We are devoted to the study of theoretical population genetics. The goal of population genetics is to identify and understand the forces that produce and maintain genetic variation in natural populations. These forces include mutation (also recombination and gene conversion), natural selection, various kinds of population structure (e.g. subdivision with migration), and the random fluctuations of gene frequencies through time known as genetic drift. We study these forces mathematically, using both analysis and computation. We also develop statistical methods to make inferences about these forces from DNA sequences or other kinds of genetic data. For more information about specific areas of research, follow the leads to lab members.


Harney É, Patterson N, Reich D, Wakeley J. Assessing the performance of qpAdm: a statistical tool for studying population admixture. Genetics. 2021;iyaa045.Abstract
qpAdm is a statistical tool for studying the ancestry of populations with histories that involve admixture between two or more source populations. Using qpAdm, it is possible to identify plausible models of admixture that fit the population history of a group of interest and to calculate the relative proportion of ancestry that can be ascribed to each source population in the model. Although qpAdm is widely used in studies of population history of human (and nonhuman) groups, relatively little has been done to assess its performance. We performed a simulation study to assess the behavior of qpAdm under various scenarios in order to identify areas of potential weakness and establish recommended best practices for use. We find that qpAdm is a robust tool that yields accurate results in many cases, including when data coverage is low, there are high rates of missing data or ancient DNA damage, or when diploid calls cannot be made. However, we caution against co-analyzing ancient and present-day data, the inclusion of an extremely large number of reference populations in a single model, and analyzing population histories involving extended periods of gene flow. We provide a user guide suggesting best practices for the use of qpAdm.
Salagnac O, Wakeley J. The consequences of switching strategies in a two-player iterated survival game. Journal of Mathematical Biology. 2021;82 :17.Abstract
We consider two-player iterated survival games in which players are able to switch from a more cooperative behavior to a less cooperative one at some step of an n-step game.  Payoffs are survival probabilities and lone individuals have to finish the game on their own.  We explore the potential of these games to support cooperation, focusing on the case in which each single step is a Prisoner's Dilemma.  We find that incentives for or against cooperation depend on the number of defections at the end of the game, as opposed to the number of steps in the game.  Broadly, cooperation is supported when the survival prospects of lone individuals are relatively bleak.  Specifically, we find three critical values or cutoffs for the loner survival probability which, in concert with other survival parameters, determine the incentives for or against cooperation.  One cutoff determines the existence of an optimal number of defections against a fully cooperative partner, one determines whether additional defections eventually become disfavored as the number of defections by the partner increases, and one determines whether additional cooperations eventually become favored as the number of defections by the partner increases.  We obtain expressions for these switch-points and for optimal numbers of defections against partners with various strategies.  These typically involve small numbers of defections even in very long games. We show that potentially long stretches of equilibria may exist, in which there is no incentive to defect more or cooperate more.  We describe how individuals find equilibria in best-response walks among n-step strategies.
Edelman NB, Frandsen PB, Miyagi M, et al. Genomic architecture and introgression shape a butterfly radiation. Science. 2019;366 (6465) :594-599. Publisher's VersionAbstract
We used 20 de novo genome assemblies to probe the speciation history and architecture of gene flow in rapidly radiating Heliconius butterflies. Our tests to distinguish incomplete lineage sorting from introgression indicate that gene flow has obscured several ancient phylogenetic relationships in this group over large swathes of the genome. Introgressed loci are underrepresented in low-recombination and gene-rich regions, consistent with the purging of foreign alleles more tightly linked to incompatibility loci. Here, we identify a hitherto unknown inversion that traps a color pattern switch locus. We infer that this inversion was transferred between lineages by introgression and is convergent with a similar rearrangement in another part of the genus. These multiple de novo genome sequences enable improved understanding of the importance of introgression and selective processes in adaptive radiation.