Data from: Genomic divergence across ecological gradients in the Central African rainforest songbird (Andropadus virens)
Zhen, Ying et al. (2017), Data from: Genomic divergence across ecological gradients in the Central African rainforest songbird (Andropadus virens), Dryad, Dataset, https://doi.org/10.5061/dryad.8n8t0
The little greenbul, a common rainforest passerine from sub-Saharan Africa, has been the subject of long-term evolutionary studies to understand the mechanisms leading to rainforest speciation. Previous research found morphological and behavioural divergence across rainforest–savannah transition zones (ecotones), and a pattern of divergence with gene flow suggesting divergent natural selection has contributed to adaptive divergence and ecotones could be important areas for rainforests speciation. Recent advances in genomics and environmental modelling make it possible to examine patterns of genetic divergence in a more comprehensive fashion. To assess the extent to which natural selection may drive patterns of differentiation, here we investigate patterns of genomic differentiation among populations across environmental gradients and regions. We find compelling evidence that individuals form discrete genetic clusters corresponding to distinctive environmental characteristics and habitat types. Pairwise FST between populations in different habitats is significantly higher than within habitats, and this differentiation is greater than what is expected from geographic distance alone. Moreover, we identified 140 SNPs that showed extreme differentiation among populations through a genomewide selection scan. These outliers were significantly enriched in exonic and coding regions, suggesting their functional importance. Environmental association analysis of SNP variation indicates that several environmental variables, including temperature and elevation, play important roles in driving the pattern of genomic diversification. Results lend important new genomic evidence for environmental gradients being important in population differentiation.
National Science Foundation, Award: PIRE #1243524, DEB-9726425, IRCEB9977072