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Importance of Water in Animal Life

Why Is Water Important for Living Organisms?

Animal life requires a steady supply of water to fulfill its vital functions. From transportation to lubrication to temperature regulation, water keeps animal life functioning; in fact, the bodies of animals consist mostly of water. All chemical reactions in the bodies of animals use water as a medium.

Temperature Regulation

Animals' body temperature should remain in a narrow, specific range. Water acts as a buffer against overheating due to water's high specific heat. Specific heat determines how much heat an object can absorb without increasing its own temperature. Water has a high specific heat because its hydrogen-oxygen bonds dissolve only when exposed to intense heat. Heated water seeps out through pores in the form of sweat and must be replenished to avoid dehydration.

pH Regulation

The acidity or basicity of compounds in the body, or pH, determines whether acids or alkalines take prominence. Acids and bases have an electrical charge and therefore seek the opposite material to form a chemical bond and neutralize their net charge. For example, bone matter consists of calcium and at least 18 other critical compounds. In the absence of alkalines, excess acid will draw minerals from these sources. Water, when introduced into an animal's system, will bring its pH closer to a neutral value and lessen the chance of unhealthy chemical reactions.

Hydrolysis and Energy Production

Hydrolysis causes the breakdown of ATP, the molecule that forms when sugar metabolizes in the digestive tract and transfers to all cells. The introduction of water--two hydrogen atoms and one oxygen atom--to a molecule of ATP, or adenosine triphosphate, pulls one phosphate atom away from the molecule, forming adenosine diphosphate. The breaking of this bond releases energy that powers the body.

Water forms the majority of the mucus lining that protects animal stomachs from the corrosive action of acid. Water passes directly into the intestine and the stomach without the need for digestion. It activates the sodium bicarbonate layer in the mucous membrane of the stomach, protecting it against hydrochloric acid. In addition, saliva, the fluid used to break down food in the mouth, consists mostly of water.

Joint Lubrication

In any animal skeleton, a protective layer of cartilage rests between bones to provide lubrication and prevent wear on the ends of the bone. Articular cartilage, the cartilage that exists in joints, consists of mostly water as well as a matrix of collagens and non-collagenous proteins. Without adequate water, cartilage wears down and restricts the range of motion in a joint.

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Water and Life
Campbell Biology: Water and Life

About the Author

Michael Smathers studies history at the University of West Georgia. He has written freelance online for three years, and has been a Demand Studios writer since April 2009. Michael has written content on health, fitness, the physical sciences and martial arts. He has also written product reviews and help articles for video games on BrightHub, and martial arts-related articles on Associated Content.

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Ocean Habitat

From outer space Earth looks like an awesome blue marble. That’s because most of Earth’s surface—more than 70 percent—is covered by oceans.

Earth Underwater

Oceans are areas of salty water that fill enormous basins on the Earth’s surface. Even though Earth has one continuous body of saltwater, scientists and geographers divide it into five different sections. From biggest to smallest, they are the Pacific, the Atlantic, the Indian, the Southern, and the Arctic Oceans.

Oceans are deep as well as wide. On average an ocean is a little over two miles deep. But about 200 miles southwest of Guam in the Pacific Ocean, the water in the Mariana Trench is almost seven miles deep. That’s the deepest part of the ocean.

Climate Control

Oceans help keep Earth’s climate habitable. By moving water around the globe, the oceans help to keep places from getting too hot or too cold.

Oceans also help keep the planet warm. In the same way that hot water in a bathtub stays warm longer than hot chocolate in a small cup, the vast amount of warm water stores heat in the ocean. Then ocean currents carry that heat around the planet. Without oceans, the Earth would be an icy rock.

Ocean or Sea?

The words “ocean” and “sea” are often used to mean the same thing. A sea, however, is a small area of an ocean, usually with land on several sides. The Mediterranean, nestled between Africa and Europe, the Baltic in northern and central Europe, and the Caribbean between North, Central, and South America are all seas.

Scientists think that up to 91 percent of marine species have not yet been identified; but there could be as many as 700,000 of them! Most—95 percent—are invertebrates , animals that don’t have a backbone, such as jellyfish and shrimp. The most common vertebrate (an animal with a backbone) on Earth is the bristlemouth, a tiny ocean fish that glows in the dark and has needlelike fangs.

Some of the smallest animals on Earth can be found in the ocean. Sea animals like zooplankton are so small you can see them only with a microscope. Big fish swim through these waters too, such as great white sharks , manta rays, and ocean sunfish .

The largest animal ever to live on Earth is an ocean mammal called the blue whale . It’s as long as two school buses! Dolphins , porpoises, and sea lions are also ocean-dwelling mammals.

The ocean teems with plant life. Most are tiny algae called phytoplankton—and these microscopic plants have a big job. Through photosynthesis, they produce about half of the oxygen that humans and other land-dwelling creatures breathe. Bigger algae like seaweed and kelp also grow in the ocean and provide food and shelter for marine animals.

Watery Habitats

Temperature, ocean depth, and distance from the shore determine the types of plants and animals living in an area of the ocean. These regions are called habitats.

Coral reefs are one type of habitat. When tiny animals called polyps die, their skeletons harden so other polyps can live on top of them. Then those polyps die, and more move in. After thousands of years, this becomes a complex structure called a coral reef that provides food and shelter for many kinds of ocean animals. In fact, corals reefs have been called the rainforests of the sea because of the wide variety of animals found there. Animals such as seahorses , clownfish , and sea turtles all live on coral reefs. And corals themselves are animals! They grab food from the water using tiny tentacle-like arms.

Kelp forests found along the coastlines of the Pacific and Antarctic Oceans also provide food and shelter for marine life. These large, brown, rubbery plants have hollow, globe-shaped growths on the leaves called pneumatocysts that help the plants rise to the surface. Sea lions, whales, shore birds, and other ocean animals make meals of the smaller critters that hide in the leaves.

Other ocean habitats aren’t actually in the ocean, such as estuaries. Estuaries are areas where rivers and oceans meet and have a mix of saltwater and freshwater. Oysters, crabs, and many birds like great herons and egrets live in estuaries.

Scientists estimate that we’ve only explored 5 percent of the ocean. Maybe you’ll be the next person to discover a new species of fish or a deeper underwater trench!

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Importance of water

An English Essay on the Importance of Water for the Students

Without water there cannot be life on our planet, that is to say on earth. Because every living organism needs water, and therefore having a good understanding and care for the water is a must for all of us. Hence, students should write an essay discussing the importance of water in the English language.

Writing an essay on such a topic opens a series of good ideas in the mind of the students regarding the role that water plays in our lives, and it can also make the students aware of the importance of water.

Also, if you wish to write an English essay on the topic My aim in life you may find this link helpful My Aim in Life Essay in English for Students | Easy Essay on My Aim in Life (vedantu.com)

Advantages of Writing an Essay on the Importance of Water.

Writing an essay on any topic helps the students be good writers, and the same goes for the topic of, Importance of water, but there are quite a few more advantages to writing the essay.

One of the most important things for everyone is to express oneself, and the practice of doing so must be given to the child from a very young age. And writing an essay helps the students in this very important thing.

For writing a good essay on any topic, the students must have a good understanding of the subject of the essay. And hence, writing an essay on the Importance of water, helps the students in learning about the value of water, not just our lives, which is to say humans, but the life of the whole planet.

In his famous play Hamlet Shakespeare writes, Brevity is the soul of wit, meaning being short or concise is very important in speech, or shortness of words is the essence of intelligence. The same rule applies in writing the essay, and doing as clear an understanding of the topic at hand is required as possible. And hence composing an essay on the importance of water helps the students understand the same.

One of the most important gifts that humans are blessed with is the gift of language, and this gift has to be used effectively. Writing an essay helps the students in learning the methods of using the language in such a manner that it makes everything clear to the reader. A good essay does not only touch the heart of the readers but it opens the mind of the reader, it can move them, that is to say, if a good essay is written on the importance of water it can make the readers aware about the same, and not just aware but also careful about using the water.

Water means Life. Water is a prime natural resource. It is a basic need for humans and a precious asset that living beings have. Water is equally vital for the survival of the plant and animal kingdoms. Soil needs water for sustaining plants. The water cycle is essential for ecological balance too. Though a big portion of the Earth is covered with water, only a small portion of it can be used for various human activities. So we need to be judicious and rational, regarding the usage of water.

Why is water important for our bodies?

Water is important for our body for the following reasons.

Above 70% of our body contains water so it is pivotal for the human race to survive.

Water helps in regulating our body temperature.

Water helps in the digestion of solid food.

It also keeps our skin healthy and hydrated.

Water helps in excreting waste from our body through sweat, urination, and defecation. So replenishing the water in our body is essential to prevent dehydration.

Drinking water also helps in reducing calories and maintaining body weight because it can increase the rate of metabolism.

Water consumption lubricates the joints, spinal cord, and tissues.

Importance of Water

All living organisms, plants, animals, and human beings contain water. Almost 70% of our body is made up of water. Our body gets water from the liquids we drink and the food we eat. Nobody can survive without water for more than a week. All plants will die if they do not get water. This would lead to the death of all the animals that depend on plants for their food. So the existence of life would come to an end.

Role of Water In Life Processes

Water plays an important role in most of the life processes by acting as a solvent. The absorption of food in our body takes place in solution form with water as the solvent. Also, many waste products are excreted in the form of solutions through urine and perspiration.

Water helps in regulating our body temperature. In hot weather, we drink a lot of water. This maintains our body temperature. Also, water evaporates from the surface of our body as sweat. This takes away heat and cools the body.

Water is essential for plants to grow. Plants need water to prepare food. They also absorb dissolved nutrients from the soil through their roots.

Aquatic plants and animals use the nutrients and oxygen dissolved in water for their survival.

Uses of Water In Everyday Life

Water is used for drinking, washing, cooking, bathing, cleaning, in our day-to-day life.

It is used to generate electricity in hydroelectric power stations.

Water is used for irrigating fields and in the manufacture of various products.

Other Uses of Water

Water serves as a means of transportation for goods and people.

It provides a medium for recreational sports such as swimming, boating, and water skiing.

Water is also used to extinguish fires.

Importance of Oceans

Oceans are of immense use to man. They are useful in many ways, directly and indirectly. They not only play a significant role in the climate of adjoining countries but also serve mankind in many ways. They are a storehouse of several resources.

An ocean is a major source of water and forms a major part of the water cycle. Oceans contribute water vapor to the atmosphere and we get the same in the form of precipitation.

The oceans are the biggest storehouse of edible forms of marine food, fish being most important. In addition to food, sea animals provide other products like oil, glue, etc.

Oceans have enormous mineral and chemical wealth. A variety of dissolved salts like sodium chloride (common salt), magnesium chloride, and potassium chloride are found in plenty in the oceans.

Oil and gas are important fuels obtained from oceans.

Importance of Lakes and Rivers

Economic and industrial development

Water storage

Hydroelectric power generation

Agricultural purposes

Modern multipurpose dams

Source of food

Source of minerals

Tourist attractions and health resorts

Rivers provide fresh drinking water

Ports can be built on them as they form good natural harbors

Major Concerns

Although our planet Earth is covered with 71% percent of water and 29% of the land, the fast-growing contamination of water is affecting both humans as well as marine life. The unequal distribution of water on the Earth and its increasing demand due to the increasing population is becoming a concern for all.

Water pollution makes it difficult for marine animals to sustain themselves.

Covering over 71% of Earth’s surface, water is undoubtedly the most precious natural resource that exists on our planet. Without the seemingly invaluable compound comprising Hydrogen and Oxygen, life on Earth would be non-existent.

We are slowly but harming our planet at a very alarming rate.

Characteristics of a Good Essay.

It must be brief: As pointed out earlier, a good essay must be short, and also to the point. So, if students are writing an essay on the importance of water it must only deal with the water, and anything which does not directly serve the purpose must be excluded.

Must cover the whole topic: Though it may seem a little contradicting to the first point, what is meant by covering the whole topic is that the maximum number of aspects dealing with the importance of water must be covered in this essay. For instance, water is important for all living organisms and not just humans, and so the same has to be covered in one or the other way in the essay on the importance of the water.

Must be to the point: The essay must remain true to the central idea of the topic, which is the importance of water in this case. Hence, almost all the sentences written in the essay must serve the main topic in one or another way. And also, writing should not be vague or ambiguous, or illogical.

Human beings should realize how important and precious water is. At the individual level, you can be more responsible and avoid wasting water so that our future generation can make the best use of this natural resource abundantly.

FAQs on Importance of water

1. Why is water important?

Water is important because it sustains all living organisms on Earth.

2. How is ocean water useful to Mankind?

Ocean water is useful to mankind in the following ways.

Oceans are a major source of water through the water cycle.

Oceans have direct control over the climate.

Oceans are the biggest storehouse of marine food.

Oceans have enormous mineral and chemical wealth.

3. How is water important for our Body?

Water helps to carry nutrients and oxygen to each and every cell of our body. It helps in digestion. It keeps our skin healthy and hydrated. Water consumption lubricates the joints, spinal cord, and tissues.

4. What are the uses of water in our Daily Life?

Water is used for drinking, bathing, cooking, cleaning, and irrigation of crops and manufacturing various products.

5. Why should I use the essay provided by Vedantu on the Importance of water?

The essay that Vedantu provides on the topic of the Importance of water is prepared by expert teachers, for the students of the English language. And hence this essay can be used by the students as an outline or an example of the essay on the Importance of water, it does not necessarily mean that the students have to copy it completely, but it serves the purpose of guiding the students in attempting the essay. Furthermore, the essay is completely free for download for all the students and also it is available in a PDF file format.

Essay on Animals and Their Habitat

Essay on animals and their habitat: introduction, animal habitat paragraphs for the main body, habitat essay conclusion, reference list.

“A habitat, or biome, is the type of environment in which plants and animals live” ( Habitats 2017, para. 1). In other words, a habitat is an environmental zone where particular species of animals, plants, and other organisms can be found. There are three main groups of habitats: terrestrial, freshwater, and marine habitats. This paper is aimed at the comparison of two natural habitats, desert and rainforest, and two species of animals that live there.

Deserts are terrestrial habitats. There are deserts all across the globe. Howard (2014, p. 6) emphasizes that “deserts cover about one-fifth of the Earth’s surface.” The area that receives less than 250 mm of rainfall a year can be named desert ( Desert 2017, para. 1). Contrary to popular belief, not all deserts are hot, dry, and sandy. Some deserts are cold. The brightest example of cold deserts is Antarctica that is covered by ice. Also, the surface area of most deserts contains rock and stones. The world’s largest hot desert is the Sahara. Cook and Vizy (2015) illustrate that the area of this desert is 9,200,000 square kilometers.

Rainforests are terrestrial habitats too. It is characterized by a warm and wet climate. Hollar (2011, p. 44) describes rainforest as “a term for a forest of broad-leaved evergreen trees that receives high annual rainfall and is characteristically associated with tropical and subtropical regions of the world.” Rainforests receive from 1,5 to 2,4 meters of rain annually. Rainforests are often named jungles. Rainforests cover about six percent of the Earth’s surface ( Rainforest 2017). There are two types of rainforests: tropical and temperate rainforests. The biggest tropical rainforest is the Amazon rainforest in South Africa.

There are some obvious differences between deserts and rainforests. However, the major difference is climate. Rainforests are warm and wet. Whereas, the majority of deserts are hot and dry and receive a small amount of rainfall annually. Despite the harsh climate, deserts do not lack life. To survive in the desert, animals and plants have to adapt to their conditions. For instance, plants that inhabit deserts do not require a great amount of water to live. When it rains, plants absorb as much water as possible very fast because water evaporates quickly in deserts, and it never goes deep into the soil. That is why a lot of desert plants have shallow roots. However, plants are scarce in deserts due to the lack of water, and the diversity of desert flora cannot be compared with a wide range of plants growing in rainforests. Rainforests contain more than half of all world’s biotic species. Some scientists assure that there are a lot of species of plants and invertebrates that are still undiscovered in tropical rainforests. Rainforests provide ideal conditions for plants, while deserts have a low ability to support plant life.

The same holds for fauna. The warm climate and constant rainfalls contribute to the diversity of animals in rainforests. As previously explained, tropical and temperate rainforests are home to more than half of all world’s biotic species. On the contrary, deserts are not considered to be the most suitable environment for animal life. There are not enough sources of water and food in deserts. What is more, hot daytime temperatures affect animals? Many desert animals are nocturnal, and they are very efficient at conserving water.

A lot of people associate deserts with camels. These animals are called ‘ships of deserts’. A distinctive feature of these mammals is a humped back. The camel has some ways to adapt to the desert. Firstly, it has humps that consist of stored fat. This fat is metabolized when the camel is short of food and water. Moreover, the camel has some features to protect itself from sand such as long lashes and a third eyelid that protect eyes. Also, the camel closes its nostrils during dust storms.

The brightest example of rainforest animals is the jaguar. The jaguar is a big cat that is perfectly adapted to rainforests. The jaguar’s spotted orange-brown fur is a sort of camouflage in rainforests. It helps to catch prey. Apart from this, the jaguar has excellent swimming abilities that are necessary because there is a lot of water in rainforests. However, the most important jaguar’s feature is a good night vision. It helps jaguars to hunt at nighttime.

To sum up, deserts and rainforests are kinds of terrestrial habitats. However, these two habitats are very different in terms of their abilities to support animal and plant life. While rainforests provide ideal conditions for plant and animal life, the climate of deserts is extremely harsh. Nevertheless, animals and plants tend to adapt to their conditions. The camel is a representative of desert animals, and the jaguar is a typical rainforest animal. Both of them have their ways to adapt to their environments.

Cook, K & Vizy, E 2015, ‘Detection and analysis of an amplified warming of the Sahara Desert’, Journal of Climate , vol. 28, no. 16, pp. 6560-6580.

Desert . 2017. Web.

Habitats . 2017. Web.

Hollar, S 2012, Investigating Earth’s desert, grassland, and rainforest biomes (introduction to Earth science) , Britannica Educational Publishing, New York.

Howard, F 2012, Deserts , ABDO Publishing Company, Edina.

Rainforest. 2017. Web.

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IvyPanda. (2023, October 31). Essay on Animals and Their Habitat. https://ivypanda.com/essays/animals-and-their-natural-habitats/

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Freshwater Ecosystem

The world's demand for fresh water is high, though there is a limited supply. How can we be more responsible with this crucial resource and its ecosystems?

Biology, Ecology, Conservation, Earth Science

Mountain Stream

A mountain stream flowing through Inverpolly, Scotland.

Photograph by Education Images

Every living thing on Earth needs water to survive, but more than 100,000 species, including our own, need a special kind of water that can only be found in certain places and is in very rare supply: fresh water. The plants, animals, microbes, rocks, soil, sunlight, and water found in and around this valuable resource are all part of what is called a freshwater ecosystem. Less than three percent of our planet’s water is fresh water, and less than half of that is available as a liquid; the rest is locked away as ice in polar caps and glaciers. For these reasons, freshwater ecosystems are a precious resource. Where is Fresh Water? Fresh water starts out as water vapor that has evaporated from the surface of oceans, lakes, and other bodies of water. When this vapor rises, it leaves salts and other contaminants behind and becomes “fresh.” The water vapor collects in drifting clouds that eventually release the water back to Earth in the form of rain or snow. After fresh water reaches the ground through precipitation , it flows downhill across a landscape called the watershed to lakes, ponds, rivers, streams, and wetlands . But fresh water can be found in less-obvious places, too. More than half of all fresh water on our planet seeps through soil and between rocks to form aquifers that are filled with groundwater. The top surface of an aquifer is called the water table , and this is the depth where wells are drilled to bring fresh water into cities and homes. Studying Freshwater Ecosystems On the volcanic island nation of Iceland, explorer Jónína Herdís Ólafsdóttir studies freshwater ecosystems that develop from groundwater seeping into fissures . These fissures are large cracks, which are caused by the tectonic plates underneath the country shifting and pulling the bedrock apart. The crystal blue water in these fissures is barely above freezing temperature. Wearing scuba gear, Olafsdóttir drops into the water and collects biological samples, recording notes about the species of fish, crustaceans, algae, and other microbes that she finds. She was one of the first scientists ever to describe the biodiversity in these Icelandic fissure ecosystems. Scientists who study freshwater ecosystems are called limnologists. Limnologists want to learn what creatures live in an ecosystem and how they interact with each other through the ecosystem’s food web , as well as how they interact with their environment. This knowledge can help the researchers know when a freshwater ecosystem is healthy and when it may be in danger. Balancing Change Freshwater ecosystems naturally share resources between habitats. The ecosystems in rivers and streams, for example, bring salts and nutrients from the mountains to lakes, ponds, and wetlands at lower elevations, and eventually they bring those nutrients to the ocean. These waterways also enable migrating species, like salmon, to bring nutrients from the ocean to upstream freshwater ecosystems. Lakes and ponds, on the other hand, can exchange nutrients in a seasonal cycle. Cold water is denser than warm water, so it sinks to the bottom, where a fairly steady temperature is maintained. However, as the air temperature drops with the arrival of winter, the water that is closest to the surface may drop below the temperature of the water at the bottom of the lake, causing it to sink and the warmer bottom water to rise. The same process happens as floating surface ice melts into very cold water in the spring. During these periods, nutrients are churned from the floor and brought to the surface. It is normal for ecosystems to encounter change. Temperatures may fluctuate, populations may rise and fall, and rain may bring an abundance of water, then taper during drought. The plants, animals, and microbes in healthy freshwater ecosystems are resilient and have adaptations that allow them to adjust appropriately until ideal conditions resume. However, if any element of the ecosystem varies too far outside of the norm, the balance of the whole system can start to fail. Signs of Danger Humans use fresh water in many ways, but these activities can be dangerous for freshwater ecosystems when we are not careful. Overfishing, pollution, and disruption of the landscape through projects like dams and deforestation are just a few ways we can put these ecosystems—and ultimately, our own access to fresh water—at risk. When the changes we cause are too great or too sudden, then ecosystems struggle to bounce back. An example of this kind of sudden change is when an invasive species enters an area, which happened in 2009 near the city of Madison, Wisconsin, when the spiny water flea ( Bythotrephes longimanus) was detected in Lake Mendota. The spiny water flea, native to Russian and European lakes, came to North America in the 1980s with cargo ships that had traveled across the Atlantic and down the St. Lawrence River to the Great Lakes. Eventually, these tiny stowaways were carried over land to Lake Mendota, and that is where they unleashed a cascade of havoc. Spiny water fleas love to eat Daphnia pulicaria plankton, which are important to the Lake Mendota ecosystem, because they eat green algae that would otherwise grow out of control. D. pulicaria is also a key food source for fish in the lake. As the population of spiny water fleas increased, algae began to overgrow and lower the oxygen content of the water, causing the fish to die and the lake water to grow murky. Ten years later, spiny water fleas are still thriving in Lake Mendota and now, a new invasive species, the zebra mussel ( Dreissena polymorpha ), is taking over the lake floor. Once an invasive species becomes established in a freshwater ecosystem, it is nearly impossible to get it out. Scientists like Canadian aquatic ecologist Dalal Hanna can help avoid disasters like these by studying ecosystems and identifying points of human interaction that might cause trouble. Hanna has researched freshwater fish in African streams and birds that live near freshwater ecosystems in Canada. Today, she is developing useful measures and management strategies so communities can gauge how to balance their need for “ecosystem services” like drinking water, recreation, and flood prevention with the health of the freshwater ecosystems upon which they rely.

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Essay On Animals

The quote by Anatole France, “Until one has loved an animal, a part of one’s soul remains unawakened”, sums it all about animals. Planet Earth is home to humans as well as animals. According to the survey, it is estimated that over 8 million species of animals exist on Earth, living on land and water. Each species has a unique place in the environment and balances the ecosystem. These species play a significant role in the stability of the ecosystem, environment, and our lives.

100 Words Essay On Animals

200 words essay on animals, 500 words essay on animals.

Since the beginning of human civilisation, humans have interacted with wildlife. Before the era of industrialisation and urbanisation, human life was dependent on animals. The big animals were a threat to our ancestors who once lived in caves and were nomads. Eventually, they learned to survive, fight and use the animal's skin for clothing, the meat for food or bait, and ivory elements as utensils or ornaments. Even as humans evolved, animals have contributed to various aspects like transportation, the economy, social life etc. The increased dependence of humans on animals has caused threats to their existence. Hence, their preservation and protection against any abuse is our responsibility.

Animals are the most adorable and loving creatures existing on Earth. They might not be able to speak, but they can understand. They have a unique mode of interaction which is beyond human understanding. There are two types of animals: domestic and wild animals.

Domestic Animals | Domestic animals such as dogs, cows, cats, donkeys, mules and elephants are the ones which are used for the purpose of domestication. Wild animals refer to animals that are not normally domesticated and generally live in forests. They are important for their economic, survival, beauty, and scientific value.

Wild Animals | Wild animals provide various useful substances and animal products such as honey, leather, ivory, tusk, etc. They are of cultural asset and aesthetic value to humankind. Human life largely depends on wild animals for elementary requirements like the medicines we consume and the clothes we wear daily.

Nature and wildlife are largely associated with humans for several reasons, such as emotional and social issues. The balanced functioning of the biosphere depends on endless interactions among microorganisms, plants and animals. This has led to countless efforts by humans for the conservation of animals and to protect them from extinction. Animals have occupied a special place of preservation and veneration in various cultures worldwide.

Animals are made up of numerous cells that can move, sense and reproduce. They play a vital role in maintaining nature’s balance. Numerous animal species exist in the land as well as water, and each has a purpose for their existence.

Different Types Of Animals

Biologists have divided into particular groups for better understanding at the species level, for instance – amphibians - animals which live on land as well as water, reptiles – which are scaled bodies and cold-blooded animals, mammals – animals which give birth to the offspring in the womb and have mammary glands, birds – animals with forelimbs evolved to wings and feather-covered body, and also lays eggs for giving birth, fishes – aquatic animals having fins in place of limbs, and gills for the respiration, insects – they are mostly six-legged or more, and mostly having a head, abdomen, and thorax.

How Animals Help Humans

Since the time of existence and evolution of human beings, we have established ourselves as the greater and more superior species because of sophisticated and advanced ways of thinking and applying. With time, humans have learned to use animals to their benefit and have also realised how to incorporate animals into our social lives:-

Animal husbandry has been in existence for a very long period of time.

Animals have been used for numerous purposes like clothing, food, entertainment, and transportation.

Animals have also been used to discover new things from tests and research. Several vaccines and medicines obtained from animals have turned out to be benison.

Animals have also been used for outer-space explorations, leading to milestone achievements in scientific discoveries.

Humans have used animals for good (sustain livelihood) and evil purposes (acts of torture to poor animals). Even as the world modernised, people have started thinking about animals and working for their rights, creating awareness among humans.

The bond between humans and animals has evolved as a strong bond, and now both coexist with a mutual understanding of nature. Humans have strived to preserve those endangered and rare species via modern conservation modes, including national parks, sanctuaries, etc.

My Experience With Animals

As a child raised in a city, I never had first-hand experience with animals. Though people domesticate animals, I was always afraid of them. Due to the fear of getting infected and being bitten, I never went near them. One fine day, I saw finches in the pet shop near my house. At first glance, I loved them for a long time, but then one of my friends asked me to reach out to them and observe them. To my astonishment, the finches drew near me and were looking at me. I thought to take them with me, and when I took them – I was amazed by their understanding, love and interactions. This led me to love the animals and look at them from a different perspective, not with a fearful heart. They are the most loving creatures existing on Earth.

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Essay on Aquatic Animals

150 words essay on aquatic animals.

Aquatic animals are those that live inside the water. Aquatic lives are different than normal terrestrial lives. Aquatic species breathe inside the water with the help of gills. Although they too need oxygen like us the medium is different. We inhale oxygen from the air as they inhale oxygen from water.

These aquatic animals are specially characterized as the ones who don’t get close contact with the world outside water. Our land is surrounded by water but for Aquatic animals, water is their world. Water is a world in itself in which both animals and plants live.

Fish is one good example of aquatic animals. The aquatic animals live in the sea, ponds, lakes, rivers, etc. but water is their permanent house. It can be saline, still, or fresh.

But we human for our own selfish mean keep on containing their homes with dirty oil-spills and garbage. This makes their life a living hell. Increasing water contamination and human interference in their habitats put thousands of aquatic species at grave risk of extinction and endangerment.

200 Words Essay on Aquatic Animals

The world of marine is very vast; it is very complex to study all of it. Some of the species are still beyond the reach of human beings.

250 Words Essay on Aquatic Animals

Different types of species with different characteristics reside in the aquatic world. Some breathe through gills and some through their skin also. These animals are very different from us in every respect. They usually have very soft and delicate body. This makes them very prone to die from a hard touch, so to be very careful in dealing with them.

300 Words Essay on Aquatic Animals

The world of marine is very vast; it is very complex to study all of it. Some of the species are still beyond the reach of human beings. Fish is one good example of aquatic animals. The aquatic animals live in the sea, ponds, lakes, rivers, etc. but water is their permanent house. It can be saline, still, or fresh.

Aquatic animals involve not only fishes but many other animals. There are many types of snakes also that live inside water. Apart from snakes, there are many types of turtles. But turtles, crocodiles, and frogs are amphibians which means they can live inside water as well as on the ground.

Different types of species with different characteristics reside in the aquatic world. Some breath through gills and some through their skin also. These animals are very different from us in every respect. They usually have a very soft and delicate body. This makes them very prone to die from a hard touch, so be very careful in dealing with them.

We have an Essay on every topic, Check the complete list here . If you are Studying in Matric Free Video Lectures of Maths , Physics and English are here, and if we got you covered for I.COM Business Maths also.

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Essay on Aquatic Animals | Brief Information

February 19, 2018 by Study Mentor Leave a Comment

Marine world is altogether different from our world. It is different and unique in its own way. We are surrounded by all around us but for Aquatic animals water is their world.

They thrive on water. Though the ocean world is completely different yet life is thoughts to have evolved from oceans millions of years ago.

Hence we cannot deny its importance and significance in our lives.

Water is a world in itself in which both animals and plants live. The animals which live in water are called Aquatic animals.

The aquatic animals live in sea, ponds, lakes, rivers etc. but water is their permanent house. It can be saline, still tor fresh.

As our houses are of different kinds similarly the aquatic animals live in different environments according to their sustainability.

Their lifestyle is totally different from ours. They have a different respiratory system. They breathe inside water with the help of gills. Although they too need oxygen like us but the medium is different. We inhale oxygen from air where as they inhale oxygen from water.

But we human for our own selfish mean keep on containing their homes with oil-spills and garbage.

This makes their life a living hell. Increasing water contamination and human interference in their habitats puts several of aquatic species at a grave risk of extinction and endangerment.

Aquatic animals also balance the equilibrium among various species connected to a food chain. Thus aquatic animals have immense importance in the world also.

As any changes in their lives affects the lives of other animals as well. So to make a good ecological balance, we should keep monitoring sea or ocean water pollution.

The world of aquatic animals is very vast; it is too complex to study all of it. Some of the species are still beyond the reach of human beings.

Although science and technology have helped in discovering various species each day, yet the fact remains that the world is as dark, complex and unknown place buts it is immensely beautiful in its own ways.

The more we acknowledge it the more it becomes unknown for us.

Different types of animals with different characteristics reside in the marine world. Some breathe through gills and some through skin also.

Other than aquatic animals some amphibians like frogs etc. have the ability to live in water as well as on the ground also.

They can breathe in both the mediums- water as well air. Aquatic animals are very different from us in all respects. They usually have soft and delicate body.

This makes them very prone to die from a hard touch. So one ought to be very careful in dealing with them.

Most of the people only think about fishes when we talk about aquatic animals. But in reality there are too many animals other than fishes that live underwater.

Animals like mammals, mollusks, cnidarians and crustaceans are also a part of this ecology.

Fishes belong to the vertebrate’s family. They have a back bone like us. Different animals have different characteristics.

A fish called Salmon can live bath in saline as well as fresh water. Dolphins and whales are mammals and can live only in water.

Whereas animals like beavers and seals can exit from water for longer hours. Mammals cannot breathe under water so they have to come out at the surface to breathe air.

Aquatic animals also use sounds to communicate just like us. Some use these sounds to hunting their prey and some uses it for relocation of food.

But sometimes they also use it to stun their prey. They also communicate but the medium is different here. The medium is water.

Marine animals seem to recognize the voices of their family members and other species from a distance.

Whales and dolphins make different combination noises to communicate underwater. Aquatic animals can see well underwater through a certain distance only, due to the lack of sunlight.

But when we go towards the deeper ends of water, it turns all cold and black; devoid of any sunlight.

Their eyes are specially designed to see underwater in low light also but sounds help them to navigate accurately under water.

Sounds waves move five times faster than air. This specialty allows the animals to talk over long distances also.

The world of aquatic animals is gigantic but we human brings interfere in their habitat and threaten their existence.

The activities like overfishing, destructive fishing, marine pollution and climate change has increased their problems for the life that remains invisible to the naked eye and lives deep in the creeks and crevices of water.

Sound and light, both are an immediate necessity for aquatic animals. It helps them in finding food, avoiding danger and relocating their mates.

Some deep sea animals can prepare their own light for all their purposes. They are equipped with special characteristics features to generate light.

Sailfish which is the fastest fish in the ocean can swim at the speed of 68 mph to escape itself from predators like octopus.

A small sea animal named Mantis shrimp which is just 18 to 30 cm. in size can ‘accelerate its forelimb in same velocity of gunshot from a rifle’.

It can shatter its prey into pieces in less than a second. Its strength power can induce shock-waves on sea-beds.

Box jelly fish which are considered the most venomous creature in the world have a transparent body which helps it to remains hidden from the eyes of predators.

Its body have 5000 stinging cells which can stop the heart beat of the person in seconds if stung by it.

Aquatic animals have strong smell receptors. They can smell their predators from miles away.

The sharks have so strong nose receptors that the prey does not stand a chance of escaping the jaws of death. Smell plays an important role in underwater communication.

Like humans fishes also detect phenomenon that facilitate mating procedures. Fish can use smell to locate food.

We all know that Salmon fish can travel miles to spawn at its birthplace.

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Short Essay on Water [100, 200, 400 Words] With PDF

In this lesson today, I will discuss how exactly you can write short essays on the important topic ‘Water.’ There will be three sets of essays in this following session, each within different word limits.

Short Essay on Water in 100 Words

Every living being on the earth needs some basic things for its survival. It includes food, water, shelter, and money as well for humans. Water is by far the principal need of living beings. About two-third part of the earth is covered with water.

Water is available in several forms on earth. Some amount is frozen in glaciers, while the larger amount of water is salty. Fresh water on earth is very little. We need water for every purpose. Drinking, cooking, bathing, washing are the basic needs, while water is also used by bigger industries to run their machines. Water is an important source of electricity. So, being the most valuable resource water must never be wasted.

Short Essay on Water in 200 Words

Water is the most significant resource among everything that humans and animals can receive. Water helps a living being to live for longer days, even when food is scarce. It is one of the most beautiful gifts of nature. Water has enormous benefits and is the life of the earth. Its medicinal properties cure several ailments in our bodies. Without it, we cannot imagine living a second on earth. The world will be a huge desert if the water on earth is destroyed.

Our earth is unique in its creation. About two-third part of it is covered with water, while the rest of it is land. If we take a deeper study, then a major part of the water is either frozen as glaciers or is present in the oceans as saltwater. The reserve of fresh water on earth is a limited amount. It can exhaust at any moment. Hence we must spend water wisely. We need water for drinking, bathing, washing clothes and utensils, cooking, cultivating, etc.

Big industries require lots of water to run their machines. Today due to the scarcity of coal, hydroelectricity is the new way of generating electrical power. This process requires huge amounts of water. In several ways, water is our saviour. It is the beauty of nature as a wonderful waterfall or a stream, and also the help to a thirsty person.

Short Essay on Water in 400 Words

Water is the basic strength behind all life forces on earth. It is the necessity of every life and is the biggest shelter for us to survive. If there is no water suddenly on earth, then it will only be a lifeless planet filled with dust and stone.

The green earth will become a long stretch of a desert without this component. Water forms about two-thirds of the earth, while only one-third is given for the land. Yet how much greater the amount of water on earth be, the availability of fresh water on earth is the minimum.

A large amount of water is left unused. It is either frozen as glaciers or is present as salty ocean water. This water cannot be applied for regular usage. So we must understand the wise utilization of water. It is a scanty but most important resource. So only its proper utilization can make it sufficient.

Water is the source of all activities in our lives. From the olden days, human beings have always tried to live near water bodies. Because those places are fertile for cultivation. A vast desert-like Egypt also survives because of the river Nile. The Ganges in India is not only a water body but one of the most sacred rivers in the world. The most important use of water is in agriculture.

Every plant needs it to grow. If crops do not receive adequate water, then they will be stunted. We use water for drinking, cooking, bathing, washing. A living body needs lots of water intake. Insufficient water intake can result in lots of ailments. Water is beneficial for this medical property. Besides these, all industries need water for producing electricity and running the turbines. Water is the potential of civilization. A civilization operates because of the availability of water

But at present, we are observing the pollution of water bodies. It is dangerous for all living beings to survive if all water sources are contaminated. Polluted water is a threat to the earth. Households, industries, insufficient cleanliness, lack of awareness, all are enough to increase pollution in several degrees. With increased consumption of water, it is being equally polluted. Thus many aquatic plants and animals, humans, other land animals are regularly dying after intaking the dirty water.

This is harming our ecosystem. So we must preserve freshwater. It is important and is available in little amount. Clean water can exhaust at any moment. It is our duty even to preserve the rainwater and use it. Every drop of water means life. A correct utility of it is the best way.

So, that was all about writing short essays on Water. In this session above, I have adopted a simplistic approach to writing all these essays for a better understanding of all kinds of students. You can let me know your queries by commenting down below. If you want to read more such lessons on various important topics regarding English composition, keep browsing our website. Thank you.

Importance of Water Essay for Students and Children

500+ words essay on importance of water.

Water is the basic necessity for the functioning of all life forms that exist on earth . It is safe to say that water is the reason behind earth being the only planet to support life. This universal solvent is one of the major resources we have on this planet . It is impossible for life to function without water. After all, it makes for almost 70% of the earth.

However, despite its vast abundance, water is very much limited. It is a non-renewable resource . In addition, we need to realize the fact that although there is an abundance of water, not all of it is safe to consume. We derive some very essential uses from the water on a daily basis.

Significance of water

If we talk about our personal lives, water is the foundation of our existence. The human body needs water for the day to day survival. We may be able to survive without any food for a whole week but without water, we won’t even survive for 3 days. Moreover, our body itself comprises of 70% water. This, in turn, helps our body to function normally.

Thus, the lack of sufficient water or consumption of contaminated water can cause serious health problems for humans. Therefore, the amount and quality of water which we consume is essential for our physical health plus fitness.

Further, our daily activities are incomplete without water. Whether we talk about getting up in the morning to brush or cooking our food, it is equally important. This domestic use of water makes us very dependent on this transparent chemical.

In addition, on a large scale, the industries consume a lot of water. They need water for almost every step of their process. It essential for the production of the goods we use every day.

If we look beyond human uses, we will realize how water plays a major role in every living beings life. It is the home of aquatic animals. From a tiny insect to a whale, every organism needs water to survive.

Therefore, we see how not only human beings but plants and animals too require water. The earth depends on water to function. We cannot be selfish and use it up for our uses without caring about the environment.

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Open access
Published: 01 May 2024

Temporal dynamics of the multi-omic response to endurance exercise training

MoTrPAC Study Group ,
Lead Analysts &

MoTrPAC Study Group

Nature volume 629 , pages 174–183 ( 2024 ) Cite this article

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Epigenetics
Metabolomics
Transcriptomics

Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood 1 , 2 , 3 . Here, the Molecular Transducers of Physical Activity Consortium 4 profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository ( https://motrpac-data.org/ ).

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Regular exercise provides wide-ranging health benefits, including reduced risks of all-cause mortality 1 , 5 , cardiometabolic and neurological diseases, cancer and other pathologies 2 , 6 , 7 . Exercise affects nearly all organ systems in either improving health or reducing disease risk 2 , 3 , 6 , 7 , with beneficial effects resulting from cellular and molecular adaptations within and across many tissues and organ systems 3 . Various ‘omic’ platforms (‘omes’) including transcriptomics, epigenomics, proteomics and metabolomics, have been used to study these events. However, work to date typically covers one or two omes at a single time point, is biased towards one sex, and often focuses on a single tissue, most often skeletal muscle, heart or blood 8 , 9 , 10 , 11 , 12 , with few studies considering other tissues 13 . Accordingly, a comprehensive, organism-wide, multi-omic map of the effects of exercise is needed to understand the molecular underpinnings of exercise training-induced adaptations. To address this need, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established with the goal of building a molecular map of the exercise response across a broad range of tissues in animal models and in skeletal muscle, adipose and blood in humans 4 . Here we present the first whole-organism molecular map of the temporal effects of endurance exercise training in male and female rats and provide multiple insights enabled by this MoTrPAC multi-omic data resource.

Multi-omic analysis of exercise training

Six-month-old male and female Fischer 344 rats were subjected to progressive treadmill endurance exercise training (hereafter referred to as endurance training) for 1, 2, 4 or 8 weeks, with tissues collected 48 h after the last exercise bout (Fig. 1a ). Sex-matched sedentary, untrained rats were used as controls. Training resulted in robust phenotypic changes (Extended Data Fig. 1a–d ), including increased aerobic capacity (VO 2 max) by 18% and 16% at 8 weeks in males and females, respectively (Extended Data Fig. 1a ). The percentage of body fat decreased by 5% in males at 8 weeks (Extended Data Fig. 1b ), without a significant change in lean mass (Extended Data Fig. 1c ). In females, the body fat percentage did not change after 4 or 8 weeks of training, whereas it increased by 4% in sedentary controls (Extended Data Fig. 1b ). Body weight of females increased in all intervention groups, with no change for males (Extended Data Fig. 1d ).

a , Experimental design and tissue sample processing. Inbred Fischer 344 rats were subjected to a progressive treadmill training protocol. Tissues were collected from male and female animals that remained sedentary or completed 1, 2, 4 or 8 weeks of endurance exercise training. For trained animals, samples were collected 48 h after their last exercise bout (red pins). b , Summary of molecular datasets included in this study. Up to nine data types (omes) were generated for blood, plasma, and 18 solid tissues, per animal: ACETYL: acetylproteomics; protein site acetylation; ATAC, chromatin accessibility, ATAC-seq data; IMMUNO, multiplexed immunoassays; METAB, metabolomics and lipidomics; METHYL, DNA methylation, RRBS data; PHOSPHO, phosphoproteomics; protein site phosphorylation; PROT, global proteomics; protein abundance; TRNSCRPT, transcriptomics, RNA-seq data; UBIQ, ubiquitylome, protein site ubiquitination. Tissue labels indicate the location, colour code, and abbreviation for each tissue used throughout this study: ADRNL, adrenal gland; BAT, brown adipose tissue; BLOOD, whole blood, blood RNA; COLON, colon; CORTEX, cerebral cortex; HEART, heart; HIPPOC, hippocampus; HYPOTH, hypothalamus; KIDNEY, kidney; LIVER, liver; LUNG, lung; OVARY, ovaries; PLASMA, plasma; SKM-GN, gastrocnemius (skeletal muscle); SKM-VL, vastus lateralis (skeletal muscle); SMLINT, small intestine; SPLEEN, spleen; TESTES, testes; VENACV, vena cava; WAT-SC, subcutaneous white adipose tissue. Icons next to each tissue label indicate the data types generated for that tissue. c , Number of training-regulated features at 5% FDR. Each cell represents results for a single tissue and data type. Colours indicate the proportion of measured features that are differential.

Whole blood, plasma and 18 solid tissues were analysed using genomics, proteomics, metabolomics and protein immunoassay technologies, with most assays performed in a subset of these tissues (Fig. 1b and Extended Data Fig. 1e,f ). Specific details for each omic analysis are provided in Extended Data Fig. 2 , Methods, Supplementary Discussion and Supplementary Table 1 . Molecular assays were prioritized on the basis of available tissue quantity and biological relevance, with the gastrocnemius, heart, liver and white adipose tissue having the most diverse set of molecular assays performed, followed by the kidney, lung, brown adipose tissue and hippocampus (Extended Data Fig. 1e ). Altogether, datasets were generated from 9,466 assays across 211 combinations of tissues and molecular platforms, resulting in 681,256 non-epigenetic and 14,334,496 epigenetic (reduced-representation bisulfite sequencing (RRBS) and assay for transposase-accessible chromatin using sequencing (ATAC-seq)) measurements, corresponding to 213,689 and 2,799,307 unique non-epigenetic and epigenetic features, respectively.

Differential analysis was used to characterize the molecular responses to endurance training (Methods). We computed the overall significance of the training response for each feature, denoted as the training P value, where 35,439 features at 5% false discovery rate (FDR) comprise the training-regulated differential features (Fig. 1c and Supplementary Table 2 ). Timewise summary statistics quantify the exercise training effects for each sex and time point. Training-regulated molecules were observed in the vast majority of tissues for all omes, including a relatively large proportion of transcriptomics, proteomics, metabolomics and immunoassay features (Fig. 1c ). The observed timewise effects were modest: 56% of the per-feature maximum fold changes were between 0.67 and 1.5. Permutation testing showed that permuting the group or sex labels resulted in a significant reduction in the number of selected analytes in most tissues (Extended Data Fig. 3a–d and Supplementary Discussion ). For transcriptomics, the hypothalamus, cortex, testes and vena cava had the smallest proportion of training-regulated genes, whereas the blood, brown and white adipose tissues, adrenal gland and colon showed more extensive effects (Fig. 1c ). For proteomics, the gastrocnemius, heart and liver showed substantial differential regulation in both protein abundance and post-translational modifications (PTMs), with more restricted results in white adipose tissue, lung and kidney protein abundance. For metabolomics, a large proportion of differential metabolites were consistently observed across all tissues, although the absolute numbers were related to the number of metabolomic platforms used (Extended Data Fig. 1e ). The vast number of differential features over the training time course across tissues and omes highlights the multi-faceted, organism-wide nature of molecular adaptations to endurance training.

Multi-tissue response to training

To identify tissue-specific and multi-tissue training-responsive gene expression, we considered the six tissues with the deepest molecular profiling: gastrocnemius, heart, liver, white adipose tissue, lung and kidney. In sum, 11,407 differential features from these datasets were mapped to their cognate gene, for a total of 7,115 unique genes across the tissues (Fig. 2a , Extended Data Fig. 4a and Supplementary Table 3 ). Most of the genes with at least one training-responsive feature were tissue-specific (67%), with the greatest number appearing in white adipose tissue (Fig. 2a ). We identified pathways enriched by these tissue-specific training-responsive genes (Extended Data Fig. 4b ) and tabulated a subset of highly specific genes to gain insight into tissue-specific training adaptation (Supplementary Table 4 ). Focusing on sexually conserved responses revealed tissue-dependent adaptations. These included changes related to immune cell recruitment and tissue remodelling in the lung, cofactor and cholesterol biosynthesis in the liver, ion flux in the heart, and metabolic processes and striated muscle contraction in the gastrocnemius ( Supplementary Discussion ). A detailed analysis of white adipose tissue adaptations to exercise training is provided elsewhere 14 . We also observed ‘ome’-specific responses, with unique transcript and protein responses at the gene and pathway levels (Extended Data Fig. 4c,d , Supplementary Discussion and Supplementary Tables 5 and 6 ).

a , UpSet plot of the training-regulated gene sets associated with each tissue. Bars and dots indicating tissue-specific differential genes are coloured by tissue. Pathway enrichment analysis is shown for selected sets of genes in b , c as indicated by the arrows. b , c , Significantly enriched pathways (10% FDR) corresponding to genes that are differential in both LUNG and WAT-SC datasets ( b ) and the 22 genes that are training-regulated in all six tissues considered in a ( c ). Redundant pathways (those with an overlap of 80% or greater with an existing pathway) were removed. ESR, oestrogen receptor; T H 17, T helper 17.

2,359 genes had differential features in at least two tissues (Fig. 2a ). Lung and white adipose tissue had the largest set of uniquely shared genes ( n = 249), with predominantly immune-related pathway enrichments (Fig. 2b ); expression patterns suggested decreased inflammation in the lung and increased immune cell recruitment in white adipose tissue (Supplementary Tables 2 and 3 ). Heart and gastrocnemius had the second-largest group of uniquely shared genes, with enrichment of mitochondrial metabolism pathways including the mitochondria fusion genes Opa1 and Mfn1 (Supplementary Table 3 ).

Twenty-two genes were training-regulated in all six tissues, with particular enrichment in heat shock response pathways (Fig. 2c ). Exercise induces the expression of heat shock proteins (HSPs) in various rodent and human tissues 15 . A focused analysis of our transcriptomics and proteomics data revealed HSPs as prominent outliers (Extended Data Fig. 5a and Supplementary Discussion ). Specifically, there was a marked, proteomics-driven up-regulation in the abundance of HSPs, including the major HSPs HSPA1B and HSP90AA1 (Extended Data Fig. 5b,c ). Another ubiquitous endurance training response involved regulation of the kininogenases KNG1 and KNG2 (Supplementary Table 3 ). These enzymes are part of the kallikrein–kininogen system and have been implicated in the hypotensive and insulin-sensitizing effects of exercise 16 , 17 .

Transcription factors and phosphosignalling

We used proteomics and transcriptomics data to infer changes in transcription factor and phosphosignalling activities in response to endurance training through transcription factor and PTM enrichment analyses (Methods). We compared the most significantly enriched transcription factors across tissues (Fig. 3a , Extended Data Fig. 6a and Supplementary Table 7 ). In the blood, we observed enrichment of the haematopoietic-associated transcription factors GABPA, ETS1, KLF3 and ZNF143; haematopoietic progenitors are proposed to be transducers of the health benefits of exercise 18 . In the heart and skeletal muscle, we observed a cluster of enriched Mef2 family transcription factor motifs (Fig. 3a ). MEF2C is a muscle-associated transcription factor involved in skeletal, cardiac and smooth muscle cell differentiation and has been implicated in vascular development, formation of the cardiac loop and neuron differentiation 19 .

a , Transcription factor motif enrichment analysis of the training-regulated transcripts in each tissue. The heat map shows enrichment z -scores across the differential genes for the 13 tissues that had at least 300 genes after mapping transcript IDs to gene symbols. Transcription factors were hierarchically clustered by their enrichment across tissues. CRE, cAMP response element. b , Estimate of activity changes in selected kinases and signalling pathways using PTM signature enrichment analysis on phosphoproteomics data. Only kinases or pathways with a significant difference in at least one tissue, sex or time point ( q value < 0.05) are shown. The heat map shows normalized enrichment score (NES) as colour; tissue, sex and time point combinations as columns, and either kinases or pathways as rows. Kinases are grouped by family; rows are hierarchically clustered within each group. FSH, follicle-stimulating hormone; TSH, thyroid-stimulating hormone.

Phosphorylation signatures of key kinases were altered across many tissues (Fig. 3b and Supplementary Table 8 ). This included AKT1 across heart, kidney and lung, mTOR across heart, kidney and white adipose tissue, and MAPK across heart and kidney. The liver showed an increase in the phosphosignature related to regulators of hepatic regeneration, including EGFR1, IGF and HGF (Extended Data Fig. 6b , Supplementary Discussion ). Increased phosphorylation of STAT3 and PXN, HGF targets involved in cell proliferation, suggest a mechanism for liver regeneration in response to exercise (Extended Data Fig. 6c ). In the heart, kinases showed bidirectional changes in their predicted basal activity in response to endurance training (Extended Data Fig. 6d and Supplementary Discussion ). Several AGC protein kinases showed a decrease in predicted activity, including AKT1, whereas tyrosine kinases, including SRC and mTOR, were predicted to have increased activity. The known SRC target phosphorylation sites GJA1 pY265 and CDH2 pY820 showed significantly increased phosphorylation in response to training (Extended Data Fig. 6e ). Notably, phosphorylation of GJA1 Y265 has previously been shown to disrupt gap junctions, key transducers of cardiac electrical conductivity 20 . This suggests that SRC signalling may regulate extracellular structural remodelling of the heart to promote physiologically beneficial adaptations. In agreement with this hypothesis, gene set enrichment analysis (GSEA) of extracellular matrix proteins revealed a negative enrichment in response to endurance training, showing decreased abundance of proteins such as basement membrane proteins (Extended Data Fig. 6f–h and Supplementary Table 9 ).

Molecular hubs of exercise adaptation

To compare the dynamic multi-omic responses to endurance training across tissues, we clustered the 34,244 differential features with complete timewise summary statistics using an empirical Bayes graphical clustering approach (Methods). By integrating these results onto a graph, we summarize the dynamics of the molecular training response and identify groups of features with similar responses (Extended Data Fig. 7 and Supplementary Table 10 ). We performed pathway enrichment analysis for many graphically defined clusters to characterize putative underlying biology (Supplementary Table 11 ).

We examined biological processes associated with training using the pathway enrichment results for up-regulated features at 8 weeks of training (Extended Data Fig. 8 , Supplementary Table 12 and Supplementary Discussion ). Compared with other tissues, the liver showed substantial regulation of chromatin accessibility, including in the nuclear receptor signalling and cellular senescence pathways. In the gastrocnemius, terms related to peroxisome proliferator-activated receptors (PPAR) signalling and lipid synthesis and degradation were enriched at the protein level, driven by proteins including the lipid droplet features PLIN2, PLIN4 and PLIN5. At the metabolomic level, terms related to ether lipid and glycerophospholipid metabolism were enriched. Together, these enrichments highlight the well-known ability of endurance training to modulate skeletal muscle lipid composition, storage, synthesis and metabolism. The blood displayed pathway enrichments related to translation and organelle biogenesis and maintenance. Paired with the transcription factor analysis (Fig. 3a ), this suggests increased haematopoietic cellular mobilization in the blood. Less studied tissues in the context of exercise training, including the adrenal gland, spleen, cortex, hippocampus and colon, also showed regulation of diverse pathways ( Supplementary Discussion ).

To identify the main temporal or sex-associated responses in each tissue, we summarized the graphical cluster sizes by tissue and time (Extended Data Fig. 7a ). We observed that the small intestine and plasma had more changes at weeks 1 and 2 of training. Conversely, many up-regulated features in brown adipose tissue and down-regulated features in white adipose tissue were observed only at week 8. The largest proportion of opposite effects between males and females was observed at week 1 in the adrenal gland. Other tissues, including the blood, heart, lung, kidney and skeletal muscle (gastrocnemius and vastus lateralis), had relatively consistent numbers of up-regulated and down-regulated features.

We next focused on characterizing shared molecular responses in the three striated muscles (gastrocnemius, vastus lateralis and heart). The three largest graphical clustering paths of differential features in each muscle tissue converged to a sex-consistent response by week 8 (Fig. 4a ). Because of the large number of muscle features that were up-regulated in both sexes at week 8, we further examined the corresponding multi-omic set of analytes (Fig. 4b ). Pathway enrichment analysis of the genes associated with these differential features demonstrated a sex- and muscle-consistent endurance training response that reflected up-regulation of mitochondrial metabolism, biogenesis and translation, and cellular response to heat stress (Fig. 4c and Supplementary Table 11 ).

a , Graphical representation of training-differential features in the three muscle tissues: gastrocnemius (SKM-GN), vastus lateralis (SKM-VL) and heart. Each node represents one of nine possible states (rows) at each of the four training time points (columns). Triangles to the left of row labels map states to symbols used in Fig. 5a . Edges represent the path of differential features over the training time course (see Extended Data Fig. 7 for a detailed explanation). Each graph includes the three largest paths of differential features in that tissue, with edges split by data type. Both node and edge size are proportional to the number of features represented. The node corresponding to features that are up-regulated in both sexes at 8 weeks of training (8w_F1_M1) is circled in each graph. b , Line plots of standardized abundances of all 8w_F1_M1 muscle features. The black line represents the average value across all features. c , Network view of significant pathway enrichment results (10% FDR) corresponding to the features in b . Nodes represent pathways; edges represent functionally similar node pairs (set similarity ≥ 0.3). Nodes are included only if they are significantly enriched in at least two of the muscle tissues, as indicated by node colour. Node size is proportional to the number of differential feature sets (for example, gastrocnemius transcripts) for which the pathway is significantly enriched. High-level biological themes were defined using Louvain community detection of the nodes. d , A subnetwork of a larger cluster identified by network clustering 8w_F1_M1 features from SKM-GN. Mech., mechanical.

We used a network connectivity analysis to study up-regulated features in the gastrocnemius at week 8 (Extended Data Fig. 9a,b , Methods and Supplementary Discussion ). Mapping features to genes revealed overlaps between transcriptomic, chromatin accessibility, and proteomic assays, but no overlaps with methylation. Three molecular interaction networks were compared (Methods), and BioGRID 21 was used for further clustering analysis, which identified three clusters (Extended Data Fig. 9c and Supplementary Table 13 ). The largest cluster was significantly enriched for multiple muscle adaptation processes (Fig. 4d and Supplementary Table 14 ). This analysis illustrates the direct linkage among pathways and putative central regulators, emphasizing the importance of multi-omic data in identifying interconnected networks and understanding skeletal muscle remodelling.

Connection to human diseases and traits

To systematically evaluate the translational value of our data, we integrated our results with extant exercise studies and disease ontology (DO) annotations (Methods). First, we compared our vastus lateralis transcriptomics results to a meta-analysis of long-term training gene-expression changes in human skeletal muscle tissue 8 , demonstrating a significant and direction-consistent overlap (Extended Data Fig. 9d–g and Supplementary Discussion ). We also identified a significant overlap between differential transcripts in the gastrocnemius of female rats trained for 8 weeks and differentially expressed genes identified in the soleus in a study of sedentary and exercise-trained female rats selectively bred for high or low exercise capacity 22 (Extended Data Fig. 9h ). Similarly, adaptations from high-intensity interval training in humans 23 significantly overlapped with the proteomics response in rats (Extended Data Fig. 9i ), particularly for female rats trained for 8 weeks (Extended Data Fig. 9j ). Finally, we performed DO enrichment analysis using the DOSE R package 24 (Supplementary Table 15 and Methods). Down-regulated genes from white adipose tissue, kidney and liver were enriched for several disease terms, suggesting a link between the exercise response and type 2 diabetes, cardiovascular disease, obesity and kidney disease (5% FDR; Extended Data Fig. 9k and Supplementary Discussion ), which are all epidemiologically related co-occurring diseases 25 . Overall, these results support a high concordance of our data from rats with human studies and their relevance to human disease.

Sex-specific responses to exercise

Many tissues showed sex differences in their training responses (Extended Data Fig. 10 ), with 58% of the 8-week training-regulated features demonstrating sex-differentiated responses. Opposite responses between the sexes were observed in adrenal gland transcripts, lung phosphosites and chromatin accessibility features, white adipose tissue transcripts and liver acetylsites. In addition, proinflammatory cytokines exhibited sex-associated changes across tissues (Extended Data Fig. 11a,b and Supplementary Table 16 ). Most female-specific cytokines were differentially regulated between weeks 1 and 2 of training, whereas most male-specific cytokines were differentially regulated between weeks 4 and 8 (Extended Data Fig. 11c ).

We observed extensive transcriptional remodelling of the adrenal gland, with more than 4,000 differential genes. Notably, the largest graphical path of training-regulated features was negatively correlated between males and females, with sustained down-regulation in females and transient up-regulation at 1 week in males (Extended Data Fig. 11d ). The genes in this path were also associated with steroid hormone synthesis pathways and metabolism, particularly those pertaining to mitochondrial function (Supplementary Table 11 ). Further, transcription factor motif enrichment analysis of the transcripts in this path showed enrichment of 14 transcription factors (5% FDR; Supplementary Table 17 ), including the metabolism-regulating factors PPARγ, PPARα and oestrogen-related receptor gamma (ERRγ). The gene-expression levels of several significantly enriched transcription factors themselves followed the same trajectory as this path (Extended Data Fig. 11e ).

In the rat lung, we observed decreased phosphosignalling activity with training primarily in males (Fig. 3b ). Among these, the PRKACA phosphorylation signature showed the largest sex difference at 1 and 2 weeks (Extended Data Fig. 11f–h and Supplementary Table 8 ). PRKACA is a kinase that is involved in signalling within multiple cellular pathways. However, four PRKACA substrates followed this pattern and were associated with cellular structures (such as cytoskeleton and cell–cell junctions): DSP, MYLK, STMN1 and SYNE1 (Extended Data Fig. 11i ). The phosphorylation of these proteins suggests a sex-dependent role of PRKACA in mediating changes in lung structure or mechanical function with training. This is supported as DSP and MYLK have essential roles in alveolar and epithelial cell remodelling in the lung 26 , 27 .

Immune pathway enrichment analysis of training-regulated transcripts at 8 weeks showed limited enrichment in muscle (heart, gastrocnemius and vastus lateralis) and brain (cortex, hippocampus, hypothalamus), down-regulation in the lung and small intestine, and strong up-regulation in brown and white adipose tissue in males only (Fig. 5a , Extended Data Fig. 12a and Supplementary Table 11 ). Many of the same immune pathways (Supplementary Table 18 ) and immune-related transcription factors (Supplementary Table 19 ) were enriched in both adipose tissues in males. Furthermore, correlation between the transcript expression profiles of male-specific up-regulated features in the adipose tissues and immune cell markers from external cell-typing assays revealed a strong positive correlation for many immune cell types, including B, T and natural killer cells, and low correlation with platelets, erythrocytes and lymphatic tissue (Fig. 5b,c , Methods and Supplementary Table 20 ). These patterns suggest recruitment of peripheral immune cells or proliferation of tissue-resident immune cells as opposed to non-biological variation in blood or lymph content. Correlations at the protein level were not as marked (Extended Data Fig. 12b,c ). Complementary analyses using CIBERTSORTx produced similar results (Extended Data Fig. 12d,e ). In summary, our data suggest an important role of immune cell activity in the adaptation of male adipose tissue to endurance training.

a , Enrichment analysis results of the training-differential transcripts at 8 weeks in Kyoto Encyclopedia of Genes and Genomes (KEGG) immune system pathways (10% FDR). NK, natural killer. b , Line plots of standardized abundances of selected training-differential transcripts. Brown and white adipose tissue show male-specific up-regulation at week 8 (8w_F0_M1). The small intestine (SMLINT) shows down-regulation in females and partial down-regulation in males at week 8 (8w_F-1_M0 or 8w_F-1_M-1). c , Box plots of the sample-level Pearson correlation between markers of immune cell types, lymphatic tissue or cell proliferation and the average value of features in b at the transcript level. A pink dot indicates that the marker is also one of the differential features plotted in b . A pound sign indicates that the distribution of Pearson correlations for a set of at least two markers is significantly different from 0 (two-sided one-sample t -test, 5% FDR). When only one marker is used to define a category on the y axis, the gene name is provided in parentheses. In box plots, the centre line represents median, box bounds represent 25th and 75th percentiles, whiskers represent minimum and maximum excluding outliers and blue dots represent outliers.

The small intestine was among the tissues with the highest enrichment in immune-related pathways (Extended Data Fig. 12a ), with down-regulation of transcripts at 8 weeks, and a more robust response in females (Fig. 5b ). This transcript set was significantly enriched with pathways related to gut inflammation (Supplementary Table 11 ). We observed positive associations between these transcripts and markers of several immune cell types, including B, T, natural killer and dendritic cells, suggesting decreased abundance (Fig. 5c and Supplementary Discussion ). Endurance training also decreased the expression of transcripts with genetic risk loci for inflammatory bowel disease (IBD), including major histocompatability complex class II 28 , a finding that also emerged through the DO enrichment analysis (Supplementary Table 15 ). Endurance training is suggested to reduce systemic inflammation, in part by increasing gut microbial diversity and gut barrier integrity 29 . In accordance, we observed decreases in Cxcr3 and Il1a with training (Extended Data Fig. 12f ), both of which are implicated in the pathogenesis of IBD 30 , 31 . Together, these data suggest that endurance training improves gut homeostasis, potentially conferring systemic anti-inflammatory effects.

Multi-tissue changes in mitochondria and lipids

We summarized the organism-wide metabolic changes for metabolomic datasets using RefMet metabolite classes (Fig. 6a and Supplementary Table 21 ) and for non-metabolomics datasets using metabolic subcategories of KEGG pathways (10% FDR; Extended Data Fig. 13a and Supplementary Table 11 ). The liver showed the greatest number of significantly enriched metabolite classes, followed by the heart, lung and hippocampus (Fig. 6a and Supplementary Discussion ). Inspection of individual metabolites and acylcarnitine groups revealed changes associated with functional alterations in response to training (Extended Data Fig. 13b–d and Supplementary Discussion ). Of particular interest, trimethylamine- N -oxide has been associated with cardiovascular disease 32 . We observed up-regulation of 1-methylhistidine, a marker of muscle protein turnover, in the kidney at 1, 2 and 4 weeks, which may indicate muscle breakdown and clearance through the kidney during early training time points. Cortisol levels were increased as expected from the physiological stress of training, and we observed a substantial increase in the kidney, again probably owing to renal clearance 33 . The liver showed up-regulation of 1-methylnicotinamide, which may have a role in inflammation 34 , at 8 weeks.

a , RefMet metabolite class enrichment calculated using GSEA with the −log 10 training P value. Significant chemical class enrichments (5% FDR) are shown as black circles with size is proportional to FDR. Small grey circles are chemical class enrichments that were not significant, and blank cells were not tested owing to low numbers of detected metabolites. TCA, tricarboxylic acid cycle. b , GSEA results using the MitoCarta MitoPathways gene set database and proteomics (PROT) or acetylome (ACETYL) timewise summary statistics for training. NESs are shown for significant pathways (10% FDR). Mitochondrial pathways shown as rows are grouped using the parental group in the MitoPathways hierarchy. OXPHOS, oxidative phosphorylation. c , Line plots of standardized abundances of liver training-differential features across all data types that are up-regulated in both sexes, with a later response in females (LIVER: 1w_F0_M1 − >2w_F0_M1 − >4w_F0_M1 − >8w_F1_M1). The black line represents the average value across all features. d , Network view of pathway enrichment results corresponding to features in c . Nodes indicate significantly enriched pathways (10% FDR); edges connect nodes if there is a similarity score of at least 0.375 between the gene sets driving each pathway enrichment. Node colours indicate omes in which the enrichment was observed. e , log 2 fold changes (logFC) relative to sedentary controls for metabolites within the ‘Lipids and lipid related compounds’ category in the 8-week liver. Heat map colour represents fold change (red, positive; blue, negative). Compounds are grouped into columns based on category (coloured bars).

The heart showed enrichment of various carbohydrate metabolism subcategories across many omes (Extended Data Fig. 13a ), and remarkably, all enzymes within the glycolysis–gluconeogenesis pathway showed a consistent increase in abundance, except for GPI, FBP2 and DLAT (Extended Data Fig. 13e ). Oxidative phosphorylation was enriched in most tissues and is consistent with the joint analyses of the muscle tissues (Fig. 4c ), suggesting potential changes in mitochondria biogenesis. We estimated proportional mitochondrial changes to endurance training using mitochondrial RNA-sequencing (RNA-seq) reads (Extended Data Fig. 14a–c ) and changes of mitochondrial functions through GSEA using gene expression, protein abundance and protein PTMs (Fig. 6b , Extended Data Fig. 14d and Supplementary Tables 22 – 25 ). Increased mitochondrial biogenesis was observed in skeletal muscle, heart and liver across these analyses. Moreover, sex-specific mitochondrial changes were observed in the adrenal gland, as described above, and in the colon, lung and kidney. These results highlight a highly adaptive and pervasive mitochondrial response to endurance training; a more in-depth analysis of this response is provided elsewhere 35 .

In the liver, we observed substantial regulation of metabolic pathways across the proteome, acetylome and lipidome (Fig. 6a,b and Extended Data Fig. 13a ). For example, there was significant enrichment in 12 metabolite classes belonging to ‘lipids and lipid-related compounds’ (Fig. 6a and Supplementary Table 26 ). We therefore focused on the large group of features that increased in abundance over time for both sexes (Fig. 6c ). Most of these liver features corresponded to protein abundance and protein acetylation changes in the mitochondrial, amino acid and lipid metabolic pathways (Fig. 6d and Supplementary Table 27 ). We also observed an increase in phosphatidylcholines and a concomitant decrease in triacylglycerols (Fig. 6e ). Finally, there was increased abundance and acetylation of proteins from the peroxisome, an organelle with key functions in lipid metabolism (Extended Data Fig. 14e ). To our knowledge, these extensive changes in protein acetylation in response to endurance training have not been described previously. Together, these molecular adaptations may constitute part of the mechanisms underlying exercise-mediated improvements in liver health, particularly protection against excessive intrahepatic lipid storage and steatosis 36 .

Mapping the molecular exercise responses across a whole organism is critical for understanding the beneficial effects of exercise. Previous studies are limited to a few tissues, a narrow temporal range, or a single sex. Substantially expanding on the current work in the field, we used 25 distinct molecular platforms in as many as 19 tissues to study the temporal changes to endurance exercise training in male and female rats. Accordingly, we identified thousands of training-induced changes within and across tissues, including temporal and sex-biased responses, in mRNA transcripts, proteins, post-translational modifications and metabolites. Each omic dataset provides unique insights into exercise adaptation, where a holistic understanding requires multi-omic analysis. This work illustrates how mining our data resource can both recapitulate expected mechanisms and provide novel biological insights.

This work can be leveraged to deepen our understanding of exercise-related improvement of health and disease management. The global heat shock response to exercise may confer cytoprotective effects, including in pathologies related to tissue damage and injury recovery 37 . Increased acetylation of liver mitochondrial enzymes and regulation of lipid metabolism may link exercise to protection against non-alcoholic fatty liver disease and steatohepatitis 36 . Similarly, exercise-mediated modulation of cytokines, receptors and transcripts linked to intestinal inflammation or IBD may be associated with improved gut health. These examples highlight unique training responses illuminated by a multi-omics approach that can be leveraged for future hypothesis-driven research on how exercise improves whole-body and tissue-specific health.

We note limitations in our experimental design, datasets and analyses ( Supplementary Discussion ). In short, samples were collected 48 h after the last exercise bout to capture sustained alterations, thereby excluding acute responses. Our assays were performed on bulk tissue and do not cover single-cell platforms. Our resource has limited omic characterization for certain tissues, and additional platforms with emerging biological relevance were not utilized, including microbiome profiling. Moreover, our results are hypothesis-generating and require biological validation; supporting this, we have established a publicly accessible tissue bank from this study.

This MoTrPAC resource provides future opportunities to enhance and refine the molecular map of the endurance training response. We expect that this dataset will remain an ongoing platform to translate tissue- and sex-specific molecular changes in rats to humans. MoTrPAC has made extensive efforts to facilitate access, exploration and interpretation of this resource. We developed the MoTrPAC Data Hub to easily explore and download data ( https://motrpac-data.org/ ), software packages to provide reproducible source code and facilitate data retrieval and analysis in R (MotrpacRatTraining6mo and MotrpacRatTraining6moData 38 , 39 ), and visualization tools for data exploration ( https://data-viz.motrpac-data.org ). Altogether, this multi-omic resource serves as a broadly useful reference for studying the milieu of molecular changes in endurance training adaptation and provides new opportunities to understand the effects of exercise on health and disease.

All methods are included in the Supplementary Information .

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

MoTrPAC data are publicly available via http://motrpac-data.org/data-access . Data access inquiries should be sent to [email protected]. Additional resources can be found at http://motrpac.org and https://motrpac-data.org/ . Interactive data visualizations are provided through a website ( https://data-viz.motrpac-data.org ) and HTML reports summarizing the multi-omic graphical analysis results in each tissue 40 . Processed data and analysis results are additionally available in the MotrpacRatTraining6moData R package 39 ( https://github.com/MoTrPAC/MotrpacRatTraining6moData ). Raw and processed data for were deposited in the appropriate public repositories as follows. RNA-seq, ATAC-seq and RRBS data were deposited at the Sequence Read Archive under accession PRJNA908279 and at the Gene Expression Omnibus under accession GSE242358 ; multiplexed immunoassays were deposited at IMMPORT under accession SDY2193 ; metabolomics data were deposited at Metabolomics Workbench under project ID PR001020 ; and proteomics data were deposited at MassIVE under accessions MSV000092911 , MSV000092922 , MSV000092923 , MSV000092924 , MSV000092925 and MSV000092931 . We used the following external datasets: release 96 of the Ensembl R. norvegicus (rn6) genome ( https://ftp.ensembl.org/pub/release-96/fasta/rattus_norvegicus/dna/ ) and gene annotation ( https://ftp.ensembl.org/pub/release-96/gtf/rattus_norvegicus/Rattus_norvegicus.Rnor_6.0.96.gtf.gz ); RefSeq protein database ( https://ftp.ncbi.nlm.nih.gov/refseq/R_norvegicus/ , downloaded 11/2018); the NCBI gene2refseq mapping files ( https://ftp.ncbi.nlm.nih.gov/gene/DATA/gene2refseq.gz , accessed 18 December 2020); RGD rat gene annotation ( https://download.rgd.mcw.edu/data_release/RAT/GENES_RAT.txt , accessed 12 November 2021); BioGRID v4.2.193 ( https://downloads.thebiogrid.org/File/BioGRID/Release-Archive/BIOGRID-4.2.193/BIOGRID-ORGANISM-4.2.193.tab3.zip ); STRING v11.5 ( https://stringdb-downloads.org/download/protein.physical.links.v11.5/10116.protein.physical.links.v11.5.txt.gz ); GENCODE release 39 metadata and annotation files ( https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_39/ , accessed 20 January 2022); MatrisomeDB ( https://doi.org/10.1093/nar/gkac1009 ); MitoPathways database available through MitoCarta ( https://personal.broadinstitute.org/scalvo/MitoCarta3.0/ ); PTMSigDB v1.9.0 PTM set database ( https://doi.org/10.1074/mcp.TIR118.000943 ); UniProt human proteome FASTA for canonical protein sequences (UniProtKB query “reviewed:true AND proteome:up000005640”, download date 3 March 2021); the CIBERSORT LM22 leukocyte gene signature matrix ( https://doi.org/10.1007/978-1-4939-7493-1_12 ); published results from Amar et al. 8 , Bye et al. 22 and Hostrup et al. 23 ; and GTEx v8 gene-expression data (dbGaP Accession phs000424.v8.p2). Details are provided in the Supplementary Information , Methods.

Code availability

Code for reproducing the main analyses is provided in the MotrpacRatTraining6mo R package 38 ( https://motrpac.github.io/MotrpacRatTraining6mo/ ). MoTrPAC data processing pipelines for RNA-seq, ATAC-seq, RRBS and proteomics are available in the following Github repositories: https://github.com/MoTrPAC/motrpac-rna-seq-pipeline 41 , https://github.com/MoTrPAC/motrpac-atac-seq-pipeline 42 , https://github.com/MoTrPAC/motrpac-rrbs-pipeline 43 and https://github.com/MoTrPAC/motrpac-proteomics-pipeline 44 . Normalization and quality control scripts are available at https://github.com/MoTrPAC/MotrpacRatTraining6moQCRep 45 .

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Acknowledgements

Funding: The MoTrPAC Study is supported by NIH grants U24OD026629 (Bioinformatics Center), U24DK112349, U24DK112342, U24DK112340, U24DK112341, U24DK112326, U24DK112331, U24DK112348 (Chemical Analysis Sites), U01AR071133, U01AR071130, U01AR071124, U01AR071128, U01AR071150, U01AR071160, U01AR071158 (Clinical Centers), U24AR071113 (Consortium Coordinating Center), U01AG055133, U01AG055137 and U01AG055135 (PASS/Animal Sites). This work was also supported by other funding sources: NHGRI Institutional Training Grant in Genome Science 5T32HG000044 (N.R.G.), National Science Foundation Graduate Research Fellowship Grant No. NSF 1445197 (N.R.G.), National Heart, Lung, and Blood Institute of the National Institute of Health F32 postdoctoral fellowship award F32HL154711 (P.M.J.B.), the Knut and Alice Wallenberg Foundation (M.E.L.), National Science Foundation Major Research Instrumentation (MRI) CHE-1726528 (F.M.F.), National Institute on Aging P30AG044271 and P30AG003319 (N.M.), and NORC at the University of Chicago grant no. P30DK07247 (E.R.). Parts of this work were performed in the Environmental Molecular Science Laboratory, a US Department of Energy national scientific user facility at Pacific Northwest National Laboratory in Richland, WA. The views expressed are those of the authors and do not necessarily reflect those of the NIH or the US Department of Health and Human Services. Some figures were created using Biorender.com. Fig. 1b was modified with permission from ref. 46 .

Author information

These authors contributed equally: David Amar, Nicole R. Gay, Pierre M. Jean-Beltran

These authors jointly supervised this work: Sue C. Bodine, Steven A. Carr, Karyn A. Esser, Stephen B. Montgomery, Simon Schenk, Michael P. Snyder, Matthew T. Wheeler

Authors and Affiliations

Department of Medicine, Stanford University, Stanford, CA, USA

David Amar, David Jimenez-Morales, Malene E. Lindholm, Shruti Marwaha, Archana Natarajan Raja, Jimmy Zhen, Euan Ashley, Matthew T. Wheeler, Karen P. Dalton, Steven G. Hershman, Mihir Samdarshi & Christopher Teng

Department of Genetics, Stanford University, Stanford, CA, USA

Nicole R. Gay, Bingqing Zhao, Jose J. Almagro Armenteros, Nasim Bararpour, Si Wu, Stephen B. Montgomery, Michael P. Snyder, Clarisa Chavez, Roxanne Chiu, Krista M. Hennig, Chia-Jui Hung, Christopher A. Jin & Navid Zebarjadi

Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA

Pierre M. Jean-Beltran, Hasmik Keshishian, Natalie M. Clark, Steven A. Carr, D. R. Mani, Charles C. Mundorff & Cadence Pearce

Department of Internal Medicine, University of Iowa, Iowa City, IA, USA

Dam Bae, Ana C. Lira, Sue C. Bodine, Michael Cicha, Luis Gustavo Oliveira De Sousa, Bailey E. Jackson, Kyle S. Kramer, Andrea G. Marshall & Collyn Z-T. Richards

Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA

Surendra Dasari

Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA

Courtney Dennis, Julian Avila-Pacheco & Clary B. Clish

Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA

Charles R. Evans & Charles F. Burant

School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, USA

David A. Gaul, Evan M. Savage & Facundo M. Fernández

Department of Medicine, Duke University, Durham, NC, USA

Olga Ilkayeva, William E. Kraus & Kim M. Huffman

Duke Molecular Physiology Institute, Duke University, Durham, NC, USA

Olga Ilkayeva, Michael J. Muehlbauer, William E. Kraus, Christopher Newgard, Kim M. Huffman & Megan E. Ramaker

Emory Integrated Metabolomics and Lipidomics Core, Emory University, Atlanta, GA, USA

Anna A. Ivanova, Xueyun Liu & Kristal M. Maner-Smith

BRCF Metabolomics Core, University of Michigan, Ann Arbor, MI, USA

Maureen T. Kachman, Alexander (Sasha) Raskind & Tanu Soni

Division of Endocrinology, Nutrition, and Metabolism, Mayo Clinic, Rochester, MN, USA

Ian R. Lanza

Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Venugopalan D. Nair, Gregory R. Smith, Yongchao Ge, Stuart C. Sealfon, Mary Anne S. Amper, Kristy Guevara, Nada Marjanovic, German Nudelman, Hanna Pincas, Irene Ramos, Stas Rirak, Aliza B. Rubenstein, Frederique Ruf-Zamojski, Nitish Seenarine, Sindhu Vangeti, Mital Vasoya, Alexandria Vornholt, Xuechen Yu & Elena Zaslavsky

Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA

Paul D. Piehowski

Department of Pathology and Laboratory Medicine, University of Vermont, Burlington, VT, USA

Jessica L. Rooney, Russell Tracy, Elaine Cornell, Nicole Gagne & Sandy May

Department of Pathology, Stanford University, Stanford, CA, USA

Kevin S. Smith, Nikolai G. Vetr, Stephen B. Montgomery & Daniel Nachun

Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA

Cynthia L. Stowe, Fang-Chi Hsu, Scott Rushing & Michael P. Walkup

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA

Gina M. Many, James A. Sanford, Joshua N. Adkins, Wei-Jun Qian, Marina A. Gritsenko, Joshua R. Hansen, Chelsea Hutchinson-Bunch, Matthew E. Monroe, Ronald J. Moore, Michael D. Nestor, Vladislav A. Petyuk & Tyler J. Sagendorf

Department of Biochemistry, Emory University, Atlanta, GA, USA

Tiantian Zhang, Zhenxin Hou & Eric A. Ortlund

Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Boston, MA, USA

David M. Presby, Laurie J. Goodyear, Brent G. Albertson, Tiziana Caputo, Michael F. Hirshman, Nathan S. Makarewicz, Pasquale Nigro & Krithika Ramachandran

Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA

Alec Steep & Jun Z. Li

Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Yifei Sun & Martin J. Walsh

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA

Sue C. Bodine

Department of Physiology and Aging, University of Florida, Gainesville, FL, USA

Karyn A. Esser & Marco Pahor

Department of Orthopaedic Surgery, School of Medicine, University of California, San Diego, La Jolla, CA, USA

Simon Schenk

Department of Biomedical Data Science, Stanford University, Stanford, CA, USA

Stephen B. Montgomery

Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA

Gary Cutter

Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA

Robert E. Gerszten & Jeremy M. Robbins

Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA

Michael E. Miller

Department of Medicine, Mayo Clinic, Rochester, MN, USA

K. Sreekumaran Nair

Department of Statistics, Stanford University, Stanford, CA, USA

Trevor Hastie & Rob Tibshirani

Department of Biomedical Data Sciences, Stanford University, Stanford, CA, USA

Rob Tibshirani

Department of Aging and Geriatric Research, University of Florida, Gainesville, FL, USA

Brian Bouverat, Christiaan Leeuwenburgh & Ching-ju Lu

Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA

Barbara Nicklas

Department of Health and Exercise Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA

W. Jack Rejeski

National Institute on Aging, National Institutes of Health, Bethesda, MD, USA

John P. Williams

National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA

Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA

Elisabeth R. Barton

Department of Biomedical Sciences, University of Missouri, Columbia, MO, USA

Frank W. Booth

Department of Medical Pharmacology and Physiology, University of Missouri, Columbia, MO, USA

Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, MO, USA

Frank W. Booth & R. Scott Rector

Dalton Cardiovascular Research Center, University of Missouri, Columbia, MO, USA

Department of Kinesiology and Health Education, University of Texas, Austin, TX, USA

Roger Farrar

Department of Medicine, Division of Endocrinology and Diabetes, University of California, Los Angeles, CA, USA

Andrea L. Hevener

Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA

Benjamin G. Ke & Chongzhi Zang

Section on Clinical, Behavioral, and Outcomes Research, Joslin Diabetes Center, Boston, MA, USA

Sarah J. Lessard

Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA

Andrea G. Marshall

Department of Health Sciences, Stetson University, Deland, FL, USA

Scott Powers

Department of Medicine, University of Missouri, Columbia, MO, USA

R. Scott Rector

NextGen Precision Health, University of Missouri, Columbia, MO, USA

Cell Biology and Physiology, Internal Medicine, University of Kansas Medical Center, Kansas City, KS, USA

John Thyfault

Center for Skeletal Muscle Research at Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA, USA

Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA

Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA, USA

Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA, USA

Fralin Biomedical Research Institute, Center for Exercise Medicine Research at Virginia Tech Carilion, Roanoke, VA, USA

Department of Human Nutrition, Foods, and Exercise, College of Agriculture and Life Sciences, Virginia Tech, Blacksburg, VA, USA

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA

Ali Tugrul Balci & Maria Chikina

Petit Institute of Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, USA

Samuel G. Moore

Department of Medicine, Emory University, Atlanta, GA, USA

Karan Uppal

Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL, USA

Marcas Bamman & Anna Thalacker-Mercer

Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

Bryan C. Bergman, Daniel H. Bessesen, Wendy M. Kohrt, Edward L. Melanson, Kerrie L. Moreau, Irene E. Schauer & Robert S. Schwartz

Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

Thomas W. Buford

Human Performance Laboratory, Ball State University, Muncie, IN, USA

Toby L. Chambers, Bridget Lester, Scott Trappe & Todd A. Trappe

Translational Research Institute, AdventHealth, Orlando, FL, USA

Paul M. Coen, Bret H. Goodpaster & Lauren M. Sparks

Department of Pediatrics, University of California, Irvine, CA, USA

Dan Cooper, Fadia Haddad & Shlomit Radom-Aizik

Pennington Biomedical Research Center, Baton Rouge, LA, USA

Kishore Gadde, Melissa Harris, Neil M. Johannsen, Tuomo Rankinen & Eric Ravussin

College of Nursing, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

Catherine M. Jankowski

Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA

Nicolas Musi

Population and Public Health, Pennington Biomedical Research Center, Baton Rouge, LA, USA

Robert L. Newton Jr

Biochemistry and Structural Biology, Center for Metabolic Health, Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center, San Antonio, TX, USA

Blake B. Rasmussen

Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center, San Antonio, TX, USA

Elena Volpi

MoTrPAC Study Group

Primary authors

Lead Analysts

, Nicole R. Gay
, Pierre M. Jean-Beltran

Lead Data Generators

, Surendra Dasari
, Courtney Dennis
, Charles R. Evans
, David A. Gaul
, Olga Ilkayeva
, Anna A. Ivanova
, Maureen T. Kachman
, Hasmik Keshishian
, Ian R. Lanza
, Ana C. Lira
, Michael J. Muehlbauer
, Venugopalan D. Nair
, Paul D. Piehowski
, Jessica L. Rooney
, Kevin S. Smith
, Cynthia L. Stowe
& Bingqing Zhao
Natalie M. Clark
, David Jimenez-Morales
, Malene E. Lindholm
, Gina M. Many
, James A. Sanford
, Gregory R. Smith
, Nikolai G. Vetr
, Tiantian Zhang
, Bingqing Zhao
, Jose J. Almagro Armenteros
, Julian Avila-Pacheco
, Nasim Bararpour
, Yongchao Ge
, Zhenxin Hou
, Shruti Marwaha
, David M. Presby
, Archana Natarajan Raja
, Evan M. Savage
, Alec Steep
, Yifei Sun
, Si Wu
& Jimmy Zhen

Animal Study Leadership

, Karyn A. Esser
, Laurie J. Goodyear
& Simon Schenk

Manuscript Writing Group Leads

Nicole R. Gay
& David Amar

Manuscript Writing Group

Malene E. Lindholm
, Simon Schenk
, Stephen B. Montgomery
, Sue C. Bodine
, Facundo M. Fernández
, Stuart C. Sealfon
, Michael P. Snyder
& Tiantian Zhang

Senior Leadership

Joshua N. Adkins
, Euan Ashley
, Charles F. Burant
, Steven A. Carr
, Clary B. Clish
, Gary Cutter
, Robert E. Gerszten
, William E. Kraus
, Jun Z. Li
, Michael E. Miller
, K. Sreekumaran Nair
, Christopher Newgard
, Eric A. Ortlund
, Wei-Jun Qian
, Russell Tracy
, Martin J. Walsh
& Matthew T. Wheeler

Co-corresponding Authors

Bioinformatics center.

, Karen P. Dalton
, Trevor Hastie
, Steven G. Hershman
, Mihir Samdarshi
, Christopher Teng
, Rob Tibshirani
, Matthew T. Wheeler

Biospecimens Repository

Elaine Cornell
, Nicole Gagne
, Sandy May
& Russell Tracy

Administrative Coordinating Center

Brian Bouverat
, Christiaan Leeuwenburgh
, Ching-ju Lu
& Marco Pahor

Data Management, Analysis, and Quality Control Center

Fang-Chi Hsu
, Scott Rushing
& Michael P. Walkup

Exercise Intervention Core

& W. Jack Rejeski
& Ashley Xia

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All authors reviewed and revised the manuscript. Detailed author contributions are provided in the Supplementary Information .

Corresponding authors

Correspondence to Sue C. Bodine , Karyn A. Esser , Simon Schenk , Stephen B. Montgomery , Michael P. Snyder , Steven A. Carr or Matthew T. Wheeler .

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Competing interests.

S.C.B. has equity in Emmyon, Inc. G.R.C. sits on data and safety monitoring boards for AI Therapeutics, AMO Pharma, Astra-Zeneca, Avexis Pharmaceuticals, Biolinerx, Brainstorm Cell Therapeutics, Bristol Meyers Squibb/Celgene, CSL Behring, Galmed Pharmaceuticals, Green Valley Pharma, Horizon Pharmaceuticals, Immunic, Mapi Pharmaceuticals, Merck, Mitsubishi Tanabe Pharma Holdings, Opko Biologics, Prothena Biosciences, Novartis, Regeneron, Sanofi-Aventis, Reata Pharmaceuticals, NHLBI (protocol review committee), University of Texas Southwestern, University of Pennsylvania, Visioneering Technologies, Inc.; serves on consulting or advisory boards for Alexion, Antisense Therapeutics, Biogen, Clinical Trial Solutions LLC, Genzyme, Genentech, GW Pharmaceuticals, Immunic, Klein-Buendel Incorporated, Merck/Serono, Novartis, Osmotica Pharmaceuticals, Perception Neurosciences, Protalix Biotherapeutics, Recursion/Cerexis Pharmaceuticals, Regeneron, Roche, SAB Biotherapeutics; and is the president of Pythagoras Inc., a private consulting company. S.A.C. is a member of the scientific advisory boards of Kymera, PrognomiQ, PTM BioLabs, and Seer. M.P.S. is a cofounder and scientific advisor to Personalis, Qbio, January AI, Filtricine, SensOmics, Protos, Fodsel, Rthm, Marble and scientific advisor to Genapsys, Swaz, Jupiter. S.B.M. is a consultant for BioMarin, MyOme and Tenaya Therapeutics. D.A. is currently employed at Insitro, South San Francisco, CA. N.R.G. is currently employed at 23andMe, Sunnyvale, CA. P.M.J.B. is currently employed at Pfizer, Cambridge, MA. Insitro, 23andMe and Pfizer had no involvement in the work presented here.

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Extended data figures and tables

Extended data fig. 1 animal phenotyping and data availability..

a-d) Clinical measurements before and after the training intervention in untrained control rats (SED), 4-week trained rats (4w), and 8-week trained rats (8w). Data are displayed pre and post for each individual rat (connected by a line), with males in blue and females in pink. Filled symbols (n = 5 per sex and time point) represent rats used for all omics analyses, whereas the rat utilized for proteomics only (n = 1 per sex and time point) is represented by a non-filled symbol. Significant results by ANOVA of the overall group effect (#, p < 0.05; ##, p < 0.01) and interaction between group and time (§, p < 0.05; §§ p < 0.01) are indicated. Significant within-group differential responses from a Bonferroni post hoc test are indicated (*, q-value < 0.05; **, q-value < 0.01). a) Aerobic capacity through a VO 2 max test until exhaustion. Data are reported in ml/(kg.min) for all individual rats and time points. b) Body fat percentage. c) Percent lean mass. ( b-c ) were assessed through nuclear magnetic resonance spectroscopy. d) Body weight (in grams). e) Description of available datasets. Colored cells indicate that data are available for that tissue and assay. Individual panels and platforms are shown for metabolomics and the multiplexed immunoassays. f) Detailed availability of sample-level data across assays. Each column represents an individual animal, ordered by training group and colored by sex. Gray cells indicate that data were generated for that animal and assay; black cells indicate that data were not generated. Rows are ordered by ome and colored by assay and tissue.

Extended Data Fig. 2 Quality control metrics for omics data.

a) Proteomics multiplexing design using TMT11 reagents for isobaric tagging and a pooled reference sample. The diagram describes processing of a single tissue. Following multiplexing, peptides were used for protein abundance analysis, serial PTM enriched for phosphosite and optional acetylsite quantification, or ubiquitylsite quantification through enrichment of lysine-diglycine ubiquitin remnants. b) Total number of fully quantified proteins per plex in each global proteome dataset. c-e) The total number of fully quantified phosphosites (c) , acetylsites (d) , and ubiquitylsites (e) per plex in each dataset. f) Distributions of coefficients of variation (CVs) calculated from metabolomics features identified in pooled samples and analyzed periodically throughout liquid chromatography-mass spectrometry runs. CVs were aggregated and plotted separately for named and unnamed metabolites. g) Transcription start site (TSS) enrichment (top) and fraction of reads in peaks (FRiP, bottom) across ATAC-seq samples per tissue. h) Distributions of RNA integrity numbers (RIN, top) and median 5′ to 3′ bias (bottom) across samples in each tissue in the RNA-Seq data. i) Percent methylation of CpG, CHG and CHH sites in the RRBS data. For boxplots in (h,i) : center line represents median; box bounds represent 25th and 75th percentiles; whiskers represent minimum and maximum excluding outliers; filled dots represent outliers. j) Number of wells across multiplexed immunoassays with fewer than 20 beads. Measurements from these 182 wells were excluded from downstream analysis. k) 2D density plot of targeted analytes’ mean fluorescence intensity (MFI) versus corresponding CHEX4 MFI from the same well for each multiplexed immunoassay measurement, where CHEX4 is a measure of non-specific binding.

Extended Data Fig. 3 Permutation tests.

a-b) Permutation tests of groups within males (a) and females (b) . For each sex, the original group labels were shuffled to minimize the number of animal pairs that remain in the same group. Only the group labels were shuffled and all other covariates remained as in the original data. For each permuted dataset, the differential abundance pipeline was rerun and the number of transcripts that were selected at 5% FDR adjustment were re-counted. c-d) Permutation tests of sex within groups. For each group and each sex, half of the animals were selected randomly and their sex was swapped. Only the sex labels were shuffled and all other covariates remained as in the original data. For each permutation the differential analysis pipeline was rerun and the timewise summary statistics were extracted. A gene was considered sexually dimorphic if for at least one time point the z-score (absolute) difference between males and females was greater than 3. c) Counts of sexually dimorphic genes among the IHW-selected genes of the original data. d) Counts of sexually dimorphic genes among the 5% FDR selected genes within each permuted dataset. Each boxplot in (a-d) represents the differential abundance analysis results over 100 permutations of the transcriptomics data in a specific tissue. Center line represents median; box bounds represent 25th and 75th percentiles; whiskers represent minimum and maximum excluding outliers; open circles represent outliers. Added points represent the results of the true data labels, and their shape corresponds to the empirical p-value ( ● : p > 0.05; ×: 0.01 < p < 0.05; *: p ≤ 0.01).

Extended Data Fig. 4 Correlations between proteins and transcripts throughout endurance training.

a) Number of tissues in which each gene, including features mapped to genes from all omes, is training-regulated. Only differential features from the subset of tissues with deep molecular profiling (lung, gastrocnemius, subcutaneous white adipose, kidney, liver, and heart) and the subset of omes that were profiled in all six of these tissues (DNA methylation, chromatin accessibility, transcriptomics, global proteomics, phosphoproteomics, multiplexed immunoassays) were considered. Numbers above each bar indicate the number of genes that are differential in exactly the number of tissues indicated on the x-axis. b) Pathways significantly enriched by tissue-specific training-regulated genes represented in Fig. 2a (q-value < 0.1). KEGG and Reactome pathways were queried, and redundant pathways were removed (i.e., those with an overlap of 80% or greater with an existing pathway). c) Heatmaps showing the Pearson correlation between the TRNSCRPT and PROT timewise summary statistics (z- and t-scores, respectively) (top, gene-level) and pathway-level enrichment results (Gene Set Enrichment Analysis normalized enrichment scores) (bottom, pathway-level). d) Scatter plots of pathway GSEA NES of the TRNSCRPT and PROT datasets in the seven tissues for which these data were acquired. Pathways showing high discordance or agreement across TRNSCRPT and PROT and with functional relevance or general interest were highlighted.

Extended Data Fig. 5 Heat shock response.

a) Scatter plots of the protein t-scores (PROT) versus the transcript z-scores (TRNSCRPT) by gene at 8 weeks of training (8 W) relative to sedentary controls. Data are shown for the seven tissues for which both proteomics and transcriptomics was acquired. Red points indicate genes associated with the heat shock response, and the labeled points indicate those with a large differential response at the protein level. b-c) Line plots showing protein b) and transcript (c) log 2 fold-changes relative to the untrained controls for a subset of heat shock proteins with increased abundance during exercise training. Each line represents a protein in a single tissue.

Extended Data Fig. 6 Regulatory signaling pathways modulated by endurance training.

a) Heatmap of differences in TF motif enrichment in training-regulated genes across tissues. Each value reflects the average difference in motif enrichment for shared transcription factors. Tissues are clustered with complete linkage hierarchical clustering. b) (left) Filtered PTM-SEA results for the liver showing kinases and signaling pathways with increased activity. (right) Heatmap showing t-scores for phosphosites within the HGF signaling pathway. c) Hypothetical model of HGF signaling effects during exercise training. Phosphorylation of STAT3 and PXN is known to modulate cell growth and cell migration, respectively. Error bars=SEM. d) Filtered PTM-SEA results for the heart showing selected kinases with significant enrichments in at least one time point. Heatmap shows the NES as color and enrichment p-value as dot size. Kinases are grouped by kinase family and sorted by hierarchical clustering. e) (top) Log 2 fold-change of GJA1 and CDH2 protein abundance in the heart. No significant response to exercise training was observed for these proteins (F-test; q-value > 0.05). (bottom) Log 2 fold-changes for selected Src kinase phosphosite targets, GJA1 pY265 and CDH2 pY820, in the heart. These phosphosites show a significant response to exercise training (F-test, 5% FDR). Error bars=SEM. f) Gene Set Enrichment Analysis (GSEA) results from the heart global proteome dataset using the matrisome gene set database. Heatmap shows NES as color and enrichment p-value as dot size. Rows are clustered using hierarchical clustering. g) Log 2 fold-change for basement membrane proteins in heart. Proteins showing a significant response to exercise training are highlighted in orange (F-test; 5% FDR). Error bars=SEM. h) Log 2 protein fold-change of NTN1 protein abundance in heart. A significant response to exercise training was observed for these proteins (F-test; 5% FDR). Error bars=SEM.

Extended Data Fig. 7 Graphical representation of differential results.

a) Number of training-regulated features assigned to groups of graphical states across tissues and time. Red points indicate features that are up-regulated in at least one sex (e.g., only in males: F0_M1; only in females: F1_M0; in both sexes: F1_M1), and blue points indicate features down-regulated in at least one sex (only in males: F0_M-1; only in females: F-1_M0; in both sexes: F-1_M-1). Green points indicate features that are up-regulated in males and down-regulated in females or vice versa (F-1_M1 and F1_M-1, respectively). Point size is proportional to the number of features. Point opacity is proportional to the within-tissue fraction of features represented by that point. Features can be represented in multiple points. The number of omes profiled in each tissue is provided in parentheses next to the tissue abbreviation. b) A schematic example of the graphical representation of the differential analysis results. Top: the z-scores of four features. A positive score corresponds to up-regulation (red), and a negative score corresponds to down regulation (blue). Bottom: the assignment of features to node sets and full path sets (edge sets are not shown for conciseness but can be easily inferred from the full paths). Node labels follow the [time]_F[x]_M[y] format where [time] shows the animal sacrifice week and can take one of (1w, 2w, 4w, or 8w), and [x] and [y] are one of (−1,0,1), corresponding to down-regulation, no effect, and up-regulation, respectively. c) Graphical representation of the feature sets. Columns are training time points, and rows are the differential abundance states. Node and edge sizes are proportional to the number of features that are assigned to each set.

Extended Data Fig. 8 Key pathway enrichments per tissue.

Key pathway enrichments for features that are up-regulated in both sexes at 8 weeks of training in each tissue. For display purposes, enrichment q-values were floored to 1e-10 (Enrichment FDR (−log10) = 10). Bars are colored by the number of omes for which the pathway was significantly enriched (q-value < 0.01) (lighter gray: 1 ome; darker gray: 2 omes; black: 3 omes). Pathways were selected from Supplementary Table 10 .

Extended Data Fig. 9 Associations with signatures of human health and complex traits.

a) Jaccard coefficients between gene sets identified by different omes in 8-week gastrocnemius up-regulated features (“X” marks overlap p > 0.05). b) Network connectivity p-values (Pathways, Biogrid, and string) among the gastrocnemius week-8 multi-omic genes and with the single-omic genes. c) Proportion of features from each ome represented in the gastrocnemius response clusters, identified by the network clustering analysis. d-g) Overlap between our rat vastus lateralis differential expression results and the meta-analysis of human long-term exercise studies by Amar et al. d-e) Spearman correlation (d) and its significance (e) between the meta-analysis fold-changes and the log 2 fold-changes foreach sex and time point. f) GSEA results. Genes were ranked by meta-analysis (−log 10 p-value*log 2 fold-change) and the rat training-differential, sex-consistent gene sets were tested for enrichment at the bottom of the ranking (negative scores) or the top (positive scores). g) Overlap between the rat gene sets from (f) and the high-heterogeneity human meta-analysis genes (I 2 > 75%). h) -log 10 overlap p-values (Fisher’s exact test), comparing rat female gastrocnemius and vastus lateralis week-8 differential transcripts from this study (p < 0.01) and the differential genes from the rat female soleus data of Bye et al. (p < 0.01). HCR: high capacity runners, LCR: low capacity runners. i) A comparison of rat gastrocnemius differential proteins from this study (p < 0.01) and the human endurance training proteomics results of Hostrup et al. (p < 0.01) using Fisher’s exact test. Left: -log 10 overlap p-values. Right: -log 10 sex concordance p-values. j) Statistics of the overlapping proteins from ( i ), week-8 female comparison (y: rat z-scores, x: human t-scores). k) DOSE disease enrichment results of the white adipose, kidney, and liver gene sets. DOSE was applied only on diseases that are relevant for each tissue. The network shows the results for the sex-consistent down-regulated features at week-8.

Extended Data Fig. 10 Characterization of the extent of sex difference in the endurance training response.

The extent of sex differences in the training response were characterized in two ways: first, by correlating log 2 fold-changes between males and females for each training-differential feature; second, by calculating the difference between the area under the log 2 fold-change curve for each training-differential feature, including a (0,0) point (Δ AUC , males - females). The first approach characterizes differences in direction of effect while the second approach characterizes differences in magnitude. Left plot for each tissue: density line plots of correlations from the first approach. Densities or correlations corresponding to features in each ome are plotted separately, with a label that provides the ome and the number of differential features represented. Right plot for each tissue: 2D density plot of Δ AUC against the correlation between the male and female log 2 fold-changes for each training-differential feature used to simultaneously evaluate sex differences in the direction and magnitude of the training response. Points at the top-center of these 2D density plots represent features with high similarity between males and females in terms of both direction and magnitude; features on the right and left sides of the plots represent features with greater magnitudes of response in males and females, respectively.

Extended Data Fig. 11 Sex differences in the endurance training response.

a) Heatmap of the training response of immunoassay analytes across tissues. Gray indicates no data. Bars indicate the number of training-regulated analytes in each tissue (top) and the number of tissues in which the analyte is training-regulated (right, 5% FDR). b) Training-differential cytokines across tissues. 5, 24, and 9 cytokines were annotated as anti-, pro-, and pro/anti- inflammatory, respectively. Bars indicate the number of annotated cytokines in each category that are differential (5% FDR). c) Counts of early vs. (1- or 2-week) vs. late (4- or 8-week) differential cytokines, according to states assigned by the graphical analysis, including all tissues. Cytokines with both early and late responses in the same tissue were excluded. d) Line plots of standardized abundances of training-differential features that follow the largest graphical path in the adrenal gland (i.e., 1w_F-1_M1 − >2w_F-1_M0 − >4w_F-1_M0 − >8w_F-1_M0 according to our graphical analysis notation). The black line represents the average value across all features. The closer a colored line is to this average, the darker it is (distance calculated using sum of squares). e) Line plots of transcript-level log 2 fold-changes corresponding to six transcription factors (TFs) whose motifs are significantly enriched by transcripts in (d) . TF motif enrichment q-values are provided in the legend (error bars = SEM). f) Male versus female NES from PTM-SEA in the lung. Anticorrelated points corresponding to PRKACA NES are in dark red. g) Line plots of standardized abundances of training-differential phosphosites that follow the largest graphical edges of phosphosites in the lung (1w_F1_M-1 − >2w_F1_M-1 − >4w_F0_M-1). h) Top ten kinases with the greatest over-representation of substrates (proteins) corresponding to training-differential phosphosites in (g) . MeanRank scores by library are shown, as reported by KEA3. i) Line plots showing phosphosite-level log 2 fold-changes of PRKACA phosphosite substrates identified in the lung as differential with disparate sex responses (error bars = SEM).

Extended Data Fig. 12 Assessment of immune responses to endurance training.

a) Heatmap of the number and percent of KEGG and Reactome immune pathways significantly enriched by training-regulated features at 8 weeks. b) Line plots of standardized abundances of training-differential proteins in white adipose tissue up-regulated only in males at 8 weeks. Black line shows average across all features. c) Boxplots of the sample-level Pearson correlation between markers of immune cell types, lymphatic tissue, or cell proliferation and the average value of features in (b) at the protein level. Center line represents median; box bounds represent 25th and 75th percentiles; whiskers represent minimum and maximum excluding outliers; filled dots represent outliers. A pink point indicates that the marker is also one of the differential features plotted in (b) . # indicates when the distribution of Pearson correlations for a set of at least two markers is significantly different from 0 (two-sided one-sample t-test, 5% BY FDR). When only one marker is used to define a category on the y-axis, the gene name is provided in parentheses. d) Trajectories of mean absolute signal of various immune cell types in BAT or WAT-SC following deconvolution of bulk RNA-Seq with CIBERSORTx (error bars = SEM). e) Immune cell type enrichment analysis results of training-differentially expressed transcripts. Points represent significant enrichments (5% FDR, one-sided Mann-Whitney U test). f) Line plots showing the log 2 fold-changes for Cxcr3 and Il1a transcripts in the small intestine (error bars = SEM).

Extended Data Fig. 13 Metabolic effects of endurance training.

a) Significant enrichments for relevant categories of KEGG metabolism pathways from features that are up- or down- regulated in both sexes at 8 weeks (8w_F1_M1 and 8w_F-1_M-1 nodes, respectively). Triangles point in the direction of the response (up or down). Points are colored by ome. b) Log 2 fold-change of metabolites regulated across many tissues (F-Test, 5% FDR, error bars=SEM). c) Log 2 fold-change of training-regulated metabolites: 1-methylhistidine in the kidney, cortisol in the kidney, and 1-methylnicotinamide in the liver (F-Test, 5% FDR, error bars = SEM). d) Volcano plots showing abundance changes (log 2 fold-changes; logFC) and significance (-log 10 nominal p-values) for acyl-carnitines. Features are colored based on the carnitine chain length. e) Protein abundance changes in the glycolysis and gluconeogenesis pathway in the heart tissue after 8 weeks of training. Line plots show the log 2 fold-changes over the training time course (error bars = SEM). Red and blue boxes indicate a statistically significant (F-test, 5% FDR) increase and decrease in abundance, respectively, for both males and females at 8 weeks.

Extended Data Fig. 14 Mitochondria and peroxisome adaptations to endurance training.

a) Boxplots showing the percent of mitochondrial genome reads across samples in each tissue that map to the mitochondrial genome (% MT reads). b) Comparison of % MT reads between untrained controls and animals trained for 8 weeks. Plot shows tissues with a statistically significant change after 8 weeks in at least one sex (red asterisk, two-sided Dunnett’s test, 10% FDR). For boxplots in (b,c) : center line represents median; box bounds represent 25th and 75th percentiles; whiskers represent minimum and maximum excluding outliers; filled dots represent outliers. c) Boxplots showing the percent of mitochondrial genome reads across tissue, sex, and time points. Center line represents median; box bounds represent 25th and 75th percentiles; whiskers represent minimum and maximum excluding outliers; open circles represent outliers. Red asterisks indicate a significant change throughout the training time course (F-test, 5% FDR). Center line represents median; box bounds represent 25th and 75th percentiles; whiskers represent minimum and maximum excluding outliers; blue dots represent outliers. d) GSEA using the MitoCarta MitoPathways gene set database and transcriptome (TRNSCRPT) or phosphoproteome (PHOSPHO) differential analysis results. NES are shown for significant pathways (10% FDR) for all tissues, sexes, and time points within the heatmap. Mitochondria pathways (rows) are grouped using the parental group in the MitoPathways hierarchy. e) Protein abundance and protein acetylation level changes in the peroxisome KEGG pathway in the liver tissue after 8 weeks of training. Red boxes indicate an increase in abundance for both males and females, while red circles indicate an increase in at least one acetylsite within the protein (8w_F1_M1 cluster).

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MoTrPAC Study Group., Lead Analysts. & MoTrPAC Study Group. Temporal dynamics of the multi-omic response to endurance exercise training. Nature 629 , 174–183 (2024). https://doi.org/10.1038/s41586-023-06877-w

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Rescue teams and volunteers help flood victims.

Alisson Moura/AFP/Getty Images

A man is rescued by military firefighters.

May 4 | Roca Sales, Brazil

A man is rescued after being injured during the floods.

May 3 | Eldorado do Sul, Brazil

Floodwaters overtake the streets.

May 3 | Porto Alegre, Brazil

A man wades through a flooded section of the city.

Carlos Macedo/AP

Residents of coastal islands near the shore of Lake Guaíba carry their belongings after being rescued.

Isaac Fontana/EPA-EFE/Shutterstock

May 2 | Encantado, Brazil

A woman carries two rescued cats.

People and a dog are rescued from the islands of Lake Guaíba.

May 1 | Encantado, Brazil

Houses next to the Taquari River are submerged by floodwaters.

May 1 | Sinimbu, Brazil

A house partially destroyed by heavy rains.

A resident climbs a rescue truck.

May 3 | Encantado, Brazil

A woman walks through mud as she tries to get to her house.

May 2 | Lajeado, Brazil

Two men are rescued by military firefighters.

Jeff Botega/Agencia RBS/Reuters

People throw bags across a puddle as they evacuate flooded areas.

Vehicles covered in mud.

Horses wade through a flooded beach along the Jacui River.

People and their pets are rescued from the flooding.

Renan Mattos/EPA-EFE/Shutterstock

Residents are rescued by the Brazilian army.

Displaced people take shelter in a public facility.

A displaced person rests at a shelter.

Are E.V.s Too Quiet and ‘Boring’?

More from our inbox:, living with roommates in college, tech in the classroom, ‘unpleasant truths’ about russia, water and politics.

A colorful illustration of a meeting room. On a whiteboard is a picture of a very angular and modern yellow car with equations and measurements surrounding it. In the foreground are four meeting participants asleep at the table.

To the Editor:

Re “ Electric Cars Are Boring ,” by Ezra Dyer (Opinion guest essay, April 13):

If E.V.s are boring, I guess I am OK with being bored. As an E.V. owner, I no longer have to stop at the gas station to fill up in all kinds of (Chicago) weather. No more oil changes, no more antifreeze concerns, no muffler or fuel pump problems. Boring is good.

No key or fob to carry, and I can preheat or precool my E.V. in various types of inclement weather.

Now for full disclosure. I bought my first E.V. 10 years ago when I was 73. I am now at the age where simpler (boring) is better. I still drive my grandson’s stick shift from time to time, but find it requires too much effort.

I was wondering if Mr. Dyer would like to go back to the horse and buggy. Just think of the road noise and the sound of real horses.

Ron Thomas Glencoe, Ill.

The slowdown in E.V. sales is not because they are boring. It’s because they are 1) too expensive; 2) take too long to charge; 3) don’t go far enough on a single charge.

I will happily buy a medium-size S.U.V. E.V. when it goes 500 miles on a five-minute charge and costs about the same as the hybrid version. Until then I will settle for the Toyota RAV4 hybrid.

John Aitken Salt Lake City

Sitting on the back deck of my house, I can hear the faint roar of traffic from the town center, about a mile away. I console myself that when more people are driving E.V.s, quiet and the sweet cacophony of bird song will prevail.

Now, Ezra Dyer tells us that E.V. manufacturers are designing speaker systems that will mimic the sound of “loud exhaust” because E.V.s are too boring.

What’s next, E.V.s equipped to spew the nostalgia-inducing “not entirely unpleasant” smell of gas, oil and diesel?

The genius of human invention never fails to amaze and horrify.

Janet Buchwald Sudbury, Mass.

What an unexpected and incredibly refreshing surprise to see the essay on electric cars by Ezra Dyer, a Car and Driver columnist. As a longtime Car and Driver subscriber and past and present owner of three Alfa Romeos, I agree wholeheartedly with his observations.

And given the fact that the Porsche 911 GT3 is one of the most coveted cars by my 25-year-old son, there is hope for the next generation. We just need the car manufacturers to listen to the roar.

Allan M. Tepper Philadelphia

Re “ Living With a Stranger Is Hard. College Students Should Try It ,” by Pamela Paul (column, April 23):

I had the unique privilege of having roommates for my first two years of college who were radically different from me. I learned an awful lot because of the experience. But there was plenty I wish I hadn’t too.

The move to college is hard enough — academically, socially, mentally — that sharing that with another person places a needless burden on new students.

Ms. Paul is quite right that students benefit from learning from those around them, and schools should emphasize this in the classroom. But if there’s one place that ought to be sacred and free from the trials of starting college, it should be one’s room.

James J. Bernstein New York

When I arrived at the University of Alaska Fairbanks as a freshman in 1972 as a Jewish New Yorker in a distant land, I met my new roommate, a Muslim from the Philippines. Two people could not have been more different. And it worked out magically.

While we have lost touch over the years, I still remember his glowing smile and warmth and am glad we were selected as roommates. It helped me to grow and appreciate people from vastly different backgrounds.

Randomness in roommate selection can generate growth and learning, which is what I always thought college is supposed to do.

Paul Neuman New York

Re “ Tech in Schools Needs ‘a Hard Reset,’ ” by Jessica Grose (Opinion, April 28):

Over the past 15 years of having school-age kids, I have been deeply frustrated by how our schools have adopted technology without enough scrutiny. It is depressing to realize how many hours my kids are required to spend in front of the computer screen daily — and all without any body of evidence pointing to its positive effect on learning.

How I dreamed about running the iPad over with my van after four years of my high schooler reading everything — even novels! — on his device.

Though I’ve heard noble rationales for tech in the classrooms — “It will save the trees!” — I agree with Ms. Grose that schools need to re-evaluate what tech companies decide the schools need.

Not only are standardized tests at every level revealing faltering learning outcomes, but the human-to-human interaction is also clearly suffering the most. Out with Google Slides; in with teaching!

Amanda Bonagura Floral Park, N.Y.

Re “ How Do I Talk to My Son About a War I Don’t Understand? ,” by Sasha Vasilyuk (Opinion guest essay, April 28):

The war in Ukraine is not “Russia’s betrayal,” as Ms. Vasilyuk writes, but Russia’s business as usual. For generations, Moscow has violently suppressed the freedoms of surrounding nations.

Rather than withhold unpleasant truths, Russian parents must teach their children what Ukrainian, Polish or Latvian children learn from theirs: Historically Russia is an aggressor.

Russia’s imperialism relies on the unquestioned belief among countless ordinary Russians that their state has a virtuous right to dominate its neighbors. Without much hard work by parents and teachers, Russia’s noxious record will continue unchallenged.

John Connelly Kensington, Calif. The writer is a professor of history at the University of California, Berkeley.

Re “ Democrats See Water as Issue to Win Over Rural Arizona Voters ” (news article, April 24):

This article points out the difficulty that Democrats face in winning over conservative voters. For these desert communities, water is a life and death issue. But even though they admit that Republican policies hurt them and Democratic policies help them, these people will vote for Donald Trump.

And it’s not as if they don’t realize which side is which. They may agree that on this crucial issue the Democrats are right and are helping them, and the Republicans are wrong and are hurting them, but it doesn’t matter. They will still vote for Mr. Trump. There could be no clearer example of people voting directly against their own interests.

If nothing else, this discouraging story shows how much stronger is the fear of migrants, of change, of big government — all abstract fears really — than the drastic reality staring these people in the face.

Tim Shaw Cambridge, Mass.

IMAGES

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COMMENTS

14 Questions About Aquatic Animals Answered
Blue whale (Balaenoptera musculus). Encyclopædia Britannica, Inc. The blue whale, which swims all of the world's oceans, is the largest mammal. The largest documented blue whale was at least 110 feet (33.5 meters) long and weighed 209 tons (189,604 kilograms). The average length is about 82 feet (25 meters) for the males, and 85 feet (26 ...
Essay on Water for Students and Children
A.1 Water is of the utmost importance for human and animal life. It gives us water to drink. It also comes in great use for farmers and industries. Even common man requires water for various purposes like drinking, cleaning, bathing and more. Q.2 List the ways to avoid wastage of water.
Importance of Water in Animal Life
Importance of Water in Animal Life. Animal life requires a steady supply of water to fulfill its vital functions. From transportation to lubrication to temperature regulation, water keeps animal life functioning; in fact, the bodies of animals consist mostly of water. All chemical reactions in the bodies of animals use water as a medium.
Ocean habitat
Scientists think that up to 91 percent of marine species have not yet been identified; but there could be as many as 700,000 of them! Most—95 percent—are invertebrates, animals that don't have a backbone, such as jellyfish and shrimp. The most common vertebrate (an animal with a backbone) on Earth is the bristlemouth, a tiny ocean fish that glows in the dark and has needlelike fangs.
Importance of Water Essay for Students in English
Water consumption lubricates the joints, spinal cord, and tissues. Importance of Water. All living organisms, plants, animals, and human beings contain water. Almost 70% of our body is made up of water. Our body gets water from the liquids we drink and the food we eat. Nobody can survive without water for more than a week.
Aquatic animal
An aquatic animal is any animal, whether vertebrate or invertebrate, that lives in water for all or most of its lifetime. [1] Many insects such as mosquitoes, mayflies, dragonflies and caddisflies have aquatic larvae, with winged adults. Aquatic animals may breathe air or extract oxygen from water through specialised organs called gills, or ...
Essay on Animals and Their Habitat: Essay Example
Essay on Animals and Their Habitat: Introduction. "A habitat, or biome, is the type of environment in which plants and animals live" ( Habitats 2017, para. 1). In other words, a habitat is an environmental zone where particular species of animals, plants, and other organisms can be found. There are three main groups of habitats: terrestrial ...
Freshwater Ecosystem
The plants, animals, microbes, rocks, soil, sunlight, and water found in and around this valuable resource are all part of what is called a freshwater ecosystem. Less than three percent of our planet's water is fresh water, and less than half of that is available as a liquid; the rest is locked away as ice in polar caps and glaciers.
Water Essay for Students and Children in English
February 13, 2024 by Prasanna. Essay on Water in English: Water, the very reason for the existence of living beings on earth, constitutes of more than 70% of the planet. Water is that magical liquid, that provides life to animals, plants, trees, bacteria and viruses. Water is the very reason why earth can support life and other planets cannot.
10 Lines on Aquatic Animals for Students and Children in English
Set 2 - 10 Lines on Aquatic Animals for School Students. Set 2 is helpful for students of Classes 6, 7 and 8. Aquatic animals are those that live in water and perform their life functions underwater. Aquatic animals have a different respiratory system that helps them breathe inside water.
Essay on Save Water Save Life for Students
500+ Words Essay on Save Water Save Life. Water has become a highly necessary part of human being's existence on Earth. Thus, the importance of water can be compared to the importance of air. All living organisms whether it is human, animals, or plants. Everyone is completely depending on fresh and potable water.
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500 Words Essay On Animals. Animals are made up of numerous cells that can move, sense and reproduce. They play a vital role in maintaining nature's balance. Numerous animal species exist in the land as well as water, and each has a purpose for their existence. Different Types Of Animals
English Essay on Aquatic Animals
150 Words Essay on Aquatic Animals. Aquatic animals are those that live inside the water. Aquatic lives are different than normal terrestrial lives. Aquatic species breathe inside the water with the help of gills. Although they too need oxygen like us the medium is different. We inhale oxygen from the air as they inhale oxygen from water.
Essay on Aquatic Animals
The animals which live in water are called Aquatic animals. The aquatic animals live in sea, ponds, lakes, rivers etc. but water is their permanent house. It can be saline, still tor fresh. As our houses are of different kinds similarly the aquatic animals live in different environments according to their sustainability.
Effects of pollution on freshwater aquatic organisms
The study assessed various freshwater water quality indicators to determine the impact of the effluent. The study showed statistical (p < 0.05) differences on antioxidant enzyme levels in the organism. Also, the presence of metals and changes in water quality indicators resulted to oxidative stress in G. dulensis. It was found that there was ...
Essay on Importance of Water
Long and Short Essays on Importance of Water for Students and Kids in English. A Long essay on the topic of Importance of Water is provided it is of 450-500 words. A short Essay of 100-150 words is also given below. The extended articles are popular among students of classes 7, 8, 9, and 10.
Short Essay on Water [100, 200, 400 Words] With PDF
Short Essay on Water in 200 Words. Water is the most significant resource among everything that humans and animals can receive. Water helps a living being to live for longer days, even when food is scarce. It is one of the most beautiful gifts of nature. Water has enormous benefits and is the life of the earth.
The Importance of Water Essay
Water is an essential resource that sustains all life on Earth. Its importance is undeniable, as it plays a vital role in various aspects of our lives and the planet's well-being. It supports ecosystems, agriculture, human health, and industry. Ecosystems rely on water as a habitat for plants and animals, ensuring biodiversity and a thriving ...
Essay on Aquatic Animals (510 Words)
Essay on Aquatic Animals (510 Words) Article shared by. Aquatic lives are much different than normal terrestrial lives. Aquatic animals are those that live inside water. They have a provision in body to make their respiration. These aquatic animals are especially characterized as the one who don't get a close contact with the world outside water.
Water Conservation Essay for Students
500+ Words Essay on Water Conservation. Water makes up 70% of the earth as well as the human body. There are millions of marine species present in today's world that reside in water. Similarly, humankind also depends on water. All the major industries require water in some form or the other. However, this precious resource is depleting day by ...
Essay on Animals in English
Long essay on Animals is for students of Classes 8,9 and 10 and competitive exam aspirants. The Earth is home to many creatures. Animals have been the inhabitants of this planet, along with humans. Historically, animals were used for transportation, protection, as well as for hunting. Animals have been companions to man since time immemorial.
Importance of Water Essay for Students and Children
500+ Words Essay on Importance of Water. Water is the basic necessity for the functioning of all life forms that exist on earth. It is safe to say that water is the reason behind earth being the only planet to support life. This universal solvent is one of the major resources we have on this planet. It is impossible for life to function without ...
What Amazes You Most About Animals?
Cheetahs are the fastest animals on land; they can also stop and start with extraordinary agility. Dogs are really good at reading our emotions, and they have a keen sense of smell. Bats can ...
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Temporal multi-omic analysis of tissues from rats undergoing up to eight weeks of endurance exercise training reveals widespread shared, tissue-specific and sex-specific changes, including ...
Flooding in Southern Brazil: Images of Rio Grande do Sul Underwater
In the state capital, Porto Alegre, a city of 1.3 million perched on the banks of the Guaiba River, streets were submerged in murky water and the airport was shuttered by the deluge, with flights ...
Costa Rica Shuts Down State Zoos, Ends Animal Captivity
"The animals that will be recovered from the state zoos will be transferred to the rescue center known as SOAVE," said José Pablo Vázquez, a conservation area official at Minae. Both facilities should have been closed in 2014, following the approval of the law, but various judicial appeals regarding the concession delayed the closure for ...
Pennsylvania will make the animal sedative xylazine a controlled ...
Xylazine is a prescription sedative used by veterinarians to safely handle and treat farm animals, wildlife, zoo animals and household pets such as cats and dogs.
Several farm animals killed as fire engulfs barn in Massachusetts
WESTPORT, Mass. (WJAR) — Multiple farm animals were killed in a Massachusetts barn fire Tuesday morning, according to authorities. The fire on was reported at about 7 a.m. The Westport Fire ...
Rio Grande do Sul, Brazil, sees worst flooding in 80 years: Photos
In the state capital, Porto Alegre, water levels of the Guaíba River peaked at 17.5 feet (5.33 meters) on Sunday — far exceeding the previous record of 15.6 feet (4.76 meters) observed in 1941 ...
Are E.V.s Too Quiet and 'Boring'?
To the Editor: Re "Electric Cars Are Boring," by Ezra Dyer (Opinion guest essay, April 13): If E.V.s are boring, I guess I am OK with being bored. As an E.V. owner, I no longer have to stop at ...