Page 146 of 148 FirstFirst ... 4696136144145146147148 LastLast
Results 1,451 to 1,460 of 1477

Thread: New DNA Papers

  1. #1451
    Registered Users
    Posts
    64
    Sex

    Haplotype-resolved diverse human genomes and integrated analysis of structural variation
    Peter Ebert et al
    Science 25 Feb 2021: eabf7117
    https://science.sciencemag.org/conte...e.abf7117.full

    Abstract
    Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent–child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average contig N50: 26 Mbp) integrate all forms of genetic variation even across complex loci. We identify 107,590 structural variants (SVs), of which 68% are not discovered by short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterize 130 of the most active mobile element source elements and find that 63% of all SVs arise by homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1,526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

    Quotes from the article:

    "The Human Genome Structural Variation Consortium (HGSVC) recently developed a method for phased genome assembly that combines long-read PacBio whole-genome sequencing (WGS) and Strand-seq data to produce fully phased diploid genome assemblies without dependency on parent–child trio data (Fig. 1A) (3). These phased assemblies enable a more complete sequence-resolved representation of variation in human genomes."

    "Here, we present a resource consisting of phased genome assemblies, corresponding to 70 haplotypes (64 unrelated and 6 children) from a diverse panel of human genomes. We focus specifically on the discovery of novel SVs performing extensive orthogonal validation using supporting technologies with the goal of comprehensively understanding SV complexity, including in regions that cannot yet be resolved by long-read sequencing (fig. S1). Further, we genotype these newly defined SVs using a pangenome graph framework (12–14) into a diversity panel of human genomes now deeply sequenced (>30-fold) with short-read data from the 1000 Genomes Project (1000GP) (15, 16). These findings allow us to establish their population frequency, identify ancestral haplotypes, and discover new associations with respect to gene expression, splicing, and candidate disease loci. The work provides fundamental new insights into the structure, variation, and mutation of the human genome providing a framework for more systematic analyses of thousands of human genomes going forward."

    "We have generated a diversity panel of phased long-read human genome assemblies that has significantly improved SV discovery and will serve as the basis to construct new population-specific references. Previous large-scale efforts have largely been inferential and biased when it comes to the detection of SVs. Here, we develop a method to discover all forms of genetic variation (PAV) directly by comparison of assembled human genomes. In contrast, SV discovery from the 1000GP was indirect and limited given the frequent proximity of SVs to repeat sequences inaccessible to short reads (15, 23). The 1000GP, for example, reported 69,000 SVs based on the analysis of 2,504 short-read sequenced genomes. In contrast, our analysis of 32 genomes (64 unrelated haplotypes) recovers 107,136 SVs, more than tripling the rate of discovery when compared to short-read Illumina SV analyses on the same samples (Fig. 2D). Recent large-scale short-read sequencing studies (5, 6), interrogating tens of thousands of samples, show even lower SV sensitivity reporting 5,000 to 10,000 SVs per sample, when compared to our phased-assembly approach, which identifies 23,000 to 28,000 SVs per sample. This lack of sensitivity for SV discovery from short reads also affects common variation (AF>5%) and we increase the amount of common SVs by 2.6-fold. The predominant source of this increase in sensitivity was among small SVs (<250 bp) localized to SDs and simple repeat sequences, where we observed a dramatic 8.4-fold increase in variant discovery (12,109 SVs per genome from long-read assembly, 1,444 per genome from Illumina short-read alignment; Fig. 5C). Notably, all discovered genetic variation is physically phased and therefore SVs are fully integrated with their flanking SNVs."

    "Compared to previous reports based on short-read sequencing (25–27), a surprising finding has been the larger fraction of SVs (63%) now assigned to homology-based (>50 bp) mutation mechanisms, including HDR, NAHR and VNTR. Breakpoint characterization with short-read data apparently biased early reports toward relatively unique regions concluding that <30% of SVs were driven by homology-based mutational mechanisms (25–27). Since a majority of unresolved structural variation still maps to large repeats, including centromeres and SDs subject to NAHR, we conclude that homology-based mutational mechanisms will contribute even further and are, therefore, the most predominant mode shaping the SV germline mutational landscape. Notwithstanding, access to fully assembled retrotransposons and their flanking sequence provides the largest collection of annotated source elements for both L1 and SVA mobile elements. We find that 14% of SVA insertions are associated with transductions compared to 8% of L1s—a difference driven in part by the proclivity of SVAs to transduce sequences at their 5ʹ and 3ʹ ends. We find a surprisingly large number of L1 source elements (19%) with defective ORFs suggesting either trans-complementation (56) or polymorphisms leading to the recent demise of these active source elements. Of note, some of the youngest L1 copies (e.g., 6p22.1-1 and 2q24.1) have been reported to be rare polymorphisms able to mediate massive bursts of somatic retrotransposition in cancer genomes (57). This suggests that recently acquired hot L1s, which have not yet reached an equilibrium with our species, contribute disproportionately to disease-causing variation (58)."
    Last edited by cpan0256; 03-01-2021 at 05:30 AM. Reason: doi link does not work

  2. The Following 9 Users Say Thank You to cpan0256 For This Useful Post:

     Agamemnon (03-01-2021),  grumpydaddybear (03-01-2021),  Jatt1 (03-05-2021),  Megalophias (03-04-2021),  palamede (03-13-2021),  pmokeefe (03-01-2021),  Ryukendo (03-02-2021),  sheepslayer (03-01-2021),  slievenamon (03-05-2021)

  3. #1452
    Registered Users
    Posts
    411
    Sex
    Location
    Moscow
    Ethnicity
    East Europe + Finland
    Nationality
    Russian
    Y-DNA (P)
    N-Z1936-Y19110
    mtDNA (M)
    H2a5b

    Russian Federation
    Human ancient DNA analyses reveal the high burden of tuberculosis in Europeans over the last 2,000 years

    Summary

    Tuberculosis (T, usually caused by Mycobacterium tuberculosis bacteria, is the first cause of death from an infectious disease at the worldwide scale, yet the mode and tempo of TB pressure on humans remain unknown. The recent discovery that homozygotes for the P1104A polymorphism of TYK2 are at higher risk to develop clinical forms of TB provided the first evidence of a common, monogenic predisposition to TB, offering a unique opportunity to inform on human co-evolution with a deadly pathogen. Here, we investigate the history of human exposure to TB by determining the evolutionary trajectory of the TYK2 P1104A variant in Europe, where TB is considered to be the deadliest documented infectious disease. Leveraging a large dataset of 1,013 ancient human genomes and using an approximate Bayesian computation approach, we find that the P1104A variant originated in the common ancestors of West Eurasians ∼30,000 years ago. Furthermore, we show that, following large-scale population movements of Anatolian Neolithic farmers and Eurasian steppe herders into Europe, P1104A has markedly fluctuated in frequency over the last 10,000 years of European history, with a dramatic decrease in frequency after the Bronze Age. Our analyses indicate that such a frequency drop is attributable to strong negative selection starting ∼2,000 years ago, with a relative fitness reduction on homozygotes of 20%, among the highest in the human genome. Together, our results provide genetic evidence that TB has imposed a heavy burden on European health over the last two millennia.

    https://www.cell.com/ajhg/fulltext/S...297(21)00051-3

  4. The Following 19 Users Say Thank You to VladimirTaraskin For This Useful Post:

     Agamemnon (03-04-2021),  Bygdedweller (03-04-2021),  Dubhthach (03-11-2021),  eastara (03-05-2021),  grumpydaddybear (03-05-2021),  jadegreg (03-04-2021),  Jatt1 (03-05-2021),  Judith (03-07-2021),  Lupriac (03-16-2021),  Megalophias (03-04-2021),  pmokeefe (03-04-2021),  R.Rocca (03-04-2021),  razyn (03-04-2021),  Riverman (03-15-2021),  Ryukendo (03-04-2021),  Saetro (03-04-2021),  sheepslayer (03-04-2021),  slievenamon (03-05-2021),  teepean47 (03-13-2021)

  5. #1453
    Gold Class Member
    Posts
    788
    Sex
    Location
    San Diego, CA
    Ethnicity
    Polish/British Isles
    Nationality
    U.S.
    Y-DNA (P)
    R-A9185
    mtDNA (M)
    H1
    mtDNA (P)
    J1c2

    Poland England Ireland Munster

    Changes in the fine-scale genetic structure of Finland through the 20th century

    Changes in the fine-scale genetic structure of Finland through the 20th century
    Sini Kerminen,Nicola Cerioli,Darius Pacauskas,Aki S. Havulinna,Markus Perola,Pekka Jousilahti,Veikko Salomaa,Mark J. Daly,Rupesh Vyas,Samuli Ripatti,Matti Pirinen

    Abstract
    Information about individual-level genetic ancestry is central to population genetics, forensics and genomic medicine. So far, studies have typically considered genetic ancestry on a broad continental level, and there is much less understanding of how more detailed genetic ancestry profiles can be generated and how accurate and reliable they are. Here, we assess these questions by developing a framework for individual-level ancestry estimation within a single European country, Finland, and we apply the framework to track changes in the fine-scale genetic structure throughout the 20th century. We estimate the genetic ancestry for 18,463 individuals from the National FINRISK Study with respect to up to 10 genetically and geographically motivated Finnish reference groups and illustrate the annual changes in the fine-scale genetic structure over the decades from 1920s to 1980s for 12 geographic regions of Finland. We detected major changes after a sudden, internal migration related to World War II from the region of ceded Karelia to the other parts of the country as well as the effect of urbanization starting from the 1950s. We also show that while the level of genetic heterogeneity in general increases towards the present day, its rate of change has considerable differences between the regions. To our knowledge, this is the first study that estimates annual changes in the fine-scale ancestry profiles within a relatively homogeneous European country and demonstrates how such information captures a detailed spatial and temporal history of a population. We provide an interactive website for the general public to examine our results.

    Author summary
    We have inherited our genomes from our parents, who, in turn, inherited their genomes from their parents, etc. Hence, a comparison between genomes of present day individuals reveals genetic population structure due to the varying levels of genetic relatedness among the individuals. We have utilized over 18,000 Finnish samples to characterize the fine-scale genetic population structure in Finland starting from a binary East-West division and ending up with 10 Finnish source populations. Furthermore, we have applied the resulting ancestry information to generate records of how the population structure has evolved each year between 1923 and 1987 in 12 geographical regions of Finland. For example, the war-related evacuation of Karelians from Southeast Finland to other parts of the country show up as a clear, sudden increase in the Evacuated ancestry elsewhere in Finland between 1939 and 1945. Additionally, different regions of Finland show very different levels of genetic mixing in 1900s, from little mixed regions like Ostrobothnia to highly mixed regions like Southwestern Finland. To distribute the results among general public, we provide an interactive website for browsing the municipality and region-level genetic ancestry profiles at https://geneviz.aalto.fi/genetic_ancestry_finland/
    YFull: YF14620 (Dante Labs 2018)

  6. The Following 22 Users Say Thank You to pmokeefe For This Useful Post:

     aaronbee2010 (03-06-2021),  Agamemnon (03-04-2021),  Andour (03-04-2021),  anglesqueville (03-09-2021),  Angoliga (03-04-2021),  Bygdedweller (03-04-2021),  cpan0256 (03-11-2021),  Dubhthach (03-11-2021),  Erikl86 (03-05-2021),  Grossvater (03-05-2021),  grumpydaddybear (03-05-2021),  hel (03-05-2021),  jadegreg (03-05-2021),  Jatt1 (03-05-2021),  JMcB (03-04-2021),  Lupriac (03-16-2021),  Megalophias (03-05-2021),  parasar (03-04-2021),  Ryukendo (03-04-2021),  sheepslayer (03-04-2021),  slievenamon (03-05-2021),  teepean47 (03-05-2021)

  7. #1454
    Registered Users
    Posts
    411
    Sex
    Location
    Moscow
    Ethnicity
    East Europe + Finland
    Nationality
    Russian
    Y-DNA (P)
    N-Z1936-Y19110
    mtDNA (M)
    H2a5b

    Russian Federation
    Y-LineageTracker: a high-throughput analysis framework for Y-chromosomal next-generation sequencing data

    Abstract

    Background
    Y-chromosome DNA (Y-DNA) has been used for tracing paternal lineages and offers a clear path from an individual to a known, or likely, direct paternal ancestor. The advance of next-generation sequencing (NGS) technologies increasingly improves the resolution of the non-recombining region of the Y-chromosome (NRY). However, a lack of suitable computer tools prevents the use of NGS data from the Y-DNA studies.

    Results
    We developed Y-LineageTracker, a high-throughput analysis framework that not only utilizes state-of-the-art methodologies to automatically determine NRY haplogroups and identify microsatellite variants of Y-chromosome on a fine scale, but also optimizes comprehensive Y-DNA analysis methods for NGS data. Notably, Y-LineageTracker integrates the NRY haplogroup and Y-STR analysis modules with recognized strategies to robustly suggest an interpretation for paternal genetics and evolution. NRY haplogroup module mainly covers haplogroup classification, clustering analysis, phylogeny construction, and divergence time estimation of NRY haplogroups, and Y-STR module mainly includes Y-STR genotyping, statistical calculation, network analysis, and estimation of time to the most recent common ancestor (TMRCA) based on Y-STR haplotypes. Performance comparison indicated that Y-LineageTracker outperformed existing Y-DNA analysis tools for the high performance and satisfactory visualization effect.

    Conclusions
    Y-LineageTracker is an open-source and user-friendly command-line tool that provide multiple functions to efficiently analyze Y-DNA from NGS data at both Y-SNP and Y-STR level. Additionally, Y-LineageTracker supports various formats of input data and produces high-quality figures suitable for publication. Y-LineageTracker is coded with Python3 and supports Windows, Linux, and macOS platforms, and can be installed manually or via the Python Package Index (PyPI). The source code, examples, and manual of Y-LineageTracker are freely available at https://www.picb.ac.cn/PGG/resource.php or CodeOcean (https://codeocean.com/capsule/7424381/tree).

    https://bmcbioinformatics.biomedcent...59-021-04057-z

  8. The Following 17 Users Say Thank You to VladimirTaraskin For This Useful Post:

     4579kx3745 (03-10-2021),  aaronbee2010 (03-12-2021),  Agamemnon (03-10-2021),  Andour (03-10-2021),  Dubhthach (03-11-2021),  Erikl86 (03-10-2021),  grumpydaddybear (03-11-2021),  jadegreg (03-13-2021),  Jatt1 (03-12-2021),  JMcB (03-14-2021),  Lupriac (03-16-2021),  Megalophias (03-10-2021),  pmokeefe (03-10-2021),  Principe (03-10-2021),  Saetro (03-10-2021),  sheepslayer (03-10-2021),  teepean47 (03-14-2021)

  9. #1455
    Registered Users
    Posts
    3
    Sex

    Genome-wide analysis of nearly all the victims of a 6200 year old massacre

    Mario Novak , Iñigo Olalde , Harald Ringbauer , Nadin Rohland, James Ahern, Jacqueline Balen ,Ivor Janković, Hrvoje Potrebica, Ron Pinhasi ,David Reich

    https://journals.plos.org/plosone/ar...l.pone.0247332

    Abstract
    Paleogenomic and bioanthropological studies of ancient massacres have highlighted sites where the victims were male and plausibly died all in battle, or were executed members of the same family as might be expected from a killing intentionally directed at subsets of a community, or where the massacred individuals were plausibly members of a migrant community in conflict with previously established groups, or where there was evidence that the killing was part of a religious ritual. Here we provide evidence of killing on a massive scale in prehistory that was not directed to a specific family, based on genome-wide ancient DNA for 38 of the 41 documented victims of a 6,200 year old massacre in Potočani, Croatia and combining our results with bioanthropological data. We highlight three results: (i) the majority of individuals were unrelated and instead were a sample of what was clearly a large farming population, (ii) the ancestry of the individuals was homogenous which makes it unlikely that the massacre was linked to the arrival of new genetic ancestry, and (iii) there were approximately equal numbers of males and females. Combined with the bioanthropological evidence that the victims were of a wide range of ages, these results show that large-scale indiscriminate killing is a horror that is not just a feature of the modern and historic periods, but was also a significant process in pre-state societies.

  10. The Following 6 Users Say Thank You to Guy Tipton For This Useful Post:

     aaronbee2010 (03-12-2021),  grumpydaddybear (03-12-2021),  Jatt1 (03-12-2021),  pegasus (03-17-2021),  Riverman (03-15-2021),  tipirneni (03-12-2021)

  11. #1456
    Registered Users
    Posts
    1,170
    Sex
    Location
    Brazil
    Ethnicity
    Rio de Janeiro Colonial
    Nationality
    Brazilian
    Y-DNA (P)
    J1a1 FGC6064+ M365+
    mtDNA (M)
    H1ao1

    Suebi Kingdom Portugal 1143 Portugal 1485 Portugal Order of Christ Brazilian Empire Brazil

    The genetic history of Greenlandic-European contact

    The genetic history of Greenlandic-European contact
    Ryan K. Waples, Aviaja L. Hauptmann, Inge Seiding, Torben Hansen, Anders Albrechtsen, Ida Moltke

    Open Access - Published:March 11, 2021DOI:https://doi.org/10.1016/j.cub.2021.02.041

    Highlights
    The present-day Greenlandic population has substantial amounts of European ancestry
    Denmark is the main source of this European ancestry
    There is little evidence of European ancestry from pre-colonial European contact
    The timing of much of the European admixture is very recent

    Summary
    The Inuit ancestors of the Greenlandic people arrived in Greenland close to 1,000 years ago.1 Since then, Europeans from many different countries have been present in Greenland. Consequently, the present-day Greenlandic population has ∼25% of its genetic ancestry from Europe.2 In this study, we investigated to what extent different European countries have contributed to this genetic ancestry. We combined dense SNP chip data from 3,972 Greenlanders and 8,275 Europeans from 14 countries and inferred the ancestry contribution from each of these 14 countries using haplotype-based methods. Due to the rapid increase in population size in Greenland over the past ∼100 years, we hypothesized that earlier European interactions, such as pre-colonial Dutch whalers and early German and Danish-Norwegian missionaries, as well as the later Danish colonists and post-colonial immigrants, all contributed European genetic ancestry. However, we found that the European ancestry is almost entirely Danish and that a substantial fraction is from admixture that took place within the last few generations.
    J1 FGC5987 to FGC6175 (188 new SNPs)
    MDKAs before Colonial Brazil
    Y-DNA - Milhazes, Barcelos, Minho, Portugal.
    mtDNA - Ilha Terceira, Azores, Portugal
    North_Swedish + PT + PT + PT @ 3.96 EUtest 4

  12. The Following 14 Users Say Thank You to RCO For This Useful Post:

     Agamemnon (03-13-2021),  alexfritz (03-16-2021),  Grossvater (03-14-2021),  grumpydaddybear (03-14-2021),  Jatt1 (03-13-2021),  Lenny Nero (03-15-2021),  Lupriac (03-16-2021),  Megalophias (03-13-2021),  Norfern-Ostrobothnian (03-14-2021),  pmokeefe (03-14-2021),  Ryukendo (03-16-2021),  Saetro (03-16-2021),  sheepslayer (03-13-2021),  ThirdTerm (03-22-2021)

  13. #1457
    Registered Users
    Posts
    411
    Sex
    Location
    Moscow
    Ethnicity
    East Europe + Finland
    Nationality
    Russian
    Y-DNA (P)
    N-Z1936-Y19110
    mtDNA (M)
    H2a5b

    Russian Federation
    Mutation Rate Variability across Human Y-Chromosome Haplogroups


    Abstract
    A common assumption in dating patrilineal events using Y-chromosome sequencing data is that the Y-chromosome mutation rate is invariant across haplogroups. Previous studies revealed interhaplogroup heterogeneity in phylogenetic branch length. Whether this heterogeneity is caused by interhaplogroup mutation rate variation or nongenetic confounders remains unknown. Here, we analyzed whole-genome sequences from cultured cells derived from >1,700 males. We confirmed the presence of branch length heterogeneity. We demonstrate that sex-chromosome mutations that appear within cell lines, which likely occurred somatically or in vitro (and are thus not influenced by nongenetic confounders) are informative for germline mutational processes. Using within-cell-line mutations, we computed a relative Y-chromosome somatic mutation rate, and uncovered substantial variation (up to 83.3%) in this proxy for germline mutation rate among haplogroups. This rate positively correlates with phylogenetic branch length, indicating that interhaplogroup mutation rate variation is a likely cause of branch length heterogeneity.


    https://academic.oup.com/mbe/article/38/3/1000/5922624

  14. The Following 13 Users Say Thank You to VladimirTaraskin For This Useful Post:

     grumpydaddybear (03-14-2021),  J1 DYS388=13 (03-14-2021),  Jatt1 (03-14-2021),  JMcB (03-14-2021),  Lupriac (03-16-2021),  Megalophias (03-14-2021),  pmokeefe (03-14-2021),  RCO (03-14-2021),  Riverman (03-15-2021),  Ruderico (03-15-2021),  Ryukendo (03-16-2021),  Saetro (03-14-2021),  sheepslayer (03-14-2021)

  15. #1458
    Registered Users
    Posts
    1,170
    Sex
    Location
    Brazil
    Ethnicity
    Rio de Janeiro Colonial
    Nationality
    Brazilian
    Y-DNA (P)
    J1a1 FGC6064+ M365+
    mtDNA (M)
    H1ao1

    Suebi Kingdom Portugal 1143 Portugal 1485 Portugal Order of Christ Brazilian Empire Brazil
    The Y chromosome of autochthonous Basque populations and the Bronze Age replacement
    Javier Rodriguez Luis, Leire Palencia-Madrid, Vivian C. Mendoza, Ralph Garcia-Bertrand, Marian M. de Pancorbo & Rene J. Herrera
    Article - Open Access - Published: 10 March 2021
    Scientific Reports volume 11, Article number: 5607 (2021)
    https://doi.org/10.1038/s41598-021-84915-1

    Abstract
    Here we report on the Y haplogroup and Y-STR diversity of the three autochthonous Basque populations of Alava (n = 54), Guipuzcoa (n = 30) and Vizcaya (n = 61). The same samples genotyped for Y-chromosome SNPs were typed for 17 Y-STR loci (DYS19, DYS385a/b, DYS398I/II, DYS390, DYS391, DYS392, DYS393, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635, Y-GATA H4) using the AmpFlSTR Yfiler system. Six major haplogroups (R, I, E, J, G, and DE) were detected, being R-S116 (P312) haplogroup the most abundant at 75.0% in Alava, 86.7% in Guipuzcoa and 87.3% in Vizcaya. Age estimates for the R-S116 mutation in the Basque Country are 3975 ± 303, 3680 ± 345 and 4553 ± 285 years for Alava, Guipuzcoa and Vizcaya, respectively. Pairwise Rst genetic distances demonstrated close Y-chromosome affinities among the three autochthonous Basque populations and between them and the male population of Ireland and Gascony. In a MDS plot, the population of Ireland segregates within the Basque cluster and closest to the population of Guipuzcoa, which plots closer to Ireland than to any of the other Basque populations. Overall, the results support the notion that during the Bronze Age a dispersal of individuals carrying the R-S116 mutation reached the Basque Country replacing the Paleolithic/Neolithic Y chromosome of the region.
    It would be a good article in 2011, ten years ago.
    J1 FGC5987 to FGC6175 (188 new SNPs)
    MDKAs before Colonial Brazil
    Y-DNA - Milhazes, Barcelos, Minho, Portugal.
    mtDNA - Ilha Terceira, Azores, Portugal
    North_Swedish + PT + PT + PT @ 3.96 EUtest 4

  16. The Following 20 Users Say Thank You to RCO For This Useful Post:

     Agamemnon (03-16-2021),  anglesqueville (03-16-2021),  Angoliga (03-16-2021),  grumpydaddybear (03-16-2021),  hartaisarlag (03-16-2021),  Imesmouden (03-16-2021),  Jatt1 (03-16-2021),  Lupriac (03-16-2021),  Menchaca (03-17-2021),  Muircheartaigh (03-16-2021),  parastais (03-16-2021),  pmokeefe (03-22-2021),  R.Rocca (03-16-2021),  razyn (03-16-2021),  Riverman (03-21-2021),  Ruderico (03-16-2021),  Ryukendo (03-16-2021),  Saetro (03-16-2021),  sheepslayer (03-16-2021),  vettor (03-17-2021)

  17. #1459
    Registered Users
    Posts
    1,501
    Sex
    Y-DNA (P)
    C-F5481
    mtDNA (M)
    M8a

    Kyrgyzstan
    https://advances.sciencemag.org/content/7/11/eabd1239

    Research Article GENETICS

    Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

    View ORCID ProfileMark Simcoe1,2, View ORCID ProfileAna Valdes1,3, View ORCID ProfileFan Liu4,5,6, Nicholas A. Furlotte7, View ORCID ProfileDavid M. Evans8,9, View ORCID ProfileGibran Hemani9,10, View ORCID ProfileSusan M. Ring9,10, View ORCID ProfileGeorge Davey Smith9,10, View ORCID ProfileDavid L. Duffy11, View ORCID ProfileGu Zhu11, View ORCID ProfileScott D. Gordon11, View ORCID ProfileSarah E. Medland11, Dragana Vuckovic12,13,14, Giorgia Girotto12,13, View ORCID ProfileCinzia Sala15, View ORCID ProfileEulalia Catamo12, View ORCID ProfileMaria Pina Concas13, Marco Brumat12, Paolo Gasparini12,13, View ORCID ProfileDaniela Toniolo15, View ORCID ProfileMassimiliano Cocca13, View ORCID ProfileAntonietta Robino13, Seyhan Yazar16, View ORCID ProfileAlex Hewitt16,17,18, View ORCID ProfileWenting Wu19, View ORCID ProfilePeter Kraft20, View ORCID ProfileChristopher J. Hammond1,2, Yuan Shi21, Yan Chen4,5,6, View ORCID ProfileChangqing Zeng5, Caroline C. W. Klaver22,23,24, Andre G. Uitterlinden23,25, M. Arfan Ikram23, Merel A. Hamer26, View ORCID ProfileCornelia M. van Duijn23,27, View ORCID ProfileTamar Nijsten26, Jiali Han19, View ORCID ProfileDavid A. Mackey16, View ORCID ProfileNicholas G. Martin11, Ching-Yu Cheng21,28, the 23andMe Research Team, the International Visible Trait Genetics Consortium, David A. Hinds7, Timothy D. Spector1,*, Manfred Kayser4,*,† and Pirro G. Hysi1,2,*,†

    Hide authors and affiliations
    Science Advances 10 Mar 2021:
    Vol. 7, no. 11, eabd1239
    DOI: 10.1126/sciadv.abd1239

    Abstract

    Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

  18. The Following 16 Users Say Thank You to rozenfeld For This Useful Post:

     Andour (03-22-2021),  grumpydaddybear (03-19-2021),  Jatt1 (03-17-2021),  JMcB (03-17-2021),  Lenny Nero (03-17-2021),  Lupriac (03-16-2021),  Milkyway (03-16-2021),  Nebuchadnezzar II (03-16-2021),  peloponnesian (03-17-2021),  pmokeefe (03-22-2021),  Riverman (03-21-2021),  Ruderico (03-16-2021),  Ryukendo (03-16-2021),  Saetro (03-16-2021),  sheepslayer (03-16-2021),  Varun R (03-23-2021)

  19. #1460
    Gold Class Member
    Posts
    788
    Sex
    Location
    San Diego, CA
    Ethnicity
    Polish/British Isles
    Nationality
    U.S.
    Y-DNA (P)
    R-A9185
    mtDNA (M)
    H1
    mtDNA (P)
    J1c2

    Poland England Ireland Munster

    Pan-African genome

    Population-specific genome graphs improve high-throughput sequencing data analysis: A case study on the Pan-African genome
    H. Serhat Tetikol, Kubra Narci, Deniz Turgut, Gungor Budak, Ozem Kalay, Elif Arslan, Sinem Demirkaya-Budak, Alexey Dolgoborodov, Amit Jain, Duygu Kabakci-Zorlu, Richard Brown, Vladimir Semenyuk, Brandi Davis-Dusenbery

    Abstract
    Graph-based genome reference representations have seen significant development, motivated by the inadequacy of the current human genome reference for capturing the diverse genetic information from different human populations and its inability to maintain the same level of accuracy for non-European ancestries. While there have been many efforts to develop computationally efficient graph-based bioinformatics toolkits, how to curate genomic variants and subsequently construct genome graphs remains an understudied problem that inevitably determines the effectiveness of the end-to-end bioinformatics pipeline. In this study, we discuss major obstacles encountered during graph construction and propose methods for sample selection based on population diversity, graph augmentation with structural variants and resolution of graph reference ambiguity caused by information overload. Moreover, we present the case for iteratively augmenting tailored genome graphs for targeted populations and test the proposed approach on the whole-genome samples of African ancestry. Our results show that, as more representative alternatives to linear or generic graph references, population-specific graphs can achieve significantly lower read mapping errors, increased variant calling sensitivity and provide the improvements of joint variant calling without the need of computationally intensive post-processing steps.
    YFull: YF14620 (Dante Labs 2018)

  20. The Following 18 Users Say Thank You to pmokeefe For This Useful Post:

     Agamemnon (03-22-2021),  Andour (03-22-2021),  Angoliga (03-22-2021),  beyoku (03-22-2021),  drobbah (03-22-2021),  grumpydaddybear (03-22-2021),  Jatt1 (03-23-2021),  JMcB (03-22-2021),  Justnotyou (03-26-2021),  Lenny Nero (03-22-2021),  Lupriac (03-22-2021),  Megalophias (03-22-2021),  Mis (03-22-2021),  RCO (03-22-2021),  rozenfeld (03-22-2021),  sheepslayer (03-22-2021),  ThaYamamoto (03-22-2021),  Varun R (03-23-2021)

Page 146 of 148 FirstFirst ... 4696136144145146147148 LastLast

Similar Threads

  1. Genetic Papers - Kurds
    By Kurd in forum Western
    Replies: 19
    Last Post: 09-19-2018, 05:33 AM
  2. Some Additional Papers on the Vikings
    By JMcB in forum I1-M253
    Replies: 3
    Last Post: 07-17-2016, 08:45 AM
  3. Replies: 4
    Last Post: 07-14-2016, 03:21 AM
  4. Papers on Z220
    By ADW_1981 in forum R1b-DF27
    Replies: 4
    Last Post: 06-05-2015, 06:00 PM

Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts
  •