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 growthrate 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.ecological genomics | genome scan | fungi | circadian clock D iscovering the genetic basis behind adaptive phenotypes has long been considered the holy grail of evolutionary genetics. Although there are now several studies that have succeeded in identifying genes responsible for such phenotypes, the majority of them use a "forward-ecology" approach whereby candidate genes are identified on the basis of their having a function related to conspicuous traits, such as pigmentation (1-4). A paucity of obvious phenotypic traits has been a major impediment for studying adaptation in microbes because these organisms are, by nature, inconspicuous. However, next-generation sequencing technology has made it possible for individual laboratories to acquire whole-genome sequence information across populations. This innovation has enabled an unbiased "reverse-ecology" approach whereby genes with functions related to ecologically relevant traits can be identified by examining patterns of genetic diversity within and between populations and identifying candidate genes as those showing the signature of recent positive selection and/or divergent adaptation between populations (5).

Assessing patterns of hybridization between North Atlantic eels using diagnostic single-nucleotide polymorphisms

“…A minimum Phred score of 10 (equivalent to 90% probability of being correct) per nucleotide position was chosen, meaning that reads were dropped if a -nucleotide position had a score of o10. This is the Phred score generally used in SNP discovery studies (Van Bers et al, 2010;Ellison et al, 2011;Scaglione et al, 2012;Wagner et al, 2012). Final read length was trimmed to 80 nucleotides in order to reduce sequencing errors present at the tail of the sequences.…”

Advances and limits of using population genetics to understand local adaptation

“…Once genes subject to selection have been identified, the phenotypes upon which selection has acted can potentially be inferred on the basis of gene function (a bottom-up [12] or reverse-ecology [13] approach). For example, a transcriptome scan for local adaptation in Neurospora crassa identified not only several genes affecting temperature-dependent growth but also a gene involved in circadian oscillation, suggesting a role for circadian cycles in latitudinal-related adaptation in this species [14]. Genome scans also may lead to a refinement of the phenotype responsible for local adaptation.…”

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

“…Currently Neurospora has nearly 2000 genome and transcriptome projects published in the National Center for Biotechnology Information Short Read Archive and over 600 strains in the FGSC collection have been subject to transcriptome or genome sequence analysis including wild-type (Ellison et al 2011a) and classical mutant strains (McCluskey et al 2011). The impact of shared resources has reinforced Neurospora as a model for plant biomass deconstruction (Znameroski et al 2012), plant–microbe interactions (Kuo et al 2014), and a myriad of areas of cell biology and physiology (Roche et al 2014a).…”