Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity. Issue 22 (8th November 2017) - Harrisson, Katherine A.; Amish, Stephen J.; Pavlova, Alexandra; Narum, Shawn R.; Telonis‐Scott, Marina; Rourke, Meaghan L.; Lyon, Jarod; Tonkin, Zeb; Gilligan, Dean M.; Ingram, Brett A.; Lintermans, Mark; Gan, Han Ming; et al.
Abstract: Adaptive differences across species' ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene–environment association studies involve distinguishing the effects of drift from those of selection and identifying subtle signatures of polygenic adaptation. We used paired‐end restriction site‐associated DNA sequencing data (6, 605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii . Two univariate gene–association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature‐ and precipitation‐related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomic studies.