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Thread: Waves of migration into South Asia

  1. #951
    Quote Originally Posted by Kurd View Post

    EDIT: Although I am not the authority on dstats (Nick Patterson is since he was involved in the creation of the program), I believe the dstat you posted only shows that Karitiana share the same amount of drift as Clovis with Ust. In other words, the drift paths of Clovis and Karitiana individually, post split of the native American branch from the tree do not affect the dstat. You may want to check the stat using various Amerindians to rule out coincidence
    I assumed that was Kale's point....modern Karitiana and late paleo Clovis exhibit a comparable degree of relatedness to Ust-I, despite the former having an additional 12K years to drift.

    All that this shows, though, is that drift doesn't seem to be an issue in this particular comparison (with Karitiana, Clovis, and Ust-I) ; it doesn't show drift can never be a factor. The Clovis sample was overall very similar to Southern Amerindians like Karitiana and less like North American. I'd be curious what would happen if you used, say, Athabaskan instead of Karitiana.

  2. #952
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    Quote Originally Posted by arigiery View Post
    I assumed that was Kale's point....modern Karitiana and late paleo Clovis exhibit a comparable degree of relatedness to Ust-I, despite the former having an additional 12K years to drift.

    All that this shows, though, is that drift doesn't seem to be an issue in this particular comparison (with Karitiana, Clovis, and Ust-I) ; it doesn't show drift can never be a factor. The Clovis sample was overall very similar to Southern Amerindians like Karitiana and less like North American. I'd be curious what would happen if you used, say, Athabaskan instead of Karitiana.

    Yes, he got me curious. I will run D (Amerind1, Amerind2, Clovis, Mbuti) in a couple of hours. I have a hunch that this may show the varying individual drifts for various Amerindians

  3. #953
    Quote Originally Posted by Kurd View Post
    Yes, he got me curious. I will run D (Amerind1, Amerind2, Clovis, Mbuti) in a couple of hours. I have a hunch that this may show the varying individual drifts for various Amerindians
    Cool. North American Indians are similar to South American Indians (as well as Clovis) but with more East Asian affinity (and less Mal'ta affinity). From what I remember, Ust-I (unlike Mal'ta) was about equally as related to Amerindians and East Asians. So, come to think of it, I am a bit skeptical that North Amerindians will end up being more/less drifted from Ust than South Amerindians or Clovis ppls are. But, anyhow, I guess we'll soon find out.

  4. #954
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    Quote Originally Posted by arigiery View Post
    Cool. North American Indians are similar to South American Indians (as well as Clovis) but with more East Asian affinity (and less Mal'ta affinity). From what I remember, Ust-I (unlike Mal'ta) was about equally as related to Amerindians and East Asians. So, come to think of it, I am a bit skeptical that North Amerindians will end up being more/less drifted from Ust than South Amerindians or Clovis ppls are. But, anyhow, I guess we'll soon find out.
    My hunch was correct. When comparing various Amerindians against Clovis, dstats show their individual drifts which vary as expected. Apparently Surui and Karitiana share the most drift with Clovis. Surui and Karitiana share similar drift to Clovis. A contributing factor could be admixture between the 2 after they split from the branch.

    result: Mayan Karitiana Clovis Mbuti -0.0324 -9.684 25518 27227 473422
    result: Mixe Karitiana Clovis Mbuti -0.0085 -2.172 25693 26131 473422
    result: Piapoco Karitiana Clovis Mbuti -0.0069 -1.718 25253 25606 473420
    result: Pima Karitiana Clovis Mbuti -0.0242 -5.926 25689 26962 473422
    result: Quechua Karitiana Clovis Mbuti -0.0387 -9.691 25405 27452 473422
    result: Surui Karitiana Clovis Mbuti -0.0000 -0.002 24922 24922 473421
    Last edited by Kurd; 11-24-2017 at 11:14 PM.

  5. #955
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    Also as expected not all American Indians share the same amount of drift with Ust-Ishim. Karitiana, Surui, and Piapaco share the most drift with Ust

    result: Mayan Karitiana UstIshim_Fu Mbuti -0.0106 -3.801 23902 24412 473306
    result: Mixe Karitiana UstIshim_Fu Mbuti -0.0032 -1.044 23620 23773 473306
    result: Piapoco Karitiana UstIshim_Fu Mbuti -0.0026 -0.775 23215 23338 473304
    result: Pima Karitiana UstIshim_Fu Mbuti -0.0060 -1.826 23950 24242 473306
    result: Quechua Karitiana UstIshim_Fu Mbuti -0.0079 -2.492 24039 24424 473306
    result: Surui Karitiana UstIshim_Fu Mbuti 0.0016 0.450 22792 22719 473305




    Karitiana also share the most drift with MA1 followed by Surui. Mayans and Quechuans share the least drift with Ust, MA1, and Clovis. Contributing factors to accelerated genetic drifts include:

    1- Smaller population sizes
    2- Greater isolation, less geneflow from the outside

    Other factors that can cause reduced shared drifts is admixture from outside the clade post split.


    EDIT: Forgot to post MA1
    result: Mayan Karitiana Malta1_Fu Mbuti -0.0182 -5.601 17668 18324 340190
    result: Mixe Karitiana Malta1_Fu Mbuti -0.0091 -2.391 17494 17817 340190
    result: Piapoco Karitiana Malta1_Fu Mbuti -0.0155 -3.852 17056 17594 340188
    result: Pima Karitiana Malta1_Fu Mbuti -0.0115 -3.042 17758 18173 340190
    result: Quechua Karitiana Malta1_Fu Mbuti -0.0169 -4.504 17752 18363 340190
    result: Surui Karitiana Malta1_Fu Mbuti -0.0075 -1.736 16828 17081 340189
    Last edited by Kurd; 11-24-2017 at 11:17 PM.

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  7. #956
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    Quote Originally Posted by Kurd View Post
    Also as expected not all American Indians share the same amount of drift with Ust-Ishim. Karitiana, Surui, and Piapaco share the most drift with Ust

    result: Mayan Karitiana UstIshim_Fu Mbuti -0.0106 -3.801 23902 24412 473306
    result: Mixe Karitiana UstIshim_Fu Mbuti -0.0032 -1.044 23620 23773 473306
    result: Piapoco Karitiana UstIshim_Fu Mbuti -0.0026 -0.775 23215 23338 473304
    result: Pima Karitiana UstIshim_Fu Mbuti -0.0060 -1.826 23950 24242 473306
    result: Quechua Karitiana UstIshim_Fu Mbuti -0.0079 -2.492 24039 24424 473306
    result: Surui Karitiana UstIshim_Fu Mbuti 0.0016 0.450 22792 22719 473305
    You act like all of those samples are 100% Native American. I don't believe that is the case. Check this admixture run...
    https://genetiker.wordpress.com/2017...opean-genomes/

    Maya, Pima, and Quechua, the only ones with borderline significant stats with Ust_Ishim are coincidentally the only ones with European admixture and the basal Eurasian that accompanies it.

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    Quote Originally Posted by Jean M View Post
    Here is my messy attempt to fit South Asians onto the Lazaridis 2014 diagram for Europeans.

    Attachment 2934

    Explanation: the South Asian population is very complex. It is a huge area that has attracted numerous inward migrations, including some from East Asia that I do not show, as they are distinct from the simple ASI/ANI model of Reich et al. 2009.

    What I attempt to show is:

    1. ASI: a migration from Africa via India to Australia, maybe 30-40 ka earlier than the next out-of-Africa migration.
    2. Palaeolithic: mtDNA haplogroup U2 (at least) from the next dispersal out of Africa. Component in Dravidian-speakers?
    3. Neolithic: migration of farmers from Iran to Indus valley. Ancestors IVC. Most likely Y-DNA J included. Language now dead, as absorbed by incoming IE. [Note: rice-farming input from east is not shown on diagram, simply to avoid creating even more mess on a chart not meant for South Asia]
    4. Indic: migration from region of BMAC, which had been taken over by Andronovo-Tazabagyab people. The mixture of IE and the language of the BMAC seems to have produced ancestral Indic http://en.wikipedia.org/wiki/Bactria...ogical_Complex


    Later inward migrations included
    1. Scythians (whom we can expect to bring more of the Yamnaya mixture, plus a bit of East Asian) http://en.wikipedia.org/wiki/Indo-Scythians
    2. Arabian
    3. Muslim conquests on the Indian subcontinent http://en.wikipedia.org/wiki/Muslim_...n_subcontinent


    I'm sure experts on South Asia can improve on this.
    What about big connection between Hungarian bronze age samples and Some soldier castes in India and South Asia ?



    For example on BR2, Hungary, 3.2ky sample, I am getting following hits

    Largest segment = 4.6 cM
    Total of segments > 1 cM = 751.9 cM
    505 matching segments

    Significant other hits in Bronze age samples. Does it indicate Bronze age people in Hungary (supposedly some cultures Maros disappear after 1400BC) moved widespread into India/SouthAsia/CentralAsis during Indo-Aryan or later.
    I get similar match to Stuttgart sample. However I got big SouthIndian component. Does it mean the migration occurred during Neolithic times into SouthAsia from Europe?

  10. #958
    Quote Originally Posted by Kale View Post
    You act like all of those samples are 100% Native American. I don't believe that is the case. Check this admixture run...
    https://genetiker.wordpress.com/2017...opean-genomes/

    Maya, Pima, and Quechua, the only ones with borderline significant stats with Ust_Ishim are coincidentally the only ones with European admixture and the basal Eurasian that accompanies it.
    That blog's writer is a White Nationalist who claims that Europeans traveled to the Americans way before the Norse.

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    Quote Originally Posted by Kale View Post
    You act like all of those samples are 100% Native American. I don't believe that is the case. Check this admixture run...
    https://genetiker.wordpress.com/2017...opean-genomes/

    Maya, Pima, and Quechua, the only ones with borderline significant stats with Ust_Ishim are coincidentally the only ones with European admixture and the basal Eurasian that accompanies it.

    That is why I wrote

    1- Smaller population sizes
    2- Greater isolation, less geneflow from the outside

    Other factors that can cause reduced shared drifts is admixture from outside the clade post split.
    The point is no one uses dstats to measure modern human contamination in aDNA. The only methods used as I stated before are:
    X CHROMOSOME (MALES ONLY):

    Since males have 1 X and are expected to be haploid on their X, you count the number of positions where the aDNA is diploid, and use that to estimate contamination in the nuclear DNA. If you check my website you'll see that I used the DICE program introduced by Renaud et al to estimate modern human contamination in the steppe samples I diploid genotyped. Then I used a technique introduced by Skoglund, PMDS to correct for contamination (those steppe samples are marked PMDS). This is essentially what Fu et al did with AG3 hence it is annotated as AG3_damage.

    As crazy as it may seem, discarding undamaged segments in aDNA, and retaining damaged ones is pretty much the only option we have for samples where we estimate high modern human contamination. I personally only use it as a last resort because it discards as much as 90+% of the sequences, and IMO introduces a bias, but that is what Fu et al did in almost 1/2 of their published ancient samples (check their supp). The margin of error increases when we do this (AG3), but it also increases due to sequencing errors introduced by things such as low coverage ( mean coverage AG2-only 0.071, AG3- only 0.17, MA1- 1.17. None of these are high enough for me to diploid genotype), and also because 90%+ of the published aDNA is pseudo-haploid (1 wrong allele at every hetrozygous) position. This is why I diploid genotype whenever mean coverage allows me to.


    mtDNA;

    Fu et al used this to estimate modern human contamination in their female samples as well as male sample along with the X chromo technique (males only). They used this to declare a sample contaminated when:

    1- The fraction of fragments matching the reconstructed consensus better than any of 311 worldwide mtDNA sequences used for comparison is <95%. OR
    2- The 95% confident lower bound of the fraction of fragments matching the consensus better than any of 311 worldwide mtDNA sequences is <85%.
    We can use dstats and f3s ONLY to gauge if something is SIGNIFICANTLY off, but not the types of stats you posted. As I mentioned before:
    If you want to use dstats, then it is best to compare members of the same clade (MA1, AG2, AG3) against various genomes to assess basaleness, Russian shift, W European shift, etc. I ran a few for you which you can archive for future use. You may be able to discern patterns although it is still impossible to quantify the amount of modern DNA contamination based on these, but you can certainly pick up oddities. To gauge basalness, I used the imputed Satsurbila, the high coverage (10X) Iran WC1, and Natufian. To assess Russian shift, I used Belarousans, and to assess W European shift I used French.
    and the stats I posted do INDICATE something is off with AG2, which is consistent with the authors estimate of 30-35% contamination by modern human DNA.

    Since the preponderance of the evidence does not indicate human contamination with MA1, that is what I am going with (Renaud's runs using DICE are noteworthy but inconclusive since the program did not converge)

    I suppose if I had all the time in the world, which I don't, I could take MA1 bam file and discard all non-damaged sequences and process only using deaminated bases (which are evidence of aDNA and thus can't be attribute to any modern contamination), and see if the results are somewhat consistent with the published ones, but I see no point at this stage.

    However, IMO AG2 should not be used based on the evidence, and AG3 should only be used in the context of a high margin of error.
    Last edited by Kurd; 11-25-2017 at 08:02 PM.

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    Quote Originally Posted by GailT View Post
    U2a, U2b and U2c are primarily found in the sub-continent and are extremely old and extremely rare in GenBank.

    We need a larger sample size from India, Pakistan, Tibet etc to understand the current frequency and geographic distribution of these groups. It should be possible to identify some of these using HVR results, but I don't know of any studies that have published mtDNA results (either HVR or FMS) for large population studies from these regions. This is a case where I think we could still learn quite a bit by looking at modern populations.
    What about big connection between Hungarian bronze age samples and Some soldier castes in India and South Asia ?



    For example on BR2, Hungary, 3.2ky sample, I am getting following nearness in GEd

    Largest segment = 4.6 cM
    Total of segments > 1 cM = 751.9 cM
    505 matching segments

    Significant other hits in Bronze age samples. Does it indicate Bronze age people in Hungary (supposedly some cultures Maros disappear after 1400BC) moved widespread into India/SouthAsia/CentralAsis during Indo-Aryan or later.
    I get similar match to Stuttgart sample. However I got big SouthIndian component. Does it mean the migration occurred during Neolithic or Chalcolithic times into SouthAsia from Europe? Why people of particular caste distribution get these big nearness to Armenian BronE Age samples , Hungary Bronze age samples, Stuttgart samples and some other Rise samples in Czeck & Russia

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