Biology subjects

Szilagyi, S. M.

Publications and source records attributed to Szilagyi, S. M..

3 recordsLinked to original sources

bioRxiv2019

Detecting selection from linked sites using an F-model

Allele frequencies vary across populations and loci, even in the presence of migration. While most differences may be due to genetic drift, divergent selection will further increase differentiation at some loci. Identifying those is key in studying local adaptation, but remains statistically challenging. A particularly elegant way to describe allele frequency differences among populations connected by migration is the F-model, which measures differences in allele frequencies by population specific FST coefficients. This model readily accounts for multiple evolutionary forces by partitioning FST coefficients into locus and population specific components reflecting selection and drift, respectively. Here we present an extension of this model to linked loci by means of a hidden Markov model (HMM) that characterizes the effect of selection on linked markers through correlations in the locus specific component along the genome. Using extensive simulations we show that our method has up to two-fold the statistical power of previous implementations that assume sites to be independent. We finally evidence selection in the human genome by applying our method to data from the Human Genome Diversity Project (HGDP).

genomics↗

bioRxiv2016

Joint inference of demography and mutation rates from polymorphism data and pedigrees

Inference of demography and mutation rates is of major interest but difficult because genetic data is only informative about the population mutation rate, the product of the effective population size times the mutation rate, and not about these quantities individually. Here we show that this limitation can be overcome by combining genetic data with pedigree information. To successfully use pedigree data, however, important aspects of real populations such as the presence of two sexes, unbalanced sex ratios and overlapping generations have to be taken into account. We present here an extension of the classic Wright-Fisher model accounting for these effects and show that the coalescent process under this model reduces to the classic Kingman coalescent with specific scaling parameters. We further derive the probability of a pedigree under that model and show how pedigree data can thus be used to infer demographic parameters. Finally, we present a computationally efficient inference approach combining pedigree information and genetic data summarized by the site frequency spectrum (SFS) that allows for the joint inference of the mutation rate, sex-specific population sizes and the fraction of overlapping generations. Using simulations we then show that these parameters can be accurately inferred from pedigrees spanning just a few generations, as are available for many species. We finally discuss future possible extensions of the model and inference framework necessary for applications to wild and domesticated species, namely the account for more complex demographies and the uncertainty in assigning pedigree individuals to specific generations.

genetics↗

bioRxiv2016

Inference of evolutionary jumps in large phylogenies using Levy processes

While it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriini parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson's hypothesis.

evolutionary biology↗