Jaison Jeevan Sequeira, M Chaitra, Ananya Rai N R, M Sudeepthi, R Shalini, Mohammed S Mustak, Jagriti Khanna, Shivkant Sharma, Rajendra V E Chilukuri, George van Driem, Pankaj Shrivastava
{"title":"Y chromosome STR variation reveals traditional occupation based population structure in India","authors":"Jaison Jeevan Sequeira, M Chaitra, Ananya Rai N R, M Sudeepthi, R Shalini, Mohammed S Mustak, Jagriti Khanna, Shivkant Sharma, Rajendra V E Chilukuri, George van Driem, Pankaj Shrivastava","doi":"10.1101/2024.08.28.610024","DOIUrl":null,"url":null,"abstract":"Earlier models of grouping Indian populations were based on language families, social stratification and geographical location. Such grouping system has often resulted in oversimplification of ancestry inferences. Moreover, we do not find many studies focused on studying the variation within these groups and the role of past demographic events in shaping them. We analysed the Y-chromosome Short Tandem Repeats haplotypes from 8153 males from India and Eurasia to explore the impact of Holocene migration on the Indian gene pool. We used haplotype variation and date estimates to understand the characteristics of each haplogroup with respect to the different grouping models. Our findings show that the Neolithic agricultural expansion has had a strong influence in shaping the male gene pool of the Indian subcontinent. Haplogroups F, L and R1a contribute greatly towards stratifying Indian populations as hunter-gatherer related, farming-related and priestly groups respectively. Although the caste system enforced endogamy, a traditional occupation based admixture existed since the Neolithic times. Dispersal of haplogroup L from the Near East played a major role in the formation of an agriculturist population that formed an intermediary between the primitive tribes and the R1a-rich priestly group. This study shows that the frequency of R1a in the hunter-gatherer tribes (1.5%) is much lower than previously reported based on other models of population clustering.","PeriodicalId":501246,"journal":{"name":"bioRxiv - Genetics","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Genetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.28.610024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Earlier models of grouping Indian populations were based on language families, social stratification and geographical location. Such grouping system has often resulted in oversimplification of ancestry inferences. Moreover, we do not find many studies focused on studying the variation within these groups and the role of past demographic events in shaping them. We analysed the Y-chromosome Short Tandem Repeats haplotypes from 8153 males from India and Eurasia to explore the impact of Holocene migration on the Indian gene pool. We used haplotype variation and date estimates to understand the characteristics of each haplogroup with respect to the different grouping models. Our findings show that the Neolithic agricultural expansion has had a strong influence in shaping the male gene pool of the Indian subcontinent. Haplogroups F, L and R1a contribute greatly towards stratifying Indian populations as hunter-gatherer related, farming-related and priestly groups respectively. Although the caste system enforced endogamy, a traditional occupation based admixture existed since the Neolithic times. Dispersal of haplogroup L from the Near East played a major role in the formation of an agriculturist population that formed an intermediary between the primitive tribes and the R1a-rich priestly group. This study shows that the frequency of R1a in the hunter-gatherer tribes (1.5%) is much lower than previously reported based on other models of population clustering.