Differentiated adaptative genetic architecture and language-related demographical history in South China inferred from 619 genomes from 56 populations

Abstract

Background The underrepresentation of human genomic resources from Southern Chinese populations limited their health equality in the precision medicine era and complete understanding of their genetic formation, admixture, and adaptive features. Besides, linguistical and genetic evidence supported the controversial hypothesis of their origin processes. One hotspot case was from the Chinese Guangxi Pinghua Han people (GPH), whose language was significantly similar to Southern Chinese dialects but whose uniparental gene pool was phylogenetically associated with the indigenous Tai-Kadai (TK) people. Here, we analyzed genome-wide SNP data in 619 people from four language families and 56 geographically different populations, in which 261 people from 21 geographically distinct populations were first reported here. Results We identified significant population stratification among ethnolinguistically diverse Guangxi populations, suggesting their differentiated genetic origin and admixture processes. GPH shared more alleles related to Zhuang than Southern Han Chinese but received more northern ancestry relative to Zhuang. Admixture models and estimates of genetic distances showed that GPH had a close genetic relationship with geographically close TK compared to Northern Han Chinese, supporting their admixture origin hypothesis. Further admixture time and demographic history reconstruction supported GPH was formed via admixture between Northern Han Chinese and Southern TK people. We identified robust signatures associated with lipid metabolisms, such as fatty acid desaturases (FADS) and medically relevant loci associated with Mendelian disorder (GJB2) and complex diseases. We also explored the shared and unique selection signatures of ethnically different but linguistically related Guangxi lineages and found some shared signals related to immune and malaria resistance. Conclusions Our genetic analysis illuminated the language-related fine-scale genetic structure and provided robust genetic evidence to support the admixture hypothesis that can explain the pattern of observed genetic diversity and formation of GPH. This work presented one comprehensive analysis focused on the population history and demographical adaptative process, which provided genetic evidence for personal health management and disease risk prediction models from Guangxi people. Further large-scale whole-genome sequencing projects would provide the entire landscape of southern Chinese genomic diversity and their contributions to human health and disease traits.

Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources

“…Recent studies utilizing ancient genomic resources have revealed that human expansion from regions such as the Mongolia Plateau, Amur River Basin, Yellow River Basin, Yangtze River Basin, and the Eurasian Steppe has gradually facilitated complex patterns of population structure and genetic diversity in East Asia [ 5 – 8 ]. Evolutionary reconstructions among ethnolinguistically modern populations suggest that differentiated selective pressures and admixture landscapes have enriched the complexity of the population history and biological adaptations of East Asians [ 6 , 9 – 12 ]. Yang et al identified genomic substructures between ancient northern East Asians (ANEAs) and ancient southern East Asians (ASEAs).…”

Editorial: Full landscape of human genomic diversity and its impact on precision medicine

“…However, the current focus of large-scale genetic research on European populations is limiting our understanding ( Bick et al, 2024 ). The underrepresentation of non-European populations in these studies not only hampers the development of disease risk models but also prevents us from fully capturing the vast spectrum of human genetic diversity ( Sun et al, 2023 ; He et al, 2024 ; Li et al, 2024 ; Sun et al, 2024 ). This is because demographic history, linkage disequilibrium, and adaptive evolutionary histories vary significantly across different continental groups.…”