Integration of Random Forest with population‐based outlier analyses provides insight on the genomic basis and evolution of run timing in Chinook salmon (Oncorhynchus tshawytscha)

Abstract

Anadromous Chinook salmon populations vary in the period of river entry at the initiation of adult freshwater migration, facilitating optimal arrival at natal spawning. Run timing is a polygenic trait that shows evidence of rapid parallel evolution in some lineages, signifying a key role for this phenotype in the ecological divergence between populations. Studying the genetic basis of local adaptation in quantitative traits is often impractical in wild populations. Therefore, we used a novel approach, Random Forest, to detect markers linked to run timing across 14 populations from contrasting environments in the Columbia River and Puget Sound, USA. The approach permits detection of loci of small effect on the phenotype. Divergence between populations at these loci was then examined using both principle component analysis and FST outlier analyses, to determine whether shared genetic changes resulted in similar phenotypes across different lineages. Sequencing of 9107 RAD markers in 414 individuals identified 33 predictor loci explaining 79.2% of trait variance. Discriminant analysis of principal components of the predictors revealed both shared and unique evolutionary pathways in the trait across different lineages, characterized by minor allele frequency changes. However, genome mapping of predictor loci also identified positional overlap with two genomic outlier regions, consistent with selection on loci of large effect. Therefore, the results suggest selective sweeps on few loci and minor changes in loci that were detected by this study. Use of a polygenic framework has provided initial insight into how divergence in a trait has occurred in the wild.

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

“…Recent empirical studies demonstrate that even seemingly complex phenotypes can be controlled by concentrated architecture [49,50]. Life-history strategies for migration timing in salmonids appear to be less extreme than these examples of traits with concentrated genetic architecture, because many loci of both large and small effects have been implicated across chromosomes [35,51]. Our study of migration timing in steelhead lends support to this notion because this trait involves at least one chromosome region of relatively large effect as well as loci across multiple chromosomes with relatively minor effects.…”

“…'finesweep' analysis), the least important loci are removed one by one, starting with a greater number than the initial optimum number of loci (here, the best 150 loci rather than the top 25; electronic supplementary material, supplemental methods S3). This 'fine-sweep' analysis was necessary to identify candidate SNPs with more precision than could be accomplished with the 'coarse-sweep' analysis, and this analysis helps to minimize the potential negative interactions across loci that may otherwise prevent identification of the best candidate SNPs [34,35]. The migration trait data in this case were the residuals of the day of passage trait from the previous MLM univariate analysis, which minimized bias from population structure and kinship.…”

On the maintenance of genetic variation and adaptation to environmental change: considerations from population genomics in fishes

“…These results are also consistent with theory implying that genetic variation underlying life‐history traits is explained mainly by loci of small phenotypic effect without excluding a role for loci of major effect. This study of Brieuc et al () provides a clear illustration of the limitations of a strictly single‐locus approach in searching for the genomic basis of adaptation.…”

“…rostrata , which were also identified by RF. As for Brieuc et al (), this study illustrates the power of combining methods for detecting signals of polygenic selection and for associating variation of markers with putative selective agents in studies aiming at documenting the dynamics of selection at the genomic level and particularly so in human‐altered environments.…”

Sewage treatment plant associated genetic differentiation in the blue mussel from the Baltic Sea and Swedish west coast

“…AFLP loci that are strong predictors of class (here pollution type) will occur in many trees resulting in a higher importance rank (Holliday, Wang & Aitken, 2012; Brieuc et al, 2015). This method is gaining popularity in molecular ecology studies as it has been shown to be useful in the search for loci under selection (Holliday, Wang & Aitken, 2012; Brieuc et al, 2015; Pavey et al, 2015; Laporte et al, 2015; Laporte et al, 2016). In varSelRF different combinations of data were tested, with individuals from each pollution type pooled in the two groups STP and REF and pair wise comparisons of the two pollution types within each location.…”