  Recent improvements in high-throughput genotyping and sequencing technologies
have afforded the collection of massive, genome-wide datasets of DNA
information from hundreds of thousands of individuals. These datasets, in turn,
provide unprecedented opportunities to reconstruct the history of human
populations and detect genotype-phenotype association. Recently developed
computational methods can identify long-range chromosomal segments that are
identical across samples, and have been transmitted from common ancestors that
lived tens to hundreds of generations in the past. These segments reveal
genealogical relationships that are typically unknown to the carrying
individuals. In this work, we demonstrate that such identical-by-descent (IBD)
segments are informative about a number of relevant population genetics
features: they enable the inference of details about past population size
fluctuations, migration events, and they carry the genomic signature of natural
selection. We derive a mathematical model, based on coalescent theory, that
allows for a quantitative description of IBD sharing across purportedly
unrelated individuals, and develop inference procedures for the reconstruction
of recent demographic events, where classical methodologies are statistically
underpowered. We analyze IBD sharing in several contemporary human populations,
including representative communities of the Jewish Diaspora, Kenyan Maasai
samples, and individuals from several Dutch provinces, in all cases retrieving
evidence of fine-scale demographic events from recent history. Finally, we
expand the presented model to describe distributions for those sites in IBD
shared segments that harbor mutation events, showing how these may be used for
the inference of mutation rates in humans and other species.
