Inferring Demographic History Using Genomic Data

Abstract

Characterizing population histories has been a major focus in evolution- ary and conservation biology for decades. Driven by a desire to understand popula- tion histories, researchers have been modeling simple demographic scenarios with genetic data since the 1970s. In the last decade, the availability of genomic data and the number of demographic inference methods have dramatically increased and constitute a continuously evolving sub-discipline within population genetics. Genome sequences—both reduced representation and whole-genome sequencing and re-sequencing—contain a trove of information related to population histories and permit reconstructing complex demographic scenarios. In combination with new powerful and flexible analytical methods, population demographic inference from genomic data has revealed surprising, dynamic, and conservation-relevant histories. This chapter discusses recent advancements in demographic inference made possible by genome sequence and new analytical tools. As the theory and models of demo- graphic inference have matured, and data sets have grown, likewise has the recog- nition of limitations and confounding effects. We caution that the increasing sophistication of methods should not override the critical evaluation of the researcher. Demographic inferences with genomic data offer powerful windows into the past but we encourage users to recognize inherent limitations of model assumptions, use simulations to identify potential biases, and include complemen- tary and supporting analyses.