People in the Computational and Molecular Population Genetics (CMPG) lab use molecular techniques, theoretical developments, and computer simulations to reconstruct the demographic history of populations and species from genetic data, and to test between alternative evolutionary scenarios.
We explore the genomic diversity of voles and humans in order to discover which genes have recently responded to selection, for instance to adapt to new environments.
We are also interested in quantifying the effect of range expansions and colonisation processes on genetic diversity, since these demographic events can lead to molecular signatures resembling those of selection.
We also develop and maintain computer programs to study and simulate the genetic diversity of populations, infer demographic parameters under complex scenarios, and detect loci under selection from genome scan.
The CMPG lab is affiliated to the Swiss Institute of Bioinformatics.
eLife - Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences
A recent study from Pouyet et. al. shows that less than 5% of the human genome can be considered as "neutral" which is a striking finding given that actual coding genes only account for 1% of the human genome. Strong positive relationship is found between local recombination rate and genetic diversity: background selection is the primary process that skews genomic diversity, though GC-biased gene conversion also contributes. The paper determineds that only ~2.5% of SNPs act effectively neutrally and suggests that alternative definitions of neutrality lead to skewed allele frequency spectra which then have downstream affects when attempting to infer demographic history.