Meeting Abstract
S4-1.5 Saturday, Jan. 5 Evolutionary and ecological genomics in a changing world: integrating Next-Gen data with environmental variation to reveal local adaptation PESPENI, M.H.; Indiana University mpespeni@indiana.edu
Understanding how populations respond to and are shaped by their environment is of fundamental importance to revealing the mechanisms of local adaptation in general and for predicting the impact of a rapidly changing climate in particular. Species distributed across heterogeneous landscapes present rich opportunities and challenges for uncovering the targets of natural selection, particularly when there is substantial gene flow among populations, as is the case in many marine, plant, insect, and microbial species. These ecologically interesting species have until recently been without the genomic resources needed to comprehensively explore their physiological and genetic means of persistence in complex ecosystems and changing environments. Here I highlight a recently developed pipeline for generating and analyzing RNAseq data. Using several case studies in the purple sea urchin, Strongylocentrotus purpuratus, I illustrate how polymorphism, gene expression, gene function, and environmental data can be integrated to identify physiological phenotypes while simultaneously testing for signals of natural selection. This broad melding of very different data sets identifies adaptive phenotypes in gene regulation as well as signals of selection in specific genes across environmental mosaics. This approach detected extensive selection on innate immunity proteins in areas of elevated disease incidence, showed strong population differentiation of biomineralization proteins in response to elevated CO2, and showed distinct gene regulatory adaptations in different coastal populations. Collectively, these efforts illustrate how genomic, transcriptomic, and environmental data can be integrated to reveal the targets of natural selection in complex environmental mosaics and can help evaluate the possibility of future evolution to climate change.
