Category Archives: Genome

SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--Genome Medical, the leading nationwide genomic care delivery company, today announced that it will acquire GeneMatters, a telehealth genetic counseling and software solutions company. Simultaneously, the company announced the closing of a $60 million Series C financing to accelerate commercial traction and advance its mission of transforming health care for all through genomic medicine. These strategic initiatives solidify its position as the preeminent technology-enabled provider of genetic health services and genomic insights.

The addition of GeneMatters, along with our Series C financing, propels us into the next phase of commercial growth and enables us to realize the genome-driven personalization of health, said Lisa Alderson, co-founder and CEO of Genome Medical. The genomic medicine industry is primed with testing capabilities and novel therapeutics; now is clearly the moment for Genome Medical to deliver expanded availability of genomic medicine for patients and providers.

Genome Medical will use the financing proceeds to expand its team and further enhance the development of its configurable technology solutions to provide innovative and efficient genomic medicine programs. The company will continue to build out its full suite of physician services, test ordering capabilities and guidelines-based care plans to ensure comprehensive, seamless care for patients.

The Series C round was led by Casdin Capital, a committed and leading long-term investor in life sciences and genomics, and was joined by new investors GV (formerly Google Ventures) and Amgen Ventures. Existing investors also participated, including Perceptive Advisors, Canaan Partners, Kaiser Permanente Ventures, Illumina Ventures, LRVHealth, Echo Health Ventures, Revelation Partners, HealthInvest Equity Partners, Avestria Ventures, Flywheel Ventures, Dreamers Fund and Blue Ivy Ventures.

In connection with the financing, the Genome Medical Board of Directors will be joined by Eli Casdin, founder and chief investment officer at Casdin Capital; Shaun Rodriguez, director of life science research at Casdin Capital; and Jill Davies, co-founder and president of GeneMatters. Anthony Philippakis, M.D., Ph.D., venture partner at GV, will join the board as an observer.

We feel fortunate to have been in the unique position to facilitate this strategic combination of two strong genomic health providers and Casdin portfolio companies, Eli Casdin said. We have been an early and active investor in the development of genetic testing capabilities broadly. The breadth and scale of Genome Medical and GeneMatters together produce the clear leader in digital health for genomics. It is also a terrific example of how one + one can equal more than two!

Together, Genome Medical and GeneMatters represent expanded technology solutions and clinical expertise to better meet the growing need for genomic medicine across health and wellness. GeneMatters will operate as a wholly owned subsidiary of Genome Medical Holding Company, with a focus on expanding the delivery of genetic services to community health systems and other partners.

The mission of GeneMatters from day one has been to increase patient access to genetic services and to support patient decision-making, said GeneMatters Davies. Joining the Genome Medical family allows for expanded capabilities, broader reach and ultimately more patients and providers being served. We are thrilled to be joining forces with this talented team that shares our mission, vision and passion for patient care.

By combining innovative, technology-enabled solutions with the virtual delivery of industry-leading clinical expertise, Genome Medical is accelerating the adoption of genetic services and genomic medicine for health care systems, large-scale research studies, health plans, employers, providers and molecular diagnostic testing laboratories. Learn more about Genome Medicals comprehensive services, including its Genome Care DeliveryTM platform and precision insights for population genomics.

About Genome Medical

Genome Medical, the leading genomic care delivery company, is personalizing health care for all through on-demand access to genetic insights and genomic medicine. We operate as an independent virtual medical practice, powered by a digital health technology platform. By partnering with health systems, providers, health plans, employers, labs and biopharma, we expand the reach and impact of precision medicine. We provide clinical assessments and tools, test recommendations and ordering, and personalized care plans to deliver optimal patient care and improve health outcomes. The company, which is headquartered in South San Francisco, was recently honored as The Best Digital Health Company to Work For by Rock Health, Fenwick & West and Goldman Sachs in their Top 50 in Digital Health awards. To learn more, visit genomemedical.com and follow @GenomeMed.

About GeneMatters

GeneMatters is a leading provider of telehealth genetic counseling and software solutions to increase access to genetic services. We deliver customizable solutions to hospitals, health networks, genetic testing labs and biopharmaceutical organizations to extend the capacity of existing genetic counseling teams, support new programs and increase patient engagement with genetic services. Our genetic expertise spans oncology, reproductive, cardiovascular and rare diseases. Founded in 2016 by Jill Davies, a genetic counselor, with a mission to increase patient access, we are committed to outstanding service delivery, unwavering quality standards, high patient satisfaction and technology to simplify care. To learn more, visit gene-matters.com and follow @GeneMatters on Twitter Linkedin

Follow this link:
Genome Medical Announces Acquisition of GeneMatters and Closing of $60 Million Series C Financing - Business Wire

CHAMPAIGN, Ill. A new paper co-written by a University of Illinois Urbana-Champaign scholar who studies the legal and ethical implications of advanced biotechnologies outlines an unexplored tool to regulate the medically and ethically dubious practice of heritable human-genome editing: patent law.

Applied judiciously, patent law could create an ethical thicket around human genome editing that ultimately discourages access to germline editing that is, changing sperm and egg to create designer children in more permissive countries such as China, Greece, Mexico, Spain, and Ukraine, said Jacob S. Sherkow, a professor of law and an affiliate of the Carl R. Woese Institute for Genomic Biology at Illinois.

The World Health Organization has explored international governance tools for human genome engineering, but as long as individual countries are allowed to set and enforce their own policies, the possibility of people engaging in medical tourism to other countries to circumvent domestic prohibitions remains a risk, the authors said in a paper published by the Journal of the American Medical Association.

A lot of policymakers and medical practitioners are concerned with some of the genomic editing technologies out there, specifically with technologies that focus on allowing parents to pick and choose their childrens height, eye color, skin tone and the like, Sherkow said. Generally speaking, reproductive technologies are somewhat regulated, but U.S. rules are totally different from what they are in Canada, certain EU countries, the United Kingdom or China. And there is no international enforcement agency out there thats going to stop people from engaging in genetic medical tourism.

So there isnt much international harmony on the issue, and its just inherently something thats pretty inimical to an international governance framework. But the gene-editing technology itself is patentable and that could potentially be an under-the-radar tool to thwart this undesirable behavior.

Theres already a trend in the U.S. toward patenting human heritable germline-editing technology, Sherkow said.

Patent protection affords researchers and their institutions significant power over the ethical limits of using such technologies, he said. For institutions that develop these technologies, its essential to build the ethical limits of their intellectual property into the patent licensing process.

Even though patents are only enforceable in whatever country theyre granted, using patent law as an enforcement mechanism would potentially allow owners to go to court to stop someone else from using a piece of technology in a way that they dont like, Sherkow said.

The typical economic conceit behind patents is it allows an inventor who doesnt like that theyre not getting paid for something they created to sue, he said. But that scope can also include the ways in which the technology is being used, like if its being used in an unethical manner by others.

Sherkow and his co-authors said this could be especially important for countries where patent laws and regulatory systems surrounding gene-editing technologies diverge.

Some countries have strong patent protections but weak regulatory protection, while other countries are the opposite, Sherkow said. Using patent protections that are granted in countries that otherwise have a weaker regulatory system we think thats an economically sensible and politically feasible path forward.

As a strategy, its not a silver bullet but a hurdle to trip up bad actors, Sherkow said.

Its not a complete solution by any means, as it relies on private interests to police the social harms of a private activity, he said. But patents present an opportunity to combine the tools of commercialization and ethical behavior in a manner not readily available in other enforcement mechanisms, especially given the disparate international regulation. So this is a particularly important moment to consider ethical governance by patent, and we think its a pretty significant arrow in the regulatory quiver.

Sherkows co-authors are Eli Y. Adashi, of Brown University, and I. Glenn Cohen, of Harvard Law School.

Read the original post:
Paper: Use patent law to curb unethical human-genome editing - University of Illinois News

Simon-Loriere, E. & Holmes, E. C. Why do RNA viruses recombine?. Nat. Rev. Microbiol. 9, 617626. https://doi.org/10.1038/nrmicro2614 (2011).

CAS Article PubMed PubMed Central Google Scholar

Dhama, K. et al. Coronavirus disease 2019-COVID-19. Clin. Microbiol. Rev. 33, e0002820. https://doi.org/10.1128/cmr.00028-20 (2020).

CAS Article Google Scholar

Cheng, V. C., Lau, S. K., Woo, P. C. & Yuen, K. Y. Severe acute respiratory syndrome coronavirus as an agent of emerging and reemerging infection. Clin. Microbiol. Rev. 20, 660694. https://doi.org/10.1128/cmr.00023-07 (2007).

CAS Article PubMed PubMed Central Google Scholar

Neches, R. Y., McGee, M. D. & Kyrpides, N. C. Recombination should not be an afterthought. Nat. Rev. Microbiol. 18, 606. https://doi.org/10.1038/s41579-020-00451-1 (2020).

CAS Article PubMed Google Scholar

Paraskevis, D. et al. Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event. Infect. Genet. Evol. 79, 104212. https://doi.org/10.1016/j.meegid.2020.104212 (2020).

CAS Article PubMed PubMed Central Google Scholar

Wu, A. et al. Mutations, Recombination and Insertion in the evolution of 2019-nCoV. bioRxiv https://doi.org/10.1101/2020.02.29.971101 (2020).

Article PubMed PubMed Central Google Scholar

Vijgen, L. et al. Complete genomic sequence of human coronavirus OC43: Molecular clock analysis suggests a relatively recent zoonotic coronavirus transmission event. J. Virol. 79, 15951604. https://doi.org/10.1128/jvi.79.3.1595-1604.2005 (2005).

CAS Article PubMed PubMed Central Google Scholar

Zhang, Y. et al. Genotype shift in human coronavirus OC43 and emergence of a novel genotype by natural recombination. J. Infect. 70, 641650. https://doi.org/10.1016/j.jinf.2014.12.005 (2015).

Article PubMed Google Scholar

Zhang, Z., Shen, L. & Gu, X. Evolutionary dynamics of MERS-CoV: Potential recombination, positive selection and transmission. Sci. Rep. 6, 25049. https://doi.org/10.1038/srep25049 (2016).

ADS CAS Article PubMed PubMed Central Google Scholar

Zhang, X. W., Yap, Y. L. & Danchin, A. Testing the hypothesis of a recombinant origin of the SARS-associated coronavirus. Arch. Virol. 150, 120. https://doi.org/10.1007/s00705-004-0413-9 (2005).

CAS Article PubMed Google Scholar

Liu, P. et al. Prevalence and genetic diversity analysis of human coronaviruses among cross-border children. Virol. J. 14, 230. https://doi.org/10.1186/s12985-017-0896-0 (2017).

CAS Article PubMed PubMed Central Google Scholar

Kin, N., Miszczak, F., Lin, W., Gouilh, M. A. & Vabret, A. Genomic analysis of 15 Human coronaviruses OC43 (HCoV-OC43s) circulating in France from 2001 to 2013 reveals a high intra-specific diversity with new recombinant genotypes. Viruses 7, 23582377. https://doi.org/10.3390/v7052358 (2015).

CAS Article PubMed PubMed Central Google Scholar

Lau, S. K. et al. Severe acute respiratory syndrome (SARS) coronavirus ORF8 protein is acquired from SARS-related coronavirus from greater horseshoe bats through recombination. J. Virol. 89, 1053210547. https://doi.org/10.1128/jvi.01048-15 (2015).

CAS Article PubMed PubMed Central Google Scholar

Lau, S. K. et al. Molecular epidemiology of human coronavirus OC43 reveals evolution of different genotypes over time and recent emergence of a novel genotype due to natural recombination. J. Virol. 85, 1132511337. https://doi.org/10.1128/jvi.05512-11 (2011).

CAS Article PubMed PubMed Central Google Scholar

Dominguez, S. R. et al. Genomic analysis of 16 Colorado human NL63 coronaviruses identifies a new genotype, high sequence diversity in the N-terminal domain of the spike gene and evidence of recombination. J. Gen. Virol. 93, 23872398. https://doi.org/10.1099/vir.0.044628-0 (2012).

CAS Article PubMed PubMed Central Google Scholar

Pyrc, K. et al. Mosaic structure of human coronavirus NL63, one thousand years of evolution. J. Mol. Biol. 364, 964973. https://doi.org/10.1016/j.jmb.2006.09.074 (2006).

CAS Article PubMed PubMed Central Google Scholar

Woo, P. C. et al. Comparative analysis of 22 coronavirus HKU1 genomes reveals a novel genotype and evidence of natural recombination in coronavirus HKU1. J. Virol. 80, 71367145. https://doi.org/10.1128/jvi.00509-06 (2006).

CAS Article PubMed PubMed Central Google Scholar

Sabir, J. S. et al. Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia. Science 351, 8184. https://doi.org/10.1126/science.aac8608 (2016).

ADS CAS Article PubMed Google Scholar

Wang, Y. et al. Origin and Possible Genetic Recombination of the Middle East Respiratory Syndrome Coronavirus from the First Imported Case in China: Phylogenetics and Coalescence Analysis. MBio 6, e01280-01215. https://doi.org/10.1128/mBio.01280-15 (2015).

CAS Article Google Scholar

Eden, J. S., Tanaka, M. M., Boni, M. F., Rawlinson, W. D. & White, P. A. Recombination within the pandemic norovirus GII.4 lineage. J. Virol. 87, 62706282. https://doi.org/10.1128/jvi.03464-12 (2013).

CAS Article PubMed PubMed Central Google Scholar

Dearlove, B. et al. A SARS-CoV-2 vaccine candidate would likely match all currently circulating variants. Proc. Natl. Acad. Sci. USA 117, 2365223662. https://doi.org/10.1073/pnas.2008281117 (2020).

Article PubMed PubMed Central Google Scholar

Montoya, V. et al. Deep sequencing increases hepatitis C virus phylogenetic cluster detection compared to Sanger sequencing. Infect. Genet. Evol. 43, 329337. https://doi.org/10.1016/j.meegid.2016.06.015 (2016).

CAS Article PubMed Google Scholar

Prez-Losada, M., Arenas, M., Galn, J. C., Palero, F. & Gonzlez-Candelas, F. Recombination in viruses: Mechanisms, methods of study, and evolutionary consequences. Infect. Genet. Evol. 30, 296307. https://doi.org/10.1016/j.meegid.2014.12.022 (2015).

CAS Article PubMed Google Scholar

Hamre, D. & Procknow, J. J. A new virus isolated from the human respiratory tract. Proc. Soc. Exp. Biol. Med. 121, 190193. https://doi.org/10.3181/00379727-121-30734 (1966).

CAS Article PubMed Google Scholar

https://www.newscientist.com/article/2268379-two-coronavirus-variants-have-merged-heres-what-you-need-to-know/, cited Feb 20 2021.

Eguia, R. T. et al. A human coronavirus evolves antigenically to escape antibody immunity. PLoS Pathog. 17, e1009453. https://doi.org/10.1371/journal.ppat.1009453 (2021).

CAS Article PubMed PubMed Central Google Scholar

McIntosh, K., Becker, W. B. & Chanock, R. M. Growth in suckling-mouse brain of IBV-like viruses from patients with upper respiratory tract disease. Proc. Natl. Acad. Sci. USA 58, 22682273. https://doi.org/10.1073/pnas.58.6.2268 (1967).

ADS CAS Article PubMed PubMed Central Google Scholar

McIntosh, K. et al. Seroepidemiologic studies of coronavirus infection in adults and children. Am. J. Epidemiol. 91, 585592. https://doi.org/10.1093/oxfordjournals.aje.a121171 (1970).

CAS Article PubMed Google Scholar

Kahn, J. S. & McIntosh, K. History and recent advances in coronavirus discovery. Pediatr Infect Dis J 24, S223-227. https://doi.org/10.1097/01.inf.0000188166.17324.60 (2005) (discussion S226).

Article PubMed Google Scholar

Chen, R. & Vasilakis, N. Denguequo tu et quo vadis?. Viruses 3, 15621608. https://doi.org/10.3390/v3091562 (2011).

Article PubMed PubMed Central Google Scholar

https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563. Accessed 31 Dec 2020.

CDC. SARS-CoV-2 Variant Classifications and Definitions. https://www.cdc.gov/coronavirus/2019-ncov/variants/variant-info.html.

Didelot, X., Gardy, J. & Colijn, C. Bayesian inference of infectious disease transmission from whole-genome sequence data. Mol. Biol. Evol. 31, 18691879. https://doi.org/10.1093/molbev/msu121 (2014).

CAS Article PubMed PubMed Central Google Scholar

Pickett, B. E. et al. ViPR: an open bioinformatics database and analysis resource for virology research. Nucleic Acids Res. 40, D593-598. https://doi.org/10.1093/nar/gkr859 (2012).

CAS Article PubMed Google Scholar

Katoh, K. & Standley, D. M. MAFFT: iterative refinement and additional methods. Methods Mol. Biol. 1079, 131146. https://doi.org/10.1007/978-1-62703-646-7_8 (2014).

Article PubMed Google Scholar

Tamura, K., Stecher, G., Peterson, D., Filipski, A. & Kumar, S. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 30, 27252729. https://doi.org/10.1093/molbev/mst197 (2013).

CAS Article PubMed PubMed Central Google Scholar

https://www.gisaid.org/. Accessed 9 Jan 2021.

Capella-Gutirrez, S., Silla-Martnez, J. M. & Gabaldn, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 19721973. https://doi.org/10.1093/bioinformatics/btp348 (2009).

CAS Article PubMed PubMed Central Google Scholar

Martin, D. P., Murrell, B., Golden, M., Khoosal, A. & Muhire, B. RDP4: Detection and analysis of recombination patterns in virus genomes. Virus Evol 1, vev003. https://doi.org/10.1093/ve/vev003 (2015).

Article PubMed PubMed Central Google Scholar

Martin, D. & Rybicki, E. RDP: Detection of recombination amongst aligned sequences. Bioinformatics 16, 562563. https://doi.org/10.1093/bioinformatics/16.6.562 (2000).

CAS Article PubMed Google Scholar

Martin, D. P., Posada, D., Crandall, K. A. & Williamson, C. A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints. AIDS Res. Hum. Retroviruses 21, 98102. https://doi.org/10.1089/aid.2005.21.98 (2005).

CAS Article PubMed Google Scholar

Smith, J. M. Analyzing the mosaic structure of genes. J. Mol. Evol. 34, 126129. https://doi.org/10.1007/bf00182389 (1992).

ADS CAS Article PubMed Google Scholar

Posada, D. & Crandall, K. A. Evaluation of methods for detecting recombination from DNA sequences: computer simulations. Proc. Natl. Acad. Sci. USA 98, 1375713762. https://doi.org/10.1073/pnas.241370698 (2001).

ADS CAS Article PubMed PubMed Central Google Scholar

Lam, H. M., Ratmann, O. & Boni, M. F. Improved algorithmic complexity for the 3SEQ recombination detection algorithm. Mol. Biol. Evol. 35, 247251. https://doi.org/10.1093/molbev/msx263 (2018).

CAS Article PubMed Google Scholar

Padidam, M., Sawyer, S. & Fauquet, C. M. Possible emergence of new geminiviruses by frequent recombination. Virology 265, 218225. https://doi.org/10.1006/viro.1999.0056 (1999).

CAS Article PubMed Google Scholar

Gibbs, M. J., Armstrong, J. S. & Gibbs, A. J. Sister-scanning: a Monte Carlo procedure for assessing signals in recombinant sequences. Bioinformatics 16, 573582. https://doi.org/10.1093/bioinformatics/16.7.573 (2000).

CAS Article PubMed Google Scholar

Weiller, G. F. Phylogenetic profiles: A graphical method for detecting genetic recombinations in homologous sequences. Mol. Biol. Evol. 15, 326335. https://doi.org/10.1093/oxfordjournals.molbev.a025929 (1998).

CAS Article PubMed Google Scholar

Lemey, P., Lott, M., Martin, D. P. & Moulton, V. Identifying recombinants in human and primate immunodeficiency virus sequence alignments using quartet scanning. BMC Bioinformatics 10, 126. https://doi.org/10.1186/1471-2105-10-126 (2009).

CAS Article PubMed PubMed Central Google Scholar

Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. jModelTest 2: More models, new heuristics and parallel computing. Nat. Methods 9, 772. https://doi.org/10.1038/nmeth.2109 (2012).

CAS Article PubMed PubMed Central Google Scholar

Guindon, S. & Gascuel, O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52, 696704. https://doi.org/10.1080/10635150390235520 (2003).

Article PubMed Google Scholar

Rambaut, A., Lam, T. T., MaxCarvalho, L. & Pybus, O. G. Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen). Virus Evol. 2, vew007. https://doi.org/10.1093/ve/vew007 (2016).

Article PubMed PubMed Central Google Scholar

https://apps.who.int/iris/bitstream/handle/10665/326126/WHO-MERS-RA-19.1-eng.pdf. Accessed 31 Dec 2020.

Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 4, vey016. https://doi.org/10.1093/ve/vey016 (2018).

Original post:
A comparative recombination analysis of human coronaviruses and implications for the SARS-CoV-2 pandemic | Scientific Reports - Nature.com

Alexander the Great Cutting The Gordian Knot

This is the first in a series describing the role of the beginning and end of the SARS-CoV-2 genome in the virus life cycle. I summarize what we know and point out what we need to know about these ends in order to develop new antiviral drugs.

Unraveling the details of the life cycle of the SARS-CoV-2 virus is much like reading a mystery novel. The truth is often deeply buried and the journey laden with misleading clues. As every reader knows, the first and last pages are inevitably the most important. The analogy is closer than you may imagine. The bookends of the viral genome are responsible for many of the viruss critical functions, including initiation of replication, protein synthesis, and messenger RNA synthesis. Unraveling the details of exactly how these functions occur requires puzzling out the most intricate mysteries. The first observation is that both the beginning five prime (5) end and terminal three prime (3) end are complex (Figure 1).

ACCESS Health International

ACCESS Health International

FIGURE 1: (A) 5 end of the SARS-CoV-2 genome; (B) 3 end of the SARS-CoV-2 genome; (C) Gordian Knot

RNA is a self-folding polymer. The 30,000-nucleotide long genome self-assembles into elaborate stem-loop structures. The stems are base-paired, G pairs with C and A with U (or T in the case of DNA), while the loops are unpaired (Figure 2).

Markova et al

FIGURE 2: (A) Theoretical stem-loop structure; (B) Schematic representation of a stem-loop.

Alternatively, these structures can fold into pseudoknots, emerging in various forms (Figure 3).

FIGURE 3: Theoretical pseudoknot stem-loop structures

Collectively, these are called secondary structures. The secondary structures of diverse coronaviruses are relatively well conserved, even though the primary genome sequences differ. The similarity of these structures suggests that the structure itself, in addition to the primary nucleotide sequence, plays an essential role in virus replication. Moreover, understanding the details of how the ends of the viral genome interact with viral and cellular proteins is a prerequisite to the discovery of new antiviral drugs.

The recent introduction of a new drug to prevent and treat influenza illustrates exactly how important this research is in finding new drugs to prevent and treat SARS-CoV-2 infection. A study from July 2020 found that the anti-influenza drug baloxavir marboxil (also referred to as Xofluza), reduced close-quarters transmission of Influenza A by 80%.

The influenza virus uses a process called cap snatching to reproduce, effectively snatching host RNA and reusing it in the reproduction process. Xofluza binds to and inhibits the proteins involved in the cap snatching process.

My hope is that these brief descriptions of what we know and dont know about the termini of SARS-CoV-2 will stimulate scientists around the world to develop drugs similar to Xofluza for the virus at hand.

Entry of the viral genome and production of the viral replication complex

Upon fusion of the viral and cellular membrane, the viral genome is deposited into the cytoplasm of the cell. The first requirement of the viral RNA is to avoid triggering the antiviral defenses, collectively called the innate immune response. A primary trigger of the innate immune response is the entry of foreign RNA. The cellular alarm signals recognize naked RNA 5 termini, unmethylated RNA, and RNA that does not carry a polyadenylated (poly-A tail). The SARS-CoV-2 genomic RNA skirts all these alarm signals as it is properly capped and methylated by the virus's own proteins. It also carries a poly-A tail. In other words, it masquerades as a cellular messenger RNA.

Once safely inside the cytoplasm, replication begins. As it enters a cell, the viral genome is organized as a compact package bound to multiple nucleocapsid capsid (N) proteins (Figure 4). The viral genome itself serves as a template for the synthesis of the very first viral proteins located in a long open reading frame that begins at the AUG initiation codon located 266 nucleotides from the 5 prime end of the genome, buried deep within the 5 stem-loop structures.

FIGURE 4: Viral RNA bound to the N protein.

Question: How do the translation machinery, translation initiation, and associated initiation factors recognize the genome RNA complexed with the N protein. Does the N protein disassociate from the RNA on entry spontaneously or is it displaced by cellular proteins and the ribosome during protein synthesis?

Virus protein synthesis begins when the ribosomes bind the 5' end of the genome and initiate synthesis (Figure 5).

FIGURE 5: Messenger RNA being translated by a ribosome.

It is no mean feat for the ribosome to navigate the intricate 5 structure. Ribosomal entry likely requires the assistance of a cellular unwinding enzyme (a helicase) allowing slippage of the ribosome along the RNA until it encounters the AUG initiation codon. Initiation of the Orf1a and Orf1b proteins begins at position 266 with stem-loop 5 (Figure 1).

We note that there is the possibility of initiation at position 107. There is an AUG codon within the reading frame at this position which would proceed to yield a nine-amino acid long peptide before encountering two termination codons

I wonder if initiation at position 107 followed by reinitiation at position 266 is possible. A similar 5 AUG occurs in SARS-CoV. As the structure of the stem-loops is nearly identical and the resulting theoretical peptide in SARS-CoV from the first AUG closely resembles that of SARS-CoV-2, this is not an anomaly confined to SARS-CoV-2 (Figure 6). It would be interesting to learn if this small peptide is functional and we will continue to research this sequence in an effort to elucidate it.

FIGURE 6: SARS-CoV and SARS-CoV-2 5 ends, denoting the initial AUG codon that results in a nine ... [+] amino acid long peptide before the Orf1ab initiating AUG downstream in the sequence. Note the resultant amino acid peptides in both SARS-CoV and SARS-CoV-2.

Question: Why does Orf1a protein start at the second AUG at position 266 and not the first AUG at position 107 (Figure 1). The general rule is that protein synthesis in mammalian cells begins at the initiation codon closest to the 5 end. Is it possible that initiation actually begins at position 107 to yield a nine amino acid-long peptide of unknown function followed by re-initiation at position 266?

The first proteins made are the two products of the Orf1a and Orf1b genes. These long polypeptides are cleaved into 15 proteins, called the non-structural proteins (NSPs1-16: there is no NSP11) that are required for the synthesis of small messenger RNA that direct the synthesis of the proteins of the virus particle S, M. E, and N, as well as the regulatory proteins.

FIGURE 7: Frameshift between Orf1a and Orf1b

The very first viral protein made, NSP1, plays a critical role in virus replication. The protein blocks the production of cellular proteins while permitting the production of viral proteins. NSP1 acts by obstructing the entry of cellular RNAs into the ribosome (Figure 8).

FIGURE 8: Ribosomal translation

Recent studies show that the N protein binds to an RNA sequence of the 40S subunit of the ribosome obstructing the entry tunnel. Preferential synthesis of viral proteins allows much of the cells energy to be devoted to producing viral components.

How then are viral proteins made? The mystery was solved by studies that show any message with stem-loop 1 located near the 5 terminus can be translated in the presence of NSP1. Both the viral genome and all viral messenger RNAs meet this requirement.

A brief description of viral messenger RNA synthesis explains why all viral messages carry the requisite 5 stem-loop. The structure protein S, M, E, and N of the virus particle and regulatory genes Orfs by the 3 end of the genome. The template for their synthesis is a nested set of negative-strand RNAs that all share a 3' and 5' termini (Figure 9).

FIGURE 9: The messenger RNA replication and transcription strategy of SARS-CoV-2. Note the nested ... [+] set of 3 messenger RNAs made by jumping from the 3 to the 5 transcriptional regulatory sequence.

As the negative strand elongates, the growing end encounters whats called termination regulatory sequences (TRS-B). Transcription pauses after copying the TRS sequences (Figure 10) and then resumes by pairing with the complementary TRS-L sequence located near the 5 terminus.

FIGURE 10: 5 End through TRS-L at nucleotide position 75.

The messenger RNAs all begin with the same 5 end that extends from nucleotide 1 through nucleotide 75 and includes stem-loops 1-3, but not stem-loops 4-7.

Question: How does the presence of stem-loop 1 relieve the NSP1 translation block? Does NSP1 bind to stem-loop 1? If so is NSP1 recognition of stem-loop 1 determined by the sequence or structure. Can stem-loop 1 of SARS-CoV-2 relieve the NSP1 block of other coronaviruses? What is the role of cellular translation initiation factors in viral messenger RNA translation?

Question: Why does transcription pause at TRS-B sequences. Does the topology of the replication complex facilitate the post pause jump to the 5 TRS? Can the jump occur only in cis to the same genome or is a trans jump possible to a second replicating genome? Can a jump occur to any TRS sequence or only the one closest to the TRS-L sequence 5 end? Do cellular proteins participate in messenger RNA synthesis?

Full coverage and live updates on the Coronavirus

Go here to read the rest:
Decoding The Gordian Knots At The Ends Of The SARS-CoV-2 Genome - Forbes

click to enlarge

Marijuana research has been federally legal in Israel for decades.

Jacqueline Collins

Colorado had a head start in that race in the United States, but medical marijuana research has been federally legal in Israel for decades, and some seriously interesting stuff about the cannabis genome is being discovered there. To get up to speed, we caught up with Lior Chatow, a lead researcher at Israel-based cannabis research and development facility Eybna.

Westword: What exactly are genomes, and how do they fit in the grand scale of the way cannabis exists and evolves?Lior Chatow: The cannabis plants genome encompasses all of the plants genetic information. The plants phenotype is the expressed genome, and it accounts for the plants characteristics, such as chemical composition and appearance. Due to environmental factors and adaptations, the plants genome may change as part of evolution and natural selection to better survive and adapt to new environments. These adaptive processes led to the creation and diversification of cannabis genomes, producing more strains with varied effects that humans can benefit from.

How does identifying and mapping out genomes help us understand more specific qualities of cannabis? By researching and studying the cannabis genome, we can learn about its expressed phenotype and, more specifically, about its expressed phytochemical makeup. The phytochemicals in cannabis include terpenes, cannabinoids, flavonoids and many more diverse compounds. These compounds are the fundamental building blocks of cannabiss therapeutic benefits. By mapping out their individual characteristics, the industry can engineer products with highly specific applications based on consumer preference and patient need.

Local

Community

Journalism

Support the independent voice of Denver and help keep the future of Westword free.

For example, Eybna is pursuing ethnobotanical research into the cannabis genome, with a particular focus in this case on the known daytime sativa-like effect and nighttime indica-like effect. This work will help identify the specific phytochemicals that create these well-known effects, and help brands further meet the functional needs of consumers across form factors.

How much research into the cannabis genome was conducted before states began legalizing the plant? In Israel, the longstanding history of cannabis research is tied to professor Raphael Mechoulam, one of the pioneers of the field. During the 1960s, Mechoulam began investigating the cannabis plant after learning about the isolation of morphine from opium. Through his collaborative efforts with Dr. Yechiel Gaoni and Dr. Yuval Shvo, Mechoulam was able to isolate many cannabinoids, most notably cannabidiol (CBD) in 1963 and tetrahydrocannabinol (THC), the psychoactive compound found in cannabis, in 1964.

At present, Israel is consistently graded among the top locations for cannabis research, and it actively encourages the industrys growth. As more countries push toward full legalization, Israels scientific approach, combined with a friendly legal framework and ongoing research efforts, have helped position the local industry to blossom. With the governments steadfast approval alongside the rich history of cannabis research within its borders, Israels cannabis sector is busily planting the seeds for tomorrows big developments.

Lior Chatow is a lead researcher at Israel-based Eybna.

Courtesy of Eybna

Eybnas belief is that the phytochemical makeup of a strain should be its main identifier instead of the given strain name. This ensures a data-driven standardization that will help bring consistency back to well-loved strains and open new doors for strain innovation. Eybnas Enhancer Line started at the genome level, tracing three OG strains back to their original breeders and using these samples to identify the genetic characteristics that define Kush," Skunk and Diesel. By mapping and packaging this data-driven standard for three iconic strains, the Enhancer Line allows for the introduction of authentic, desired essences that cannabis products may be lacking today due to the natural divergence from the original genome, as well as post-harvest processes.

Does your research validate or invalidate any claims or beliefs about identifying cannabis, and how certain cultivars and terpenes are tied to certain effects? Eybna's efforts with Seach Medical Group resulted in uncovering a certain terpene pattern that correlates to nighttime strains and daytime strains. The study was conducted on medical cannabis patients in Israel and highlighted the phytochemical difference between these two strains, showing correlations between certain terpenes and effects. Some of these correlations validated certain existing claims, and some contradicted previous findings and claims.

The results provide us with the understanding that there is still much more to uncover when it comes to phytochemicals' effects on the pharmacological value of cannabis products. With the right data, tools and people, Eybna is hard at work cracking these codes and unlocking the world of targeted, data-driven cannabis experiences.

Does the growing scenario or environment impact a cannabis genome?The fact that genetically identical plants can have vastly different phenotypes demonstrates that gene-environment interaction is a key regulator of phenotypic diversity. Environmental factors play an important role in the production of the characteristics in cannabis; however, they do not change the genome.

Genetic adaptation is the change in genome that occurs to fit a new environment, and is the key agent in evolution. For example, the leaf morphological change that occurred to cannabis sativa throughout the years is believed to be due to temperature adaptation from cold to hot climate, and the phytochemical differences may be due to the exposure to new pathogens and diseases in new environments.

Breeders of the worlds most beloved strains got started by experimenting with genetic adaptations. With the Enhancer Line, Eybna is working to help preserve the legacy and authenticity, and embrace the process of evolution and change that naturally continues. We believe that introducing a new genetics-driven approach to cannabis will be crucial to help the industry further expand, innovate and reach new communities worldwide.

See more here:
What Unlocking the Genomes of Marijuana Strains Tells Us - Westword

The Delta variant is a highly contagious SARS-CoV-2 virus strain.

Scientists have sequenced samples from hundreds of confirmed cases in this outbreak, to generate whole genomes that represent the virus' entire genetic make-up. It's made a crucial difference in managing the outbreak in real time, while also confirming a link with Australia's Delta outbreak. What other insights have we gleaned? Dr David Welch and Dr Jordan Douglas of the University of Auckland, Dr James Hadfield, a Wanaka-based phylogeneticist with Seattle's Bedford Lab, Otago University and ESR virologist Dr Jemma Geoghegan, and ESR's Dr Joep de Ligt discuss the results.

Why is genome sequencing an important tool in managing Covid-19 outbreaks?

First, it reassures us that the cases are indeed part of the current outbreak, as opposed to transmission from an unrelated border incursion, such as the Air New Zealand worker from earlier in August.

Second, as diversity appears within the genomes of the outbreak it allows contact tracers to focus on the locations of interest where the genomes match, and rule out those associated with a different sub-cluster.

Sequencing every positive case allows us to define cluster membership when epidemiological links are lacking or murky, which is particularly important during a large outbreak like this one.

The rapid pace at which genomes are generated in New Zealand - usually within less than 24 hours of a case being detected - means that they can assist public health investigations in real time, with sequence data often available at about the same time contact tracing interviews are completed.

From a research point of view, the data we are collecting is invaluable because we have a very complete sampling of genomes and very detailed epidemiological data associated with each case.

Having these sources together allows us to create an accurate transmission tree from which we can understand properties of the virus such as how fast it spreads within households and where super-spreading events have taken place, or how effective alert levels are at slowing the spread.

Finally, sequencing every case in MIQ tells us exactly which variants are coming into the country.

When variants of concern such as Alpha or Delta that need more stringent management are found, the public health response can change accordingly.

What has sequencing taught us in this latest episode?

In this outbreak, we found a genomic link to an MIQ case who tested positive eight days before the first community case was detected.

It is clear that this outbreak is linked to New South Wales as the genomes of the first local cases exactly match recent genomes from there.

Indeed, they exactly match the genome of a case in MIQ who come from New South Wales.

But we must be cautious when interpreting genomic data.

While genomic data can provide clues about the transmission chain, proving transmission is a lot more difficult even with infection from a genetically identical coronavirus there are lots of genomes in New South Wales that are identical to the first case here and there were lots of people on those "red zone" flights.

So, although the genomics strongly supports a connection there are some missing pieces in the transmission puzzle.

Genomic evidence shows that there was, within MIQ, spread from the New South Wales traveller in question to their neighbours, which further bolsters the view that this MIQ case was the source; we just need to find those epidemiological links.

At this point we can't definitively rule out a separate introduction but that is not for lack of trying.

And what can we say about the evolution of this variant, and its path from its point of origin to New Zealand today?

The Delta lineage was first detected in late 2020 and caused an enormous second wave in India in early 2021.

The variant began to rise in frequency across the world replacing many other variants, including Alpha, which was dominant at that time.

Public Health England declared it a "variant of concern" in May 2021 based on its increased transmissibility.

Delta continues to be the most dominant lineage sequenced worldwide and, in many countries, it's pretty much the only lineage found.

There are many millions of Delta chains of transmission globally and a large diversity of genomes within the Delta lineage, including "Delta+" variants that contain mutations associated with other variants of concern.

Looking at the positive MIQ cases we've sequenced in the past two months, all but one was Delta.

As this graph shows, the vast majority of all covid cases around the world are now Delta.

Within this outbreak itself, can we see any level of genomic diversity?

As with any large Covid-19 outbreak, there is a great deal of genomic diversity within the outbreak.

Of the 388 complete genomes we have so far, we can identify about 80 distinct genomes.

There are 56 so-called "single nucleotide variations" which are single letter changes within the genetic code of the 30,000-letter-long genome.

The remainder of the changes are "deletions", where a small number of letters are omitted from the sequence.

These mutations help to define sub-clusters and link cases together.

This information, combined with epidemiological data, can help contact tracers by linking cases to a potential source or even excluding them from a sub-cluster.

Having said this, 221 of the 388 genomes are genetically indistinguishable from each other, which is similar to what we have seen in other outbreaks.

Genomes are also being shared with global platforms. How do these work, and why are they important in managing the wider pandemic?

Researchers around the world, including us, share genomic data - without any personally identifiable information - to databases such as GenBank and GISAID.

This reciprocal sharing helps when trying to understand where a new case may have originated.

Platforms such as Nextstrain analyse global data and present a high-level view into Sars-CoV-2 spread and evolution.

Our understanding of the behaviour of variants such as Delta relies on this kind of global sharing.

How does the genomic profile of this outbreak differ from those of previous ones? Our main wave last year, for instance, carried much more genomic diversity and included 300 introductions from different parts of the world.

The genomic profile of this outbreak is very different to the first wave in 2020.

Not only because it is the Delta variant, but also because the outbreak's genomic diversity is much smaller, due to all cases sharing a single introduction.

This differs from our first wave where there were multiple introductions and genomic diversity that reflected the diversity seen across the world.

We are also testing and sequencing much more so will be picking up the large majority of cases involved in this outbreak.

In the first wave, particularly early on, there were significant gaps in testing so that the extent of the outbreak was not fully understood.

This outbreak, with over 550 cases, is by far the biggest single cluster we have seen in New Zealand.

Before this, the largest outbreak was the 2020 Auckland outbreak - with 179 cases followed by the Bluff Wedding cluster with 98 cases.

Go here to read the rest:
Covid 19 Delta outbreak: What genomes reveal about this outbreak - New Zealand Herald

TMR Research is a leader in developing well-researched reports. The expertise of the researchers at TMR Research makes the report stand out from others. TMR Research reports help the stakeholders and CXOs make impactful decisions through a unique blend of innovation and analytical thinking. The use of innovation and analytical thinking while structuring a report assures complete and ideal information of the current status of the market to the stakeholders.

Also known as genome editing with engineered nucleases (GEEN), genome editing is a method of altering DNA within a cell in a safe manner. The technique is also used for removing, adding, or modifying DNA in the genome. By thus editing the genome, it is possible to change the primary characteristic features of an organism or a cell.

The global genome editing market can be segmented on the basis of delivery method, technology, application, and geography. By technology, the global genome editing market can be segmented into Flp-In, CRISPR, PiggyBac, and ZFN. Based on delivery method, in vivo and ex vivo can be the two broad segments of the global genome editing market. By application, the global genome editing market can be categorized into medicine, academic research, and biotechnology.

Get Brochure of the Report @ https://www.tmrresearch.com/sample/sample?flag=B&rep_id=2588

Global Genome Editing Market: Key Trends

Since genome editing is gaining rising adoption in the domain of scientific research for attaining a better understanding of biological aspects of organisms and how they work, the global genome editing market is likely to promise considerable growth over the forthcoming years. More importantly, genome editing is being used by medical technologies, where it can be used for modifying human blood cells which can then be placed back in the body for treating conditions such as AIDS and leukemia. The technology can also be potentially utilized to combat infections such as MRSA as well as simple genetic disorders including hemophilia and muscular dystrophy.

Global Genome Editing Market: Market Potential

As more easy-to-use and flexible genome technologies are being developed, greater potential of genome editing is being recognized across bioprocessing and treatment modalities. For instance, in May 2017, MilliporeSigma announced that it successfully developed a novel genome editing tool which can make the CRISPR system more productive, specific, and flexible. The researchers thus have a more number of experimental options along with faster results.

All this can lead to a growing rate of drug development, enabling access to more advanced therapies. Proxy-CRISPR, the new technique, makes access to earlier inaccessible aspects of the genome possible. As most of the existing CRISPR systems cannot manage without re-engineering of human cells, the new method is expected to gain more popularity by virtue of the elimination of the need for re-engineering, simplifying the procedures.

Several other market players are focusing on clinical studies with a view to produce effective treatments for different health conditions. For example, another major genome editing firm, Editas Medicine, Inc. announced the results of its pre-clinical study displaying the success of the CEP290 gene present in the retina of primates in the same month. With the positive results of the study, the companys belief in the vast potential of its candidate in the treatment of a genetically inherited retinal degenerative disease, Leber congenital amaurosis type 10, affecting childrens eyesight has been reinforced.

Global Genome Editing Market: Regional Outlook

By geography, the global genome editing market can be segmented into Latin America, Europe, Asia Pacific, the Middle East and Africa, and North America. North America registered the highest growth in the past, and has been claiming the largest portion of the global genome editing market presently. The extraordinary growth of this region can be attributed to greater adoption of cutting edge technologies across several research organizations. The U.S., being the hub of research activities, is expected to emerge as the leading contributor. Asia Pacific is also likely to witness tremendous demand for genome editing over the forthcoming period, assisting the expansion of the global genome editing market.

Global Genome Editing Market: Competitive Analysis

CRISPR THERAPEUTICS, Caribou Biosciences, Inc., Sigma Aldrich Corporation, Sangamo, Intellia Therapeutics, Inc., Editas Medicine, Thermo Fisher Scientific, Inc., and Recombinetics, Inc are some of the key firms operating in the global genome editing market.

Get Table of Content of the Report @ https://www.tmrresearch.com/sample/sample?flag=T&rep_id=2588

The 5-point growth formula includes the following points:

Current and Future Threats

Along with studying the opportunities necessary for growth, threats are also an important aspect to look upon for the companies and stakeholders in a specific sector. TMR Research studies every negative aspect that will hinder the growth of a specific area of business and includes it in the report. The stakeholders and CXOs will have the benefit of assessing the threat and take the necessary steps to prevent the hindrance caused due to the threats.

Accurate Trend Analysis

Keeping up with the latest trends is crucial in any business or sector. While stakeholders are aware of the trends that are on the surface, TMR Researchers find trends that are deeply entrenched in the particular market or sector. The reports are constantly updated with the latest trends so that the stakeholders and CXOs can derive benefits from the trends and generate good revenues.

Regional Assessment

Demography forms an important part of the growth pattern of all the markets. Diving deep into the demographics enables maximum output from specific areas. The TMR Research team assesses every region and picks out the vital points that have a large impact on the growth of a market.

Industrial Analogy

The analysts at TMR Research conduct an all-round analysis on the competitive landscape of the market. The observations recorded by the analysts are added to the reports so that every stakeholder gets a glimpse of the competitive scenario and frame their business plans according to the situation.

COVID-19 Impact

The COVID-19 outbreak has changed the growth projections of numerous sectors and businesses. The analysts at TMR Research have conducted a conscientious survey on the markets after the pandemic struck. The analysts have put forth their brilliant and well-researched opinions in the report. The opinions will help the stakeholders to plan their strategy accordingly.

About TMR Research

TMR Research is a premier provider of customized market research and consulting services to business entities keen on succeeding in todays supercharged economic climate. Armed with an experienced, dedicated, and dynamic team of analysts, we are redefining the way our clients conduct business by providing them with authoritative and trusted research studies in tune with the latest methodologies and market trends.

Contact:

Rohit Bhisey

TMR Research,

3739 Balboa St # 1097,

San Francisco, CA 94121

United States

Tel: +1-415-520-1050

Visit Site: https://www.tmrresearch.com/

Original post:
Genome Editing Market | How has COVID-19 affected the market? - BioSpace

Feasibility of genomic skimming on the ONT minION sequencer

The term genomic skimming was first coined by in 2012 by Straub et al. (2012)20 as a way to utilize shallow sequencing of gDNA to obtain relatively deeper coverage of high-copy portions of the genome, including mitogenomes. In combining genomic skimming with ONT long-read sequencing, we successfully reconstructed a complete marmoset mitogenome without the need for prior PCR enrichment, using standard molecular biology equipment, and a compact portable sequencer that connects to a laptop computer. Preparation of genetic material for ONT sequencing in this study took less than a full day, and sequencing reads were available within 48 hours. Although the coverage of our reconstructed ONT mitogenome was low-medium (9x) and one of the largest sources of error for the ONT reads were missing reads in long homopolymer runs, the ONT data showed a high degree of concordance with gold standard mtDNA Sanger sequencing reads for the same individual. Hence, this work along with a number of previous studies (e.g.,5,21), highlights ONT-based genomic skimming as holding great potential for enhancing mitogenomic and diversity studies of data-deficient and/or non-model organisms.

A major challenge in ONT sequencing is the relatively high sequencing error (5%-15%), but the application of computational polishing significantly reduces errors of raw ONT data (e.g.22). Another challenge with ONT methodologies is the large amount of input DNA needed for sequencing relative to other types of methods, particularly PCR and Sanger sequencing. Multiplexing samples onto the same flow cell is one way to reduce the required amount of per sample DNA, and currently ONT chemistry allows for up to 24 individual gDNA samples to be multiplex per flow cell. Another option to improve mitogenome coverage from genome skimming shotgun data, especially for sensitive applications is to use sample preparation approaches that specifically enrich for mtDNA (e.g., https://www.protocols.io/view/isolation-of-high-quality-highly-enriched-mitochon-mycc7sw).

It is important to point out that our approach represents a starting point from which methodological aspects could be adjusted to further improve and modify our protocol. An important consideration for long-read sequencing is access to high-quality DNA which is not degraded. For marmosets especially, another consideration for input DNA is whether chimerism could bias genomic analysis or not, as levels of chimerism vary between marmoset biological tissues. Marmosets usually give birth to twins that are natural hematopoietic chimeras due to cellular exchange from placental vascular anastomoses during early fetal development23,24,25. This chimerism may result in the presence of up to 4 alleles of a single-copy genomic locus within a single individual. In marmosets, skin shows some of the lowest amounts of chimerism while blood is highly chimeric24,25,26. Depending on project design, high levels of chimerism can bias base calling of nuclear genome derived sequence reads, but this is less of a concern for mitogenomic studies as mtDNA is haploid and transmitted maternally.

In this work, we obtained DNA from a ear skin biopsy, but this represents a minimally invasive source of genetic material. As an epidermal tissue, buccal swabs are a relatively less invasive source of low-chimerism epidermal DNA. Recently, urine has also been shown to be a non-invasive source of high-quality DNA27, but the amount of chimerism is currently not known for marmoset urine. Urine represents a potentially non-invasive genetic tissue which could be combined with genomic skimming of highly endangered non-model organisms, particularly within captive settings.

Our original aim in this work was to reconstruct the mitogenome of the endangered buffy-tufted-ear marmoset with a PCR-free genomic skimming approach with minimal technical requirements. We successfully reconstructed the full mitogenome from a captive individual possessing a C. aurita phenotype, but the mitogenomic lineage showed unexpected discordance with this phenotype. While we expected the mitogenome of the sampled individual to be that of C. aurita, instead the sampled individual possessed a C. penicillata mitogenomic lineage. Our results also represent the first ever known instance of one-way genetic introgression from C. penicillata into C. aurita, and indicate that our sampled marmoset was actually a cryptic C. aurita x C. penicillata hybrid.

Although a number of scenarios could explain the phenotypic-genotypic discordance we uncovered in individual BJT022, this case is likely the result of relatively recent anthropogenic hybridization between a C. penicillata female and C. aurita male. Callithrix species are naturally allo- and parapatric, and natural hybridization occurs between marmoset species under secondary contact8. Past natural genetic introgression between C. aurita and C. penicillata would most likely have occurred in the natural contact zone between these species that exists in the transitional areas between the Cerrado and Atlantic Forest Biomes of southeastern Brazil. Because C. penicillata mitogenomic clades tend to be well defined by their biogeographic origin7, for past, natural introgresssion of C. penicillata into C. aurita, we would expect haplotype BJT022 to have grouped with the C. penicillata Atlantic Forest/Cerrado clade. However, that is not the case, as the BJT022 haplotype grouped instead within the C. penicillata Caatinga Clade. There is a relatively large geographic separation between the Caatinga biome of northeastern Brazil and the portion of the southeastern Brazilian Atlantic Forest that houses the natural region of C. aurita. This wide geographic gap highly reduces the possibility of past natural interbreeding between Caatinga populations of C. penicillata and any C. aurita population.

We could also consider incomplete lineage sorting to explain the phylogenetic position of the BJT022 mitogenomic haplotype as reflecting a C. aurita mitogenome that sorted within a C. penicillata phylogenetic clade instead of a C. aurita clade. Overall, we see strong consistency in grouping patterns of mitogenomic haplotypes within their expected Callithrix phylogenetic clades. Further, C. aurita and the jacchus marmoset subgroup (C. geofforyi, C. kuhlii, C. jacchus, C. penicillata) diverged about 3.54 million years ago7, leaving relatively more time for mitochondrial lineage sorting between C. aurita and the jacchus group than among jacchus group species. While incomplete lineage sorting has indeed been used to explain C. penicillata and C. kuhlii polyphyly7, we still do see clear grouping patterns of C. kuhlii and C. penicillata mitogenomic clades according to their species of origin. Therefore, the strong tendency for Callithrix mitogenomic lineages to group within their expected clades reduces the likelihood of incomplete lineage sorting of mitogenomic lineages between C. aurita and the jacchus group.

The similarity of the case of BJT022 to other likely instances of anthropogenic Callithrix hybridization provide further support for BJT022 representing anthropogenic interbreeding between C. aurita and C. penicillata. Callithrix penicillata and C. jacchus have been introduced into the native range of C. aurita in southeastern Brazil largely as a result of the illegal pet trade and subsequent releases of exotic marmosets into forest fragments7,8. Malukiewicz et al. (2021)7 recently found evidence of genetic introgression from of exotic C. jacchus into C. aurita within the metropolitan area of the city of So Paulo. A cryptic C. aurita hybrid sampled by Malukiewicz et al.7 originates from the municipality of Mogi das Cruzes, which lies in the eastern portion of metropolitan So Paulo8,28. Following zoological records, BJT022 originated from the municipality of So Jose dos Campos, which also lies in the eastern portion of metropolitan So Paulo. These cryptic hybrids also likely represent an advanced stage of anthropogenic hybridization between native C. aurita and exotic jacchus group species. First generation and early generation aurita and jacchus group marmoset hybrids are known to possess a distinct koala bear appearance10,11,29. As this is not the phenotype seen for BJT022 and the cryptic C. aurita hybrids from Malukiewicz et al.7, this observation suggests that these cases of anthropogenic hybridization arose through backcrossing of an earlier non-cryptic C. aurita x Callithrix sp. hybrid with C. aurita. Eventually these backcrosses led to the genomic capture of introgressed jacchus group mitogenome lineages by the C. aurita populations of the eastern portion of the So Paulo metropolitan area.

The above results are alarming since they suggest that genetic introgression is underway from exotic, invasive marmosets to the endangered, native marmosets of southeastern Brazil. At this time, it is not possible to determine how board this pattern is at the geographic, genomic and species levels, and whether introgression is only unidirectional and exactly which exotic and native species are involved. Specifically for C. aurita, unidirectional genetic introgression from invasive marmosets as well as cryptic hybridization is worrying due to the species threatened conservation status. A small number of captive facilities around southeastern Brazil are currently breeding captive C. aurita for eventual reintroductions into the wild8,12. Individuals within these captive populations should be confirmed both genetically and phenotypically as not being of hybrid origin, as to avoid introducing exogenous genetic material into the captive population and subsequently into the wild. Additionally, further genetic information is needed for wild C. aurita populations to not only characterize diversity within the species, but also to better assess the occurrence of hybridization between exotic and native marmosets in southeastern Brazil. This information is critical for defining genetic diversity of C. aurita and maintaining species genetic integrity in the wild and captivity.

The buffy-tufted-ear marmoset is not only critically endangered but also highly data-deficient in terms of genetic information. The limited number of genetic studies involving C. aurita have used the mtDNA control region13,15, COI10, and the mitogenome7 for phylogenetic study of Callithrix mtDNA lineages, species identification, and detection of hybridization. The phylogenies obtained by us and Malukiewicz et al. (2021)7 do show some geographical separation between C. aurita mitogenome haplotypes originating from different portions of the species natural range. Our calculation of Callithrix mtDNA diversity indexes based on data from Malukiewicz et al. (2021)7 show that diversity in C. aurita is still comparable to that of other Callithrix species. However, a large sampling effort of C. aurita in terms of individual numbers and across the species range is needed for accurate determination of current levels of species standing genetic variation. Additionally, surveys should be conducted of the standing genetic variation levels of the captive C. aurita population. These data are crucial for understanding anthropogenic impacts on the species as well for making appropriate decisions for species conservation.

The application of genomic skimming based on portable ONT long-read technology can be applied to address several of these knowledge gaps for C. aurita. First, with large-scale sampling of wild and captive C. aurita, genetic diversity estimates, demographic history, and other evolutionary analyses can be calculated relatively easily from mitogenomic data. Given the relatively fast turnaround time to obtain sequencing data from the minION, such data could be quickly obtained for a primate as highly endangered as C. aurita, without weeks or months long wait times for sequencing data. Laboratory setup of the minION also does not require any additional special equipment, which also makes genomic work with highly endangered species as C. aurita accessible for investigators under relatively constrained budgets.

Callithrix auritas sister species Callithrix flaviceps faces a similar plight as C. aurita, but with an adult population estimated to be at about 2000 adult individuals30. Currently there are also plans to breed C. flaviceps in captivity for eventual wild reintroduction, but currently there is, to our knowledge, no genetic data available for this species. Thus, the same sort of sampling and research efforts are needed for C. flaviceps as for C. aurita, perhaps even more urgently for the former species given its smaller population. As such, C. flaviceps is a good candidate case for the adaptation of techniques such as genomic skimming and low-cost desktop sequencing to rapidly increase genomic resources for a non-model species for conservation and evolutionary studies.

In the case of marmosets, while mitogenomics shows great potential for usage in evolutionary and conservation studies, we strongly urge against sole use of mtDNA markers for identification of species and hybrids. As the results of this study, as well as that of Malukiewicz et al. (2021)7 clearly show, cryptic hybrids can easily be mistaken for species, and had we only depended on mtDNA results we would have misidentified three cryptic Callithrix hybrids as C. jacchus and C. penicillata. Instances of cryptic hybrids have also been shown among natural C. jacchus x C. penicillata hybrids25. All of these instances underline the need to use several lines of evidence for taxanomic identification of marmoset individuals, particularly due to widespread anthropogenic hybridization among marmosets. We used a combination of phenotypic and mitochondrial data to classify the sampled individual BJT022 as a cryptic hybrid. As mitochondrial DNA is maternally transmitted, it is also not possible to genetically identify the paternal lineage of hybrids without further use of autosomal or Y-chromosome genetic markers. When ever phenotypic data are available, these data should be used jointly with molecular data for identification or classification of a marmoset individual as belonging to a specific species or hybrid type. Indeed, the integrated use of phenotypic and molecular approaches will lead to a better understand the phenomena that involve hybridization processes31.

Brazilian legal instruments that protect C. aurita consider hybridization a major threat to the survival of this species8,12. In this report, we have uncovered the first known case of cryptic hybridization between C. aurita and C. penicillata, which may represent a larger trend of genetic introgression from exotic into native marmosets in southeastern Brazil. Our findings are based on the combination of two recent innovations in the field of genomics, that of genomic skimming and portable long-read sequencing on the ONT minION. Given that C. aurita is still very deficient for genetic data, our approach provides a substantial advance in making more genomic data available for one of the worlds most endangered primates. Genomic skimming based on ONT sequencing can be integrated easily with phenotypic and other genetic data to quickly make new information accessible on species biodiversity and hybridization. Such data can then be utilized within the legal Brazilian framework to protect endangered species like C. aurita. More specifically, rapid access to emerging biological information on such species leads to more informed decisions on updating or modifying legal actions for protecting endangered fauna. The ONT genomic skimming approach we present here can be further utilized and optimized to more rapidly generate genomic information without the need for specialized technological infrastructure nor the need for a priori genomic information.

See original here:
Genomic skimming and nanopore sequencing uncover cryptic hybridization in one of world's most threatened primates | Scientific Reports - Nature.com

This article was originally published here

PLoS One. 2021 Aug 31;16(8):e0256451. doi: 10.1371/journal.pone.0256451. eCollection 2021.

ABSTRACT

BACKGROUND: We investigated the genome diversity of SARS-CoV-2 associated with the early COVID-19 period to investigate evolution of the virus in Pakistan.

MATERIALS AND METHODS: We studied ninety SARS-CoV-2 strains isolated between March and October 2020. Whole genome sequences from our laboratory and available genomes were used to investigate phylogeny, genetic variantion and mutation rates of SARS-CoV-2 strains in Pakistan. Site specific entropy analysis compared mutation rates between strains isolated before and after June 2020.

RESULTS: In March, strains belonging to L, S, V and GH clades were observed but by October, only L and GH strains were present. The highest diversity of clades was present in Sindh and Islamabad Capital Territory and the least in Punjab province. Initial introductions of SARS-CoV-2 GH (B.1.255, B.1) and S (A) clades were associated with overseas travelers. Additionally, GH (B.1.255, B.1, B.1.160, B.1.36), L (B, B.6, B.4), V (B.4) and S (A) clades were transmitted locally. SARS-CoV-2 genomes clustered with global strains except for ten which matched Pakistani isolates. RNA substitution rates were estimated at 5.86 x10-4. The most frequent mutations were 5 UTR 241C > T, Spike glycoprotein D614G, RNA dependent RNA polymerase (RdRp) P4715L and Orf3a Q57H. Strains up until June 2020 exhibited an overall higher mean and site-specific entropy as compared with sequences after June. Relative entropy was higher across GH as compared with GR and L clades. More sites were under selection pressure in GH strains but this was not significant for any particular site.

CONCLUSIONS: The higher entropy and diversity observed in early pandemic as compared with later strains suggests increasing stability of the genomes in subsequent COVID-19 waves. This would likely lead to the selection of site-specific changes that are advantageous to the virus, as has been currently observed through the pandemic.

PMID:34464419 | DOI:10.1371/journal.pone.0256451

Excerpt from:
Higher entropy observed in SARS-CoV-2 genomes from the first COVID-19 wave in Pakistan - DocWire News

As the coronavirus evolves, health authorities across the globe rely on the work of scientists at Childrens Hospital Los Angeles, who use genomic sequencing to track mutations.

LOS ANGELES, August 31, 2021--(BUSINESS WIRE)--The COVID-19 pandemic has introduced many new words into our everyday lives. Beyond N-95 and quarantine, new terms like Delta variant are now commonplace. But what is a variant? How are variants identified? And why is it important to track them?

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20210831005726/en/

Xiaowu Gai, PhD, Jennifer Dien Bard, PhD, and their colleagues at Children's Hospital Los Angeles are using genomic sequencing to track SARS-CoV-2 mutations and COVID-19 variants. (Photo: Business Wire)

Scientists at Childrens Hospital Los Angeles have been paying close attention to the behavior of SARS-CoV-2, since the beginning of the pandemic. This means reading out the genetic sequence of the virus from every COVID-19-positive sample to identify mutations. But this also means alerting authorities to notable changes in the virus. Recently, in fact, their research has uncovered mutations recognized by the global scientific community, mutations that may explain why certain versions of the viruslike the Delta variantare so much more contagious.

"Genomic surveillance is critical," says Xiaowu Gai, PhD, Director of Bioinformatics in the Center for Personalized Medicine at Childrens Hospital Los Angeles. "This is the only tool we have to identify mutations. We can track these mutations to help guide public health measures." This tracking has been critical throughout the pandemic.

"Sequencing the genome of SARS-CoV-2 allowed for development of the vaccine," adds Dr. Gai. "Now it remains just as important given the evolving virus and all its variants."

What is a variant?

When a virus infects someone, it replicates, making many copies of itself. Inevitably, mistakes called mutations are made in that process. Sometimes, these mutations make it easier for the virus to be spread or infect cells. When this happens, the new version of the virusor variantwill become more common in the population. The more a virus spreads from person to person, the more chances it has to mutate and for new variants to develop.

Story continues

SARS-CoV-2 has infected more than 200 million individuals worldwide, giving it ample chance to mutate. According to experts, SARS-CoV-2, the virus that causes COVID-19, mutates every couple of weeks. At Childrens Hospital Los Angeles, scientists in the Department of Pathology & Laboratory Medicine and the Center for Personalized Medicine have been tracking these mutations since the beginning of the pandemic in order to identify variants and anticipate the emergence of "variants of concern," which can potentially be more contagious or cause more severe disease.

A virus family tree

Over time, a variant will develop new mutations of its own, leading to multiple sub-lineages, much like a family tree. But not all mutations are cause for concern. In fact, many of them are inconsequential, much like how dropping one letter from a word still leaves a sentence that can be read. In some cases, mutations may even cause the virus to become weaker and die off. But in otherssuch as the current Delta variantthese changes can help a virus spread.

The Centers for Disease Control and Prevention (CDC) reports that the Delta variant is twice as contagious as previous strains. This means that people exposed to the Delta variant are more likely to be infected, and that over time the Delta variant out-competes other variants to become dominant. Today more than 90% of new COVID-19 cases are caused by the Delta variant.

Our understanding and awareness of variants depends on scientists tracking the mutations using a technology called sequencing. With specialized high-throughput machines, scientists can read the entire genetic sequence, sometimes called the genome, of SARS-CoV-2. Then, samples can be compared to determine where mutations have arisen. This allows public health officials to be aware of the presence of different variants and the emergence of new more contagious strains of SARS-CoV-2.

Tracking the virus

At Childrens Hospital Los Angeles, geneticist Dr. Gai and his colleagues have sequenced every COVID-19-positive sample they have received since the beginning of the pandemic, over 3,000 samples to date. In addition to sequencing, Dr. Gais bioinformatics team analyzes the results for viral mutations. This allows them to identify existing and emerging variants to support CHLAs contact tracing and genomic epidemiology efforts to track transmission patterns. The team then shares findings with databases used to by investigators studying COVID-19 around the world.

Sharing information across the globe

Working with Jennifer Dien Bard, PhD, and colleagues in the Department of Pathology & Laboratory Medicine, Dr. Gai and his team have helped CHLA publish the result of multiple SARS-CoV-2 studies, including the largest pediatric COVID-19 study of its time last year, which identified a potential link between certain mutations and severity of disease in children. Another publication demonstrated the effectiveness of public safety measures in limiting the spread of specific strains of the virus.

As the pandemic reaches the year and a half mark, Dr. Gais team is not slowing down. In fact, their recent work has been recognized internationally.

Recently, investigators in the Center for Personalized Medicine analyzed more than 1.3 million SARS-CoV-2 genome sequences from global databases to trace the lineage of the Alpha variant, which emerged in the U.K. in September 2020. The Alpha variant rapidly became dominant, accounting for over 90% of cases in Europe and nearly 60% of COVID-19 cases in the United States, until the emergence of the Delta variant.

The teams most recent work reveals mutations in genes that affect the viruss ability to bind to and infect human cells. One study identified a sub-lineage of the Alpha variant that became officially recognized and named "Q.3." in the internationally recognized SARS-CoV-2 classification system Pangolin. The study was also included in the CDCs COVID-19 Genomics and Precision Public Health Weekly Update and cited by the Global Virus Network, an international resource portal for tracking SARS-CoV-2 mutations.

One of the mutations they reported in the paper (called "M:I82T") is now a recognized feature in the well-known Delta variant. "This mutation affects a protein that sits on the surface of the virus," says Lishuang Shen, PhD, Senior Bioinformatics Scientist at Childrens Hospital Los Angeles and the first author of the publication. "This mutation may indeed be the reason the Delta variant is so much more infectious andin some casesmore deadly."

A second study identified the emergence of a mutation that increased in frequency by more than a factor of 10 in the United States in just two months (February through April of 2021). The team is carefully tracking the mutation for any signs that it may contribute to an emerging variant of concern.

"We need to know what is happening with this virus in as much detail as possible," says Dr. Gai. "Sequencing COVID-19 positive samples allows us to do this." Keeping tabs on the behavior of the virus will alert public health officials to things like how well the vaccine works against new variants.

At the beginning of the pandemic, Dr. Gai and his colleagues in the Department of Pathology & Laboratory Medicine and Center for Personalized Medicine began working around the clock to keep up with testing and sequencing. Almost a year and a half into the pandemic, the team continues to remain vigilant. "The pandemic is not going away," says Dr. Gai, "so neither are we."

The team conducting this work in the Department of Pathology & Laboratory Medicine and the Center for Personalized Medicine includes: Lishuang Shen, first author on both new publications; Jennifer Dien Bard, PhD, the Director of the Clinical Microbiology and Virology Laboratories; Maurice OGorman, PhD, Chief of Laboratory Medicine, Jaclyn Biegel, PhD, Chief of Genomic Medicine and Director of the Center for Personalized Medicine, Timothy Triche, MD, PhD, Co-Director of the Center for Personalized Medicine; Alexander Judkins, MD, Pathologist in Chief and Executive Director of the Center for Personalized Medicine.

View source version on businesswire.com: https://www.businesswire.com/news/home/20210831005726/en/

Contacts

Melinda SmithResearch Communications Specialistmsmith@chla.usc.edu

Here is the original post:
A Pediatric Research Institution is Setting the Pace for Monitoring SARS-CoV-2 Mutations and COVID-19 Variants - Yahoo Finance