Population genomics and local adaptation in wild isolates of a model microbial eukaryote

Abstract

Elucidating the connection between genotype, phenotype, and adaptation in wild populations is fundamental to the study of evolutionary biology, yet it remains an elusive goal, particularly for microscopic taxa, which comprise the majority of life. Even for microbes that can be reliably found in the wild, defining the boundaries of their populations and discovering ecologically relevant phenotypes has proved extremely difficult. Here, we have circumvented these issues in the microbial eukaryote Neurospora crassa by using a "reverse-ecology" population genomic approach that is free of a priori assumptions about candidate adaptive alleles. We performed Illumina whole-transcriptome sequencing of 48 individuals to identify single nucleotide polymorphisms. From these data, we discovered two cryptic and recently diverged populations, one in the tropical Caribbean basin and the other endemic to subtropical Louisiana. We conducted high-resolution scans for chromosomal regions of extreme divergence between these populations and found two such genomic "islands." Through growth-rate assays, we found that the subtropical Louisiana population has a higher fitness at low temperature (10 °C) and that several of the genes within these distinct regions have functions related to the response to cold temperature. These results suggest the divergence islands may be the result of local adaptation to the 9 °C difference in average yearly minimum temperature between these two populations. Remarkably, another of the genes identified using this unbiased, whole-genome approach is the well-known circadian oscillator frequency, suggesting that the 2.4°-10.6° difference in latitude between the populations may be another important environmental parameter.