Category Archives: Genome

The Covid-19 crisis that gripped the UK between September 2020 and June 2021 can be thought of as a series of overlapping epidemics, rather than a single event, say researchers at the Wellcome Sanger Institute, EMBLs European Bioinformatics Institute (EMBL-EBI) and their collaborators. During this period, the country wrestled with several versions of the SARS-CoV-2 virus that possessed different biological properties and required a different public health response.

The study, published today (14 October) in Nature, is the most detailed analysis of SARS-CoV-2 genomic surveillance information to date. It describes the scientific story of the pandemic as it unfolded and underlines the importance of high-speed, large-scale genomic surveillance to understand and respond to infectious outbreaks.

In March 2020, just as the UK was preparing to enter the first of several lockdowns, the Covid-19 Genomics UK (COG-UK) consortium was set up to monitor the spread and evolution of SARS-CoV-2 by sequencing the viruss genome1.

Since then, the consortium has identified and monitored numerous viral variants, including the Alpha variant first identified in Kent in September 2020 and the Delta variant first identified in India in April 2021. Both of these variants subsequently changed the course of the pandemic, not only in the UK but globally.

For this study, researchers at the Wellcome Sanger Institute and EMBL-EBI analysed SARS-CoV-2 genomic surveillance data from England2 collected between September 2020 and June 2021. They characterised the growth rates and geographic spread of 71 lineages and reconstructed how newly emerging variants changed the course of the epidemic.

At the end of 2020, the Alpha variant (B.1.1.7) spread despite a series of restrictions, including a national lockdown in November and regional restrictions in December. Though these measures slowed the spread of other variants, Alpha was found to possess a 50 to 60 per cent growth advantage over previous variants and continued to spread rapidly.

In the system of tiered restrictions operating in December 2020, infection rates were higher in areas with fewer restrictions. Alpha was only brought under control in a third national lockdown between January and March 2021, which was introduced after a peak of 72,088 daily cases on 29 December. This measure simultaneously eliminated most variants that had been dominant in September and October 2020. When restrictions began to be lifted on 8 March 2021, the daily case rate had fallen to 5,500.

While Alpha was being brought under control, variants associated with a greater ability to circumvent immunity from vaccination or prior infection continued to appear in the UK at low levels in early 2021. These variants were characterised by the spike mutation E484K, the most significant of which were the Beta variant (B.1.351, first identified in South Africa) and Gamma variant (P.1, first identified in Brazil). But despite repeated introductions of these variants, they were confined to short-lived local outbreaks.

In March 2021, the first samples of B.1.617, which originated in India, began appearing in sequence data. This was in fact two lineages, Kappa (B.1.617.1) and Delta (B.1.617.2). Though Delta contained different mutations to previous variants of concern, these mutations achieved even greater transmissibility3. While Kappa grew slowly and has since faded away, Delta had spread to all local authorities and accounted for 98 per cent of viral genomes sequenced by 26 June 2021.

Dr Moritz Gerstung, a senior author of the paper from EMBL-EBI and The German Cancer Research Centre (Deutsches Krebsforschungszentrum, DKFZ), said: Time has proven how ingenious an idea it was to set up the Covid-19 Genomics UK (COG-UK) consortium at the beginning of the pandemic. Being able to see lineages side-by-side, mapped to specific locations, has been incredibly informative in terms of understanding how this series of epidemics has unfolded. To see Alpha growing faster in nearly 250 out of 315 local authorities was a clear signal that we were dealing with something very different. At the same time, weve learned that the genetics of SARS-CoV-2 are incredibly complex. Even though we knew all of Deltas mutations, it wasnt immediately clear that it would become the dominant lineage, for example.

Analysis of Delta indicates that its growth rate was 59 per cent higher than that of Alpha, the greatest growth advantage observed in any other variant to date. Overall, the researchers estimate that the spread of more transmissible variants between August 2020 and the early summer of 2021 more than doubled the average growth rate of the virus in England.

Dr Meera Chand, COVID-19 incident director at the UK Health Security Agency (UKHSA) and one of the authors of the paper, said: Thanks to genomic surveillance in the UK and internationally, it is clear that we are dealing a virus that has changed considerably since the one that we faced in March 2020. We will continue to monitor the SARS-CoV-2 virus to ensure that we can use the most effective vaccines, treatments and public health measures against current and future variants.

Although it remains impossible to predict what the virus will do next, the COG-UK consortium has advanced the field of genomic surveillance considerably and proven the value of monitoring for infectious agents. Just 18 months after its inception, the programme catalysed the establishment of national sequencing systems that provide near real-time epidemiological information to inform the UKs public health response. It is hoped that one day scientists will be able to predict the emergence of new variants.

Dr Jeff Barrett, a senior author of the paper and Director of the COVID-19 Genomics Initiative at the Wellcome Sanger Institute, said: These genomic surveillance data have given us a totally new way of watching an outbreak unfold, which has taught us a lot about how a new infectious agent spreads and evolves. My hope is that similar genomic surveillance programmes will be developed across the world, so that we are as well-prepared as we can be to respond to future infectious disease outbreaks whether they be familiar pathogens or new ones.

ENDS

Contact details: Dr Matthew MidgleyPress OfficeWellcome Sanger InstituteCambridge, CB10 1SAPhone: 01223 494856Email: press.office@sanger.ac.uk

Notes to Editors:

1 An overview of how Covid-19 genomes are sequenced is available on the Sanger Institute blog. More information on COG-UK is available on their website.

2. These data track SARS-CoV-2 lineages in 315 Lower Tier Local Authorities (LTLAs) in England. An LTLA is an administrative region with approximately 100,000200,000 inhabitants. In total, 281,178 viral genomes were sequenced during this period.

3 Kappa and Delta contained the L452R spike protein mutation, thought to reduce antibody recognition, and P681R, which helps the virus enter human cells in a similar manner to Alphas P681H mutation. Delta contains 5 additional spike protein mutations, the consequences of which are not fully understood yet.

Publication:

Harald S. Vhringer, Theo Sanderson and Matthew Sinnott et al. (2021). Genomic reconstruction of the SARS-CoV-2 epidemic in England. Nature. DOI: 10.1038/s41586-021-04069-y

Funding:

COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute.

Selected websites:

European Bioinformatics Institute (EMBL-EBI)

The European Bioinformatics Institute (EMBL-EBI) is a global leader in the storage, analysis and dissemination of large biological datasets. We help scientists realise the potential of big data by enhancing their ability to exploit complex information to make discoveries that benefit humankind.

We are at the forefront of computational biology research, with work spanning sequence analysis methods, multi-dimensional statistical analysis and data-driven biological discovery, from plant biology to mammalian development and disease.

We are part of EMBL and are located on the Wellcome Genome Campus, one of the worlds largest concentrations of scientific and technical expertise in genomics.

Website:www.ebi.ac.uk

The Wellcome Sanger InstituteThe Wellcome Sanger Institute is a world leading genomics research centre. We undertake large-scale research that forms the foundations of knowledge in biology and medicine. We are open and collaborative; our data, results, tools and technologies are shared across the globe to advance science. Our ambition is vast we take on projects that are not possible anywhere else. We use the power of genome sequencing to understand and harness the information in DNA. Funded by Wellcome, we have the freedom and support to push the boundaries of genomics. Our findings are used to improve health and to understand life on Earth. Find out more at http://www.sanger.ac.uk or follow us on Twitter, Facebook, LinkedIn and on our Blog.

About Wellcome

Wellcome supports science to solve the urgent health challenges facing everyone. We support discovery research into life, health and wellbeing, and were taking on three worldwide health challenges: mental health, global heating and infectious diseases. https://wellcome.org/

Genomic reconstruction of the SARS-CoV-2 epidemic in England

14-Oct-2021

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The inside story of England COVID pandemic described in new study - EurekAlert

Welcome to OncLive On Air! Im your host today, Caroline Seymour.

OncLive On Air is a podcast from OncLive, which provides oncology professionals with the resources and information they need to provide the best patient care. In both digital and print formats, OncLive covers every angle of oncology practice, from new technology to treatment advances to important regulatory decisions.

In todays episode, sponsored by PierianDx, we had the pleasure of speaking with Lucio N. Gordan, MD, to discuss Florida Cancer Specialists move toward the full integration of in-house genomic testing.

Streamlined processes afforded by in-house genomic testing have the potential to provide clinical, collaborative, and financial benefits, according to Gordan, president and managing physician of Florida Cancer Specialists (FCS) & Research Institute, which recently expanded their in-house next-generation sequencing (NGS) capabilities.

In our exclusive interview, Gordan, also of FCS Gainesville Cancer Center, discussed the advantages of in-house genomic testing, the transition from external to internal sequencing, and the anticipated effects of the move.

Check back on Mondays and Thursdays for exclusive interviews with leading experts in the oncology field. For more updates in oncology, be sure to visit http://www.OncLive.com and sign up for our e-newsletters.

OncLive is also on social media. On Twitter, follow us at @OncLive and @OncLiveSOSS. On Facebook, like us at OncLive and OncLive State of the Science Summit and follow our OncLive page on LinkedIn.

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Gordan on Growing the Infrastructure for In-House Genomic Testing - OncLive

Privacy International has warned of a potentially serious breach of privacy regulations by a firm that has been awarded 169.4 million in Government contracts

Privacy campaigners have raised concerns over a Government-approved Coronavirus testing company using customer data to market its own genomics services without affirmative consent, the Byline Intelligence Team and The Citizens can reveal.

In contracts first revealed by Byline Times in November 2020, Dante Labs has been commissioned by the Government to deliver 169.4 million worth of COVID-19 testing services.

Speaking to Byline Times, Privacy Internationals legal officer Lucie Audibert said that COVID-19 testing providers should not be exploiting the various mandatory testing requirements for their own marketing and that the contact details people provide to receive results of their tests should be used for just that not to contact you at a later date to try and sell you other services.

Without providing sufficient information and obtaining valid consent, this can be a serious breach of privacy laws, she added.

When taking the details of customers who are purchasing its tests, Dante pre-populates the tickbox consenting to marketing emails. According to guidelines from the Direct Marketing Association, under GDPR rules, a person gives consent by a statement or by a clear affirmative action. That affirmative action could include ticking a box when visiting an internet website. It goes on to say that pre-ticked boxes or inactivity should therefore not constitute consent.

The Information Commissioners Office (ICO) is also clear, telling companies: Dont use pre-ticked boxes or any other method of default consent.

A Dante customer, who was subsequently targeted by the firm with marketing emails, said that they immediately felt like my data and samples might be used for something else or for something that I might not really be aware of and that when you take a PCR COVID test with Dante Labs, they ask you many questions, including your ethnicity.

Under the UKs General Data Protection Regulation (GDPR)and PECR regulations, it is not permissible for companies to use data gathered for one purpose to then be used for another without the individuals consent. Further, companies need to obtain explicit, informed consent to market other services to customers.

Dante Labs privacy policy states that based on your consent, Dante Labs can, furthermore, process your email address to send you newsletters and marketing communications.

One email promoted Dantes Kurix Premium service, a whole genome sequencing test. It was sent to customers who had ordered a Dante PCR COVID test when travelling abroad.

A spokesperson for the Information Commissioners Office said: Businesses should only contact individuals for electronic marketing purposes where consent has been provided or, in limited circumstances, where they have an existing relationship with a customer. If anyone has concerns about how their data has been handled, they can report these concerns to us.

The Government is at the start of proposing a new data regime to replace GDPR, a law introduced by the EU. The digital rights organisation, Open Rights Group, has warned that Government plans would grant unprecedented freedom to collect, use, and share information regarding buying habits, social relationships, creditworthiness, lifestyle, hobbies, and personality of parents and children for marketing purposes.

If data protections in the UK are watered-down, stories like this could become far morefrequent.

Dante Labs and the company it owns, Immensa Health, have both won large contracts to deliver COVID-19 testing services. In this way, the firms are able to collect data from large numbers of people who are dependent on taking PCR tests to go about their daily lives, including to travel.

This access to a wide and captive customer base is behind the concerns that Dante may be exploiting mandatory testing requirements as suggested by Audibert.

In July, Dante Labs took over one of the Governments Lighthouse Labs, designed to fast-track COVID-19 testing. BusinessLive said that Dante Labs would be delivering COVID-19 testing and clinical whole genome sequencing on a large scale at the lab.

Immensa Health has won two Government contracts for PCR testing worth169,435,000. The largest of the two contracts worth 119,035,000 was awarded without competition under emergency contracting regulations. At the time, Immensa Health had only been founded four months previously.

Immensa has been named as a preferred company in a number of Department of Health and Social Care framework contracts, including as one of 50 suppliers listed in a 15 billion framework agreement for clinical laboratory diagnostic testing services. Immensa is also listed as a supplier in two smaller microbiology framework contracts worth a total of 4 billion across numerous suppliers.

Dante Labs has been expanding significantly in the UK, buying Cambridge Cancer Genomics a leader in machine learning for clinical oncology and is investing 30 million in the UK to run a global surveillance programme of the new variants of the SARS-CoV-2 virus.

A Dante Labs spokesperson told Byline Times: We do not share genetic data with any parties beyond Immensa, a Dante Labs company, and Public Health England, as per Government requirements. The sharing of relevant data with PHE is mandatory and is helping the UK to track the progression of potential COVID-19 variants which, unless monitored closely, could cost many thousands of lives. We do not sell this data, whether individual or aggregated.

Dante Labs did not respond to multiple requests for comment regarding its internal use of customer data. However, after the Byline Intelligence Team contacted the firm, it appeared to have deleted the page that was featured in its marketing emails about Kurix Premium.

Dante is also under investigation by the Competition and Markets Authority (CMA), due to concerns over its treatment of customers. There have been complaints that Dante has been not delivering PCR tests and/or results on time or at all; that it has been failing to respond to complaints or provide proper customer service; refusing or delaying refunds when requested; and using T&Cs which may unfairly limit consumers rights.

It was further revealed on 15 October that at least 43,000 people in the UK may have been wrongly given a negative COVID test by a private laboratory in Wolverhampton, run by Immensa Health Clinic. Operations have now been suspended at the lab.

This article was produced by theByline Intelligence Team a collaborative investigative project formed byByline Times with The Citizens. If you would like to find out more about the Intelligence Team and how to fund its work,click on the button below.

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Genomic Marketing of COVID Testing Company Without People's Affirmative Consent Byline Times - Byline Times

Dr Mishra | (Pic: Edexlive)

In another milestone achieved by Centurion University, Dr Rukmini Mishra, Associate Professor, Department of Botany, School of Applied Sciences, has received a grant titled Engineering Anthracnose Resistance in Chilli Pepper (Capsicum annuum L) using a Single Transcript CRISPR/Cas9 Genome Editing System under the SERB POWER Grant scheme by Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India.

The study will aim at developing a single transcript CRISPR/Cas9 gene-editing platform to introduce sequence-specific mutations at the targeted genetic loci of Capsicum annuum L to engineer broad-spectrum resistance to colletotrichum truncatum, the most aggressive anthracnose pathogen in chilli pepper. It could be used as a benchmark tool for genome engineering in other important solanaceous crops such as tomato, potato and brinjal where fungal pathogenicity is still a big problem.

Prof Supriya Pattanayak, Vice-Chancellor; Dr Anita Patra, Registrar along with the faculty members of the university congratulatedDr Mishra for her achievement. Dr Mishra is currently heading the Department of Botany under the School of Applied Sciences and is also the team lead of the Centre of Genetics and Genomics at Centurion University.

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This associate professor from Centurion University is working on research that could be used as a benchmark tool for genome engineering - EdexLive

I am the proud descendant of people who, at least 1,000 years ago, made one of the riskiest decisions in human history: to leave behind their homeland and set sail into the worlds largest ocean. As the first Native Hawaiian to be awarded a Ph.D. in genome sciences, I realized in graduate school that there is another possible line of evidence that can give insights into my ancestors voyaging history: our mookuauhau, our genome. Our ancestors genomes were shaped by evolutionary and cultural factors, including our migration and the ebb and flow of the Pacific Ocean. They were also shaped by the devastating history of colonialism.

Through analyzing genomes from present-day peoples, we can do incredible things like determine the approximate number of waa (voyaging canoes) that arrived when my ancestors landed on Hawaii island, or even reconstruct the genomes of some of the legendary Chiefs and navigators that discovered the islands of the Pacific. And beyond these scientific and historical discoveries, genomics research can also help us understand and rectify the injustices of the past. For instance, genomics might clarify how colonialism affected things like genetic susceptibility to illnessinformation crucial for developing population specific medical interventions. It can also help us reconstruct the history of land use, which might offer new evidence in court cases over disputed territories and land repatriation.

First, lets examine what we already know from oral tradition and experimental archeology about our incredible voyaging history in the Pacific. Using complex observational science and nature as their guide, my ancestors drew on bird migration patterns, wind and weather systems, ocean currents, the turquoise glint on the bottom of a cloud reflecting a lagoon, and a complex understanding of stars, constellations and physics to find the most remote places in the world. These intrepid voyagers were the first people to launch what Kanaka Maoli (Hawaiian) master navigator Nainoa Thompson refers to as the original moonshot.

This unbelievably risky adventure paid off: In less than fifty generations (1,000 years), my ancestors mastered the art of sailing in both hemispheres. Traveling back and forth along an oceanic superhighway the space of Eurasia in double-hulled catamarans filled to the brim with taro, sweet potatoes, pigs and chickens, using the stars at night to navigate and other advanced techniques and technologies, iteratively perfected over time. This would be humankinds most impressive migratory featno other culture in human history has covered so much distance in such a short amount of time.

The history of my voyaging ancestors and their legacy has been passed to us traditionally through our lelo (language), moolelo (oral history) and hula. As a Kanaka Maoli, I have grown up knowing them: of how Maui pulled the Hawaiian Islands from the sea and how Herb Kne, Ben Finney, Tommy Holmes, Mau Piailug and many other members of the Polynesian Voyaging Society enabled the first noninstrumental voyage from Tahiti to Hawaii in over 600 years aboard the waa, Hklea.

Genomes from modern Pacific Islanders have enabled us to reconstruct precise timings, paths, and branching patterns, or bifurcations, of these ancient voyages giving a refined understanding of the order in which many archipelagoes in the Pacific were settled. By working collaboratively with communities, our approach has directly challenged colonial sciences legacy of taking artifacts and genetic materials without consent. Similar tools to the new genomics have no doubt been misused in the past to justify racist and social Darwinist ends. Yet by using genetic data graciously provided by multiple communities across the Pacific, and by allowing them to shape research priorities, my colleagues and I have been able to I ka w mamua, ka w ma hope, or walk backward into the future.

So how can our knowledge of the genomic past allow us to walk toward this better future? Genome sequence data are not just helpful in providing refined historical information, they also help us understand and treat important contemporary matters such as population-specific disease. The time frame of these ancestors arrival in the Pacific, and the order in which the most remote islands in the world were settled, matters for understanding the incidence and severity among Islander populations of many complex diseases today.

Think of our genetic history as a tree, with present-day populations at the tips of branches and older ones closer to the trunk. Moving backward in timeor from the tips to the trunkyou encounter places where two branches, or populations, were descended from the same ancestor. The places where the branches split represent events in settlement histories in which two populations split, often because of a migration to a new place.

These events provide key insights into what geneticists call founder effects and population bottlenecks, which are extremely important for understanding disease susceptibility. For example, if there is a specific condition in a population at the trunk of a branching event, then populations on islands that are settled later will have a higher chance of presenting that same health condition as well. Founder populations have provided key insights into rare population-specific diseases. Some examples include Ashkenazi Jews and susceptibility to Tay-Sachs disease and Mennonite communities and susceptibility to maple syrup urine disease (MSUD).

This research also sheds important light on colonialism. As European settlers arrived in the Pacific in places such as Hawaii, Tahiti, and Aotearoa (New Zealand), they didnt just bring the printing press, the Bible and gunpowder, they brought deadly pathogens. In the case of many Indigenous peoples, historical contact with Europeans resulted in a population collapse (a loss of approximately 80 percent of an Indigenous populations size), mostly as a result of virgin-soil epidemics of diseases such as smallpox. From Hernn Corts to James Cook, these bottlenecks have shaped the contemporary genetics of Indigenous peoples in ways that directly impact our susceptibility to disease.

By integrating digital sequence information (DSI) from both modern and ancient Indigenous genomes in genetic regions such as the human leukocyte antigen (HLA) system, we can observe a reduction in human genetic variation in contemporary populations, as compared with ancient ones. In this way, we can observe empirically how colonialism has shaped the genomes of modern Indigenous populations.

Today fewer than 1 percent of genome-wide association studies, which identify associations between diseases and genetic variants, and less than 5 percent of clinical trials include Indigenous peoples. We have just begun to develop mRNA vaccine-based therapies that have already shown their ability to save the world. Given their success and potential, why not design treatments, such as gene therapies, that are population specific and reflect the local complexity that speaks to Indigenous peoples unique migratory histories and experiences with colonialism?

Finally, genomics also has the potential to impact the politics of Indigenous rights, and specifically how we think about the history of land stewardship and belonging. For instance, emerging genomics evidence can empirically verify who first lived on contested territoriese.g. indigenous groups could prove how many generations they arrived before colonistswhich could be used in a court of law to settle land and resource repatriation claims.

Genetics gives us insights into the impact of both our peoples proud history of migration and the shameful legacy of colonialism. We need to encourage the use of these data to design treatments for the least, the last, the looked over and the left out, and to generate policies and legal decisions that can rectify the history of injustice. In this way, genomics can connect where we come from to where we will go. Once used to make claims about Indigenous peoples inferiority, today the science of the genome can be part of an Indigenous future we can all believe in.

Read more from the original source:
Genomes Show the History and Travels of Indigenous Peoples - Scientific American

Historical and recent mixing of Europeans, Native Americans, Africans, and Asians has resulted in a relatively large number of admixed individuals in the U.S. The amalgamation of DNA segments associated with different races and ethnicities often affects the ability of physicians to accurately use genomic test results to inform precision care.

To help bridge this gap, researchers at the University of California (UC) San Diego School of Medicine have been awarded $11.7 million to launch the Genetic & Social Determinants of Health: Center for Admixture Science and Technology (CAST) to address the issue of admixed individuals whose DNA reflect multiple ancestries. CAST will use the largest genomic datasets of individuals with diverse ancestry, in combination with socioeconomic data, to better predict health and disease in admixed individuals.

CAST is one of the latest additions to the renowned Centers of Excellence in Genomic Science (CEGS) funded by the NIH. Each center focuses on a unique aspect of genomics research with the intention of blazing new trails in our understanding of human biology and disease.

To bring the CEGS program to our campus is a huge honor, and a national recognition of UC San Diego as a major player in genomics, said Lucila Ohno-Machado, MD, PhD, Distinguished Professor of Medicine at UC San Diego School of Medicine, chair of the Department of Biomedical Informatics at UC San Diego Health, and founding faculty of the Halcolu Data Science Institute.

Ohno-Machado will lead the center with Kelly Frazer, PhD, professor of pediatrics and director of the Institute for Genomic Medicine at UC San Diego School of Medicine, and Melissa Gymrek, PhD, assistant professor at UC San Diego School of Medicine and Jacobs School of Engineering.

Researchers need data on many peoples genomes and health outcomes in order to find consistent relationships among them. The health of individuals from different racial and ethnic groups is also affected by social factors, so this information must be included in models of disease. To do all this, CAST will develop computational tools to combine, protect, and analyze data from two national studies:All of UsResearch Program and the Million Veterans Program. These projects aim to recruit one million participants each, equipping CAST with an unprecedentedly large and diverse pool of data.

Their ultimate goal is for anyone to be able to visit their physician, have their genome sequenced, and learn not only if they are at higher risk for any particular disease, but also which prevention and treatment plans are best suited for them.

As it stands, white people will be able to do this, but our existing knowledge may not be useful to most others, said Gymrek. We want to bring the genomic revolution to everyone.

People may not realize that a large number of people living in America are likely admixed, so we would be excluding a large portion of our community if we were not taking these mixed genomes into account, added Ohno-Machado.

CAST will use advanced approaches to study admixed genomes. Their models will consider each individuals unique patchwork of ancestry, rather than grouping individuals into established categories like white or Asian. And while most groups focus on changes in single nucleotide polymorphisms (SNPs), the CAST team will consider a much broader spectrum of genetic variation. This includes investigating tandem repeats and the major histocompatibility complex (MHC), which is one of the most diverse sections of the genome across races, in part because it is related to immune function, which is tailored to each populations local environment.

CAST will also innovate the way large-scale and complex data is processed. The team will develop privacy-preserving algorithms that consult the data in theAll of Usand the Million Veterans enclaves without needing to centralize the data in a single place. They will also use natural language processing to extract information on social determinants of health from patients clinical notes.

These innovations are expected to come from collaborations between informatics researchers at UC San Diego, the Broad Institute, University of Texas Health, Indiana University and the Veterans Administration.

I really think we have the dream team here, said Frazer. Were excited to use our complementary expertise to push the limits of genomic medicine at UC San Diego and beyond.

See the article here:
New UCSD Genome Center Will Address Genetics, Care Disparities of Admixed Populations - Clinical OMICs News

Soumya Kannan is a 2021-22 Yang-Tan Center for Molecular Therapeutics Graduate Student Fellow in the lab of MIT Professor Feng Zhang and co-first author with Han Altae-Tran of a study reporting a new class of programmable DNA modifying systems known as OMEGAs. Credit: Caitlin Cunningham

Researchers find RNA-guided enzymes are more diverse and widespread than previously believed.

Within the last decade, scientists have adapted CRISPR systems from microbes into gene editing technology, a precise and programmable system for modifying DNA. Now, scientists at MITs McGovern Institute for Brain Research and the Broad Institute of MIT and Harvard have discovered a new class of programmable DNA modifying systems called OMEGAs (Obligate Mobile Element Guided Activity), which may naturally be involved in shuffling small bits of DNA throughout bacterial genomes.

These ancient DNA-cutting enzymes are guided to their targets by small pieces of RNA. While they originated in bacteria, they have now been engineered to work in human cells, suggesting they could be useful in the development of gene editing therapies, particularly as they are small (about 30 percent of the size of Cas9), making them easier to deliver to cells than bulkier enzymes. The discovery, reported on September 9, 2021, in the journal Science, provides evidence that natural RNA-guided enzymes are among the most abundant proteins on Earth, pointing toward a vast new area of biology that is poised to drive the next revolution in genome editing technology.

Comparison of (OMEGA) systems with other known RNA-guided systems. In contrast to CRISPR systems, which capture spacer sequences and store them in the locus within the CRISPR array, systems may transpose their loci (or trans-acting loci) into target sequences, converting targets into RNA guides. Credit: Courtesy of the researchers

The research was led by McGovern Investigator Feng Zhang, who is the James and Patricia Poitras Professor of Neuroscience at MIT, a Howard Hughes Medical Institute investigator, and a Core Institute Member of the Broad Institute. Zhangs team has been exploring natural diversity in search of new molecular systems that can be rationally programmed.

We are super excited about the discovery of these widespread programmable enzymes, which have been hiding under our noses all along, says Zhang. These results suggest the tantalizing possibility that there are many more programmable systems that await discovery and development as useful technologies.

Programmable enzymes, particularly those that use an RNA guide, can be rapidly adapted for different uses. For example, CRISPR enzymes naturally use an RNA guide to target viral invaders, but biologists can direct Cas9 to any target by generating their own RNA guide. Its so easy to just change a guide sequence and set a new target, says Soumya Kannan, MIT graduate student in biological engineering and co-first author of the paper. So one of the broad questions that were interested in is trying to see if other natural systems use that same kind of mechanism.

The first hints that OMEGA proteins might be directed by RNA came from the genes for proteins called IscBs. The IscBs are not involved in CRISPR immunity and were not known to associate with RNA, but they looked like small, DNA-cutting enzymes. The team discovered that each IscB had a small RNA encoded nearby and it directed IscB enzymes to cut specific DNA sequences. They named these RNAs RNAs.

The teams experiments showed that two other classes of small proteins known as IsrBs and TnpBs, one of the most abundant genes in bacteria, also use RNAs that act as guides to direct the cleavage of DNA.

Zhang lab graduate student Han Altae-Tran is co-author of a recent Science paper on OMEGAS with Soumya Kannan. Credit: Courtesy of the Zhang lab

IscB, IsrB, and TnpB are found in mobile genetic elements called transposons. Han Altae-Tran, MIT graduate student in biological engineering and co-first author on the paper, explains that each time these transposons move, they create a new guide RNA, allowing the enzyme they encode to cut somewhere else.

Its not clear how bacteria benefit from this genomic shuffling or whether they do at all. Transposons are often thought of as selfish bits of DNA, concerned only with their own mobility and preservation, Kannan says. But if hosts can co-opt these systems and repurpose them, hosts may gain new abilities, as with CRISPR systems that confer adaptive immunity.

IscBs and TnpBs appear to be predecessors of Cas9 and Cas12 CRISPR systems. The team suspects they, along with IsrB, likely gave rise to other RNA-guided enzymes, too and they are eager to find them. They are curious about the range of functions that might be carried out in nature by RNA-guided enzymes, Kannan says, and suspect evolution likely already took advantage of OMEGA enzymes like IscBs and TnpBs to solve problems that biologists are keen to tackle.

A lot of the things that we have been thinking about may already exist naturally in some capacity, says Altae-Tran. Natural versions of these types of systems might be a good starting point to adapt for that particular task.

The team is also interested in tracing the evolution of RNA-guided systems further into the past. Finding all these new systems sheds light on how RNA-guided systems have evolved, but we dont know where RNA-guided activity itself comes from, Altae-Tran says. Understanding those origins, he says, could pave the way to developing even more classes of programmable tools.

Reference: The widespread IS200/IS605 transposon family encodes diverse programmable RNA-guided endonucleases by Han Altae-Tran, Soumya Kannan, F. Esra Demircioglu, Rachel Oshiro, Suchita P. Nety, Luke J. McKay, Mensur Dlaki, William P. Inskeep, Kira S. Makarova, Rhiannon K. Macrae, Eugene V. Koonin and Feng Zhang, 1 October 2021, Science.DOI: 10.1126/science.abj6856

This work was made possible with support from the Simons Center for the Social Brain at MIT, the National Institutes of Health and its Intramural Research Program, Howard Hughes Medical Institute, Open Philanthropy, G. Harold and Leila Y. Mathers Charitable Foundation, Edward Mallinckrodt, Jr. Foundation, Poitras Center for Psychiatric Disorders Research at MIT, Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, Yang-Tan Center for Molecular Therapeutics at MIT, Lisa Yang, Phillips family, R. Metcalfe, and J. and P. Poitras.

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Discovery Points Toward the Next Revolution in Genome Editing Technology - SciTechDaily

Newswise The NIGMS Human Genetic Cell Repository (HGCR) and NHGRI Sample Repository for Human Genetic Research (SRHGR) now offer high molecular weight (HMW) DNA samples isolated from cell lines in the collections. HMW DNA is useful for long-read next-generation sequencing and studies that investigate large-scale genomic variation such as structural variation.

Recent advances in long-read next-generation sequencing technology, including Pacific BiosciencesSingle Molecule, Real-Time (SMRT) sequencingand Oxford Nanopore TechnologiesNanopore sequencing, have made it possible to produce sequence reads of up to 100 kilobases (kb). This has sparked a growing interest from the research community in obtaining high (100-300kb) and ultra-high (>300kb) molecular weight DNA for long-read sequencing.

Long-read sequencing allows researchers to characterize structural variation in regions of the genome that may be more challenging with other approaches, including inversions, translocations, duplications, and other types of repetitive elements. Additionally, longer sequence read lengths improve the accuracy of haplotype phasing and genome assembly. Long-read sequencing was also utilized to generate a complete sequence of a human genome from a hydatidiform mole cell line in arecent 2021 study, and is currently being utilized by theHuman Pangenome Reference Consortiumin their efforts to improve, expand, and diversify the human reference genome.

Coriells Molecular Biology Laboratory usesCirculomics Nanobind technologyfor automated preparation of high and ultrahigh molecular weight DNA (PMID: 27862402). High quality HMW DNA will be available for several reference samples via our catalog, and additional HMW DNA will be available on-demand as a custom service. A complete list of available samples on our catalog can be foundhere. If you are interested in HMW DNA from a cell line that is not currently available, please submit your request as acustom service.

About the Coriell Institute for Medical Research

Founded in 1953, the Coriell Institute for Medical Research is a nonprofit research institute dedicated to improving human health through biomedical research. Coriell scientists lead research in personalized medicine, cancer biology, epigenetics, and the genomics of opioid use disorder. Coriell also hosts one of the world's leading biobankscomprising collections for the National Institutes of Health, disease foundations and private clientsand distributes biological samples and offers research and biobanking services to scientists around the globe. To facilitate drug discovery and disease study, the Institute also develops and distributes collections of induced pluripotent stem cells. For more information, visit Coriell.org.

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High Molecular Weight DNA Now Available from NIGMS and NHGRI Collections - Newswise

Genetic variation and population substructure in Mexican Indigenous groups is influenced by geography

First, we compared our 716 Mexican Indigenous individuals from 60 ethnic groups (72 communities) with 146 previously published populations worldwide2,8,12, including Mexican Native American populations previously reported by Reich et al.8, Moreno-Estrada et al.2, and Silva-Zolezzi et al.12. The merged data set comprised 3490 individuals from 218 populations and 61,393 autosomal SNVs. Principal component analysis (PCA)13 indicated that Mexican Indigenous populations clustered with other Native American groups from North and South America (Supplementary Fig.1). On the other hand, admixture14 analyses assuming K=4 clusters showed that some Native American individuals are admixed with European and African populations, which is consistent with the history of the Mexican populations. We detected 325 Indigenous samples from the MAIS cohort with at least 0.99 Native American ancestry (Supplementary Fig.2, upper panel).

In order to minimize the effects of recent admixture on our simulations, we performed local ancestry inference using RFMIX15 in each data set, except for Reich et al.8 data set as detailed in the Methods section. Non-Native ancestry tracks were masked in the individuals from Indigenous populations, and the masking accuracy was assessed by running the admixture analyses again assuming K=4 clusters (Supplementary Fig.2, lower panel).

Next, to assess the genetic structure of the Mexican Indigenous populations without the recent European and African ancestry, we combined the masked genomes of the Mexican Indigenous individuals from the MAIS cohort with the data sets from Reich et al.8, Moreno-Estrada et al.2, and Silva-Zolezzi et al.12, yielding a total of 1086 individuals. PCA in the whole Mexican Indigenous masked data set showed that the first axis of variation discriminated the Indigenous Mexican populations from the North, mainly groups from Aridoamerica, from those of Mesoamerica in the Center/South and Southeast (Fig.1b). We also found a correlation between PC1 and the longitude and latitude (Supplementary Fig.3a, b), and a Mantel test showed a significant correlation between genetic and geographical distances (p=0.001, r=0.63, Supplementary Fig.3c). Moreover, PCA of Mesoamerican populations showed that the first two axes of variation separated the populations from the Center/South and Southeast following a geographic pattern (Fig.1c). These results suggest that geographic location influences the genetic structure of these populations.

Furthermore, pairwise-FST comparisons identified the Tarahumara, Pima, Guarijio, and Cucapa in northern Mexico, and previously published populations, such as the Seri (North) and Lacandon (Southeast)2, had the highest levels of genetic differentiation when compared with the other populations based on this statistic (Fig.2a and Supplementary Data1). These observations suggest that these populations have experienced higher degrees of isolation or genetic drift, and possibly various founder effects that amplified this drift.

a Pairwise-FST matrix for all tested populations. Colored bars represent the linguistic family. b FST-based neighbor-joining tree showing the correlation with geographic location independent of linguistic classification (colored names), the numbers above the branches indicate the bootstrap values. Colored vertical lines represent the identified geographic regions: North (blue), Northwest (red), Central-east (orange), South (green), and Southeast (yellow). c Admixture analysis assuming K=9 clusters in Mexican Indigenous populations. Superscript numbers are the corresponding references.

A midpoint rooted neighbor-joining (NJ) tree based on the pairwise-FST population distances showed a correlation between genetic structure and geographic distance, independently of the linguistic classification (Fig.2b). The NJ tree topology revealed five major regions, with high clustering of the ethnic groups according to their geographic location. Furthermore, several ethnic groups from different regions are genetically closer to their geographical neighbors even if they belong to different linguistic families. For example, the Nahuatl from San Luis Potosi (Yuto-nahua), Pames (Oto-mangue), and Huasteco (Mayan) co-inhabiting the Huasteca region fall into the same clade from the NJ tree. Similarly, the Mixe (Mixe-zoque) inhabiting Oaxaca are closer to Oto-mangue linguistic family groups from Oaxaca and the Zoque (Mixe-zoque) from Chiapas are closer to Mayan linguistic family groups (Fig.2a, b).

To better understand the genetic composition of Mexican Indigenous populations, we carried out a genetic clustering analysis with the unsupervised model algorithm ADMIXTURE14 using K=216 clusters (Supplementary Fig.4). The cross-validation procedure showed that, within the Mexican Indigenous populations, the K=9 yields the lowest cross-validation error (Supplementary Fig.5). Based on this K, six of these clusters were mainly observed in a single population (Seri, Tarahumara, Pima, Tepehuano, Huichol, and Lacandon). On the other hand, two of the clusters were mainly observed in several ethnic groups inhabiting the Center and South (here referred to as multi-ethnics), principally in populations from the Oto-mangue linguistic family, and the other cluster in populations from the Southeast that are part of the Mayan linguistic family. We observed that the multi-ethnic and Mayan components had opposite gradients, where the Mayan component was the most prevalent in the Southeast and the multi-ethnic components were more prevalent in the Center and South of Mexico (Fig.2c and Supplementary Fig.6).

To track the demographic histories of Indigenous Mexican populations, we estimated the effective population size (Ne) across time based on two different methods. We included 48 ethnic groups from the masked data set, all of them with sample sizes of at least 10 individuals (Supplementary Table2). Demographic reconstructions based on linkage disequilibrium (LD) analysis16,17 showed little evidence of a fluctuation in Ne before 150 generations ago (Supplementary Fig.7). To evaluate more recent demographic changes, we estimated the Ne based on identity by descent (IBD) tracks implemented in the IBDNe software18,19. We observed a decline in the Ne between 15 and 30 generations ago in all tested populations that overlaps with the beginning of the European colonization of the Americas, followed by an expansion (Fig.3a and Supplementary Fig.8).

a Demographic measure of effective population size across time showing a decline in population sizes in the five main geographic regions identified here: North, Northwest, Center, South and Southeast. b Long-term Ne of all tested populations, shapes represent the long-term Ne and errors bars represent the 95% confidence interval. Colors are according to the legends in Fig.1. Numbers between brackets are the corresponding references. c Divergence time between pairs of populations. d Mean of the observed T between Aridoamerican and Mesoamerican populations expressed in ka.

Next, we estimated the long-term Ne based on LD patterns using Neon Software16,17. The long-term Ne calculated in the whole sample set was 3169 (confidence interval of 29523402), which is similar to previous findings5,20,21. However, here we documented a variation in the long-term Ne between ethnic groups (Fig.3b and Supplementary Table3). The long-term Ne was smaller in highly differentiated populations, such as Seris and Lacandons (984 and 1593, respectively). Other ethnic groups had a long-term Ne between 1825 and 3331 individuals (Supplementary Table3) and are similar to those previously reported in populations such like Tarahumara, Huichol, Triqui, and Maya22. The smaller long-term Ne may have contributed to greater genetic drift and lower genetic diversity in these ethnic groups. To confirm this hypothesis, we inferred autozygosity using runs of homozygosity (ROH). As expected, the Seri and Lacandon groups had the highest proportion of the genome in ROH compared to the other populations tested, suggesting that the high genetic differentiation observed in these populations is due to genetic drift as previously reported2 (Supplementary Fig.9). We did not observe this phenomenon for other divergent populations, such as the Cucapa, Tarahumara, Guarijio, Tepehuano, and Huichol. In addition, the categorization of ROH by size showed that all tested Native American populations have a high proportion of short ROH (12Mb), which is consistent with the fact that these populations have experienced a series of bottlenecks throughout their history23,24. Moreover, with the exception of Yaqui, Mazateco from Oaxaca, Chontal from Oaxaca, and Maya from Yucatan and Quintana Roo, we observed that all tested populations exhibited different proportions of ROH longer than 8Mb (Supplementary Fig.10), which is consistent with the presence of episodes of isolation and/or inbreeding23,24.

Both the long-term Ne and FST between pairs of populations were employed to calculate the divergence time between populations in generations (T) assuming a clean split between them. To scale T in years, we assumed 28 years per generation25. Seri and Lacandon populations have the highest T values compared to other populations (Fig.3c and Supplementary Data2), and the uppermost value of T was observed between Seri and Maya from Quintana Roo (T=11.8 ka ago, Supplementary Data2). Considering the ecogeographic region, we observed a higher T between populations from different regions than those from the same region. Populations from northern Mexico corresponding to Aridoamerica diverged from the populations in the Center/South around 3.969.47 ka ago and from the Southeast populations ~4.84 to 10.15 ka ago (Fig.3c, d and Supplementary Data2).

To better understand the demographic connections among the Mexican indigenous populations, we performed an IBD analysis in 325 individuals from our data set with >99% Native American ancestry using Hap-IBD26 (see Methods section) (Supplementary Table4). We also explored the ethnic group genetic affinities within and between different geographical regions according to those observed in the NJ tree and defined previously by Contreras-Cubas et al.9. In line with that observed with allele frequency-based methods (Supplementary Fig.3), the IBD analysis also showed that the indigenous populations are related to each other following an isolation by distance model, both at the intra and interregional level. Therefore, in most cases, neighboring indigenous populations are more likely to relate to each other than to distant groups (Fig.4 and Supplementary Fig.11). At the intraregional level, this trend is exemplified by Tarahumara and Guarijio from North (Fig.4a) or Chuj and Kanjobal from Southeast (Fig.4e). Additionally, the shared IBD segment analysis revealed gene flow between Indigenous populations from different regions in Mexico. Some examples with shared IBD blocks were observed between Cora from Northwest and Zapoteco from South or Guarijio, Tarahumara and Seri from the North and Mayan groups from the Southeast (Supplementary Data37).

IBD segments analysis performed in Indigenous populations with at least 99% of Native American ancestry inferred from Admixture K=4. Analyses were restricted for segments >7cM. Shared IBD fragments shown proximal and distal connections between populations from the same and different regions. a North IBD segments, b Northeast IBD segments, c Central East IBD segments and d South IBD segments and e Southeast IBD segments. The width of each edge is proportional to the mean IBD length. f Table showing the mean values of IBD sharing within and between regions.

An IBD analysis incorporating all populations per region using both intermediate (510cM) or large (>10cM) shared IBD blocks revealed possible spatiotemporal interaction dynamic patterns among indigenous groups. Intermediate IBD block sizes are suggested to be dated to 5001500 years ago (oldest), while large tracks are thought to be originated 0500 years ago (youngest)27.

Analysis of intermediate block sizes revealed that the Central East, South, and Southeast regions have older connections among them than do the northern regions (Supplementary Fig.11a). Meanwhile, large IBD track analysis suggested that the North region has a more recent gene flow with Northwestern and Central East regions than do South and Southeast regions (Supplementary Fig.11b).

To gain more insight into the early migration patterns, we compared the previously published genomes of the Anzick-128 and Upward Sun River 1 (USR1)29 individuals with our data from the most representative sample of Indigenous peoples in the Mesoamerican and Aridoamerican regions of Mexico to date. First, we compared the ancient genomes with 59 worldwide populations and 325 individuals from our data set with at least 99% Native American ancestry (Supplementary Table4) using an outgroup f3-statistic in the form of f3(Yoruba; Ancient, Modern). This analysis showed a high affinity of both ancient genomes with present-day Mexican Indigenous samples (Supplementary Fig.12 and Supplementary Data8).

We then combined the 325 indigenous samples with seven ancient genomes from American and South American populations3,30 (Supplementary Table5), yielding a total of 111,586 autosomal SNVs. A TreeMix tree on this data set placed the USR1 genome at the basal position of all Native American populations tested, including Anzick-1. Meanwhile, all Aridoamerican populations formed a separate clade from those formed by the Mesoamerican populations and Anzick-1 and the NNA/ANC-B branch. Similarly, a PCA including the ancient samples showed that the Anzick-1 genome is more closely related to Mesoamerican populations than Aridoamerican populations, whereas USR1 is placed as an outlier in the PCA space (Supplementary Fig.13).

The TreeMix tree analysis suggested a deep divergence between populations in Aridoamerica and Mesoamerica (Fig.5a and Supplementary Fig.14) prior to the divergence between Mesoamerica and the Anzick-1 individual. This observation is inconsistent with T<10 ka, as calculated based on FST and long-term Ne (Fig.3c), and the fact that a TreeMix tree allowing 20 migration edges (Supplementary Fig.14) and the IBD networks analyses (Fig.4) exhibited multiple gene flow between Mesoamerican and Aridoamerican populations. To test this, we calculated a D-statistic in the form of D(Yoruba, NNA/ANC-B; AA, MA) using the Ancient Southern Ontario population Canada_Lucier31 and Athabaskan32 ancient genomes as representatives of NNA/ANC-B ancestry. We found these results to be consistent with D ~ 0, suggesting that the NNA/ANC-B populations are an outgroup for those from Aridoamerica and Mesoamerica from Mexico (Supplementary Figs.15 and 16), which is consistent with the TreeMix tree. To test whether Mesoamerican populations form a clade with Anzick-1 to the exclusion of Aridoamerican populations, we estimated a D-statistic in the form of D(Yoruba, AA; Anzick-1, MA). We found that Mesoamerican populations share more alleles with Aridoamerica than Anzick-1 shares with Aridoamerica (Supplementary Fig.17).

a Maximum-likelihood tree inferred from allele frequency, residual plot from the maximum-likelihood tree is shown. b Possible tree topologies resolved by D-statistics. c D-statistic in the form of D(Yoruba, USR1; Mex Nat, Karitiana) shows that all Mexican populations are related to the USR1 genome. d D-statistic in the form of D(Yoruba, Ancient; Mex Nat, Karitiana). Error bars in c, d represent 3 standard errors estimated by a weighted block jackknife. Mex Nat Mexican Native population.

To further explore the relationships between the Indigenous Mexican populations and the ancient samples, we estimated a D-statistic in the form of D(Yoruba, Ancient; Mexican Native population, South American), where the ancient samples were either USR1 or Anzick-1, and the South American samples were either Karitiana or Aymara. We also included the Tzotzil population as an internal control. When USR1 was used to represent the ancient population, we did not observe any significant deviation from zero in any of the tests (Fig.5b and Supplementary Fig.18a, b). However, when Anzick-1 was used in the test, we found that Anzick-1 shares more alleles with the South American population than with some of the Indigenous Mexican populations. This is particularly the case for populations from Aridoamerica, with the exception of Cucapa and Seri, as well as some Mesoamerican populations, such as Totonaco from Veracruz, Nahuatl from Puebla, Otomi from Hidalgo, Mixteco Costa, Chocholteco, Mocho, and as previously observed Mixe. Although we only found significant results (|Z|3.2) when Karitiana and Tzotzil were used in the comparison, we observed a similar trend when Aymara was used in the test (Fig.5c and Supplementary Fig.18c, d). These results suggest that some of the Indigenous populations in our data set carry ancestry from a population that split before the Anzick-1 individual. Previous studies have suggested that the Mixe carry additional ancestry from an unknown population related to the SNA/ANC-A branch that split above the Anzik-1 individual (UPopA)33. Our results are consistent with this observation, suggesting that other populations from Aridoamerica and Mesoamerica may carry this ancestry (Fig.5c and Supplementary Fig.18c, d).

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The genomic landscape of Mexican Indigenous populations brings insights into the peopling of the Americas - Nature.com

This article was originally published here

Cancer Res. 2021 Oct 12:canres.CAN-21-2056-E.2021. doi: 10.1158/0008-5472.CAN-21-2056. Online ahead of print.

ABSTRACT

Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. However, the impact of this instability on the non-coding genome and its three-dimensional organization to aid progression is unclear. Using primary benign and tumor tissue, we find a high concordance in higher order three-dimensional genome organization. This concordance argues for constraints to the topology of prostate tumor genomes. Nonetheless, we identified changes in focal chromatin interactions, typical of loops bridging non-coding cis-regulatory elements, and showed how structural variants can induce these changes to guide cis-regulatory element hijacking. Such events resulted in opposing differential expression of genes found at antipodes of rearrangements. Collectively, these results argue that changes to focal chromatin interactions, as opposed to higher order genome organization, allow for aberrant gene regulation and are repeatedly mediated by structural variants in primary prostate cancer.

PMID:34642184 | DOI:10.1158/0008-5472.CAN-21-2056

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Reorganization of the 3D genome pinpoints non-coding drivers of primary prostate tumors - DocWire News