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Thread: R1a1 in India cuts across language, caste, tribe, and religion

  1. #21
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    A total of 32 Y-chromosomal markers in 560 North Indian males collected from three higher caste groups (Brahmins, Chaturvedis and Bhargavas) and two Muslims groups (Shia and Sunni) were genotyped. Three distinct lineages were revealed based upon 13 haplogroups. The first was a Central Asian lineage harbouring haplogroups R1 and R2. The second lineage was of Middle-Eastern origin represented by haplogroups J2*, Shia-specific E1b1b1, and to some extent G* and L*. The third was the indigenous Indian Y-lineage represented by haplogroups H1*, F*, C* and O*. Haplogroup E1b1b1 was observed in Shias only. The results revealed that a substantial part of today’s North Indian paternal gene pool was contributed by Central Asian lineages who are Indo-European speakers, suggesting that extant Indian caste groups are primarily the descendants of Indo-European migrants. The presence of haplogroup E in Shias, first reported in this study, suggests a genetic distinction between the two Indo Muslim sects. The findings of the present study provide insights into prehistoric and early historic patterns of migration into India and the evolution of Indian populations in recent history.

    Ann Hum Biol. 2009 Jan–Feb; 36(1): 46–59.
    doi: 10.1080/03014460802558522


    India occupies a unique stage in human population evolution because one of the early waves of migration of modern humans was out of Africa, through West Asia, into India (Cann 2001). More recently, about 15 000–10 000 years before present (ybp), when agriculture developed in the Fertile Crescent region that extended from Israel through Northern Syria to Western Iran, there was an eastward wave of human migration (Renfrew 1989; Cavalli-Sforza et al. 1994). It has been postulated that this wave brought the Dravidian language into India (Renfrew 1989). Subsequently, the Indo-European (Aryan) language was introduced into India from the Iranian plateau approximately 4000–3000 ybp, where this language was probably brought by pastoral nomads from the Central Asian steppes (Renfrew 1989). Therefore, linguistic evidence suggests that West Asia and Central Asia were two major geographical sources contributing to the Indian gene pool.
    https://archive.is/KQ4MK#selection-945.0-965.148

    Indian society predominantly revolves around the concept of caste, or the Caste System, a strong socio-cultural conglomerate of traditions that have created and maintained a great number of hierarchically arranged endogamous groups (Bamshad et al. 2001). This unique social system exists only in India. One impact of the system is that a person’s fate, including even the choice of marriage partner, is largely determined at his/her birth. The Hindu caste system plays a major role in social and economic organization of the Indian population. In this system, the society is divided into four broad castes: (from low to high) Sudras, Vaishyas, Kshatriyas and Brahmins. The rules that generally prevent marriages between castes may have contributed to population substructure and the pattern of genetic diversity.

    Another important feature in Indian population history was the occurrence of four separate or distinct waves of migration into the subcontinent (Cordaux et al. 2004): (i) an ancient Palaeolithic migration by modern humans, (ii) an early Neolithic migration, probably via Proto-Dravidian speakers from the eastern horn of the Fertile Crescent, (iii) an influx of Indo-European speakers, and (iv) a migration from East/Southeast Asians, i.e. Tibeto-Burman speakers. In addition to these migrations, India has also experienced colonization by Europeans, which may have also contributed to the ethnic multiplicity. Furthermore, it has been reported (Cordaux et al. 2004) that the Y lineages of Indian castes are more closely related to Central Asians than to Indian tribal populations, suggesting that Indian caste groups are primarily the descendants of Indo-European migrants.
    https://archive.is/KQ4MK#selection-969.0-981.209

    Shia Muslims were distinct from the other populations probably due to the presence of its unique Y-lineage E1b1b1 and the high frequency of haplogroup J2.
    https://archive.is/KQ4MK#selection-1629.186-1629.339

    The supporting evidence of the Middle East or West Asian migrations in Indian Muslims was demonstrated by the presence of 11.0% of haplogroup E1b1b1 in Shia Muslims.

    Our results revealed that Shia Muslims are different from Sunnis and other upper caste populations. Our results revealed that Shia Muslims are different from Sunnis and other upper caste populations. They possess a relatively high frequency of the E1b1b1 haplogroup which was not observed in any other population selected for the present study.
    https://archive.is/KQ4MK#selection-2155.255-2155.501

    Haplogroup R is widely spread in central Asian Turkic-speaking populations and in eastern European Finno-Ugric and Slavic speakers and is less frequent in populations from the Middle East and Sino-Tibetan regions of northern China (Karafet et al. 1999; Underhill et al. 2000). Interestingly, the high frequency of the R1a1★ haplogroup seems to be concentrated around the elevated terrain of central and western Asia. Although haplogroup R1a in Central Asians depicted a low genetic diversity estimate, many researchers (Kivisild et al. 2003; Zerjal et al. 2003) have suggested a recent founder effect or drift that led to the high frequency of R1a in the Southeastern Central Asia. It has also been suggested that R1a might have an independent origin in the Indian subcontinent (Kivisild et al. 2003).

    The high level of L1-M76 chromosomes in Vokkaligas suggests an agricultural expansion in the region, while the predominance of R1a1a1b2-Z93 and J2a-M410 lineages in Lingayat indicates gene flow from neighboring south Indian populations and West Asia, respectively.
    https://www.theapricity.com/forum/sh...=1#post7388636

    Migratory routes of paternal lineages of Indian upper caste and Muslim populations: https://archive.is/lgeF1/ec13f60ee8a...b33db5e7f7.jpg

    ec13f60ee8a3168f0aa48d60b9c2a2b33db5e7f7.jpg

    Global distribution of Y haplogroups: https://www.sciencedirect.com/topics...ogy/haplogroup

    The members of R1b are believed to be the descendants of the first modern humans who entered Europe, and is now the most common Y haplogroup in Europe. More than half of men of European descent belong to R1b. Haplogroup R1a is currently found in central and western Asia, India, and in Slavic populations of Eastern Europe.

    https://archive.is/SJ7mK#selection-667.2-667.325
    Last edited by VikLevaPatel; 12-26-2021 at 09:47 PM.
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  2. #22
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    Quote Originally Posted by NSXD60 View Post
    In other words: We was Kurgs 'n shit. (Just kidding, it was too easy to pass up.)
    Seems that way. Along with a long list of other indigenous and foreign ethnic groups.

    We wuz Aryanz, Shudras, Ungabunga, Scythians
    https://archive.is/LxQvg#selection-2341.0-2341.44
    https://defenceforumindia.com/thread...6#post-2089362

    You Can't Make This Sh*t Up:

    "India is known for its vast human diversity, consisting of more than four and a half thousand anthropologically well-defined populations. Each population differs in terms of language, culture, physical features and, most importantly, genetic architecture. The size of populations varies from a few hundred to millions. Based on the social structure, Indians are classified into various caste, tribe and religious groups. These social classifications are very rigid and have remained undisturbed by emerging urbanisation and cultural changes. The variable social customs, strict endogamy marriage practices, long-term isolation and evolutionary forces have added immensely to the diversification of the Indian populations. These factors have also led to these populations acquiring a set of Indian-specific genetic variations responsible for various diseases in India."

    Rakesh Tamang & Kumarasamy Thangaraj
    Investigative Genetics volume 3, Article number: 20 (2012)
    https://archive.md/LEWA3#selection-799.0-799.542
    Last edited by VikLevaPatel; 12-26-2021 at 08:47 PM.
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  3. #23
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    Quote Originally Posted by VikLevaPatel View Post
    Haplogroup E1b1b1 was observed in Shias only. The presence of haplogroup E in Shias, first reported in this study, suggests a genetic distinction between the two Indo Muslim sects.
    This is nonsense muslims are a single group of genes.

    The classification is wrong.
    https://defenceforumindia.com/thread...4#post-2105604

    I'm pretty sure Gujarati Muslims are different from other Muslims.

    And let's also not forget that the Lohana have provided the recruiting base for the Muslims.

    Gujaratis form a distinct cluster. 100% bootstrap support for a Gujarati grouping: https://anthrogenica.com/showthread....arati-grouping

    I personally know Azim Premji's daughter-in-law's family. We're family friends. She is a Mehta/Patel and her mother is a Lewa Patel like me.

    https://defenceforumindia.com/thread...5#post-2112583
    https://defenceforumindia.com/thread...5#post-2112586
    Last edited by VikLevaPatel; 12-29-2021 at 06:41 AM.
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  4. #24
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    A genetic chronology for the Indian Subcontinent points to heavily sex-biased dispersals

    Background: India is a patchwork of tribal and non-tribal populations that speak many different languages from various language families. Indo-European, spoken across northern and central India, and also in Pakistan and Bangladesh, has been frequently connected to the so-called "Indo-Aryan invasions" from Central Asia ~3.5 ka and the establishment of the caste system, but the extent of immigration at this time remains extremely controversial. South India, on the other hand, is dominated by Dravidian languages. India displays a high level of endogamy due to its strict social boundaries, and high genetic drift as a result of long-term isolation which, together with a very complex history, makes the genetic study of Indian populations challenging.

    Results: We have combined a detailed, high-resolution mitogenome analysis with summaries of autosomal data and Y-chromosome lineages to establish a settlement chronology for the Indian Subcontinent. Maternal lineages document the earliest settlement ~55-65 ka (thousand years ago), and major population shifts in the later Pleistocene that explain previous dating discrepancies and neutrality violation. Whilst current genome-wide analyses conflate all dispersals from Southwest and Central Asia, we were able to tease out from the mitogenome data distinct dispersal episodes dating from between the Last Glacial Maximum to the Bronze Age. Moreover, we found an extremely marked sex bias by comparing the different genetic systems. Conclusions: Maternal lineages primarily reflect earlier, pre-Holocene processes, and paternal lineages predominantly episodes within the last 10 ka. In particular, genetic influx from Central Asia in the Bronze Age was strongly male-driven, consistent with the patriarchal, patrilocal and patrilineal social structure attributed to the inferred pastoralist early Indo-European society. This was part of a much wider process of Indo-European expansion, with an ultimate source in the Pontic-Caspian region, which carried closely related Y-chromosome lineages, a smaller fraction of autosomal genome-wide variation and an even smaller fraction of mitogenomes across a vast swathe of Eurasia between 5 and 3.5 ka.

    We see no evidence that the caste system emerged in the wake of the arrival of Indo-Aryan speakers from the north, in agreement with formal admixture analyses. Higher-ranking castes do seem closer genetically to Pakistan and ultimately Caucasus and Central Asian populations, but this proximity was most likely established overmillennia, by several distinct migratory events—indeed, a sizeable fraction of the non-R1a West Eurasian Y-chromosome lineages (e.g. R2a-M124, J2-M241, L1a-M27, L1c-M357) were most likely associated with the spread ofagriculture or even earlier expansions from Southwest Asia, as with the mtDNA lineages.

    December 2017BMC Evolutionary Biology 17(1)
    DOI:10.1186/s12862-017-0936-9

    a ADMIXTURE analysis for K = 7. b PCA of South Asian populations. Detailed information on the populations included in the Additional file 1: Table S3. Note that the three typical European components are not detected here in the Tuscans, probably due to the small overall European representation in the analysis

    https://archive.is/eenoz/0ad84ec1988...b7eaba8cb9.png

    Integrating Linguistics, Social Structure, and Geography to Model Genetic Diversity within India

    India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification. While geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure using a ridge leverage score statistic. Integrating data from India with a dataset of additional 1,323 individuals from 50 Eurasian populations we find that Indo-European and Dravidian speakers of India show shared genetic drift with Europeans, whereas the Tibeto-Burman speaking tribal groups have maximum shared genetic drift with East Asians.

    Shared genetic drift between 33 Indian populations (denoted by X) and 50 Eurasian/East Asian populations (denoted by Y) as estimated by f 3 statistics with Yoruba as an outgroup f 3 (YRI;X,Y). The darkest colors correspond to greatest portions of shared genetic drift with Indian populations.

    https://www.researchgate.net/profile...asian-East.ppm

    A map of locations of the 33 populations in the normalized set and the results of principal component analysis. A. Map of India showing the locations of the 368 individuals in the normalized subset across 33 well-defined populations, 47,283 SNPs (see Supplementary Figure S1A for the pan-Indian dataset of 90 ethnic groups and Supplementary Figure S2 for the corresponding PCA plot). The populations are colored by their sociolinguistic group. B. Top two PCs of the normalized dataset show clustering by language groups. C. PCA plot colored and marked by sociolinguistic groups shows the genetic structure stratified by sociolinguistic groups.

    https://archive.is/1nWIN/b3c5b0e7620...91285eb9a5.png

    January 2021Molecular Biology and Evolution
    DOI:10.1093/molbev/msaa321
    Last edited by VikLevaPatel; 02-08-2022 at 09:13 PM.
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  5. #25
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    It is clear that there is a very strong sex bias in the ancestry of South Asians. The female line of descent is mostly autochthonous and traces back to the first settlement ~55 ka. However, the male line of descent emphasizes more recent ancestry, since the LGM, from Southwest Asia and Central Asia.

    A markedly higher proportion of male lineages of likely West Eurasian origin, of ~50-90%, is evident across the Subcontinent, in comparison with both the maternal line and the GW pattern. The last four millennia witnessed major cultural changes in the Indian Subcontinent, with the decline of the Indus Valley civilisation and the rise of Vedic religion, based on a strict caste system, often associated with the arrival of Indo-Aryan speakers. The mix of autochthonous and immigrant genetic lineages seen across South Asia, however, suggests a gradual merging of male-dominated Andronovo/BMAC immigrants with the indigenous descendants of the Indus Valley civilisation, possibly associated with the spread of the Megalithic cultureas far south as Sri Lanka in the first century Before Common Era (BCE), prior to the establishment of the full jāti caste system very roughly ~2 ka. Basu et al. date the “freezing”of India’s population structure to ~1.5 ka.

    Prehistoric West Eurasian lineages make up almost 20% of the South Asian genetic pool overall. The main non-autochthonous component in the Subcontinent, the Iran/Caucasus/Steppe component, exceeds 35% in Pakistan and Gujarat, although it reaches most of the Subcontinent. Although South Asia displays a very high level of indigenous variation, the region subsequently received substantial genetic input from both west and east, dramatically re-shaping its genetic structure. South Asian populations are closer to the Caucasus and Central Asian groups rather than to other West Eurasian populations. Pakistanis and Gujaratis in particular carry a preponderance of the “Ancestral North Indian”(ANI) gene pool, contrasting with the ASI or autochthonous population of the Subcontinent.

    https://www.researchgate.net/publica...sed_dispersals
    https://www.researchgate.net/figure/...fig1_315596347
    https://www.researchgate.net/figure/...fig3_315596347
    https://www.nature.com/articles/s41598-020-66953-3
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  6. #26
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    Gujarāti (Leva) Pātidār. Caste (Jāt): Leva/Lewa Patel of Central Gujarat
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    Iran_N, IVC-IRN, ANE-NEA, EEF, Yamnaya, Afanasevo, Bell Beaker, Corded Ware, Sintashta,, Andronovo
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    Great Britain
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    Indian Ocean
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    R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896
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    W6 (Gotland/Sweden)
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    CHG/Iran, EHG-Steppe, EEF/ENF, Indo-Caucasoid, Mesocephalic (Gujarati)
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    Cleansing of Earth; Desolation of Abomination; Millennial Reign; Preparing a People for Millennium
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    Default

    Steppe pastoralists were the source of Indo-European languages in South Asia

    This Steppe hypothesis has also been recently supported by Shinde et al., who have shown that there is negligible ancestry from Anatolian farmers in the ancient South Asian farmers represented in the Indus Valley Civilization.

    Scientific Reports volume 10, Article number: 10075 (2020)

    We show that tribal groups have had much smaller effective population sizes than castes, and that genetic drift has had a higher impact in tribal populations. We also show clear affinities between the Bhil and Pawara tribes, and to a lesser extent, between the Warli and Kokana tribes. Our comparisons with available modern and ancient DNA datasets from South Asia indicate that the Brahmin caste has higher Ancient Iranian and Steppe pastoralist contributions than the Kunbi Marathas caste. Additionally, in contrast to the two castes, tribal groups have very high Ancient Ancestral South Indian (AASI) contributions. Indo-European tribal groups tend to have higher Steppe contributions than Dravidian tribal groups, providing further support for the hypothesis that Steppe pastoralists were the source of Indo-European languages in South Asia, as well as Europe.

    Tribal populations are considered to be the indigenous populations of India and constitute approximately 8.63% of the total population. The non-tribal populations consist of religious communities outside the caste system, and hierarchically arranged, endogamous social groups known as castes. This fundamental division of the Indian population into castes, tribes and religious groups has resulted in a large number of effective populations or endogamous groups.

    Although both Indo-European and Dravidian tribal groups have very high AASI contributions, Indo-European tribal groups tend to have higher Steppe contributions than Dravidian tribal groups. This provides indirect support for a model that explains the spread of the Indo-European languages as a result of the migration of the Steppe pastoralists to Europe and South Asia, in contrast to the alternative model that supports the spread of Indo-European languages as a consequence of the migration of Anatolian farmers.

    Overall, our results are in agreement with recent ancient DNA studies providing support for Steppe pastoralists as a source of Indo-European languages in Europe and South Asia. Comparisons of mtDNA, Y-chromosome and autosomal data indicate that this migration was primarily male-driven. Our comparisons with available genomic data from modern and ancient samples from South Asia indicate higher Ancient Iranian and Steppe pastoralist contributions in the WM Brahmin caste than in the WM Kunbi Marathas caste. In contrast to the two castes, WM tribal groups have very high AASI contributions. Although both Indo-European and Dravidian tribal groups from India have very high AASI contributions, Indo-European tribal groups tend to have higher Steppe contributions than Dravidian tribal groups, providing further support for the hypothesis that Steppe pastoralists were the source of Indo-European languages in South Asia.

    Debortoli, G., Abbatangelo, C., Ceballos, F. et al. Novel insights on demographic history of tribal and caste groups from West Maharashtra (India) using genome-wide data. Sci Rep 10, 10075 (2020). https://doi.org/10.1038/s41598-020-66953-3

    Proto-Caucasoid ancestry (also known as AASI): 1632865746121.png

    Ancient ancestral south indians (AASI) came from the east, not straight from Africa!
    ASI (Ancient ancestral South Indians) is a hypothetical ancient indian population which hasnt been sampled yet. AASI have the andamanese tribals as their genetically closest sampled population (but still distant due to isolation and genetic drift). AASI almost definitely also arrived in Indian subcontinent from this eastern route after the OoA event. This qpgraph generated by me makes it clear.
    The Deep Origins Of East Eurasians
    We know that the humans were in Australia by 40-45,000 years ago, at the latest. This establishes a timeline for the point of divergence of all these lineages. Though Andamanese are used as proxies for AASIs in population genetic analyses, it turns out they are very distantly related to them. All of these dark-skinned people across southern Eurasia and into Oceania are more related to each other than they are to East Asians, but only very distantly and marginally.
    Proportions of Ancient Ancestry in South Asian Populations qpAdm plot indicating proportions of ancestry made up of ancient sources (Iran_N, Steppe_MLBA, and Onge) among different South Asian populations.

    c56eba0815b7e1c2.png

    https://archive.is/p5HJF/c56eba0815b...84619654f1.png

    Mapping the Single Largest Ancestral Component in South Asian populations. i.e Indo-European "Steppe" is a minority component everywhere in Southern Asia.

    https://i.ibb.co/NS85v1L/79gj6g627dr61.jpg

    https://i.ibb.co/ZTmTmmz/vhupcz50a7r61.png

    Attachment 112566

    Fiffty Fiffty: https://archive.is/f3sEe/349516a75fd...e32cf4a92d.jpg

    Genetic signals of Indo-European expansions
    Contrary to earlier studies, recent analyses ofY-chromosome sequence data suggest thathaplogroup R1a expanded both west and east across Eurasia during the Late Neolithic/Bronze Age. R1a-M17(R1a-M198 or R1a1a) accounts for 17.5% of male line-ages in Indian data overall, and it displays significantlyhigher frequencies in Indo-European than in Dravidian speakers. There are now sufficient high-quality Y-chromosomedata available (especially Poznik et al.) to be able todraw clear conclusions about the timing and direction ofdispersal of R1a. The indigenous South Asian subclades are too young to signal Early Neolithicdispersals from Iran, and strongly support Bronze Age incursions from Central Asia. The derived R1a-Z93 and the further derived R1a-Z94 subclades harbour the bulk of Central and South Asian R1a lineages, as well as including some Russian and European lineages, and have been variously dated to 5.6 [4.0;7.3] ka, 4.5–5.3 ka with expansions ~4.0–4.5 ka, or 4.7 [4.0;5.5] ka (Yfull tree v4.10). The South Asian R1a-L657, dated to ~4.2 ka [3.3;5.1] (Yfull tree v4.10]), is the largest (in the 1KG dataset) of several closely related subclades within R1a-Z94 of very similar time depth. Moreover, notonly has R1a been found in all Sintashta and Sintashta-derived Andronovo and Srubnaya remains analysed todate at the genome-wide level (nine in total), andbeen previously identified in a majority of Andronovo (2/3) and post-Andronovo Iron Age (Tagar and Tachtyk:6/6) male samples from southern central Siberia testedusing microsatellite analysis, it has also been identi-fied in other remains across Europe and Central Asia ran-ging from the Mesolithic up until the Iron Age.
    Migration and Mixing. The mixture between a smaller, dominant steppe population, and a larger farmer population created the ANI genetic population that became dominant in northwest India after 1,500 BCE. Meanwhile, the ASI genetic population, a mixture of farmers and aborigines, was prevalent throughout most of the rest of India. The high fraction of ANI among South Indian tribal groups who are isolated from even Dravidian caste groups is a clue to the likelihood that the admixture event is very ancient, and probably precedes the arrival of the Aryans to the Indian subcontinent. India’s genetic diversity can be best described by a model of mixture between two statistically reconstructed ancestral populations: The Ancestral Northern Indians (ANI), which are related genetically to West Eurasians, including Middle Easterners, Central Asians and Europeans, and Ancestral South Indians (ASI), which are distantly related to Indigenous Andaman Islanders4. ANI ancestry is proportionally higher among Indo-European speakers and is also more prevalent in upper castes than in lower or middle castes4. Furthermore, the ANI component has a discernable geographic pattern in South Asia decreasing from the northwest. This gradient relating the ANI with the ASI is known as the “Indian Cline”.

    Recent studies incorporating genomic data from both ancient DNA (aDNA) and present-day South Asians have modeled the formation of the Indian Cline as a combination of three source populations: (1) the Ancient Ancestral South Indians (AASI), which represent a hypothesized South Asian Hunter-Gatherer lineage arising from a population split contemporaneous with the split of East Asian, Onge and Australian Aboriginal Ancestors; (2) Ancient Iranians and (3) Middle and Late Bronze Age Steppe populations (Steppe-MLBA)5,6,7. These studies suggest that a distinctive genetic mixture of ancient Iranians and AASI could have formed the genetic basis of the Indus Valley Civilization (IVC), thus this mixture was denoted the “Indus Periphery”. It has been hypothesized that the Indus Periphery played a pivotal role in the transformation of the three source populations into the two ancestral populations, ANI and ASI, which shape the current Indian Cline5,6. During the decline of the IVC, a portion of the Indus Periphery population admixed with the AASI to form the ASI in the Southern regions of India, whereas subsequent interaction between Indus Periphery and incoming Steppe-MLBA populations in the Northern regions resulted in the formation of the ANI5,6. Notably, following this period of admixture (4200-1900 years ago), Indian populations appear to have exhibited a shift toward endogamy, thereafter reducing gene flow8. In this context, a range of historic migrations and long-standing socio-cultural divisions have structured India’s genetic variation into a unique pattern of different endogamous groups.
    https://archive.is/w7ltr#selection-1137.0-1177.188

    Y-DNA genetic evidence reveals several different ancient origins in the Brahmin population

    The ancient geographical origins of Brahmins-a prominent ethnic group in the Indian subcontinent-have remained controversial for a long time. This study employed the AMOVA (analysis of molecular variance) test to evaluate genetic affinities of this group with thirty populations of Central Asia and Europe. The results showed that Brahmins had genetic affinities with several foreign populations and also shared their genetic heritage with several domestic non-Brahmin groups. The study concluded that about 83% of the Brahmins in the dataset belonged to four major haplogroups, of which two emerged from Central Asia, one from the Fertile Crescent, and one was of an indigenous Indian origin.

    January 2021Molecular Genetics and Genomics 296(2)
    DOI:10.1007/s00438-020-01725-2

    Distance to Uttar Pradesh Brahmin: 1624311677426.png
    Distance to Paniya: 1617979360994.png

    ADMIXTURE MATTERS:
    https://archive.is/ZFDhj/bad42de6da2...7d02159060.jpg
    https://i.ibb.co/P5ZDvVz/1561106262552.jpg

    Genes:
    1606135827726.png
    1606219888455.png
    https://i.ibb.co/X3rQbsY/1606135827726.png
    https://i.ibb.co/w4Pk0WC/1606219888455.png
    https://i.ibb.co/x8bw5zQ/1559702761438-1.jpg
    https://archive.is/wFtfz/65531cb0d58...0525521cd9.png
    https://archive.is/9qnVg/9ca481ddd4d...71c36338da.png

    medPCA: https://archive.is/18YMl/fda342eb59b...b114bed3a7.png
    med gene distance: https://i.ibb.co/LS6zkZQ/1558141561705.png
    pcas: https://archive.is/WK4Ui/095b6c227da...b8626ac0fe.jpg

    European Vs Indian Chart:
    EuropeanVsIndianChart.jpg
    https://i.ibb.co/jgC6p2R/1560602143030.jpg
    https://archive.is/OSK9P/4b5bb8fe9bd...5a09fa4fc6.jpg

    All Indo-Iranian languages originated from a common ancestor, the reconstructed Proto-Indo-Iranian language that was spoken around the end of the 3rd millennium BC. The speakers of this proto-language, Proto-Indo-Iranians, are commonly identified with the Sintashta archaeological culture and its successor, the (early) Andronovo culture, located in the vast area between the Southern Ural and the Tian Shan mountains and dated back from the end of the 3rd millennium BC to the 1st half of the 2nd millennium BC. The ANI and ASI gene pools arose subsequently around the 2nd millennium BCE, concurrent with the decline of the Indus Valley civilization (IVC) that propelled a massive upheaval in human settlements across northern parts of the Indian subcontinent. The southward dispersal of Steppe_MLBA (later Middle to late Bronze Age Steppe) populations occurred around this time into South Asia; it is envisioned that the Indus_Periphery related groups admixed with the Steppe_MLBA immigrants to form the ANI, while additional Indus_ Periphery people migrated further south and eastward within peninsular India to mingle with AASI and formed the ASI. The distinctive population structure of the Indian subcontinent is a unique amalgamation resulting from the extensive and intricate percolation of people across it for long periods together with the rigorous enforcement of sociocultural practices, such as endogamy in many groups.

    The ancestry of South Asian 1KGP populations according to different molecular markers: https://www.researchgate.net/figure/...fig3_315596347

    Complete mitogenomes document substantial genetic contribution from the Eurasian Steppe into northern Pakistani Indo-Iranian speakers

    To elucidate whether Bronze Age population dispersals from the Eurasian Steppe to South Asia contributed to the gene pool of Indo-Iranian-speaking groups, we analyzed 19,568 mitochondrial DNA (mtDNA) sequences from northern Pakistani and surrounding populations, including 213 newly generated mitochondrial genomes (mitogenomes) from Iranian and Dardic groups, both speakers from the ancient Indo-Iranian branch in northern Pakistan. Our results showed that 23% of mtDNA lineages with west Eurasian origin arose in situ in northern Pakistan since ~5000 years ago (kya), a time depth very close to the documented Indo-European dispersals into South Asia during the Bronze Age. Together with ancient mitogenomes from western Eurasia since the Neolithic, we identified five haplogroups (~8.4% of maternal gene pool) with roots in the Steppe region and subbranches arising (age ~5-2 kya old) in northern Pakistan as genetic legacies of Indo-Iranian speakers. Some of these haplogroups, such as W3a1b that have been found in the ancient samples from the late Bronze Age to the Iron Age period individuals of Swat Valley northern Pakistan, even have sub-lineages (age ~4 kya old) in the southern subcontinent, consistent with the southward spread of Indo-Iranian languages. By showing that substantial genetic components of Indo-Iranian speakers in northern Pakistan can be traced to Bronze Age in the Steppe region, our study suggests a demographic link with the spread of Indo-Iranian languages, and further highlights the corridor role of northern Pakistan in the southward dispersal of Indo-Iranian-speaking groups.
    February 2021 European Journal of Human Genetics 29(6)
    DOI:10.1038/s41431-021-00829-6
    Last edited by VikLevaPatel; 02-09-2022 at 02:45 AM.
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  7. #27
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    VikLevaPatel's Avatar
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    Gujarāti (Leva) Pātidār. Caste (Jāt): Leva/Lewa Patel of Central Gujarat
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    Iran_N, IVC-IRN, ANE-NEA, EEF, Yamnaya, Afanasevo, Bell Beaker, Corded Ware, Sintashta,, Andronovo
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    Great Britain
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    Indian Ocean
    Y-DNA
    R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896
    mtDNA
    W6 (Gotland/Sweden)
    Taxonomy
    CHG/Iran, EHG-Steppe, EEF/ENF, Indo-Caucasoid, Mesocephalic (Gujarati)
    Politics
    Cleansing of Earth; Desolation of Abomination; Millennial Reign; Preparing a People for Millennium
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    Graha (Grasper and Possessor); Auspicious Messiah (Son of God), "the Destroyer"; India's Bismarck
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    Great Grasper and Possessor (mahāgraha), "I AM" (yāh), Descent/Incarnation (Avatāra)
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    Exclamation Yamnaya R1b

    Proto-Indo-Europeans expanded under R1b bottlenecks. And the so-called “Steppe ancestry” refers to two different components, one Yamnaya or Steppe_EMBA ancestry, and the other one Corded Ware or Steppe_MLBA ancestry.

    Carlos Quiles contends that the expansion of Indo-European languages from the steppe was linked to the expansion of R1b1a1b-M269 lineages in Eurasia. In particular, genetic data recovered from ancient individuals seemed to support that the expansion of R1b1a1b1-L23 lineages in Europe was associated with Yamna migrants, and thus also subsequently with the expansion of East Bell Beakers as North-West Indo-European-speakers in Europe.

    Yamnaya men had almost exclusively R1b Y-haplogroups, and pre-Yamnaya Eneolithic Volga–Caspian–Caucasus steppe men were principally R1b, with a significant Q1a minority.

    Bell Beakers and Mycenaeans from Yamnaya; Corded Ware from the forest steppe
    Arrival of Beaker folk changed Britain for ever, ancient DNA ...
    Central European prehistory was highly dynamic - ScienceDaily
    The genetic and cultural impact of the Steppe migration into Europe
    The Beaker Phenomenon and the Genomic Transformation of Northwest Europe
    Of horses, camels and extinct lineages
    Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genome
    Ancient Genomes Reveal Yamnaya-Related Ancestry and a Potential Source of Indo-European Speakers in Iron Age Tianshan
    The Beaker people: a new population for ancient Britain
    Dynamic changes in genomic and social structures in third millennium BCE central Europe

    Ancient DNA shows that the culture that brought Bronze Age technology to Britain was connected to a migration that almost completely replaced the island's earlier inhabitants.

    Bell Beakers were at the origin of the North-West Indo-European expansion in Europe. Yamnaya ancestry proper evolved into Afanasievo, Bell Beakers and Balkan peoples. The most relevant quest right now for Indo-European studies is to ascertain the chain of admixture events that led to the development and expansion of Indo-Uralic and its offshoots, Indo-European and Uralic.

    yamnaya r1b: https://www.google.com/search?q=yamn...=gws-wiz-books
    ‘R1a-Z93’: https://archive.4plebs.org/pol/search/text/%20R1a-Z93/
    ‘yamnaya r1b’: https://archive.4plebs.org/pol/searc...yamnaya%20r1b/

    Story of most murderous people of all time revealed in ancient DNA

    Starting 5000 years ago, the Yamnaya embarked on a violent conquest of Europe. Now genetic analysis tells their tale for the first time.

    Between 5000 and 4000 years ago, the Yamnaya and their descendants colonised swathes of Europe, leaving a genetic legacy that persists to this day. Their arrival coincided with profound social and cultural changes. Burial practices shifted dramatically, a warrior class appeared, and there seems to have been a sharp upsurge in lethal violence. Irish Bronze Age haplotypic similarity is strongest within modern Irish, Scottish, and Welsh populations, and several important genetic variants that today show maximal or very high frequencies in Ireland appear at this horizon. These include those coding for lactase persistence, blue eye color, Y chromosome R1b haplotypes, and the hemochromatosis C282Y allele.
    Last edited by VikLevaPatel; 03-25-2022 at 12:18 AM.
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  8. #28
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
    "Friend of Apricity"

    VikLevaPatel's Avatar
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    Ethnicity
    Gujarāti (Leva) Pātidār. Caste (Jāt): Leva/Lewa Patel of Central Gujarat
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    Iran_N, IVC-IRN, ANE-NEA, EEF, Yamnaya, Afanasevo, Bell Beaker, Corded Ware, Sintashta,, Andronovo
    Country
    Great Britain
    Region
    Indian Ocean
    Y-DNA
    R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896
    mtDNA
    W6 (Gotland/Sweden)
    Taxonomy
    CHG/Iran, EHG-Steppe, EEF/ENF, Indo-Caucasoid, Mesocephalic (Gujarati)
    Politics
    Cleansing of Earth; Desolation of Abomination; Millennial Reign; Preparing a People for Millennium
    Hero
    Graha (Grasper and Possessor); Auspicious Messiah (Son of God), "the Destroyer"; India's Bismarck
    Religion
    Great Grasper and Possessor (mahāgraha), "I AM" (yāh), Descent/Incarnation (Avatāra)
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    Exclamation Monoamin Oxidase A (Warrior-Gene)

    Quote Originally Posted by VikLevaPatel View Post
    Proto-Indo-Europeans expanded under R1b bottlenecks.

    Story of most murderous people of all time revealed in ancient DNA

    Starting 5000 years ago, the Yamnaya embarked on a violent conquest of Europe. Now genetic analysis tells their tale for the first time.

    Between 5000 and 4000 years ago, the Yamnaya and their descendants colonised swathes of Europe, leaving a genetic legacy that persists to this day. Their arrival coincided with profound social and cultural changes. Burial practices shifted dramatically, a warrior class appeared, and there seems to have been a sharp upsurge in lethal violence. Irish Bronze Age haplotypic similarity is strongest within modern Irish, Scottish, and Welsh populations, and several important genetic variants that today show maximal or very high frequencies in Ireland appear at this horizon. These include those coding for lactase persistence, blue eye color, Y chromosome R1b haplotypes, and the hemochromatosis C282Y allele.
    iGENEA Results Monoamin Oxidase A (Warrior-Gene)

    https://www.theapricity.com/forum/sh...=1#post7469670
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


  9. #29
    "A Genetically Superior Caste." Prof. Gidwani, UMN Apricity Funding Member
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    Ethnicity
    Gujarāti (Leva) Pātidār. Caste (Jāt): Leva/Lewa Patel of Central Gujarat
    Ancestry
    Iran_N, IVC-IRN, ANE-NEA, EEF, Yamnaya, Afanasevo, Bell Beaker, Corded Ware, Sintashta,, Andronovo
    Country
    Great Britain
    Region
    Indian Ocean
    Y-DNA
    R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896
    mtDNA
    W6 (Gotland/Sweden)
    Taxonomy
    CHG/Iran, EHG-Steppe, EEF/ENF, Indo-Caucasoid, Mesocephalic (Gujarati)
    Politics
    Cleansing of Earth; Desolation of Abomination; Millennial Reign; Preparing a People for Millennium
    Hero
    Graha (Grasper and Possessor); Auspicious Messiah (Son of God), "the Destroyer"; India's Bismarck
    Religion
    Great Grasper and Possessor (mahāgraha), "I AM" (yāh), Descent/Incarnation (Avatāra)
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    Lightbulb Bias, A Zillion-Fold Everywhere. All things are relative. And the 0.1% difference.

    Seems like a lot of things are cutting across me lately.



    It really makes you feel like a "SACK OF SHIT" and a "shit breather" again. Fuckin' 'Dancing Shit Crap Stool Poop.

    For one thing, those applications, which grow on platforms radically biased by their coverage and their context and densely patterned by biases and sensitivities looking so skewed and crooked they're practically screaming "bias"!

    Everything is based on color, and everything is colored by bias.

    Realize, too, as pointed out here, that each person's perception of reality is colored by bias and does not actually correspond to reality.

    See this example: https://www.theapricity.com/forum/sh...77#post7556377



    I can also rack up big scores pretty easily, and rack it up faster than to quote Omar Suarez: "a rabbit gets f**ked!"

    Every application assembles its components differently, so make sure you're making accurate comparisons when browsing. But all these comparisons can be hindered when different grouping approaches are used in different admixes. Different approaches work differently, so be sure that you are comparing apples to apples. In this case that means comparing the major or principal component or components of "your ancestry". And that also means using the right benchmark as a basis of comparison. Your benchmark is your principal ancestral component, and all analyses should be controlled for principal components (of genetic ancestry). The examples below are sufficient enough to make my point.

    Ganj Dareh N 58-63
    Sintashta MLBA 37-42


    And I can certainly get it (Sintashta) up to 45 -- and maybe even more. If I really wanted to. But it would be entirely incorrect and seriously misleading to attempt to claim that. It is dangerous, not to mention naive, to even think that. And it certainly is impossible for me to even think that. Just how fucking stupid are these Indians or South Asians (no offence) to even think that might be a possibility!

    And we are already seeing how bad things can get. And if there's any doubt about that, it's dispelled. See for yourself how bad things can get here: https://www.theapricity.com/forum/sh...77#post7556377



    https://i.ibb.co/S6xw7cp/sint1.png, https://i.ibb.co/w4Hr5Fj/sint2.png, https://i.ibb.co/wcQk59f/pca.png, https://i.ibb.co/y4wfhGL/pca2.png, https://i.ibb.co/QJgksV1/sint3.png, https://i.ibb.co/NKPWJ6x/oracle1.png, https://i.ibb.co/ncQb9WX/oracle2.png, https://i.ibb.co/sjTTsZQ/mlba.png, https://i.ibb.co/nPzkGsY/mlba2.png

    Corded Ware: https://i.ibb.co/pLfDhmL/corded.png, https://i.ibb.co/5jrhffg/oracles.png, https://i.ibb.co/cLj5mKP/average.png, https://i.ibb.co/hf9YGgK/average2.png

    Ganj Dareh N 71-75
    Corded Ware 14-29


    Yamnaya: https://i.ibb.co/RyHf7NW/yamna.png, https://i.ibb.co/jy6y0tf/yamna2.png, https://i.ibb.co/vZWvmc2/y1.png, https://i.ibb.co/kQrSb0c/y2.png, https://i.ibb.co/56907fJ/zach.png

    Ganj Dareh N (Average) 71
    Yamnaya RUS Samara (Median) 23


    Here's a three way comparison of the three components, namely Indus P, Shahr-i Sokhta, and Gujarati:

    And we have to recognize that one component might take precedence over another.

    The presence of one component might for example suppress the response to the other (suppression or hypoadditivity) or enhance it (synergism). Tinkering with one component might get you somewhat better results, but there's going to be a limit to the improvement. And who doesn't love a good quote? And, boy, don't we just LOVE this quote from The New York Times: "You can't just put a Ferrari engine in a Mini Cooper and expect it to act like a Ferrari."

    Indus P (Iran): https://i.ibb.co/qpsbVM2/indus.png, https://i.ibb.co/qd05Vsz/indusp.png, https://i.ibb.co/KbDVnDQ/indusp2.png

    Shahr-i Sokhta (Iran): https://i.ibb.co/fvPwRbQ/shahr.png, https://i.ibb.co/0fTXYwR/shahr2.png, https://i.ibb.co/wwWXzy9/oracles2.png

    sample: Shahr_I_Sokhta_BA3 • Average
    distance: 4.95

    sample: Indus_P • Average
    distance: 6.57

    sample: Shahr_I_Sokhta_BA2 • Average
    distance: 7.86

    sample: Shahr_I_Sokhta_BA1 • Average
    distance: 21.93

    sample: Ganj_Dareh_N • Average
    distance: 25.61
    It goes without saying that they (the applications and studies) are heavily dependent on sample size and representativity and other included variables. And, moreover, that their accuracy can significantly vary, and that that they significantly vary with sampling effort. We can also ask whether or not the samples are sufficient enough for obtaining accurate results and to jump to a conclusion. Obtaining accurate results, of course, requires taking into account the variables that affect the assessment. And it almost goes without saying that genetic studies and genetic ancestry tests have often yielded equivocal or inconsistent results and serious unwanted adverse effects, rather than desired benefits. And this, in turn, may lead to inappropriate actions or applications and unnecessary mental and health problems.

    :

    The variables inevitably include the population size, the population strain, the sample size (including mean, median and range), and the core area of the foci. Another possible source of bias is that all variables, including outcome and potential predictors, are self-reported. And of course there's the problem of sample bias. It can certainly be difficult to interpret because of numerous confounding variables, including selection bias, reference bias, and the well-recognised "referral bias". Methodological challenges include sampling bias and computational complexity. And, for sure, the scores or the data can simply be dismissed as noise or as biased, or as measurement error, bias in perception, or misuse of scales. Or, we can even dismiss the data or data points as being "outliers". This, of course, raises the question: how can you forget something that will not go away? And how can we forget that all humans are 99.9 percent identical, genetically speaking, but that tiny 0.1 percent variation in our genetic make up is what makes all the difference. Welcome to the "tough and wacky" world of DNA. Nevertheless, it's important to note that being genetically similar to something is different than sharing the same DNA. It's a strange world, indeed. Get ready for a strange ride indeed. And these are strange indeed.

    Around 5-8% of your DNA isn’t human – it’s viral DNA. Scientists believe we carry about 100,000 pieces of DNA from retroviruses that have accumulated over the course of human evolution. We share 96% of our DNA with primates such as chimpanzees, gorillas and orangutans. But we are also genetically related to bananas – with whom we share 50% of our DNA – and slugs – with whom we share 70% of our DNA. Around 99.9% of the DNA in all humans is identical. It is the tiny 0.1% difference that allows us to be individuals with different skin, hair and eye colour. Scientists also believe that the remaining 0.1% holds important clues about the causes of diseases. Humans have approximately 10 trillion cells. If we unravelled our entire DNA, it would stretch six billion miles – which would be the same as travelling from the Earth to the sun 65 times. Human beings have 20,000 to 25,000 genes but they account for only about 3% of our DNA. Scientists are not sure about the function of the remaining 97%, although they think it may have something to do with controlling the genes. The human genome contains three billion base pairs of DNA. It is estimated that if you type eight hours a day at 60 words per minute, it would take approximately 50 years to type the human genome. Unlike the octopus, we can’t naturally edit our own genes. But scientists have developed a complex protein-based tool called CRISPR-Cas9 which has been used to successfully alter DNA in defective embryos to prevent inherited diseases.

    We’ve all noticed these differences, and we all know why these differences exist amongst us. Yes, it's genetics, and it's what you're born with, namely your genetics. And there's no denying it's an exciting time in genetics, especially when the use of this particular term "racial genetics" in this context is in lieu of the term "racial science," as the New York Times noted in a story on Jewish genetic history: ''Racial science, has brought so many terrible things. But it's a norm now in genetics to study the racial genetics of groups, so it's an amazing difference." Call it genetic science for the common man. In fact, it does feel right to call it "genetic science", and as pointed out by Dr. Schiffman, president of the Association for Jewish Studies, the study of racial differences has led to disaster in the past but the new analysis of genetic differences is ''a form of racial science for the good, rather than the bad.'' Whatever else they may be, however, and whatever else becomes the norm, but that line about how "it's all to do with genetics" undermines a lot of warnings or warning signs. Last but not least, it is also the distance that matters, the gap. And we can't help but be affected by the distance. This mechanism essentially allows one component to (for want of a better phrase or of a better description) lock out or dump out another (so to speak). It was, depending on your perspective, eased out, locked out, or pushed out. Same difference, really, just different packaging. It is essentially about one component causing another component to take a back seat. Or, to put it another way: One surfaces to the top and takes precedence over the others, and must necessarily take precedence over the other. In many ways, it may seem like a re-run of the chorus of Futurology, which runs like this, "We'll come back one day, we never really went away". Goes away and comes back. It's like it's screaming its head off, with the words: "I am going away in order to come back". The tension, it goes away, but it comes back tenfold. There's really no way to get around this unfortunate truth. Such is the wacky world of DNA. But what cannot ever be disputed by rational means is the fact that geography and ecology have undoubtedly influenced genetic divergence or distance and structure among populations. Of course, it goes without saying that the two phrases "genetic divergence" and "geographic distance" actually can mean the same thing and can be used almost interchangeably. They are indeed often overlapped and often used interchangeably. In general, a law is defined as a regularity that is valid across time and space. Overall, Laws are statements that are valid across time and space. They are valid across time means, among others, and they are valid in future to some extent; thus, we can use them for prediction. And here are facts that cannot be disputed:

    Similarity in species composition exhibit a strong geographic distance decay, in agreement with the first law of geography.

    Convergence is guaranteed by applying the first law of geography. But I would go further and add variation and mimicry and divergence and evolution.

    Geographic variation, convergence, and mimicry are "guaranteed" by applying the first law of geography.

    It is applying the first law of geography and the concept of distance decay.

    Here's a simple example to illustrate this point.

    Source Group(s): Ganj_Dareh_N

    Ganj_Dareh_N (Average): 24.36
    Ganj_Dareh_N (Median) 24.44

    https://i.ibb.co/NWfpbYg/ganj.png

    Source Group(s): Shahr-i Sokhta

    Shahr_I_Sokhta_BA3 (Average): 4.95
    Shahr_I_Sokhta_BA3 (Median): 4.95
    Shahr_I_Sokhta_BA2 (Average): 7.86
    Shahr_I_Sokhta_BA2 (Median): 7.89
    Shahr_I_Sokhta_BA1 (Median): 21.83
    Shahr_I_Sokhta_BA1 (Average): 21.93

    https://i.ibb.co/9YRt909/shah.png, https://i.ibb.co/Rz22S3w/sok.png

    Source Group(s): Gujarati

    Gujarati (Median): 1.19
    Gujarati (Average): 1.84

    Gujarati 100%

    https://i.ibb.co/YDNzGYR/guj.png, https://i.ibb.co/H73VxCb/guja.png, https://i.ibb.co/B4xcgCR/averageg.png, https://i.ibb.co/cvX6hYn/gujarat.png, https://i.ibb.co/jTdjWXj/map.png

    Aakar Patel may have been right, after all. For he writes with the assurance and historical command of someone who has been thinking about his topic for a long time, "The real native, the best example and in fact the apotheosis of Gujarati Man, is the Patel. He is characterized by his stubbornness and his rigidity." And looking at the literature about the Patidar or Patel caste, you have to admit he is sort of right.
    Steve Zwick (2000) even mentions this phenomenon of "stubborn Patelness" in his brilliant piece "Who Are All Those Patels?" But by the same token, the highly intellectual and landowning Anavil Brahmin caste of South Gujarat, to use the words of Uday Mahurkar (2014), who can also be referred to as "ritually pure" landowners, as they were and as they have already been described by B.B. Chaudhuri (2008), can also lay claim to being the apotheosis of Gujarati culture. This point is clearly illustrated by a fantastic passage in Dosoo Framjee Karaka's book, "Morarji":

    "By caste we are Gujarati," she said, "we are Anavil Brahmins". The word "Anavil" means 'pure'. The Anavil Brahmins believe in the Hindu god, Shiv.

    A staggering number of books shed all sorts of light on the surprisingly inexhaustible topic of caste and are readily available on Google Books or Google Book Search. And several intriguing observations have been recently made in this regard. Take the subject of this book, for instance. It is titled "State and Repressive Culture: A Case Study of Gujarat". And it sheds dramatic light on the relevance of caste and visible differences. The authors, namely Akshayakumar Ramanlal Desai and Wilfred D'Costa, make a convincing argument and make two salient points in this regard. Regarding the first observation, it should be noted, as the authors do, that the Anavil Brahmins "are comparable to the Patidars and are to be bracketed with them". This first observation is in perfect agreement with the other studies. It is certainly something that fits with my own data concerning marriage and hierarchy among the Anavil Brahmins and Leva Patidars of Gujarat. Generally, the intermediaries belonged to Patidar or Anavil Brahmin castes. And in terms of hierarchy we would say that the Anavil Brahmin caste is superior to the Patidar caste in Gujarat. In reality the Anavils themselves are "a lower-status subcaste within the high-status Brahmin caste." Or so states Maritsa Poros (2010). And according to Majmudar, the Anavils of South Gujarat are a different type of Brahmins (i.e., outsiders accepted as Brahmins). The Anavils themselves are internally divided into the superior "Desais" and the inferior "Bathelas". The fact that all Anavil Brahmins are grihastha is often interpreted as an indication that this Brahman group has been settled in Gujarat for a very long period, and the notable position traditionally occupied by the Anavil Brahmins has been based on their lifestyle as big landowners. And the importance of this observation by Shovan Ray (2007) cannot be stressed enough.

    The Jhas of Bihar and the Anavil Brahmins of South Gujarat also claim Brahmin status and consider themselves to be higher than those Brahmins who are religious officiates.

    (Thakorlal Bharabhai Naik's insider book about the Anavils is aptly titled The Unspoilt Brahmins). The second observation is even more pertinent in a society based on grotesque hierarchy and inequality. Such simplicity belies a complex effect and suggests an impressive amount of research. For it is one of the book's best passages and is one of the best analyzed observations. And, to quote from the book "State and Repressive Culture":

    The Patidars or Patels in Gujarat are, therefore, the most powerful and influential community, forming about 15 to 20 percent of the population. Their mental and cultural make-up is a curious mixture of feudal mentality and capitalist outlook, marking them out as a very aggressive, patronising, ruthless and achieving class in Gujarat.

    Let us now turn back to the topic of genetic distance, and there does seem to be an overall correlation between genetic distance and geographic distance. On this, there can be no dispute and doubt. I know I harp a lot on the reality of what is, rather than on the illusion of what is not, and on the fact that everything is relative, but it is important to be sure, as is the first law of geography, which states that "all things are related, but nearby things are more related than distant things". For everything can be conceived of in terms of a relative concept, since everything is identical with itself and distinct from everything else. As such, "all" is entirely relative, and in this world of shared misery, all things are relative (including "suffering and anguish"). All truth is relative. Reality, it seems, is all relative. And the Real itself? In the history of religions, we find innumerable gods, with different characteristics. Shall we say they all exist? Can belief in all of them be rational?

    John Hick has proposed a ”pluralistic hypothesis“ to deal with the problem of religious diversity (Hick, 1984, Chapter 14). According to the pluralistic hypothesis, the great world faiths embody different perceptions and conceptions of one reality that Hick christens ”the Real.“ The Real itself is never experienced directly, but has ”masks“ or ”faces“ which are experienced, depending on how a particular culture or religion thinks of the Real. The Real itself is, therefore, neither personal nor impersonal, these categories being imposed upon the Real by different cultural contexts. Hence, the typical experiences of the major faiths are to be taken as validly of the Real, through mediation by the local face of the Real.

    And here's some more. All comparisons are relative. All values are relative. And all potentials are relative. All results, too, are relative. Risks also are relative: what one person considers too dangerous, another might not. The basic idea of relativism, the idea that there is no one truth or one reality that we all try to capture, is captured by the battle cry "all is relative" and the oft-repeated slogan "all is relative". I could go on and on and on, obviously. All meaning is relative. All statistical significance is relative, and all data is relative to control values. Nature is relative, while all human experience is natural. According to an essential theory of physics, all time is relative. Of course, like everything else in the world, the problems are all relative (they are not universal), and the solutions equally so. After all, but everything is relative. Tobler's first law was a product of the quantitative revolution of the 1960s, and of the efforts to turn geography into a nomothetic science.

    Spatial autocorrelation is the first law of geography.

    Tobler's first law of geography, 'Everything is related to everything else, but near things are more related than distant things', usually referred to as simply Tobler's law, was first applied to urban growth systems, but it also applies to biological systems. Important as geography might be, the idea of geography's importance seems still more important. Further and as is typical, geography and cultural affinities play a key role here and in these calculations. This is consistent with increasing interconnectedness. Again, these characteristics of the data are indeed consistent with Tobler's first law of geography. Basically, Tobler's (1976) first law, which is commonly referred to as "gravity model", states that measures at locations close to each other will tend to be more similar than measures at distant locations. The examples shown here prove he was right. And they are also supported by data from other sources.

    Source Group(s): Shahr_I_Sokhta, Indus P, Ganj_Dareh_N

    Shahr_I_Sokhta_BA3 66-86%
    Indus_P 8-27%
    Shahr_I_Sokhta_BA2 2-9%

    Shahr_I_Sokhta_BA3 4.46
    Indus_P 6.08
    Shahr_I_Sokhta_BA2 7.41
    Shahr_I_Sokhta_BA1 21.67
    Ganj_Dareh_N 25.34
    Ganj_Dareh_Historic 28.05

    https://i.ibb.co/ZLJNSFq/ba3.png, https://i.ibb.co/Lt9ZJcr/3way.png, https://i.ibb.co/kDPMXm3/pca3.png, https://i.ibb.co/bz6qZgc/pca4.png

    Source Group(s): Gujarati, Ganj_Dareh_N

    Gujarati (Average): 1.84
    Ganj_Dareh_N: 23.12

    Gujarati 100%

    https://i.ibb.co/0fzjfg2/gan.png

    Source Group(s): Gujarati, Shahr_I_Sokhta

    Gujarati: 62-78%
    Shahr_I_Sokhta: 23-38%
    Gujarati (Average): 1.61
    Shahr_I_Sokhta_BA3: (4.49)
    Shahr_I_Sokhta_BA2 (Average): 6.04
    Shahr_I_Sokhta_BA1 (Average): 20.64

    https://i.ibb.co/s32g50D/ba.png

    Source Group(s): Gujarati, Indus P

    Gujarati: 89-100%
    Indus_P: 0-12%
    Gujarati Average: 3.2
    Indus_P Average: 5.89

    https://i.ibb.co/10X1SgD/indusper.png, https://i.ibb.co/sCjF23S/mapindusp.png

    Source Group(s): Gujarati, Indus P, Shahr_I_Sokhta

    Gujarati: 62-78%
    Shahr_I_Sokhta: 22-38%
    Gujarati (Average): 1.61
    Shahr_I_Sokhta_BA3 (Average): 4.49
    Indus_P Average (4.83)
    Shahr_I_Sokhta_BA2 (Average): 6.04
    Shahr_I_Sokhta_BA1 (Average): 20.64

    https://i.ibb.co/S73D2cx/indusperip.png, https://i.ibb.co/7GMqCbY/orac.png

    And now for the final.......

    Source Group(s): Gujarati, Ganj_Dareh_N, Shahr_I_Sokhta, Indus P

    Gujarati: 62-78%
    Shahr_I_Sokhta: 22-38%
    Ganj_Dareh_N: 0-1%

    Gujarati • Average (sample) 1.61 (distance)
    Shahr_I_Sokhta_BA3 • Average 4.49
    Indus_P • Average 4.83
    Shahr_I_Sokhta_BA2 • Average 6.04
    Shahr_I_Sokhta_BA1 • Average 20.64
    Ganj_Dareh_N • Average 24.33
    Ganj_Dareh_Historic • Average 27.2

    https://i.ibb.co/qgrh6PS/distance.png, https://i.ibb.co/kVnwmKB/sokt.png, https://i.ibb.co/NLvmMzs/geno.png

    It certainly follows that one category always takes precedence over another, or takes precedence over the others.

    As it does here.

    Shahr_I_Sokhta_BA3: 4.95
    Shahr_I_Sokhta_BA2: 7.86
    Shahr_I_Sokhta_BA1: 21.93
    Sintashta_MLBA_o1: 27.65
    Sintashta_MLBA_contam: 30.88
    Sintashta_MLBA_o3: 31.14
    Sintashta_MLBA: 32.34

    https://i.ibb.co/1X6B8vt/sintas.png, https://i.ibb.co/W5bk1zG/ist.png, https://i.ibb.co/5nLfWmN/prec.png, https://i.ibb.co/rvHHZPN/pre.png, https://i.ibb.co/LtgHdfj/sample.png

    Speaking of sampling….

    And not only that, but it is also clear that the range and the orientation of the samples have very significant and profound effects on the statistics and results. Not forgetting, of course, that larger samples have smaller margins of error. The situation here perfectly illustrates both the importance of using multiple genetic tests and the importance of getting it right.

    CG_IVCp • IRN_Shahr_I_Sokhta_BA2_I8728: 5.4
    CG_IVCp • IRN_Shahr_I_Sokhta_BA2_I11459: 7.29
    CG_IVCp • IRN_Shahr_I_Sokhta_BA2_I11456: 8.39
    CG_IVCp • IRN_Shahr_I_Sokhta_BA2_I11466: 10.24
    CG_IVCp • IRN_Shahr_I_Sokhta_BA2_I8726: 14.58

    https://i.ibb.co/1KPMkNT/ivc.png, https://i.ibb.co/CtGsntN/shahiran.png, https://i.ibb.co/7kz5J9y/cg.png

    Sintashta_MLBA_o1 • I1017: 26.69
    Sintashta_MLBA_o1 • Average: 27.65
    Sintashta_MLBA_o2 • I0983: 28.21
    Sintashta_MLBA_o1 • I1007: 28.99
    Sintashta_MLBA_o2 • Average: 29.02
    Sintashta_MLBA • I1063: 30.42
    Sintashta_MLBA • I0943: 32.97
    Sintashta_MLBA • I0942: 33.98

    https://i.ibb.co/q7V2gt7/mlb.png, https://i.ibb.co/CQCRM1Q/ora.png

    Yamnaya_UKR 80-90%

    Yamnaya_UKR_Ozera_o • Average: 28.33
    Yamnaya_RUS_Caucasus • Average: 29.47
    Yamnaya_KAZ_Mereke • Average: 30.11
    Yamnaya_UKR • Average: 30.78
    Yamnaya_KAZ_Karagash • Average: 31.10
    Yamnaya_RUS_Samara • Average: 31.14
    Yamnaya_RUS_Kalmykia • Average: 31.19
    Yamnaya_BGR • Average: 31.36

    https://i.ibb.co/fvDt32k/yamnaya.png, https://i.ibb.co/BVFjt9P/pie.png, https://i.ibb.co/1X1RRtS/ukr.png, https://i.ibb.co/XJmm8F0/naya.png

    Yamnaya_KAZ 27-34%
    Ganj_Dareh_N 66-72%


    Ganj_Dareh_N • Average: 24.6
    Ganj_Dareh_N • Median: 24.67
    Yamnaya_UKR_Ozera_o • Average: 28.33
    Yamnaya_RUS_Caucasus • Average: 29.47
    Yamnaya_KAZ_Mereke • Average: 30.11
    Yamnaya_UKR • Average: 30.78
    Yamnaya_KAZ_Karagash • Average: 31.1
    Yamnaya_RUS_Samara • Average: 31.14
    Yamnaya_RUS_Kalmykia • Average: 31.19
    Yamnaya_BGR • Average: 31.36

    https://i.ibb.co/42mWFrZ/kaz.png, https://ibb.co/9prRGVM, https://i.ibb.co/dk58mrK/tamkaz.png, https://i.ibb.co/PQkCxxJ/irann.png

    Yamnaya_RUS_Caucasus 44-54%

    Yamnaya_RUS_Caucasus • RK1007 distance: 28.21

    https://i.ibb.co/1v9ZXc1/rus.png, https://i.ibb.co/yWGkf6p/rusyam.png, https://i.ibb.co/GP5n0nZ/pcayam.png, https://i.ibb.co/XSnvzwR/distance1.png

    CG_IVCp 100%

    CG_IVCp • Average: 7.57
    Shahr_I_Sokhta_BA1 • Average: 20.66
    Yamnaya_RUS_Caucasus • Average: 28.67
    Yamnaya_UKR • Average: 30

    https://i.ibb.co/kcP5HBk/ivc2.png, https://i.ibb.co/CJXTLcv/ivcp.png, https://i.ibb.co/1T9NzqK/ba1.png

    Shahr_I_Sokhta_BA3 • Average: 4.21
    CG_IVCp • Average: 8.72
    Yamnaya_RUS_Caucasus • Average: 29.31
    Yamnaya_UKR • Average: 30.57

    https://i.ibb.co/89V4TWN/ba3iran.png, https://i.ibb.co/sFGMKpc/av.png, https://i.ibb.co/rpjCxnJ/aver.png, https://i.ibb.co/tM1yjz2/pcaplot.png, https://i.ibb.co/2tkKJnt/ukraine.png

    If ever an app was at once meaningful and meaningless, this was it.

    This cannot be said any better! "Meaningful, meaningless, meaningful, meaningless, this is the wave that washes through our lives and creates its inherent tension."
    Y-DNA (P): R1b-S47 (Irish/Scot), E1b1b1 (Proto-Semitic), C1b-Z5896. mtDNA (M): W6 (Gotland/Sweden). Ancient (European) Origins: Indo-European (Metal Age Invader) 67%, Early/First/Neolithic European Farmer (EEF/FEF/ENF) 8–10%, WHG 3–7%; Turkey 20–30%; Caucasian-Anatolian-Balkan 40–43%; Volga Region 18–20%; Ukrainian 11–12%; Viking 10%; Scandinavian 6–7% EHG–Steppe: Corded Ware 28–34, Yamnaya (Steppe Pastoralist) 23–25%, Bell Beaker 22–24%; Steppe to SCAsian 20–23%; Euro HG 11-12% CHG/Iran: Caucasus (CHG) 31–33%; Iran_N 54–60%; IVC 64-67%


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