Health
The Human Pangenome Project: a global resource to map genomic diversity
International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).
Venter, J. C. et al. The sequence of the human genome. Science 291, 1304–1351 (2001).
Gibbs, R. A. The Human Genome Project changed everything. Nat. Rev. Genet. 21, 575–576 (2020).
Venter, J. C. et al. The sequence of the human genome. Science 291, 1304–1351 (2001).
Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).
Sherman, R. M. & Salzberg, S. L. Pan-genomics in the human genome era. Nat. Rev. Genet. 21, 243–254 (2020).
Rhie, A. et al. Towards complete and error-free genome assemblies of all vertebrate species. Nature 592, 737–746 (2021).
Need, A. C. & Goldstein, D. B. Next generation disparities in human genomics: concerns and remedies. Trends Genet. 25, 489–494 (2009).
Schneider, V. A. et al. Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly. Genome Res. 27, 849–864 (2017).
Bustamante, C. D., Burchard, E. G. & De la Vega, F. M. Genomics for the world. Nature 475, 163–165 (2011). Emphasizes the importance of reference data from ancestral and diverse genomes, as well as stating that researchers should invest time and money into education and outreach to explain why studying global (and local) health is so important.
Miga, K. H. & Wang, T. The need for a human pangenome reference sequence. Annu. Rev. Genomics Hum. Genet. 22, 81–102 (2021).
International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature 431, 931–945 (2004).
Garrison, E. et al. Variation graph toolkit improves read mapping by representing genetic variation in the reference. Nat. Biotechnol. 36, 875–879 (2018). A model for presenting genomes that aims to improve read mapping by representing genetic variation in the reference.
Martiniano, R., Garrison, E., Jones, E. R., Manica, A. & Durbin, R. Removing reference bias and improving indel calling in ancient DNA data analysis by mapping to a sequence variation graph. Genome Biol. 21, 250 (2020).
Alkan, C., Coe, B. P. & Eichler, E. E. Genome structural variation discovery and genotyping. Nat. Rev. Genet. 12, 363–376 (2011).
Sedlazeck, F. J. et al. Accurate detection of complex structural variations using single-molecule sequencing. Nat. Methods 15, 461–468 (2018).
Sudmant, P. H. et al. An integrated map of structural variation in 2,504 human genomes. Nature 526, 75–81 (2015).
Chaisson, M. J. P. et al. Multi-platform discovery of haplotype-resolved structural variation in human genomes. Nat. Commun. 10, 1784 (2019).
Li, R. et al. Building the sequence map of the human pan-genome. Nat. Biotechnol. 28, 57–63 (2010).
Miga, K. H. et al. Telomere-to-telomere assembly of a complete human X chromosome. Nature 585, 79–84 (2020). The sequence of the first complete human chromosome.
Logsdon, G. A. et al. The structure, function and evolution of a complete human chromosome 8. Nature 593, 101–107 (2021).
Nurk, S. et al. The complete sequence of a human genome. Preprint at bioRxiv https://doi.org/10.1101/2021.05.26.445798 (2021). The first complete genome assembly issued from the T2T Consortium, which closed all remaining gaps in the GRCh38, including all acrocentric short arms, segmental duplications and human centromeric regions.
Sirugo, G., Williams, S. M. & Tishkoff, S. A. The missing diversity in human genetic studies. Cell 177, 26–31 (2019).
Tettelin, H. et al. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome”. Proc. Natl Acad. Sci. USA 102, 13950–13955 (2005).
Vernikos, G., Medini, D., Riley, D. R. & Tettelin, H. Ten years of pan-genome analyses. Curr. Opin. Microbiol. 23, 148–154 (2015).
Computational Pan-Genomics Consortium. Computational pan-genomics: status, promises and challenges. Brief Bioinform. 19, 118–135 (2018).
Eizenga, J. M. et al. Pangenome graphs. Annu. Rev. Genomics Hum. Genet. 21, 139–162 (2020).
Rehm, H. L. et al. ClinGen—the clinical genome resource. N. Engl. J. Med. 372, 2235–2242 (2015).
Genomes Project Consortium. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Popejoy, A. B. et al. The clinical imperative for inclusivity: race, ethnicity, and ancestry (REA) in genomics. Hum. Mutat. 39, 1713–1720 (2018).
Popejoy, A. B. et al. Clinical genetics lacks standard definitions and protocols for the collection and use of diversity measures. Am. J. Hum. Genet. 107, 72–82 (2020).
Bonham, V. L. et al. Physicians’ attitudes toward race, genetics, and clinical medicine. Genet. Med. 11, 279–286 (2009).
Race, Ethnicity & Genetics Working Group. The use of racial, ethnic, and ancestral categories in human genetics research. Am. J. Hum. Genet. 77, 519–532 (2005).
Dodson, M. & Williamson, R. Indigenous peoples and the morality of the Human Genome Diversity Project. J. Med. Ethics 25, 204–208 (1999).
Couzin-Frankel, J. Ethics. DNA returned to tribe, raising questions about consent. Science 328, 558 (2010).
Dukepoo, F. C. The trouble with the Human Genome Diversity Project. Mol. Med. Today 4, 242–243 (1998).
Fox, K. The illusion of inclusion—the “All of Us” research program and Indigenous peoples’ DNA. N. Engl. J. Med. 383, 411–413 (2020).
Devaney, S. A., Malerba, L. & Manson, S. M. The “All of Us” program and Indigenous peoples. N. Engl. J. Med. 383, 1892 (2020).
Hudson, M. et al. Rights, interests and expectations: Indigenous perspectives on unrestricted access to genomic data. Nat. Rev. Genet. 21, 377–384 (2020).
Carroll, S. R., Herczog, E., Hudson, M., Russell, K. & Stall, S. Operationalizing the CARE and FAIR principles for Indigenous data futures. Sci. Data 8, 108 (2021).
Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
Genome in a Bottle. NIST https://www.nist.gov/programs-projects/genome-bottle (updated 16 February 2022).
Jarvis, E. D. et al. Automated assembly of high-quality diploid human reference genomes. Preprint at bioRxiv https://doi.org/10.1101/2022.03.06.483034 (2021).
Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with HiFiasm. Nat. Methods 18, 170–175 (2021). HiFiasm is a haplotype-resolved assembler specifically designed for PacBio HiFi reads that aims to represent haplotype information in a phased assembly graph.
Nurk, S. et al. HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. Genome Res. 30, 1291–1305 (2020).
Schatz, M. C. et al. Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space. Cell Genom. 2, 100085 (2022). The AnVIL platform provides scalable solutions for genomic data access, analysis and education.
Li, H., Feng, X. & Chu, C. The design and construction of reference pangenome graphs with Minigraph. Genome Biol. 21, 265 (2020). The Minigraph toolkit has been used to efficiently construct a pangenome graph, which is useful for mapping and constructing graphs that encode structural variation.
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
Rosen, Y., Eizenga, J. & Paten, B. Modelling haplotypes with respect to reference cohort variation graphs. Bioinformatics 33, i118–i123 (2017).
Ebert, P. et al. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science 372, eabf7117 (2021). The use of long-read data from 64 human genomes to predict structural variants and the patterns of variation across diverse populations.
Abel, H. J. et al. Mapping and characterization of structural variation in 17,795 human genomes. Nature 583, 83–89 (2020).
Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
Paten, B. et al. Cactus: algorithms for genome multiple sequence alignment. Genome Res. 21, 1512–1528 (2011). Cactus is a highly accurate, reference-free multiple genome alignment program that is useful for studying general rearrangement and copy number variation.
Pangenome Graph Builder. GitHub https://github.com/pangenome/pggb (2022).
O’Leary, N. A. et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 44, D733–D745 (2016).
Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).
Spooner, W. et al. Haplosaurus computes protein haplotypes for use in precision drug design. Nat. Commun. 9, 4128 (2018).
Arita, M., Karsch-Mizrachi, I. & Cochrane, G. The international nucleotide sequence database collaboration. Nucleic Acids Res. 49, D121–D124 (2021).
Clarke, L. et al. The 1000 Genomes Project: data management and community access. Nat. Methods 9, 459–462 (2012).
Clarke, L. et al. The International Genome Sample Resource (IGSR): a worldwide collection of genome variation incorporating the 1000 Genomes Project data. Nucleic Acids Res. 45, D854–D859 (2017).
Courtot, M. et al. BioSamples database: an updated sample metadata hub. Nucleic Acids Res. 47, D1172–D1178 (2019).
Vollger, M. R. et al. Segmental duplications and their variation in a complete human genome. Preprint at bioRxiv https://doi.org/10.1101/2021.05.26.445678 (2021).
Aganezov, S. et al. A complete reference genome improves analysis of human genetic variation. Preprint at bioRxiv https://doi.org/10.1101/2021.07.12.452063 (2021). The importance of complete T2T genomes in novel variant discovery and of offering major improvements of variant calls within clinically relevant genes are highlighted.
Miller, D. E. et al. Targeted long-read sequencing identifies missing disease-causing variation. Am. J. Hum. Genet. 108, 1436–1449 (2021).
Logsdon, G. A., Vollger, M. R. & Eichler, E. E. Long-read human genome sequencing and its applications. Nat. Rev. Genet. 21, 597–614 (2020).
Kim, D. et al. The architecture of SARS-CoV-2 transcriptome. Cell 181, 914–921.e90 (2020).
Zhou, P. et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579, 270–273 (2020).
Toh, C. & Brody, J. P. Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation. Hum. Genomics 14, 36 (2020).
Zeberg, H. & Paabo, S. The major genetic risk factor for severe COVID-19 is inherited from Neanderthals. Nature 587, 610–612 (2020).
Okubo, K., Sugawara, H., Gojobori, T. & Tateno, Y. DDBJ in preparation for overview of research activities behind data submissions. Nucleic Acids Res. 34, D6–D9 (2006).
Kent, W. J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).
Navarro Gonzalez, J. et al. The UCSC Genome Browser database: 2021 update. Nucleic Acids Res. 49, D1046–D1057 (2021).
Stalker, J. et al. The Ensembl web site: mechanics of a genome browser. Genome Res. 14, 951–955 (2004).
Howe, K. L. et al. Ensembl 2021. Nucleic Acids Res. 49, D884–D891 (2021).
Zhou, X. et al. The Human Epigenome Browser at Washington University. Nat. Methods 8, 989–990 (2011).
Li, D., Hsu, S., Purushotham, D., Sears, R. L. & Wang, T. WashU Epigenome Browser update 2019. Nucleic Acids Res. 47, W158–W165 (2019).
Popejoy, A. B. & Fullerton, S. M. Genomics is failing on diversity. Nature 538, 161–164 (2016). Analysis of sample descriptions included in the genome-wide association study catalogue indicates that some populations are still under-represented and left behind in studies of genomic medicine.
Mills, M. C. & Rahal, C. A scientometric review of genome-wide association studies. Commun. Biol. 2, 9 (2019).
Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).
Ulahannan, N. et al. Nanopore sequencing of DNA concatemers reveals higher-order features of chromatin structure. Preprint at bioRxiv https://doi.org/10.1101/833590 (2019).
Liu, B., Guo, H., Brudno, M. & Wang, Y. deBGA: read alignment with de Bruijn graph-based seed and extension. Bioinformatics 32, 3224–3232 (2016).
Limasset, A., Cazaux, B., Rivals, E. & Peterlongo, P. Read mapping on de Bruijn graphs. BMC Bioinformatics. 17, 237 (2016).
Heydari, M., Miclotte, G., Van de Peer, Y. & Fostier, J. BrownieAligner: accurate alignment of Illumina sequencing data to de Bruijn graphs. BMC Bioinformatics 19, 311 (2018).
1001 Genomes. GenomeMapper. 1001 Genomes https://www.1001genomes.org/software/genomemapper_graph.html (accessed 2021).
Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).
Hickey, G. et al. Genotyping structural variants in pangenome graphs using the vg toolkit. Genome Biol. 21, 35 (2020).
Rautiainen, M. & Marschall, T. GraphAligner: rapid and versatile sequence-to-graph alignment. Genome Biol. 21, 253 (2020).
Jain, C., Misra, S., Zhang, H., Dilthey, A. & Aluru, S. Accelerating sequence alignment to graphs. IEEE Int. Parallel and Distributed Processing Symp. (IPDPS) 451–461 (2019).
Dvorkina, T., Antipov, D., Korobeynikov, A. & Nurk, S. SPAligner: alignment of long diverged molecular sequences to assembly graphs. BMC Bioinformatics 21, 306 (2020).
Mokveld, T., Linthorst, J., Al-Ars, Z., Holstege, H. & Reinders, M. CHOP: haplotype-aware path indexing in population graphs. Genome Biol. 21, 65 (2020).
Ghaffaari, A. & Marschall, T. Fully-sensitive seed finding in sequence graphs using a hybrid index. Bioinformatics 35, i81–i89 (2019).
Wick, R. R., Schultz, M. B., Zobel, J. & Holt, K. E. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 31, 3350–3352 (2015).
Gonnella, G., Niehus, N. & Kurtz, S. GfaViz: flexible and interactive visualization of GFA sequence graphs. Bioinformatics 35, 2853–2855 (2019).
Kunyavskaya, O. & Prjibelski, A. D. SGTK: a toolkit for visualization and assessment of scaffold graphs. Bioinformatics 35, 2303–2305 (2019).
Mikheenko, A. & Kolmogorov, M. Assembly Graph Browser: interactive visualization of assembly graphs. Bioinformatics 35, 3476–3478 (2019).
Beyer, W. et al. Sequence tube maps: making graph genomes intuitive to commuters. Bioinformatics 35, 5318–5320 (2019).
Yokoyama, T. T., Sakamoto, Y., Seki, M., Suzuki, Y. & Kasahara, M. MoMI-G: modular multi-scale integrated genome graph browser. BMC Bioinformatics 20, 548 (2019).
ODGI. GitHub https://github.com/pangenome/odgi (2021).
Shlemov, A. & Korobeynikov, A. in Algorithms for Computational Biology (eds Holmes, I., Martín-Vide, C. & Vega-Rodríguez, M. A.) 80–94 (Springer, 2019).
Ebler, J. et al. Pangenome-based genome inference. Preprint at bioRxiv https://doi.org/10.1101/2020.11.11.378133 (2020).
Leggett, R. M. et al. Identifying and classifying trait linked polymorphisms in non-reference species by walking coloured de Bruijn graphs. PLoS ONE 8, e60058 (2013).
Sibbesen, J. A. et al. Accurate genotyping across variant classes and lengths using variant graphs. Nat. Genet. 50, 1054–1059 (2018).
Chen, S. et al. Paragraph: a graph-based structural variant genotyper for short-read sequence data. Genome Biol. 20, 291 (2019).
Eggertsson, H. P. et al. GraphTyper2 enables population-scale genotyping of structural variation using pangenome graphs. Nat. Commun. 10, 5402 (2019).
|
Sources 2/ https://www.nature.com/articles/s41586-022-04601-8 The mention sources can contact us to remove/changing this article |
What Are The Main Benefits Of Comparing Car Insurance Quotes Online
LOS ANGELES, CA / ACCESSWIRE / June 24, 2020, / Compare-autoinsurance.Org has launched a new blog post that presents the main benefits of comparing multiple car insurance quotes. For more info and free online quotes, please visit https://compare-autoinsurance.Org/the-advantages-of-comparing-prices-with-car-insurance-quotes-online/ The modern society has numerous technological advantages. One important advantage is the speed at which information is sent and received. With the help of the internet, the shopping habits of many persons have drastically changed. The car insurance industry hasn't remained untouched by these changes. On the internet, drivers can compare insurance prices and find out which sellers have the best offers. View photos The advantages of comparing online car insurance quotes are the following: Online quotes can be obtained from anywhere and at any time. Unlike physical insurance agencies, websites don't have a specific schedule and they are available at any time. Drivers that have busy working schedules, can compare quotes from anywhere and at any time, even at midnight. Multiple choices. Almost all insurance providers, no matter if they are well-known brands or just local insurers, have an online presence. Online quotes will allow policyholders the chance to discover multiple insurance companies and check their prices. Drivers are no longer required to get quotes from just a few known insurance companies. Also, local and regional insurers can provide lower insurance rates for the same services. Accurate insurance estimates. Online quotes can only be accurate if the customers provide accurate and real info about their car models and driving history. Lying about past driving incidents can make the price estimates to be lower, but when dealing with an insurance company lying to them is useless. Usually, insurance companies will do research about a potential customer before granting him coverage. Online quotes can be sorted easily. Although drivers are recommended to not choose a policy just based on its price, drivers can easily sort quotes by insurance price. Using brokerage websites will allow drivers to get quotes from multiple insurers, thus making the comparison faster and easier. For additional info, money-saving tips, and free car insurance quotes, visit https://compare-autoinsurance.Org/ Compare-autoinsurance.Org is an online provider of life, home, health, and auto insurance quotes. This website is unique because it does not simply stick to one kind of insurance provider, but brings the clients the best deals from many different online insurance carriers. In this way, clients have access to offers from multiple carriers all in one place: this website. On this site, customers have access to quotes for insurance plans from various agencies, such as local or nationwide agencies, brand names insurance companies, etc. "Online quotes can easily help drivers obtain better car insurance deals. All they have to do is to complete an online form with accurate and real info, then compare prices", said Russell Rabichev, Marketing Director of Internet Marketing Company. CONTACT: Company Name: Internet Marketing CompanyPerson for contact Name: Gurgu CPhone Number: (818) 359-3898Email: [email protected]: https://compare-autoinsurance.Org/ SOURCE: Compare-autoinsurance.Org View source version on accesswire.Com:https://www.Accesswire.Com/595055/What-Are-The-Main-Benefits-Of-Comparing-Car-Insurance-Quotes-Online View photos
to request, modification Contact us at Here or [email protected]
 |
 |
 |
