Identifying genes that enable species to adapt to their environments is one of the main goals of evolutionary research. Most adaptation events are reached via so-called polygenic adaptation through changes in many genes. The bad news is that, statistically, it is extremely challenging to uncover the subtle signals of polygenic adaptation from genomic data. This is because different loci (genes at specific positions on a chromosome) may interact with each other in a potentially unequal, non-linear way.
Identifying the signature of selection for adaptation
“The main goal of FORGENET was to explore the statistical performance of tests to detect the genomic signature of polygenic adaptation in simulated and real-world data sets,” outlines Katalin Csilléry, Marie Skłodowska-Curie fellow at the University of Zurich. Pairwise tests were applied to detect non-random associations between loci among populations. This reveals the signature selection leaves behind that indicates adaptation. “During the execution phase, we implemented a model of gene interactions in Nemo, an individual-based forward time simulator. This new tool explicitly accounts for gene interactions among loci in affecting a trait controlled by many genes and is able to deliver genome-scale data for a large variety of demographic scenarios,” Csilléry explains. Exploring the effect of gene interactions on adaptation, several key parameters were varied. These included the degree of gene flow, mutation rate, the recombination rate, the selection variance and the strength of gene interactions between loci. “Significantly, we found that gene interactions can foster adaptation in a changing environment,” Csilléry emphasises. Populations adapted faster and reached the phenotypic optimum more closely in comparison to a scenario where each gene acts independently. The next step was to look if these results obtained by simulations could be confirmed in real-world data. “In collaboration with Olivier Francois, professor at the University of Grenoble, and with Pär Ingvarsson, professor at the Swedish University of Agricultural Sciences, we are applying pairwise tests in adaptation to photoperiod (periods of light and dark) in Arabidopsis thaliana and European aspen (Populus tremula).” Data was collected from populations from the same regions of Sweden for the two species. Photoperiod is supposedly the main selective driver of the timing of bud set between northern and southern Swedish aspen populations. This analysis is still in progress.
Forest trees’ drought tolerance is particularly relevant today
FORGENET assessed drought tolerance of an ecologically and economically important European conifer: silver fir (Abies alba). They did this using an evolutionary quantitative (many genes in control) genetic approach. Populations originating from areas of low soil water-holding capacity were more drought tolerant than others. “However, these populations also had a slow growth rate, which could be in conflict with foresters’ interests,” she adds. Many forest tree species are endangered by climate change at their current growing habitats and estimating their adaptability is an important European research priority. Csilléry sums up: “The results of this study can now be used to select populations for genomic data to identify gene networks that play a role in adaptation to drought stress response.” The results have been published in a peer-reviewed paper.
FORGENET distributes its special brand of Big Data genomic analysis
A kick-off summer school focused on polygenic adaptation, and a research symposium on ‘Detecting the Genomic Signal of Polygenic Adaptation and the Role of Epistasis in Evolution’ disseminated the FORGENET approach to genomic data analysis. A peer-reviewed publication in Molecular Ecology sports the same title as the symposium.
FORGENET, polygenic adaptation, selection, drought tolerance, forest, gene network