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Recent improvements in high-throughput genotyping and sequencing technologieshave afforded the collection of massive, genome-wide datasets of DNAinformation from hundreds of thousands of individuals. These datasets, in turn,provide unprecedented opportunities to reconstruct the history of humanpopulations and detect genotype-phenotype association. Recently developedcomputational methods can identify long-range chromosomal segments that areidentical across samples, and have been transmitted from common ancestors thatlived tens to hundreds of generations in the past. These segments revealgenealogical relationships that are typically unknown to the carryingindividuals. In this work, we demonstrate that such identical-by-descent (IBD)segments are informative about a number of relevant population geneticsfeatures: they enable the inference of details about past population sizefluctuations, migration events, and they carry the genomic signature of naturalselection. We derive a mathematical model, based on coalescent theory, thatallows for a quantitative description of IBD sharing across purportedlyunrelated individuals, and develop inference procedures for the reconstructionof recent demographic events, where classical methodologies are statisticallyunderpowered. We analyze IBD sharing in several contemporary human populations,including representative communities of the Jewish Diaspora, Kenyan Maasaisamples, and individuals from several Dutch provinces, in all cases retrievingevidence of fine-scale demographic events from recent history. Finally, weexpand the presented model to describe distributions for those sites in IBDshared segments that harbor mutation events, showing how these may be used forthe inference of mutation rates in humans and other species.

Population genetics of identity by descent