Abstract
BACKGROUND: Ancient northern East Asians (ANEA) from the Yellow River region, who pioneered millet cultivation, play a crucial role in understanding the origins of ethnolinguistically diverse populations in modern China and the entire landscape of deep genetic structure and variation discovery in modern East Asians. However, the direct links between ANEA and geographically proximate modern populations, as well as the biological adaptive processes involved, remain poorly understood. RESULTS: Here, we generated genome-wide SNP data for 264 individuals from geographically different Han populations in Shandong. An integrated genomic resource encompassing both modern and ancient East Asians was compiled to examine fine-scale population admixture scenarios and adaptive traits. The reconstruction of demographic history and hierarchical clustering patterns revealed that individuals from the Shandong Peninsula share a close genetic affinity with ANEA, indicating long-term genetic continuity and mobility in the lower Yellow River basin since the early Neolithic period. Biological adaptive signatures, including those related to immune and metabolic pathways, were identified through analyses of haplotype homozygosity and allele frequency spectra. These signatures are linked to complex traits such as height and body mass index, which may be associated with adaptations to cold environments, dietary practices, and pathogen exposure. Additionally, allele frequency trajectories over time and a haplotype network of two highly differentiated genes, ABCC11 and SLC10A1, were delineated. These genes, which are associated with axillary odor and bilirubin metabolism, respectively, illustrate how local adaptations can influence the diversification of traits in East Asians. CONCLUSIONS: Our findings provide a comprehensive genomic dataset that elucidates the fine-scale genetic history and evolutionary trajectory of natural selection signals and disease susceptibility in Han Chinese populations. This study serves as a paradigm for integrating spatiotemporally diverse ancient genomes in the era of population genomic medicine.