How Extreme Were Caste Founder Events In South Asia

Endogamy, estimated to have lasted about 2,000 years, has produced genetically distinguishable differences between varna in the Indian caste system which is the main several layers of the caste system (with broad regional and linguistic divides as well) and distinctive levels in recessive gene disease risk associated with endogamy in a population with a small founding population (not true inbreeding) in a significant number of jati which are far more specific sub-castes with more specific occupational and ethnic associations within a varna.

Razib emphasizes the fact that this is inconsistent with the notion that caste only becomes significant around the time of the British colonial period as one leading account suggests. My own priors, based on what I was taught in the relevant classes in college, meanwhile, are for endogamy to have arisen not long after the Bronze Age, so 2,000 years seems young to me.

The more than 1.5 billion people who live in South Asia are correctly viewed not as a single large population, but as many small endogamous groups. We assembled genome-wide data from over 2,800 individuals from over 260 distinct South Asian groups. We identify 81 unique groups, of which 14 have estimated census sizes of more than a million, that descend from founder events more extreme than those in Ashkenazi Jews and Finns, both of which have high rates of recessive disease due to founder events. We identify multiple examples of recessive diseases in South Asia that are the result of such founder events. This study highlights an under-appreciated opportunity for reducing disease burden among South Asians through the discovery of and testing for recessive disease genes.

Nathan Joel Nakasuka, et al., "The promise of disease gene discovery in South Asia" ((June 6, 2017) doi: https://doi.org/10.1101/047035

There paper estimates that there are 4,600 populations in South Asia which are defined by endogamy and comparable to the 260 groups examined in this study.

I have also rarely seen a paper with so little body text. In relegates almost all of its detailed conclusions to supplementary materials. There is almost no discussion the populations studied from an interdisciplinary perspective, and there is almost no effort to see a larger context and the root these findings in a meaningful narrative that can be fit to historical reality as a cross-check to confirm that the findings are robust.

Another recent paper takes on South Asian population structure as its primary focus:

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification operating in concert. To date, no study has attempted to model and evaluate how these evolutionary forces have interacted to shape the patterns of genetic diversity within India. Geography has been shown to closely correlate with genetic structure in other parts of the world. However, the strict endogamy imposed by the Indian caste system, and the large number of spoken languages add further levels of complexity. 

We merged all publicly available data from the Indian subcontinent into a data set of 835 individuals across 48,373 SNPs from 84 well-defined groups. Bringing together geography, sociolinguistics and genetics, we developed COGG (Correlation Optimization of Genetics and Geodemographics) in order to build a model that optimally explains the observed population genetic sub-structure. 

We find that shared language rather than geography or social structure has been the most powerful force in creating paths of gene flow within India. Further investigating the origins of Indian substructure, we create population genetic networks across Eurasia. We observe two major corridors towards mainland India; one through the Northwestern and another through the Northeastern frontier with the Uygur population acting as a bridge across the two routes. Importantly, network, ADMIXTURE analysis and f3 statistics support a far northern path connecting Europe to Siberia and gene flow from Siberia and Mongolia towards Central Asia and India.

Aritra Bose, et al., "Dissecting Population Substructure in India via Correlation Optimization of Genetics and Geodemographics" bioRxiv (July 17, 2017) doi: https://doi.org/10.1101/164640