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Thread: Population genomics of Bronze Age Eurasia (Allentoft et al. 2015)

  1. #831
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    Quote Originally Posted by Kurd View Post
    Although I am a fan of formal methods, modeling Pashtuns based on Sintashta, ~15% Dai, Armenians, Andronovo, Yamnaya, and Bedouin, simply does not account for the S Asian/Indian admixture component present in modern Pashtuns, and also to a lesser extent Iranians. We need this component to sensibly account for admixture, and I do believe adding this will yield good fits whenever this happens.


    EDIT: Modeling individuals based on admixture should not be discounted especially if the references are not too old. As you may be aware there are a couple of methods available to do this. Allele frequencies which everyone is familiar with and by segments (ie 23andMe)
    One important thing to keep in mind about qpAdm is that it reflects really old ancestral components. The result is not to be taken literally and as mentioned above, part of Sintashta in Pashtuns for instance may well be actually represent a contribution from a South Asian-like population.

    However, when I look at those qpAdm results my train of thought goes like this: a very good fit for Ukrainians is chisq 0,711 tail prob 0,870727 Yamnaya 0,445 EN 0,409 WHG 0,125 East Asian 0,021.

    Now, so far we have no reason to believe there is some sort of ancestry in Ukrainians that is not covered by those populations (basically what they don't cover to at least some degree is certain African and Oceanian stuff), and that fit being good demonstrates qpAdm works well.

    Now the gist: if Pashtuns get fits of similar quality or better with Sintashta, Dai and modern Caucasus pops or BA Armenians, I think the most likely conclusion is that we have the real deal there. That has implications for ASI - any differences that exist between it and what's in the three populations used in the fit (primarily Dai?) appear to be inconsequential when it comes to deep phylogeny - and if that is the case any apparently meaningful differences we may see in a PCA or an ADMIXTURE run are basically not meaningful in that particular sense, just results of drift etc.

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  3. #832
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    Quote Originally Posted by Shaikorth View Post
    One important thing to keep in mind about qpAdm is that it reflects really old ancestral components. The result is not to be taken literally and as mentioned above, part of Sintashta in Pashtuns for instance may well be actually represent a contribution from a South Asian-like population.

    However, when I look at those qpAdm results my train of thought goes like this: a very good fit for Ukrainians is chisq 0,711 tail prob 0,870727 Yamnaya 0,445 EN 0,409 WHG 0,125 East Asian 0,021.

    Now, so far we have no reason to believe there is some sort of ancestry in Ukrainians that is not covered by those populations (basically what they don't cover to at least some degree is certain African and Oceanian stuff), and that fit being good demonstrates qpAdm works well.

    Now the gist: if Pashtuns get fits of similar quality or better with Sintashta, Dai and modern Caucasus pops or BA Armenians, I think the most likely conclusion is that we have the real deal there. That has implications for ASI - any differences that exist between it and what's in the three populations used in the fit (primarily Dai?) appear to be inconsequential when it comes to deep phylogeny - and if that is the case any apparently meaningful differences we may see in a PCA or an ADMIXTURE run are basically not meaningful in that particular sense, just results of drift etc.
    The problem is that Sintashta does not nearly have enough S Asian contribution to account for S Asian admixture in modern Pashtuns.
    The analogy with the Ukranian example is not good, because the African and Oceanian stuff in Ukrainians is miniscule in comparison to the Indian "stuff" in Pashtuns.

    Additionally, with regards to drift we know that indigenous Indian populations pre date BA Sintashta, so the likelihood of no contribution from these "old" Indian populations, in light of the geographical placement, and Indian admixture levels in present Pashtuns has to be close to nil. As Everest59 mentioned in the previous post, the Dai is supposed to capture ASI, since the software cannot distinguish various E Eurasian components well (Dai/ ASI does not give the whole picture with regards to Pashtun).


    Like Everest59, I believe that Sintashta admixture is being overestimated due to a lack of S Asian aDNA, and based on the ~10% N European scores in Pashtuns, I would also guess <30% Sintashta admixture in Pashtuns.

    In summary, we need the S Asian aDNA to accurately model Pashtuns in light of their geographical placement and the ancientness of Indian groups.
    Last edited by Kurd; 06-28-2015 at 11:04 PM.

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    Quote Originally Posted by Kurd View Post
    The problem is that Sintashta does not nearly have enough S Asian contribution to account for S Asian admixture in modern Pashtuns.
    The analogy with the Ukranian example is not good, because the African and Oceanian stuff in Ukrainians is miniscule in comparison to the Indian "stuff" in Pashtuns.

    Additionally, with regards to drift we know that indigenous Indian populations pre date BA Sintashta, so the likelihood of no contribution from these "old" Indian populations, in light of the geographical placement, and Indian admixture levels in present Pashtuns has to be close to nil. As Everest59 mentioned in the previous post, the Dai is supposed to capture ASI, since the software cannot distinguish various E Eurasian components well (Dai/ ASI does not give the whole picture with regards to Pashtun).


    Like Everest59, I believe that Sintashta admixture is being overestimated due to a lack of S Asian aDNA, and based on the ~10% N European scores in Pashtuns, I would also guess <30% Sintashta admixture in Pashtuns.
    Sintashta alone doesn't represent South Asian, and doesn't have to, but the fit being that good means Sintashta + Caucasus pop + Dai do approximate the South Asian contribution to Pashtuns (which is ASI+ANI going by the famous model), and the purpose of my Ukrainian comparison is to demonstrate that it does it well - which again means the known South Asian contribution is represented by some combination of the three populations. As I said, the qpAdm fit doesn't need to be the literal Sintashta percentage. The Dai proxies for ASI, and if it produces good fits while doing so it's because it's similar to ASI.

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    The reverse also holds true for the WHG component; Sintashta and Andronovo were revealed to possess even more of the WHG-related components than Yamnaya. I distinctly recall one of them scoring over 60% WHG-UHG via GEDmatch. Conversely, there doesn't appear to be very much WHG-UHG among either Afghan Tajiks or Pashtuns (3.72-3.85%).

    If Pashtuns are to be modelled as 50% Sintashta, how could one reconcile the approximate input in Kazakhs (9.15%), whose country resides on Sintashta and Andronovo territory? Are they going to be 140% Sintashta?

    A facetious comment, no doubt, but it underscores the resounding problem here; the disconnect with prior data is simply too great for any rigid and literal interpretations of qpAdm stats to be viable even in passing. Shaikorth's posts regarding a re-assessment of the nature of ASI from these numbers, on the other hand, is certainly a legitimate inference, given we are dealing with what is still a hypothetical "ghost" component.

    It's not much different from the erroneous conflation of Y-DNA/mtDNA haplogroup frequency with the location of origin, a fallacious mindset in the early 2000's... New parameter, same trap. Let's not fall into it, folks!

    Quote Originally Posted by Shaikorth View Post
    As I said, the qpAdm fit doesn't need to be the literal Sintashta percentage. The Dai proxies for ASI, and if it produces good fits while doing so it's because it's similar to ASI.
    Could it not be the case that people are assuming ASI to be best modelled by just the Dai in such a combination, and it's actually the presence of both Sintashta and Dai that accounts for ASI here?

    I don't see why this cannot be the case, given ANI is commonly taken as a mixture of different ancestral waves from West Eurasia.

    Thus, in that respect, the Dai score could well be underestimating the actual ASI component in Pashtuns by quite a bit.

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    Quote Originally Posted by Shaikorth View Post
    Sintashta alone doesn't represent South Asian, and doesn't have to, but the fit being that good means Sintashta + Caucasus pop + Dai do approximate the South Asian contribution to Pashtuns (which is ASI+ANI going by the famous model), and the purpose of my Ukrainian comparison is to demonstrate that it does it well - which again means the known South Asian contribution is represented by some combination of the three populations. As I said, the qpAdm fit doesn't need to be the literal Sintashta percentage. The Dai proxies for ASI, and if it produces good fits while doing so it's because it's similar to ASI.
    Sure, it does well based on the aDNA data that we have. However, without actual aDNA from South Asia, there is no way of knowing how good the fit actually is. We cannot discount all discrepancies between ADMIXTURE/PCA and qpdm(and other formal tests) as drift.
    To be honest, we do not know the characteristics of ASI very well. It may well be a transitional population between West Eurasian and East Eurasian. Who knows?

    Pashtuns live in a very different territory, so logically, to calculate their ancestral composition, we need aDNA from their surroundings. Sintashta is I think a good aDNA sample to model the Indo-Aryan ancestry. Now we need some other aDNA data. ASI, pre-indo-Aryan ANI, etc.

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  11. #836
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    Quote Originally Posted by Shaikorth View Post
    Sintashta alone doesn't represent South Asian, and doesn't have to, but the fit being that good means Sintashta + Caucasus pop + Dai do approximate the South Asian contribution to Pashtuns (which is ASI+ANI going by the famous model), and the purpose of my Ukrainian comparison is to demonstrate that it does it well - which again means the known South Asian contribution is represented by some combination of the three populations. As I said, the qpAdm fit doesn't need to be the literal Sintashta percentage. The Dai proxies for ASI, and if it produces good fits while doing so it's because it's similar to ASI.
    I agree that the model gives a good fit for Pashtuns, but that does not necessarily equate with historical reality. Other factors, such as geographical placement, surrounding populations can not be ignored. All I am saying is that I believe a better fitting model is likely if one of the 3 input prongs is ancient S Asian aDNA

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    Quote Originally Posted by everest59 View Post
    The Dai is supposed to capture ASI, since these softwares cannot distinguish various East Eurasian like components well.
    However, IMO the Sintashta admixture in Pashtuns is being overestimated big time due to lack of South Asian adna.
    My guess would be 20 to 30% Sintashtashtalike admixture in Pashtuns based on that 10% Northern Euro score.
    That's basically what I see on my runs. Since Yamnaya shares more of the Caucasus stuff with S Asia, SC Asians usually get 30% Yamnaya. Less Caucasus and more Euro like should result in something low to mid 20s. I've got a run that gives 30% Yamnaya, along with a farmer component that is about 20% ASI. Maybe it's similar to a Harrapan farmer, I don't know. I've added Andronovo and Sintashta to see if I can get a cluster. If it works, I'll post it.

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    Quote Originally Posted by DMXX View Post
    The reverse also holds true for the WHG component; Sintashta and Andronovo were revealed to possess even more of the WHG-related components than Yamnaya. I distinctly recall one of them scoring over 60% WHG-UHG via GEDmatch. Conversely, there doesn't appear to be very much WHG-UHG among either Afghan Tajiks or Pashtuns (3.72-3.85%).

    If Pashtuns are to be modelled as 50% Sintashta, how could one reconcile the approximate input in Kazakhs (9.15%), whose country resides on Sintashta and Andronovo territory? Are they going to be 140% Sintashta?

    A facetious comment, no doubt, but it underscores the resounding problem here; the disconnect with prior data is simply too great for any rigid and literal interpretations of qpAdm stats to be viable even in passing. Shaikorth's posts regarding a re-assessment of the nature of ASI from these numbers, on the other hand, is certainly a legitimate inference, given we are dealing with what is still a hypothetical "ghost" component.

    It's not much different from the erroneous conflation of Y-DNA/mtDNA haplogroup frequency with the location of origin, a fallacious mindset in the early 2000's... New parameter, same trap. Let's not fall into it, folks!



    Could it not be the case that people are assuming ASI to be best modelled by just the Dai in such a combination, and it's actually the presence of both Sintashta and Dai that accounts for ASI here?

    I don't see why this cannot be the case, given ANI is commonly taken as a mixture of different ancestral waves from West Eurasia.

    Thus, in that respect, the Dai score could well be underestimating the actual ASI component in Pashtuns by quite a bit.
    Re: the apparent ADMIXTURE WHG and qpAdm Sintashta contradiction, there is overlap between the components that hides shared ancestry, so they don't need to correlate with fits done by qpAdm or similar methods. Kazakhs as West Asian+Sintashta+Dai would be an interesting experiment, but my expectation would be a lot less Sintashta and a lot more Dai compared to Pashtuns. If this thing works equally well for Ukrainians (belonging to the very well studied European group) and for S-C Asians using a different set of populations, I'm basically willing to give it precedence over older methods (used pre-Lazaridis & Haak) in both cases.

    ASI being a hybrid of West Eurasian + "Dai-like" is a possibility that the fits leave open for now, I agree. In absence of ancient DNA it's hard to figure, at least the various "ASI"-components people have created for their ADMIXTURE runs could be compared as zombies to Dai and West Eurasians using f4 or D-stats to see if those are "hybrids".

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    I've been gone all day, and a lot seems to have happened in terms of discussion.

    To address a few points:

    1) The BA Armenians aren't (obviously) the direct ancestral population for Iranians. Rather, populations like them constitute around 70%-80% of Iranian genetic ancestry, just like populations similar to Sintashta constitute around 60%-70% of Pashtun genetic ancestry.

    2) These stats cut very deep into the phylogeny, so ASI (as understood to be South Asian-specific ENA) has excellent representation via Dai. ASI will have the same relationships to the outgroup populations as any ENA population, which is why Dai does so well (this is all based on how the left populations relate to the right populations. Residual fitting is the name of the game).

    3) The Pashtun-Sintashta fits are always the best fits produced by this software, probably because Sintashta are directly ancestral to Pashtuns and company (a fact borne out by the presence of R1a1a lineages in Sintashta which are the exact same lineages found in anywhere from around 50% to 70% of Pashtun males. Also, Sintashta and Andronovo in Allentoft et al. have a hefty share of mtDNA U2 lineages, which constitute the largest share of the modern Pashtun mtDNA gene pool). If they were a broad proxy for general steppe admixture, the fits would be great, but not as amazingly excellent as they are now. Just something to think about.

    4) WHG as understood in Lazaridis et al. has a very different meaning now, post-Haak et al. We now know that WHGs were probably admixed between North Eurasian people and some sort of populational group that was basal to North Eurasian people (but they were certainly a stabilized mixture). EHG and MA1 are different spatio-temporal nodes on the "North Eurasian" populational network. The befuddlement a lot of people here are feeling is mainly because they still have the "old model" in mind. The WHG-ANE-ENF model wasn't final.

    5) These Pashtun fits are better than what Europeans tend to get, with any combination of modern and ancient populations. If the Pashtun fits are doubted, than the European models are in serious trouble, and the whole Haak et al. paper needs to be reevaluated (and it's main theoretical thrust, in terms of concrete results, has to be thrown into the dustbin). I don't think anyone seriously entertains the undertaking of that route.

    6) Finally, qpAdm output overrides anything produced via ADMIXTURE, and to a lesser extent, PCA. As I've written before:

    "There is a tendency to look at ADMIXTURE output in these cases, but I think that leads us nowhere. Looking at Chad's ADMIXTURE experiments, that software is very sensitive to slight population/component additions. Drift wrecks havoc with the clusters. At the end of the day, interpreting the output tends to involve a lot of unsubstantiated speculation. Most importantly, there is just no real mechanism for deciding whether the output reflects reality or not.

    By contrast, the f4-stat based modelling used in Haak et al. is very robust to things like drift, and doesn't need the "tinkering" involved in ADMIXTURE. Most importantly, the output can be judged on a statistical basis, and is construable as robust, weak, or even as a failure ("infeasible")." In addition, as Shaikorth has noted, ADMIXTURE components overlap.

    To summarize, we need to wake up and smell the coffee (), the results are what they are. The only thing we need is Neolithic aDNA from South Central Asia/South Asia, and the picture has been drawn.

    Edit: Everest once used ALDER (another piece in the ADMIXTOOLS package) on the HGDP Pashtuns. With Lithuanians, he got Pashtuns to be 66% Lithuanian-admixed. That is quite close to the Sintashta percentages. Here is what he wrote to me:

    "Interesting. Alder can calculate admixture % using just 1 reference samples. I tried computer admixture % for Pashtuns using Georgians, Sindhis and then Lithuanians. The admixture using Lithuanian was a whopping 66%."
    Last edited by Sein; 06-29-2015 at 05:48 AM.

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    Quote Originally Posted by DMXX View Post
    Some discussion points addressing the validity of this proposition:

    1) We have no aDNA from anywhere in the Iranian plateau. Frankly, based on our available data, suppositions regarding the relevance of the Bronze Age Armenians in the ethnogenesis of modern Iranians makes as much sense as relating the West Anatolian farmer (identical to Stuttgart) to Bedouins.

    2) Outside of location, little is known about the archaeological or linguistic context of these Bronze Age Armenians. Their identification with Hurrians is, as far as I can see from the discussions here, entirely speculative. It could well be the case they are early speakers of proto-Armenian (logical given their position in the northern Armenian highlands). As such, any steppe-mediated ancestry in the Iranian qpAdm results could well be masked within the Bronze Age Armenian scores.

    3) There is no reason to solely rely on qpAdm statistics (which appears to be preferred here) given
    a) The outcomes are entirely dependent on prior-selected populations (I could model Pashtuns using Yamnaya, Burusho and Dai and am fairly certain they will end up with <5% steppe ancestry), and
    b) We have an abundance of both prior genetic (Y-DNA R1a1a and mtDNA U4/5/T frequencies? ADMIXTURE component differences with immediate neighbours?) and archaeological data (Grey Ware culture?) suggesting some sort of movement (currently unknown genetic contribution) from Central Asia into northern Iran.

    The other results also do suffer from a similar problem; we do not have, for instance, relevant samples from Maikop (yet, hopefully) or any archaeological cultures around the Caspian brim which may have contributed the "teal" to Yamnaya. Outside of giving us some directionality (which you inferred and I agree with), we're no closer to identifying precisely what happened in a genomic context in either the steppes or the Caucasus other than north-to-south geneflow.

    Then again, I prefer taking a methodological and nuanced approach to these topics. I've seen the Eurogenes comments and, quite evidently, I'm a minority at least there.
    Just a side note, but this isn't an equal comparison. The BA Armenians are an ancient population in the vicinity of modern NW Iranians. By contrast, the Burusho are a modern population in the vicinity of modern Pashtuns. Pashtuns will naturally come out as predominantly Burusho (with a big caveat to be noted), since both Pashtuns and Burusho are living end points on a shared deep populational history, with shared source populations for both ethnic groups.

    Also, having it based on actual ancient populations that are "prior selected" makes much more historical and biological sense then what ADMIXTURE does. ADMIXTURE simply produces panmictic populations (at varying K levels to boot), and panmixia has never really been at play in the actual history of our species. By contrast, we are actually descended (albeit in very complex and multifaceted ways) from the aDNA samples that are retrieved, and continue to be retrieved, by these research labs.

    Now, here is the big caveat to be noted. Basically, qpAdm will probably have the model as "infeasible". That's the beauty of qpAdm, it isn't a Dodecad oracle. If a model can't work, it won't. In this case, I'm sure it won't, since the ENA differential doesn't make sense. Pashtuns have intermediate ENA affinity in relation to Burusho and Sintashta, but Pashtuns and Burusho have nearly identical affinities to North Eurasian and Southwest Asian populations, when one adjusts for the heightened ENA affinity in the Burusho. Sintashta just wouldn't figure into it, but Dai wouldn't either. And the greater ENA pull in the Burusho will make them a poor proxy for Pashtuns in terms of f4-relationships. So, the model will just fail ("infeasible").

    Here is an example of a "infeasible" model for Iranians (it doesn't work):

    left pops:
    Iranian
    RISE_baSin
    RISE_baArm
    Dai

    right pops:
    Ju_hoan_North
    Mbuti
    Karitiana
    Surui
    Ulchi

    0 Iranian 8
    1 RISE_baSin 5
    2 RISE_baArm 7
    3 Dai 10
    4 Ju_hoan_North 5
    5 Mbuti 10
    6 Karitiana 12
    7 Surui 8
    8 Ulchi 25
    jackknife block size: 0.050
    snps: 525444 indivs: 90
    number of blocks for block jackknife: 720
    dof (jackknife): 605.965
    numsnps used: 335605
    codimension 1
    f4info:
    f4rank: 2 dof: 2 chisq: 2.228 tail: 0.328213251 dofdiff: 4 chisqdiff: -2.228 taildiff: 1
    B:
    scale 1.000 1.000
    Mbuti -0.005 -0.040
    Karitiana 0.962 1.221
    Surui 0.945 0.877
    Ulchi 1.477 -1.318
    A:
    scale 160.465 2548.580
    RISE_baSin 0.083 1.700
    RISE_baArm -0.027 0.324
    Dai 1.730 -0.066


    full rank 1
    f4info:
    f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 2 chisqdiff: 2.228 taildiff: 0.328213251
    B:
    scale 1.000 1.000 1.000
    Mbuti -0.006 -0.086 1.852
    Karitiana 0.962 1.191 0.533
    Surui 0.947 0.880 -0.536
    Ulchi 1.476 -1.341 0.004
    A:
    scale 160.562 2598.118 16762.745
    RISE_baSin 0.082 1.708 0.278
    RISE_baArm -0.042 0.281 -1.709
    Dai 1.730 -0.074 -0.055


    best coefficients: -0.227 1.198 0.030
    ssres:
    -0.000230794 -0.000199664 -0.000056880 -0.000137406
    -1.359687850 -1.176288948 -0.335096890 -0.809508082

    Jackknife mean: -0.183558573 1.153392901 0.030165672
    std. errors: 0.228 0.229 0.016

    error covariance (* 1000000)
    52086 -52247 161
    -52247 52655 -408
    161 -408 247


    fixed pat wt dof chisq tail prob
    000 0 2 2.228 0 -0.227 1.198 0.030 infeasible
    001 1 3 5.238 0 -0.394 1.394 0.000 infeasible
    010 1 3 40.571 8.06223e-09 0.967 -0.000 0.033
    100 1 3 3.796 0.284399 -0.000 0.970 0.030
    011 2 4 46.234 2.20113e-09 1.000 -0.000 0.000
    101 2 4 8.941 0.0625991 0.000 1.000 0.000
    110 2 4 3105.744 0 0.000 -0.000 1.000
    best pat: 000 0 - -
    best pat: 100 0.284399 chi(nested): 1.567 p-value for nested model: 0.210584
    best pat: 101 0.0625991 chi(nested): 5.145 p-value for nested model: 0.0233121

    ## end of run

    Basically, one can not model Iranians as Sintashta + BA Armenian + Dai (it's a failure), even though that is an excellent model for Pashtuns. Since Pashtuns and Iranians tend to overlap considerably in ADMIXTURE, this striking difference tells us something about the broad genetic roots of both populations.
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