Biscutella-2

Phänotypische und genetische Variation in Biscutella didyma und anderen Brassicaceen und Anpassung an Umweltveränderungen - ein kombinierter ökologisch-genomischer Ansatz

01.12.2014 bis 30.11.2017

Local adaptation and geographic separation are crucial for the evolution of diversity, and recent whole-genome analyses in humans have revealed evidence for spatial distribution of genetic differences. The forces shaping these patterns are, however, only understood in few cases, because it is generally not known how genetic differentiation arises in the first place. Top-down approaches can point to regions of the genome under selection in the recent past, but they rarely identify the responsible genes and the selected traits. Conversely, ecological studies on local adaptation have made little use of the progress in genomics. Here, we combine modern evolutionary ecology with state-of-the-art genomics to study real-time evolution in Biscutella didyma and other Brassicaceae species. We utilize a unique field experiment to test genome-wide differentiation along an aridity gradient, study whether genome-wide signatures of selection are detectable in populations that have been exposed to manipulated precipitation regimes, and whether phenotypic variability in response to selection gradients corresponds to theoretical predictions. Building on the results from phase one, we will study genome-wide selection signature in three independent aridity clines in B. didyma and four related species. In addition, we will phenotype another six related species along the gradients. We will expand our trait measurements to new traits for which genetic pathways are well-known and which exhibit clines along the climate gradient: stomata and trichome density, herbivore defense, and selfing rates. By focusing on adaptive traits with well-characterized genetic networks, we will not only identify selected genes, but answer to how adaptive potential is being realized in independent comparisons. Our findings will enable us to develop models of adaptive capacity under predicted climate change.