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Thread: okarinaofsteiner's East Eurasian GEDmatch megathread

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    okarinaofsteiner's East Eurasian GEDmatch megathread

    Hello Anthrogenica! Some of you may know me as that person from Anthroscape who posted a lot about how East Eurasians score on GEDmatch calculators. Not proud of being associated with the "race realism" aspect Anthroscape (I was always uncomfortable with the association between "phenotype classification" and racial supremacist ideas), but I find population genetics/history interesting, and I stayed on the forum to participate in the community of Overseas Asians that developed there. There was a lot of discussion of geography, economics, immigration, pop culture, and diaspora Asians' relationships with their native and host cultures in the "Nordsinid/Mittelsinid/Sudsinid" megathread.

    Anyway, I thought I'd make a thread here for re-sharing the content I posted on Anthroscape as a hobby. I never intended for my content to be associated with racialist ideas or ideologies, and thought this could be a better site for hosting that information, since it's more focused on human population genetics.

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    For starters, these are my WeGene and DNA Land results from my 23andMe raw data file

    WeGene
     


    DNA Land
     



    And this is what my single and mixed-mode ancestry for G25 look like, per Tomenable.

    Top 10 Single Population matches
     


    Multiple Populations matches, minus components <1.0%, S_Korea_all (3.7%), and N_Korea_all (1.8%)
     
    Last edited by okarinaofsteiner; 06-26-2020 at 10:34 PM.

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    Analysis of East Asia Genetic Substructure Using Genome-Wide SNP Arrays from 2008

    The populations including those from the HGDP, HapMap, the I-control database, a Korean sample set and East Asian Americans. For all but the East Asian American and Korean samples set, genotypes were available from online databases. These included HapMap subjects (44 CHB and 44 JPT) and HGDP subjects (10 Cambodian, 10 Dai, 24 Hazara, 9 Hezhen, 27 Japanese, 10 Miaozu, 7 Naxi, 8 Oroqen, 10 She, 10 Tu, 10 Tujia, 8 Xibo, 13 Yakut and 44 Han Chinese) from the I-ControlDB (www.illumina.com/iControlDB, Illumina, San Diego, CA). Genotypes from other HGDP subjects (10 Daur, 8 Lahu, 9 Mongola, 10 Uygur, 10 Yi,) were from the NIH Laboratory of Neurogenetics (http://neurogenetics.nia.nih.gov/paperdata/public/).

    The EAS American samples were individuals born in the respective EAS country and were from Vietnam (22 subjects), Philippines (17 subjects) and different regions of the Peoples Republic of China (23 subjects) and Taiwan (9 subjects)... 32 Chinese American samples were recruited in Houston TX. Of the Chinese American participants (CHA), 28 also indicated their general origin from regions within China (6 north, 10 south, 3 central and 9 subjects Taiwan).


    CHB is a sample of Han Chinese people from Beijing, CHA is a sample of Chinese Americans from Texas, and TWN is a subset of CHA referred to as "Chinese Americans from Taiwan". The PCA shows clear Northern Han and Southern Han clusters, although the southern cluster is more diffuse. The distribution of the CHA samples corresponds with their regional origin within China; 7 of the 23 CHA samples fall within the Northern Han cluster, which corresponds to the 6 Chinese Americans who indicated they were of Northern Chinese origin. The "Southern Han" CHA samples also form two separate clusters which appear to correspond to Central and South China.
    Last edited by okarinaofsteiner; 09-12-2020 at 05:41 AM.

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    Genetic Structure of the Han Chinese Population Revealed by Genome-wide SNP Variation from 2009

    Abstract

    Population stratification is a potential problem for genome-wide association studies (GWAS), confounding results and causing spurious associations. Hence, understanding how allele frequencies vary across geographic regions or among subpopulations is an important prelude to analyzing GWAS data. Using over 350,000 genome-wide autosomal SNPs in over 6000 Han Chinese samples from ten provinces of China, our study revealed a one-dimensional ‘‘north-south’’ population structure and a close correlation between geography and the genetic structure of the Han Chinese. The north-south population structure is consistent with the historical migration pattern of the Han Chinese population. Metropolitan cities in China were, however, more diffused ‘‘outliers,’’ probably because of the impact of modern migration of peoples.

    At a very local scale within the Guangdong province, we observed evidence of population structure among dialect groups, probably on account of endogamy within these dialects. Via simulation, we show that empirical levels of population structure observed across modern China can cause spurious associations in GWAS if not properly handled. In the Han Chinese, geographic matching is a good proxy for genetic matching, particularly in validation and candidate-gene studies in which population stratification cannot be directly accessed and accounted for because of the lack of genome-wide data, with the exception of the metropolitan cities, where geographical location is no longer a good indicator of ancestral origin. Our findings are important for designing GWAS in the Chinese population, an activity that is expected to intensify greatly in the near future.
    North-South Structure among Han Chinese. a) Selected Chinese provinces. b) CHB (Beijing university students, purple), Shanghai (orange), and Singapore (yellow). c) Guangdong dialect groups- Cantonese, Hakka, and Teochew.
     


    Map of selected provinces and where they plot on the PCA
     


    Another visualization of the north-south differences among Han subgroups. Red = SEA-like, yellow = Japanese-like, brown = "Continental"
     





    TL;DR:
    1. Most of the regional genetic differences among Han Chinese occur along a north-south axis.
    2. Due to the uneven geography of the country and a history of north->south expansion, Northern Chinese are more homogeneous than Southern Chinese.
    3. Southern China is more mountainous than the north, which resulted in strong founder effects among different subgroups separated by mountain ranges. This resulted in greater linguistic and genetic diversity among and within different Southern Chinese provinces.
    4. This means any rigorous estimate of how "northern" or "southern" different Chinese subgroups are needs to take native topolect and known regional ancestry into account, especially for Southern Chinese provinces/groups.
    Last edited by okarinaofsteiner; 09-12-2020 at 07:00 AM.

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    Quick note on the 1000 Genomes reference populations/datasets:



    CHB (n = 103) -> Chinese university students studying in Beijing (cosmopolitan origin as indicated by their PCA clustering).

    CHS (n -= 105) -> Han Chinese sample of Hunan and Fujian origin (source: http://anthropogenesis.kinshipstudie...s-out-of-asia/)

    “We next tested certain obvious predictions of the out of East Asia model. First, the model predicts lower diversity in people directly associated with the original AMH and higher diversity in people resulting from admixture of AMH with archaic humans. We calculated the hom PGD in slow SNPs as well as het numbers for each of the 25 groups totaling 2534 individuals in 1kGP. The lowest hom PGD level was found in LWK followed by slightly higher level in CHS (Supplementary Figure S8-A). However, LWK has significantly higher numbers of het than CHS (Supplementary Figure S8-. As high level heterozygosity indicates high genetic diversity and would reduce hom distance, it is likely that CHS has lower genetic diversity than LWK. We further found that within CHS (made of 72 individuals from Hunan and 36 from Fujian), Hunan samples have lower hom PGD and het numbers than Fujian samples (Supplementary Figure S8-CD). These results indicate that CHS, in particular Hunan people, have lowest genetic diversity levels among the 25 groups in 1kGP. Given that known admixed groups such as MXL and PUR showed the highest genetic diversity or PGD (Supplementary Figure S8-A), it may be inferred that CHS or Hunan people may have the least amount of admixture and hence represent the original AMH group, at least among the 25 groups sampled here.”
    The other populations of interest are
    • JPT (Japanese from Tokyo)
    • KHV (Kinh/ethnic Vietnamese from Ho Chi Minh City)
    • CDX (Chinese Dai from Xishuangbanna in Yunnan province)




    1000 Genomes paper: https://www.nature.com/articles/nature11632
    Last edited by okarinaofsteiner; 12-26-2020 at 07:27 PM.

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    2017 paper on regional autosomal genetic differences among Han Chinese within China. This paper inspired me to do independent amateur research on how Han Chinese from different regions of Greater China cluster on GEDmatch calculators, because I wanted to see how I compared to other Chinese people haha.

    These samples were taken from hospitals throughout the country- data samples are labeled according to place of birth. (All the Zhejiang samples are of people born in Zhejiang province, all the Shaanxi samples are of people born in Shaanxi province, etc.) I was a bit surprised to see how much more northern Fujian was from Guangdong- I figured Fujian would be more southern-shifted considering how linguistically divergent the Min branch (native to Fujian) of spoken Chinese is from other Chinese varieties that are more directly descended from Middle Chinese.

    https://www.biorxiv.org/content/10.1101/162982v1

    A comprehensive map of genetic variation in the world’s largest ethnic group - Han Chinese
    Charleston W. K. Chiang, Serghei Mangul, Christopher R. Robles, Warren W. Kretzschmar, Na Cai, Kenneth S. Kendler, Sriram Sankararam, Jonathan Flint
    doi: https://doi.org/10.1101/162982
    Now published in Molecular Biology and Evolution doi: 10.1093/molbev/msy170

    https://www.tapatalk.com/groups/anth...ch-t74452.html (Anthroscape link doesn't work anymore)

    Chinese and East Asian users may be interested in this tweet and study:
    https://twitter.com/CharlestonCWKC/s...40817649246208

    Shows population structure in PCA between provinces of China:

    This is cool because they found an East-West dimension beyond the simple North Chinese-South Chinese difference.

    Due to sampling issues, this is effectively just a plot of Shaanxi, Liaoning, Jiangsu, Zhejiang, Sichuan, and Guangdong samples. You could remove all the other provinces and the plot would look exactly the same aside from provincial averages.

    Few cities in their supplement:

    Beijing mostly falls within the Northern China cluster, Shanghai mostly falls within the Jiangzhe (Yangtze Delta) cluster, and Chongqing mostly falls within the range you see with Sichuan samples. Beijing and Shanghai both seem to have a few "southern" outliers, but only a few of the Shanghai samples (and virtually none of the Beijing samples) overlap with the Guangdong samples.

    N-count for each province in the survey. Heilongjiang (HLJ) and Liaoning (LN) in the Northeast are wildly overrepresented relative to population size, as are Shaanxi in the northwest and Jiangsu and Zhejiang in the Yangtze Delta (near Shanghai). Meanwhile, Anhui (AH), Hunan (HUN), Fujian (FJ), and Guangxi (GX)- all southern rice-growing provinces- are underrepresented.






    (Razib Khan’s analysis) https://www.gnxp.com/WordPress/2017/...-map-of-china/
    The most important thing about this preprint is not that the sample size is large enough that they could detect low frequency variants and add to the catalog. No, for me, it is that they sampled so many of the provinces. As you can see in the figure up top just like Europe China’s Han population recapitulate the map of China. That is, populations arrange themselves spatially when projected onto a principle components analysis plot in the same manner that they do geographically. This is a new finding in some ways because previous sampling strategies had not been robust enough to detect the east-west cline (though to be honest if you looked at the Chinese samples in the 1000 Genomes there was suggestion of this).
    Last edited by okarinaofsteiner; 01-29-2021 at 06:47 PM.

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    Quote Originally Posted by okarinaofsteiner View Post
    2017 paper on regional autosomal genetic differences among Han Chinese within China. This paper inspired me to do independent amateur research on how Han Chinese from different regions of Greater China cluster on GEDmatch calculators, because I wanted to see how I compared to other Chinese people haha...


    (Razib Khan’s analysis) https://www.gnxp.com/WordPress/2017/...-map-of-china/
    Do you think the western shift in some Han samples has to do more with drift or differential ancestry sources? In G25 for example, it seems SW Han get more Tanshishan_N admixture while SE Han more Taiwan_Hanben-like.

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    Quote Originally Posted by Max_H View Post
    Do you think the western shift in some Han samples has to do more with drift or differential ancestry sources? In G25 for example, it seems SW Han get more Tanshishan_N admixture while SE Han more Taiwan_Hanben-like.
    If you're talking about the differences along the x-axis of the A comprehensive map of genetic variation in the world’s largest ethnic group - Han Chinese study, I would say drift and migration patterns. Sichuan being close to the other Yangtze Basin provinces is consistent with large-scale migrations into Sichuan from Hubei and Hunan during the last few hundred years. It's also consistent with Sichuan historically being isolated from the north by the Qinling and Daba mountain ranges.

    I was wondering who would be the first person other than me to post in this thread.

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    Do you get any segment matches on the GED archaic match thing? And do you know if it changed recently?
    Last edited by Bbgum; 02-05-2021 at 02:07 AM.

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    Quote Originally Posted by Bbgum View Post
    Do you get any segment matches on the GED archaic match thing? And do you know if it changed recently?
    I match many of the archaic European populations (including the Spain Ice Age ones) using a 0.5 cM threshold, much fewer (but still some) using a 1.0 cM threshold, and just one segment with Ballynahatty (Ireland) 3.2k BP using a 2.0 cM threshold.

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