Himalayan whole-genome sequences provide insight into population formation and adaptation

High-altitude environments pose substantial challenges for human survival and reproduction, attracting considerable attention to the demographic and adaptive histories of high-altitude populations. Previous work focused mainly on Tibetans, establishing their genetic relatedness to East Asians and their genetic adaptation to high altitude, especially at EPAS1. Here, we present 87 new whole-genome sequences from 16 Himalayan populations and the insight they provide into the genomic history of the region. We show that population structure in the Himalayas began to emerge as early as 10,000 years ago, predating archaeological evidence of permanent habitation above 2,500 meters by approximately 6,000 years. The high prevalence of the introgressed adaptive EPAS1 haplotype in all high-altitude populations today supports a shared genetic origin and its importance for survival in this region. We also identify additional selection signals in genes associated with hypoxia, physical activity, immunity and metabolism which could have facilitated adaptation to the harsh environment. Over time, increasing genetic structure led to the diverse and strongly differentiated ethnic groups observed today, most of which maintained small population sizes throughout their history or experienced severe bottlenecks. Between 6,000 and 3,000 years ago, a few uniparental lineages became predominant, likely coinciding with the advent of agriculture, although significant population growth was not observed in the Himalayas except in the Tibetans. In more recent times, we detect bidirectional gene flow between high-altitude and lowland groups, occurring on both sides of the Himalayan range. The timing of this admixture aligns with the rise and expansion of historical regional powers, particularly during the Tibetan Empire and the northern Indian Gupta Empire. In the past few centuries, migrations to the Himalayas seem to have occurred alongside conflicts and population displacements in nearby regions and show some sex bias.