Lab-grown meat will soon be sold in the U.S., but who will buy It?
Last November, when the U.S. Food and Drug Administration disclosed that chicken from a California firm called UPSIDE Foods did not raise safety concerns, it drily upended how humans have obtained animal protein for thousands of generations.
“The FDA is ready to work with additional firms developing cultured animal cell food and production processes to ensure their food is safe and lawful,” the agency said in a statement at the time.
Assuming UPSIDE obtains clearances from the U.S. Department of Agriculture, its chicken – grown entirely in a laboratory without harming a single bird – could be sold in supermarkets in the coming months.
“Ultimately, we want our products to be available everywhere meat is sold, including retail and food service channels,” a company spokesperson said. The upscale French restaurant Atelier Crenn in San Francisco will have UPSIDE chicken on its menu once it is approved, she added.
Known as lab-grown or cultured meat, a product such as UPSIDE’s is created using stem cells and other tissue obtained from a chicken, cow or other livestock. Those cells are then multiplied in a nutrient-dense environment, usually in conjunction with a “scaffold” of plant-based materials or gelatin to give them a familiar form, such as a chicken breast or a ribeye steak. A Dutch company called Mosa Meat claims it can produce 80,000 hamburgers derived from a cluster of tissue the size of a sesame seed.
Critics say the doubts about lab-grown meat and the possibility it could merge “Brave New World” with “The Jungle” and “Soylent Green” have not been appropriately explored.
That’s a far cry from when it took months of work to create the first lab-grown hamburger a decade ago. That minuscule patty – which did not contain any fat and was literally plucked from a Petri dish to go into a frying pan – cost about $325,000 to produce.
Just a decade later, an Israeli company called Future Meat said it can produce lab-grown meat for about $1.70 per pound. It plans to open a production facility in the U.S. sometime in 2023 and distribute its products under the brand name “Believer.”
Costs for production have sunk so low that researchers at Carnegie Mellon University in Pittsburgh expect sometime in early 2024 to produce lab-grown Wagyu steak to showcase the viability of growing high-end cuts of beef cheaply. The Carnegie Mellon team is producing its Wagyu using a consumer 3-D printer bought secondhand on eBay and modified to print the highly marbled flesh using a method developed by the university. The device costs $200 – about the same as a pound of Wagyu in the U.S. The initiative’s modest five-figure budget was successfully crowdfunded last year.
“The big cost is going to be the cells (which are being extracted by a cow somewhere in Pennsylvania), but otherwise printing doesn’t add much to the process,” said Rosalyn Abbott, a Carnegie Mellon assistant professor of bioengineering who is co-leader on the project. “But it adds value, unlike doing this with ground meat.”
Lab-Grown Meat’s Promise
Proponents of lab-grown meat say it will cut down on traditional agriculture, which has been a leading contributor to deforestation, water shortages and contaminated waterways from animal waste, as well as climate change.
An Oxford University study from 2011 concludes lab-grown meat could have greenhouse emissions 96 percent lower compared to traditionally raised livestock. Moreover, proponents of lab-grown meat claim that the suffering of animals would decline dramatically, as they would no longer need to be warehoused and slaughtered. A recently opened 26-story high-rise in China dedicated to the raising and slaughtering of pigs illustrates the current plight of livestock in stark terms.
Scientists may even learn how to tweak lab-grown meat to make it more nutritious. Natural red meat is high in saturated fat and, if it’s eaten too often, can lead to chronic diseases. In lab versions, the saturated fat could be swapped for healthier, omega-3 fatty acids.
But critics say the doubts about lab-grown meat and the possibility it could merge “Brave New World” with “The Jungle” and “Soylent Green” have not been appropriately explored.
A Slippery Slope?
Some academics who have studied the moral and ethical issues surrounding lab-grown meat believe it will have a tough path ahead gaining acceptance by consumers. Should it actually succeed in gaining acceptance, many ethical questions must be answered.
“People might be interested” in lab-grown meat, perhaps as a curiosity, said Carlos Alvaro, an associate professor of philosophy at the New York City College of Technology, part of the City University of New York. But the allure of traditionally sourced meat has been baked – or perhaps grilled – into people’s minds for so long that they may not want to make the switch. Plant-based meat provides a recent example of the uphill battle involved in changing old food habits, with Beyond Meat’s stock prices dipping nearly 80 percent in 2022.
"There are many studies showing that people don’t really care about the environment (to that extent)," Alvaro said. "So I don’t know how you would convince people to do this because of the environment.”
“From my research, I understand that the taste (of lab-grown meat) is not quite there,” Alvaro said, noting that the amino acids, sugars and other nutrients required to grow cultivated meat do not mimic what livestock are fed. He also observed that the multiplication of cells as part of the process “really mimic cancer cells” in the way they grow, another off-putting thought for would-be consumers of the product.
Alvaro is also convinced the public will not buy into any argument that lab-grown meat is more environmentally friendly.
“If people care about the environment, they either try and consume considerably less meat and other animal products, or they go vegan or vegetarian,” he said. “But there are many studies showing that people don’t really care about the environment (to that extent). So I don’t know how you would convince people to do this because of the environment.”
Ben Bramble, a professor at Australian National University who previously held posts at Princeton and Trinity College in Ireland, takes a slightly different tack. He noted that “if lab-grown meat becomes cheaper, healthier, or tastier than regular meat, there will be a large market for it. If it becomes all of these things, it will dominate the market.”
However, Bramble has misgivings about that occurring. He believes a smooth transition from traditionally sourced meat to a lab-grown version would allow humans to elide over the decades of animal cruelty perpetrated by large-scale agriculture, without fully reckoning with and learning from this injustice.
“My fear is that if we all switch over to lab-grown meat because it has become cheaper, healthier, or tastier than regular meat, we might never come to realize what we have done, and the terrible things we are capable of,” he said. “This would be a catastrophe.”
Bramble’s writings about cultured meat also raise some serious moral conundrums. If, for example, animal meat may be cultivated without killing animals, why not create products from human protein?
Actually, that’s already happened.
It occurred in 2019, when Orkan Telhan, a professor of fine arts at the University of Pennsylvania, collaborated with two scientists to create an art exhibit at the Philadelphia Museum of Art on the future of foodstuffs.
Although the exhibit included bioengineered bread and genetically modified salmon, it was an installation called “Ouroboros Steak” that drew the most attention. That was comprised of pieces of human flesh grown in a lab from cultivated cells and expired blood products obtained from online sources.
The exhibit was presented as four tiny morsels of red meat – shaped in patterns suggesting an ouroboros, a dragon eating its own tail. They were placed in tiny individual saucers atop a larger plate and placemat with a calico pattern, suggesting an item to order in a diner. The artwork drew international headlines – as well as condemnation for Telhan’s vision.
Telhan’s artwork is intended to critique the overarching assumption that lab-grown meat will eventually replace more traditional production methods, as well as the lack of transparency surrounding many processed foodstuffs. “They think that this problem (from industrial-scale agriculture) is going be solved by this new technology,” Telhan said. “I am critical (of) that perspective.”
Unlike Bramble, Telhan is not against lab-grown meat, so long as its producers are transparent about the sourcing of materials and its cultivation. But he believes that large-scale agricultural meat production – which dates back centuries – is not going to be replaced so quickly.
“We see this again and again with different industries, like algae-based fuels. A lot of companies were excited about this, and promoted it,” Telhan said. “And years later, we know these fuels work. But to be able to displace the oil industry means building the infrastructure to scale takes billions of dollars, and nobody has the patience or money to do it.”
Alvaro concurred on this point, which he believes is already weakened because a large swath of consumers aren’t concerned about environmental degradation.
“They’re going to have to sell this big, but in order to convince people to do so, they have to convince them to eat this product instead of regular meat,” Alvaro said.
Hidden Tweaks?
Moreover, if lab-based meat does obtain a significant market share, Telhan suggested companies may do things to the product – such as to genetically modify it to become more profitable – and never notify consumers. That is a particular concern in the U.S., where regulations regarding such modifications are vastly more relaxed than in the European Union.
“I think that they have really good objectives, and they aspire to good objectives,” Telhan said. “But the system itself doesn't really allow for that much transparency.”
No matter what the future holds, sometime next year Carnegie Mellon is expected to hold a press conference announcing it has produced a cut of the world’s most expensive beef with the help of a modified piece of consumer electronics. It will likely take place at around the same time UPSIDE chicken will be available for purchase in supermarkets and restaurants, pending the USDA’s approvals.
Abbott, the Carnegie Mellon professor, suggested the future event will be both informative and celebratory.
“I think Carnegie Mellon would have someone potentially cook it for us,” she said. “Like have a really good chef in New York City do it.”
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”