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Thread: New DNA Papers

  1. #901
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    https://www.biorxiv.org/content/earl...medium=twitter

    MITOMIX, an Algorithm to Reconstruct Population Admixture Histories Indicates Ancient European Ancestry of Modern Hungarians

    Zoltan Maroti, Tibor Torok, Endre Neparaczki, Istvan Rasko, Istvan Nagy, Miklos Maroti, Tamas Varga, Peter Bihari, Zsolt Boldogkoi, Dora Tombacz, Tibor Kalmar

    doi: https://doi.org/10.1101/247395

    Abstract

    By making use of the increasing number of available mitogenomes we propose a novel population genetic distance metric, named Shared Haplogroup Distance (SHD). Unlike FST, SHD is a true mathematical distance that complies with all metric axioms, which enables our new algorithm (MITOMIX) to detect population-level admixture based on SHD minimum optimization. In order to demonstrate the effectiveness of our methodology we analyzed the relation of 62 modern and 25 ancient Eurasian human populations, and compared our results with the most widely used FST calculation. We also sequenced and performed an in-depth analysis of 272 modern Hungarian mtDNA genomes to shed light on the genetic composition of modern Hungarians. MITOMIX analysis showed that in general admixture occurred between neighboring populations, but in some cases it also indicated admixture with migrating populations. SHD and MITOMIX analysis comply with known genetic data and shows that in case of closely related and/or admixing populations, SHD gives more realistic results and provides better resolution than FST. Our results suggest that the majority of modern Hungarian maternal lineages have Late Neolith/Bronze Age European origins (partially shared also with modern Danish, Belgian/Dutch and Basque populations), and a smaller fraction originates from surrounding (Serbian, Croatian, Slovakian, Romanian) populations. However only a minor genetic contribution (<3%) was identified from the IXth Hungarian Conquerors whom are deemed to have brought Hungarians to the Carpathian Basin. Our analysis shows that SHD and MITOMIX can augment previous methods by providing novel insights into past population processes.

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  3. #902
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    https://www.nature.com/articles/s41588-017-0031-6

    Reconstructing an African haploid genome from the 18th century

    Anuradha Jagadeesan, Ellen D. Gunnarsdóttir, S. Sunna Ebenesersdóttir, Valdis B. Guðmundsdóttir, Elisabet Linda Thordardottir, Margrét S. Einarsdóttir, Hákon Jónsson, Jean-Michel Dugoujon, Cesar Fortes-Lima, Florence Migot-Nabias, Achille Massougbodji, Gil Bellis, Luisa Pereira, Gísli Másson, Augustine Kong, Kári Stefánsson & Agnar Helgason

    Nature Genetics (2018)
    doi:10.1038/s41588-017-0031-6

    Received: 01 March 2017
    Accepted: 18 December 2017
    Published online: 15 January 2018

    Abstract

    A genome is a mosaic of chromosome fragments from ancestors who existed some arbitrary number of generations earlier. Here, we reconstruct the genome of Hans Jonatan (HJ), born in the Caribbean in 1784 to an enslaved African mother and European father. HJ migrated to Iceland in 1802, married and had two children. We genotyped 182 of his 788 descendants using single-nucleotide polymorphism (SNP) chips and whole-genome sequenced (WGS) 20 of them. Using these data, we reconstructed 38% of HJ’s maternal genome and inferred that his mother was from the region spanned by Benin, Nigeria and Cameroon.


    UPD: In addition, we used WGS data from a sixth-generation patrilineal descendant of HJ to determine that his Y chromosome belongs to haplogroup I2a2a3a2 (according to the ISOGG 2013 classification system), which has a frequency of 0.15% in Iceland.
    Last edited by rozenfeld; 01-15-2018 at 08:34 PM.

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  5. #903
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    https://www.nature.com/articles/s41598-017-18893-8

    Article | Open

    Ancient Human Migrations to and through Jammu Kashmir- India were not of Males Exclusively

    Indu Sharma, Varun Sharma, Akbar Khan, Parvinder Kumar, Ekta Rai, Rameshwar N. K. Bamezai, Miguel Vilar & Swarkar Sharma

    Scientific Reports 8, Article number: 851 (2018)
    doi:10.1038/s41598-017-18893-8

    Received: 23 June 2017
    Accepted: 19 December 2017
    Published online: 16 January 2018

    Abstract

    Jammu and Kashmir (J&K), the Northern most State of India, has been under-represented or altogether absent in most of the phylogenetic studies carried out in literature, despite its strategic location in the Himalayan region. Nonetheless, this region may have acted as a corridor to various migrations to and from mainland India, Eurasia or northeast Asia. The belief goes that most of the migrations post-late-Pleistocene were mainly male dominated, primarily associated with population invasions, where female migration may thus have been limited. To evaluate female-centered migration patterns in the region, we sequenced 83 complete mitochondrial genomes of unrelated individuals belonging to different ethnic groups from the state. We observed a high diversity in the studied maternal lineages, identifying 19 new maternal sub-haplogroups (HGs). High maternal diversity and our phylogenetic analyses suggest that the migrations post-Pleistocene were not strictly paternal, as described in the literature. These preliminary observations highlight the need to carry out an extensive study of the endogamous populations of the region to unravel many facts and find links in the peopling of India.

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    Estimating time to the common ancestor for a beneficial allele

    Joel Smith1,*, Graham Coop2, Matthew Stephens3,4, and John Novembre3

    Abstract

    The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele’s age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the sur- rounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to ap- proaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans.

    https://watermark.silverchair.com/ms...W_fcBIHfryzczg

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  9. #905
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    Quote Originally Posted by Chad Rohlfsen View Post
    Estimating time to the common ancestor for a beneficial allele

    Joel Smith1,*, Graham Coop2, Matthew Stephens3,4, and John Novembre3

    Abstract

    The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele’s age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the sur- rounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to ap- proaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans.

    https://watermark.silverchair.com/ms...W_fcBIHfryzczg
    That link would not work for me.
    This one does https://www.biorxiv.org/content/early/2016/08/24/071241
    But this is a pre-print from August 2016.
    Could not locate formal publication. Chad, is that what your link connected to?

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