Artificial Wombs Are Getting Closer to Reality for Premature Babies
In 2017, researchers at the Children's Hospital of Philadelphia grew extremely preterm lambs from hairless to fluffy inside a "biobag," a dark, fluid-filled bag designed to mimic a mother's womb.
"There could be quite a lot of infants that would benefit from artificial womb technologies."
This happened over the course of a month, across a delicate period of fetal development that scientists consider the "edge of viability" for survival at birth.
In 2019, Australian and Japanese scientists repeated the success of keeping extremely premature lambs inside an artificial womb environment until they were ready to survive on their own. Those researchers are now developing a treatment strategy for infants born at "the hard limit of viability," between 20 and 23 weeks of gestation. At the same time, Dutch researchers are going so far as to replicate the sound of a mother's heartbeat inside a biobag. These developments signal exciting times ahead--with a touch of science fiction--for artificial womb technologies. But is there a catch?
"There could be quite a lot of infants that would benefit from artificial womb technologies," says Josephine Johnston, a bioethicist and lawyer at The Hastings Center, an independent bioethics research institute in New York. "These technologies can decrease morbidity and mortality for infants at the edge of viability and help them survive without significant damage to the lungs or other problems," she says.
It is a viewpoint shared by Frans van de Vosse, leader of the Cardiovascular Biomechanics research group at Eindhoven University of Technology in the Netherlands. He participates in a university project that recently received more than $3 million in funding from the E.U. to produce a prototype artificial womb for preterm babies between 24 and 28 weeks of gestation by 2024.
The Eindhoven design comes with a fluid-based environment, just like that of the natural womb, where the baby receives oxygen and nutrients through an artificial placenta that is connected to the baby's umbilical cord. "With current incubators, when a respiratory device delivers oxygen into the lungs in order for the baby to breathe, you may harm preterm babies because their lungs are not yet mature for that," says van de Vosse. "But when the lungs are under water, then they can develop, they can mature, and the baby will receive the oxygen through the umbilical cord, just like in the natural womb," he says.
His research team is working to achieve the "perfectly natural" artificial womb based on strict mathematical models and calculations, van de Vosse says. They are even employing 3D printing technology to develop the wombs and artificial babies to test in them--the mannequins, as van de Vosse calls them. These mannequins are being outfitted with sensors that can replicate the environment a fetus experiences inside a mother's womb, including the soothing sound of her heartbeat.
"The Dutch study's artificial womb design is slightly different from everything else we have seen as it encourages a gestateling to experience the kind of intimacy that a fetus does in pregnancy," says Elizabeth Chloe Romanis, an assistant professor in biolaw at Durham Law School in the U.K. But what is a "gestateling" anyway? It's a term Romanis has coined to describe neither a fetus nor a newborn, but an in-between artificial stage.
"Because they aren't born, they are not neonates," Romanis explains. "But also, they are not inside a pregnant person's body, so they are not fetuses. In an artificial womb the fetus is still gestating, hence why I call it gestateling."
The terminology is not just a semantic exercise to lend a name to what medical dictionaries haven't yet defined. "Gestatelings might have a slightly different psychology," says Romanis. "A fetus inside a mother's womb interacts with the mother. A neonate has some kind of self-sufficiency in terms of physiology. But the gestateling doesn't do either of those things," she says, urging us to be mindful of the still-obscure effects that experiencing early life as a gestateling might have on future humans. Psychology aside, there are also legal repercussions.
The Universal Declaration of Human Rights proclaims the "inalienable rights which everyone is entitled to as a human being," with "everyone" including neonates. However, such a legal umbrella is absent when it comes to fetuses, which have no rights under the same declaration. "We might need a new legal category for a gestateling," concludes Romanis.
But not everyone agrees. "However well-meaning, a new legal category would almost certainly be used to further erode the legality of abortion in countries like the U.S.," says Johnston.
The "abortion war" in the U.S. has risen to a crescendo since 2019, when states like Missouri, Mississippi, Kentucky, Louisiana and Georgia passed so-called "fetal heartbeat bills," which render an abortion illegal once a fetal heartbeat is detected. The situation is only bound to intensify now that Justice Ruth Bader Ginsburg, one of the Supreme Court's fiercest champions for abortion rights, has passed away. If President Trump appoints Ginsburg's replacement, he will probably grant conservatives on the Court the votes needed to revoke or weaken Roe v. Wade, the milestone decision of 1973 that established women's legal right to an abortion.
"A gestateling with intermediate status would almost certainly be considered by some in the U.S. (including some judges) to have at least certain legal rights, likely including right-to-life," says Johnston. This would enable a fetus on the edge of viability to make claims on the mother, and lead either to a shortening of the window in which abortion is legal—or a practice of denying abortion altogether. Instead, Johnston predicts, doctors might offer to transfer the fetus to an artificial womb for external gestation as a new standard of care.
But the legal conundrum does not stop there. The viability threshold is an estimate decided by medical professionals based on the clinical evidence and the technology available. It is anything but static. In the 1970s when Roe v. Wade was decided, for example, a fetus was considered legally viable starting at 28 weeks. Now, with improved technology and medical management, "the hard limit today is probably 20 or 21 weeks," says Matthew Kemp, associate professor at the University of Western Australia and one of the Australian-Japanese artificial womb project's senior researchers.
The changing threshold can result in situations where lots of people invested in the decision disagree. "Those can be hard decisions, but they are case-by-case decisions that families make or parents make with the key providers to determine when to proceed and when to let the infant die. Usually, it's a shared decision where the parents have the final say," says Johnston. But this isn't always the case.
On May 9th 2016, a boy named Alfie Evans was born in Liverpool, UK. Suffering seizures a few months after his birth, Alfie was diagnosed with an unknown neurodegenerative disorder and soon went into a semi-vegetative state, which lasted for more than a year. Alfie's medical team decided to withdraw his ventilation support, suggesting further treatment was unlawful and inhumane, but his parents wanted permission to fly him to a hospital in Rome and attempt to prolong his life there. In the end, the case went all the way up to the Supreme Court, which ruled that doctors could stop providing life support for Alfie, saying that the child required "peace, quiet and privacy." What happened to little Alfie raised huge publicity in the UK and pointedly highlighted the dilemma of whether parents or doctors should have the final say in the fate of a terminally-ill child in life-support treatment.
"In a few years from now, women who cannot get pregnant because of uterine infertility will be able to have a fully functional uterus made from their own tissue."
Alfie was born and, thus had legal rights, yet legal and ethical mayhem arose out of his case. When it comes to gestatelings, the scenarios will be even more complicated, says Romanis. "I think there's a really big question about who has parental rights and who doesn't," she says. "The assisted reproductive technology (ART) law in the U.K. hasn't been updated since 2008....It certainly needs an update when you think about all the things we have done since [then]."
This June, for instance, scientists from the Wake Forest Institute for Regenerative Medicine in North Carolina published research showing that they could take a small sample of tissue from a rabbit's uterus and create a bioengineered uterus, which then supported both fertilization and normal pregnancy like a natural uterus does.
"In [a number of] years from now, women who cannot get pregnant because of uterine infertility will be able to have a fully functional uterus made from their own tissue," says Dr. Anthony Atala, the Institute's director and a pioneer in regenerative medicine. These bioengineered uteri will eventually be covered by insurance, Atala expects. But when it comes to artificial wombs that externally gestate premature infants, will all mothers have equal access?
Medical reports have already shown racial and ethnic disparities in infertility treatments and access to assisted reproductive technologies. Costs on average total $12,400 per cycle of treatment and may require several cycles to achieve a live birth. "There's no indication that artificial wombs would be treated any differently. That's what we see with almost every expensive new medical technology," says Johnston. In a much more dystopian future, there is even a possibility that inequity in healthcare might create disturbing chasms in how women of various class levels bear children. Romanis asks us to picture the following scenario:
We live in a world where artificial wombs have become mainstream. Most women choose to end their pregnancies early and transfer their gestatelings to the care of machines. After a while, insurers deem full-term pregnancy and childbirth a risky non-necessity, and are lobbying to stop covering them altogether. Wealthy white women continue opting out of their third trimesters (at a high cost), since natural pregnancy has become a substandard route for poorer women. Those women are strongly judged for any behaviors that could risk their fetus's health, in contrast with the machine's controlled environment. "Why are you having a coffee during your pregnancy?" critics might ask. "Why are you having a glass of red wine? If you can't be perfect, why don't you have it the artificial way?"
Problem is, even if they want to, they won't be able to afford it.
In a more sanguine version, however, the artificial wombs are only used in cases of prematurity as a life-saving medical intervention rather than as a lifestyle accommodation. The 15 million babies who are born prematurely each year and may face serious respiratory, cardiovascular, visual and hearing problems, as well as learning disabilities, instead continue their normal development in artificial wombs. After lots of deliberation, insurers agree to bear the cost of external wombs because they are cheaper than a lifetime of medical care for a disabled or diseased person. This enables racial and ethnic minority women, who make up the majority of women giving premature birth, to access the technology.
Even extremely premature babies, those babies (far) below the threshold of 28 weeks of gestation, half of which die, could now discover this thing called life. In this scenario, as the Australian researcher Kemp says, we are simply giving a good shot at healthy, long-term survival to those who were unfortunate enough to start too soon.
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.”