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Thread: Waves of migration into South Asia

  1. #2161
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    Quote Originally Posted by jesus View Post
    Yusufzais/Pashtuns are recent arrivals to the Swat area. It’s better to use nearby kalash or indo aryan groups for comparison.
    Yes I had read about the Yusufzai migration.
    But the other paper has Yusufzai and others such as Gujars - R1a1 is predominant overall in that dataset too.

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    In the studies I've seen Kalash and Burusho have L1c not L1a, and Pashtuns have more L1c than L1a (I don't know about in private testing).

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    Quote Originally Posted by Megalophias View Post
    In the studies I've seen Kalash and Burusho have L1c not L1a, and Pashtuns have more L1c than L1a (I don't know about in private testing).
    Yes thats consistent with what I've seen

  4. #2164
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    Swat Saidu Sharif on HarappaSharif sample.PNG


    Clusters very close to modern day Kashmiris.
    Population (source) Distance
    1 kashmiri (harappa) 3.75
    2 kashmiri-pandit (reich) 3.78
    3 punjabi-jatt-muslim (harappa) 4.3
    4 punjabi (harappa) 4.76
    5 punjabi-khatri (harappa) 5.36
    6 sindhi (harappa) 5.47
    7 gujarati-muslim (harappa) 5.78
    8 kashmiri-pahari (harappa) 6.41
    9 punjabi-brahmin (harappa) 6.41
    10 singapore-indian-c (sgvp) 6.84
    11 punjabi-arain (xing) 7.05
    12 punjabi-ramgarhia (harappa) 7.5
    13 punjabi-jatt-sikh (harappa) 7.68
    14 up-muslim (harappa) 7.8
    15 pathan (hgdp) 8.68
    16 sindhi (hgdp) 8.74
    17 bhatia (harappa) 9.72
    18 burusho (hgdp) 9.78
    19 kalash (hgdp) 10.58
    Last edited by pegasus; 04-11-2018 at 11:26 PM.

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    Quote Originally Posted by pegasus View Post
    Swat Saidu Sharif on HarappaSharif sample.PNG


    Clusters very close to modern day Kashmiris.
    Population (source) Distance
    1 kashmiri (harappa) 3.75
    2 kashmiri-pandit (reich) 3.78
    3 punjabi-jatt-muslim (harappa) 4.3
    4 punjabi (harappa) 4.76
    5 punjabi-khatri (harappa) 5.36
    6 sindhi (harappa) 5.47
    7 gujarati-muslim (harappa) 5.78
    8 kashmiri-pahari (harappa) 6.41
    9 punjabi-brahmin (harappa) 6.41
    10 singapore-indian-c (sgvp) 6.84
    11 punjabi-arain (xing) 7.05
    12 punjabi-ramgarhia (harappa) 7.5
    13 punjabi-jatt-sikh (harappa) 7.68
    14 up-muslim (harappa) 7.8
    15 pathan (hgdp) 8.68
    16 sindhi (hgdp) 8.74
    17 bhatia (harappa) 9.72
    18 burusho (hgdp) 9.78
    19 kalash (hgdp) 10.58
    Wow within 5 distance of a modern pop

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    So basically SAs were already well mixed by the time of these samples, though not as mixed - look at the oracle distances

    Jiroft looks to be an SA extension with no Euro steppe admixture (NE Euro or Med)

    Shahr-I-Sokhta BA2

    HarappaWorld 4-Ancestors Oracle
    This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
    Questions about results should be sent to him at: [email protected]
    Original concept proposed by Sergey Kozlov.
    Many thanks to Alexandr for helping us get this web version developed.

    23 April 2013 - Oracle reference population percentages revised.

    Admix Results (sorted):

    # Population Percent
    1 Baloch 53.49
    2 S-Indian 30.48
    3 Caucasian 13.40
    4 SW-Asian 1.35


    Finished reading population data. 377 populations found.
    16 components mode.

    --------------------------------

    Least-squares method.

    Using 1 population approximation:
    1 sindhi_hgdp @ 10.631093
    2 punjabi-arain_xing @ 12.523808
    3 bhatia_harappa @ 15.057607
    4 kashmiri-pahari_harappa @ 15.586733
    5 sindhi_harappa @ 16.389328
    6 punjabi-ramgarhia_harappa @ 16.416433
    7 singapore-indian-c_sgvp @ 17.105780
    8 kashmiri-pandit_reich @ 17.195734
    9 punjabi_harappa @ 17.317476
    10 punjabi-brahmin_harappa @ 17.632967
    11 punjabi-jatt-muslim_harappa @ 17.744486
    12 kalash_hgdp @ 18.088846
    13 pathan_hgdp @ 18.291321
    14 gujarati-muslim_harappa @ 18.418484
    15 punjabi-khatri_harappa @ 18.692505
    16 balochi_hgdp @ 18.933041
    17 kashmiri_harappa @ 19.026968
    18 punjabi-jatt-sikh_harappa @ 19.048235
    19 burusho_hgdp @ 19.586412
    20 meena_metspalu @ 19.977560

    Using 2 populations approximation:
    1 50% brahui_hgdp +50% goan_harappa @ 8.730488


    Using 3 populations approximation:
    1 50% brahui_hgdp +25% sindhi_hgdp +25% velama_reich @ 8.583436


    Using 4 populations approximation:
    ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++
    1 brahui_hgdp + brahui_hgdp + sindhi_hgdp + velama_reich @ 8.583436
    2 balochi_hgdp + balochi_hgdp + gujarati-patel_harappa + sindhi_hgdp @ 8.620640
    3 brahui_hgdp + brahui_hgdp + punjabi-arain_xing + velama_reich @ 8.628778
    4 balochi_hgdp + brahui_hgdp + sindhi_hgdp + velama_reich @ 8.637354
    5 balochi_hgdp + brahui_hgdp + gujarati-patel_harappa + sindhi_hgdp @ 8.638119
    6 balochi_hgdp + brahui_hgdp + gujarati-patel_harappa + punjabi-arain_xing @ 8.663149
    7 brahui_hgdp + brahui_hgdp + sindhi_hgdp + velama_metspalu @ 8.699452
    8 balochi_hgdp + balochi_hgdp + gujarati-a_hapmap + sindhi_hgdp @ 8.710600
    9 balochi_hgdp + brahui_hgdp + sindhi_hgdp + velama_metspalu @ 8.718814
    10 brahui_hgdp + brahui_hgdp + punjabi-arain_xing + velama_metspalu @ 8.729499
    11 balochi_hgdp + balochi_hgdp + gujarati-patel_harappa + punjabi-arain_xing @ 8.729913
    12 brahui_hgdp + brahui_hgdp + goan_harappa + goan_harappa @ 8.730488
    13 balochi_hgdp + brahui_hgdp + gujarati-a_hapmap + sindhi_hgdp @ 8.741231
    14 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + punjabi-arain_xing @ 8.752000
    15 balochi_hgdp + brahui_hgdp + gujarati-a_hapmap + punjabi-arain_xing @ 8.759062
    16 balochi_hgdp + brahui_hgdp + punjabi-arain_xing + velama_reich @ 8.769739
    17 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + kashmiri-pahari_harappa @ 8.792599
    18 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + kashmiri-pandit_reich @ 8.802500
    19 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + sindhi_hgdp @ 8.810875
    20 balochi_hgdp + balochi_hgdp + gujarati-a_1000genomes + sindhi_hgdp @ 8.811920
    Last edited by bmoney; 04-12-2018 at 12:56 AM.

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  10. #2167
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    Post the Gonur and the really AASI shifted sample

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    Quote Originally Posted by bmoney View Post
    So basically SAs were already well mixed by the time of these samples, though not as mixed - look at the oracle distances

    Jiroft looks to be an SA extension with no Euro steppe admixture (NE Euro or Med)

    Shahr-I-Sokhta BA2

    HarappaWorld 4-Ancestors Oracle
    This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
    Questions about results should be sent to him at: [email protected]
    Original concept proposed by Sergey Kozlov.
    Many thanks to Alexandr for helping us get this web version developed.

    23 April 2013 - Oracle reference population percentages revised.

    Admix Results (sorted):

    # Population Percent
    1 Baloch 53.49
    2 S-Indian 30.48
    3 Caucasian 13.40
    4 SW-Asian 1.35


    Finished reading population data. 377 populations found.
    16 components mode.

    --------------------------------

    Least-squares method.

    Using 1 population approximation:
    1 sindhi_hgdp @ 10.631093
    2 punjabi-arain_xing @ 12.523808
    3 bhatia_harappa @ 15.057607
    4 kashmiri-pahari_harappa @ 15.586733
    5 sindhi_harappa @ 16.389328
    6 punjabi-ramgarhia_harappa @ 16.416433
    7 singapore-indian-c_sgvp @ 17.105780
    8 kashmiri-pandit_reich @ 17.195734
    9 punjabi_harappa @ 17.317476
    10 punjabi-brahmin_harappa @ 17.632967
    11 punjabi-jatt-muslim_harappa @ 17.744486
    12 kalash_hgdp @ 18.088846
    13 pathan_hgdp @ 18.291321
    14 gujarati-muslim_harappa @ 18.418484
    15 punjabi-khatri_harappa @ 18.692505
    16 balochi_hgdp @ 18.933041
    17 kashmiri_harappa @ 19.026968
    18 punjabi-jatt-sikh_harappa @ 19.048235
    19 burusho_hgdp @ 19.586412
    20 meena_metspalu @ 19.977560

    Using 2 populations approximation:
    1 50% brahui_hgdp +50% goan_harappa @ 8.730488


    Using 3 populations approximation:
    1 50% brahui_hgdp +25% sindhi_hgdp +25% velama_reich @ 8.583436


    Using 4 populations approximation:
    ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++
    1 brahui_hgdp + brahui_hgdp + sindhi_hgdp + velama_reich @ 8.583436
    2 balochi_hgdp + balochi_hgdp + gujarati-patel_harappa + sindhi_hgdp @ 8.620640
    3 brahui_hgdp + brahui_hgdp + punjabi-arain_xing + velama_reich @ 8.628778
    4 balochi_hgdp + brahui_hgdp + sindhi_hgdp + velama_reich @ 8.637354
    5 balochi_hgdp + brahui_hgdp + gujarati-patel_harappa + sindhi_hgdp @ 8.638119
    6 balochi_hgdp + brahui_hgdp + gujarati-patel_harappa + punjabi-arain_xing @ 8.663149
    7 brahui_hgdp + brahui_hgdp + sindhi_hgdp + velama_metspalu @ 8.699452
    8 balochi_hgdp + balochi_hgdp + gujarati-a_hapmap + sindhi_hgdp @ 8.710600
    9 balochi_hgdp + brahui_hgdp + sindhi_hgdp + velama_metspalu @ 8.718814
    10 brahui_hgdp + brahui_hgdp + punjabi-arain_xing + velama_metspalu @ 8.729499
    11 balochi_hgdp + balochi_hgdp + gujarati-patel_harappa + punjabi-arain_xing @ 8.729913
    12 brahui_hgdp + brahui_hgdp + goan_harappa + goan_harappa @ 8.730488
    13 balochi_hgdp + brahui_hgdp + gujarati-a_hapmap + sindhi_hgdp @ 8.741231
    14 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + punjabi-arain_xing @ 8.752000
    15 balochi_hgdp + brahui_hgdp + gujarati-a_hapmap + punjabi-arain_xing @ 8.759062
    16 balochi_hgdp + brahui_hgdp + punjabi-arain_xing + velama_reich @ 8.769739
    17 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + kashmiri-pahari_harappa @ 8.792599
    18 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + kashmiri-pandit_reich @ 8.802500
    19 brahui_hgdp + brahui_hgdp + gujarati-patel_harappa + sindhi_hgdp @ 8.810875
    20 balochi_hgdp + balochi_hgdp + gujarati-a_1000genomes + sindhi_hgdp @ 8.811920
    Shahr e Sokta 2 is very similar to the Memon Khoja sample I noticed minus the minor NE component. Its pretty close considering its a nearly 5Kya genome.

    Kit F207412

    Admix Results (sorted):

    # Population Percent
    1 Baloch 47.15
    2 S-Indian 27.68
    3 Caucasian 13.61
    4 NE-Euro 6.46
    5 NE-Asian 2.46
    6 SW-Asian 0.85
    7 Papuan 0.78
    8 W-African 0.46
    9 Beringian 0.28
    10 American 0.21
    11 Mediterranean 0.03
    12 San 0.02
    Last edited by pegasus; 04-12-2018 at 06:22 AM.

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  14. #2169
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    Quote Originally Posted by pegasus View Post
    This sample is very similar to the Memon Khoja sample I noticed minus the minor NE component. Its pretty close considering its a nearly 5Kya genome.

    Kit F207412

    Admix Results (sorted):

    # Population Percent
    1 Baloch 47.15
    2 S-Indian 27.68
    3 Caucasian 13.61
    4 NE-Euro 6.46
    5 NE-Asian 2.46
    6 SW-Asian 0.85
    7 Papuan 0.78
    8 W-African 0.46
    9 Beringian 0.28
    10 American 0.21
    11 Mediterranean 0.03
    12 San 0.02
    damn son... thats super close, amazed at the genetic continuity in the NW.

    The Memons haha who'd have thunk it

    So most of the ANI ASI mixing probably just happened from Central to South India with the NW remaining relatively static

    So the IVC cultural zone is SE Iran to southern Indus

    How did the Brahui keep such a low AASI profile I wonder

    I've asked for Shahr-e-Sokhta BA3 in gedmatch form, that sample is more AASI shifted
    Last edited by bmoney; 04-12-2018 at 07:17 AM.

  15. #2170
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    Quote Originally Posted by bmoney View Post
    damn son... thats super close, amazed at the cultural continuity in the NW.

    The Memons haha who'd have thunk it

    So most of the ANI ASI mixing probably just happened from Central to South India with the NW remaining relatively static

    So the IVC cultural zone is SE Iran to southern Indus

    How did the Brahui keep such a low AASI profile I wonder

    I've asked for Shahr-e-Sokhta BA3 in gedmatch form, that sample is more AASI shifted
    Yeah it is , I think the other sample will be like some modern day Tamil group . This city had upto 100 000 people at its peak which is huge, and ironic. Ancient Iran's most urban populations were concentrated largely in the Southern regions and today its the complete opposite its the north which has the large urban populations. Also SE Iran/SW Pakistan was more like a grassland in the past but rapid climate changes in the bronze age caused the collapse of Helmand/Jiroft related cities/towns and IVC cities like Harappa at the same time.

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