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Thread: New DNA Papers

  1. #1341
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    geographic structure of Mexico's rich genetic diversity

    Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform
    William A Freyman, Kimberly F McManus, Suyash S Shringarpure, Ethan M Jewett, Katarzyna Bryc, Adam Auton
    Abstract
    Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer (DTC) genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to haplotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Additionally we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale datasets with millions of samples. Furthermore we describe a binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals the geographic structure of Mexico's rich genetic diversity. Our software implementation of the TPBWT is freely available in the code repository
    YFull: YF14620 (Dante Labs 2018)

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  3. #1342
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    Population genomics of the Viking world

    Ashot Margaryan, Daniel J. Lawson, […]Eske Willerslev
    Nature volume 585, pages390–396(2020)


    Abstract
    The maritime expansion of Scandinavian populations during the Viking Age (about AD 750–1050) was a far-flung transformation in world history1,2. Here we sequenced the genomes of 442 humans from archaeological sites across Europe and Greenland (to a median depth of about 1×) to understand the global influence of this expansion. We find the Viking period involved gene flow into Scandinavia from the south and east. We observe genetic structure within Scandinavia, with diversity hotspots in the south and restricted gene flow within Scandinavia. We find evidence for a major influx of Danish ancestry into England; a Swedish influx into the Baltic; and Norwegian influx into Ireland, Iceland and Greenland. Additionally, we see substantial ancestry from elsewhere in Europe entering Scandinavia during the Viking Age. Our ancient DNA analysis also revealed that a Viking expedition included close family members. By comparing with modern populations, we find that pigmentation-associated loci have undergone strong population differentiation during the past millennium, and trace positively selected loci—including the lactase-persistence allele of LCT and alleles of ANKA that are associated with the immune response—in detail. We conclude that the Viking diaspora was characterized by substantial transregional engagement: distinct populations influenced the genomic makeup of different regions of Europe, and Scandinavia experienced increased contact with the rest of the continent.

    And the samples are avalaibe, lots of new stuff for G25?

    https://www.nature.com/articles/s41586-020-2688-8
    Last edited by Finn; 09-16-2020 at 06:52 PM.

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  5. #1343
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    What Shapes the Willingness to Donate DNA and Health Data?

    Global Public Perceptions of Genomic Data Sharing: What Shapes the Willingness to Donate DNA and Health Data?
    Anna Middleton, et. al.
    Summary
    Analyzing genomic data across populations is central to understanding the role of genetic factors in health and disease. Successful data sharing relies on public support, which requires attention to whether people around the world are willing to donate their data that are then subsequently shared with others for research. However, studies of such public perceptions are geographically limited and do not enable comparison. This paper presents results from a very large public survey on attitudes toward genomic data sharing. Data from 36,268 individuals across 22 countries (gathered in 15 languages) are presented. In general, publics across the world do not appear to be aware of, nor familiar with, the concepts of DNA, genetics, and genomics. Willingness to donate one’s DNA and health data for research is relatively low, and trust in the process of data’s being shared with multiple users (e.g., doctors, researchers, governments) is also low. Participants were most willing to donate DNA or health information for research when the recipient was specified as a medical doctor and least willing to donate when the recipient was a for-profit researcher. Those who were familiar with genetics and who were trusting of the users asking for data were more likely to be willing to donate. However, less than half of participants trusted more than one potential user of data, although this varied across countries. Genetic information was not uniformly seen as different from other forms of health information, but there was an association between seeing genetic information as special in some way compared to other health data and increased willingness to donate. The global perspective provided by our “Your DNA, Your Say” study is valuable for informing the development of international policy and practice for sharing genomic data. It highlights that the research community not only needs to be worthy of trust by the public, but also urgent steps need to be taken to authentically communicate why genomic research is necessary and how data donation, and subsequent sharing, is integral to this.
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  7. #1344
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    Y Chromosome as a Tool for DNA Identification and Determination of Ethnoterritorial Origin

    Abstract

    Genetic diversity of a large number of populations is analyzed using various Y-chromosome markers. Genotyping of a wide range of novel highly informative SNP and YSTR markers shows that most of the Y-chromosome haplogroups can be divided not only into ethnically specific lineages but also into narrower sublineages and clusters of haplotypes. A significant extent of population and interethnic genetic differentiation is revealed. Most ethnic gene pools are characterized by the predominance or even complete dominance of specific SNPs across all major haplogroups, that is highly promising for the application in ethnic identification of biological samples of males.

    https://link.springer.com/article/10...22795420090112

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  9. #1345
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    Whole-genome sequencing of 1,171 elderly admixed individuals from the largest Latin American metropolis (São Paulo, Brazil)
    Michel S. Naslavsky, Mayana Zatz et al.

    Abstract
    As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enabled identifying ~2,000 novel mobile element insertions, nearly 5Mb of genomic segments absent from human genome reference, and over 140 novel alleles from HLA genes. We reclassified and curated nearly four hundred variant's pathogenicity assertions in genes associated with dominantly inherited Mendelian disorders and calculated the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observed that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.
    doi: https://doi.org/10.1101/2020.09.15.298026

    https://www.biorxiv.org/content/10.1...09.15.298026v1

    We should take into consideration the size and the growth of the city of São Paulo in 1950 – 2.200.000 and in 2020 – 12.350.000 and that’s only the city, the Município of São Paulo because the metropolitan area is close to 25 million and the entire state of São Paulo is nowadays close to 45 million, so in absolute numbers every segment, (unmixed or admixed) has grown consistently even with the new admixtures.
    J1 FGC5987 to FGC6175 (188 new SNPs)
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    Y-DNA - Milhazes, Barcelos, Minho, Portugal.
    mtDNA - Ilha Terceira, Azores, Portugal
    North_Swedish + PT + PT + PT @ 3.96 EUtest 4

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  11. #1346
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    Ancestry Inference Using Reference Labeled Clusters of Haplotypes

    Ancestry Inference Using Reference Labeled Clusters of Haplotypes
    Keith Noto, Yong Wang, Shiya Song, Joshua G. Schraiber, Alisa Sedghifar, Jake K. Byrnes, David A Turissini, Eurie L. Hong, Catherine A. Ball
    Abstract
    We present ARCHes, a fast and accurate haplotype-based approach for inferring an individual's ancestry composition. Our approach works by modeling haplotype diversity from a large, admixed cohort of hundreds of thousands, then annotating those models with population information from reference panels of known ancestry. The running time of ARCHes does not depend on the size of a reference panel because training and testing are separate processes, and the inferred population-annotated haplotype models can be written to disk and used to label large test sets in parallel (in our experiments, it averages less than one minute to assign ancestry from 32 populations to 1,001 sections of a genotype using 10 CPU). We test ARCHes on public data from the 1,000 Genomes Project and HGDP as well as simulated examples of known admixture. Our results demonstrate that ARCHes outperforms RFMix at correctly assigning both global and local ancestry at regional levels regardless of the amount of population admixture.

    Competing Interest Statement
    The authors declare competing financial interests: authors affiliated with AncestryDNA may have equity in Ancestry. The work described in this manuscript is covered by one or more patents including US patent entitled Local Genetic Ethnicity Determination System US10558930B2.
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  13. #1347
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    Quote Originally Posted by RCO View Post
    Whole-genome sequencing of 1,171 elderly admixed individuals from the largest Latin American metropolis (São Paulo, Brazil)
    Michel S. Naslavsky, Mayana Zatz et al.



    doi: https://doi.org/10.1101/2020.09.15.298026

    https://www.biorxiv.org/content/10.1...09.15.298026v1

    We should take into consideration the size and the growth of the city of São Paulo in 1950 – 2.200.000 and in 2020 – 12.350.000 and that’s only the city, the Município of São Paulo because the metropolitan area is close to 25 million and the entire state of São Paulo is nowadays close to 45 million, so in absolute numbers every segment, (unmixed or admixed) has grown consistently even with the new admixtures.
    And that's why getting from one side of the city to the airport is at least a two hour drive. During a rain storm - forget it!
    Paternal: R1b-U152 >> L2 >> FGC10543 >> PR5365, Pietro Rocca, b. 1559, Agira, Sicily, Italy
    Maternal: H4a1-T152C!, Maria Coto, b. ~1864, Galicia, Spain
    Mother's Paternal: J1+ FGC4745/FGC4766+ PF5019+, Gerardo Caprio, b. 1879, Caposele, Avellino, Campania, Italy
    Father's Maternal: T2b-C150T, Francisca Santa Cruz, b.1916, Garganchon, Burgos, Spain
    Paternal Great (x3) Grandfather: R1b-U106 >> L48 >> CTS2509, Filippo Ensabella, b.~1836, Agira, Sicily, Italy

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  15. #1348
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    Quote Originally Posted by Huck Finn View Post
    Ancient DNA, SW Finland. These people look like Estonians, Russians, Belorussians and such, very different from Levänluhta group.

    https://eaa.klinkhamergroup.com/eaa2...q51ZoW7lGj99c0
    It looks like this has been taken down. What were the major conclusions, and from which time period are the samples from?
    Quoted from this Forum:

    "Which superman haplogroup is the toughest - R1a or R1b? And which SNP mutation spoke Indo-European first? There's only one way for us to find out ... fight!"

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    Quote Originally Posted by Ryukendo View Post
    It looks like this has been taken down. What were the major conclusions, and from which time period are the samples from?
    Their conclusions were a bit wonky because they didn't or couldn't run a proper intra-North European analysis.

    These samples have nothing at all to do with Belorussians, but they kind of just cluster close to them in the usual West Eurasian PCA.

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  18. #1350
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    I believe they were from the Middle Ages.

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