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A species goes extinct when there are none of its kind left. In other words, extinction is about small numbers, so how does big data help us study extinction? Luckily for us, each individual of a species carries with it signatures of its past, information on how connected/ isolated it is today, and other information on what may predict its future, in its genome. The last fifteen years have witnessed a major change in how we can read genomes, and information from genomes of individuals and species can help better plan their conservation. 

All life on Earth harbours genetic material. Often called the blueprint of life, this genetic material could be DNA or RNA. We all know what DNA is, but another way to think of DNA is as data. All mammals, for example harbour between 2 to 3.5 billion bits of data in every one of their cells. The entire string of DNA data is called the whole genome. Recent changes in technology allow us to read whole genomes. We read short 151 letter long information bits many, many times, and piece together the whole genome by comparing it to a known reference. This helps us figure out where each of these 151 letter long pieces go in the 3 billion letter long word. Once we have read each position on an average of 10 or 20 times, we can be confident about it. If each genome is sequenced even ten times and only ten individuals are sampled, for mammals each dataset would consist of 200 to 350 billion bits of data!

Over time, the genome changes because of mutation, or spelling errors that creep in. Such spelling errors create variation, or differences between individual genomes in a population (a set of animals or plants). Similarly, large populations with many individuals will hold a variety of spellings or high genetic variation. Since DNA is the genetic blueprint, changes in the environment can also get reflected in these DNA spellings, with individuals with certain words in their genome surviving better than others under certain conditions. Changes in population size often changes the variety of letters observed at a specific location in the genome, or variation at a specific genomic position. Migration or movement of animals into a population adds new letters and variation. Taking all these together, the history of a population can be understood by comparing the DNA sequences of individuals. The challenge lies in the fact that every population faces all of these effects: changes in population size, environmental selection, migration and mutation, all at once, and it is difficult to separate the effects of different factors. Here, the big data comes to the rescue.

genome wildlife concept genomics

Photo Credit: Dr Anubhab Khan

Genomic data has allowed us to understand how a population has been affected by changes in climate, and whether it has the necessary genomic variation to survive in the face of ongoing climate change. Or how specific human activities have impacted a population in the past. We can understand more about the origins of a population. How susceptible is a population to certain infections? Or whether the individuals in a population are related to each other. Some of these large datasets have helped identify if certain populations are identical and should be managed together or separately. All of these questions help in the management and conservation of a population.

We have worked on such big genomic datasets for tigers, and our research has helped us identify which populations of tigers have high genomic variation and are more connected to other populations. We have identified populations that are small and have low genomic variation, but also seem to have mis-spelled or badly spelled words, or a propensity of ‘bad’ mutations. We have identified unknown relationships between individuals within populations and have suggested strategies that could allow these isolated populations to recover their genomic variation. It has been amazing to peek into animals lives through these big data approaches, and we hope these types of genomic dataset will contribute to understanding how biodiversity can continue to survive on this Earth.


Uma Ramakrishnan is fascinated by unravelling the mysteries of nature using DNA as tool. Along with her lab colleagues, she has spent the last fifteen years studying endangered species in India.She hopes such understanding will contribute to their conservation. Uma is a professor at the National Centre for Biological Sciences.

Dr. Anubhab Khan is a wildlife genomics expert. He has researching genetics of small isolated populations for past several years and has created and analyzed large scale genome sequencing data of tigers, elephants and small cats among others. He keen about population genetics, wildlife conservation and genome sequencing technologies. He is passionate about ending technology disparity in the world by either making advanced technologies and expertise available or by developing techniques that are affordable and accessible to all.

This series is an initiative by the Nature Conservation Foundation (NCF), under their programme ‘Nature Communications’ to encourage nature content in all Indian languages. To know more about birds and nature, Join The Flock


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Astronomers Discover 3I/ATLAS, Largest Interstellar Comet Yet Detected

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Astronomers Discover 3I/ATLAS, Largest Interstellar Comet Yet Detected

Astronomers have discovered the third interstellar comet to pass through our solar system. Named 3I/ATLAS (initially A11pl3Z), it was first spotted July 1 by the ATLAS telescope in Chile and confirmed the same day. Pre-discovery images show it in the sky as far back as mid-June. The object is racing toward the inner system at roughly 150,000 miles per hour on a near-straight trajectory, too fast for the Sun to capture. Estimates suggest its nucleus may be 10–20 km across. Now inside Jupiter’s orbit, 3I/ATLAS will swing closest to the Sun in October and should remain observable into late 2025.

Discovery and Classification

According to NASA, in early July the ATLAS survey telescope in Chile spotted a faint moving object first called A11pl3Z, and the IAU’s Minor Planet Center confirmed the next day that it was an interstellar visitor. The object was officially named 3I/ATLAS and noted as likely the largest interstellar body yet detected. At first it appeared to be an ordinary near-Earth asteroid, but precise orbit measurements showed it speeding at ~150,000 mph – far too fast for the Sun to capture. Astronomers estimate 3I/ATLAS spans roughly 10–20 km across. Signs of cometary activity – a faint coma and short tail – have emerged, earning it the additional comet designation C/2025 N1 (ATLAS).

Studying a Pristine Comet

3I/ATLAS was spotted well before its closest approach, giving astronomers time to prepare detailed observations. It will pass within about 1.4 AU of the Sun in late October. Importantly, researchers can study it while it is still a pristine frozen relic before solar heating alters it. As Pamela Gay notes, discovering the object on its inbound leg leaves “ample time” to analyze its trajectory. Astronomers are now racing to obtain spectra and images – as Chris Lintott warns, the comet will be “baked” by sunlight as it nears perihelion.

Determining its composition and activity is considered “a rare chance” to learn how planets form in other star systems. With new facilities like the Vera C. Rubin Observatory coming online, researchers expect more such visitors in the years ahead. 3I/ATLAS offers a rare chance to study material from another star system.

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NASA’s New Horizons Proves Deep-Space Navigation via Stellar Parallax



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NASA’s New Horizons Proves Deep-Space Navigation via Stellar Parallax

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NASA's New Horizons Proves Deep-Space Navigation via Stellar Parallax

NASA’s New Horizons spacecraft carried out an unprecedented deep-space star navigation test while 438 million miles from Earth. Using its long-range camera in April 2020, it captured images of Proxima Centauri and Wolf 359, which appeared slightly shifted in the sky compared to Earth’s view – a striking demonstration of stellar parallax. It was the first-ever demonstration of deep-space stellar navigation. By comparing these images to Earth-based observations and a 3D star chart, scientists calculated New Horizons’ position to within about 4.1 million miles, only about 26 inches across the United States.

Stellar Parallax Test

According to the paper describing the results, accepted for publication in The Astronomical Journal, New Horizons’ camera imaged Proxima Centauri (4.2 light-years away) and Wolf 359 (7.86 light-years) on April 23, 2020. From the spacecraft’s distant vantage point, the two stars appear in different positions than seen from Earth – the essence of stellar parallax. By comparing those images with Earth-based data and a three-dimensional map of nearby stars, the team worked out the probe’s location to within about 4.1 million miles.

As lead author Tod Lauer explained, “Taking simultaneous Earth/Spacecraft images we hoped would make the concept of stellar parallaxes instantly and vividly clear”. He added, “It’s one thing to know something, but another to say ‘Hey, look! This really works!’”.

New Horizons and Future Missions

New Horizons, the fifth spacecraft to leave Earth and reach interstellar space, flew past Pluto and its moon Charon in 2015, sending home the first close-up images of those distant icy worlds. Now on an extended mission, the probe is studying the heliosphere.

New Horizons’ principal investigator Alan Stern called the parallax test “a pioneering interstellar navigation demonstration” that shows a spacecraft can use onboard cameras “to find its way among the stars”, in a statement. He also noted it “could be highly useful for future deep space missions in the far reaches of the Solar System and in interstellar space”

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AI Designs Ocean Gliders Inspired by Sea Creatures to Boost Underwater Research Efficiency

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AI Designs Ocean Gliders Inspired by Sea Creatures to Boost Underwater Research Efficiency

Marine animals like fish and seals have long inspired ocean engineers due to their fluid, energy-efficient movements. Now, researchers are turning to these sea animals to create a new class of underwater gliders that requires very little energy, according to a team led by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the University of Wisconsin-Madison. They used artificial intelligence to design forms that slide through the water with less resistance, making long-term ocean exploration more efficient. These gliders, fabricated via 3D printing, promise better data collection on currents, salt levels, and climate impacts.

AI-Powered 3D Designs Create Energy-Efficient Underwater Gliders Inspired by Marine Life Forms

As per a study published on the arXiv preprint server, the team used machine learning to create and simulate numerous novel 3D glider shapes. By comparing traditional models—like submarines and sharks—with digitally altered versions, their algorithm learnt how different designs behaved at various “angles-of-attack.” A neural network then evaluated the lift-to-drag ratio of each shape, identifying those most likely to glide efficiently through water. These shapes were then fabricated using lightweight materials that minimised energy use.

In tests, two AI-generated prototypes—one shaped like a two-winged plane and the other like a four-finned flatfish—were built and tested both in wind tunnels and underwater. Key hardware was integrated with the gliders, including buoyancy control by a pump and a mass shifter to move the angle during displacements. The new gliders, with better shapes and lift-to-drag ratios, could travel farther on less power than traditional torpedo-shaped types.

The team added that what they are doing not only makes new types of designs possible but also reduces design times and cuts the cost since it doesn’t require physical prototyping. “This high degree of shape diversity hasn’t been investigated before,” Peter Yichen Chen, an MIT postdoc and co-lead author on the project, mentioned. He also noted that their AI pipeline allows testing forms that would be “very taxing” for humans to manually design.

The future plans are to produce slimmer and more manoeuvrable gliders and to improve the AI system with more configurable options. Intelligent bioinspired vehicles like these, the researchers say, will be essential in studying dynamic ocean environments that are changing quickly with the intensifying demands of industrial activity, ultimately offering more flexible and efficient ways for us to explore Earth’s last frontier.

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Hubble Observations Give Forgotten Globular Cluster Its Moment to Shine



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