Insights into human adaptation from ancient DNA

Abstract

Author Manuscript Ancient DNA (aDNA) has revolutionized our ability to study human evolution by enabling the direct observation of genetic changes through time. This has reshaped our understanding of human adaptation and its relevance for modern health and disease. In recent years, high-quality ancient genomes and large datasets have made it possible to track allele frequency dynamics and identify episodes of natural selection with unprecedented resolution. Here, we synthesize insights from recent studies that have systematically investigated how humans adapted to shifts in diet, mobility, pathogen exposure, and environment. We summarize the approaches used to detect selection in aDNA, examine the role of major migration and admixture events, and connect results across time periods and archaeological contexts. Finally, we outline future challenges and opportunities that need to be addressed for aDNA studies to provide new insights into human adaptation that could not be inferred from present-day genomes alone. Author Manuscript Keywords Ancient DNA; natural selection; human adaptation; population genetics; allele frequency dynamics; migration and admixture; evolutionary history Author Manuscript Interest in natural selection and adaptation has long been central to evolutionary biology1. Understanding how selective pressures shape biological diversity has been key to explaining the origins of species, the maintenance of genetic variation, and the emergence of complex traits2–6. In humans, questions about adaptation touch directly on our biology, behavior, and health, providing insight into how we have responded to changing diets, climates, pathogens, and ways of life over time7. As genomic technologies advanced, particularly with the rise of population-scale sequencing projects, such as the HapMap8 and 1000 Genomes9, this long-standing focus began to shift from studying adaptation at the phenotypic level to investigating its genetic basis. Genome-wide genetic variation data enabled the detection of selection footprints, such as reduced diversity, extended haplotypes, and elevated population differentiation, using statistical methods10–12. This, in turn, sparked growing interest in identifying the specific genes under selection and understanding their functional roles * Correspondence: Christian D. Huber, Mueller Laboratory, Room 512A, University Park, PA 16802, USA, cdh5313@psu.edu.