Whole-genome duplications have occurred in the recent ancestors of many plants, fish, and amphibians, resulting in a pervasiveness of paralogous loci and the potential for both disomic and tetrasomic inheritance in the same genome. Paralogs can be difficult to reliably genotype and are often excluded from genotyping-by-sequencing (GBS) analyses; however, removal requires paralogs to be identified which is difficult without a reference genome. We present a method for identifying paralogs in natural populations by combining two properties of duplicated loci: (i) the expected frequency of heterozygotes exceeds that for singleton loci, and (ii) within heterozygotes, observed read ratios for each allele in GBS data will deviate from the 1:1 expected for singleton (diploid) loci. These deviations are often not apparent within individuals, particularly when sequence coverage is low; but, we postulated that summing allele reads for each locus over all heterozygous individuals in a population would provide sufficient power to detect deviations at those loci. We identified paralogous loci in three species: Chinook salmon (Oncorhynchus tshawytscha) which retains regions with ongoing residual tetrasomy on eight chromosome arms following a recent whole-genome duplication, mountain barberry (Berberis alpina) which has a large proportion of paralogs that arose through an unknown mechanism, and dusky parrotfish (Scarus niger) which has largely rediploidized following an ancient whole-genome duplication. Importantly, this approach only requires the genotype and allele-specific read counts for each individual, information which is readily obtained from most GBS analysis pipelines.

Regions of the genome displaying elevated differentiation (genomic islands of divergence) are thought to play an important role in local adaptation, especially in populations experiencing high gene flow. However, the characteristics of these islands as well as the functional significance of genes located within them remain largely unknown. Here, we used data from thousands of SNPs aligned to a linkage map to investigate genomic islands of divergence in three ecotypes of sockeye salmon (Oncorhynchus nerka) from a single drainage in southwestern Alaska. We found ten islands displaying high differentiation among ecotypes. Conversely, neutral structure observed throughout the rest of the genome was low and not partitioned by ecotype. One island on linkage group So13 was particularly large and contained six SNPs with F > 0.14 (average F of neutral SNPs = 0.01). Functional annotation revealed that the peak of this island contained a nonsynonymous mutation in a gene involved in growth in other species (TULP4). The islands that we discovered were relatively small (80-402 Kb), loci found in islands did not show reduced levels of diversity, and loci in islands displayed slightly elevated linkage disequilibrium. These attributes suggest that the islands discovered here were likely generated by divergence hitchhiking; however, we cannot rule out the possibility that other mechanisms may have produced them. Our results suggest that islands of divergence serve an important role in local adaptation with gene flow and represent a significant advance towards understanding the genetic basis of ecotypic differentiation.

In their recently corrected manuscript, "Breaking RAD: An evaluation of the utility of restriction site associated DNA sequencing for genome scans of adaptation", Lowry et al. argue that genome scans using RADseq will miss many loci under selection due to a combination of sparse marker density and low levels of linkage disequilibrium in most species. We agree that marker density and levels of LD are important considerations when designing a RADseq study; however, we dispute that RAD-based genome scans are as prone to failure as Lowry et al. suggest. Their arguments ignore the flexible nature of RADseq; the availability of different restriction enzymes and capacity for combining restriction enzymes ensures that a well-designed study should be able to generate enough markers for efficient genome coverage. We further believe that simplifying assumptions about linkage disequilibrium in their simulations are invalid in many species. Finally, it is important to note that the alternative methods proposed by Lowry et al. have limitations equal to or greater than RADseq. The wealth of studies with positive impactful findings that have used RAD genome scans instead supports the argument that properly conducted RAD genome scans are an effective method for gaining insight into ecology and evolution, particularly for non-model organisms and those with large or complex genomes.

Understanding the genetic architecture of phenotypic traits can provide important information about the mechanisms and genomic regions involved in local adaptation and speciation. Here, we used genotyping-by-sequencing and a combination of previously published and newly generated data to construct sex-specific linkage maps for sockeye salmon (Oncorhynchus nerka). We then used the denser female linkage map to conduct quantitative trait locus (QTL) analysis for 4 phenotypic traits in 3 families. The female linkage map consisted of 6322 loci distributed across 29 linkage groups and was 4082 cM long, and the male map contained 2179 loci found on 28 linkage groups and was 2291 cM long. We found 26 QTL: 6 for thermotolerance, 5 for length, 9 for weight, and 6 for condition factor. QTL were distributed nonrandomly across the genome and were often found in hotspots containing multiple QTL for a variety of phenotypic traits. These hotspots may represent adaptively important regions and are excellent candidates for future research. Comparing our results with studies in other salmonids revealed several regions with overlapping QTL for the same phenotypic trait, indicating these regions may be adaptively important across multiple species. Altogether, our study demonstrates the utility of genomic data for investigating the genetic basis of important phenotypic traits. Additionally, the linkage map created here will enable future research on the genetic basis of phenotypic traits in salmon.

Salmonids are an important cultural and ecological resource exhibiting near worldwide distribution between their native and introduced range. Previous research has generated linkage maps and genomic resources for several species as well as genome assemblies for two species. We first leveraged improvements in mapping and genotyping methods to create a dense linkage map for Chinook salmon Oncorhynchus tshawytscha by assembling family data from different sources. We successfully mapped 14 620 SNP loci including 2336 paralogs in subtelomeric regions. This improved map was then used as a foundation to integrate genomic resources for gene annotation and population genomic analyses. We anchored a total of 286 scaffolds from the Atlantic salmon genome to the linkage map to provide a framework for the placement 11 728 Chinook salmon ESTs. Previously identified thermotolerance QTL were found to colocalize with several candidate genes including HSP70, a gene known to be involved in thermal response, as well as its inhibitor. Multiple regions of the genome with elevated divergence between populations were also identified, and annotation of ESTs in these regions identified candidate genes for fitness related traits such as stress response, growth and behaviour. Collectively, these results demonstrate the utility of combining genomic resources with linkage maps to enhance evolutionary inferences.

Chinook salmon (Oncorhynchus tshawytscha) are migratory fish that are highly valued for subsistence, sport, and commercial fisheries throughout their native range. Populations of Chinook salmon in western Alaska have exhibited long-term declines, leading to restrictions on harvests. Management priorities require greater resolution for genetic stock identification (GSI) than is available with current methods. We leveraged RADseq, TaqMan, and GT-seq data originating from multiple sources, collected through time, to develop a set of GT-seq panels containing 1092 single nucleotide polymorphisms (SNPs) that improved GSI resolution in western Alaska for at-sea and in-river sampling. We generated a dense linkage map to ensure that markers selected for panels spanned the entire genome. In addition, we identified multiple RADseq markers that were associated with sex; these aligned to a 5-centimorgan (cM) region on the sex chromosome. Finally, we developed a bioinformatic pipeline to streamline analysis of GT-seq data that is capable of genotyping microhaplotypes and paralogs, both of which can improve GSI resolution over traditional single-SNP data. Our panels and pipeline provide tools for management agencies to rapidly and easily analyze large-scale genotyping projects.

Migratory behaviour patterns in animals are controlled by a complex genetic architecture. Rainbow trout (Oncorhynchus mykiss) is a salmonid fish that spawns in streams but exhibits three primary life history pathways: stream‐resident (fluvial), lake‐migrant (adfluvial) and ocean‐migrant (anadromous). Previous studies examining fluvial and anadromous O. mykiss have identified several genes associated with life history divergence including the presence of an inversion complex within chromosome 5 (Omy05) that appears to maintain a suite of linked genes controlling migratory behaviour. However, adfluvial trout are migratory without being anadromous, and the genetic basis for this life history has not been investigated from evolutionary perspectives. We sampled wild, native nonanadromous rainbow trout occupying connected stream and lake habitats in a southwest Alaskan watershed to determine whether these fish exhibit genetic divergence between fluvial and adfluvial ecotypes, and whether that divergence parallels that documented in fluvial and anadromous O. mykiss. Data from restriction site‐associated DNA (RAD) sequencing revealed an association between frequencies of both the Omy05 inversion complex and other single nucleotide polymorphisms (SNPs) with habitat type (stream or lake), supporting the genetic divergence of fluvial and adfluvial individuals in sympatry. The presence of a genetic basis for migration into lakes, analogous to that documented for anadromy, indicates that the adfluvial ecotype must be recognized separately from the fluvial form of O. mykiss even though neither is anadromous. These results highlight the genetic architecture underlying migration and the importance of chromosomal inversions in promoting and sustaining intraspecific diversity.

The increasing feasibility of assembling large genomic datasets for non-model species presents both opportunities and challenges for applied conservation and management. A popular theme in recent studies is the search for large-effect loci that explain substantial portions of phenotypic variance for a key trait(s). If such loci can be linked to adaptations, 2 important questions arise: 1) Should information from these loci be used to reconfigure conservation units (CUs), even if this conflicts with overall patterns of genetic differentiation? 2) How should this information be used in viability assessments of populations and larger CUs? In this review, we address these questions in the context of recent studies of Chinook salmon and steelhead (anadromous form of rainbow trout) that show strong associations between adult migration timing and specific alleles in one small genomic region. Based on the polygenic paradigm (most traits are controlled by many genes of small effect) and genetic data available at the time showing that early-migrating populations are most closely related to nearby late-migrating populations, adult migration differences in Pacific salmon and steelhead were considered to reflect diversity within CUs rather than separate CUs. Recent data, however, suggest that specific alleles are required for early migration, and that these alleles are lost in populations where conditions do not support early-migrating phenotypes. Contrasting determinations under the US Endangered Species Act and the State of California’s equivalent legislation illustrate the complexities of incorporating genomics data into CU configuration decisions. Regardless how CUs are defined, viability assessments should consider that 1) early-migrating phenotypes experience disproportionate risks across large geographic areas, so it becomes important to identify early-migrating populations that can serve as reliable sources for these valuable genetic resources; and 2) genetic architecture, especially the existence of large-effect loci, can affect evolutionary potential and adaptability.