Gene sequence similarity due to shared ancestry after a duplication event, that is paralogy, complicates the assessment of genetic variation, as sequences originating from paralogs can be difficult to distinguish. These confounded sequences are often removed prior to further analyses, leaving the underlying loci uncharacterized. Salmonids have only partially rediploidized subsequent to a whole-genome duplication; residual tetrasomic inheritance has been observed in males. We present a maximum-likelihood-based method to resolve confounded paralogous loci by observing the segregation of alleles in gynogenetic haploid offspring and demonstrate its effectiveness by constructing two linkage maps for chum salmon (Oncorhynchus keta), with and without these newly resolved loci. We find that the resolved paralogous loci are not randomly distributed across the genome. A majority are clustered in expanded subtelomeric regions of 14 linkage groups, suggesting a significant fraction of the chum salmon genome may be missed by the exclusion of paralogous loci. Transposable elements have been proposed as drivers of genome evolution and, in salmonids, may have an important role in the rediploidization process by driving differentiation between homeologous chromosomes. Consistent with that hypothesis, we find a reduced fraction of transposable element annotations among paralogous loci, and these loci predominately occur in the genomic regions that lag in the rediploidization process.
As climate change intensifies, there is increasing interest in developing models that reduce uncertainties in projections of global climate and refine these projections to finer spatial scales. Forecasts of climate impacts on ecosystems are far more challenging and their uncertainties even larger because of a limited understanding of physical controls on biological systems. Management and conservation plans that explicitly account for changing climate are rare and even those generally rely on retrospective analyses rather than future scenarios of climatic conditions and associated responses of specific ecosystems. Using past biophysical relationships as a guide to predicting the impacts of future climate change assumes that the observed relationships will remain constant. However, this assumption involves a long chain of uncertainty about future greenhouse gas emissions, climate sensitivity to changes in greenhouse gases, and the ecological consequences of climate change. These uncertainties in forecasting biological responses to changing climate highlight the need for resource management and conservation policies that are robust to unknowns and responsive to change. We suggest how policy might develop despite substantial uncertainties about the future state of salmon ecosystems.
Local adaptation is often facilitated by loci clustered in relatively few regions of the genome, termed genomic islands of divergence. However, the mechanisms that create, mold, and maintain these islands are poorly understood. Here, we use sockeye salmon as a model species to investigate the mechanisms responsible for creating islands of divergence linked to adaptive variation. Previous research suggests that multiple islands are involved in adaptive radiation of sockeye salmon. However, these studies were based on low-density genomic methods that genotyped tens to thousands of loci, making it difficult to elucidate the mechanisms responsible for islands. We used whole genome resequencing to genotype millions of loci to investigate these mechanisms. We discovered 64 islands, 16 of which were shared between two isolated populations; these 16 islands were clustered in four genomic regions. Characterization of the shared regions suggested that three of four were likely created by chromosomal inversions, while the other was created by processes not involving structural variation. Additionally, all four regions were relatively small (< 600 kb), suggesting inversions and other low recombination regions do not have to span megabases to be important for adaptive divergence. In sum, our study demonstrates that heterogeneous selection can lead to a mosaic of islands created by different mechanisms within the same genome. Future studies should continue to investigate how gene flow, selection, and the architecture of genetic traits interact to influence the genomic landscape of adaptive divergence.
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