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Thread: New DNA Papers

  1. #1441
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    Y chromosome analysis for common surnames in the Japanese male population

    https://www.nature.com/articles/s10038-020-00884-9#Tab1

    C-M130 - 10,1%
    D*-M174 - 7,9%
    D1b1-M116.1 - 29,3%
    N-M231 - 0,4%
    O*-P186 - 2,3%
    O1b-M268 - 28,7%
    O2-P198 - 20,8%
    Q-M242 - 0,5%

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  3. #1442
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    Inner-Dual Structure”model on the formation of the modern Japanese population

    Genome-wide SNP data of Izumo and Makurazaki populations support inner-dual structure model for origin of Yamato people
    Timothy Jinam, Yosuke Kawai, Yoichiro Kamatani, Shunro Sonoda, Kanro Makisumi, Hideya Sameshima, Katsushi Tokunaga & Naruya Saitou

    Abstract
    The “Dual Structure” model on the formation of the modern Japanese population assumes that the indigenous hunter-gathering population (symbolized as Jomon people) admixed with rice-farming population (symbolized as Yayoi people) who migrated from the Asian continent after the Yayoi period started. The Jomon component remained high both in Ainu and Okinawa people who mainly reside in northern and southern Japan, respectively, while the Yayoi component is higher in the mainland Japanese (Yamato people). The model has been well supported by genetic data, but the Yamato population was mostly represented by people from Tokyo area. We generated new genome-wide SNP data using Japonica Array for 45 individuals in Izumo City of Shimane Prefecture and for 72 individuals in Makurazaki City of Kagoshima Prefecture in Southern Kyushu, and compared these data with those of other human populations in East Asia, including BioBank Japan data. Using principal component analysis, phylogenetic network, and f4 tests, we found that Izumo, Makurazaki, and Tohoku populations are slightly differentiated from Kanto (including Tokyo), Tokai, and Kinki regions. These results suggest the substructure within Mainland Japanese maybe caused by multiple migration events from the Asian continent following the Jomon period, and we propose a modified version of “Dual Structure” model called the “Inner-Dual Structure” model.
    YFull: YF14620 (Dante Labs 2018)

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  5. #1443
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    Genetic profiles of 103,106 individuals in the Taiwan Biobank

    Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese
    Chun-Yu Wei, Jenn-Hwai Yang, Erh-Chan Yeh, Ming-Fang Tsai, Hsiao-Jung Kao, Chen-Zen Lo, Lung-Pao Chang, Wan-Jia Lin, Feng-Jen Hsieh, Saurabh Belsare, Anand Bhaskar, Ming-Wei Su, Te-Chang Lee, Yi-Ling Lin, Fu-Tong Liu, Chen-Yang Shen, Ling-Hui Li, Chien-Hsiun Chen, Jeffrey D. Wall, Jer-Yuarn Wu & Pui-Yan Kwok

    Abstract
    Personalized medical care focuses on prediction of disease risk and response to medications. To build the risk models, access to both large-scale genomic resources and human genetic studies is required. The Taiwan Biobank ( TWB ) has generated high-coverage, whole-genome sequencing data from 1492 individuals and genome-wide SNP data from 103,106 individuals of Han Chinese ancestry using custom SNP arrays. Principal components analysis of the genotyping data showed that the full range of Han Chinese genetic variation was found in the cohort. The arrays also include thousands of known functional variants, allowing for simultaneous ascertainment of Mendelian disease-causing mutations and variants that affect drug metabolism. We found that 21.2% of the population are mutation carriers of autosomal recessive diseases, 3.1% have mutations in cancer-predisposing genes, and 87.3% carry variants that affect drug response. We highlight how TWB data provide insight into both population history and disease burden, while showing how widespread genetic testing can be used to improve clinical care.

    Taiwan.png
    a Number of novel (non-Taiwanese Minnan) variants for each additional sample stratified by province (axes markings represent latitudes and longitudes). Adapted from the Digital Map Database of China, 2020, “Provincial Boundary”, https://doi.org/10.7910/DVN/DBJ3BX, Harvard Dataverse, V1. b Estimated past population sizes for Taiwanese Minnan.
    Last edited by pmokeefe; 02-14-2021 at 01:29 PM.
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  7. #1444
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    Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection

    Kevin K. Esoh, Tobias O. Apinjoh, Steven G. Nyanjom, Ambroise Wonkam, Emile R. Chimusa, Lucas Amenga-Etego, Alfred Amambua-Ngwa & Eric A. Achidi

    Abstract

    Inferences from genetic association studies rely largely on the definition and description of the underlying populations that highlight their genetic similarities and differences. The clustering of human populations into subgroups (population structure) can significantly confound disease associations. This study investigated the fine-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fine-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi-Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric differentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confirming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in the HBB gene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fine-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.



    Very interesting regarding fine-scale differentiation in and around the region, the haplotype variation is crazy. Some interesting points for me personally based on g25 and other observations:

    The SB appeared genetically closer to the Yoruba of Nigeria (YRI) (FST SBvsYRI = 0.002) than did the BA (FST BAvsYRI = 0.003) contrary to previous estimates20. We further found that the FO ethnicity is relatively less genetically related to the YRI (FST = 0.004) compared to Cameroonian SB and BA populations. In addition, contrary to prior estimates that the Cameroonian BA population was genetically closer to the Luhya population of Kenya (LWK), we observed no difference in FST among the LWK population and all Cameroonian populations herein studied (all pairwise FST = 0.005). Interestingly, the FO, like the LWK population appeared to be more genetically close to populations of European and Asian ancestries as compared to the BA and SB, supporting possible influence of Eurasian migration back into Africa
    Although they didn't employ a TVD analysis which is far more helpful for fine-scale African genomics imo.

    edit: the second bolded part on LWK being closer to Eurasians is most likely just due to Dinka being closer to Eurasians and thus the admixture results in that right?
    Last edited by ThaYamamoto; 02-17-2021 at 08:57 PM.

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  9. #1445
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    The first complete genome assembly of the Zoroastrian-Parsi community of Indiai

    Ancient migrations - The first complete genome assembly, annotation and variants of the Zoroastrian-Parsi community of India
    Naseer Pasha, Kashyap Krishnasamy, Naveenkumar Nagarajan, Seshank Mutya, Bhavika Mam, Kouser Sonnekhan, Chellappa Gopalakrishnan, Renuka Jain, Villoo-Morawala Patell

    Abstract
    With the advent of Next Generation Sequencing, many population specific whole genome sequences published thus far, predominantly represent individuals of European ancestry. While sequencing efforts of underrepresented communities in genomes datasets, like the Yoruba West-African, Han Chinese, Tibetan, South Korean, Egyptian and Japanese have recently added to the public genomic repositories, a comprehensive understanding of human genomic diversity and discovery of trait-associated variants necessitates the need for additional population specific analysis. In this context, the genomics of the population from the Indian sub-continent, given its genetic heterogeneity needs further elucidation. In this context, the endogamous Zoroastrian-Parsi community of India, offer an exceptional insight into a homogenous population that has culturally, socially, and genetically remained intact, for 13 centuries amidst the genomic, social and cultural Indian landscape, consequent to their migration from the ancient Persian plateau. Notwithstanding longevity as a trait, this endangered community is highly susceptible to cancers, rare genetic disorders, and display a documented high incidence of neurodegenerative and autoimmune conditions. The community as a matter of cultural practice abstains from smoking. Here, we describe the assembly and annotation of the genome of an adult female, Zoroastrian-Parsi individual sequenced at a high depth of 173X using a combination of short Illumina reads (160X) and long nanopore reads (13X). Using a combination of hybrid assemblers, we created a new, population-specific human reference genome, The Zoroastrian-Parsi Genome Reference Female, AGENOME-ZPGRF, contains 2,778,216,114 nucleotides as compared to 3,096,649,726 in GRCh38 constituting 93.235% of the total genomic fraction. Annotation identified 20833 genomic features, of which 14996 are almost identical to their counterparts on GRCh38 while 5837 genomic features were covered in partial. AGENOME-ZPGRF contained 5,426,310 variants of which the majority were SNPs (4,291,601) and 960,867 SNPs were AGENOME-ZPGRF specific personal variants not listed in dbSNP. We present, AGENOME-ZPGRF as a whole reference for any genetic studies involving Zoroastrian-Parsi individuals extending their application to identify disease relevant prognostic biomarkers and variants in global population genomics studies.
    YFull: YF14620 (Dante Labs 2018)

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  11. #1446
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    I don't know if this one has been posted :

    Social stratification without genetic differentiation at the site of Kulubnarti in Christian Period Nubia


    https://www.biorxiv.org/content/10.1...02.17.431423v1

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  13. #1447
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    Personalized genealogical history of UK individuals inferred from biobank-scale IBD

    Personalized genealogical history of UK individuals inferred from biobank-scale IBD segments
    Ardalan Naseri, Kecong Tang, Xin Geng, Junjie Shi, Jing Zhang, Pramesh Shakya, Xiaoming Liu, Shaojie Zhang & Degui Zhi

    Abstract
    Background
    The genealogical histories of individuals within populations are of interest to studies aiming both to uncover detailed pedigree information and overall quantitative population demographic histories. However, the analysis of quantitative details of individual genealogical histories has faced challenges from incomplete available pedigree records and an absence of objective and quantitative details in pedigree information. Although complete pedigree information for most individuals is difficult to track beyond a few generations, it is possible to describe a person’s genealogical history using their genetic relatives revealed by identity by descent (IBD) segments—long genomic segments shared by two individuals within a population, which are identical due to inheritance from common ancestors. When modern biobanks collect genotype information for a significant fraction of a population, dense genetic connections of a person can be traced using such IBD segments, offering opportunities to characterize individuals in the context of the underlying populations. Here, we conducted an individual-centric analysis of IBD segments among the UK Biobank participants that represent 0.7% of the UK population.

    Results
    We made a high-quality call set of IBD segments over 5 cM among all 500,000 UK Biobank participants. On average, one UK individual shares IBD segments with 14,000 UK Biobank participants, which we refer to as “relatives.” Using these segments, approximately 80% of a person’s genome can be imputed. We subsequently propose genealogical descriptors based on the genetic connections of relative cohorts of individuals sharing at least one IBD segment and show that such descriptors offer important information about one’s genetic makeup, personal genealogical history, and social behavior. Through analysis of relative counts sharing segments at different lengths, we identified a group, potentially British Jews, who has a distinct pattern of familial expansion history. Finally, using the enrichment of relatives in one’s neighborhood, we identified regional variations of personal preference favoring living closer to one’s extended families.

    Conclusions
    Our analysis revealed genetic makeup, personal genealogical history, and social behaviors at the population scale, opening possibilities for further studies of individual’s genetic connections in biobank data.
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  15. #1448
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    A Chromosome-Painting Based Pipeline to Infer Local Ancestry ...

    A Chromosome-Painting Based Pipeline to Infer Local Ancestry under Limited Source Availability
    Ludovica Molinaro, Davide Marnetto, Mayukh Mondal, Linda Ongaro, Burak Yelmen, Daniel John Lawson, Francesco Montinaro, Luca Pagani

    Abstract
    Contemporary individuals are the combination of genetic fragments inherited from ancestors belonging to multiple populations, as the result of migration and admixture. Isolating and characterising these layers is crucial to the understanding of the genetic history of a given population. Ancestry deconvolution approaches make use of a large amount of source individuals, therefore constraining the performance of local ancestry inferences when only few genomes are available from a given population. Here we present WINC, a local ancestry framework derived from the combination of ChromoPainter and NNLS approaches, as a method to retrieve local genetic assignments when only a few reference individuals are available. The framework is aided by a score assignment based on source differentiation to maximise the amount of sequences retrieved, and is capable of retrieving accurate ancestry assignments when only two individuals for source populations are used.
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  17. #1449
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    https://www.biorxiv.org/content/10.1...M6QxlZ_kyz-LDI

    Using Y-chromosome capture enrichment to resolve haplogroup H2 shows new evidence for a two-Path Neolithic expansion to Western Europe

    View ORCID ProfileAdam Benjamin Rohrlach, Luka Papac, Ainash Childebayeva, Maite Rivollat, Vanessa Villalba-Mouco, Gunnar U Neumann, Sandra Penske, Eirini B Skourtanioti, Marieke van de Loosdrecht, Murat Akar, Kamen Boyadzhiev, Yavor Boyadzhiev, Marie-France Deguilloux, Miroslav Dobes, Yilmaz S Erdal, Michal Ernee, Marcella Frangipane, Miroslaw Furmanek, Susanne Friederich, Emmanuel Ghesquiere, Agata Haluszko, Svend Hansen, Mario Kuessner, Marcello Mannino, Rana Oezbal, Sabine Reinhold, Stephane Rottier, Domingo Carlos Salazar-Garcia, Jorge Soler Diaz, Philipp W Stockhammer, Consuelo Roca de Togores Munoz, K. Aslıhan Yener, Cosimo Posth, Johannes Krause, View ORCID ProfileAlexander Herbig, Wolfgang Haak
    doi: https://doi.org/10.1101/2021.02.19.431761


    https://www.biorxiv.org/content/10.1...761v1.full.pdf
    Last edited by vettor; 02-20-2021 at 08:33 PM.


    My Path = ( K-M9+, TL-P326+, T-M184+, L490+, M70+, PF5664+, L131+, L446+, CTS933+, CTS3767+, CTS8862+, Z19945+, BY143483+ )


    Grandfather via paternal grandmother = I1-Y33791 ydna
    Great grandmother paternal side = T1a1e mtdna

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  19. #1450
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    Has this been posted before? Perhaps when it was on a preprint server?

    https://www.pnas.org/content/pnas/11...09118.full.pdf AF8E3966-34F5-4115-BB68-A3C301E72545.png
    Image “Westray wifie” replica of Neolithic figurine Hidden Content
    Out of 64 pre 1800 births 45% Cheshire, 1% Irish (or Scottish), 25% south Derbyshire, 13% Burton on Trent area (where 4 counties within 10 miles), 7% Shropshire, 1% Staffs, 8% Lancs. So far all British Isles despite what some testing companies say.

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