In this project, we study the mechanisms behind the long-term adaptation of human populations to their local environments. In numerous instances, traits involved in local adaptation are “complex”, i.e. determined by multiple genes and loci (modification of metabolic pathways in response to diet changes, adaptation of immune response to new pathogens, ...). One of the major mechanisms by which this adaptation occurs is polygenic adaptation. In this scenario, beneficial alleles at several loci, each with a small effect on the trait value, are selected at the same time. At the molecular level, this is reflected by slight increases in beneficial allele frequencies in the population, and most of the time, by very attenuated molecular signatures (decrease in heterozygosity and increase in haplotype length around the selected loci). For this reason, polygenic selection signatures are very difficult to detect using traditional population genetics methods. Several approaches have thus been developed, which consist in combining signatures of positive selection across functionally homogeneous sets of genes or variants. However, recent studies have shown that most of the genetic bases of complex traits were located in regulatory regions such as promoters or enhancers, which are often poorly functionally characterized. Their role in local adaptation is thus poorly understood.
In this project, we aim to (i) combine network biology and population genetics methods in order to develop new tools to detect polygenic selection signatures in regulatory regions, and (ii) characterize biological functions that evolve under local polygenic adaptation in humans by applying these tools to data from of the Genotype-Tissue Expression (GTEx, https://www.gtexportal.org/home/) project.
With these results, we aim at providing to the population genetics community effective tools to study polygenic adaptation. Second, it will improve our general understanding of the extent to which polygenic adaptation has been shaping the human genetic diversity. This will provide new information about the history of human populations and how they adapted to their local environment. Finally, susceptibility to complex diseases is thought to be partially linked to local adaptation (autoimmune diseases for example, are believed to be the result of selection for strong immune defenses against pathogens). Better understanding the evolutionary mechanisms underlying local adaptation of human population should thus allow us to better understand the genetic bases of complex diseases.
Tools and Pipelines
All tools and pipelines developped during this project are available on github: https://github.com/maudf/PATTERNS
Maud Fagny and Frédéric Austerlitz (2021). Polygenic Adaptation: Integrating Population Genetics and Gene Regulatory Networks. Trends in Genetics. doi:10.1016/j.tig.2021.03.005.
Marie Skłodowska-Curie Action – Individual Fellowship PATTERNS 845083. https://cordis.europa.eu/project/id/845083