Thursday, August 6, 2015

Steppe Ancestry Estimations in West, Central & South Asia (Ancestral Proportions Method) [Original Work]

This is largely a re-post, albeit with additional explanations, from a recent ADMIXTURE autosomal run (Eurasia K20) performed at Anthrogenica by the user Kurd. Full technical information and the original files may be found in his original thread. Full acknowledgement is provided to him for the great work. Unless stated otherwise, assume the contents refer to the Eurasia K20 run. This entry may be updated at any time to include further investigations based on future runs. Finally, this entry assumes the mainstream Pontic-Caspian theory for the genesis of the Indo-Europeans to be fully accurate.

This entry/repost contains a "quick and dirty" method for a preliminary attempt at deriving their Sintashta admixture levels in West, Central and South Asians based on the Eurasia K20 scores. Given the different admixture histories elsewhere in Eurasia, this probably won't be very informative for users with ancestral backgrounds outside the lands between Kurdistan and the Indo-Gangetic plains. This is especially the case with modern Europeans, who share the same core components with Sintashta, while also deriving their own Indo-European ancestries from different archaeological cultures and time periods.

Establishing the Context
According to this Eurasia K20 run, Sintashta are approximately 62% Yamnaya, 22% EEF, 10% European and 3% SHG_WHG. Sintashta, at present, appear to be the best proxy for the Indo-Iranians that arrived in West and South Asia. The above four components define the majority (94%) of Sintashta's autosomal profile here.

As discussed elsewhere in Anthrogenica (kudos to user Sein for pointing this out), Sintashta should be considered better surrogates for the Andronovo-related waves which reached West, Central and South Asia than the actual Andronovo samples derived from Allentoft et al. 2015. This is due to the Andronovo samples being derived from the extreme northeast of the archaeological horizon (above the Altai, near Afanasievo). Their position opens up the possibility for extraneous admixture from other steppe groups (including early speakers of Tocharian through Afanasievo?).

The user Kurd has previously demonstrated that recent steppe-related admixture may be segregated from other components. While undertaking this exercise, it also looks like Kurd has done an excellent job addressing the "teal" component that defined up to half of Samara Yamnaya and a big chunk of Sintashta. Kurd's K20 is, in my view, the most effective attempt thus far at separating the complicated autosomal overlapping in West and Central Eurasia.

Introducing the Ancestral Proportions Method (APM)
At present, the genetic landscape in West, Central and South Asia presents as a triple conundrum:

  1. There is, to date (and with the exception of the poor quality Barcin Neolithic Turkish sample), absolutely no interpretable ancient DNA (aDNA) from any of these regions, or indeed, at any point in this broad area's history. Perhaps the greatest obstacle at present.
  2. Autosomal and uniparental marker data from across the region are either inconsistent in sample strategy, or outdated, preventing a knowledge-based approach towards interpreting results.
  3. Archaeological evidence is inconsistent across the region; some cultures are well-studied, whereas others have fallen to mirthful speculation or cannot be readily assigned to any particular prehistoric group.

The APM is, in principle, unconcerned with these issues. Instead, it relies on objective data from a single ancient population to discern the numerical degree of overlap with modern populations.

Whether or not Iranians, Punjabis or Nepalis derive the bulk of their ancestry from unrelated group X or Y is beside the point. The sole purpose of the APM is, therefore, to establish whether or not ancient population Z has left any genetic imprint on modern populations A-K, and if so, to what extent. As such, the methodology described here is completely different as it is assymetrical; one-way gene flow across space and time from one ancestral (extinct) population to numerous extant populations. APM or derivative approaches should be considered as supplementary rather than directly competing with symmetrical modelling techniques such as f3 statistics.

The APM was specifically designed to answer the question; to what degree did Sintashta-related populations contribute to the modern groups of West, Central and South Asia? This simple inquiry has a tendency to attract considerable debate and wildly differing estimates in online discussion boards. Today, using the APM and recently generated data from the Eurasia K20 run, I hope to provide one set of estimations completely independent of extraneous modelling factors.

This approach is entirely reliant on high component specificity (e.g. minimal overlap or bleed-over from one component to another). This particular parameter is not within my control in this instance. As such, the outputs from APM here should be considered cautionary preliminary estimates at best, given the potential for ADMIXTURE-related shortcomings in the absence of relevant aDNA. I anticipate this approach will be much more effective at gleaning admixture extents once aDNA from West and Central Asia dating <2200 B.C. are retrieved.

The APM Approach
To contrast against the ADMIXTURE Sintashta scores, two different approaches are utilised together:

1) Direct Overlap (DO): summarised, for each component, the maximum overlap between a given population average and Sintashta's scores are calculated. This is done individually across all four components (Yamnaya, EEF, European, SHG_WHG) with the outputs added. See image below for schematic (conceptual breakdown of how the DO principle works between hypothetical samples 1 and 2, with Components a-d representing the distinct components).

Schematic diagram showing the principle behind Direct Overlap calculation

2) Component Proportions (CP): A single dominating component (frequency > 50%) is considered modal for the ancestral population of choice, with the other values considered as a fraction of this in modern populations. Given the Yamnaya component makes up almost two-thirds of Sintashta, the ratio between a population's and Sintashta's Yamnaya score are calculated and re-applied to the rest.

There are, however, problems with either approach:

1) DO is overinflated the more West Eurasian a population is. For example, several of the Iranian or Kurdish users at Anthrogenica had component scores greater than what is found in Sintashta (e.g. European being 12% in one sample, when it's 10% in Sintashta). This biases the results for Iranians and Kurds greatly, even when absolute value adjustments are set in place, which the formula shows is (it is highly improbable an Iranian with 10% European derived all of it from Sintashta).

2) CP is more accurate given the Yamnaya component appears highly steppe-oriented in Eurasia K20 and can therefore serve as a direct admixture marker. However, some of the South Asians are scoring very low, or almost none of, the other key components found in Sintashta (e.g. EEF). Due to this, CP doesn't fully account for the "missing variation" in South Asians, biasing the results slightly in their favour.

One convenient workaround is undertaking an average of both scores. However. given CP is intuitively more accurate due to the reasonable specificity of the Yamnaya component, a weighted average biased in favour of CP by a ratio of 3:1 was undertaken. The ratio choice in this variant of the APM is arbitrary here. Other variants (2:1, 4:1) would not result in radically different outcomes.

Full results from up to 24 populations are shown in the Data Sink (interactive chart below). Summarised, Pamiri Tajiks are the most Sintashta-derived at 31.9%. North Caucasian (Ossetian) and Central Asian ethnic groups (Pashtuns, Uzbek, other Tajiks, Turkmen) follow at 22-19%. Various other ethnic groups across West, Central and South Asia follow. The lowest scoring population sampled here are the Makrani at 9.2%.

Internal Validation
The output (Data Sink) readily demonstrates strong correlation between DO and CP scores per population (e.g. Tajik Pamiris at 34.20% & 30.8%, Nepalis at 15% & 14.5% and Makrani at 10.2% & 8.7% respectively account for the top, middle and bottom pairs). The only marked deviation between the DO and CP scores were noted in West Asian populations (Armenians, Kurds, Iranians), as mentioned previously. Thus, empirical confirmation of correlation (e.g. Spearman's rank order) is unwarranted here.

Another means of confirming the validity of APM is to confirm Andronovo is a descendant of Sintashta. As the Andronovo archaeological horizon originates from Sintashta directly, one would expect very high (>90%) Sintashta-derived ancestry among them.

This appears to be the case. compared against Sintashta, Andronovo exhibits DO = 83.9%, CP = 97.3%, an average of 90.6% and a weighted average of 92.8%.

Summarised, these two results (dataset-wide correlation, ancestral-immediate successor high overlap) validate the outcomes of the APM.

Closing Thoughts
The results featured in this entry are in line with both broad uniparental marker data, previously published IBD results (unfortunately removed from sources) and are largely (though not fully) compatible with the degree of archaeological input from Andronovo-derived cultures in Asia. As stated previously, due to earlier shortcomings, they should not be considered definitive.

Given the CP here is not exclusively associated with Sintashta, I anticipate this technique will be more accurate if future "steppe"/"Yamnaya"/"Yamanya_related" components are shown to define more of the Sintashta samples. I look forward to extending this method in the near future.

Special thanks to the user Kurd from Anthrogenica for making this data available and obliging member inquiries with productive responses, as well as the user Sapporo for generating several of the population averages.


  1. I'm not sure it's possible to use the Andronovo samples to validate these results, mostly because of the accumulation of a lot of recent local drift among present-day populations.

    The recent drift is a problem because it affects the Admixture results. For instance, a lot of Sintashta-derived ancestry might be hiding in the South Asian-specific components. Sintashta and Andronovo won't show any membership in such clusters for obvious reasons, but there's no reason to say they're not partly ancestral to them.

    On the other hand, methods based on f4 stats, like qpAdm, in theory might suffer from going back too far in the phylogeny and thus ignoring a lot of informative drift. So the only way to solve this problem is to compare Bronze Age samples from West and South Central Asia to Sintashta and Andronovo.

  2. Thanks for the comment. I fully agree with all points raised. Given the inadequate aDNA coverage of the region, none of the tools or methods we currently have work as a sufficient workaround for addressing the genetic architecture issue. ADMIXTURE is certainly no exception.

    The intention here was to derive as much informativeness from ADMIXTURE as is currently possible. As you pointed out, the accuracy of the numbers are reliant on the methodology used to generate them. I suspect these numbers serve as a lower bound regarding what we'll see when Bronze Age aDNA emerges from West, Central and South Asia. Based on the uniparental data f.ex., I suspect the Pamiri Tajiks will be between 45-55% Sintashta-derived.