Category Archives: Transhuman News

Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, US

Usman A. Tahir,Daniel H. Katz,Jeremy M. Robbins,Zsu-Zsu Chen,Mark D. Benson,Daniel E. Cruz,Debby Ngo,Shuliang Deng,Xu Shi,Shuning Zheng,Aaron S. Eisman,Laurie Farrell,James G. Wilson&Robert E. Gerszten

Broad Institute of Harvard and MIT, Cambridge, MA, US

Julian Avila-Pachecho,Alexander G. Bick,Akhil Pampana,Zhi Yu,Clary B. Clish,Pradeep Natarajan&Robert E. Gerszten

University of Mississippi Medical Center, Jackson, MS, US

Michael E. Hall&Adolfo Correa

Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, US

Russell P. Tracy&Peter Durda

The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor UCLA Medical Center, Torrance, CA, US

Kent D. Taylor,Xiuqing Guo,Jie Yao,Yii-Der Ida Chen&Jerome I. Rotter

Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, US

Yongmei Liu

Department of Biostatistics, University of Washington, Seattle, WA, US

W. Craig Johnson,Erin Buth,Matthew Conomos,Ben Heavner,Susanne May,Caitlin McHugh,Sarah C. Nelson,Catherine Tong&Kayleen Williams

Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, US

Ani W. Manichaikul&Stephen S. Rich

Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, US

Ani W. Manichaikul&Stephen S. Rich

Section of Cardiovascular Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA, US

Frederick L. Ruberg

Columbia University Medical Center, New York, NY, US

William S. Blaner

University of Washington, Seattle, Washington, US

Deepti Jain,Peter Anderson,Jennifer Brody,Jai Broome,Colleen Davis,Leslie Emery,Chris Frazar,Stephanie M. Fullerton,Stephanie Gogarten,Alyna Khan,Cathy Laurie,Cecelia Laurie,David Levine,Bruce Psaty,Ken Rice,Josh Smith,Nona Sotoodehnia,Adrienne M. Stilp,Adam Szpiro,Timothy A. Thornton,David Tirschwell,Fei Fei Wang,Bruce Weir&Quenna Wong

Human Genomic Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, US

Claude Bouchard

Department of Exercise Science, University of South Carolina, Columbia, SC, US

Mark A. Sarzynski

Department of Medicine, UT Southwestern Medical Center, Dallas, TX, US

Thomas J. Wang

Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, US

Pradeep Natarajan

New York Genome Center, New York, New York, 10013, US

Namiko Abe,Karen Bunting,Bo-Juen Chen,Heather Geiger,Soren Germer,Melissa Marton,Catherine Reeves,Nicolas Robine,Alexi Runnels,Tanja Smith,Lara Winterkorn&Michael Zody

University of Michigan, Ann Arbor, Michigan, 48109, US

Gonalo Abecasis,Larry Bielak,Thomas Blackwell,Matthew Flickinger,Colin Gross,Sharon Kardia,Jonathon LeFaive,Patricia Peyser,Jacob Pleiness,Albert Vernon Smith,Jennifer Smith,Daniel Taliun,Peter VandeHaar,Jiongming Wang,Ketian Yu&Sebastian Zoellner

Broad Institute, Cambridge, Massachusetts, 2142, US

Francois Aguet,Kristin Ardlie,Mark Chaffin,Seung Hoan Choi,Stacey Gabriel,Namrata Gupta,Carolina Roselli&Seyedeh Maryam Zekavat

Cedars Sinai, Boston, Massachusetts, 2114, US

Christine Albert

Childrens Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, US

Laura Almasy

Emory University, Atlanta, Georgia, 30322, US

Alvaro Alonso,Rich Johnston,Lawrence S. Phillips&Zhaohui Qin

University of Maryland, Baltimore, Maryland, 21201, US

Seth Ament,Amber Beitelshees,Christy Chang,Coleen Damcott,Scott Devine,Mao Fu,Da-Wei Gong,Yue Guan,Elliott Hong,Michael Kessler,Joshua Lewis,Patrick McArdle,Braxton D. Mitchell,May E. Montasser,Jeff OConnell,Tim OConnor,James Perry,Toni Pollin,Robert Reed,Amol Shetty,Elizabeth Streeten,Simeon Taylor&Huichun Xu

University of Mississippi, Jackson, Mississippi, 38677, US

Pramod Anugu,Lynette Ekunwe,Yan Gao,Hao Mei&Nancy Min

National Institutes of Health, Bethesda, Maryland, 20892, US

Deborah Applebaum-Bowden

Johns Hopkins University, Baltimore, Maryland, 21218, US

Dan Arking,Dimitrios Avramopoulos,Emily Barron-Casella,Terri Beaty,Lewis Becker,James Casella,Kimberly Jones,Barry Make,Rasika Mathias,Rakhi Naik,Ingo Ruczinski,Steven Salzberg,Margaret Taub,Dhananjay Vaidya&Lisa Yanek

University of Kentucky, Lexington, Kentucky, 40506, US

Donna K. Arnett

Duke University, Durham, North Carolina, 27708, US

Allison Ashley-Koch&Marilyn Telen

University of Alabama, Birmingham, Alabama, 35487, US

Stella Aslibekyan,Bertha Hidalgo,Marguerite Ryan Irvin&Merry-Lynn McDonald

Stanford University, Stanford, California, 94305, US

Tim Assimes,Chris Gignoux,Marco Perez&Michael Snyder

Medical College of Wisconsin, Milwaukee, Wisconsin, 53211, US

Paul Auer

Providence Health Care, Medicine, Vancouver, CA, US

Najib Ayas

Baylor College of Medicine Human Genome Sequencing Center, Houston, Texas, 77030, US

Adithya Balasubramanian,Huyen Dinh,Harsha Doddapaneni,Shannon Dugan-Perez,Jesse Farek,Richard Gibbs,Yi Han,Jianhong Hu,Ziad Khan,Sandra Lee,Vipin Menon,Ginger Metcalf,Zeineen Momin,Donna Muzny,Caitlin Nessner,Osuji Nkechinyere,Geoffrey Okwuonu,Mahitha Rajendran,Sejal Salvi,Jireh Santibanez&Jennifer Watt

Cleveland Clinic, Cleveland, Ohio, 44195, US

John Barnard,Mina Chung&Serpil Erzurum

Tempus, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, US

Kathleen Barnes

Columbia University, New York, New York, 10032, US

R. Graham Barr

The Emmes Corporation, LTRC, Rockville, Maryland, 20850, US

Lucas Barwick

Cleveland Clinic, Quantitative Health Sciences, Cleveland, Ohio, 44195, US

Gerald Beck

Johns Hopkins University, Medicine, Baltimore, Maryland, 21218, US

Diane Becker

National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, 20892, US

Rebecca Beer,Weiniu Gan,Cashell Jaquish,Andrew Johnson,Dan Levy,James Luo,Julie Mikulla,George Papanicolaou&Pankaj Qasba

Boston University, Massachusetts General Hospital, Boston University School of Medicine, Boston, Massachusetts, 2114, US

Emelia Benjamin

University of Pittsburgh, Pittsburgh, Pennsylvania, 15260, US

Takis Benos,Mark Geraci,Mark Gladwin,Ryan L. Minster&Frank Sciurba

Fundao de Hematologia e Hemoterapia de Pernambuco - Hemope, Recife, 52011-000, BR, Brazil

Marcos Bezerra

University of Washington, Cardiovascular Health Research Unit, Department of Medicine, Seattle, Washington, 98195, US

Joshua Bis

University of Texas Rio Grande Valley School of Medicine, Human Genetics, Brownsville, Texas, 78520, US

John Blangero

University of Utah, Obstetrics and Gynecology, Salt Lake City, Utah, 84132, US

Nathan Blue

University of Texas Health at Houston, Houston, Texas, 77225, US

Eric Boerwinkle,Myriam Fornage&James Hixson

Wake Forest Baptist Health, Department of Biochemistry, Winston-Salem, North Carolina, 27157, US

Donald W. Bowden&Nicholette Palmer

National Jewish Health, National Jewish Health, Denver, Colorado, 80206, US

Russell Bowler,James Crapo,Elizabeth Regan&Snow Xueyan Zhao

Medical College of Wisconsin, Pediatrics, Milwaukee, Wisconsin, 53226, US

Ulrich Broeckel

Here is the original post:
Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals - Nature.com

For nearly 40 years, geneticists have looked to ancient DNA to find answers about our modern condition. And, beyond just ancient DNA, research institutionsincluding Penn Medicinehave sought to sequence current human DNA to better understand how genetic variations affect health and disease.

What Iain Mathieson wants to do is compare the past and present to understand how certain genes have evolved, in the process shining new light on some of today and yesterdays diseases.

What were interested in is, Can we say anything about the phenotypes of these ancient individuals? explains Mathieson, an assistant professor of genetics in the Perelman School of Medicine. A lot of people are trying to use present-day genomes to discover genetic variants in people today that are related to specific diseases. [We want to see if] we can take that information and use it to say anything about the ancient people and their diseases. What were doing is combining ancient genomes with information about genetic variants and diseases from present day people to learn about disease in ancient people.

This summer, Mathieson and postdoctoral researcher Samantha Cox are working with two rising second-year students to collate and analyze existing data from scientific literature conducted around the world. Carson Shin, of Herndon, Virginia, who is an anthropology major in the School of Arts & Sciences, conducts anthropological and archaeological literature reviews to find new archaeological and DNA data. Kaeli Kaymak-Loveless, a computer science major in the School of Engineering and Applied Science, then takes that data and tries to analyze it using the statistical computing program R. The students work is funded by the Center for Undergraduate Research and Fellowships.

While Mathieson is ultimately interested in answering big questions, like how the rise of agriculture influenced the genome, hes first looking to see if his method for comparison works. He and his team of CURF interns are collating DNA data, tracking down information on skeletons, and determining height. Theyre examining height in particular, Mathieson says, because theres already a lot known about genetic variants and their relationship to height in present-day people. If they can accurately predict the height of ancient people through genetics, then, the next question becomes, What else can we say?

What wed like is to be able to say things we cant measure in the skeletons, Mathieson says. One of the big technology changes in the last 10,000 years is the development of agriculture; before that, people lived by hunting and gathering, and in the last 6,000 to 8,000 years many transitioned to an agricultural diet. You might wonder if variants of diseases todayobesity, diabetes, or even some autoimmune diseasesmight have a genetic basis in that diet.

Shin began his first year at Penn as a global health major before switching to anthropology, concentrating in archaeology. Heading into the summer, he knew he wanted to work on a project thats hands-on and interdisciplinary; Mathiesons project felt like a perfect fit.

As an anthropology major, its fascinating to me that even though were so separated from our ancestors by time, so little has actually changed about us as humans, Shin muses. Biologically, were pretty much the same. If I met someone from 3,000 years ago, I wouldnt be looking down on them or looking uptheyd be almost the same height as me, eye to eye.

As hes worked, he says, hes realized that he needs more coding experience and plans to take a half-credit course on R in the Wharton School once he meets prerequisitesthe sort of flexibility he says brought him to Penn in the first place. He says he never expected to take a computer science course, coming to Penn, but has relented.

Ive got to know how to code, he says.

Kaymak-Loveless, meanwhile, began as a bioengineering major before switching to computer science. Shes been weighing what to concentrate in but says the internship has allowed her to settle on computational biology, with an aim to take more biostatistics courses.

Most freshmen struggle to find something meaningful to do in their first summer, and I honestly wasnt really expecting to be doing anything meaningful this summer, says Kaymak-Loveless. But I feel like Im applying myself and learningthis has been a great experience.

Mathieson says he usually works with fourth-year students, but has been really impressed with how quickly Kaymak-Loveless and Shin have learned. In the short-term, Mathieson plans to develop the project into a paper.

But once we establish this technique and the ability to do this [successfully], wed like to use this to learn about traits you cant see in skeletons, related to diet and disease, Mathieson says. Thats the end goal.

Read more:
What the genomes of ancient humans can teach us about modern health | Penn Today - Penn Today

More than half of all cancers have mutations in a gene called p53. The protein made from this gene is whats called a tumor suppressor: When working properly, it guards against cancer development in part, by detecting damaged DNA and alerting cells to repair it.

Cells without working p53 are unable to properly repair damaged DNA, leading to a buildup of mutations, including large chromosomal alterations. Because of its important role in maintaining DNA integrity, scientists long ago dubbed p53 the guardian of the genome.

But 30 years on from that christening, many questions remain about exactly how p53 guards the genome and how its loss promotes cancer.

One hotly debated question has been whether the guardian role of p53 is important for preventing cancer. While tumors with p53 mutations show evidence of chromosomal alterations, research has shown that the normal p53 protein controls several other processes that might explain why its inactivation promotes cancer. For example, p53 promotes apoptosis, or programmed cell death, in cells that have developed precancerous features.

Another question relates to how the genetic instability arises following p53 loss. One longstanding assumption has been that p53 loss acts as a kind of gateway to genetic chaos. In other words, losing the tumor suppressor leads to random buildup of genetic mutations without much rhyme or reason. But a new study from researchers at the Sloan Kettering Institute (SKI) challenges that assumption and brings some insight into p53s guardian role.

Rather than promoting genetic chaos, what we see when cells lose p53 is an orderly progression of genetic changes that is actually quite predictable, says Scott Lowe, Chair of the Cancer Biology and Genetics Program in SKI and the senior author on the study, which was published August 17, 2022, in the journal Nature. That came as a complete surprise to us and suggests a new way to think about possibly treating cancer.

Scientists have struggled to fully understand p53s role in cancer, particularly its effects on the genome, in part because there are few good laboratory models that allow the study of p53 function at the earliest (benign) stages of tumor development, well before cells have acquired obvious cancerous properties.

By staining cells taken from mouse models, researchers can learn about how the loss of the p53 gene leads to cancer. The image on the left shows tumor tissue. The red cells, which have lost p53, are cancerous, and the green cells are not cancerous. The image on the right is taken from normal tissue. It shows a few red cells that have the potential to become cancer interspersed among the green cells.

The vast majority of cancer genomic studies are based on analyzing human tumors, says Timour Baslan, the ONeil Charitable Trust Fellow in the Lowe Lab and one of the papers lead authors. The limited availability of patient tissue before and after tumor development means it has been impossible to gain a temporal picture of how p53 loss leads to cancer, starting from the earliest stages.

To bring those early changes into view, Drs. Baslan and Lowe along with former Lowe Lab members and cancer biologists Zhen Zhao and John P. Morris IV produced a unique mouse model of pancreatic cancer in which p53 mutational status can be detected, irrespective of tumor development, thereby allowing measurements of genetic changes as incipient cancer cells transition from a benign to malignant state.

The models key feature is a set of fluorescent tags that record specific genetic events and can be detected with a microscope. One tag is red and records the presence of a mutated KRAS gene known to be involved in promoting pancreatic cancer in both humans and mice. The other tag is green and records loss of p53. Cells with mutated KRAS but working p53 emit both red and green fluorescence, while cells that are missing p53 emit only red.

This visual trick allowed the scientists to identify specific populations of cells in the mouse that had lost p53 function but were still very far from being a full-fledged cancer. Its sort of like the first step when the wheels start to fall off the wagon, Dr. Lowe says.

By collecting these specific cells and then performing single-cell DNA sequencing on them, the scientists were able to identify the genetic changes that occurred immediately following p53 loss and continuing after.

The mouse really gave us the opportunity to look at a specific stage of cancer evolution, pull it out, and characterize it at a level thats has never been done before, Dr. Baslan says.

To the scientists surprise, the changes they observed always seemed to happen in a consistent pattern. First, the cells lost particular regions of chromosomes called deletions. Later on, genome doubling occurred, but only after a lot of deletions were accrued. Finally, following genome doubling, the cells continued to acquire further deletions but also uniquely gained additional copies of specific genes called gains and amplifications.

Since p53 mutations are often linked with genomic chaos, we were stunned to see there was a preferred order of events, says Dr. Morris, now an assistant professor at the University of North Carolina at Chapel Hill.

The mouse really gave us the opportunity to look at a specific stage of cancer evolution, pull it out, and characterize it at a level that's has never been done before.

Timour Baslan, research fellow

Even though cells from early stages had lost p53, the researchers were able to show that they were not yet cancerous, but instead, required these changes to look and act like cancer cells. Together, these observations suggested to the researchers that p53 loss by itself is not sufficient to cause cancer; instead, cells lacking p53 must acquire additional genetic changes, in an orderly manner, to fully go rogue.

Whats true of the mouse also seems to be true of humans: The scientists could see evidence that the same sorts of deletions, doublings, and amplifications that occur in the mouse also occur in human pancreas tumors.

And its likely not just pancreatic cancer that follows this pattern. Since the team has started discussing their results with colleagues at Memorial Sloan Kettering Cancer Center (MSK), others have been finding similar changes in cancer types besides pancreatic cancer.

Knowing that there are rules to the genetic evolution of tumors suggests a different way of thinking about treating them, the scientists say.

Many existing cancer drugs target gene amplifications in tumors. But because these are acquired late in tumor evolution, not all cells in the tumor will have them. This means that drugs targeting these amplifications may kill off only certain cancer cells, leaving others unscathed.

A more effective approach to treating cancer might be to target the gene deletions that occur very early in cancer development, since these changes will be found in all, or nearly all, tumor cells. (Changes that occur early in tumor evolution are called truncal changes because they are found in the trunk of the tumors evolutionary tree.)

Targeting these deletions could be tricky, but Dr. Lowe says the possibility is there: If its not genetic chaos, and theres order and rules to cancer development, then you might ultimately be able to exploit those rules against the cancer itself, he says.

Fittingly, this new paper comes just after the 30th anniversary of the publication of the original Nature paper, by scientist David Lane, that named p53 the guardian of the genome in the first place. Since that time, scientists have developed a much deeper understanding of p53s importance, with this latest paper bringing the multifaceted role of p53 into the sharpest focus yet.

Read the rest here:
SKI Scientists Solve 30-Year-Old Mystery About p53 Protein Dubbed Guardian of the Genome - On Cancer - Memorial Sloan Kettering

Shahid Akhter, editor, ETHealthworld, spoke to Tony Jose, Co-founder and CEO of Clevergene, to ascertain the roadblocks that still prevent the fast-forward screening of genetic disorders. Genetic Diagnostics: Opportunities & ChallengesToday there are about 7 crore Indians who are living with an undiagnosed genetic disease and about 15 lakh children are born every year with some genetic defect. However, when you look at the number of genetic tests being done, the numbers are just below one lakh, which means there is a huge gap and therefore huge opportunity to offer diagnosis as well as screening tests for genetic disorders.

In the recent past, we have seen an increasing awareness amongst the general population on the incidence of genetic disorders and there is also a pull from the doctors for application of genomics driven diagnosis for their patients. However, one of the challenges that we are seeing at the moment is that the average industry yield or diagnostic yield for these tests are just about 50%. Which means if hundred patients with classical clinical symptoms for a genetic disease take the test, only about 50% are getting clear diagnosis.

This is happening because the current testing methodology as well as the algorithms that are being used for data analysis and reporting work-based on database search. So it's sort of, we generate the data from the patient's DNA and upload that into or compare that with the publicly available mutation database, and if there is a match, we get a diagnosis, and if not, we don't get a diagnosis. And there is also challenge that many of these algorithms are automated only halfway and the last mile reporting has to be done by humans who are trained in Human Genetics.

Another area where we need governmental support is to create guidelines and policies around genetic testing and application of genomics driven test in clinical practice. The rare disease policy of India is a welcoming step towards this which is aimed at spreading the awareness about genetic disorders, building capability for genetic testing as well as giving financial support for patients who have been diagnosed with certain genetic diseases.

Clevergene: Bringing changeClevergene started its journey in genomics in 2013 as a full stack genomics company with expertise in molecular biology, genomics and genomic data analysis. The company has achieved sustenance by offering Discovery Genomics services for discovery of biomarkers genetic disorders and cancer.

So our algorithm is built on the fundamentals of Human Genetics and the inheritance patterns and we have integrated the clinical symptoms, the genomic data that we generate from the patient, the principles of Human Genetics as well as certain knowledge bases into the system. So when we feed a patient data and the clinical symptom, the algorithm calls the mutations or the variations in the DNA and start prioritizing them based on certain parameters that we have set in and throws out the top three, possible mutations and the diagnosis for the patient.

So now the only thing that a clinical interpreter has to do is to look at this last report that comes out, verify and pick the most possible diagnosis and generate the report. This approach has helped us in scaling up the diagnosis to an extent that instead of having an army of clinical interpreters, we only have a handful of specialized clinical Human geneticists who look at the results and create the reports.

We have been offering this test for the last one year through our brand called the Gene Lab, and we've been seeing more than 90% diagnostic yield for the patients who we have tested. Moving forward we are developing assays around genetic screening so our first few tests that would be launching into the market would include genetic carrier screening which looks at almost 2500 autosomal recessive and late onset autosomal dominant disorders. This helps prospective couples to see their carrier status for genetic disorders and the chance of them having offspring with a genetic disease.

The next test that we have developed is the non-invasive prenatal test which we have developed in house which looks at the chromosomal aberrations in a fetus and the chance of the fetus having a genetic disorder.

We are also developing tests around cancer because cancer is another area where in genomics can create an impact. We currently offer tests that are for both for prediction of hereditary cancers as well as precision medicine in cancer.

Clevergenes road map for success is Discovery, Diagnosis, Screening and Cure.

Read more from the original source:
We need a baseline dataset for the Indian human genome that should be publicly available: Tony Jose, Cleverg.. - ETHealthWorld

COVID-19 transmission dynamics in Brazil

The first confirmed infection of SARS-CoV-2 in Brazil was on 26 February 2020 in the State of So Paulo (SP), in a traveller returning from Italy (Fig. 1a). On 17 March 2020, the first COVID-19-related death, a 61-year-old male, was reported in the same state4,5. Four days later, all Brazilian states reported at least one confirmed case of COVID-19 and the Brazilian Ministry of Health (BRMoH) declared an outbreak of large-scale community transmission of the virus6. By 10 April 2020, the virus had already reached remote locations, such as the Yanomami indigenous community located in the state of Roraima in northern Brazil6 (Fig. 1a).

a, Timeline of SARS-CoV-2 key events in Brazil. b, Epidemic curve showing the progression of reported daily viral infection numbers in Brazil from the beginning of the epidemic (grey) and deaths (red) in the same period, with restriction phases indicated by the horizontal bar at the bottom. c, Map of cumulative SARS-CoV-2 cases per 100,000 inhabitants in Brazil up to June 2021.

After the World Health Organization (WHO) declared the outbreak of SARS-CoV-2 as a public health emergency of international concern on 30 January 2020, the Brazilian government introduced restriction measures to mitigate viral spread (Fig. 1a)7. The primary measure involved social isolation, followed by the closure of schools, universities and non-essential businesses8. Additional measures included the mandatory use of personal protective masks9, the cancellation of events expected to attract large numbers of people and tourists, and opening only of services considered as essential such as markets and pharmacies8,10. However, while the epidemic was growing, restriction measures were progressively eased to mitigate negative impacts on the economy. Notably, even during periods of restriction, travel between Brazilian states largely remained possible, enabling SARS-CoV-2 transmission throughout the country11. Travel was probably linked to the emergence of more contagious viral lineages, such as VOC Gamma (lineage P.1) and VUM Zeta (lineage P.2). Notably, these variants may have contributed to a second wave that was more severe in terms of infections and deaths than the first wave (Fig. 1b)11,12,13,14.

The COVID-19 death toll in Brazil rose steadily after March 2021. It reached a daily total of 4,250 deaths on April 2021, the highest number of daily fatalities from COVID-19 worldwide (Fig. 1b). Signs of collapse of the health system were reported in numerous cities around the country. The situation worsened after multiple VOCs and VUMs emerged during a slow vaccination campaign15. Vaccination in Brazil began on 17 January 2021, when the Instituto Butantan imported the first 6 million doses of CoronaVac (a whole-virus inactivated vaccine) from Sinovac Biotech (Fig. 1a)16,17. As of 16 February 2022, approximately 71.8% of the Brazilian population had been vaccinated with the first dose of any of the vaccines available (CoronaVac, AstraZeneca, Pfizer and Janssen), but only 22% were fully vaccinated (with a single dose of Janssen or two doses of any other vaccine)18.

By analysing the total number of COVID-19 notified cases to the end of September 2021, we observed that the Brazilian region with the highest population density (Southeast) also contained the highest number of the cases registered in the country, with the state of So Paulo documenting the largest number of cases (n=4,369,410) in that period (Fig. 1c). However, when we considered the incidence rate (number of reported cases per population) by state, we found that the Midwest, the least populated region in Brazil, had the highest incidence rate, with 13,604.23 cases per 100,000 inhabitants1.

A total of 3,866 near-full genome sequences from SARS-CoV-2 RTqPCR positive samples were obtained as part of this study. SARS-CoV-2 sequencing spanned February 2020 to June 2021, with samples from 8 of the 27 Brazilian states (So Paulo, 3,309; Rio Grande do Sul, 48; Paran, 55; Minas Gerais, 80; Mato Grosso do Sul, 36; Mato Grosso, 51; Bahia, 224) and one neighbouring country, Paraguay (n=63). Almost half of the sequences were from Southeast Brazil, comprising the states of So Paulo and Rio de Janeiro that reported the most cases (Fig. 1c)6. Sequenced genomes were from samples collected from 2,023 females and 1,843 males (Supplementary Tables 1 and 2), with a median age of 41.72 years (range: 1 to 90 years of age). All tested samples contained sufficient viral genetic material (2ngl1) for library preparation. For positive samples, PCR cycle threshold (Ct) values were on average 19.93 (range: 10.7530). Sequences had a median genome coverage of 95% (range: 8099.99) and average genome coverage was typically higher for samples with lower Ct values (Supplementary Fig. 1). Epidemiological information and sequencing statistics of the generated sequences from Brazil and Paraguay are reported in Supplementary Tables 1 and 2, respectively. Sequences were assigned to 39 different PANGO lineages on the basis of the proposed dynamic nomenclature for SARS-CoV-2 lineages (Supplementary Fig. 1, and Tables 1 and 2) and have been submitted to GISAID following the WHO guidelines (Supplementary Tables 1 and 2) (Pangolin version 3.1.7, August 2021).

The rapid spread of SARS-CoV-2, together with the reported circulation of several VOCs and VUMs in Brazil, prompted an intensification of genomic surveillance by the National Network for Pandemic Alert of SARS-CoV-2 at the end of December 2020. As of 30 June 2021, more than 17,135 SARS-CoV-2 genomes from all 27 Brazilian states had been deposited in the GISAID database (Fig. 2a). The states with the highest number of sequenced genomes were So Paulo (n=9,600) and Rio de Janeiro (n=2,031). Although genomic surveillance began as soon as the first confirmed infections were detected in Brazil, by the end of June 2021 there was still a paucity of genomic data from some states, such as Roraima (n=29), Acre (n=29), Rondnia (n=37), Tocantins (n=27), Piau (n=19) and the Federal District (n=33) (Fig. 2a). Half of all Brazilian genomes were deposited in early 2021, suggesting that surveillance was at its peak in the second wave following the emergence of Gamma (and other VOCs (for example, Alpha/B.1.1.7)) and VUMs (for example, Zeta) throughout the country (Fig. 2b).

a, Map of Brazil with the number of sequences in GISAID as of 30 June 2021. The map is coloured according to geographical macro region: North (red), Northeast (green), Southeast (purple), Midwest (light blue) and South (light orange). AC, Acre; AL, Alagoas; AP, Amap; AM, Amazonas; BA, Bahia; CE, Cear; DF, Distrito Federal; ES, Esprito Santo; GO, Gois; MA, Maranho; MT, Mato Grosso; MS, Mato Grosso do Sul; MG, Minas Gerais; PA, Par; PB, Paraba; PR, Paran; PE, Pernambuco; PI, Piau; RR, Roraima; RO, Rondnia; RJ, Rio de Janeiro; RN, Rio Grande do Norte; RS, Rio Grande do Sul; SC, Santa Catarina; SP, So Paulo; SE Sergipe; TO, Tocantins. b, Temporal sampling of sequences in Brazilian states through time with VOCs highlighted and annotated according to their PANGO lineage assignment. c, Time-resolved maximum-likelihood phylogeny containing high-quality near-full genome sequences from Brazil (n=3,866) obtained from this study, analysed against a backdrop of global reference sequences (n=25,288). VUMs and VOCs are highlighted on the phylogeny. d, Sources of viral introductions into Brazil characterized as external introductions from the rest of the world. e, Sources of viral exchanges (imports and exports) into and out of Brazil. f, Number of viral exchanges within Brazilian regions by counting the state changes from the root to the tips of the phylogeny in c.

To understand the dynamics of SARS-CoV-2 spread in Brazil, we coupled epidemiological data with phylodynamic analysis for a data set comprising 25,288 available globally representative genomes, including the genomes sequenced in this study (n=3,866) sampled from 26 December 2019 to 28 June 2021 (Figs. 2c and 3). A date-stamped phylogeny of these data indicated that most of the Brazilian sequences were interspersed with those introduced from several countries (Figs. 2c,d). This pattern further indicated that the co-circulation of multiple SARS-CoV-2 lineages over time was linked to multiple importations followed by large local transmissions concomitant with a high number of infections (Fig. 2c,d).

Time-resolved maximum-likelihood phylogeny containing 17,135 high-quality Brazilian SARS-CoV-2 near-full-genome sequences (n=3,866 generated in this study) analysed against a backdrop of global reference sequences. VUMs and VOCs are highlighted.

Using an ancestral location state reconstruction on the dated phylogeny, we were able to infer the number of viral imports and exports between Brazil and the rest of the world, and between individual Brazilian regions (hereafter referred as the North, Northeast, Midwest, Southeast and South regions) (Fig. 2df). The bulk of imported introductions (estimated to be 114 independent ones) were largely from Europe (Fig. 2d), occurring before the implementation of restriction measures (April 2020) when the epidemic was rapidly progressing (Fig. 2d,e). However, at least 33 introduction events were inferred to have occurred during enforcement of preventive measures up to August 2020 (Fig. 2d,e), and hence before those measures were loosened. Finally, although Brazil was a major virus importer, there were approximately 10 times more inferred exportation events out of Brazil than viral introductions into Brazil (Fig. 2e).

Our estimates of viral movement within Brazil further suggested that the Southeast region was the largest contributor of viral exchanges to other regions, comprising approximately 40% of viral movements from one geographical region to another, followed by the North region that contributed to approximately 25% of all viral movements. Although these estimates are in line with epidemiological data, this observation is probably also influenced by these two regions having the greatest number of sequences available for analysis.

We next focused on two variants (Gamma/P.1 and Zeta/P.2) that evolved from the B.1.1.28 lineage and grew into large transmission clusters during the second wave of the epidemic in Brazil after January 2021. To assess the detailed evolution of these lineages over time, we performed a spatiotemporal phylogeographic analysis using a molecular clock model.

The Gamma VOC was first sampled in Brazil in early January 202112,19. It displayed an unusual number of lineage-defining mutations in the S protein, including three designated that may impact transmission, immune escape and virulenceN501Y, E484K and K417T20,21,22. In line with previous estimates12,19, our phylogeographic analysis suggested that the Gamma variant emerged around 21 November 2020 (95% highest posterior density, 1229 November 2020) in Manaus (Amazonas state) in Northern Brazil and spread extensively among Brazilian regions (Fig. 4a,c). Our data reveal multiple introductions of this lineage from the Amazonas state to Brazils southeastern, northeastern and midwestern states (Fig. 4a,c). By mid-January 2021, the southeastern and northern regions had also acted as source populations for the introduction of this variant into the neighbouring southern region (Fig. 4a,c).

a, Phylogeographic reconstruction of the spread of the Gamma VOC in Brazil. Circles represent nodes of the maximum clade credibility phylogeny and are coloured according to their inferred time of occurrence. Shaded areas represent the 80% highest posterior density interval and depict the uncertainty of the phylogeographic estimates for each node. Solid curved lines denote the links between nodes and the directionality of movement. Differences in population density are shown on a dark-white scale. b, Phylogeographic reconstruction of the spread of the Zeta VUM across Brazil. Circles represent nodes of the maximum clade credibility phylogeny and are coloured according to their inferred time of occurrence. Shaded areas represent the 80% highest posterior density interval and depict the uncertainty of the phylogeographic estimates for each node. Solid curved lines denote the links between nodes and the directionality of movement. Differences in population density are shown on a dark-white scale. c, Number of exchanges of the Gamma variant between Brazilian regions (N, North; NE, Northeast; MD, Midwest; SE, Southeast; S, South). d, Number of exchanges of the Zeta variant between Brazilian regions. e, Sources of viral export of the VOC and VUM from Brazil to the rest of the world.

Zeta (P.2) is defined by the presence of the S:E484K mutation in the receptor binding domain (RBD) and other lineage-defining mutations outside the S protein13,14. Although it was first described in samples from October 2020 in the state of Rio de Janeiro, our phylogeographic reconstruction suggests that the variant originated from Paran state in South Brazil in late August 2020 (95% highest posterior density, 19 August to 03 September 2020) (Fig. 4b). Since then, Zeta has spread multiple times to much of the southeastern, northeastern, midwestern and northern Brazilian regions (Fig. 4d). Together, our results further suggest that the transmission dynamics roughly followed patterns of population density, moving most often between the most populous localities (Fig. 4a,b).

By estimating the pattern of migration flows, we also examined the potential role of Brazil as an exporter of the Gamma and Zeta variants to the rest of the world (Fig. 4). While the North region seeded approximately 47% of all Gamma infections into other regions, consistent with it being where this lineage originated, there is strong evidence both from phylogeographic analysis (Fig. 4a) and ancestral state reconstruction (Fig. 4c) that there was considerable subsequent transfer of Gamma between all regions. Zeta had a different dispersal pattern from Gamma, with 73% of all Zeta movements originating from the Southeast and South regions, consistent with our phylogeographic reconstruction that this is the geographic source of this lineage (Fig. 4).

Our analysis further revealed that Brazil has contributed to the international spread of both variants, with at least 316 and 32 exportation events to the rest of the world detected for Gamma and Zeta variants, respectively (Fig. 4e). Consistent with importations, most exports were to South America (65%) and Europe (14%), followed by Asia (11%), North America (5%), Africa (2.5%) and Oceania (2.5%), with an increase between January and March 2021 coinciding with the second wave of infections in Brazil and some relaxation of international travel restrictions (Fig. 4e). As shown elsewhere, these results demonstrate that under relaxation of travel restrictions, SARS-CoV-2 lineages can spread to a diverse range of international locations23,24,25,26,27,28.

To explore the burden of the Brazilian SARS-CoV-2 pandemic on other South American countries, we provide a preliminary overview of the SARS-CoV-2 epidemic in Paraguay. The first COVID-19 confirmed case was documented in Paraguay on 7 March 2020 in a 32-year-old man from San Lorenzo, Central Department. Thirteen days later, the first death and the first case of community transmission were also confirmed. COVID-19 cases in Paraguay rose sharply in March (Fig. 5a), resulting in 100% occupancy of intensive care beds, prompting the government to declare a strict quarantine to mitigate the spread of the virus29,30. By the end of June 2021, a total number of 460,000 confirmed cases and 15,000 coronavirus-related deaths had been reported in Paraguay29.

a, Epidemic curve showing the progression of reported viral infection numbers in Paraguay from the beginning of the epidemic (grey) and deaths (red) in the same period. b, Progressive distribution of the top 20 PANGO lineages in Paraguay over time. c, Time-resolved maximum-likelihood tree containing high-quality near-complete genome sequences from Paraguay (n=63) obtained in this study, analysed against a backdrop of global reference sequences. VUMs and VOCs are highlighted on the phylogeny. Genome sequences from Paraguay obtained in this study are highlighted with red borders.

The COVID-19 epidemic in Paraguay can generally be characterized by three phases: phase I starting from 10 March 2020, characterized by restriction measures; phase II since 4 May 2020, also called intelligent/smart quarantine with a gradual return to work and social activities; and phase III implemented since 5 October 2020, known as the COVID way of living, characterized by the relaxation of the restriction measures and the reopening of national borders and resumption of international flights30.

Since the beginning of the epidemic, there has been a paucity of whole-genome sequences from Paraguay, with only n=165 whole-genome sequences available on GISAID by the end of July 2021, about 0.0003% of known cases. This seriously impacts the ability to characterize the molecular epidemiology of SARS-CoV-2 at a regional level. In collaboration with the Pan-American Health Organization and the National Public Health Laboratory of Asuncin in Paraguay, we obtained a total of 63 near-complete genome sequences sampled between July 2020 and June 2021, representing ~40% of the currently available genomes from this country. The selection of the samples was based on the Ct value (30) and availability of epidemiological metadata, such as date of sample collection, sex, age and municipality of residence. Thus, by applying these inclusion criteria, only 63 positive samples were considered suitable for this study. As expected, we observed the co-circulation of multiple SARS-CoV-2 lineages (Fig. 5b), linked to multiple importations and subsequently characterized by large transmission clusters.

Importantly, our phylogenetic analysis revealed that most of the SARS-CoV-2 variants currently circulating in Paraguay, including lineages B.1.1.28, B.1.1.33, Zeta and Gamma, originally emerged in Brazil (Fig. 5a,b), thus suggesting cross-border transmission from Brazil to Paraguay (Fig. 5b,c). This reinforces the importance of non-pharmaceutical measures in containing and preventing the spread of viral strains into neighbouring countries.

As of 31 July 2021, a total of 78% of available genomic sequences from Paraguay were linked to infections caused by Brazilian variants, with the Gamma VOC being the most prevalent lineage in the country. As genome sequencing is not widespread, it is difficult to determine how widely these variants have spread within Paraguay and to other Latin American countries. However, the abundance of COVID-19 cases in Brazil, a country that shares borders with ten countries, suggests that this risk is probably high.

Read more here:
Genomic epidemiology of the SARS-CoV-2 epidemic in Brazil - Nature.com

Dr Sanghera said the UKs golden triangle of Oxford, Cambridge, and London could become the Silicon Valley of global genomics provided the government plays its cards well.

If you look at the way Silicon Valley developed it was the result of defence spending after World War Two, which then led to a micro-electronics hub. We could see the same here with life sciences: it could be a big source of export revenues and help a lot of developing countries, he said.

The impediment is the constant crisis overwhelming the NHS. We need to stop using our brilliant technologists to fight fires and create a separate research institute focussed on nothing but genomics. It should be like the cracking of the Enigma Code, he said.

The first dividend of the whole genome is to diagnose illness early and open the way to personalised medicine. The more futuristic second phase is to correct genes through the miracle cure of gene therapy. It is no longer science fiction.

A trial by University College London and Royal Free Hospital and with Freeline Therapeutics concluded last month that a single injection of gene therapy could largely restore normal blood-clotting for patients with Haemophilia B.

Unfortunately, this is much harder to pull off with the common diseases of diabetes, cancer, heart failure, or Alzheimers, since there are so many other variables and triggers a complex cascade in the lingo but the direction of travel is clear.

Kate Tatton-Brown, a professor of genetics at St Georges, said it used to take three months and cost $1,000 to read a single gene. Now we can do all 22,000 genes in parallel in a couple of days. But it is still no easy task to isolate a variant and determine whether an anomaly is noise or the harbinger of disease.

It is like trying to find a needle in a haystack, she said.

Were just at the beginning. We havent even begun to mine the normal genetic variation and understand the complexity of diseases.

Natural variation is the reason why there is no one-size-fits-all treatment but it is also key to our survival as a species. If we all had the same immune system, wed be extinct by now, said Sir Munir Pirmohamed, professor of pharmacogenetics at Liverpool University.

It is estimated that 3pc of all deaths in rich countries are caused by adverse reactions to medical drugs. Some 7pc of hospital patients have serious complications from drugs, and the consequences can be very expensive.

The appropriate dose of warfarin varies wildly for each person. If you get the dose wrong for some auto-immune disorders you can end up with bone-marrow depression or even death.

Sir Munir said pharmacogenetics is starting to pre-empt tragic mistakes. With a point-of-care test for warfarin you can get a result in 45 minutes that tells you the right dose. We could avoid diabetes being triggered by the wrong drug, he said.

Eventually everyone will have a full genome that lasts their whole life, and then we get over the issue of having to do tests each time. You just upload your genome from your smartphone. Bingo. Costs collapse.

If the first gains look like a slow English waltz, they will soon accelerate to a fast tarantella. Genomic science is tracking the evolution of the early internet, before it changed the world entirely and forever, and this time Britain is at the forefront.

So my modest proposal for the next prime minister is simple: issue 5bn of genomic bonds; call it infrastructure investment; exempt it from current fiscal spending under a revamped golden rule; grasp the nettle; do it fast.

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Britain's path to economic and national renewal is the genome revolution - The Telegraph

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The Tasmanian tiger, or thylacine, roamed portions of southern Australia until settlers killed off the dog-sized marsupial carnivore. By 1936, the last of these creatures with distinctive tiger-like stripes on their backs died in captivity. But a Dallas, Texas-based company called Colossal Biosciences plans to bring the thylacine back to Australia through de-extinction, the (aspirational) process of birthing a new version of a lost species.

On the heels of a September 2021 announcement, outlining plans to rebirth the woolly mammoth, Colossal Biosciences has partnered with an Australian scientist to work on the de-extinction of the Tasmanian tiger. Combining the science of genetics with the business of discovery, we endeavor to jumpstart natures ancestral heartbeat, the company says on its website.

Getting that ancestral heartbeat pumping again is no simple feat, though.

Colossal outlines a 10-step process for resurrecting the thylacine, from extinction to birth; that includes sequencing the creatures genome through DNA extracted from a 108-year-old specimen preserved at the Victoria Museum in Australia. Andrew Pask, a professor of biosciences at the University of Melbourne and a member of the Colossal Scientific Advisory Board, will lead the charge on sequencing. As the foremost expert on the thylacine genome, he heads the universitys TIGGR Lab (Thylacine Integrated Genetic Restoration Research).

In 2018, Pasks team published the first genome sequence of the thylacine. While the draft assembly of the thylacine genome contained the overwhelming majority of its genetic information, we were unable to piece everything back together, according to the TIGGR Lab website. Nailing that genome sequence will be the first monumental step in the process toward de-extinction.

If that pans out, bioengineering comes next. That includes everything from sequencing the thylacines closest living relatives, to computational biology to enhance a recipient host genome to be more thylacine-like, and establishing compatible cell lines for cell editing, sequencing, and stem-cell derivation.

Ultimately, this will lead to inserting thylacine genes into the genome of a dasyurid and stimulating embryonic growth until it is ready for a surrogate and eventual birth. The current plan calls for taking stem cells from the living dasyurid, or dunnarta marsupial relative that bears basically no resemblance to the thylacine (think: mouse-like dunnart vs. wolf-like Tasmanian tiger)and then editing genes to get as close to a new thylacine as possible.

Colossal expects this process to last a decade and Pask claims the first version will offer up a de-extincted thylacine-ish thing about 90 percent thylacine with the eventual goal to get to 99.9 percent, he tells Scientific American. In a Jurassic Park-like proposal, the engineered animals will live in their own enclosure with the continued goal of dropping the Tasmanian tiger back into the wild.

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The thylacine started a steady decline when settlers started killing them off due to an incentive of a 1 bounty at the time (along with the help of dingoes). The thylacine was winnowed down to freedom only on the island of Tasmania, and a captive thylacine ended the species run after dying at the Hobart Zoo in 1936.

Not everyone believes this grand de-extinction plan is a sound judgement call. Since 1999, researchers have tried to sequence the genome of the Tasmanian tiger. It hasnt worked. And even if it does pan out in the future, there are ethical questions about how to handle the creature, and if funding couldve been better spent on conservation and protecting currently endangered species.

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With Colossal already moving forward on the woolly mammoth effortthe genome of that animal is sequenced, and scientists will soon place it into the genome of the Asian elephantthe thylacine needs the final 4 percent of its genome sequenced before scientists can explore the possibility of using a dunnart genome for the next steps. Marsupials mark a relatively new world of research, so much of the plan has never before been done, and experts dont believe the thylacine and dunnart are close enough to make it work.

Jeremy Austin from the Australian Centre for Ancient DNA tells the Sydney Morning Herald the entire plan is about media attention for the scientists. De-extinction is a fairytale science, he says. Only a new Tasmanian tiger (or something resembling it) could change that.

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Scientists Are Planning to Resurrect the Extinct Tasmanian Tiger - Popular Mechanics

Insights into the DNA of European flat oysters from a series of studies could inform selective breeding approaches for the scarce shellfish, to improve food security and sustainability.

Scientists from the Roslin Institute developed extensive genetic resources detailing the DNA of oysters and used them to help address the challenges this species faces in terms of conservation, restoration and aquaculture.

Our results could contribute to sustainable food production, as oysters have among the lowest environmental impact of any animal protein production, said Dr Tim Bean, Oyster research expert at the Roslin Institute.

The researchers found that two areas of the oyster genome are significantly associated with faster growth.

The incorporation of genomic information into breeding schemes could be a cost-effective way of enhancing growth traits such as weight and shell size in oysters, scientists concluded.

A separate study, led by scientists from the University of Santiago de Compostela and involving Roslin experts, discovered that variations in a region of oyster DNA may be associated with tolerance to a deadly parasite.

To help understand all the genetics information in their studies, the researchers decoded the complete DNA code of the European flat oyster.

Two high-quality reference genomes were separately built to the chromosome level by the Roslin team and scientists from Sorbonne University in France.

Both genomes have been published in Evolutionary Applications and are already being widely used by oyster researchers in Europe.

Scientists analysed the genome of the European flat oyster to look for variations and assess whether growth traits are under genetic control and could therefore be improved through selective breeding.

This research, published in Frontiers in Genetics, concluded that it is feasible to genetically improve growth traits in oysters.

In a separate study, scientists compared the genome of oysters that had not been exposed to the deadly parasite Bonamia ostreae with that of long-term affected populations.

The team explored areas of the oyster genome previously linked to resilience to the parasite and identified an area that was strongly associated with resilience to the parasite.

The study was published in Evolutionary Applications.

Oysters were once a plentiful source of food and a mainstay of the Scottish people but have long been in decline. The research at the Roslin Institute, in collaboration with UK and European academics, industry, environmental charities and government scientists, used genomics and genetic tools to help inform breeding strategies of the native European flat oyster.

High quality reference genome assemblies are of immense value when applying genetic tools in aquaculture and conservation. Our genome assembly enhances the resources available for flat oyster research, supports ongoing conservation efforts and selective breeding programmes, and improves our understanding of bivalve genome evolution, said Dr Manu Gundappa, Post-doctoral research fellow, Roslin Institute.

Our study shows that breeding programmes for flat oyster aquaculture and restoration would benefit from the incorporation of genetic information to identify the best candidates for breeding, thereby fast-tracking genetic progress in key traits in a sustainable way, said Dr Carolina Pealoza, Post-doctoral research fellow, Roslin Institute.

Continued here:
Using genetics to unlock the growth potential in oysters - The Fish Site

Cambridge-based Constructive Bio has launched as a biotechnology company which will see it create synthetic genomes from scratch.

The technology can be used for commercial applications across a range of industries including agriculture, manufacturing and materials. Novel polymers can also be designed with the ability to breakdown and recycle the monomers to support a circular, sustainable economy a move that could transform the US$750bn global polymers market while simultaneously helping the planet.

Polymers are found in everything from food packaging to mobile phones, plastic bottle to car parts.

The company, which has completed a US$15 million seed round, has also been granted an exclusive license from the Medical Research Council (MRC) to IP developed by The Chin Lab at the MRC Laboratory of Molecular Biology (MRC-LMB).

Over the last 20 years, we have created a cellular factory that we can reliably and predictably program to create new polymers, says Professor Jason Chin, Programme Leader at the MRC Laboratory of Molecular Biology and Chief Scientific Officer of Constructive Bio.

The range of applications for this technology is vast using our approach we have already been able to program cells to make new molecules including from an important class of drugs and to program cells to make completely synthetic polymers containing the chemical linkages found in biodegradable plastics.

Now is the right time to commercialise these technologies. By taking inspiration from nature and reimagining what life can become we have the opportunity to build the sustainable industries of the future.

Constructive Bio is led by CEO and Board member Dr Ola Wlodek, former Chief Operating Officer at Reflection Therapeutics. Ola brings more than 15 years of biopharma and R&D experience.

The company was set-up with support from Ahrens Commercial Engine and with Ahren Science Partner input. The seed round was led by Ahren alongside Amadeus Capital Partners, General Inception and OMX Ventures. The funding will be used to build out the technology platforms for commercial application.

If we think of cellular biosystems as biological factories, we need to be able to write the cells operating system in a rapid, accurate and affordable way, says Pierre Socha, Partner, Amadeus Capital Partners.

The foundational challenge then becomes how to write the DNA of whole living organisms, from scratch, to optimise the manufacturing of these bioproducts. And thats what Constructive Bio is going after. By creating tools that allow us to design and program cells, we will address issues from protein-based therapeutic design, industrial and environmental sustainability, food and agriculture, to consumer care and electronics.

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Constructive Bio targets sustainability with genome tech - Sustainability Magazine

New Jersey, United States Analysis of Genome Editing Market 2022 to 2028, Size, Share, and Trends by Type, Component, Application, Opportunities, Growth Rate, and Regional Forecast

Genome editing is likewise alluded to as quality editing, a group of innovations that empowers scientists to change the DNA of an organic entity. These advancements permit expansion, evacuation or adjustment of hereditary material at specific areas in the genome. Moreover, various approaches have been developed for genome editing. A new one is called CRISPR-Cas9, short for routinely clustered consistently interspaced short palindrome repeats and CRISPR-related protein9. Besides, a ton of fervor has been created in established researchers through the CRISPR-Cas9 framework, which is quicker, cheaper, and more effective than other existing genome editing techniques.

The Genome Editing market, which was valued at US$ million in 2022, is expected to grow at a CAGR of approximately percent over the forecast period, according to our most recent report.

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In addition, the prevention and treatment of human illnesses is of extraordinary importance to genome editing. Most exploration is as of now being improved to comprehend infections using cell and creature models. Researchers are as yet exploring whether this approach is safe and viable for human use. It is being explored in research on a large number of illnesses, for example, single-quality sicknesses like hemophilia, cystic fibrosis, and sickle cell illness. It likewise can possibly treat and prevent complex sicknesses like coronary illness, malignant growth, human immunodeficiency virus (HIV) contamination, and psychological maladjustment. Continuous mechanical progressions in quality editing devices is a main consideration driving the development of the market. Moreover, accessibility of government subsidizing and development in the quantity of genomics projects and an increase in prevalence of disease and other hereditary problems are projected to likewise drive the market development. Whats more, development of CRISPR based novel analytic apparatuses to alleviate the antagonistic impact of the COVID-19 pandemic additionally helped the genome editing market development.

The flare-up of COVID-19 has disrupted work processes in the medical services area across the world. The sickness has constrained various industries to close their entryways temporarily, including a few sub-spaces of medical services. Besides, it affects various medical care administrations, including the genome editing market. At the point when COVID-19 was first recognized, numerous scientists diverted their focus to the investigation of this clever virus and the infection it causes. People working with CRISPR were no exception, and the quality editing apparatus was before long taken to the cutting edges in the worldwide conflict against COVID-19. Moreover, with the innovation in view of a normally happening bacterial quality editing framework that plays a key job the prokaryotic safeguard against viral contamination, the CRISPR Cas framework is intended to battle viruses.

Division Segment

The global genome editing market is segmented based on application, innovation, end user and locale. Based on application, the market is additionally ordered into cell line designing, hereditary designing, drug disclosure, quality altered cell therapy and diagnostics and different applications. By innovation, it is separated into CRISPR, TALEN, ZFN and different advancements. In light of end users, it is partitioned in to scholastics and government foundations, biotechnology and pharma companies, contract research associations. District wise, the market is broken down across North America, Europe, Asia-Pacific, and LAMEA.

By innovation, the CRISPR segment represented the biggest portion of the genome editing market in 2022. The enormous portion of this segment can be credited to the usability related with CRISPR, which gives it a huge benefit over ZFN and TALEN. Pharmaceutical companies segment represented the biggest portion of the genome editing market in 2022. The rising prevalence of infectious illnesses and malignant growth is driving examination exercises worldwide. This is expected to drive the interest for genome editing in biotechnology and pharmaceutical companies.

Regional Analysis

The genome editing/genome designing market is partitioned into five significant districts North America, Europe, Asia Pacific, Latin America (LATAM), and the Middle East and Africa (MEA). North America is projected to represent a significant portion of the global genome editing market during the estimate period. The market in the locale is anticipated to fill from here on out, attributable to development of quality therapy in the U.S., ascend being used of hereditarily changed crops, flood in prevalence of infectious sicknesses and disease, and the accessibility of examination awards and financing are propelling market development in North America.

Competitive Analysis

Key market players and their systems have been dissected to figure out the competitive viewpoint of the market. The key market players profiled in the report incorporates: Agilent Technologies, CRISPR Therapeutics, Danaher, Eurofins Scientific, Editas Medicine, GenScript, Horizon Discovery Limited, Lonza, Merck and Thermo Fisher Scientific.

Click here to Download the full index of the Genome Editing market research report 2022

Contact Us:Amit JainSales Co-OrdinatorInternational: +1 518 300 3575Email: [emailprotected]Website: https://www.infinitybusinessinsights.com

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Genome Editing Market is Slated to Witness Tremendous Growth in Coming Years | Latest Report by IBI - Digital Journal