FDA, researchers work to make clinical trials more diverse
Nestled in a predominately Hispanic neighborhood, a new mural outside Guadalupe Centers Middle School in Kansas City, Missouri imparts a powerful message: “Clinical Research Needs Representation.” The colorful portraits painted above those words feature four cancer survivors of different racial and ethnic backgrounds. Two individuals identify as Hispanic, one as African American and another as Native American.
One of the patients depicted in the mural is Kim Jones, a 51-year-old African American breast cancer survivor since 2012. She advocated for an African American friend who participated in several clinical trials for ovarian cancer. Her friend was diagnosed in an advanced stage at age 26 but lived nine more years, thanks to the trials testing new therapeutics. “They are definitely giving people a longer, extended life and a better quality of life,” said Jones, who owns a nail salon. And that’s the message the mural aims to send to the community: Clinical trials need diverse participants.
While racial and ethnic minority groups represent almost half of the U.S. population, the lack of diversity in clinical trials poses serious challenges. Limited awareness and access impede equitable representation, which is necessary to prove the safety and effectiveness of medical interventions across different groups.
A Yale University study on clinical trial diversity published last year in BMJ Medicine found that while 81 percent of trials testing the new cancer drugs approved by the U.S. Food and Drug Administration between 2012 and 2017 included women, only 23 percent included older adults and 5 percent fairly included racial and ethnic minorities. “It’s both a public health and social justice issue,” said Jennifer E. Miller, an associate professor of medicine at Yale School of Medicine. “We need to know how medicines and vaccines work for all clinically distinct groups, not just healthy young White males.” A recent JAMA Oncology editorial stresses out the need for legislation that would require diversity action plans for certain types of trials.
Ensuring meaningful representation of racial and ethnic minorities in clinical trials for regulated medical products is fundamental to public health.--FDA Commissioner Robert M. Califf.
But change is on the horizon. Last April, the FDA issued a new draft guidance encouraging industry to find ways to revamp recruitment into clinical trials. The announcement, which expanded on previous efforts, called for including more participants from underrepresented racial and ethnic segments of the population.
“The U.S. population has become increasingly diverse, and ensuring meaningful representation of racial and ethnic minorities in clinical trials for regulated medical products is fundamental to public health,” FDA commissioner Robert M. Califf, a physician, said in a statement. “Going forward, achieving greater diversity will be a key focus throughout the FDA to facilitate the development of better treatments and better ways to fight diseases that often disproportionately impact diverse communities. This guidance also further demonstrates how we support the Administration’s Cancer Moonshot goal of addressing inequities in cancer care, helping to ensure that every community in America has access to cutting-edge cancer diagnostics, therapeutics and clinical trials.”
Lola Fashoyin-Aje, associate director for Science and Policy to Address Disparities in the Oncology Center of Excellence at the FDA, said that the agency “has long held the view that clinical trial participants should reflect the clinical and demographic characteristics of the patients who will ultimately receive the drug once approved.” However, “numerous studies over many decades” have measured the extent of underrepresentation. One FDA analysis found that the proportion of White patients enrolled in U.S. clinical trials (88 percent) is much higher than their numbers in country's population. Meanwhile, the enrollment of African American and Native Hawaiian/American Indian and Alaskan Native patients is below their national numbers.
The FDA’s guidance is accelerating researchers’ efforts to be more inclusive of diverse groups in clinical trials, said Joyce Sackey, a clinical professor of medicine and associate dean at Stanford School of Medicine. Underrepresentation is “a huge issue,” she noted. Sackey is focusing on this in her role as the inaugural chief equity, diversity and inclusion officer at Stanford Medicine, which encompasses the medical school and two hospitals.
Until the early 1990s, Sackey pointed out, clinical trials were based on research that mainly included men, as investigators were concerned that women could become pregnant, which would affect the results. This has led to some unfortunate consequences, such as indications and dosages for drugs that cause more side effects in women due to biological differences. “We’ve made some progress in including women, but we have a long way to go in including people of different ethnic and racial groups,” she said.
A new mural outside Guadalupe Centers Middle School in Kansas City, Missouri, advocates for increasing diversity in clinical trials. Kim Jones, 51-year-old African American breast cancer survivor, is second on the left.
Artwork by Vania Soto. Photo by Megan Peters.
Among racial and ethnic minorities, distrust of clinical trials is deeply rooted in a history of medical racism. A prime example is the Tuskegee Study, a syphilis research experiment that started in 1932 and spanned 40 years, involving hundreds of Black men with low incomes without their informed consent. They were lured with inducements of free meals, health care and burial stipends to participate in the study undertaken by the U.S. Public Health Service and the Tuskegee Institute in Alabama.
By 1947, scientists had figured out that they could provide penicillin to help patients with syphilis, but leaders of the Tuskegee research failed to offer penicillin to their participants throughout the rest of the study, which lasted until 1972.
Opeyemi Olabisi, an assistant professor of medicine at Duke University Medical Center, aims to increase the participation of African Americans in clinical research. As a nephrologist and researcher, he is the principal investigator of a clinical trial focusing on the high rate of kidney disease fueled by two genetic variants of the apolipoprotein L1 (APOL1) gene in people of recent African ancestry. Individuals of this background are four times more likely to develop kidney failure than European Americans, with these two variants accounting for much of the excess risk, Olabisi noted.
The trial is part of an initiative, CARE and JUSTICE for APOL1-Mediated Kidney Disease, through which Olabisi hopes to diversify study participants. “We seek ways to engage African Americans by meeting folks in the community, providing accessible information and addressing structural hindrances that prevent them from participating in clinical trials,” Olabisi said. The researchers go to churches and community organizations to enroll people who do not visit academic medical centers, which typically lead clinical trials. Since last fall, the initiative has screened more than 250 African Americans in North Carolina for the genetic variants, he said.
Other key efforts are underway. “Breaking down barriers, including addressing access, awareness, discrimination and racism, and workforce diversity, are pivotal to increasing clinical trial participation in racial and ethnic minority groups,” said Joshua J. Joseph, assistant professor of medicine at the Ohio State University Wexner Medical Center. Along with the university’s colleges of medicine and nursing, researchers at the medical center partnered with the African American Male Wellness Agency, Genentech and Pfizer to host webinars soliciting solutions from almost 450 community members, civic representatives, health care providers, government organizations and biotechnology professionals in 25 states and five countries.
Their findings, published in February in the journal PLOS One, suggested that including incentives or compensation as part of the research budget at the institutional level may help resolve some issues that hinder racial and ethnic minorities from participating in clinical trials. Compared to other groups, more Blacks and Hispanics have jobs in service, production and transportation, the authors note. It can be difficult to get paid leave in these sectors, so employees often can’t join clinical trials during regular business hours. If more leaders of trials offer money for participating, that could make a difference.
Obstacles include geographic access, language and other communications issues, limited awareness of research options, cost and lack of trust.
Christopher Corsico, senior vice president of development at GSK, formerly GlaxoSmithKline, said the pharmaceutical company conducted a 17-year retrospective study on U.S. clinical trial diversity. “We are using epidemiology and patients most impacted by a particular disease as the foundation for all our enrollment guidance, including study diversity plans,” Corsico said. “We are also sharing our results and ideas across the pharmaceutical industry.”
Judy Sewards, vice president and head of clinical trial experience at Pfizer’s headquarters in New York, said the company has committed to achieving racially and ethnically diverse participation at or above U.S. census or disease prevalence levels (as appropriate) in all trials. “Today, barriers to clinical trial participation persist,” Sewards said. She noted that these obstacles include geographic access, language and other communications issues, limited awareness of research options, cost and lack of trust. “Addressing these challenges takes a village. All stakeholders must come together and work collaboratively to increase diversity in clinical trials.”
It takes a village indeed. Hope Krebill, executive director of the Masonic Cancer Alliance, the outreach network of the University of Kansas Cancer Center in Kansas City, which commissioned the mural, understood that well. So her team actively worked with their metaphorical “village.” “We partnered with the community to understand their concerns, knowledge and attitudes toward clinical trials and research,” said Krebill. “With that information, we created a clinical trials video and a social media campaign, and finally, the mural to encourage people to consider clinical trials as an option for care.”
Besides its encouraging imagery, the mural will also be informational. It will include a QR code that viewers can scan to find relevant clinical trials in their location, said Vania Soto, a Mexican artist who completed the rendition in late February. “I’m so honored to paint people that are survivors and are living proof that clinical trials worked for them,” she said.
Jones, the cancer survivor depicted in the mural, hopes the image will prompt people to feel more open to partaking in clinical trials. “Hopefully, it will encourage people to inquire about what they can do — how they can participate,” she said.
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.”