Reconstructing the population history of Sinhalese, the major ethnic group in Śrī Laṅkā:
Interestingly, we found an unexpected excess of smaller chunks sharing between Marāṭhā and Sinhala (>16%) than the Marāṭhā and STU, thus supporting the linguistic hypothesis of Geiger, Turner and van Driem. To confirm the excess sharing, we looked for the population which was sharing maximum IBD with Sinhala and STU.
Looks like confirmation of Sinhala western Indian origins rather than eastern Indian origins.
The full version of this paper is out, South Asian medical cohorts reveal strong founder effects and high rates of homozygosity. It’s not the best for understanding population structure because they focus on within South Asia variation, but it does seem to confirm that among Bengalis there is a cline from west to east, irrespective of religion (see the discussion where they note that Muslims in the west cluster with westerners). I found a PCA in the supplements where I added some explanatory notes. It’s really hard to parse their figures because they really didn’t care, and the Genomes Asia Consortium doesn’t release their data… (their browser sucks)
On the limits of fitting complex models of population history to f-statistics:
These results show that at least with regard to the AG analysis, a key historical conclusion of the study (that the predominant genetic component in the Indus Periphery lineage diverged from the Iranian clade prior to the date of the Ganj Dareh Neolithic group at ca. 10 kya and thus prior to the arrival of West Asian crops and Anatolian genetics in Iran) depends on the parsimony assumption, but the
preference for three admixture events instead of four is hard to justify based on archaeological or other arguments.
Why did the Shinde et al. 2019 AG analysis find support for the IP Iranian-related lineage being the first to split, while our findGraphs analysis did not? The Shinde et al. 2019 study sought to carry out a systematic exploration of the AG space in the same spirit as findGraphs—one of only a few papers in the literature where there has been an attempt to do so—and thus this qualitative difference in findings is notable. We hypothesize that the inconsistency reflects the fact that the deeply-diverging WSHG-related ancestry (Narasimhan et al. 2019) present in the IP genetic grouping at a level of ca. 10% was not taken into account explicitly neither in the AG analysis nor in the admixture-corrected f4-symmetry tests also reported in Shinde et al. (2019).
This piece arguing for the end to cousin marriage in the UK in The Times (driven by Pakistanis) took me to a paper in PLOS One, Genetic and reproductive consequences of consanguineous marriage in Bangladesh:
The mean prevalence of CM in our studied population was 6.64%. Gross fertility was higher among CM families, as compared to the non-CM families (p < 0.05). The rate of under-5 child (U5) mortality was significantly higher among CM families (16.6%) in comparison with the non-CM families (5.8%) (p < 0.01). We observed a persuasive rise of abortion/miscarriage and U5 mortality rates with the increasing level of inbreeding. The value of lethal equivalents per gamete found elevated for autosomal inheritances as compared to sex-linked inheritance. CM was associated with the incidence of several single-gene and multifactorial diseases, and congenital malformations, including bronchial asthma, hearing defect, heart diseases, sickle cell anemia (p < 0.05). The general attitude and perception toward CM were rather indifferent, and very few people were concerned about its genetic burden.
A rate around 5% is in line with my intuition and what I’ve seen elsewhere, though there is wide variance by locality. The best thing about the paper is the chart above, the offspring of first cousin marriage have mortality rates 3 times greater than non-cousin marriages. There are other numbers relating to disease, etc. The paper is good because it’s from a developing country without world-class healthcare (though no longer a total basketcase) so you can see disease risk plainly.
More generally in relation to “cousin marriage”
– I have seen “outbred” Pakistani genomes that look like the product of cousin marriage due to the practice’s frequently earlier on in the pedigree
– This is comparable to some Indian caste groups that practice exogamy (North Indian) on the jati level. The jati has been endogamous so long that everyone has become a second cousin…
Click to see larger version.
A Maharashtra Deshastha Brahmin sent me his sample. He plots with the Maharashtra Kayastha. He’s much more like a South Indian Brahmin than a North Indian Brahmin. The Maharashtra Saraswat Brahmin seems more north shifted.
I got a sample from someone where one parent was a West Bengal Sadgop, and another parent a Baidya with family origins in East Bengal. One hypothesis that I’ve see is that Baidya are basically Brahmins who lost their caste. Genetically this does not seem to be the case. Bengali Brahmins shift considerably toward the steppe samples compared to average Bangladeshis, and this individual does not. Rather, their uniqueness is that they have very little East Asian ancestry compared to the median. This is typical of non-Bramin West Bengalis. It is plausible to me that this individual’s Baidya parent, from East Bengal (Bangal), had more East Asian ancestry than their West Bengali (Ghoti) parent, so you see an average.
Though there are some exceptions, it seems that the non-Brahmnin bhadralok castes did undergo ritual uplift from that of conventional peasant cultivators at some point in Bengal. This seems similar with regard to Kayasthas in UP, but not in Maharashtra, where CKPs seem to have an affinity with Brahmins distinct from the Maratha cultivators.
Update: I found a preprint that pretty much answers all the questions re: Bengalis.
Here is a panel with a UMAP representation of genetic distance, and you see West Bengal is adjacent to Bangladesh. But there is a “tail” of individuals that are parallel to South Indians.
This UMAP makes clear Bengali Brahmins are distinct from Kayasthas and Sadgop. These populations seem roughly similar to most Bangladeshis except they are shift over, and I assume this means less East Asian ancestry, as PCA seems to how:
The mitochondrial genomes of two Pre-historic Hunter Gatherers in Sri Lanka:
Sri Lanka is an island in the Indian Ocean connected by the sea routes of the Western and Eastern worlds. Although settlements of anatomically modern humans date back to 48,000 years, to date there is no genetic information on pre-historic individuals in Sri Lanka. We report here the first complete mitochondrial sequences for Mesolithic hunter-gatherers from two cave sites. The mitochondrial haplogroups of pre-historic individuals were M18a and M35a. Pre-historic mitochondrial lineage M18a was found at a low prevalence among Sinhalese, Sri Lankan Tamils, and Sri Lankan Indian Tamil in the Sri Lankan population, whereas M35a lineage was observed across all Sri Lankan populations with a comparatively higher frequency among the Sinhalese. Both haplogroups are Indian derived and observed in the South Asian region and rarely outside the region.
No idea why this comes out of Sri Lanka first, and not India (bigger country), but it is what it is.
I noticed something interesting a few weeks ago in the supplements of the Genomes Asian 1000K paper. Look at where the Toda are on the PCA.
Now look at the Indus Valley samples I have….
I don’t have access to the Toda samples. But there’s a lot of evidence that this is a very unique population that resembles the IVC population in having less AASI but not too much (if any) steppe.
Sometimes people pass me data. Turns out Rajasthani Brahmins are quite different from UP Brahmins (more northwest-shifted). In this, they are like Pandits. In contrast, Bihar Babhans are just like UP Brahmins, who don’t seem to have much structure. Gujarati Brahmins are between South Indian Brahmins and North Indian Brahmins, and closer to the latter, while Maharashtra Brahmins seem more like South Indian Brahmins.