Title: Inference of Population Size History from Genome-Wide Molecular Data

Abstract:

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. In this context, several methods that take advantage of whole-genome sequences have been recently published, including the popular PSMC or MSMC.

In the first part of the talk, I will present the popsizeABC method. Based on approximate Bayesian computation, this method allows using large samples of complete genomes, in contrast to SMC approaches, and combines information from both allele frequencies and LD.

It provides accurate estimations of past population sizes from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. Another important question concerning the estimation of past population size changes, is the influence of population structure.

In 2016, we showed that, for any model of population structure, it is always possible to find a panmictic model with a particular function of population size changes, having exactly the same distribution of T2 (the coalescence time for a sample of size two) than the structured model. We called this function the IICR,

because the value of this function (i.e. the population size) at time t before sampling is actually the Inverse of the Instantaneous Coalescent Rate in the population at this time.

In the second part of the talk, I will present several recent developments around this idea.