@article {Wilton054957, author = {Peter R. Wilton and Pierre Baduel and Matthieu M. Landon and John Wakeley}, title = {Population structure and coalescence in pedigrees: comparisons to the structured coalescent and a framework for inference}, elocation-id = {054957}, year = {2016}, doi = {10.1101/054957}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Contrary to what is often assumed in population genetics, independently segregating loci do not have completely independent ancestries, since all loci are inherited through a single, shared population pedigree. Previous work has shown that the non-independence between gene genealogies of independently segregating loci created by the population pedigree is weak in panmictic populations, and predictions made from standard coalescent theory are accurate for populations that are at least moderately sized. Here, we investigate patterns of coalescence in pedigrees of structured populations. We find that population structure creates deviations away from the predictions of standard theory that persist on a longer timescale than in panmictic populations. Nevertheless, we find that the structured coalescent provides a reasonable approximation for the coalescent process in structured population pedigrees so long as migration events are moderately frequent and there is no admixture in the recent pedigree of the sample. When the sampled individuals have admixed ancestry, we find that distributions of coalescence in the sample can be modeled as a mixture of distributions from different sample configurations. We use this observation to motivate a maximum-likelihood approach for inferring migration rates and population sizes jointly with features of the recent pedigree such as admixture and relatedness. Using simulation, we demonstrate that our inference framework accurately recovers long-term migration rates in the presence of recent admixture in the sample pedigree.}, URL = {https://www.biorxiv.org/content/early/2016/05/24/054957}, eprint = {https://www.biorxiv.org/content/early/2016/05/24/054957.full.pdf}, journal = {bioRxiv} }