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Genome Data from Africa Reveal Millions of New Variants

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Credit: Human Heredity and Health in Africa Initiative

The first Homo sapiens emerged in Africa hundreds of thousands of years ago. We are all descended from that common pool of ancestors. Put another way, we are all Africans. While it’s not possible to study the DNA of these vanished original human populations, it is possible to study the genetic material of today’s African peoples to learn more about the human genome and its evolution over time. The degree of genetic diversity in Africa is greater than anywhere else in the world.

Progress continues to be made in this important area of genomic research. The latest step forward is a study just published in the journal Nature that analyzes more than 400 complete human genomes, including 50 distinct groups of people from 13 African countries. This work has uncovered about 3.4 million unique gene variants that had never before been described, greatly expanding our knowledge of human genetic variation and its implications for health and disease.

This work is the latest from the Human Heredity and Health in Africa (H3Africa) Initiative , which I helped establish a decade ago. This partnership between NIH, the Wellcome Trust, and the Alliance for Accelerating Excellence in Science in Africa (AESA) seeks to train a new generation of African scientists in genomic science and other disciplines, while conducting state-of-the-art health research on the African continent. The hope is to help these scientists use their new knowledge to improve human health in Africa and to help fill significant gaps in our knowledge of the diversity within human genomes.

The new study was led by Zané Lombard, the University of the Witwatersrand, South Africa; Neil Hanchard, Baylor College of Medicine, Houston; and Adebowale Adeyemo, NIH’s National Human Genome Research Institute, Bethesda, MD. It also included more than 50 other H3Africa data providers and data analysts from across Africa and around the world.

These researchers sequenced and analyzed the genomes of 426 individuals, almost all from studies and countries within the H3Africa Consortium, the network of NIH and Wellcome Trust-funded research sites in Africa. These individuals were carefully selected to provide broad coverage of the diverse landscape of African genomic variation. They also included many populations that hadn’t been studied at the genetic level before. The team focused its attention on single-letter differences, also known as single nucleotide variants (SNVs), located across the 3 billion DNA letters of the human genome.

All told, the researchers observed more than 31 million confirmed SNVs. Of the 3.4 million newly discovered SNVs, most turned up in the genomes of individuals from previously unstudied African ethnic groups with their own distinct languages. Even among SNVs that had been previously reported, several were found much more often than in other populations. That’s important because medical geneticists often include information about frequency in deciding whether a gene variant is a likely cause of rare disease. So, this more complete picture of normal genetic variation will be valuable for diagnosing such genetic conditions around the globe.

The researchers also found more than 100 regions of the genome where the pattern of genetic variation was suggestive of underlying variants that were evolutionarily favored at some time in the past. Sixty-two of those chromosomal locations weren’t previously known to be under such strong natural selection in human populations. Interestingly, those selected regions were found to contain genes associated with viral immunity, DNA repair, reproduction, and metabolism, or occurred close to variants that have been associated with conditions such as uterine fibroids and chronic kidney disease.

The findings suggest that viral infections, such as outbreaks of Ebola, yellow fever, and Lassa fever, may have played an important role over centuries in driving genetic differences on the African continent. The data also point to the possibility of human adaptation to differences across the African continent in local environments and diets, and these adaptations could be relevant to common diseases and traits we see now.

The researchers used the data to help gain insight into past migrations of human populations. The genetic data revealed complex patterns of ancestral mixing within and between groups. It also uncovered how distinct groups likely moved large distances across Africa in the past, going back hundreds to thousands of years. The findings also offered a more complete picture of the timing and extent of the migration of speakers of Africa’s most common language group (Bantu) as they moved from West Africa to the southern and eastern reaches of the continent—a defining event in the genetic history of Africa.

There’s still much more to learn about the diversity of human genomes, and a need for continued studies, including many more individuals representing more distinct groups in Africa. Indeed, H3Africa now consists of 51 projects all across the continent, focused on population-based genomic studies of many common health conditions, from heart disease to tuberculosis. As the cradle of all humanity, Africa has much to offer genomic research in the years ahead that will undoubtedly have far-reaching implications for people living in all parts of our planet.


[1] High-depth African genomes inform human migration and health. Choudhury A et al. 2020 Oct;586(7831):741-748.


Human Heredity and Health in Africa (H3Africa) (NIH)

H3Africa (University of Cape Town, South Africa)

NIH Support: National Human Genome Research Institute; National Institute of Allergy and Infectious Diseases

Rogue Antibodies and Gene Mutations Explain Some Cases of Severe COVID-19

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Caption: Colorized scanning electron micrograph of a dying cell (blue) heavily infected with SARS-CoV-2 virus particles (yellow), isolated from a patient sample. Credit: National Institute of Allergy and Infectious Diseases, NIH

One of the many perplexing issues with COVID-19 is that it affects people so differently. That has researchers trying to explain why some folks bounce right back from the virus, or don’t even know they have it—while others become critically ill. Now, two NIH-funded studies suggest that one reason some otherwise healthy people become gravely ill may be previously unknown trouble spots in their immune systems, which hamper their ability to fight the virus.

According to the new findings in hundreds of racially diverse people with life-threatening COVID-19, a small percentage of people who suffer the most severe symptoms carry rare mutations in genes that disrupt their antiviral defenses. Another 10 percent with severe COVID-19 produce rogue “auto-antibodies,” which misguidedly disable a part of the immune system instead of attacking the virus.

Either way, the outcome is the same: the body has trouble fending off SARS-CoV-2, the novel coronavirus that causes COVID-19. The biological reason is there’s not enough of an assortment of signaling proteins, called type I interferons, that are crucial to detecting dangerous viruses like SARS-CoV-2 and sounding the alarm to prevent serious illness.

The research was led by Jean-Laurent Casanova, Howard Hughes Medical Institute and The Rockefeller University, New York; and the Imagine Institute, Necker Hospital, Paris. Casanova and his team began enrolling people with COVID-19 last February, with a particular interest in young adults battling severe illness. They were curious whether inherent weaknesses in their immune systems might explain their surprising vulnerability to the virus despite being otherwise young and healthy. Based on earlier findings in other infectious illnesses, they were especially interested in a set of 13 genes involved in interferon-driven immunity.

In their first study, published in the journal Science, researchers compared this set of genes in 659 patients with life-threatening COVID-19 to the same genes in 534 people with mild or asymptomatic COVID-19 [1]. It turned out that 23, or 3.5 percent, of people with severe COVID-19 indeed carried rare mutations in genes involved in producing antiviral interferons. Those unusual aberrations never turned up in people with milder disease. The researchers went on to show in lab studies that those genetic errors leave human cells more vulnerable to SARS-CoV-2 infection.

The discovery was certainly intriguing, but given the rarity of those mutations, it doesn’t explain most instances of severe COVID-19. Still, it did give Casanova’s team another idea. Perhaps some other people who suffer from severe COVID-19 lack interferons too, but for different reasons. Perhaps their bodies were producing rogue antibodies that were crippling their own antiviral defenses.

In their second study, also in Science, that’s exactly what researchers found in 101 of 987 (over 10 percent) patients from around the world with life-threatening COVID-19 [2]. In the bloodstreams of such individuals, they detected auto-antibodies against an assortment of interferon proteins. Those antibodies, which blocked the interferons’ antiviral activity, weren’t found in people with more mild cases of COVID-19.

Interestingly, the vast majority of patients with those harmful antibodies were men. The findings might help to explain the observation that men are at greater risk than women for developing severe COVID-19. The patients with auto-antibodies also were slightly older, with about half over the age of 65.

Many questions remain. For instance, it’s not yet clear what drives the production of those debilitating auto-antibodies. Might there be more mutations in antiviral defense-related genes that researchers have yet to discover? Is it possible that interferon treatment may help some people with severe COVID-19? Such treatment may be difficult in patients with auto-antibodies, although some clinical trials to explore this possibility already are underway.

The findings, if confirmed, have some potentially immediate implications. It’s possible that screening patients for the presence of damaging auto-antibodies might help to identify those at greater risk for progressing to severe disease. Treatments to remove those antibodies from the bloodstream or to boost antiviral defenses in other ways also may help. Ideally, it would be a good idea to make sure donated convalescent plasma now being tested in clinical trials as a treatment for severe COVID-19 doesn’t contain such disruptive auto-antibodies.

These new findings come from an international effort involving hundreds of scientists called the COVID Human Genetic Effort. Besides its ongoing efforts to understand severe COVID-19, Casanova says his team is also taking a look at the other side of the coin: how some people who’ve been exposed to severe COVID-19 in their own households manage to not get sick. A related international group called the COVID-19 Host Genetics Initiative is pursuing similar goals. Such insights will be invaluable as we continue to manage and treat COVID-19 patients in the future.


[1] Inborn errors of type I IFN immunity in patients with life-threatening COVID-19. Zhang Q, Bastard P, Liu Z, Le Pen J, Moncada-Velez M, Gorochov G, Béziat V, Jouanguy E, Sancho-Shimizu V, Rice CM, Abel L, Notarangelo LD, Cobat A, Su HC, Casanova JL et al. Science. 2020 Sep 24:eabd4570. [Published online ahead of print.]

[2] Auto-antibodies against type I IFNs in patients with life-threatening COVID-19. Bastard P, Rosen LB, Zhang Q, Michailidis E, Hoffmann HH, Gorochov G, Jouanguy E, Rice CM, Cobat A, Notarangelo LD, Abel L, Su HC, Casanova JL et al. Science. 2020 Sep 24:eabd4585. [Published online ahead of print.]


Coronavirus (COVID-19) (NIH)

Interferons (Alpha, Beta) (NIH)

Interferons. Taylor MW. Viruses and Men: A History of Interactions. 2014 July 22. (Pubmed)

Video: Understanding the underlying genetics of COVID-19, Jean-Laurent Casanova (Youtube)

Jean-Laurent Casanova (The Rockefeller University, New York)

COVID Human Genetic Effort

NIH Support: National Institute of Allergy and Infectious Diseases

How COVID-19 Took Hold in North America and Europe

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SARS-CoV-2 Tracking
Caption: SARS-CoV-2 introductions to U.S. and Europe. Credit: Modified from Worobey M, Science, 2020.

It was nearly 10 months ago on January 15 that a traveler returned home to the Seattle area after visiting family in Wuhan, China. A few days later, he started feeling poorly and became the first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) in the United States. The rest is history.

However, new evidence published in the journal Science suggests that this first COVID-19 case on the West Coast didn’t snowball into the current epidemic. Instead, while public health officials in Washington state worked tirelessly and ultimately succeeded in containing its sustained transmission, the novel coronavirus slipped in via another individual about two weeks later, around the beginning of February.

COVID-19 is caused by the novel coronavirus SARS-CoV-2. Last winter, researchers sequenced the genetic material from the SARS-CoV-2 that was isolated from the returned Seattle traveler. While contact tracing didn’t identify any spread of this particular virus, dubbed WA1, questions arose when a genetically similar virus known as WA2 turned up in Washington state. Not long after, WA2-like viruses then appeared in California; British Columbia, Canada; and eventually 3,000 miles away in Connecticut. By mid-March, this WA2 cluster accounted for the vast majority—85 percent—of the cases in Washington state.

But was it possible that the WA2 cluster is a direct descendent of WA1? Did WA1 cause an unnoticed chain of transmission over several weeks, making the Seattle the epicenter of the outbreak in North America?

To answer those questions and others from around the globe, Michael Worobey, University of Arizona, Tucson, and his colleagues drew on multiple sources of information. These included data peretaining to viral genomes, airline passenger flow, and disease incidence in China’s Hubei Province and other places that likely would have influenced the probability that infected travelers were moving the virus around the globe. Based on all the evidence, the researchers simulated the outbreak more than 1,000 times on a computer over a two-month period, beginning on January 15 and assuming the epidemic started with WA1. And, not once did any of their simulated outbreaks match up to the actual genome data.

Those findings suggest to the researchers that the idea WA1 is responsible for all that came later is exceedingly unlikely. The evidence and simulations also appear to rule out the notion that the earliest cases in Washington state entered the United States by way of Canada. A deep dive into the data suggests a more likely scenario is that the outbreak was set off by one or more introductions of genetically similar viruses from China to the West Coast. Though we still don’t know exactly where, the Seattle area is the most likely site given the large number of WA2-like viruses sampled there.

Worobey’s team conducted a second analysis of the outbreak in Europe, and those simulations paint a similar picture to the one in the United States. The researchers conclude that the first known case of COVID-19 in Europe, arriving in Germany on January 20, led to a relatively small number of cases before being stamped out by aggressive testing and contact tracing efforts. That small, early outbreak probably didn’t spark the later one in Northern Italy, which eventually spread to the United States.

Their findings also show that the chain of transmission from China to Italy to New York City sparked outbreaks on the East Coast slightly later in February than those that spread from China directly to Washington state. It confirms that the Seattle outbreak was indeed the first, predating others on the East Coast and in California.

The findings in this report are yet another reminder of the value of integrating genome surveillance together with other sources of data when it comes to understanding, tracking, and containing the spread of COVID-19. They also show that swift and decisive public health measures to contain the virus worked when SARS-CoV-2 first entered the United States and Europe, and can now serve as models of containment.

Since the suffering and death from this pandemic continues in the United States, this historical reconstruction from early in 2020 is one more reminder that all of us have the opportunity and the responsibility to try to limit further spread. Wear your mask when you are outside the home; maintain physical distancing; wash your hands frequently; and don’t congregate indoors, where the risks are greatest. These lessons will enable us to better anticipate, prevent, and respond to additional outbreaks of COVID-19 or any other novel viruses that may arise in the future.


[1] The emergence of SARS-CoV-2 in Europe and North America. Worobey M, Pekar J, Larsen BB, Nelson MI, Hill V, Joy JB, Rambaut A, Suchard MA, Wertheim JO, Lemey P. Science. 2020 Sep 10:eabc8169 [Epub ahead of print]


Coronavirus (COVID-19) (NIH)

Michael Worobey (University of Arizona, Tucson)

NIH Support: National Institute of Allergy and Infectious Diseases; Fogarty International Center; National Library of Medicine

Experts Conclude Heritable Human Genome Editing Not Ready for Clinical Applications

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We stand at a critical juncture in the history of science. CRISPR and other innovative genome editing systems have given researchers the ability to make very precise changes in the sequence, or spelling, of the human DNA instruction book. If these tools are used to make non-heritable edits in only relevant tissues, they hold enormous potential to treat or even cure a wide range of devastating disorders, such as sickle cell disease, inherited neurologic conditions, and muscular dystrophy. But profound safety, ethical, and philosophical concerns surround the use of such technologies to make heritable changes in the human genome—changes that can be passed on to offspring and have consequences for future generations of humankind.

Such concerns are not hypothetical. Two years ago, a researcher in China took it upon himself to cross this ethical red line and conduct heritable genome editing experiments in human embryos with the aim of protecting the resulting babies against HIV infection. The medical justification was indefensible, the safety issues were inadequately considered, and the consent process was woefully inadequate. In response to this epic scientific calamity, NIH supported a call by prominent scientists for an international moratorium on human heritable, or germline, genome editing for clinical purposes.

Following on the heels of this unprecedented ethical breach, the U.S. National Academy of Sciences, U.S. National Academy of Medicine, and the U.K. Royal Society convened an international commission, sponsored by NIH, to conduct a comprehensive review of the clinical use of human germline genome editing. The 18-member panel, which represented 10 nations and four continents, included experts in genome editing technology; human genetics and genomics; psychology; reproductive, pediatric, and adult medicine; regulatory science; bioethics; and international law. Earlier this month, this commission issued its consensus study report, entitled Heritable Human Genome Editing [1].

The commission was designed to bring together thought leaders around the globe to engage in serious discussions about this highly controversial use of genome-editing technology. Among the concerns expressed by many of us was that if heritable genome editing were allowed to proceed without careful deliberation, the enormous potential of non-heritable genome editing for prevention and treatment of disease could become overshadowed by justifiable public outrage, fear, and disgust.

I’m gratified to say that in its new report, the expert panel closely examined the scientific and ethical issues, and concluded that heritable human genome editing is too technologically unreliable and unsafe to risk testing it for any clinical application in humans at the present time. The report cited the potential for unintended off-target DNA edits, which could have harmful health effects, such as cancer, later in life. Also noted was the risk of producing so-called mosaic embryos, in which the edits occur in only a subset of an embryo’s cells. This would make it very difficult for researchers to predict the clinical effects of heritable genome editing in human beings.

Among the many questions that the panel was asked to consider was: should society ever decide that heritable gene editing might be acceptable, what would be a viable framework for scientists, clinicians, and regulatory authorities to assess the potential clinical applications?

In response to that question, the experts replied: heritable gene editing, if ever permitted, should be limited initially to serious diseases that result from the mutation of one or both copies of a single gene. The first uses of these technologies should proceed incrementally and with extreme caution. Their potential medical benefits and harms should also be carefully evaluated before proceeding.

The commission went on to stress that before such an option could be on the table, all other viable reproductive possibilities to produce an embryo without a disease-causing alteration must be exhausted. That would essentially limit heritable gene editing to the exceedingly rare instance in which both parents have two copies of a recessive, disease-causing gene variant. Or another quite rare instance in which one parent has two copies of an altered gene for a dominant genetic disorder, such as Huntington’s disease.

Recognizing how unusual both scenarios would be, the commission held out the possibility that some would-be parents with less serious conditions might qualify if 25 percent or less of their embryos are free of the disease-causing gene variant. A possible example is familial hypercholesterolemia (FH), in which people carrying a mutation in the LDL receptor gene have unusually high levels of cholesterol in their blood. If both members of a couple are affected, only 25 percent of their biological children would be unaffected. FH can lead to early heart disease and death, but drug treatment is available and improving all the time, which makes this a less compelling example. Also, the commission again indicated that such individuals would need to have already traveled down all other possible reproductive avenues before considering heritable gene editing.

A thorny ethical question that was only briefly addressed in the commission’s report is the overall value to be attached to a couple’s desire to have a biological child. That desire is certainly understandable, although other options, such an adoption or in vitro fertilization with donor sperm, are available. This seems like a classic example of the tension between individual desires and societal concerns. Is the drive for a biological child in very high-risk situations such a compelling circumstance that it justifies asking society to start down a path towards modifying human germline DNA?

The commission recommended establishing an international scientific advisory board to monitor the rapidly evolving state of genome editing technologies. The board would serve as an access point for scientists, legislators, and the public to access credible information to weigh the latest progress against the concerns associated with clinical use of heritable human genome editing.

The National Academies/Royal Society report has been sent along to the World Health Organization (WHO), where it will serve as a resource for its expert advisory committee on human genome editing. The WHO committee is currently developing recommendations for appropriate governance mechanisms for both heritable and non-heritable human genome editing research and their clinical uses. That panel could issue its guidance later this year, which is sure to continue this very important conversation.


[1] Heritable Human Genome Editing, Report Summary, National Academy of Sciences, September 2020.


Heritable Genome Editing Not Yet Ready to Be Tried Safely and Effectively in Humans,” National Academies of Sciences, Engineering, and Medicine news release, Sep. 3, 2020.

International Commission on the Clinical Use of Human Germline Genome Editing (National Academies of Sciences, Engineering, and Medicine/Washington, D.C.)

Video: Report Release Webinar , International Commission on the Clinical Use of Human Germline Genome Editing (National Academies of Sciences, Engineering, and Medicine)

National Academy of Sciences (Washington, D.C.)

National Academy of Medicine (Washington, D.C.)

The Royal Society (London)

Genome Data Help to Track COVID-19 Superspreading Event

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Boston skyline
Credit: iStock/Chaay_Tee

When it comes to COVID-19, anyone, even without symptoms, can be a “superspreader” capable of unknowingly infecting a large number of people and causing a community outbreak. That’s why it is so important right now to wear masks when out in public and avoid large gatherings, especially those held indoors, where a superspreader can readily infect others with SARS-CoV-2, the virus responsible for COVID-19.

Driving home this point is a new NIH-funded study on the effects of just one superspreader event in the Boston area: an international biotech conference held in February, before the public health risks of COVID-19 had been fully realized [1]. Almost a hundred people were infected. But it didn’t end there.

In the study, the researchers sequenced close to 800 viral genomes, including cases from across the first wave of the epidemic in the Boston area. Using the fact that the viral genome changes in very subtle ways over time, they found that SARS-CoV-2 was actually introduced independently to the region more than 80 times, primarily from Europe and other parts of the United States. But the data also suggest that a single superspreading event at the biotech conference led to the infection of almost 20,000 people in the area, not to mention additional COVID-19 cases in other states and around the world.

The findings, posted on medRxiv as a pre-print, come from Bronwyn MacInnis and Pardis Sabeti at the Broad Institute of MIT and Harvard in Cambridge, MA, and their many close colleagues at Massachusetts General Hospital, the Massachusetts Department of Public Health, and the Boston Health Care for the Homeless Program. The initial focus of MacInnis, Sabeti, and their Broad colleagues has been on developing genome data and tools for surveillance of viruses and other infectious diseases in and viral outbreaks in West Africa, including Lassa fever and Ebola virus disease.

Closer to home, they’d expected to focus their attention on West Nile virus and tick-borne diseases. But, when the COVID-19 outbreak erupted, they were ready to pivot quickly to assist several Centers for Disease Control and Prevention (CDC) and state labs in the northeastern United States to use genomic tools to investigate local outbreaks.

It’s been clear from the beginning of the pandemic that COVID-19 cases often arise in clusters, linked to gatherings in places such as cruise ships, nursing homes, and homeless shelters. But the Broad Institute team and their colleagues realized, it’s difficult to see how extensively a virus spreads from such places into the wider community based on case counts alone.

Contact tracing certainly helps to track community spread of the virus. This surveillance strategy depends on quick, efficient identification of an infected individual. It follows up with the identification of all who’ve recently been in close contact with that person, allowing the contacts to self-quarantine and break the chain of transmission.

But contact tracing has its limitations. It’s not always possible to identify all the people that an infected person has been in recent contact with. Genome data, however, is particularly useful after the fact for connecting those dots to get a big picture view of viral transmission.

Here’s how it works: as SARS-CoV-2 spreads, the virus sometimes picks up a new mutation. Those tiny spelling changes in the viral genome usually have no effect on how the virus causes disease, but they do serve as distinct genomic fingerprints. Using those fingerprints to guide the way, researchers can trace the path the virus took through a community and beyond, identifying connections among cases that would be untrackable otherwise.

With this in mind, MacInnis and Sabeti’s team set out to help Boston’s public health officials understand just how the epidemic escalated so quickly in the Boston area, and just how much the February conference had contributed to community transmission of the virus. They also investigated other case clusters in the area, including within a skilled nursing facility, homeless shelters, and at Massachusetts General Hospital itself, to understand the spread of COVID-19 in these settings.

Based on contact tracing, officials had already connected approximately 90 cases of COVID-19 to the biotech conference, 28 of which were included in the original 772 viral genomes in this dataset. Based on the distinct genomic fingerprint carried by the 28 genomes, the researchers went on to discover that more than one-third of Boston area cases without any known link to the conference could indeed be traced back to the event.

When the researchers considered this proportion to the number of cases recorded in the region during the study, they extrapolated that the superspreader event led to nearly 20,000 cases in the Boston area. In contrast, the genome data show cases linked to another superspreader event that took place within a skilled nursing facility, while devastating to the residents, had much less of an impact on the surrounding community.

The analysis also uncovered some unexpected connections. The dataset showed that SARS-CoV-2 was brought to clients and staff at the Boston Health Care for the Homeless Program at least seven times. Remarkably, two of those introductions also traced back to the biotech conference. Researchers also found infections in Chelsea, Revere, and Everett, which were some of the hardest hit communities in the Boston area, that were connected to the original superspreading event.

There was some reassuring news about how precautions in hospitals are working. The researchers examined cases that were diagnosed among patients at Massachusetts General Hospital, raising concerns that the virus might have spread from one patient to another within the hospital. But the genome data show that those cases, in fact, weren’t part of the same transmission chain. They may have contracted the virus before they were hospitalized. Or it’s possible that staff may have inadvertently brought the virus into the hospital. But there was no patient-to-patient transmission.

Massachusetts is one of the states in which the COVID-19 pandemic had a particularly severe early impact. As such, these results present broadly applicable lessons for other states and urban areas about how the virus spreads. The findings highlight the value of genomic surveillance, along with standard contact tracing, for better understanding of viral transmission in our communities and improved prevention of future outbreaks.


[1] Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events. Lemieux J. et al. medRxiv. August 25, 2020.


Coronavirus (COVID-19) (NIH)

Bronwyn MacInnis (Broad Institute of Harvard and MIT, Cambridge, MA)

Sabeti Lab (Broad Institute of Harvard and MIT)

NIH Support: National Institute of Allergy and Infectious Diseases; National Human Genome Research Institute; National Institute of General Medical Sciences

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