Data from: Mechanisms of thermal adaptation and evolutionary potential of conspecific populations to changing environments

Heterogeneous and ever-changing thermal environments drive the evolution of populations and species, especially when extreme conditions increase selection pressure for traits influencing fitness. However, projections of biological diversity under scenarios of climate change rarely consider evolutionary adaptive potential of natural species. In this study, we tested for mechanistic evidence of evolutionary thermal adaptation among ecologically divergent redband trout populations (Oncorhynchus mykiss gairdneri) in cardiorespiratory function, cellular response and genomic variation. In a common garden environment, fish from an extreme desert climate had significantly higher critical thermal maximum (p3°C) than fish from cooler montane climate. In addition, the desert population had the highest maximum heart rate during warming (20% greater than montane populations), indicating improved capacity to deliver oxygen to internal tissues. In response to acute heat stress, distinct sets of cardiac genes were induced among ecotypes, which helps to explain the differences in cardiorespiratory function. Candidate genomic markers and genes underlying these physiological adaptations were also pinpointed, such as genes involved in stress response and metabolic activity (hsp40, ldh-b and camkk2). These markers were developed into a multi-variate model that not only accurately predicted critical thermal maxima, but also evolutionary limit of thermal adaptation in these specific redband trout populations relative to the expected limit for the species. This study demonstrates mechanisms and limitations of an aquatic species to evolve under changing environments that can be incorporated into advanced models to predict ecological consequences of climate change for natural organisms

Data from: Mechanisms of thermal adaptation and evolutionary potential of conspecific populations to changing environments

Heterogeneous and ever-changing thermal environments drive the evolution of populations and species, especially when extreme conditions increase selection pressure for traits influencing fitness. However, projections of biological diversity under scenarios of climate change rarely consider evolutionary adaptive potential of natural species. In this study, we tested for mechanistic evidence of evolutionary thermal adaptation among ecologically divergent redband trout populations (Oncorhynchus mykiss gairdneri) in cardiorespiratory function, cellular response and genomic variation. In a common garden environment, fish from an extreme desert climate had significantly higher critical thermal maximum (p<0.05) and broader optimum thermal window for aerobic scope (>3°C) than fish from cooler montane climate. In addition, the desert population had the highest maximum heart rate during warming (20% greater than montane populations), indicating improved capacity to deliver oxygen to internal tissues. In response to acute heat stress, distinct sets of cardiac genes were induced among ecotypes, which helps to explain the differences in cardiorespiratory function. Candidate genomic markers and genes underlying these physiological adaptations were also pinpointed, such as genes involved in stress response and metabolic activity (hsp40, ldh-b and camkk2). These markers were developed into a multi-variate model that not only accurately predicted critical thermal maxima, but also evolutionary limit of thermal adaptation in these specific redband trout populations relative to the expected limit for the species. This study demonstrates mechanisms and limitations of an aquatic species to evolve under changing environments that can be incorporated into advanced models to predict ecological consequences of climate change for natural organisms

Data from: Genetic basis of adult migration timing in anadromous steelhead discovered through multivariate association testing

Migration traits are presumed to be complex and to involve interaction among multiple genes, thus we employed both univariate analyses and multivariate Random Forest (RF) machine learning algorithm to conduct association mapping of 15,239 single nucleotide polymorphisms (SNPs) for adult migration-timing phenotype in steelhead (Oncorhynchus mykiss). Our study focused on a model natural population of steelhead that exhibits two distinct migration-timing life histories with high levels of admixture in nature. Neutral divergence was limited between fish exhibiting summer- and winter-run migration owing to high levels of interbreeding, but a univariate mixed linear model found three SNPs from a major effect gene to be significantly associated with migration-timing (p < 0.000005) that explained 46% of trait variation. Alignment to the annotated S. salar genome provided evidence that all three SNPs localize within a 46 kb region overlapping GREB1-like (an estrogen target gene) on chromosome Ssa03. Additionally, multivariate analyses with RF identified that these 3 SNPs plus 15 additional SNPs explained up to 60% of trait variation. These candidate SNPs may provide the ability to predict adult migration-timing of steelhead to facilitate conservation management of this species and this study demonstrates the benefit of multivariate analyses for association studies

TASSLE_input15239Ind237vfinal_traits

This file contains additional traits and covariates that were used to perform a univariate GWAS in TASSLE. Covariates include collection "year", and gender (1=male, 2=female). The trait phenotype is listed as "Dayreorder" which represents migration-timing in units of ordinal day as the phenotype. We "re-ordered" these days to reflect the biological sequence of annual steelhead migrations. Refer to the methods in the study for more detail

TASSLE_input15239Ind237vfinal_covtraits

This file contains the population structure individual Q values that were used as trait covariates in the program TASSLE to perform a univariate GWAS. Included are the individual proportions of ancestry using a K=6 and a K=10. For the analyses reported in the study, we used K=10, but we mentioned examining results with K=6 in the supplemental methods

TASSLEgeno15239Ind237vfinal_genotype.hmp

The input file of genotypes for the program TASSLE which was used to perform the univariate GWAS for this study

Data from: Genomic patterns of diversity and divergence of two introduced salmonid species in Patagonia, South America

Invasive species have become widespread in aquatic environments throughout the world, yet there are few studies that have examined genomic variation of multiple introduced species in newly colonized environments. In this study, we contrast genomic variation in two salmonid species (anadromous Chinook Salmon, Oncorhynchus tshawytscha, 11,579 SNPs and resident Brook Charr Salvelinus fontinalis, 13,522 SNPs) with differing invasion success after introduction to new environments in South America relative to populations from their native range in North America. Estimates of genetic diversity were not significantly different between introduced and source populations for either species, indicative of propagule pressure that has been shown to maintain diversity in founding populations relative to their native range. Introduced populations also demonstrated higher connectivity and gene flow than those in their native range. Evidence for candidate loci under divergent selection was observed, but was limited to specific introduced populations and was not widely evident. Patterns of genomic variation were consistent with general dispersal potential of each species and therefore also the notion that life history variation may contribute to both invasion success and subsequent genetic structure of these two salmonids in Patagonia