Beyond Henrietta Lacks: How the Law Has Denied Every American Ownership Rights to Their Own Cells
The common perception is that Henrietta Lacks was a victim of poverty and racism when in 1951 doctors took samples of her cervical cancer without her knowledge or permission and turned them into the world's first immortalized cell line, which they called HeLa. The cell line became a workhorse of biomedical research and facilitated the creation of medical treatments and cures worth untold billions of dollars. Neither Lacks nor her family ever received a penny of those riches.
But racism and poverty is not to blame for Lacks' exploitation—the reality is even worse. In fact all patients, then and now, regardless of social or economic status, have absolutely no right to cells that are taken from their bodies. Some have called this biological slavery.
How We Got Here
The case that established this legal precedent is Moore v. Regents of the University of California.
John Moore was diagnosed with hairy-cell leukemia in 1976 and his spleen was removed as part of standard treatment at the UCLA Medical Center. On initial examination his physician, David W. Golde, had discovered some unusual qualities to Moore's cells and made plans prior to the surgery to have the tissue saved for research rather than discarded as waste. That research began almost immediately.
"On both sides of the case, legal experts and cultural observers cautioned that ownership of a human body was the first step on the slippery slope to 'bioslavery.'"
Even after Moore moved to Seattle, Golde kept bringing him back to Los Angeles to collect additional samples of blood and tissue, saying it was part of his treatment. When Moore asked if the work could be done in Seattle, he was told no. Golde's charade even went so far as claiming to find a low-income subsidy to pay for Moore's flights and put him up in a ritzy hotel to get him to return to Los Angeles, while paying for those out of his own pocket.
Moore became suspicious when he was asked to sign new consent forms giving up all rights to his biological samples and he hired an attorney to look into the matter. It turned out that Golde had been lying to his patient all along; he had been collecting samples unnecessary to Moore's treatment and had turned them into a cell line that he and UCLA had patented and already collected millions of dollars in compensation. The market for the cell lines was estimated at $3 billion by 1990.
Moore felt he had been taken advantage of and filed suit to claim a share of the money that had been made off of his body. "On both sides of the case, legal experts and cultural observers cautioned that ownership of a human body was the first step on the slippery slope to 'bioslavery,'" wrote Priscilla Wald, a professor at Duke University whose career has focused on issues of medicine and culture. "Moore could be viewed as asking to commodify his own body part or be seen as the victim of the theft of his most private and inalienable information."
The case bounced around different levels of the court system with conflicting verdicts for nearly six years until the California Supreme Court ruled on July 9, 1990 that Moore had no legal rights to cells and tissue once they were removed from his body.
The court made a utilitarian argument that the cells had no value until scientists manipulated them in the lab. And it would be too burdensome for researchers to track individual donations and subsequent cell lines to assure that they had been ethically gathered and used. It would impinge on the free sharing of materials between scientists, slow research, and harm the public good that arose from such research.
"In effect, what Moore is asking us to do is impose a tort duty on scientists to investigate the consensual pedigree of each human cell sample used in research," the majority wrote. In other words, researchers don't need to ask any questions about the materials they are using.
One member of the court did not see it that way. In his dissent, Stanley Mosk raised the specter of slavery that "arises wherever scientists or industrialists claim, as defendants have here, the right to appropriate and exploit a patient's tissue for their sole economic benefit—the right, in other words, to freely mine or harvest valuable physical properties of the patient's body. … This is particularly true when, as here, the parties are not in equal bargaining positions."
Mosk also cited the appeals court decision that the majority overturned: "If this science has become for profit, then we fail to see any justification for excluding the patient from participation in those profits."
But the majority bought the arguments that Golde, UCLA, and the nascent biotechnology industry in California had made in amici briefs filed throughout the legal proceedings. The road was now cleared for them to develop products worth billions without having to worry about or share with the persons who provided the raw materials upon which their research was based.
Critical Views
Biomedical research requires a continuous and ever-growing supply of human materials for the foundation of its ongoing work. If an increasing number of patients come to feel as John Moore did, that the system is ripping them off, then they become much less likely to consent to use of their materials in future research.
Some legal and ethical scholars say that donors should be able to limit the types of research allowed for their tissues and researchers should be monitored to assure compliance with those agreements. For example, today it is commonplace for companies to certify that their clothing is not made by child labor, their coffee is grown under fair trade conditions, that food labeled kosher is properly handled. Should we ask any less of our pharmaceuticals than that the donors whose cells made such products possible have been treated honestly and fairly, and share in the financial bounty that comes from such drugs?
Protection of individual rights is a hallmark of the American legal system, says Lisa Ikemoto, a law professor at the University of California Davis. "Putting the needs of a generalized public over the interests of a few often rests on devaluation of the humanity of the few," she writes in a reimagined version of the Moore decision that upholds Moore's property claims to his excised cells. The commentary is in a chapter of a forthcoming book in the Feminist Judgment series, where authors may only use legal precedent in effect at the time of the original decision.
"Why is the law willing to confer property rights upon some while denying the same rights to others?" asks Radhika Rao, a professor at the University of California, Hastings College of the Law. "The researchers who invest intellectual capital and the companies and universities that invest financial capital are permitted to reap profits from human research, so why not those who provide the human capital in the form of their own bodies?" It might be seen as a kind of sweat equity where cash strapped patients make a valuable in kind contribution to the enterprise.
The Moore court also made a big deal about inhibiting the free exchange of samples between scientists. That has become much less the situation over the more than three decades since the decision was handed down. Ironically, this decision, as well as other laws and regulations, have since strengthened the power of patents in biomedicine and by doing so have increased secrecy and limited sharing.
"Although the research community theoretically endorses the sharing of research, in reality sharing is commonly compromised by the aggressive pursuit and defense of patents and by the use of licensing fees that hinder collaboration and development," Robert D. Truog, Harvard Medical School ethicist and colleagues wrote in 2012 in the journal Science. "We believe that measures are required to ensure that patients not bear all of the altruistic burden of promoting medical research."
Additionally, the increased complexity of research and the need for exacting standardization of materials has given rise to an industry that supplies certified chemical reagents, cell lines, and whole animals bred to have specific genetic traits to meet research needs. This has been more efficient for research and has helped to ensure that results from one lab can be reproduced in another.
The Court's rationale of fostering collaboration and free exchange of materials between researchers also has been undercut by the changing structure of that research. Big pharma has shrunk the size of its own research labs and over the last decade has worked out cooperative agreements with major research universities where the companies contribute to the research budget and in return have first dibs on any findings (and sometimes a share of patent rights) that come out of those university labs. It has had a chilling effect on the exchange of materials between universities.
Perhaps tracking cell line donors and use restrictions on those donations might have been burdensome to researchers when Moore was being litigated. Some labs probably still kept their cell line records on 3x5 index cards, computers were primarily expensive room-size behemoths with limited capacity, the internet barely existed, and there was no cloud storage.
But that was the dawn of a new technological age and standards have changed. Now cell lines are kept in state-of-the-art sub zero storage units, tagged with the source, type of tissue, date gathered and often other information. Adding a few more data fields and contacting the donor if and when appropriate does not seem likely to disrupt the research process, as the court asserted.
Forging the Future
"U.S. universities are awarded almost 3,000 patents each year. They earn more than $2 billion each year from patent royalties. Sharing a modest portion of these profits is a novel method for creating a greater sense of fairness in research relationships that we think is worth exploring," wrote Mark Yarborough, a bioethicist at the University of California Davis Medical School, and colleagues. That was penned nearly a decade ago and those numbers have only grown.
The Michigan BioTrust for Health might serve as a useful model in tackling some of these issues. Dried blood spots have been collected from all newborns for half a century to be tested for certain genetic diseases, but controversy arose when the huge archive of dried spots was used for other research projects. As a result, the state created a nonprofit organization to in essence become a biobank and manage access to these spots only for specific purposes, and also to share any revenue that might arise from that research.
"If there can be no property in a whole living person, does it stand to reason that there can be no property in any part of a living person? If there were, can it be said that this could equate to some sort of 'biological slavery'?" Irish ethicist Asim A. Sheikh wrote several years ago. "Any amount of effort spent pondering the issue of 'ownership' in human biological materials with existing law leaves more questions than answers."
Perhaps the biggest question will arise when -- not if but when -- it becomes possible to clone a human being. Would a human clone be a legal person or the property of those who created it? Current legal precedent points to it being the latter.
Today, October 4, is the 70th anniversary of Henrietta Lacks' death from cancer. Over those decades her immortalized cells have helped make possible miraculous advances in medicine and have had a role in generating billions of dollars in profits. Surviving family members have spoken many times about seeking a share of those profits in the name of social justice; they intend to file lawsuits today. Such cases will succeed or fail on their own merits. But regardless of their specific outcomes, one can hope that they spark a larger public discussion of the role of patients in the biomedical research enterprise and lead to establishing a legal and financial claim for their contributions toward the next generation of biomedical research.
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.”