whispers on the wind

We now turn our attention to the land plant groups comprising mosses, liverworts and hornworts, collectively referred to as bryophytes (Fig. 1 ). Like all land plants, bryophytes exhibit an alternation of multicellular haploid and diploid stages during the life cycle. However, in contrast to all vascular plants, the life cycle of bryophytes is characterized by the dominance of the haploid gametophytic stage (Shimamura 2015 ), rendering it the main stage for resource acquisition and support for the diploid embryonic sporophyte which remains attached to the maternal plant for the entirety of its development. The possibility of imprinting in bryophytes has been considered in detail (Haig 2013 ; Haig and Wilczek 2006 ), though no evidence has yet supported its existence.

From a theoretical standpoint, parental genomic imprinting is anticipated to take place in bryophytes (Carey et al. 2020b ; Shaw et al. 2011 ). Several observations of bryophyte sporophytic development, mentioned below, suggest that imprinting may be found in these species. The direct and persistent interface between haploid mother and diploid offspring throughout the entirety of the life of the latter allows for prolonged crosstalk between the two. Extensive cell wall ingrowths and a unique cell wall composition in the region connecting the sporophyte to the maternal gametophyte are suggestive of a specialization to enable communication between the sporophyte and gametophyte (Moody 2020 ; Regmi et al. 2017 ). There is also the possibility for multiple embryos to develop per female gametophyte which can be sired by multiple males (Szovenyi et al. 2009 ). It has been hypothesized that the elongated seta, the stalk that connects the sporophyte to the gametophyte and elevates the former into the air, as well as stomata of moss sporophytes are innovations promoting resource transfer from gametophytes to sporophytes (Haig 2013 ).

Ultimately, the presence of imprinting in mosses will have to be determined by a detailed examination of crosses between distinct accessions with specific polymorphisms enabling parent-of-origin transcriptome analyses. In the moss Sphagnum, a preliminary analysis of sporophyte transcriptomes suggests parent-of-origin effects on transcription due to differences in gene expression between embryos borne on different maternal plants, but the authors concluded that these effects may be due to epigenetic, genetic, or maternal environmental effects (Shaw et al. 2016 ). The authors propose that more detailed analyses of these data, with the ability to discriminate the parental origin of transcripts, may provide valuable insights into imprinting and epigenetic effects on gene expression in moss sporophytes. Despite this initial report, an investigation into parent-of-origin biases of gene expression has not been conducted, thus imprinting has not been demonstrated in bryophytes.

If imprinting were to exist in bryophytes, recent results suggest that DNA methylation may be involved. In the liverwort Marchantia polymorpha , levels of DNA methylation in sperm are higher than in eggs and other tissues (Schmid et al. 2018 ). Mechanistically, this asymmetry of DNA methylation would allow for parental alleles to be distinguished from each other, and maintenance of this asymmetry on promoter regions may lead to the selective silencing of one allele. However, there is a lack of a direct report of DNA methylation on parental alleles during sporophyte development to reach a conclusion.

Predictions of imprinting: gazing into the crystal ball

Under each hypothesis that attempts to explain the evolutionary conditions to allow for or favour imprinting, predictions can and have been made regarding its effects (Haig 2013 ; Patten et al. 2014 ; Rodrigues and Zilberman 2015 ). Here, we will briefly expand on these predictions, particularly in non-seed plants.

Parental conflict and differential dosage hypotheses

Both the parental conflict hypothesis and differential dosage hypothesis revolve around contrasting optima in gene expression between maternal and paternal alleles in offspring (Dilkes and Comai 2004 ; Haig and Westoby 1989 ). Thus, imprinting would be predicted to occur when parental alleles in offspring would “disagree” on the level of expression. We will primarily illustrate this in examples of resource allocation from the mother plant to offspring, and consequently focus on tissues and timepoints in which resource transfer occurs.

In flowering plants, the endosperm is the primary post-fertilization tissue that fulfils the role of nutrient acquisition from and interfacing with the mother plant (Fig. 2 D). The majority of imprinted genes are imprinted and expressed in the endosperm in monocots and eudicots, thus the endosperm appears to be the focus of imprinting in ANA-grade angiosperms under the parental conflict hypothesis. Parent-of-origin effects on endosperm growth in interploidy crosses indicate the presence of imprinted genes in this tissue and is supportive of the prediction under the parental conflict hypothesis that expressed paternal alleles of imprinted genes will favour increased endosperm growth, while the opposite is predicted for expressed maternal alleles. However, the relegation of resource storage to maternal tissues, the perisperm or nucellus, in the Nymphaeales and Austrobaileyales (Fig. 2 C) may have resulted in a relaxation of selection for imprinted genes in the endosperm, as the pool of resources offspring may draw from is determined prior to fertilization by the maternal plant. One may consider the innovation of a maternal perisperm as an alternative strategy to the triploid endosperm with an extra copy of the maternal genome in eudicots and monocots, as both accomplish greater maternal control of resource allocation to offspring. Amborella lacks both a perisperm and nucellus and has a triploid endosperm that is thought to have originated independently from the triploid endosperm of monocots and eudicots (Fig. 1 ). Therefore, the same selective pressures should be acting on Amborella as other species in which imprinting has been described, and we would expect similar genes or pathways to be imprinted.

While genomic imprinting may exist in ferns, it is unlikely to support the parental conflict hypothesis. In most ferns, the main photosynthetic stage is the sporophyte, and the gametophytes are short-lived and therefore mostly function as a platform for fertilization. The gametophytes are not continuously nutritionally supported by the sporophyte and the resources invested into the gametophyte are determined prior to fertilization, similar in fashion to resource allocation to the perisperm in some ANA-grade angiosperms. In addition, most fern female gametophytes give rise to a single zygote and sporophyte (Fig. 2 B), thus all resources can be dedicated to this single fertilization event and there is limited potential for future offspring and alternative uses for stored resources. Therefore, it can be envisaged that maternal and paternal alleles in the offspring would both be selected to maximize resource transfer from the gametophytic mother to the sporophytic offspring. However, some ferns have been observed to bear multiple embryos per gametophyte (Stone 1958 ). In this situation, maternal alleles in the offspring may be favoured to limit resource acquisition from the maternal gametophyte that could be used to nourish other offspring on the same plant, whereas paternal alleles may still be favoured to maximize resource acquisition. Therefore, comparing the presence or absence of imprinting between these two scenarios would clearly delineate support for or against the parental conflict hypothesis. Fern embryos are easier to access than those of other land plant species due to the relative dearth of encapsulating maternal tissue (Bell 1975 ), which facilitates investigations into the presence of imprinted genes and biased chromosome segregation in ferns.

Lycophytes have a similar life cycle structure as ferns, therefore the same predictions as above apply, though no report addressing imprinting in lycophytes has been found. Yet, one difference is that fertilization of lycophytes may take place on the maternal sporophyte inside the wall of the megaspore (Schulz et al. 2010 ; Spencer et al. 2020 ). While this type of maternal protection and investment may favour the evolution of imprinting, this type of fertilization occurs when the plants are self-fertilizing, thus “maternal” and “paternal” alleles are not distinguished as they both originate from the same individual.

A recent study using single-cell transcriptomics in Arabidopsis endosperm showed that, compared to the average in endosperm, a greater proportion of genes show imprinted expression in the chalazal endosperm, a specialized structure in the endosperm that directly interfaces with the maternal sporophyte (Picard et al. 2020 ). In bryophytes, the foot of the sporophyte is the tissue analogous to the chalazal endosperm, specialized for nutrient transfer between the maternal gametophyte and sporophyte (Shimamura 2015 ). Thus, the sporophyte foot may be a hotspot for imprinting. Additionally, the sporophyte remains connected to the gametophyte for the duration of its growth. Rapid growth may cause the sporophyte to act as a nutrient sink and thus function to draw resources from the mother plant since (Fig. 2 A). Specific innovations such as continuous stomatal opening (Kubásek et al. 2021 ; Merced and Renzaglia 2013 ) and elongation of the seta (Haig 2013 ) may be controlled by imprinted genes and would warrant special consideration.

Coadaptation hypothesis

An alternative to the parental conflict hypothesis, the coadaptation hypothesis, is not based on competing influences of the parental genomes in the offspring. Instead, this theory is centred on the interactions amongst gene products from the offspring and mother, and predicts the expression of maternal alleles of imprinted genes to aid in this communication as these alleles are guaranteed to match the maternal genotype (Patten et al. 2014 ; Wolf and Hager 2006 ). In all land plants, there is a potential for interactions between the offspring genotype and maternal genotype (Fig. 2 ). As in all sexually reproducing organisms, the zygote interacts with any maternal factors deposited in the egg, though these factors would likely not persist for many cell divisions. Imprinting of genes expressed immediately after fertilization would be predicted, irrespective of whether this is in the embryo or endosperm. The fertilized egg is always initially surrounded by the maternal gametophyte, and in the case of bryophytes, the offspring remain in direct contact for the duration of its phase in the life cycle. In any case in which resources are transferred or growth is coordinated between mother an offspring, genes in the signalling pathway would be expected to be imprinted. Therefore, the prediction is for specific expression of maternal alleles to coordinate interactions between offspring and mother but does not allow for biased paternal expression.

In ANA-grade angiosperms, like in other angiosperms, the endosperm and embryo suspensor are likely to be the primary post-fertilization tissues involved in interacting with the maternal plant. The main difference of predictions made under the coadaptation hypothesis relative to the parental conflict or differential dosage hypotheses centres on the Nymphaeales and Austrobaileyales. Since the perisperm or nucellus are the main nutrient storage tissues for the developing embryo, a greater number of genes may be imprinted to better coordinate resource transfer to the embryo (Fig. 2 C).

In ferns and lycophytes, the interaction between mother and embryo is often relatively brief, consisting of only the earliest stages of embryonic growth for ferns and lycophytes. While short, this interaction is at a crucial stage of the life cycle, thus imprinting of maternal genes to ensure proper coordination with the gametophytic mother of early growth could be expected to arise (Fig. 2 B).

In bryophytes, the connection between mother and offspring is sustained and necessary (Fig. 2 A). In the context of the coadaptation hypothesis, this strong relation between mother and offspring is expected to result in a large number of imprinted genes as many stages of development may need to be coordinated. Coordinated growth between embryos and mothers may favour imprinting of relevant genes in liverworts more strongly than in mosses and hornworts, as liverwort embryos spend a greater proportion of their life encapsulated by maternal tissue.

Perspectives

To further our understanding of the evolution of imprinting in land plants, we propose three lines of investigation. In all cases, analyses of allele-specific gene expression from transcriptomes devoid of maternal RNA contamination is necessary. First, it is required to establish the presence or absence of imprinting in the endosperm and the embryo of ANA-grade angiosperms to elucidate whether imprinting in angiosperms is always prevalent in the endosperm. Second, investigating the expression of parental alleles in fern embryos will enable the hypothesis of whole chromosome imprinting to be revisited. Thirdly, predictions of imprinting in bryophytes need to be tested at the genomic level by sequencing parental allele specific transcriptomes.

To this end, several recently developed tools will aid in the investigation of imprinting in these species. Published genomes in Nymphaea (Povilus et al. 2020 ; Zhang et al. 2020b ), ferns (Lang et al. 2018 ; Li et al. 2018 , 2020 ; Marchant et al. 2019 ; Rensing et al. 2008 ; Zhang et al. 2020a ) and bryophytes (Bowman et al. 2017 ; Carey et al. 2020a ; McDaniel et al. 2007 ; Montgomery et al. 2020 ) provide good templates to sequence additional natural accessions required to establish parental allele specific transcriptomes. The recent utilization of single-cell RNA sequencing to uncover the spatial heterogeneity of imprinted gene expression in different functional domains of Arabidopsis endosperm (Picard et al. 2020 ) will provide interesting additional information regarding cell type specific imprinting and the function of imprinted genes. Single-cell RNA sequencing would be beneficial to use when looking at the reduced endosperm of ANA-grade angiosperms and early stages of embryogenesis in ferns and bryophytes, particularly focusing on the cells at the interface between embryos and mothers, because the cells in which imprinting may occur in these tissues may be a small percentage of the total population of cells in the tissue. Regardless of whether whole tissues or single cells are collected, special care must be taken to prevent contamination of transcriptomes by RNA from surrounding maternal tissues (Schon and Nodine 2017 ). Finally, assuming that parental genomic imprinting is found in ferns, lycophytes, and bryophytes, a bioinformatic comparison of imprinted genes across all land plant groups using a recently published pipeline (Picard and Gehring 2020 ) may help uncover if common pathways are affected.

Author contribution statement

SAM and FB wrote the manuscript.

Armenta-Medina A, Gillmor CS (2019) Chapter Eighteen—Genetic, molecular and parent-of-origin regulation of early embryogenesis in flowering plants. In: Grossniklaus U (ed) Current topics in developmental biology, vol 131. Academic Press, Boca Raton, pp 497–543. https://doi.org/10.1016/bs.ctdb.2018.11.008

Chapter Google Scholar

Baroux C, Spillane C, Grossniklaus U (2002) Evolutionary origins of the endosperm in flowering plants. Genome Biol 3:reviews1026.1021. https://doi.org/10.1186/gb-2002-3-9-reviews1026

Article Google Scholar

Batista RA, Köhler C (2020) Genomic imprinting in plants-revisiting existing models. Genes Dev 34:24–36. https://doi.org/10.1101/gad.332924.119

Article CAS PubMed PubMed Central Google Scholar

Bayer M, Nawy T, Giglione C, Galli M, Meinnel T, Lukowitz W (2009) Paternal control of embryonic patterning in Arabidopsis thaliana . Science 323:1485–1488. https://doi.org/10.1126/science.1167784

Article CAS PubMed Google Scholar

Bell PR (1975) Observations on the male nucleus during fertilization in the fern Pteridium aquilinum . J Cell Sci 17:141–153

Article CAS Google Scholar

Berger F, Vu TM, Li J, Chen B (2012) Hypothesis: selection of imprinted genes is driven by silencing deleterious gene activity in somatic tissues. Cold Spring Harb Symp Quant Biol 77:23–29. https://doi.org/10.1101/sqb.2012.77.014514

Bordonneau M, Tourte Y (1994) Differential expression of parental genomes during formation of embryonic organs in the early development of the fern Marsilea quadrifolia . Plant Syst Evol 189:149–164. https://doi.org/10.1007/BF00939723

Borg M et al (2020) Targeted reprogramming of H3K27me3 resets epigenetic memory in plant paternal chromatin. Nat Cell Biol 22:621–629. https://doi.org/10.1038/s41556-020-0515-y

Borg M, Papareddy RK, Dombey R, Axelsson E, Nodine MD, Twell D, Berger F (2021) Epigenetic reprogramming rewires transcription during the alternation of generations in Arabidopsis. Elife 10:e61894. https://doi.org/10.7554/eLife.61894

Bowman JL et al (2017) Insights into land plant evolution garnered from the Marchantia polymorpha genome. Cell 171(287–304):e215. https://doi.org/10.1016/j.cell.2017.09.030

Calarco Joseph P et al (2012) Reprogramming of DNA methylation in pollen guides epigenetic inheritance via small RNA. Cell 151:194–205. https://doi.org/10.1016/j.cell.2012.09.001

Carey SB et al (2020a) The Ceratodon purpureus genome uncovers structurally complex, gene rich sex chromosomes. bioRxiv. https://doi.org/10.1101/2020.07.03.163634

Article PubMed PubMed Central Google Scholar

Carey SB, Kollar LM, McDaniel SF (2020b) Does degeneration or genetic conflict shape gene content on UV sex chromosomes? EcoEvoRxiv. https://doi.org/10.32942/osf.io/hs6w3

Chen C et al (2018) Characterization of imprinted genes in rice reveals conservation of regulation and imprinting with other plant species. Plant Physiol 177:1754–1771. https://doi.org/10.1104/pp.17.01621

Chen Z, Yin Q, Inoue A, Zhang C, Zhang Y (2019) Allelic H3K27me3 to allelic DNA methylation switch maintains noncanonical imprinting in extraembryonic cells. Sci Adv 5:7246. https://doi.org/10.1126/sciadv.aay7246

Crouse HV (1960) The controlling element in sex chromosome behavior in sciara. Genetics 45:1429–1443

de la Filia AG, Mongue AJ, Dorrens J, Lemon H, Laetsch DR, Ross L (2021) Males that silence their father’s genes: genomic imprinting of a complete haploid genome. Mol Biol Evol. https://doi.org/10.1093/molbev/msab052

Deakin JE (2013) Marsupial X chromosome inactivation: past, present and future Australian. J Zool 61:13–23

Google Scholar

Dilkes BP, Comai L (2004) A differential dosage hypothesis for parental effects in seed development. Plant Cell 16:3174–3180. https://doi.org/10.1105/tpc.104.161230

Floyd SK, Friedman WE (2000) Evolution of endosperm developmental patterns among basal flowering plants. Int J Plant Sci 161:S57–S81. https://doi.org/10.1086/317579

Friedman WE (2008) Hydatellaceae are water lilies with gymnospermous tendencies. Nature 453:94–97. https://doi.org/10.1038/nature06733

Friedman WE, Bachelier JB, Hormaza JI (2012) Embryology in Trithuria submersa (Hydatellaceae) and relationships between embryo, endosperm, and perisperm in early-diverging flowering plants. Am J Bot 99:1083–1095. https://doi.org/10.3732/ajb.1200066

Article PubMed Google Scholar

Geeta R (2003) The origin and maintenance of nuclear endosperms: viewing development through a phylogenetic lens. Proc Biol Sci 270:29–35. https://doi.org/10.1098/rspb.2002.2206

Gehring M, Satyaki PR (2017) Endosperm and imprinting, inextricably linked. Plant Physiol 173:143–154. https://doi.org/10.1104/pp.16.01353

Gehring M, Missirian V, Henikoff S (2011) Genomic analysis of parent-of-origin allelic expression in Arabidopsis thaliana seeds. PLoS ONE 6:e23687. https://doi.org/10.1371/journal.pone.0023687

Grossniklaus U, Vielle-Calzada J-P, Hoeppner MA, Gagliano WB (1998) Maternal control of embryogenesis by MEDEA , a Polycomb group gene in Arabidopsis . Science 280:446–450. https://doi.org/10.1126/science.280.5362.446

Haig D (2013) Filial mistletoes: the functional morphology of moss sporophytes. Ann Bot 111:337–345. https://doi.org/10.1093/aob/mcs295

Haig D (2014) Coadaptation and conflict, misconception and muddle, in the evolution of genomic imprinting. Heredity 113:96–103. https://doi.org/10.1038/hdy.2013.97

Haig D, Westoby M (1989) Parent-specific gene expression and the triploid endosperm. Am Nat 134:147–155. https://doi.org/10.1086/284971

Haig D, Wilczek A (2006) Sexual conflict and the alternation of haploid and diploid generations. Philos Trans R Soc Lond B Biol Sci 361:335–343. https://doi.org/10.1098/rstb.2005.1794

Hatorangan MR, Laenen B, Steige KA, Slotte T, Köhler C (2016) Rapid evolution of genomic imprinting in two species of the brassicaceae. Plant Cell 28:1815–1827. https://doi.org/10.1105/tpc.16.00304

Hsieh T-F et al (2011) Regulation of imprinted gene expression in Arabidopsis endosperm. Proc Natl Acad Sci 108:1755–1762. https://doi.org/10.1073/pnas.1019273108

Ingouff M, Haseloff J, Berger F (2005) Polycomb group genes control developmental timing of endosperm. Plant J 42:663–674. https://doi.org/10.1111/j.1365-313X.2005.02404.x

Inoue A, Chen Z, Yin Q, Zhang Y (2018) Maternal Eed knockout causes loss of H3K27me3 imprinting and random X inactivation in the extraembryonic cells. Genes Dev 32:1525–1536. https://doi.org/10.1101/gad.318675.118

Jahnke S, Scholten S (2009) Epigenetic resetting of a gene imprinted in plant embryos. Curr Biol 19:1677–1681. https://doi.org/10.1016/j.cub.2009.08.053

Jullien PE, Katz A, Oliva M, Ohad N, Berger F (2006) Polycomb group complexes self-regulate imprinting of the Polycomb group gene MEDEA in Arabidopsis. Curr Biol 16:486–492. https://doi.org/10.1016/j.cub.2006.01.020

Jullien Pauline E, Susaki D, Yelagandula R, Higashiyama T, Berger F (2012) DNA methylation dynamics during sexual reproduction in Arabidopsis thaliana . Curr Biol 22:1825–1830. https://doi.org/10.1016/j.cub.2012.07.061

Kawashima T, Berger F (2014) Epigenetic reprogramming in plant sexual reproduction. Nat Rev Genet 15:613–624. https://doi.org/10.1038/nrg3685

Kelsey G, Feil R (2013) New insights into establishment and maintenance of DNA methylation imprints in mammals. Philos Trans R Soc Lond B Biol Sci 368:20110336. https://doi.org/10.1098/rstb.2011.0336

Klosinska M, Picard CL, Gehring M (2016) Conserved imprinting associated with unique epigenetic signatures in the Arabidopsis genus. Nat Plants 2:16145. https://doi.org/10.1038/nplants.2016.145

Kordyum EL, Mosyakin SL (2020) Endosperm of angiosperms and genomic imprinting. Life 10:104

Kubásek J, Hájek T, Duckett J, Pressel S, Šantrůček J (2021) Moss stomata do not respond to light and CO 2 concentration but facilitate carbon uptake by sporophytes: a gas exchange, stomatal aperture and 13C labelling study. New Phytol. https://doi.org/10.1111/nph.17208

Lafon-Placette C, Hatorangan MR, Steige KA, Cornille A, Lascoux M, Slotte T, Köhler C (2018) Paternally expressed imprinted genes associate with hybridization barriers in Capsella. Nat Plants 4:352–357. https://doi.org/10.1038/s41477-018-0161-6

Lang D et al (2018) The Physcomitrella patens chromosome-scale assembly reveals moss genome structure and evolution. Plant J 93:515–533. https://doi.org/10.1111/tpj.13801

Li F-W et al (2018) Fern genomes elucidate land plant evolution and cyanobacterial symbioses. Nat Plants 4:460–472. https://doi.org/10.1038/s41477-018-0188-8

Li F-W et al (2020) Anthoceros genomes illuminate the origin of land plants and the unique biology of hornworts. Nat Plants 6:259–272. https://doi.org/10.1038/s41477-020-0618-2

Liu Y, Jing X, Zhang H, Xiong J, Qiao Y (2021) Identification of imprinted genes based on homology: an example of Fragaria vesca. Genes 12:380

Losada JM, Bachelier JB, Friedman WE (2017) Prolonged embryogenesis in Austrobaileya scandens (Austrobaileyaceae): its ecological and evolutionary significance. New Phytol 215:851–864. https://doi.org/10.1111/nph.14621

Luo M et al (2011) A genome-wide survey of imprinted genes in rice seeds reveals imprinting primarily occurs in the endosperm. PLOS Genet 7:e1002125. https://doi.org/10.1371/journal.pgen.1002125

Luo A, Zhao P, Zhang L-Y, Sun M-X (2016) Initiation of programmed cell death in the suspensor is predominantly regulated maternally in a tobacco hybrid. Sci Rep 6:29467. https://doi.org/10.1038/srep29467

Madrid EN, Friedman WE (2010) Female gametophyte and early seed development in Peperomia (Piperaceae). Am J Bot 97:1–14. https://doi.org/10.3732/ajb.0800423

Makarevich G, Villar CB, Erilova A, Kohler C (2008) Mechanism of PHERES1 imprinting in Arabidopsis . J Cell Sci 121:906–912. https://doi.org/10.1242/jcs.023077

Marchant DB, Sessa EB, Wolf PG, Heo K, Barbazuk WB, Soltis PS, Soltis DE (2019) The C-Fern ( Ceratopteris richardii ) genome: insights into plant genome evolution with the first partial homosporous fern genome assembly. Sci Rep 9:18181. https://doi.org/10.1038/s41598-019-53968-8

McDaniel SF, Willis JH, Shaw AJ (2007) A linkage map reveals a complex basis for segregation distortion in an interpopulation cross in the moss Ceratodon purpureus . Genetics 176:2489–2500. https://doi.org/10.1534/genetics.107.075424

McGrath J, Solter D (1984) Completion of mouse embryogenesis requires both the maternal and paternal genomes. Cell 37:179–183. https://doi.org/10.1016/0092-8674(84)90313-1

Merced A, Renzaglia KS (2013) Moss stomata in highly elaborated Oedipodium (Oedipodiaceae) and highly reduced Ephemerum (Pottiaceae) sporophytes are remarkably similar. Am J Bot 100:2318–2327. https://doi.org/10.3732/ajb.1300214

Montgomery SA et al (2020) Chromatin organization in early land plants reveals an ancestral association between H3K27me3 transposons, and constitutive heterochromatin. Curr Biol 30:573-588.e577. https://doi.org/10.1016/j.cub.2019.12.015

Moody LA (2020) Three-dimensional growth: a developmental innovation that facilitated plant terrestrialization. J Plant Res 133:283–290. https://doi.org/10.1007/s10265-020-01173-4

Moreno-Romero J, Del Toro-De LG, Yadav VK, Santos-González J, Köhler C (2019) Epigenetic signatures associated with imprinted paternally expressed genes in the Arabidopsis endosperm. Genome Biol 20:41. https://doi.org/10.1186/s13059-019-1652-0

Nodine MD, Bartel DP (2012) Maternal and paternal genomes contribute equally to the transcriptome of early plant embryos. Nature 482:94–97. https://doi.org/10.1038/nature10756

Okamoto I, Otte AP, Allis CD, Reinberg D, Heard E (2004) Epigenetic dynamics of imprinted X inactivation during early mouse development. Science 303:644–649. https://doi.org/10.1126/science.1092727

Patten MM, Ross L, Curley JP, Queller DC, Bonduriansky R, Wolf JB (2014) The evolution of genomic imprinting: theories, predictions and empirical tests. Heredity 113:119–128. https://doi.org/10.1038/hdy.2014.29

Picard CL, Gehring M (2020) Identification and comparison of imprinted genes across plant species. In: Spillane C, McKeown P (eds) Plant epigenetics and epigenomics: methods and protocols. Springer, New York, pp 173–201. https://doi.org/10.1007/978-1-0716-0179-2_13

Picard CL, Povilus RA, Williams BP, Gehring M (2020) Single nucleus analysis of Arabidopsis seeds reveals new cell types and imprinting dynamics. bioRxiv. https://doi.org/10.1101/2020.08.25.267476

Pignatta D, Erdmann RM, Scheer E, Picard CL, Bell GW, Gehring M (2014) Natural epigenetic polymorphisms lead to intraspecific variation in Arabidopsis gene imprinting. Elife 3:e03198. https://doi.org/10.7554/eLife.03198

Pillot M et al (2010) Embryo and endosperm inherit distinct chromatin and transcriptional states from the female gametes in Arabidopsis . Plant Cell 22:307–320. https://doi.org/10.1105/tpc.109.071647

Povilus RA, Diggle PK, Friedman WE (2018) Evidence for parent-of-origin effects and interparental conflict in seeds of an ancient flowering plant lineage. Proc Biol Sci. https://doi.org/10.1098/rspb.2017.2491

Povilus RA et al (2020) Water lily ( Nymphaea thermarum ) genome reveals variable genomic signatures of ancient vascular cambium losses. Proc Natl Acad Sci 117:8649–8656. https://doi.org/10.1073/pnas.1922873117

Raissig MT, Bemer M, Baroux C, Grossniklaus U (2013) Genomic imprinting in the Arabidopsis embryo is partly regulated by PRC2. PLOS Genet 9:e1003862. https://doi.org/10.1371/journal.pgen.1003862

Regmi KC, Li L, Gaxiola RA (2017) Alternate modes of photosynthate transport in the alternating generations of Physcomitrella patens . Front Plant Sci. https://doi.org/10.3389/fpls.2017.01956

Rensing SA et al (2008) The Physcomitrella genome reveals evolutionary insights into the conquest of land by plants. Science 319:64–69. https://doi.org/10.1126/science.1150646

Rodrigues JA, Zilberman D (2015) Evolution and function of genomic imprinting in plants. Genes Dev 29:2517–2531. https://doi.org/10.1101/gad.269902.115

Rong H, Yang W, Zhu H, Jiang B, Jiang J, Wang Y (2021) Genomic imprinted genes in reciprocal hybrid endosperm of Brassica napus . BMC Plant Biol 21:140. https://doi.org/10.1186/s12870-021-02908-8

Roth M, Florez-Rueda AM, Paris M, Städler T (2018) Wild tomato endosperm transcriptomes reveal common roles of genomic imprinting in both nuclear and cellular endosperm. Plant J 95:1084–1101. https://doi.org/10.1111/tpj.14012

Sazhenova EA, Lebedev IN (2021) Evolutionary aspects of genomic imprinting molecular. Biology 55:1–15. https://doi.org/10.1134/S0026893320060102

Schatlowski N, Köhler C (2012) Tearing down barriers: understanding the molecular mechanisms of interploidy hybridizations. J Exp Bot 63:6059–6067. https://doi.org/10.1093/jxb/ers288

Schmid MW, Giraldo-Fonseca A, Rövekamp M, Smetanin D, Bowman JL, Grossniklaus U (2018) Extensive epigenetic reprogramming during the life cycle of Marchantia polymorpha . Genome Biol 19:9. https://doi.org/10.1186/s13059-017-1383-z

Schon MA, Nodine MD (2017) Widespread contamination of Arabidopsis embryo and endosperm transcriptome data sets. Plant Cell 29:608–617. https://doi.org/10.1105/tpc.16.00845

Schulz C et al (2010) An overview of the morphology, anatomy, and life cycle of a new model species: the lycophyte Selaginella apoda (L) spring. Int J Plant Sci 171:693–712. https://doi.org/10.1086/654902

Shaw AJ, Szovenyi P, Shaw B (2011) Bryophyte diversity and evolution: windows into the early evolution of land plants. Am J Bot 98:352–369. https://doi.org/10.3732/ajb.1000316

Shaw AJ, Schmutz J, Devos N, Shu S, Carrell AA, Weston DJ (2016) Chapter Five—The Sphagnum genome project: anew model for ecological and evolutionary genomics. In: Rensing SA (ed) Advances in botanical research, vol 78. Academic Press, Boca Raton, pp 167–187. https://doi.org/10.1016/bs.abr.2016.01.003

Shimamura M (2015) Marchantia polymorpha : taxonomy, phylogeny and morphology of a model system. Plant Cell Physiol 57:230–256. https://doi.org/10.1093/pcp/pcv192

Spencer V, Nemec Venza Z, Harrison CJ (2020) What can lycophytes teach us about plant evolution and development? Modern perspectives on an ancient lineage. Evol Dev. https://doi.org/10.1111/ede.12350

Stewart-Cox JA, Britton NF, Mogie M (2004) Endosperm triploidy has a selective advantage during ongoing parental conflict by imprinting. Proc R Soc Lond Ser B Biol Sci 271:1737–1743. https://doi.org/10.1098/rspb.2004.2783

Stone I (1958) The gametophyte and embryo of Polyphlebium venosum (R. Br.) Copeland (Hymenophyllaceae). Aust J Bot 6:183–203. https://doi.org/10.1071/BT9580183

Surani MA, Barton SC, Norris ML (1984) Development of reconstituted mouse eggs suggests imprinting of the genome during gametogenesis. Nature 308:548–550. https://doi.org/10.1038/308548a0

Szovenyi P, Ricca M, Shaw AJ (2009) Multiple paternity and sporophytic inbreeding depression in a dioicous moss species. Heredity (Edinb) 103:394–403. https://doi.org/10.1038/hdy.2009.82

Takagi N, Sasaki M (1975) Preferential inactivation of the paternally derived X chromosome in the extraembryonic membranes of the mouse. Nature 256:640–642. https://doi.org/10.1038/256640a0

Tobe H, Kimoto Y, Prakash N (2007) Development and structure of the female gametophyte in Austrobaileya scandens (Austrobaileyaceae). J Plant Res 120:431–436. https://doi.org/10.1007/s10265-007-0085-0

Tourte Y, Kuligowski-Andres J, Barbier-Ramond C (1980) Different behaviour of paternal and maternal genomes during embryogenesis in the fern, Marsilea (author’s transl). Eur J Cell Biol 21:28–36

CAS PubMed Google Scholar

Tuteja R et al (2019) Paternally expressed imprinted genes under positive darwinian selection in Arabidopsis thaliana . Mol Biol Evol 36:1239–1253. https://doi.org/10.1093/molbev/msz063

Ueda M et al (2017) Transcriptional integration of paternal and maternal factors in the Arabidopsis zygote. Genes Dev 31:617–627. https://doi.org/10.1101/gad.292409.116

von Wangenheim K-H, Peterson H-P (2004) Aberrant endosperm development in interploidy crosses reveals a timer of differentiation. Dev Biol 270:277–289. https://doi.org/10.1016/j.ydbio.2004.03.014

Waters AJ et al (2011) Parent-of-origin effects on gene expression and DNA methylation in the maize endosperm. Plant Cell 23:4221–4233. https://doi.org/10.1105/tpc.111.092668

Waters AJ, Bilinski P, Eichten SR, Vaughn MW, Ross-Ibarra J, Gehring M, Springer NM (2013) Comprehensive analysis of imprinted genes in maize reveals allelic variation for imprinting and limited conservation with other species. Proc Natl Acad Sci USA 110:19639–19644. https://doi.org/10.1073/pnas.1309182110

Wolf JB, Hager R (2006) A maternal-offspring coadaptation theory for the evolution of genomic imprinting. PLOS Biol 4:e380. https://doi.org/10.1371/journal.pbio.0040380

Wyder S, Raissig MT, Grossniklaus U (2019) Consistent reanalysis of genome-wide imprinting studies in plants using generalized linear models increases concordance across datasets. Sci Rep 9:1320. https://doi.org/10.1038/s41598-018-36768-4

Yang G et al (2018) Genomic imprinting was evolutionarily conserved during wheat polyploidization. Plant Cell 30:37–47. https://doi.org/10.1105/tpc.17.00837

Yang L, Xing F, He Q, Tahir ul Qamar M, Chen L-L, Xing Y (2020) Conserved imprinted genes between intra-subspecies and inter-subspecies are involved in energy metabolism and seed development in rice. Int J Mol Sci 21:9618

Yoshida T, Kawanabe T, Bo Y, Fujimoto R, Kawabe A (2018) Genome-wide analysis of parent-of-origin allelic expression in endosperms of brassicaceae species, Brassica rapa . Plant Cell Physiol 59:2590–2601. https://doi.org/10.1093/pcp/pcy178

Zhang M et al (2017) Maternal control of embryogenesis by MPK6 and its upstream MKK4/MKK5 in Arabidopsis. Plant J 92:1005–1019. https://doi.org/10.1111/tpj.13737

Zhang J et al (2020a) The hornwort genome and early land plant evolution. Nat Plants 6:107–118. https://doi.org/10.1038/s41477-019-0588-4

Zhang L et al (2020b) The water lily genome and the early evolution of flowering plants. Nature 577:79–84. https://doi.org/10.1038/s41586-019-1852-5

Zhao P et al (2019) Two-step maternal-to-zygotic transition with two-phase parental genome contributions. Dev Cell 49:882-893.e885. https://doi.org/10.1016/j.devcel.2019.04.016

Zhao P, Zhou X, Zheng Y, Ren Y, Sun M-X (2020) Equal parental contribution to the transcriptome is not equal control of embryogenesis. Nat Plants 6:1354–1364. https://doi.org/10.1038/s41477-020-00793-x

Download references

Acknowledgements

This work was supported by the the Austrian Academy of Sciences [to FB], and the Austrian Science Fund (FWF): P26887, P28320, P32054, and P33380 [to FB] and the doctoral school DK W1238 (SAM and FB).

Open access funding provided by Research Institute of Molecular Pathology (IMP) / Institute of Molecular Biotechnology (IMBA)/ Gregor Mendel Institute of Molecular Plant Biology (GMI). This work was supported by the Austrian Science Fund (FWF): P26887, P28320, P32054, and P33380 (to FB) and the doctoral school DK W1238 (to SAM).

Author information

Authors and affiliations.

Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Dr. Bohr Gasse 3, 1030, Vienna, Austria

Sean A. Montgomery & Frédéric Berger

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Frédéric Berger .

Ethics declarations

Conflict of interest.

The authors declare no conflict of interest.

Additional information

Communicated by Thomas Dresselhaus.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

A contribution to the special issue ‘Evolution of Plant Reproduction’.

Rights and permissions

Reprints and permissions

About this article

Montgomery, S.A., Berger, F. The evolution of imprinting in plants: beyond the seed. Plant Reprod 34 , 373–383 (2021). https://doi.org/10.1007/s00497-021-00410-7

Download citation

Received : 01 February 2021

Accepted : 12 April 2021

Published : 29 April 2021

Issue Date : December 2021

DOI : https://doi.org/10.1007/s00497-021-00410-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Find a journal
Publish with us
Track your research

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Institute of Medicine (US) Committee on Assessing Interactions Among Social, Behavioral, and Genetic Factors in Health; Hernandez LM, Blazer DG, editors. Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate. Washington (DC): National Academies Press (US); 2006.

Cover of Genes, Behavior, and the Social Environment

Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate.

Hardcopy Version at National Academies Press

3 Genetics and Health

Although there are many possible causes of human disease, family history is often one of the strongest risk factors for common disease complexes such as cancer, cardiovascular disease (CVD), diabetes, autoimmune disorders, and psychiatric illnesses. A person inherits a complete set of genes from each parent, as well as a vast array of cultural and socioeconomic experiences from his/her family. Family history is thought to be a good predictor of an individual’s disease risk because family members most closely represent the unique genomic and environmental interactions that an individual experiences ( Kardia et al., 2003 ). Inherited genetic variation within families clearly contributes both directly and indirectly to the pathogenesis of disease. This chapter focuses on what is known or theorized about the direct link between genes and health and what still must be explored in order to understand the environmental interactions and relative roles among genes that contribute to health and illness.

GENETIC SUSCEPTIBILITY

For more than 100 years, human geneticists have been studying how variations in genes contribute to variations in disease risk. These studies have taken two approaches. The first approach focuses on identifying the individual genes with variations that give rise to simple Mendelian patterns of disease inheritance (e.g., autosomal dominant, autosomal recessive, and X-linked) (see Table 3-1 ; Mendelian Inheritance in Man). The second approach seeks to understand the genetic susceptibility to disease as the con sequence of the joint effects of many genes. Each of these approaches will be discussed below.

Online Mendelian Inheritance in Man (OMIM) Statistics (as of May 15, 2006), Number of Entries.

In general, diseases with simple Mendelian patterns of inheritance tend to be relatively uncommon or frequently rare, with early ages of onset, such as phenylketonuria, sickle cell anemia, Tay-Sachs disease, and cystic fibrosis. In addition, some of these genes have been associated with extreme forms of common diseases, such as familial hypercholesterolemia, which is caused by mutations in the low-density lipoprotein (LDL) receptor that predispose individuals to early onset of heart disease ( Brown and Goldstein, 1981 ).

Another example of Mendelian inheritance is familial forms of breast cancer associated with mutations in the BRCA1 and BRCA2 genes that predispose women to early onset breast cancer and often ovarian cancer. The genes identified have mutations that often are highly penetrant—that is, the probability of developing the disease in someone carrying the disease susceptibility genotype is relatively high (greater than 50 percent). These genetic diseases often exhibit a genetic phenomenon known as allelic heterogeneity, in which multiple mutations within the same gene (i.e., alleles) are found to be associated with the same disease. This allelic heterogeneity often is population specific and can represent the unique demographic and mutational history of the population.

In some cases, genetic diseases also are associated with locus heterogeneity , meaning that a deleterious mutation in any one of several genes can give rise to an increased risk of the disease. This is a finding common to many human diseases including Alzheimer’s disease and polycystic kidney disease. Both allelic heterogeneity and locus heterogeneity are sources of variation in these disease phenotypes since they can have varying effects on the disease initiation, progression, and clinical severity.

Environmental factors also vary across individuals and the combined effect of environmental and genetic heterogeneity is etiologic heterogeneity. Etiologic heterogeneity refers to a phenomenon that occurs in the general population when multiple groups of disease cases, such as breast cancer clusters, exhibit similar clinical features, but are in fact the result of differing events or exposures. Insight into the etiology of specific diseases as well as identification of possible causative agents is facilitated by discovery and examination of disease cases demonstrating etiologic heterogeneity. The results of these studies may also highlight possible gene-gene interactions and gene-environment interactions important in the disease process. Identifying etiologic heterogeneity can be an important step toward analysis of diseases using molecular epidemiology techniques and may eventually lead to improved disease prevention strategies ( Rebbeck et al., 1997 ).

As opposed to the Mendelian approach, the second approach to studying how variations in genes contribute to variations in disease risk focuses on understanding the genetic susceptibility to diseases as the consequence of the joint effects of many genes, each with small to moderate effects (i.e., polygenic models of disease) and often interacting among themselves and with the environment to give rise to the distribution of disease risk seen in a population (i.e., multifactorial models of disease). This approach has been used primarily for understanding the genetics of birth defects and common diseases and their risk factors. As described below, several steps are involved in developing such an understanding.

As a first step, study participants are asked to provide a detailed family history to assess the presence of familial aggregation. If individuals with the disease in question have more relatives affected by the disease than individuals without the disease, familial aggregation is identified. While familial aggregation may be accounted for through genetic etiology, it may also represent an exposure (e.g., pesticides, contaminated drinking water, or diet) common to all family members due to the likelihood of shared environment.

When there is evidence of familial aggregation, the second step is to focus research studies on estimating the heritability of the disease and/or its risk factors. Heritability is defined as the proportion of variation in disease risk in a population that is attributable to unmeasured genetic variations inferred through familial patterns of disease. It is a broad population-based measure of genetic influence that is used to determine whether further genetic studies are warranted, since it allows investigators to test the overarching null hypothesis that no genes are involved in determining disease risk. Twin studies and family studies are frequently used in the study of heritability.

Twin studies comparing the disease and risk factor variability of monozygotic and dizygotic twins have been a common study design used to easily estimate both genetic and cultural inheritance. Studies of monozygotic twins reared together versus those reared apart also have been important in estimating both genetic and environmental contributions to patterns of inheritance. The modeling of the sources of phenotypic variation using family studies has become quite sophisticated, allowing the inclusion of model parameters to represent the additive genetic component (i.e., polygenes), the nonadditive genetic component (i.e., genetic dominance, as well as gene-environment and gene-gene interactions), shared family environment, and individual environments. The contributions of these factors have been shown to vary by age and population.

When significant evidence of genetic involvement is established, the next step is to identify the responsible genes and the mutations that are associated with increased or decreased risk, using either genetic linkage analysis or genetic association studies. For example, in the study of birth defects, this often involves the search for chromosomal deletions, insertions, duplications, or translocations.

GENETIC LINKAGE ANALYSIS AND GENETIC ASSOCIATION STUDIES

The human genome is made up of tens of thousands of genes. With approximately 30,000 genes to choose from, assigning a specific gene or group of genes to a corresponding human disease demands a methodical approach consisting of many steps. Traditionally, the process of gene discovery begins with a linkage analysis that assesses disease within families. Linkage analyses are typically followed by genetic association studies that assess disease across families or across unrelated individuals.

Genetic Linkage Analysis

The term linkage refers to the tendency of genes proximally located on the same chromosome to be inherited together. Linkage analysis is one step in the search for a disease susceptibility gene. The goal of this analysis is to approximate the location of the disease gene in relation to a known genetic marker, applying an understanding of the patterns of linkage. Traditional linkage analysis that traces patterns of heredity of both the disease phenotype and genetic markers in large, high-risk families have been used to locate disease-causing gene mutations such as the breast cancer gene (BRCA1) on chromosome 17 ( Hall et al., 1990 ).

Because the mode of inheritance is often not clear for common diseases, an alternative approach to classic linkage analysis was developed to capitalize on the basic genetic principle that siblings share half of their alleles on average. By investigating the degree of allelic sharing across their genomes, pairs of affected siblings (i.e., two or more siblings with the same disease) can be used to identify chromosomal regions that may contain genes whose variations are related to the disease being studied. If numerous sibling pairs affected by the disease of interest exhibit a greater than expected sharing of the known alleles of the polymorphic genetic marker being used, then the genetic marker is likely to be linked (that is, within close proximity along the chromosome) to the susceptibility gene responsible for the disease being studied. To find chromosomal regions that show evidence for linkage using this affected sibling pair method typically requires typing numerous affected sibships with hundreds of highly polymorphic markers uniformly positioned along the human genome ( Mathew, 2001 ).

This approach has been widely used to identify regions of the genome thought to contribute to common chronic diseases. However, results of linkage analyses have not been consistently replicated. The inability to successfully replicate linkage findings may be a result of insufficient statistical power (that is, including an inadequate number of sibling pairs with the disease of interest) or results that included false positives in the original study. An alternate explanation could be that different populations are affected by different susceptibility genes than those that were studied originally ( Mathew, 2001 ). Without consistent replication of results it is premature to draw conclusions about the contribution of a gene locus to a specific disease.

Upon the confirmation of a linkage, researchers can begin to search the region for the candidate susceptibility gene. The search for a single susceptibility gene for common diseases often involves examination of very large linkage regions, containing 20 to 30 million base pairs and potentially hundreds of genes ( Mathew, 2001 ). It is also important to note, however, that while linkage mapping is a powerful tool for finding Mendelian disease genes, it often produces weak and sometimes inconsistent signals in studies of complex diseases that may be multifactorial. Linkage studies perform best when there is a single susceptibility allele at any given disease locus and generally performs poorly when there is substantial genetic heterogeneity.

Genetic Association Studies

Technological advances in high-throughput genotyping have allowed the direct examination of specific genetic differences among sizable numbers of people. Genetic association techniques are often the most efficient approach for assessing how specific genetic variation can affect disease risk. Genetic association studies, which have been used for decades, have perpetually progressed in terms of the development of new study designs (such as case-only and family-based association designs), new genotyping systems (such as array-based genotyping and multiplexing assays), and new methods used for addressing biases such as population ( Haines and Pericak-Vance, 1998 ).

Analysis of the effects of genetic variation typically involves first the discovery of single nucleotide polymorphisms (SNPs) 1 and then the analysis of these variations in samples from populations. SNPs occur on average approximately every 500 to 2,000 bases in the human genome. The most common approach to SNP discovery is to sequence the gene of interest in a representative sample of individuals. Currently, sequencing of entire genes on small numbers of individuals (~25 to 50) can detect polymorphisms occurring in 1 to 3 percent of the population with approximately 95 percent confidence. The Human DNA Polymorphism Discovery Program of the National Institute of Environmental Health Sciences’ Environmental Genome Project is one example of the application of automated DNA sequencing technologies to identify SNPs in human genes that may be associated with disease susceptibility and response to environment ( Livingston et al., 2004 ). The National Heart, Lung, and Blood Institute’s Programs in Genomic Applications also has led to important increases in our knowledge about the distribution of SNPs in key genes thought to be already biologically implicated in disease risk (i.e., biological candidate genes 2 ).

Impressive and rapid advances in SNP analysis technology are rapidly redefining the scope of SNP discovery, mapping, and genotyping. New array-based genotyping technology enables “whole genome association” analyses of SNPs between individuals or between strains of laboratory animal species ( Syvanen, 2005 ). Arrays used for these analyses can represent hundreds of thousands of SNPs mapped across a genome ( Klein et al., 2005 ; Hinds et al., 2005 ; Gunderson et al., 2005 ). This approach allows rapid identification of SNPs associated with disease and susceptibility to environmental factors. The strength of this technology is the massive amount of easily measurable genetic variation it puts in the hands of researchers in a cost-effective manner ($500 to $1,000 per chip). The criteria for the selection of SNPs to be included on these arrays are a critical consideration, since they affect the inferences that can be drawn from using these platforms. Of course, the ultimate tool for SNP discovery and genotyping is individual whole genome sequencing. Although not currently feasible, the rapid advancement of technology now being stimulated by the National Human Genome Research Institute’s “$1,000 genome” project likely will make this approach the optimal one for SNP discovery and genotyping in the future.

With the ability to examine large quantities of genetic variations, researchers are moving from investigations of single genes, one at a time, to consideration of entire pathways or physiological systems that include information from genomic, transcriptomic, proteomic, and metabonomic levels that are all subject to different environmental factors ( Haines and Pericak-Vance, 1998 ). However, these genome- and pathway-driven study designs and analytic techniques are still in the early stages of development and will require the joint efforts of multiple disciplines, ranging from molecular biologists to clinicians to social scientists to bioinformaticians, in order to make the most effective use of these vast amounts of data.

GENE-ENVIRONMENT AND GENE-GENE INTERACTIONS

The study of gene-environment and gene-gene interactions represents a broad class of genetic association studies focused on understanding how human genetic variability is associated with differential responses to environmental exposures and with differential effects depending on variations in other genes. To illustrate the concept of gene-environment interactions, recent studies that identify genetic mutations that appear to be associated with differential response to cigarette smoke and its association with lung cancer are reviewed below. Tobacco smoke contains a broad array of chemical carcinogens that may cause DNA damage. There are several DNA repair pathways that operate to repair this damage, and the genes within this pathway are prime biological candidates for understanding why some smokers develop lung cancers but others do not. In a study by Zhou et al. (2003) , variations in two genes responsible for DNA repair were examined for their potential interaction with the level of cigarette smoking and concomitant association with lung cancer. Briefly, one putatively functional mutation in the XRCC1 (X-ray cross-complementing group 1) gene and two putatively functional mutations in the ERCC2 (excision repair cross-complementing group 2) gene were genotyped in 1,091 lung cancer cases and 1,240 controls. When the cases and controls were stratified into heavy smokers versus nonsmokers, Zhou et al. (2003) found that nonsmokers with the mutant XRCCI genotype had a 2.4 times greater risk of lung cancer than nonsmokers with the normal genotype. In contrast, heavy smokers with the mutant XRCCI genotype had a 50 percent reduction in lung cancer risk compared to their counterparts with the more frequent normal genotype. When the three mutations from these two genes were examined together in the extreme genotype combination (individual with five or six mutations present in his/her genotype) there was a 5.2 time greater risk of lung cancer in nonsmokers and a 70 percent reduction of risk in the heavy smokers compared to individuals with no mutations. The protective effect of these genetic variations in heavy smokers may be caused by the differential increase in the activity of these protective genes stimulated by heavy smoking. Similar types of gene-smoking interactions also have been found for other genes in this pathway, such as ERCC1. These studies illustrate the importance of identifying the genetic variations that are associated with the differential risk of disease related to human behaviors. Note that this type of research also raises many different kinds of ethical and social issues, since it identifies susceptible subgroups and protected subgroups of subjects by both genetic and human behavior strata (see Chapter 10 ).

The study by Zhou et al. (2003) also demonstrates the increased information provided by jointly examining the effects of multiple mutations on toxicity-related disease. Other studies of mutations in genes involved in the Phase II metabolism (GSTM1, GSTT1, GSTP1) also have demonstrated the importance of investigating the joint effects of mutations ( Miller et al., 2002 ) on cancer risk. Although these two studies focused on the additive effects of multiple genes, gene-gene interactions are another important component to develop a better understanding of human susceptibility to disease and to interactions with the environment.

To adequately understand the continuum of genomic susceptibility to environmental agents that influences the public’s health, more studies of the joint effects of multiple mutations need to be conducted. Advances in bioinformatics can play a key role in this endeavor. For example, methods to screen SNP databases for mutations in transcriptional regulatory regions can be used for both discovery and functional validation of polymorphic regulatory elements, such as the antioxidant regulatory element found in the promoter regions of many genes encoding antioxidative and Phase II detoxification enzymes ( Wang et al., 2005 ). Comparative sequence analysis methods also are becoming increasingly valuable to human genetic studies, because they provide a means to rank order SNPs in terms of their potential deleterious effects on protein function or gene regulation ( Wang et al., 2004 ). Methods of performing large-scale analysis of nonsynonymous SNPs to predict whether a particular mutation impairs protein function ( Clifford et al., 2004 ) can help in SNP selection for genetic epidemiological studies and can be used to streamline functional analysis of mutations that are found to be statistically associated with differential response to environmental factors such as diet, stress, and socioeconomic factors.

MECHANISMS OF GENE EXPRESSION

Identifying genes whose variations are associated with disease is just the first step in linking genetics and health. Understanding the mechanisms by which the gene is expressed and how it is influenced by other genes, proteins, and the environment is becoming increasingly important to the development of preventive, diagnostic, and therapeutic strategies.

When genes are expressed, the chromosomal DNA must be transcribed into RNA and the RNA is then processed and transported to be translated into protein. Regulating the expression of genes is a vital process in the cell and involves the organization of the chromosomal DNA into an appropriate higher-order chromatin structure. It also involves the action of a host of specific protein factors (to either encourage or suppress gene expression), which can act at different steps in the gene expression pathway.

In all organisms, networks of biochemical reactions and feedback signals organize developmental pathways, cellular metabolism, and progression through the cell cycle. Overall coordination of the cell cycle and cellular metabolism results from feed-forward and feedback controls arising from sets of dependent pathways in which the initiation of events is dependent on earlier events. Within these networks, gene expression is controlled by molecular signals that regulate when, where, and how often a given gene is transcribed. These signals often are stimulated by environmental influences or by signals from other cells that affect the gene expression of many genes through a single regulatory pathway. Since a regulatory gene can act in combination with other signals to control many other genes, complex branching networks of interactions are possible ( McAdams and Arkin, 1997 ).

Gene regulation is critical because by switching genes on or off when needed, cells can be responsive to changes in environment (e.g., changes in diet or activity) and can prevent resources from being wasted. Variation in the DNA sequences associated with the regulation of a gene’s expression are therefore likely candidates for understanding gene-environment interactions at the molecular level, since these variations will affect whether an environmental signal transduced to the nucleus will successfully bind to the promoter sequence in the gene and stimulate or repress gene expression. Combining genomic technologies for SNP genotyping with high-density gene expression arrays in human studies has only recently elucidated the extent to which this type of molecular gene-environment interaction may be occurring.

Cells also regulate gene expression by post-transcriptional modification; by allowing only a subset of the mRNAs to go on to translation; or by restricting translation of specific mRNAs to only when and where the product is needed. The genetic factors that influence post-transcriptional control are much more difficult to study because they often involve multiprotein complexes not easily retrieved or assayed from cells. At other levels, cells regulate gene expression through epigenetic mechanisms, including DNA folding, histone acetylation, and methylation (i.e., chemical modification) of the nucleotide bases. These mechanisms are likely to be influenced by genetic variations in the target genes as well as variations manifested in translated cellular regulatory proteins. Gene regulation occurs throughout life at all levels of organismal development and aging.

A classic example of developmental control of gene expression is the differential expression of embryonic, fetal, and adult hemoglobin genes (see Box 3-1 ). The regulation of the epsilon, delta, gamma, alpha, and beta genes occurs through DNA methylation that is tightly controlled through developmental signals. During development a large number of genes are turned on and off through epigenetic regulation. One of the fastest growing fields in genetics is the study of the developmental consequences of environmental exposures on gene expression patterns and the impact of genetic variations on these developmental trajectories.

Gene Expression and Globin. The production of hemoglobin is regulated by a number of transcriptional controls, such as switching, that dictate the expression of a different set of globin genes in different parts of the body throughout the various stages (more...)

An Example of a Single-Gene Disorder with Significant Clinical Variability: Sickle Cell Disease 3

Sickle cell disease refers to an autosomal recessive blood disorder caused by a variant of the β-globin gene called sickle hemoglobin (Hb S). A single nucleotide substitution (T→A) in the sixth codon of the β-globin gene results in the substitution of valine for glutamic acid (GTG→GAG), which can cause Hb S to polymerize (form long chains) when deoxygenated ( Stuart and Nagel, 2004 ). An individual inheriting two copies of Hb S (Hb SS) is considered to have sickle cell anemia , while an individual inheriting one copy of Hb S plus another deleterious β-globin variant (e.g., Hb C or Hb β-thalassemia) is considered to have sickle cell disease . An individual is considered to be a carrier of the sickle cell trait if he/she has one copy of the normal β-globin gene and one copy of the sickle variant (Hb AS) ( Ashley-Koch et al., 2000 ).

Four major β-globin gene haplotypes have been identified. Three are named for the regions in Africa where the mutations first appeared: BEN (Benin), SEN (Senegal), and CAR (Central African Republic). The fourth haplotype, Arabic-India, occurs in India and the Arabic peninsula ( Quinn and Miller, 2004 ).

Disease severity is associated with several genetic factors ( Ashley-Koch et al., 2000 ). The highest degree of severity is associated with Hb SS, followed by Hb s/β0-thalassemia, and Hb SC. Hb S/β + -thalassemia is associated with a more benign course of the disease ( Ashley-Koch et al., 2000 ). Disease severity also is related to β-globin haplotypes, probably due to variations in hemoglobin level and fetal hemoglobin concentrations. The Senegal haplotype is the most benign form, followed by the Benin, and the Central African Republic haplotype is the most severe form ( Ashley-Koch et al., 2000 ).

Thus, although sickle cell disease is a monogenetic disorder, its phenotypic expression is multigenic (see Appendix D ). There are two cardinal pathophysiologic features of sickle cell disease—chronic hemolytic anemia and vasoocclusion. Two primary consequences of hypoxia secondary to vasoocclusive crisis are pain and damage to organ systems. The organs at greatest risk are those in which blood flow is slow, such as the spleen and bone marrow, or those that have a limited terminal arterial blood supply, including the eye, the head of the femur and the humerus, and the lung as the recipient of deoxygenated sickle cells that escape the spleen or bone marrow. Major clinical manifestations of sickle cell disease include painful events, acute chest syndrome, splenic dysfunction, and cerebrovascular accidents.

Efforts to enhance clinical care are focusing on increasing our understanding of the pathophysiology of sickle cell disease in order to facilitate a precise prognosis and individualized treatment. Required is knowledge about which genes are associated with the hemolytic and vascular complications of sickle cell disease and how variants of these genes interact among themselves and with their environment ( Steinberg, 2005 ).

ASPECTS OF HEALTH INFLUENCED BY GENETICS

Because every cell in the body, with rare exception, carries an entire genome full of variation as the template for the development of its protein machinery, it can be argued that genetic variation impacts all cellular, biochemical, physiological, and morphological aspects of a human being. How that genetic variation is associated with particular disease risk is the focus of much current research. For common diseases such as CVD, hypertension, cancer, diabetes, and many mental illnesses, there is a growing appreciation that different genes and different genetic variations can be involved in different aspects of their natural history. For example, there are likely to be genes whose variations are associated with a predisposition toward the initiation of disease and other genes or gene variations that are involved in the progression of a disease to a clinically defined endpoint. Furthermore, an entirely different set of genes may be involved in how an individual responds to pharmaceutical treatments for that disease. There also are likely to be genes whose variability controls how much or how little a person is likely to be responsive to the environmental risk factors that are associated with disease risk. Finally, there are thought to be genes that affect a person’s overall longevity that may counteract or interact with genes that may otherwise predispose that person to a particular disease outcome and thus may have an additional impact on survivorship.

In many ways, we are only at the beginning the process of developing a true understanding of how genomic variations give rise to disease susceptibility. Indeed many would argue that, without incorporating the equally important role of the environment, we will never fully understand the role of genetics in health. As progress is made through utilizing the new technologies for measuring biological variation in the genome, transcriptome, proteome, and metabonome, we are likely to have to make large shifts in our conceptual frameworks about the roles of genes in disease. Global patterns of genomic susceptibility are likely to emerge only when we consider the influence of the many interacting components working simultaneously that are dependent on contexts such as age, sex, diet, and physical activity that modify the relationship with risk. For the most part, we are still at the stage of documenting the complexity, finding examples and types of genetic susceptibility genes, understanding disease heterogeneity, and postulating ways to develop models of risk that use the totality of what we know about human biology, from our genomes to our ecologies to model risk.

Cardiovascular Disease (CVD)

The study of CVD can be used to illustrate the issues that are encountered in using genetic information in order to understand the etiology of the most common chronic diseases as well as in identifying those at highest risk of developing these diseases. The majority of CVD cases have a complex multifactorial etiology, and even full knowledge of an individual’s genetic makeup cannot predict with certainty the onset, progression, or severity of disease ( Sing et al., 2003 ). Disease develops as a consequence of interactions between a person’s genotype and exposures to environmental agents, which influence cardiovascular phenotypes beginning at conception and continuing throughout adulthood. CVD research has found many high-risk environmental agents and hundreds of genes, each with many variations that are thought to influence disease risk. As the number of interacting agents involved increases, a smaller number of cases of disease will be found to have the same etiology and be associated with a particular genotype ( Sing et al., 2003 ). The many feedback mechanisms and interactions of agents from the genome through intermediate biochemical and physiological subsystems with exposure to environmental agents contribute to the emergence of a given individual’s clinical phenotype. In attempting to sort out the relative contributions of genes and environment to CVD, a large array of factors must be considered, from the influence of genes on cholesterol (e.g., LDL levels) to psychosocial factors such as stress and anger. Although hundreds of genes have been implicated in the initiation, progression, and clinical manifestation of CVD, relatively little is known about how a person’s environment interacts with these genes to tip the balance between the atherogenic and anti-atherogenic processes that result in clinically manifested CVD. Please see Chapters 4 and 6 for further discussion of effects of social environment on CVD.

It is well known that many social and behavioral factors ranging from socioeconomic status, job stress, and depression, to smoking, exercise, and diet affect cardiovascular disease risk (see Chapters 2 , 3 , and 6 for more detailed discussion of these factors). As more studies of gene-environment interaction consider these factors as part of the “environment,” which are examined in conjunction with genetic variations, multiple intellectual and methodological challenges arise. First, how are the social factors embodied such that an interaction with a particular genotype can be associated with differential risk? Second, how can we handle complex interactions to address questions, such as how does an individual’s genotype influence his/her behavior? For example, one’s genetic susceptibility to nicotine addiction is actually a risk factor for CVD and its effect on CVD risk may be contingent on interactions with other genetic factors.

Pharmacogenetics

It has been well established that individuals often respond differently to the same drug therapy. The drug disposition process is a complex set of physiological reactions that begin immediately upon administration. The drug is absorbed and distributed to the targeted areas of the body where it interacts with cellular components, such as receptors and enzymes, that further metabolize the drug, and ultimately the drug is excreted from the body ( Weinshilboum, 2003 ). At any point during this process, genetic variation may alter the therapeutic response of an individual and cause an adverse drug reaction (ADR) ( Evans and McLeod, 2003 ). It has been estimated that 20 to 95 percent of variations in drug disposition, such as ADRs, can be attributed to genetic variation ( Kalow et al., 1998 ; Evans and McLeod, 2003 ).

Sensitivity to both dose-dependent and dose-independent ADRs can have roots in genetic variation. Polymorphisms in kinetic and dynamic factors, such as cytochrome P450 and specific drug targets can cause these individuals susceptibilities to ADRs. While the characteristics of the ADR dictate the true significance of these factors, in most cases, multiple genes are involved ( Pirmohamed and Park, 2001 ). Future analyses using genome-wide SNP profiling could provide a technique for assessing several genetic susceptibility factors for ADRs and ascertaining their joint effects. One of the challenges to the study of the relationship between genetic variation and ADRs is an inadequate number of patient samples. To remedy this problem, Pirmohamed and Park (2001) have proposed that prospective randomized controlled clinical trials become a part of standardized practice to ultimately prove the clinical utility of genotyping all patients as a measure to prevent ADRs.

Here we review some of the current work in pharmacogenetics as an example of what might be expected to arise from rigorous study of the interaction between social, behavioral, and genetic factors. Researchers have provided a few well-established examples of differences in individual drug response that have been ascribed to genetic variations in a variety of cellular drug disposition machinery, such as drug transporters or enzymes responsible for drug metabolism ( Evans and McLeod, 2003 ). For example:

With the knowledge that the HER2 gene is overexpressed in approximately one fourth of breast cancer cases, researchers developed a humanized monoclonal antibody against the HER2 receptor in hopes of inhibiting the tumor growth associated with the receptor. Genotyping advanced breast cancer patients to identify those with tumors that overexpress the HER2 receptor has produced promising results in improving the clinical outcomes for these breast cancer patients ( Cobleigh et al., 1999 ).
A therapeutic class of drugs called thiopurines is used as part of the treatment regimen for childhood acute lymphoblastic leukemia. One in 300 Caucasians has a genetic variation that results in low or nonexistent levels of thiopurine methyltransferase (TPMT), an enzyme that is responsible for the metabolism of the thiopurine drugs. If patients with this genetic variation are given thiopurines, the drug accumulates to toxic levels in their body causing life-threatening myelosuppression. Assessing the TPMT phenotype and genotype of the patient can be used to determine the individualized dosage of the drug ( Armstrong et al., 2004 ).
The family of liver enzymes called cytochrome P450s plays a major role in the metabolism of as many as 40 different types of drugs. Genetic variants in these enzymes may diminish their ability to effectively break down certain drugs, thus creating the potential for overdose in patients with less active or inactive forms of the cytochrome P450 enzyme. Varying levels of reduced cytochrome P450 activity is also a concern for patients taking multiple drugs that may interact if they are not properly metabolized by well-functioning enzymes. Strategies to evaluate the activity level of cytochrome P450 enzymes have been devised and are valuable in planning and monitoring successful drug therapy. Some pharmaceutical drug trials are now incorporating early tests that evaluate the ability of differing forms of cytochrome P450 to metabolize the new drug compound ( Obach et al., 2006 ).

Some pharmacogenetics research has focused on the treatment of psychiatric disorders. With the introduction of a class of drugs known as selective serotonin re-uptake inhibitors (SSRIs), pharmacological treatment of many psychiatric disorders changed drastically. SSRIs offer significant improvements over the previous generation of treatments, including improved efficacy and tolerance for many patients. However, not all patients respond positively to SSRI treatment and many experience ADRs. New pharmacogenetic studies have indicated that these ADRs may be the result of genetic variations in serotonin transporter genes and cytochrome P450 genes. Further study and replication of these findings are necessary. If the characterization of the genetic variations is completed and is fully understood it would be possible to screen and monitor patients using genotyping techniques to create individualized drug therapies similar to those discussed above ( Mancama and Kerwin, 2003 ).

A significant challenge to the development of individualized drug therapies is the often polygenic or multifactorial inherited component of drug responses. Isolating the polygenic determinants of the drug responses is a sizable task. A good understanding of the drug’s mechanism of action and metabolic and disposition pathways should be the basis of all investigations. This knowledge can aid in directing genome-wide searches for gene variations associated with drug effects and subsequent candidate-gene approaches of investigation. Additionally, proteomic and gene-expression profiling studies are also important ways to substantiate and understand the pathways by which the gene of interest operates to affect the individual’s response to the drug ( Evans and McLeod, 2003 ). It is not enough to show an association; characterization of the underlying biological mechanisms is an essential component of moving genetic findings into the area of risk reduction. Another key component of utilizing genetics to improve prevention and reduce disease is an understanding of the distribution of the genetic variations in the populations being served.

GENETICS OF POPULATONS AS RELATED TO HEALTH AND DISEASE

Human populations differ in their distribution of genetic variations. This is a consequence of their historical patterns of mutation, migration, reproduction, mating, selection, and genetic drift. Inherited mutations typically occur during gametogenesis within a single individual and then can be passed on to offspring for many generations. Whether that mutation goes on to become a prevalent polymorphism (i.e., a mutation with a population frequency of greater than 1 percent) is determined by both evolutionary forces and chance events. For example, it depends on whether the original child who inherited the mutation survives to adulthood and reproduces and whether that child’s children survive to reproduce, and so on. The number of children in a family also influences the prevalence of the mutation, and this is often tied to environmental factors that impact fertility and mating patterns that influence the speed with which a private mutation becomes a public polymorphism. There are well-known examples of what are called founder mutations in which this trajectory can be documented. For example, one particular district in what is Quebec (Canada) today was originally founded by only a few families from a particular French province. One of the founding fathers carried a 10kb deletion in his LDL receptor (LDL-R) gene that was passed down through the generations quickly and today is carried by 1 in 154 French Canadians in northeastern Quebec. This mutation is associated with familial hypercholesterolemia, and French Ca nadians have one of the highest prevalences of this disease in the world because of the small founding populations followed by population expansion ( Moorjani et al., 1989 ).

There are also a number of examples where mutations that arise in an individual become more prevalent because of the selective advantage they impart on their carriers. The best known example is the mutation associated with sickle cell anemia. The geographical pattern of this mutation strongly mirrors the geographical pattern of malarial infection. It has been molecularly demonstrated that individuals carrying the sickle cell mutation have a resistance to malarial infection. Because many of the selection pressures that may have given rise to the current distribution of mutations in particular populations are in our evolutionary past, it is difficult to assess how much variation within or among populations is due to these types of selection forces.

Another major force in determining the distribution of genetic variations within and among human populations is their migration and reproductive isolation. According to our best knowledge, one of the most important periods in human evolution occurred approximately 100,000 years ago, when some humans migrated to other continents from the African basin and established new communities with relative reproductive isolation. Genetic differences among people in different geographical areas have been associated with the concept of race for hundreds of years. Although race is still used as a label, the original concept of race as genetically distinct subspecies of humans has been rejected through modern genetic information. For numerous reasons, discussed in the section below, it is more appropriate to reconceptualize the old genetics of race into a more accurate genetics of ancestry.

In addition to distant evolutionary patterns of migration, more modern migration patterns also have had a profound effect on the genetics of populations. For example, the current population of the United States and much of North America is very diverse genetically as a consequence of the mixing of many people from many different countries and continents.

A central reason for studying the origins and nature of human genetic variation is that the similarities and differences in the type and frequencies of genetic variations within and among populations can have a profound impact on studies that attempt to understand the influence of genes on disease risk. For example, some genetic variations, such as the apolipoprotein E protein polymorphisms, are found in every population and have very similar genotype frequencies around the world ( Wu et al., 2002 ; Deniz Naranjo et al., 2004 ). The variation’s association with increased heart disease and Alzheimer’s disease could be and has been tested in many of the world’s populations. Other mutations such as the 10kb deletion in the LDL-R gene described above are more population-specific variations.

Furthermore, from a statistical point of view, the effect of a genetic variation on the continuum of risk found in any population is correlated with its frequency. For example, common genetic polymorphisms with frequencies near 50 percent cannot be associated with large phenotypic effects within a population because the genotype classes each represent a large fraction of the population and, since most risk is normally distributed, the average risk for a highly prevalent genotype class cannot deviate from the overall risk of the population to any large degree. This correlation between genotype frequency and effect does not mean that common variations cannot be significant in their effects. The statistical significance of an association between a genetic variant and a disease is a joint function of sample size and the size of the effect. In addition, genetic research among populations that differ in their genotype frequencies can differ in their inferences about which polymorphisms have significant effects even if the absolute phenotypic effect is the same. See Cheverud and Routman (1995) for a more formal statistical explanation of this phenomenon and its impact on assessing gene-gene interactions.

Another key consideration in understanding the relationship between genetic variations and measures of disease risk is the population differences in the correlations between genotype frequencies at different SNP locations. There are two common reasons why the frequency of an allele or genotype at a particular SNP could be correlated with the frequency of an allele or genotype for a different SNP. First, a phenomenon known as linkage disequilibrium creates correlations among SNPs as a consequence of the mutation’s history. When mutations arise, they occur on a particular genetic background, which creates a correlation with the other SNPs on the chromosome. Second, the mixing of populations known as admixture that occurs typically through migration means that SNPs with population-specific frequencies will be correlated in a larger mixed sample. In this case, population stratification is the cause of the correlation, and there has been much genetic epidemiological research on this phenomenon and how to control for it. Population stratification is thought to be a possible source of spurious genetic associations with disease (see Box 3-2 ).

Population Stratification (Confounding). When the risk of disease varies between two ethnic groups, any genetic or environmental factor that also varies between the groups will appear to be related to disease. This phenomenon is called “population (more...)

In large part, the twentieth century was dominated by studies of human health and disease that focused on identifying single genetic and environmental agents that could explain variation in disease susceptibility. This new century has been characterized by huge advances in our understanding of Mendelian disorders with severe clinical outcomes. However, the Men delian paradigm has failed to elucidate the genetic contribution to susceptibility to most common chronic diseases, which researchers know have a substantial genetic component because of their familial aggregation and studies that demonstrate significant heritabilities for these diseases. Likewise, environmental and social epidemiological studies have been wildly successful in illuminating the role of many environmental factors such as diet, exercise, and stress on disease risk. However, these environmental factors still do not, by themselves, fully explain the variance in the prevalence of several diseases in different populations. Researchers are only now beginning to study in earnest the potential interactions between the genetic and environmental factors that are likely to be contributing to a large fraction of disease in most populations. There is much that can be done to incorporate measures of social environment into genetic studies and to also incorporate genetic measures into social epidemiological studies.

Over the last two decades, progress in identifying specific genes and mutations that explain genetic susceptibility to common conditions has been relatively slow, for a variety of reasons. First, the diseases being studied tend to be complex in their etiology, meaning that different people in a population will develop disease for different genetic and/or environmental reasons. Any single genetic or environmental factor is expected to explain only a very small fraction of disease risk in a population. Moreover, these factors are expected to interact, and other biological processes (e.g., epigenetic modifications) are likely to be contributors to the complex puzzle of susceptibility. An accurate phenotypic definition of disease and its subtypes is crucial to identifying and understanding the complexities of disease-specific genetic and environmental causes.

Second, geneticists only recently have developed the knowledge base or methods needed to measure genetic variations and their metabolic consequences with sufficient ease and cost-effectiveness so that the large number of genes thought to be involved can be studied. With the completion of the Human Genome Project in 2003, many different scientific entities (e.g., the Environmental Genome Project and the International HapMap Consortium) have been working to identify the mutational spectra in human populations, and genetic epidemiologists are just now beginning to understand the extensive nature of common variations (>1 percent population frequency) within the human genome that could be affecting people’s risk of disease. The SNP data generated by these initiatives are now centrally located in a number of public databases, including the National Center for Biotechnology Information’s dbSNPs database, the National Cancer Institute’s CGAP Genetic Annotation Initiative SNP Database, and the Karolinska Institute Human Genic Bi-Allelic Sequences Database. At present, the largest dataset on human variation is being generated by the International HapMap Project, 4 which is genotyping millions of SNPs on 270 individuals from 4 geographically separated sites from around the world. The International HapMap Project has greatly increased the number of validated SNPs available to the research community to be used to study human variation and is producing a map of genomic haplotypes in four populations with ancestry from parts of Africa, Asia, and Europe. In addition, high-throughput methods of genotyping large numbers of SNPs (thousands) in large epidemiological cohorts are only now becoming available (see above). Unfortunately, high-throughput methods of measuring the environment have not kept a similar pace. For many studies of common disease, a rate-limiting step to increasing our understanding will continue to be the difficult and costly measurement of environmental factors.

Finally, progress also has been hampered because of a lack of adequate investment in developing new methods of analysis that can incorporate the high-dimensional biological reality that we can now measure. The complex genetic and environmental architecture of multifactorial diseases is not easily detected or deciphered using the traditional statistical modeling methods that are focused on the estimation of a single overall model of disease for a population. For example, using traditional logistic regression methods it would be simply impossible to enter all the hundreds of genetic variations that are thought to be involved in CVD risk or in any of the other common disease complexes currently being studied. Beyond the obvious issues of power and overdetermination in such a large-scale model, we also do not know how to model or interpret interactions among many factors simultaneously or how to incorporate the rare, large effects of some genes relative to the common, small effects of others. New modeling strategies that take advantage of advances in pattern recognition, machine learning, and systems analysis (e.g., scale-free networks, Bayesian belief networks, random forest methods) are going to be needed in order to build more comprehensive, predictive models of these etiologically heterogeneous diseases.

The field of human genetics, like many other disciplines, is in transition, and there is much to be gained by joining forces with a wide range of other disciplines that are focused on improving prevention and reducing the disease burden in our populations.

Altshuler D, Kruglyak L, Lander E. Genetic polymorphisms and disease. New England Journal of Medicine. 1998; 338 (22):1626. [ PubMed : 9606122 ]
Ardlie KG, Lunetta KL, Seielstad M. Testing for population subdivision and association in four case-control studies. American Journal of Human Genetics. 2002; 71 (2):304–311. [ PMC free article : PMC379163 ] [ PubMed : 12096349 ]
Armstrong VW, Shipkova M, von Ahsen N, Oellerich M. Analytic aspects of monitoring therapy with thiopurine medications. Therapeutic Drug Monitoring. 2004; 26 (2):220–226. [ PubMed : 15228169 ]
Ashley-Koch A, Yang Q, Olney R. Sickle hemoglobin (Hb S) allele and sickle cell disease: A HuGE review. American Journal of Epidemiology. 2000; 151 (9):839–845. [ PubMed : 10791557 ]
Bridges K. Hemoglobinopathies (Hemoglobin Disorders). 2002. [accessed May 15, 2006]. [Online]. Available: sickle .bwh.harvard.edu/hemoglobinopathy .html .
Brown MS, Goldstein JL. Lowering plasma cholesterol by raising LDL receptors. New England Journal of Medicine. 1981; 305 (9):515–517. [ PubMed : 6265781 ]
Cardon LR, Bell JI. Association study designs for complex diseases. Nature Reviews Genetics. 2001; 2 (2):91–99. [ PubMed : 11253062 ]
Cheverud JM, Routman EJ. Epistasis and its contribution to genetic variance components. Genetics. 1995; 139 (3):1455–1461. [ PMC free article : PMC1206471 ] [ PubMed : 7768453 ]
Clifford RJ, Edmonson MN, Nguyen C, Buetow KH. Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms. Bioinformatics. 2004; 20 (7):1006–1014. [ PubMed : 14751981 ]
Cobleigh MA, Vogel CL, Tripathy D, Robert NJ, Scholl S, Fehrenbacher L, Wolter JM, Paton V, Shak S, Lieberman G, Slamon DJ. Multinational study of the efficacy and safety of humanized anti-HER2 monoclonal antibody in women who have HER2-overexpressing metastatic breast cancer that has progressed after chemotherapy for metastatic disease. Journal of Clinical Oncology. 1999; 17 (9):2639–2648. [ PubMed : 10561337 ]
Deniz Naranjo MC, Munoz Fernandez C, Alemany Rodriguez MJ, Perez Vieitez MC, Irurita Latasa J, Suarez Armas R, Suarez Valentin MP, Sanchez Garcia F. Gender has a strong modulating effect on the risk of Alzheimer’s disease conferred by the apolipoprotein E gene in the population of the Canary Islands, Spain. Revista de Neurologia. 2004; 38 (7):615–618. [ PubMed : 15098180 ]
Evans WE, McLeod HL. Pharmacogenomics—drug disposition, drug targets, and side effects. New England Journal of Medicine. 2003; 348 (6):538–549. [ PubMed : 12571262 ]
Gunderson KL, Steemers FJ, Lee G, Mendoza LG, Chee MS. A genome-wide scalable SNP genotyping assay using microarray technology. Nature Genetics. 2005; 37 (5):549–554. [ PubMed : 15838508 ]
Haines JL, Pericak-Vance MA. Approaches to Gene Mapping in Complex Human Diseases. New York: Wiley-Liss; 1998.
Hall JM, Lee MK, Newman B, Morrow JE, Anderson LA, Huey B, King MC. Linkage of early-onset familial breast cancer to chromosome 17q21. Science. 1990; 250 (4988):1684–1689. [ PubMed : 2270482 ]
Hinds DA, Stuve LL, Nilsen GB, Halperin E, Eskin E, Ballinger DG, Frazer KA, Cox DR. Whole-genome patterns of common DNA variation in three human populations. Science. 2005; 307 (5712):1072–1079. [ PubMed : 15718463 ]
IOM (Institute of Medicine). Implications of Genomics for Public Health. Washington, DC: The National Academies Press; 2005. [ PubMed : 22379649 ]
Kalow W, Tang BK, Endrenyi L. Hypothesis: Comparisons of inter- and intra-individual variations can substitute for twin studies in drug research. Pharmacogenetics. 1998; 8 (4):283–289. [ PubMed : 9731714 ]
Kardia SL, Modell SM, Peyser PA. Family-centered approaches to understanding and preventing coronary heart disease. American Journal of Preventive Medicine. 2003; 24 (2):143–151. [ PubMed : 12568820 ]
Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, Henning AK, SanGiovanni JP, Mane SM, Mayne ST, Bracken MB, Ferris FL, Ott J, Barnstable C, Hoh J. Complement factor H polymorphism in age-related macular degeneration. Science. 2005; 308 (5720):385–389. [ PMC free article : PMC1512523 ] [ PubMed : 15761122 ]
Lander ES, Schork NJ. Genetic dissection of complex traits. Science. 1994; 265 (5181):2037–2048. [ PubMed : 8091226 ]
Livingston RJ, von Niederhausern A, Jegga AG, Crawford DC, Carlson CS, Rieder MJ, Gowrisankar S, Aronow BJ, Weiss RB, Nickerson DA. Pattern of sequence variation across 213 environmental response genes. Genome Research. 2004; 14 (10A):1821–1831. [ PMC free article : PMC524406 ] [ PubMed : 15364900 ]
Mancama D, Kerwin RW. Role of pharmacogenomics in individualising treatment with SSRIs. CNS Drugs. 2003; 17 (3):143–151. [ PubMed : 12617694 ]
Mathew C. Science medicine and the future—postgenomic technologies: Hunting the genes for common disorders. British Medical Journal. 2001; 322 (7293):1031–1034. [ PMC free article : PMC1120184 ] [ PubMed : 11325769 ]
McAdams HH, Arkin A. Stochastic mechanisms in gene expression. Proceedings of the National Academy of Sciences of the United States of America. 1997; 94 (3):814–819. [ PMC free article : PMC19596 ] [ PubMed : 9023339 ]
Miller DP, Liu G, De Vivo I, Lynch TJ, Wain JC, Su L, Christiani DC. Combinations of the variant genotypes of GSTP1, GSTM1, and p53 are associated with an increased lung cancer risk. Cancer Research. 2002; 62 (10):2819–2823. [ PubMed : 12019159 ]
Moorjani S, Roy M, Gagne C, Davignon J, Brun D, Toussaint M, Lambert M, Campeau L, Blaichman S, Lupien P. Homozygous familial hypercholesterolemia among French Canadians in Quebec Province. Arteriosclerosis. 1989; 9 (2):211–216. [ PubMed : 2923577 ]
Obach RS, Walsky RL, Venkatakrishnan K, Gaman EA, Houston JB, Tremaine LM. The utility of in vitro cytochrome P450 inhibition data in the prediction of drug-drug interactions. Journal of Pharmacology and Experimental Therapeutics. 2006; 316 (1):336–348. [ PubMed : 16192315 ]
Pirmohamed M, Park BK. Genetic susceptibility to adverse drug reactions. Trends in Pharmacological Sciences. 2001; 22 (6):298–305. [ PubMed : 11395158 ]
Pritchard JK, Rosenberg NA. Use of unlinked genetic markers to detect population stratification in association studies. American Journal of Human Genetics. 1999; 65 (1):220–228. [ PMC free article : PMC1378093 ] [ PubMed : 10364535 ]
Quinn CT, Miller ST. Risk factors and prediction of outcomes in children and adolescents who have sickle cell anemia. Hematology/Oncology Clinics of North America. 2004; 18 (6 SPEC.ISS):1339–1354. [ PubMed : 15511619 ]
Rebbeck TR, Walker AH, Phelan CM, Godwin AK, Buetow KH, Garber JE, Narod SA, Weber BL. Defining etiologic heterogeneity in breast cancer using genetic biomarkers. Progress in Clinical and Biological Research. 1997; 396 :53–61. [ PubMed : 9108589 ]
Rimoin DL, Connor JM, Pyeritz RE, Korf BR, editors. Emery and Rimoin’s Principles and Practice of Medical Genetics. 4th edition. Vol. 2. New York: Churchill Livingstone; 2002.
Risch NJ. Searching for genetic determinants in the new millennium. Nature. 2000; 405 (6788):847–856. [ PubMed : 10866211 ]
Satten GA, Flanders WD, Yang Q. Accounting for unmeasured population substructure in case-control studies of genetic association using a novel latent-class model. American Journal of Human Genetics. 2001; 68 (2):466–477. [ PMC free article : PMC1235279 ] [ PubMed : 11170894 ]
Sing CF, Stengard JH, Kardia SLR. Genes, environment, and cardiovascular disease. Arteriosclerosis, Thrombosis, and Vascular Biology. 2003; 23 :1190–1196. [ PubMed : 12730090 ]
Smith G. The Genomics Age: How DNA Technology Is Transforming the Way We Live and Who We Are. New York: AMACOM; 2005.
Steinberg MH. Predicting clinical severity in sickle cell anaemia. British Journal of Haematology. 2005; 129 (4):465–481. [ PubMed : 15877729 ]
Stuart MJ, Nagel RL. Sickle-cell disease. Lancet. 2004; 364 (9442):1343–1360. [ PubMed : 15474138 ]
Syvanen AC. Toward genome-wide SNP genotyping. Nature Genetics. 2005;(37 Suppl):S5–S10. [ PubMed : 15920530 ]
Thompson MW, McInnes RR, Willard, editors. Thompson & Thompson Genetics in Medicine. 5th edition. Philadelphia, PA: W.B. Saunders Company; 1991.
Wacholder S, Rothman N, Caporaso N. Population stratification in epidemiologic studies of common genetic variants and cancer: Quantification of bias. Journal of the National Cancer Institute. 2000; 92 (14):1151–1158. [ PubMed : 10904088 ]
Wang X, Tomso DJ, Liu X, Bell DA. Single nucleotide polymorphism in transcriptional regulatory regions and expression of environmentally responsive genes. Toxicology and Applied Pharmacology. 2005; 207 (2 Suppl):84–90. [ PubMed : 16002116 ]
Wang Z, Fan H, Yang HH, Hu Y, Buetow KH, Lee MP. Comparative sequence analysis of imprinted genes between human and mouse to reveal imprinting signatures. Genomics. 2004; 83 (3):395–401. [ PubMed : 14962665 ]
Weinshilboum R. Inheritance and drug response. New England Journal of Medicine. 2003; 348 (6):529–537. [ PubMed : 12571261 ]
Wu JH, Lo SK, Wen MS, Kao JT. Characterization of apolipoprotein E genetic variations in Taiwanese association with coronary heart disease and plasma lipid levels. Human Biology. 2002; 74 (1):25–31. [ PubMed : 11931577 ]
Zhou W, Liu G, Miller DP, Thurston SW, Xu LL, Wain JC, Lynch TJ, Su L, Christiani DC. Polymorphisms in the DNA repair genes XRCC1 and ERCC2, smoking, and lung cancer risk. Cancer Epidemiology, Biomarkers and Prevention. 2003; 12 (4):359–365. [ PubMed : 12692111 ]

An SNP is the DNA sequence variation that occurs when a single nucleotide (A, T, C, or G) in the genome sequence is altered ( Smith, 2005 ).

A candidate gene is a gene whose protein product is involved in the metabolic or physiological pathways associated with a particular disease ( IOM, 2005 ).

The sickle cell example is abstracted from a commissioned paper prepared by Robert J. Thompson, Jr., Ph.D. ( Appendix D ).

See www .hapmap.org .

Cite this Page Institute of Medicine (US) Committee on Assessing Interactions Among Social, Behavioral, and Genetic Factors in Health; Hernandez LM, Blazer DG, editors. Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate. Washington (DC): National Academies Press (US); 2006. 3, Genetics and Health.
PDF version of this title (2.1M)

In this Page

Other titles in this collection.

The National Academies Collection: Reports funded by National Institutes of Health

Related information

PMC PubMed Central citations
PubMed Links to PubMed

Recent Activity

Genetics and Health - Genes, Behavior, and the Social Environment Genetics and Health - Genes, Behavior, and the Social Environment

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

IMAGES

Graphical illustration of Knudson's two-hit hypothesis and exceptions
PPT
genes1-concept-s
The gatekeeper hypothesis. The figure shows a Venn diagram of the genes
2: The split gene hypothesis. (A) Gene structure and the flow of
Gene for-gene hypothesis & its validty in the present scenario

VIDEO

The Good Genes Hypothesis
Concept of Hypothesis
Proportion Hypothesis Testing, example 2
What Is A Hypothesis?
Hypothesises About Cancer
PRACTICAL RESEARCH 2

COMMENTS

Genetics and Statistical Analysis
In your experiment, there are two expected outcome phenotypes (tall and short), so n = 2 categories, and the degrees of freedom equal 2 - 1 = 1. Thus, with your calculated chi-square value (0.33 ...
One gene, one enzyme
The one gene, one enzyme hypothesis is the idea that each gene encodes a single enzyme. Today, we know that this idea is generally (but not exactly) correct. Sir Archibald Garrod, a British medical doctor, was the first to suggest that genes were connected to enzymes. Beadle and Tatum confirmed Garrod's hypothesis using genetic and biochemical ...
1.5: The Function of Genes
B&T's 1 gene: 1 enzyme hypothesis led to Biochemical Pathway dissection using genetic screens and mutations. Beadle and Tatum's experiments are important not only for its conceptual advances in understanding genes, but also because they demonstrate the utility of screening for genetic mutants to investigate a biological process - genetic analysis.
A current guide to candidate gene association studies
CGAS is the usual approach for rare variants. It involves resequencing of hypothesis-driven rationally selected candidate genes in carefully defined phenotypic groups of cases and controls. In simplified terms, WGASs can be viewed as hypothesis-generating and CGASs as hypothesis-testing approaches.
Eighty years of gene-for-gene relationship and its applications in
Gene-for-gene hypothesis helped in identification of several R genes in host and their corresponding Avr genes in the pathogen. Further, cloning of plant R genes and understanding their mechanism has played a great role in understanding these R-Avr gene interactions (Van der Hoorn and Kamoun 2008).
The Gene Balance Hypothesis: From Classical Genetics to Modern Genomics
A hypothesis was formulated that the stoichiometry of regulatory genes was influential in modulating the levels of expression of the target genes studied (Birchler and Newton, 1981). The failure to find a dosage effect for ADH was referred to as dosage compensation.
Hypothesis-driven science in large-scale studies: the case of GWAS
However, there is at present no evidence that the 'core gene' hypothesis need invariably be true for complex diseases (cf. Wray et al. ), so one might be inclined to reject the original hypothesis that all diseases must fit the mould of 'small number of genes cause complex diseases'. In so doing, one would thereby need to embrace the ...
The Evolving Definition of the Term "Gene"
Gene fusion, at the level of transcripts, is a reality, and is completely at odds with the "one gene—one mRNA—one protein" hypothesis. And this is not a rare phenomenon. It has been estimated that at least 4-5% of the tandem gene pairs in the human genome can be transcribed into a single RNA sequence, called chimeric transcripts ...
Hypotheses and facts for genetic factors related to severe COVID-19
Dementia, cardiovascular disease, and type 2 diabetes were identified as major risk factors for severe COVID-19 in older individuals in the United Kingdom [ 84 - 86 ]. The APOE gene, with its three major isoforms APOE2, APOE3, and APOE4, is encoded by ε2, ε3, and ε4 alleles.
Gene-for-Gene Relationship
Gene-for-gene relationships have been proposed by some authors for virus-host interactions (e.g. Fraser, 1987a). A well-studied example of the gene-for-gene hypothesis applied to a plant virus and its host is the resistance of tomato to ToMV (Table 10.3). There are three resistance genes: Tm-1, Tm-2 and Tm-2 2. The virus has evolved variants ...
6.1: One Gene
The One Gene - One Enzyme Theory. Sucrose, a few salts, and one vitamin — biotin — provide the nutrients that Neurospora needs to synthesize all the macromolecules of its cells. Figure 6.1.1 Beadle - Tatum Experiment on Neurospora. Geneticists George W. Beadle and E. L. Tatum exposed some of the conidia of one mating type of Neurospora to ...
The Good Genes Hypothesis
The good genes hypothesis (GGH) was formulated by evolutionary biologist W.D. Hamilton and behavioral ecologist M. Zuk ().It proposes that the characteristics preferred by females are a signal of males' ability to pass on genes (coding that certain characteristic) which will increase the survival and reproductive success of the offspring sired with a male possessing them.
The evolution of genomic imprinting: theories, predictions and ...
If imprinted genes should prove to be highly expressed, then they may share certain structural properties with other highly expressed genes, such as amino acid bias, codon bias and few, small ...
Good genes hypothesis
good genes hypothesis, in biology, an explanation which suggests that the traits females choose when selecting a mate are honest indicators of the male's ability to pass on genes that will increase the survival or reproductive success of her offspring. Although no completely unambiguous examples are known, evidence supporting the good genes hypothesis is accumulating, primarily through the ...
Gene-for-gene relationship
The gene-for-gene relationship is a concept in plant pathology that plants and their diseases each have single genes that interact with each other during an infection. ... Several experiments support this hypothesis, e.g. the Rpm1 gene in Arabidopsis thaliana is able to respond to two completely unrelated avirulence factors from Pseudomonas ...
Gene-for-gene hypothesis
gene-for-gene hypothesis. The proposal that during their evolution a host and its parasite develop complementary genetic systems, with each gene that provides the host with resistance matched by a gene in the parasite that confers susceptibility. The interacting genes from the two species are called corresponding genes, since for each gene that ...
Genomic imprinting: theories and data
The most prominent rationale for the evolution of imprinting is Haig and colleagues' genetic conflict or kinship hypothesis (Haig and Graham, 1991; Moore and Haig, 1991), which argues that imprinting is the result of a conflict of interest between paternally and maternally derived genes.
Retinoblastoma: present scenario and future challenges
Retinoblastoma gene is best known as the tumour suppressor that inspired the 'two-hit' hypothesis. The idea that the loss of both the alleles of a tumour suppressor gene is a pre-requisite for tumour initiation occurred to Knudson in the 1970s.
Epidemiological and Evolutionary Outcomes in Gene-for-Gene and Matching
The Gene-for-Gene Hypothesis. Qualitative resistance lies at the heart of the GFG system elucidated by Flor in a series of elegant experiments involving the rust pathogen Melampsora lini and its host plant Linum usitatissimum (Flor, 1946, 1947, 1955).
The evolution of imprinting in plants: beyond the seed
Likewise, the hypothesis that individual imprinted genes have arisen under weak or relaxed selection (Berger et al. 2012; Rodrigues and Zilberman 2015) relies on the pre-existence of imprinting mechanisms that inadvertently act on these genes. This idea does not address the origin of imprinting and will also not be discussed here.
Effects of paternal arachidonic acid supplementation on offspring
Arachidonic acid (AA) is involved in inflammation and plays a role in growth and brain development in infants. We previously showed that exposure of mouse sires to AA for three consecutive generations induces a cumulative change in fatty acid (FA) involved in inflammation and an increase in body and liver weight in the offspring. Here, we tested the hypothesis that paternal AA exposure changes ...
Hypothesis-free phenotype prediction within a genetics-first ...
c Novel variant in related gene. Chr12 Pos52913668, KRT5-G138E. d Single variant. Chr17 Pos29586054, NF1-L1425R. e Single variant. Chr19 Pos17927755, INSL3-R102C. f Novel variant in known gene ...
Genetics and Health
It is a broad population-based measure of genetic influence that is used to determine whether further genetic studies are warranted, since it allows investigators to test the overarching null hypothesis that no genes are involved in determining disease risk. Twin studies and family studies are frequently used in the study of heritability.
Does the host drive Wolbachia gene expression?
The first published RNA-Seq study on Wolbachia showed the differential expression of a DNA methyltransferase, an enzyme able to methylate adenine or cytosine on specific patterns and often involved in the regulation of bacteria gene expression. In this work, we tested the hypothesis that DNA methylation can affect gene expression in Wolbachia.
Genes associated with depression and coronary artery disease are
Importantly, this hypothesis was motivated by genetic findings suggesting that the genes associated with both depression and CAD are enriched for pathways with a known role in immune and ...

Biology library

One gene, one enzyme

Key points:

Introduction

Pinpointing the broken pathway

"One gene-one enzyme" today

Works cited:

Additional references:

6.1: One Gene - One Enzyme Theory

Neurospora crassa

The One Gene - One Enzyme Theory

Contributors and Attributions

Recently viewed (0)

Related Content

More Like This

gene-for-gene hypothesis

Related content in Oxford Reference

Retinoblastoma: present scenario and future challenges

Introduction

Classification of retinoblastoma (WHO classification)

Epidemiology

Screening and diagnosis of retinoblastoma

Treatment and management of the disease

Enucleation

Intra-arterial (IAC) chemotherapy

Intravitreal chemotherapy (IVitC)

Thermotherapy

Cryotherapy

External beam radiation (EBR)

Retinoblastoma: the genetics behind the disease

The broad spectrum of mutations with respect to retinoblastoma

Signalling pathways involved in Retinoblastoma

p53 pathway

Wnt signalling

Ras/MEK/ERK pathway

Notch pathway

Conclusion and future perspective

Availability of data and materials

Acknowledgements

Author information

Contributions

Corresponding authors

Ethics declarations

Competing interests

Additional information

Rights and permissions

About this article

Share this article

Cell Communication and Signaling

The evolution of imprinting in plants: beyond the seed

Cite this article

Similar content being viewed by others

Identification and Comparison of Imprinted Genes Across Plant Species

Conserved imprinting associated with unique epigenetic signatures in the Arabidopsis genus

DNA Demethylation and Gene Imprinting in Flowering Plants

Introduction

Imprinting in land plants: a spotlight on angiosperms

Getting to the origins of imprinting and endosperm: ANA-grade angiosperms

Imprinting without seeds: observations from the past

Imprinting in bryophytes: whispers on the wind

Predictions of imprinting: gazing into the crystal ball

Parental conflict and differential dosage hypotheses

Coadaptation hypothesis

Perspectives

Author contribution statement

Acknowledgements

Author information

Corresponding author

Ethics declarations

Additional information

Publisher's Note

Rights and permissions

About this article

Share this article

Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate.

3 Genetics and Health

Genetic Linkage Analysis

Genetic Association Studies

An Example of a Single-Gene Disorder with Significant Clinical Variability: Sickle Cell Disease 3

Cardiovascular Disease (CVD)