Linkage mapping with paralogs exposes regions of residual tetrasomic inheritance in chum salmon (Oncorhynchus keta)

Abstract

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.

Harnessing the power of RADseq for ecological and evolutionary genomics

“…Therefore the reverse reads at any given locus are staggered 20 , and these data can be used to assemble long contigs , for example as long as 1kb if library fragments are tailored to be this length 19,21 . These RAD contigs allow for better identification of paralogs 22 , provide more sequence for BLAST searching of functionally important loci 20 , and could provide haplotype data for genealogical or phylogenetic analysis. Longer contig sequences also allow for the design of PCR primers or sequence capture probes to target loci of interest for further study 23,24 .…”

Salmonid chromosome evolution as revealed by a novel method for comparing RADseq linkage maps

“…This included maps generated with haploid crosses for mapping regions exhibiting residual tetraploidy (Limborg et al 2016), although in most cases, we only retained the nonduplicated loci due to problems in pairing these markers (described in workflow below). Some of these maps also contain centromere information, including Chinook Salmon (Brieuc et al 2014), Coho Salmon (Kodama et al 2014), Sockeye Salmon (Everett et al 2012; Limborg et al 2015), and Chum Salmon (Waples et al 2016). A high-density map for Atlantic Salmon with information on duplicate regions is also available (Lien et al 2011).…”

“…Genome Size ( C value) (Gregory 2016)Exp. Genome Size (Gbp)Northern Pike a (Rondeau et al 2014) Esox lucius EST-based microsatellite (524)250.85–1.400.8–1.4Lake Whitefish (Gagnaire et al 2013) Coregonus clupeaformis RADseq with Sbf I (3,438)402.44–3.442.4–3.4Atlantic Salmon (Lien et al 2011) Salmo salar EST-based SNP chip (5,650)292.98–3.272.8–3.2Brook Charr Salvelinus fontinalis RADseq with Pst I and Msp I (3,826)422.86–3.502.8–3.4Rainbow Trout (Palti et al 2015) Oncorhynchus mykiss RADseq with Sbf I (955)291.87–2.921.8–2.9Coho Salmon (Kodama et al 2014) O. kisutch RADseq with Sbf I (5,377)302.60–3.052.5–3.0Chinook Salmon (Brieuc et al 2014) O. tshawytscha RADseq with Sbf I (6,352)342.45–3.302.4–3.2Pink Salmon (Limborg et al 2014) O. gorbuscha RADseq with Sbf I (7,035)262.23–2.572.2–2.5Chum Salmon (Waples et al 2016) O. keta RADseq with Sbf I (6,119)372.49–2.762.4–2.7Sockeye Salmon (Larson et al 2016) O. nerka RADseq with Sbf I (6,262)292.77–3.042.7–3.0…”

“…High-density linkage maps have been constructed for Lake Whitefish Coregonus clupeaformis (Gagnaire et al 2013), Atlantic Salmon S. salar (Lien et al 2011; Gonen et al 2014) and members of Oncorhynchus including Rainbow Trout O. mykiss (Miller et al 2012; Palti et al 2015), Chinook Salmon O. tshawytscha (Brieuc et al 2014), Coho salmon O. kisutch (Kodama et al 2014), Pink Salmon O. gorbuscha (Limborg et al 2014), Chum Salmon O. keta (Waples et al 2016) and Sockeye Salmon O. nerka (Everett et al 2012; Larson et al 2016). No high-density maps exist for members of Salvelinus , but low-density microsatellite-based maps exist for Arctic Charr S. alpinus and Brook Charr S. fontinalis (Woram et al 2004; Timusk et al 2011), as well as a low-density (∼300 marker) EST-derived SNP map for S. fontinalis (Sauvage et al 2012a).…”

Exploring the phylogeography of a hexaploid freshwater fish by RAD sequencing

“…This method is popular and has been used in many studies since its inception (Figure S1). RAD sequencing has been used, particularly in fish, to identify population divergence (Boehm, Waldman, Robinson, & Hickerson, 2015; Ferchaud & Hansen, 2016; Larson et al., 2014), for SNP identification in polyploid fish (Hohenlohe, Amish, Catchen, Allendorf, & Luikart, 2011; Ogden et al., 2013; Palti et al., 2014), in phylogeographic studies (Macher et al., 2015; Reitzel, Herrera, Layden, Martindale, & Shank, 2013), for QTL analysis (Gagnaire, Normandeau, Pavey, & Bernatchez, 2013; Houston et al., 2012; Yoshizawa et al., 2015), for linkage mapping (Brieuc, Waters, Seeb, & Naish, 2014; Henning, Lee, Franchini, & Meyer, 2014), in hybridization studies (Hand et al., 2015; Lamer et al., 2014; Pujolar et al., 2014), for exploration of genome architecture and evolution (Brawand et al., 2014; Kai et al., 2014; Waples, Seeb, & Seeb, 2016), and in phylogenetic analyses (Gonen, Bishop, & Houston, 2015; Wagner et al., 2013). This methodology should be particularly suited to phylogeographic studies as the inference power from large numbers of markers may identify patterns that are not easily visible in traditional analyses based on relatively few loci (Davey et al., 2011).…”