TY - JOUR AU - Pearse, Devon E AB - Abstract Whole-genome duplications (WGDs) have occurred repeatedly and broadly throughout the evolutionary history of eukaryotes. However, the effects of WGD on genome function and evolution remain unclear. The salmonid WGD that occurred approximately 88 million years ago presents an excellent opportunity for studying the effects of WGD as ∼10–15% of each salmonid genome still exhibits tetrasomic inheritance. Herein, we utilized the rainbow trout (Oncorhynchus mykiss) genome assembly and brain transcriptome data to examine the fate of gene pairs (ohnologs) following the salmonid whole-genome duplication. We find higher sequence identity between ohnologs located within known tetrasomic regions than between ohnologs found in disomic regions, and that tetrasomically inherited ohnologs showed greater similarity in patterns of gene expression and per ohnolog were lower expressed, than disomically inherited ohnologs. Enrichment testing for Gene Ontology terms identified 49 over-represented terms in tetrasomically inherited ohnologs compared to disomic ohnologs. However, why these ohnologs are retained as tetrasomic is difficult to answer. It could be that we have identified salmonid specific “dangerous duplicates”, that is, genes that cannot take on new roles following WGD. Alternatively, there may be adaptive advantages for retaining genes as functional duplicates in tetrasomic regions, as presumably, movement of these genes into disomic regions would affect both their sequence identity and their gene expression patterns. Salmonidae, Ohnologs, Homeologs, Differential Gene Expression, Smoltification Whole-genome duplication (WGD) events are widespread in the eukaryotic tree of life (e.g., Campbell et al., 2016; Soltis and Soltis 1999; Van de Peer et al., 2017). WGDs create copies of the same gene – termed ohnologs – and this genetic redundancy has long been thought to provide the molecular blueprint for evolution and adaptation (e.g., Ohno 1970). While the influence of WGDs on long-term processes like organismal diversification are unclear (e.g., Mayrose et al., 2011; Santini et al., 2009; Wood et al., 2009; Zhan et al., 2014), evidence suggests that WGDs present a variety of challenges during both mitosis and meiosis (Hollister 2015). These challenges are reflected by the observation that most neopolyploid species revert to diploidy soon after duplication (Gerstein and Otto 2009; Wolfe 2001). Following WGD, ohnologs typically follow four basic patterns: (1) Nonfunctionalization where through mutation the new duplicate loses functionality (Langham et al., 2004), (2) Subfunctionalization in which the duplicates retain subsets of the original gene function (Force et al., 1999; Sémon and Wolfe 2008), (3) Neofunctionalization in which a gene copy takes on a new function (Muller 1936; Ohno 1970; Rastogi and Liberles 2005), and, (4) Conservation of the same function by both copies of the gene (Dean et al., 2008; Tischler et al., 2006; Vavouri et al., 2008). Understanding why some genes are able to become neo- or sub-functionalized while others are lost or conserved is critical for understanding the reversion to diploidy characteristic of polyploid genomes. Previous research has indicated that the most common fate of a duplicated gene is to become nonfunctionalized and lost (Lynch and Conery 2000). For example, various estimates across fishes suggest that only 12–24% of all genes have been retained as functional duplicates following the teleost WGD 350 million years ago (e.g., Braasch and Postlethwait 2012; Kassahn et al., 2009; Postlethwait et al., 2000; Woods et al., 2005). However, the retention of some ohnologs following duplication indicates that these ohnolog pairs must have experienced functional divergence either by subfunctionalization or neofunctionalization (Braasch et al., 2018, 2016; Sandve et al., 2018). Subfunctionalization leads to limited changes to gene function, as both genes within an ohnolog pair contribute to the original function either by maintaining gene expression to pre-duplication levels, or by obtaining mutations that do not change the functions of either protein (Force et al., 1999; Stoltzfus 1999). Neofunctionalization, on the other hand, results in two genes with different functions – the original function is conserved by one gene copy while mutation of the second gene copy leads to the development of a new function. Neofunctionalization and subfunctionalization are not necessarily mutually exclusive processes and subfunctionalization may be an intermediate step toward neofunctionalization (Rastogi and Liberles 2005). Lastly, ohnologs may be conserved as redundant pairs with both copies retaining the original functions. Selection for redundancy may be due to different processes depending on the functions of the ohnologs. For example, ohnologs connected to haploinsufficent phenotypes, ohnologs with an increased likelihood of acquiring dominant deleterious mutations (the “dangerous duplicates” hypothesis; e.g., Singh et al., 2012), or when the expression of each ohnolog is required for regular function (the dosage-compensation model (Edger and Pires 2009; Hughes et al., 2007; Pires and Conant 2016) may all explain why some ohnologs are conserved. One way to differentiate between these hypotheses is to investigate the function of retained duplicates. For example Singh et al. (2015) proposed that mutations in ohnologs are three times as likely as mutations in non-ohnologs to be associated with autosomal dominant diseases and up to eight times more likely to encode for genes with autoinhibitory protein folds (Singh et al., 2012; 2015; i.e., the “dangerous duplicates hypothesis”). On the other hand, genes involved in processes such as metabolism, transcription, and translation appear to exhbit a reduction in expression in both copies compared to non-duplicates (i.e., the “dosage-balance hypothesis”: Aury et al., 2006; Hughes et al., 2007). In order to more fully understand how patterns of gene expression link with retaining ohnologs post WGD, more data from a wider range of taxa are required. The common ancestor of salmonid fishes has been identified as an autopolyploid that experienced a whole-genome duplication approximately 88 million years ago (Allendorf and Thorgaard 1984; Berthelot et al., 2014; Macqueen and Johnston 2014). Since then, salmonid genomes have mostly reverted to diploidy (Lien et al. 2016), with lineage-specific divergences in ohnolog function (Robertson et al. 2017). This re-diploidization is demonstrated by the reduction in the number of protein coding genes from a theorized 62,952 in the ancestral tetraploid salmonid to 46,585 in the modern rainbow trout genome (Berthelot et al., 2014). However, there is evidence that 10–15% of most salmonid genomes are inherited tetrasomically, with eight chromosome arm pairs commonly forming tetravalents during meiosis (Allendorf et al. 2015). Strikingly, the homologs of these eight chromosome arm pairs have independently maintained tetrasomy during the evolution of Salmo, Salvelinus, and Oncorhynchus despite multiple fusion and fission events between chromosome arms across species (e.g., Brieuc et al., 2014; Kodama et al., 2014; Lien et al., 2011; Sutherland et al., 2016; Waples et al. 2016). Phylogenetic correlation could potentially explain the retained duplication patterns for the eight homeologous arms at recent time scales; however, the conservation of tetrasomic inheritance by the same genes and genomic regions across Salmo, Oncorhynchus, and Salvelinus despite tens of millions of years of independent divergence among these lineages strongly supports underlying selection vs. phylogenetic correlation. The conservation of these eight chromosome arm pairs is well known, yet, there is limited information regarding why these regions are maintained as tetrasomic or how their tetrasomic inheritance influences patterns of gene expression. The aims of this manuscript are threefold: (1) to compare sequence similarity between tetrasomically and disomically inherited ohnologs; (2) to compare and contrast patterns of gene expression between tetrasomically and disomically inherited ohnologs; and (3) to compare and contrast functionality of ohnologs – as inferred from Gene Ontology terms - between tetrasomic and disomically inherited regions of the genome. To accomplish these aims we use the newly updated Oncorhynchus mykiss (rainbow and steelhead trout) genome assembly (https://www.ncbi.nlm.nih.gov/assembly/GCF_002163495.1/; Pearse et al., 2018) and gene expression data from a population of rainbow trout that has become a model system for understanding the genetic basis of migration (Hale et al., 2016; 2013; Hecht et al., 2015; 2012; McKinney et al., 2015). Here we demonstrate that ohnolog pairs in tetrasomic regions are more similar in their sequence identity than those in disomic regions of inheritance, and that patterns of gene expression are more similar between ohnologs in tetrasomically inherited regions than between ohnologs in disomic regions. GO enrichment identified 49 over-represented terms among ohnologs in tetrasomically inherited genomic regions, indicative of differences in function between inheritance modes. These results provide insight into the underlying constraints that sustain tetrasomic inheritance in these regions of the genome. Methods Ohnolog identification, similarity and inheritance mode A table of ohnolog pairs arising from the salmonid-specific autotetraploidization event (Ss4R, Berthelot et al. 2014) that includes overall similarity between each member of a pair (percent identity in terms of DNA similarity, PID) and genomic locations of both members of a pair was generated following methods used in Lien et al. (2016). Briefly, an all-vs.-all BLASTP (Altschul et al., 1990) of amino acid translations of the longest transcript for each locus was performed with the following guidelines: minimum alignment length of 50% and minimum percentage sequence identity of 85%. The top ranked BLASTP hits from known Ss4R homeolog regions (see Pearse et al. 2018) were identified. Ohnologs were then divided into six categories based on overall DNA sequence similarity between both members of the pair, (<90%, 90–95%, and >95% PID, similar to other salmonid studies, e.g., Lien et al. 2016), and inheritance mode (tetrasomic or disomic) as determined by the location of the ohnologs in the rainbow trout genome. It is well known that homeologous regions of the salmonid genome form tetravalent meioses in Oncorhynchus, Salmo, and Salvelinus (Kodama et al., 2014; Lien et al., 2016; Sutherland et al., 2016); therefore, positional information on the rainbow trout genome was deemed as sufficient evidence for tetrasomic inheritance. To visualize the relationship between ohnolog PID and inheritance mode, we plotted the chromosome position on the x - axis and PID of each ohnolog to its partner on the y - axis while splitting by inheritance mode (i.e., tetrasomic or disomic). The PID values were plotted using a smoothed conditional means approach (geom_smooth function of ggplot) to avoid over plotting and increase visibility of patterns. Overall differences in ohnolog sequence similarity were characterized by generating histograms of percent similarity of ohnolog pairs within disomic and tetrasomic regions of the rainbow trout genome, with each histogram scaled to integrate to 1.0 for comparative purposes (geom_histogram function in R package ggplot2). We tested the difference in mean PID of ohnolog pairs between disomic and tetrasomic genome regions with a Welch Two Sample t-Test (t.test function of base R with alpha = 0.05). All analysis and figures were constructed using R version 3.3.1 (R Development Core Team 2017) and the ggplot2.2.1 package (Wickham 2009). Gene expression analysis To compare patterns of gene expression between ohnolog pairs, RNA-seq data were used from a previous study examining differences in gene expression between migratory and non-migratory O. mykiss from Sashin Creek, Alaska (NCBI Sequence Read Archive under the BioProject Number PRJNA269115; Hale et al., (2016)). Briefly, two-year-old fish originating from two type of crosses - one between two migratory anadromous parents (A x A) and one between two resident parents (R x R) - were reared in a common garden experiment at the Little Port Walter Marine Station to examine developmental gene expression using RNA-seq (Hale et al., 2016). At age 2, seven fish from the A x A line (n = 4 females and n = 3 males) and eight fish from the R x R line (n = 4 females and n = 4 males) were killed using a lethal dose of buffered MS222. Whole brains were dissected and stored immediately in RNAlater (ThermoFisher). Complete details of RNA extraction, library preparation, and sequencing are described in Hale et al. (2016). The study herein constitutes a re-analysis of the data presented in Hale et al. (2016). Instead of a de novo assembly, the most recent version of the rainbow trout genome was used as a reference to map RNA-seq reads (NCBI accession number: GCF_002163495.1; Pearse et al., 2018). Prior to alignment, RNA-seq reads were filtered for low quality bases (Phred scores < 33) and reads less than 25 base pairs (bp) were discarded with Trimmomatic version 0.36 (Bolger et al., 2014). Cleaned reads were mapped to assembled chromosomes of the rainbow trout genome with hisat2 version 2.0.4 under the default settings (Kim et al., 2015). The resulting Sequence Alignment Map (SAM) files were processed by converting to sorted binary files (BAM) using SAMtools version 1.3 (Li et al., 2009). From BAM files, the htseq-count script of HTSeq version 0.6.1 (Anders et al., 2015) was used to generate read count matrices with the option “-m union” specified to allow reads that align over part of a gene or across exons to be counted while considering those reads aligning over parts of two genes to be ambiguous. To examine global expression differences between ohnolog pairs located in disomic and tetrasomic genomic regions we examined the total expression matrix and divided it by cross type. We further divided the expression data matrix by each cross type and sex (four total data sets: A x A Females, A x A Males, R x R Females, R x R Males). For each of these cross type and sex data sets (7 total) expression between ohnolog pairs was calculated as the absolute value of log2 fold change with DESeq2 (Love et al., 2014), providing a measure of expression difference between copies of an ohnolog pair specific to each cross and sex. We visualized resulting log2 fold change measures with two-dimensional kernel density estimates of the absolute value of log fold change between the two genes in an ohnolog pair split by inheritance mode for each of the four data sets resulting from splitting by cross type and sex (stat_density_2d function of ggplot with R version 3.3.1) (R Development Core Team 2017; Wickham 2009). For the x - axis, we generated relative positions of the ohnolog by dividing the position of the ohnolog by the total length of the chromosome. The y - axis component is an expression of absolute fold change, presented as the absolute value of log2 fold changes found between ohnologs calculated by DESeq2, to show differences without direction (negative or positive fold changes). We examined the mean and variance of the absolute value of log2 fold changes between ohnolog pairs of different inheritance modes (summary function of base R) and tested for differences between the means with a Welch t-Test (t.test function of base R). To identify genes and ohnologs that may have sex-specific or life history-specific function, we tested for differential expression between cross types, A x A (n = 7) vs. R x R (n = 8), and between cross types split by sex. That is, read count data were further subdivided by both cross type and sex, and were analyzed as A x A females (n = 4) vs. R x R females (n = 4) or A x A males (n = 3) vs. R x R males (n = 4). To be tested for differential expression, a gene was required to have at least five reads mapping to it when summed across individuals. Differential expression was tested by DESeq2 with the “DESeq” function which includes normalization of raw read counts as described in Love et al., (2014). We tested all anadromous individuals against all resident individuals with sex considered a cofactor within the model. For sex-specific models, this co-factor was not included. Significance was designated with an adjusted p – value < 0.1 in DESeq2 with an implementation of the Benjamini-Hochberg false discovery rate method (Benjamini and Hochberg 1995). Gene ontology (GO) analysis Ohnologs were classified as being inherited via disomy or tetrasomy based on their location in the rainbow trout genome (Pearse et al., 2018). All 7,879 ohnolog pairs were annotated by using BLAST against the UniProt database (downloaded 10-12-2017) using a maximum e-value of 1.0 × 10−8 and default parameters. Associated Gene Ontology (GO) terms were mapped using Blast2GO with default parameters. Fisher’s exact tests were used for testing enrichment of GO terms in all tetrasomic ohnologs compared to all disomic ohnologs. A maximum p – value cut off of 0.001 was used to infer enrichment. Protein complexes In order to identify differences in protein-protein interactions between ohnologs located in disomic regions and ohnologs located in tetrasomic regions, we obtained the number of subunits each protein encoded by ohnologs interacted with. These data were manually downloaded from the UniProtKB/Swiss-Prot database on January 26, 2019. Information on protein interactions was downloaded for three organisms: Atlantic salmon, zebrafish and mouse. A Perl script (extract_complex_info_UniProt.pl, available at https://github.com/julien-roux/Roux_Liu_and_Robinson-Rechavi_2016) designed by Roux et al. (2017) was used to identify the “subunit structure” annotation category linked to the annotated ohnologs. The following complex categories were utilized by Roux et al. (2017) and by this study: monomers, homomultimers, heterodimers, heteromultimers (more than two different subunits), and “other complexes” for descriptions that could not be automatically categorized. We tested if the proportions of complex categories from annotated ohnologs differed between disomic and tetrasomic ohnologs with a X-squared test (prop.test function in base R). Data availability A table of rainbow trout ohnologs originating from the Ss4R as described is provided as Supplemental File S1. Supplemental File S2 contains summary alignment statistics from the HTSeq analysis. Supplemental File S3 contains information on gene expression from DeSeq2 including log2 fold difference in expression, raw, and FDR corrected p –values. Supplemental File S4 shows the specific genes associated with enriched GO terms in tetrasomic regions of the rainbow trout genome. Supplemental File S5 shows differentially expressed genes between cross type with associated GO terms. Supplemental File S6 shows proportions of disomic and tetrasomic ohnologs with protein-protein interaction information. All RNA-seq data used in this manuscript have been uploaded to NCBI (BioProject Number PRJNA269115) and the rainbow trout genome can be accessed at https://www.ncbi.nlm.nih.gov/assembly/GCF_002163495.1/. Supplemental material available at FigShare: https://doi.org/10.25387/g3.7732358. Results Ohnolog identification, similarity and inheritance mode Of the 7,979 ohnolog pairs originating from the Ss4R identified from the rainbow trout genome, 5,701 (72.4%) were predicted to be inherited disomically and 2,278 (27.6%) were predicted to be inherited tetrasomically based on their locations on the rainbow trout genome (Table 1, Supplemental File S1). Most disomically inherited ohnologs showed low (i.e., less than <90%) sequence similarity, whereas most tetrasomically inherited ohnologs show very high (>95%) sequence similarity, and ohnolog pairs within tetrasomic regions showed greater similarity (PID) than those located in disomic regions (Figures 2 & 3). This difference was statistically significant as mean disomic PID per ohnolog = 91.28, n = 11,402, was lower than the mean tetrasomic PID per ohnolog = 94.98, n = 4,556 (t = -43.989, df = 9133.3, p-value < 2.2e-16). Despite the high sequence similarity for ohnologs in most tetrasomic pairings, ohnologs on Omy01q and Omy23 had lower levels of sequence similarity (only 25% of ohnologs had >95% PID) whereas most ohnolog pairs in these regions had medium (90–95%) or low (<90%) sequence similarity (Figure 4). This result confirms previous studies in Atlantic salmon (Lien et al., 2016) and rainbow trout (Pearse et al. 2018) that found that the homologs of Omy01q and Omy23 (Ssa18qa and Ssa01qa) show reduced evidence of tetrasomic inheritance compared to the other seven tetrasomic pairings. Summary of ohnologs split by identity and location in genome. Ohnolog pairs are divided into three categories of overall similarity in terms of DNA sequence similarity for both tetrasomic and disomic pairs, and the percentage of each category is presented Table 1 Summary of ohnologs split by identity and location in genome. Ohnolog pairs are divided into three categories of overall similarity in terms of DNA sequence similarity for both tetrasomic and disomic pairs, and the percentage of each category is presented Similarity Category . Tetrasomic Ohnolog Pairs . Category as Percentage . Disomic Ohnolog Pairs . Category as Percentage . >95% 1,410 62% 1,591 28% 95–90% 528 23% 1,950 34% <90% 340 15% 2,160 38% Total 2,278 5,701 Similarity Category . Tetrasomic Ohnolog Pairs . Category as Percentage . Disomic Ohnolog Pairs . Category as Percentage . >95% 1,410 62% 1,591 28% 95–90% 528 23% 1,950 34% <90% 340 15% 2,160 38% Total 2,278 5,701 Open in new tab Table 1 Summary of ohnologs split by identity and location in genome. Ohnolog pairs are divided into three categories of overall similarity in terms of DNA sequence similarity for both tetrasomic and disomic pairs, and the percentage of each category is presented Similarity Category . Tetrasomic Ohnolog Pairs . Category as Percentage . Disomic Ohnolog Pairs . Category as Percentage . >95% 1,410 62% 1,591 28% 95–90% 528 23% 1,950 34% <90% 340 15% 2,160 38% Total 2,278 5,701 Similarity Category . Tetrasomic Ohnolog Pairs . Category as Percentage . Disomic Ohnolog Pairs . Category as Percentage . >95% 1,410 62% 1,591 28% 95–90% 528 23% 1,950 34% <90% 340 15% 2,160 38% Total 2,278 5,701 Open in new tab Gene expression analysis On average, the fifteen rainbow trout samples from PRJNA269115 had 18,420,094.13 reads aligned to genes in the rainbow trout genome (Minimum 4,404,216, Maximum 25,608,943, Supplemental File S2). In the four sample groups (A x A Female, A x A Male, R x R Female, and R x R Male) the vast majority of ohnolog pairs were expressed (from 7,802 to 7,860) in all samples (Table 2). The absolute values of log2 fold changes in expressed genes were consistently lower between ohnologs located in tetrasomic regions than between pairs in disomic regions in all seven comparisons of the expression data (t = 8.8826 to 9.6825, P < 0.001 in all contrasts; Table 2). Visualizations of expression data shows that tetrasomic genes cluster toward the ends of chromosomes and exhibit less ohnolog to ohnolog variation in expression than those in disomic regions (Figure 5). For each cross split by sex the mean and variance for the absolute value of log2 fold change for both disomically and tetrasomically inherited ohnologs is presented. The results of Welch t-Tests testing for a difference in means with the 95% confidence interval of the test are presented Table 2 For each cross split by sex the mean and variance for the absolute value of log2 fold change for both disomically and tetrasomically inherited ohnologs is presented. The results of Welch t-Tests testing for a difference in means with the 95% confidence interval of the test are presented Cross Type . Sex . Mean Absolute Value of Log2 Fold Change between ohnologs . Variance Absolute Value of Log2 Fold Change between ohnologs . Welch t-Test Results . 0.95 . Disomic . Tetrasomic . Disomic . Tetrasomic . A x A F 2.11 1.78 5.22 4.14 t = 8.8826, df = 9147.3, p-value < 2.2e-16 0.26 - 0.40 A x A M 2.11 1.76 5.02 3.94 t = 9.4028, df = 9107.8, p-value < 2.2e-16 0.28 - 0.42 A x A All 2.08 1.74 5.04 3.98 t = 9.2441, df = 9178.2, p-value < 2.2e-16 0.27 - 0.41 R x R F 2.08 1.72 5.38 4.21 t = 9.5302, df = 9186.5, p-value < 2.2e-16 0.29 - 0.43 R x R M 2.08 1.73 5.36 4.16 t = 9.2808, df = 9197.5, p-value < 2.2e-16 0.28 - 0.42 R x R All 2.05 1.69 5.24 4.03 t = 9.6825, df = 9294.2, p-value < 2.2e-16 0.29 - 0.43 Both All 2.04 1.69 5.08 3.96 t = 9.5941, df = 9255.6, p-value < 2.2e-16 0.28 - 0.42 Cross Type . Sex . Mean Absolute Value of Log2 Fold Change between ohnologs . Variance Absolute Value of Log2 Fold Change between ohnologs . Welch t-Test Results . 0.95 . Disomic . Tetrasomic . Disomic . Tetrasomic . A x A F 2.11 1.78 5.22 4.14 t = 8.8826, df = 9147.3, p-value < 2.2e-16 0.26 - 0.40 A x A M 2.11 1.76 5.02 3.94 t = 9.4028, df = 9107.8, p-value < 2.2e-16 0.28 - 0.42 A x A All 2.08 1.74 5.04 3.98 t = 9.2441, df = 9178.2, p-value < 2.2e-16 0.27 - 0.41 R x R F 2.08 1.72 5.38 4.21 t = 9.5302, df = 9186.5, p-value < 2.2e-16 0.29 - 0.43 R x R M 2.08 1.73 5.36 4.16 t = 9.2808, df = 9197.5, p-value < 2.2e-16 0.28 - 0.42 R x R All 2.05 1.69 5.24 4.03 t = 9.6825, df = 9294.2, p-value < 2.2e-16 0.29 - 0.43 Both All 2.04 1.69 5.08 3.96 t = 9.5941, df = 9255.6, p-value < 2.2e-16 0.28 - 0.42 Open in new tab Table 2 For each cross split by sex the mean and variance for the absolute value of log2 fold change for both disomically and tetrasomically inherited ohnologs is presented. The results of Welch t-Tests testing for a difference in means with the 95% confidence interval of the test are presented Cross Type . Sex . Mean Absolute Value of Log2 Fold Change between ohnologs . Variance Absolute Value of Log2 Fold Change between ohnologs . Welch t-Test Results . 0.95 . Disomic . Tetrasomic . Disomic . Tetrasomic . A x A F 2.11 1.78 5.22 4.14 t = 8.8826, df = 9147.3, p-value < 2.2e-16 0.26 - 0.40 A x A M 2.11 1.76 5.02 3.94 t = 9.4028, df = 9107.8, p-value < 2.2e-16 0.28 - 0.42 A x A All 2.08 1.74 5.04 3.98 t = 9.2441, df = 9178.2, p-value < 2.2e-16 0.27 - 0.41 R x R F 2.08 1.72 5.38 4.21 t = 9.5302, df = 9186.5, p-value < 2.2e-16 0.29 - 0.43 R x R M 2.08 1.73 5.36 4.16 t = 9.2808, df = 9197.5, p-value < 2.2e-16 0.28 - 0.42 R x R All 2.05 1.69 5.24 4.03 t = 9.6825, df = 9294.2, p-value < 2.2e-16 0.29 - 0.43 Both All 2.04 1.69 5.08 3.96 t = 9.5941, df = 9255.6, p-value < 2.2e-16 0.28 - 0.42 Cross Type . Sex . Mean Absolute Value of Log2 Fold Change between ohnologs . Variance Absolute Value of Log2 Fold Change between ohnologs . Welch t-Test Results . 0.95 . Disomic . Tetrasomic . Disomic . Tetrasomic . A x A F 2.11 1.78 5.22 4.14 t = 8.8826, df = 9147.3, p-value < 2.2e-16 0.26 - 0.40 A x A M 2.11 1.76 5.02 3.94 t = 9.4028, df = 9107.8, p-value < 2.2e-16 0.28 - 0.42 A x A All 2.08 1.74 5.04 3.98 t = 9.2441, df = 9178.2, p-value < 2.2e-16 0.27 - 0.41 R x R F 2.08 1.72 5.38 4.21 t = 9.5302, df = 9186.5, p-value < 2.2e-16 0.29 - 0.43 R x R M 2.08 1.73 5.36 4.16 t = 9.2808, df = 9197.5, p-value < 2.2e-16 0.28 - 0.42 R x R All 2.05 1.69 5.24 4.03 t = 9.6825, df = 9294.2, p-value < 2.2e-16 0.29 - 0.43 Both All 2.04 1.69 5.08 3.96 t = 9.5941, df = 9255.6, p-value < 2.2e-16 0.28 - 0.42 Open in new tab Of the 42,087 expressed genes in the brain transcriptome, 367 are upregulated in A x A fish and 209 in R x R fish when testing for differential expression with sex as a co-factor (n = 8 and n = 7, Supplemental File S3). When cross types were further divided by sex, 212 genes were differentially expressed between cross types in at least one contrast, of which, 26 genes were upregulated in A x A females, 30 were upregulated in R x R females, 40 genes were upregulated in A x A males, and 116 were upregulated in R x R males. Of these differentially expressed genes, eight and seven were ohnologs in the A x A females and R x R females respectively, and 17 and 41 were ohnologs in the R x R females and R x R males respectively, indicating that some genes in the brain transcriptome and potentially important in the development of anadromy are ohnologs. GO analysis A total of 7,692 ohnolog pairs (out of 7,979) were annotated against the UniProt database. Enrichment analysis revealed that 49 GO terms were overrepresented in tetrasomically inherited ohnologs compared to disomic ohnologs from 185 genes (Table 3; Supplemental File S4). These terms represent an enrichment of functions connected to iron binding and respiration, with three Molecular Functions— iron ion binding, oxidoreductase activity, and oxygen binding— enriched in both cross types. Genes annotated with these GO terms included many myosin, cytochrome P450, and hemoglobin genes, suggesting conservation of genes connected to respiration and gaseous exchange being maintained in tetrasomic regions of high sequence similarity (see Supplemental File S4 for a full list of genes annotated with enriched GO terms). Enriched GO terms in tetrasomic high similarity (>95% protein similarity). GO categories are abbreviated to BP (biological process), MF (molecular function), and CC (cellular component. P-values following a Fisher’s exact test are reported Table 3 Enriched GO terms in tetrasomic high similarity (>95% protein similarity). GO categories are abbreviated to BP (biological process), MF (molecular function), and CC (cellular component. P-values following a Fisher’s exact test are reported GO ID . GO Term . . P-value . GO:0051295 establishment of meiotic spindle localization BP 4.38E-05 GO:0010728 regulation of hydrogen peroxide biosynthetic process BP 9.27E-05 GO:0010248 establishment or maintenance of transmembrane electrochemical gradient BP 1.29E-04 GO:0050665 hydrogen peroxide biosynthetic process BP 3.80E-04 GO:0090662 ATP hydrolysis coupled transmembrane transport BP 6.41E-04 GO:1903919 negative regulation of actin filament severing BP 9.22E-04 GO:0010729 positive regulation of hydrogen peroxide biosynthetic process BP 9.22E-04 GO:0032796 uropod organization BP 1.10E-03 GO:1903918 regulation of actin filament severing BP 1.10E-03 GO:0021678 third ventricle development BP 1.13E-03 GO:0040023 establishment of nucleus localization BP 1.22E-03 GO:0006958 complement activation, classical pathway BP 1.89E-03 GO:0070602 regulation of centromeric sister chromatid cohesion BP 1.89E-03 GO:0007097 nuclear migration BP 2.07E-03 GO:0001778 plasma membrane repair BP 2.41E-03 GO:0030241 skeletal muscle myosin thick filament assembly BP 2.75E-03 GO:0071688 striated muscle myosin thick filament assembly BP 2.75E-03 GO:0002455 humoral immune response mediated by circulating immunoglobulin BP 2.85E-03 GO:0010726 positive regulation of hydrogen peroxide metabolic process BP 3.02E-03 GO:0021592 fourth ventricle development BP 3.02E-03 GO:0060004 reflex BP 5.58E-03 GO:0031034 myosin filament assembly BP 5.75E-03 GO:0030220 platelet formation BP 6.29E-03 GO:0036344 platelet morphogenesis BP 6.29E-03 GO:0070162 adiponectin secretion BP 6.63E-03 GO:0070163 regulation of adiponectin secretion BP 6.63E-03 GO:1903921 regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1903923 positive regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1900756 protein processing in phagocytic vesicle BP 6.80E-03 GO:0048172 regulation of short-term neuronal synaptic plasticity BP 7.58E-03 GO:1904707 positive regulation of vascular smooth muscle cell proliferation BP 8.64E-03 GO:0060283 negative regulation of oocyte development BP 8.64E-03 GO:0070989 oxidative demethylation BP 8.65E-03 GO:0031449 regulation of slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0031444 slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0008635 activation of cysteine-type endopeptidase activity involved in apoptotic process cytochrome c BP 8.65E-03 GO:0005826 actomyosin contractile ring CC 1.54E-04 GO:0005833 hemoglobin complex CC 2.85E-03 GO:0016705 oxidoreductase activity, acting on paired donors, with incorporation or reduction of oxygen MF 5.14E-05 GO:0005506 iron ion binding MF 1.95E-04 GO:0019825 oxygen binding MF 3.16E-04 GO:0043495 protein anchor MF 2.75E-03 GO:0030250 guanylate cyclase activator activity MF 6.63E-03 GO:0030249 guanylate cyclase regulator activity MF 6.63E-03 GO:0019785 ISG15-specific protease activity MF 6.63E-03 GO:0010853 cyclase activator activity MF 6.63E-03 GO:0005344 oxygen transporter activity MF 6.80E-03 GO:0004030 aldehyde dehydrogenase [NAD(P)+] activity MF 8.65E-03 GO:0016840 carbon-nitrogen lyase activity MF 8.65E-03 GO ID . GO Term . . P-value . GO:0051295 establishment of meiotic spindle localization BP 4.38E-05 GO:0010728 regulation of hydrogen peroxide biosynthetic process BP 9.27E-05 GO:0010248 establishment or maintenance of transmembrane electrochemical gradient BP 1.29E-04 GO:0050665 hydrogen peroxide biosynthetic process BP 3.80E-04 GO:0090662 ATP hydrolysis coupled transmembrane transport BP 6.41E-04 GO:1903919 negative regulation of actin filament severing BP 9.22E-04 GO:0010729 positive regulation of hydrogen peroxide biosynthetic process BP 9.22E-04 GO:0032796 uropod organization BP 1.10E-03 GO:1903918 regulation of actin filament severing BP 1.10E-03 GO:0021678 third ventricle development BP 1.13E-03 GO:0040023 establishment of nucleus localization BP 1.22E-03 GO:0006958 complement activation, classical pathway BP 1.89E-03 GO:0070602 regulation of centromeric sister chromatid cohesion BP 1.89E-03 GO:0007097 nuclear migration BP 2.07E-03 GO:0001778 plasma membrane repair BP 2.41E-03 GO:0030241 skeletal muscle myosin thick filament assembly BP 2.75E-03 GO:0071688 striated muscle myosin thick filament assembly BP 2.75E-03 GO:0002455 humoral immune response mediated by circulating immunoglobulin BP 2.85E-03 GO:0010726 positive regulation of hydrogen peroxide metabolic process BP 3.02E-03 GO:0021592 fourth ventricle development BP 3.02E-03 GO:0060004 reflex BP 5.58E-03 GO:0031034 myosin filament assembly BP 5.75E-03 GO:0030220 platelet formation BP 6.29E-03 GO:0036344 platelet morphogenesis BP 6.29E-03 GO:0070162 adiponectin secretion BP 6.63E-03 GO:0070163 regulation of adiponectin secretion BP 6.63E-03 GO:1903921 regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1903923 positive regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1900756 protein processing in phagocytic vesicle BP 6.80E-03 GO:0048172 regulation of short-term neuronal synaptic plasticity BP 7.58E-03 GO:1904707 positive regulation of vascular smooth muscle cell proliferation BP 8.64E-03 GO:0060283 negative regulation of oocyte development BP 8.64E-03 GO:0070989 oxidative demethylation BP 8.65E-03 GO:0031449 regulation of slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0031444 slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0008635 activation of cysteine-type endopeptidase activity involved in apoptotic process cytochrome c BP 8.65E-03 GO:0005826 actomyosin contractile ring CC 1.54E-04 GO:0005833 hemoglobin complex CC 2.85E-03 GO:0016705 oxidoreductase activity, acting on paired donors, with incorporation or reduction of oxygen MF 5.14E-05 GO:0005506 iron ion binding MF 1.95E-04 GO:0019825 oxygen binding MF 3.16E-04 GO:0043495 protein anchor MF 2.75E-03 GO:0030250 guanylate cyclase activator activity MF 6.63E-03 GO:0030249 guanylate cyclase regulator activity MF 6.63E-03 GO:0019785 ISG15-specific protease activity MF 6.63E-03 GO:0010853 cyclase activator activity MF 6.63E-03 GO:0005344 oxygen transporter activity MF 6.80E-03 GO:0004030 aldehyde dehydrogenase [NAD(P)+] activity MF 8.65E-03 GO:0016840 carbon-nitrogen lyase activity MF 8.65E-03 Open in new tab Table 3 Enriched GO terms in tetrasomic high similarity (>95% protein similarity). GO categories are abbreviated to BP (biological process), MF (molecular function), and CC (cellular component. P-values following a Fisher’s exact test are reported GO ID . GO Term . . P-value . GO:0051295 establishment of meiotic spindle localization BP 4.38E-05 GO:0010728 regulation of hydrogen peroxide biosynthetic process BP 9.27E-05 GO:0010248 establishment or maintenance of transmembrane electrochemical gradient BP 1.29E-04 GO:0050665 hydrogen peroxide biosynthetic process BP 3.80E-04 GO:0090662 ATP hydrolysis coupled transmembrane transport BP 6.41E-04 GO:1903919 negative regulation of actin filament severing BP 9.22E-04 GO:0010729 positive regulation of hydrogen peroxide biosynthetic process BP 9.22E-04 GO:0032796 uropod organization BP 1.10E-03 GO:1903918 regulation of actin filament severing BP 1.10E-03 GO:0021678 third ventricle development BP 1.13E-03 GO:0040023 establishment of nucleus localization BP 1.22E-03 GO:0006958 complement activation, classical pathway BP 1.89E-03 GO:0070602 regulation of centromeric sister chromatid cohesion BP 1.89E-03 GO:0007097 nuclear migration BP 2.07E-03 GO:0001778 plasma membrane repair BP 2.41E-03 GO:0030241 skeletal muscle myosin thick filament assembly BP 2.75E-03 GO:0071688 striated muscle myosin thick filament assembly BP 2.75E-03 GO:0002455 humoral immune response mediated by circulating immunoglobulin BP 2.85E-03 GO:0010726 positive regulation of hydrogen peroxide metabolic process BP 3.02E-03 GO:0021592 fourth ventricle development BP 3.02E-03 GO:0060004 reflex BP 5.58E-03 GO:0031034 myosin filament assembly BP 5.75E-03 GO:0030220 platelet formation BP 6.29E-03 GO:0036344 platelet morphogenesis BP 6.29E-03 GO:0070162 adiponectin secretion BP 6.63E-03 GO:0070163 regulation of adiponectin secretion BP 6.63E-03 GO:1903921 regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1903923 positive regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1900756 protein processing in phagocytic vesicle BP 6.80E-03 GO:0048172 regulation of short-term neuronal synaptic plasticity BP 7.58E-03 GO:1904707 positive regulation of vascular smooth muscle cell proliferation BP 8.64E-03 GO:0060283 negative regulation of oocyte development BP 8.64E-03 GO:0070989 oxidative demethylation BP 8.65E-03 GO:0031449 regulation of slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0031444 slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0008635 activation of cysteine-type endopeptidase activity involved in apoptotic process cytochrome c BP 8.65E-03 GO:0005826 actomyosin contractile ring CC 1.54E-04 GO:0005833 hemoglobin complex CC 2.85E-03 GO:0016705 oxidoreductase activity, acting on paired donors, with incorporation or reduction of oxygen MF 5.14E-05 GO:0005506 iron ion binding MF 1.95E-04 GO:0019825 oxygen binding MF 3.16E-04 GO:0043495 protein anchor MF 2.75E-03 GO:0030250 guanylate cyclase activator activity MF 6.63E-03 GO:0030249 guanylate cyclase regulator activity MF 6.63E-03 GO:0019785 ISG15-specific protease activity MF 6.63E-03 GO:0010853 cyclase activator activity MF 6.63E-03 GO:0005344 oxygen transporter activity MF 6.80E-03 GO:0004030 aldehyde dehydrogenase [NAD(P)+] activity MF 8.65E-03 GO:0016840 carbon-nitrogen lyase activity MF 8.65E-03 GO ID . GO Term . . P-value . GO:0051295 establishment of meiotic spindle localization BP 4.38E-05 GO:0010728 regulation of hydrogen peroxide biosynthetic process BP 9.27E-05 GO:0010248 establishment or maintenance of transmembrane electrochemical gradient BP 1.29E-04 GO:0050665 hydrogen peroxide biosynthetic process BP 3.80E-04 GO:0090662 ATP hydrolysis coupled transmembrane transport BP 6.41E-04 GO:1903919 negative regulation of actin filament severing BP 9.22E-04 GO:0010729 positive regulation of hydrogen peroxide biosynthetic process BP 9.22E-04 GO:0032796 uropod organization BP 1.10E-03 GO:1903918 regulation of actin filament severing BP 1.10E-03 GO:0021678 third ventricle development BP 1.13E-03 GO:0040023 establishment of nucleus localization BP 1.22E-03 GO:0006958 complement activation, classical pathway BP 1.89E-03 GO:0070602 regulation of centromeric sister chromatid cohesion BP 1.89E-03 GO:0007097 nuclear migration BP 2.07E-03 GO:0001778 plasma membrane repair BP 2.41E-03 GO:0030241 skeletal muscle myosin thick filament assembly BP 2.75E-03 GO:0071688 striated muscle myosin thick filament assembly BP 2.75E-03 GO:0002455 humoral immune response mediated by circulating immunoglobulin BP 2.85E-03 GO:0010726 positive regulation of hydrogen peroxide metabolic process BP 3.02E-03 GO:0021592 fourth ventricle development BP 3.02E-03 GO:0060004 reflex BP 5.58E-03 GO:0031034 myosin filament assembly BP 5.75E-03 GO:0030220 platelet formation BP 6.29E-03 GO:0036344 platelet morphogenesis BP 6.29E-03 GO:0070162 adiponectin secretion BP 6.63E-03 GO:0070163 regulation of adiponectin secretion BP 6.63E-03 GO:1903921 regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1903923 positive regulation of protein processing in phagocytic vesicle BP 6.80E-03 GO:1900756 protein processing in phagocytic vesicle BP 6.80E-03 GO:0048172 regulation of short-term neuronal synaptic plasticity BP 7.58E-03 GO:1904707 positive regulation of vascular smooth muscle cell proliferation BP 8.64E-03 GO:0060283 negative regulation of oocyte development BP 8.64E-03 GO:0070989 oxidative demethylation BP 8.65E-03 GO:0031449 regulation of slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0031444 slow-twitch skeletal muscle fiber contraction BP 8.65E-03 GO:0008635 activation of cysteine-type endopeptidase activity involved in apoptotic process cytochrome c BP 8.65E-03 GO:0005826 actomyosin contractile ring CC 1.54E-04 GO:0005833 hemoglobin complex CC 2.85E-03 GO:0016705 oxidoreductase activity, acting on paired donors, with incorporation or reduction of oxygen MF 5.14E-05 GO:0005506 iron ion binding MF 1.95E-04 GO:0019825 oxygen binding MF 3.16E-04 GO:0043495 protein anchor MF 2.75E-03 GO:0030250 guanylate cyclase activator activity MF 6.63E-03 GO:0030249 guanylate cyclase regulator activity MF 6.63E-03 GO:0019785 ISG15-specific protease activity MF 6.63E-03 GO:0010853 cyclase activator activity MF 6.63E-03 GO:0005344 oxygen transporter activity MF 6.80E-03 GO:0004030 aldehyde dehydrogenase [NAD(P)+] activity MF 8.65E-03 GO:0016840 carbon-nitrogen lyase activity MF 8.65E-03 Open in new tab Differentially expressed genes between cross types were generally found in disomic rather than tetrasomic regions of the genome. Most of the differentially expressed genes in disomic regions were associated with GO terms connected to functions such as nervous system development, neuron differentiation, brain development and gland development (Supplemental File S5). Largely the same under-represented GO terms were assigned to genes upregulated in R x R fish. Only one gene that was differentially expressed had a GO term that is over-represented in tetrasomic genomic regions. The gene CIGENEomyV6.45980 located on Omy13q, with the GO term “signal transducer activity” was upregulated in the A x A fish compared to the R x R (Supplemental File S5). Protein complexes We obtained 11,135 disomic ohnologs and 4,336 tetrasomic ohnologs from the rainbow trout genome annotations that also contained UniProtKB accessions. From testing for different proportions of protein-protein interactions between disomic and tetrasomic ohnologs, only two significantly different proportions were detected. The mouse UniProt data indicated that the proportion of tetrasomic ohnologs identified as monomers is ∼1.7 times that of disomic ohnologs and significantly different (p – value = 0.019). Additionally, the proportion of tetrasomic ohnologs identified as heterodimers is ∼1.4 times that of disomic ohnologs and significantly different (p – value = 0.032). The full results for all three references are presented in Supplemental File S6. Discussion All vertebrates are descended from a common ancestor with two historic WGD events (Blomme et al., 2006; Dehal and Boore 2005; Nakatani et al., 2007; Vandepoele et al., 2004). However, few subsequent vertebrate WGDs have been documented, which makes investigating the fate of ohnologs difficult, as the genomes of most vertebrates have reverted to diploidy (Mable 2004; Orr 1990). To that end, the teleosts are an excellent group for studying the effects of WGD as not only do they share a third WGD event (∼350 million years ago), but several lineages also have independently undergone a fourth WGD event (e.g., the catostomids, cyprinids, and salmonids: Allendorf and Thorgaard 1984; Ohno et al., 1967; Uyeno and Smith 1972). These more recent WGD events provide opportunities to ask questions about how WGD affects genome organization and how the rate of diploidization varies between species and among different regions of the genome. Although gene duplication has long been hypothesized to generate novelty by permitting adaptation via the evolution of new molecular functions (i.e., neofunctionalization; Ohno 1970), here we demonstrate that gene conservation is also a substantial outcome of WGD, at least for salmonids. For example, despite the fact that only 10% of the rainbow trout genome is tetrasomically inherited, ∼28% of conserved ohnolog pairs are located in tetrasomic regions, indicating that tetrasomic inheritance suppresses the process of neofunctionalization and molecular adaptation (see Figure 1). In addition, we demonstrate that tetrasomic ohnologs are conserved in both function and expression and are enriched for molecular processes that might play important roles in salmonid life history adaptation. Figure 1 Open in new tabDownload slide Circos plot showing homeologous blocks in the rainbow trout genome dating from the last whole-genome duplication in salmonids. Chromosomes (Omy01-Omy29) are plotted, arms (e.g., 1p, and 1q) are shaded, and the length of the chromosomes are indicated. Links show pairing between genomic regions originating from duplication at the Ss4R. Track A, overall similarity between homeologous regions is indicated by shading, yellow - low, red - high, and height of the plot. Track B. The eight pairs of homeologous blocks still exhibiting tetrasomic inheritance are indicated by green bars in the outer ring. Circos plot adapted from Pearse et al. (2018). Conservation of the ‘Magic Eight’ Data generated from linkage mapping studies and whole genome sequencing projects suggests that eight pairs of homeologous chromosomes still form tetravalent meioses in Oncorhynchus, Salmo, and Salvelinus (e.g., Berthelot et al., 2014; Kodama et al., 2014; Lien et al., 2011; Sutherland et al., 2016). The analysis presented herein reveals that ohnologs in tetrasomic regions of the O. mykiss genome have greater sequence similarity compared to ohnologs in disomically inherited regions, presumably due to recombination between homeologs and a subsequent maintenance of genetic variation and gene function. By contrast, ohnologs in disomic regions are able to acquire mutations and diverge, and therefore have lower levels of sequence similarity. Interestingly, we found evidence that one pair of homeologs in rainbow trout (Omy01q and Omy23) shows reduced sequence similarity, in line with levels observed in disomically inherited ohnologs (see Figures 1, 2, and 4). This suggests that tetravalent meioses occur less frequently between Omy01q and Omy23 than the other seven homeologous pairs in rainbow trout. Similar evidence comes from the Atlantic salmon genome, as the homologous chromosome arms to Omy01q and Omy23 (Ssa18qa and Ssa01qa) also show reduced sequence similarity compared to other tetrasomic regions of the Atlantic salmon genome (Lien et al., 2016). We believe this is due to a reduction in the number of tetravalent meioses between Omy01q and Omy23 and a faster return to a disomic state than the other tetrasomic chromosomal regions. Further genome sequencing studies in Salvelinus and other Oncorhynchus will help confirm if reduced evidence for tetrasomy exists in the homologs of Omy01q and Omy23. Figure 2 Open in new tabDownload slide Sequence similarity between ohnologs in different regions of the rainbow trout genome. Disomic inherited regions of the genome are represented in blue and tetrasomic regions are represented in green. The x - axis is the position on each chromosome with percent identity in terms of DNA sequence similarity between ohnolog pairs plotted on the y - axis. Figure 3 Open in new tabDownload slide Histograms of the distribution of DNA sequence percent similarity (PID) of ohnolog pairs within disomic (blue) and tetrasomic (green) regions. Mean disomic PID = 91.28, n = 11,402. Mean tetrasomic PID = 94.98, n = 4,556. The means are significantly different (Welch Two Sample t-Test, t = -43.989, df = 9133.3, p-value < 2.2e-16). Figure 4 Open in new tabDownload slide Box plot showing variance in DNA sequence percentage identity between ohnologs located in tetrasomic regions of the genome. Ohnologs are split into eight groups based on their locations in known tetrasomic regions of the rainbow trout genome. Lines represent the median value for, boxes the first and third quartiles and whiskers represent the minimum and maximum value. Figure 5 Open in new tabDownload slide Two dimensional kernel density estimates of the absolute value of log2 fold change of ohnolog pairs located in disomic and tetrasomic genomic regions for (A) the female progeny of the A x A cross; (B) the male progeny of the A x A cross; (C) the female progeny of the R x R cross; and, (D) the male progeny of the R x R cross. The plot is color-coded by the density of (x,y) observations, where the x - axis is relative position along chromosomes, and the y - axis is the absolute value of log2 fold change between ohnologs. Red indicates a high density of observations, and blue indicates a low density. Tetrasomically inherited ohnologs are overall more similar in expression level than disomically inherited ohnologs and are clustered near the telomeric ends of chromosomes. Dangerous duplicates and dosage compensation retain tetrasomic ohnologs Although gene loss following WGD is the ultimate fate of most ohnologs it is clear that some ohnologs are retained (e.g., Kellis et al., 2004; Wolfe and Shields 1997). Maintaining two functional copies of a gene is thought to require the action of selection to either reduce the accumulation of mutations which leads to either nonfunctionalization or neofunctionalization (Braasch et al., 2018; Sandve et al., 2018), and/or to reduce the expression of both duplicates to match the expression pre-duplication. These two hypotheses both explain how some ohnologs but not others are maintained post duplication. Genes predisposed to haploinsufficiency may be more likely to be retained as functional duplicates to counteract the potential negative effects of mutations in one copy, that is, the dangerous duplicates hypothesis (Singh et al. 2012; 2015). However, selection to maintain duplicates and prevent haploinsufficiency has been suggested to be weak, limiting the potential for this explantion for duplicate retention (Pires and Conant; 2016). Nontheless, duplicates involved in immune function, cell cycle regulation, transcriptional control, and cell signaling pathways have been found to be retained during vertebrate evolution (e.g., Freeling and Thomas 2006; Makino and McLysaght 2010). However, enrichment analysis of GO terms presented herein found limited evidence of genes connected to such functions in tetrasomic regions of the genome. Instead, many of the enriched GO terms are connected to functions such as oxidoreductase activity, regulation of hydrogen peroxide, iron binding, and oxygen binding (Table 3). These functions may well be important in the development of life-history variation in salmonids and the smoltification process more broadly, suggesting that that selection can cause the retention of different ohnologs post-duplication depending on the organism-specific factors (e.g., ecological niche). In addition to trying to understand why some regions of the genome have been maintained as tetrasomic, we also wanted to explore if tetrasomic inheritance modifies the way ohnologs are expressed. The doubling of DNA post whole genome duplication could have a substantial effect on gene expression if, as theorized, duplicates quickly become non-functionalized and silenced. One mechanism that can reduce the effects of dosage imbalance after nonfunctionalization begins is reducing gene expression of both members of an ohnolog pair to equal gene expression pre-duplication (i.e., dosage compensation; Hughes et al. 2007). Previous studies in yeast, mice, and Paramecium suggest that duplicated genes show lower expression levels than non-duplicated genes regardless of function (e.g., Qian et al., 2010; Aury et al. 2006) and that genes involved in protein complexes with multiple subunits should be preferentially retained as duplicates (Roux et al., 2017; Veitia et al., 2008). We found evidence of reduced expression of ohnologs in tetrasomic regions compared to disomic regions in the brain transcriptome of rainbow trout (see Table 2) and evidence of differences in protein-protein interactions between tetrasomic and disomic ohnologs. Veitia et al. (2008) suggested that proteins involved in complex interactions (i.e., those with at least two different polypeptides and three subunits) should be more sensitive to dosage imbalance than proteins with more simple interactions. We divided genes into five groups of which one (heteromultimer) were suggested by Roux et al. (2017) to be the most sensitive to dosage imbalance. If retention of ohnologs in tetrasomic regions is due to sensitivity of genes to dosage imbalance, then it would be expected that genes involved in heteromultimers should be enriched in tetrasomic regions, which is not what we observed (p – value > 0.05 for each comparison; see Supplemental File S6). This might suggest a lack of support for dosage imbalance as a reason for retention of ohnologs in tetrasomic regions. However, it must be stressed that the number of ohnologs with known protein-protein interactions was small (especially for comparisons to the zebra fish and Atlantic salmon UniProtKB/Swiss-Prot databases) and this lack of significance could be an artifact of small sample size. In addition, we also see a difference in gene function, as previous studies have suggested that many of the ohnologs used to support the dosage-balance hypothesis are involved in essential cellular processes such as metabolism, transcriptional control, and translation. Again, our enrichment analysis does not suggest that genes with these functions are any more likely to be located in tetrasomic regions than disomic regions. Although it is certainly possible that the retention of many ohnologs in tetrasomic regions could be caused by selection impeding neofunctionalization and/or nonfunctionalization because any change would cause alterations in dosage-balance, it is highly likely that different processes are responsible for maintaining both copies of an ohnolog pair in the rainbow trout genome. Although we demonstrate that gene expression is reduced in ohnologs in tetrasomic regions of the rainbow trout genome, it is important to be mindful of the tissue type investigated. The brain is a key part of the neural system, and previous studies in a range of species (e.g., zebrafish and mice) suggest that genes important in the neural system are a) highly expressed, b) highly conserved, and c) contain a high proportion of ohnologs (Roux et al., 2017). Roux et al. (2017) consistently found that genes expressed in neural tissue are more likely to be retained in duplicates after WGD. Although few studies have investigated how tissue specific expression influences the process of ohnolog retention, many studies have found genes annotated with functions connected to neurodevelopment, cell signaling, and behavior to be more likely to be maintained as ohnologs than genes with other functions (e.g., Brunet et al., 2006; Howe et al., 2013; Putnam et al., 2008). Although it is impossible to make similar inferences between tissues with the data herein (especially as brain tissue is complex), future studies that aim to investigate expression patterns of ohnologs across different salmonid species, different tissues, and different time points would be enlightening. It is possible, that the patterns of expression discussed herein are time, tissue, population, or species specific, although this seems unlikely both due to previous studies that have documented a reduction in expression post duplication, and the conservation of homologous tetrasomic regions in Salmo, Salvelinus, and Oncorhynchus. Ultimately, gene expression reduction could be a mechanism that maintains duplicates, preventing them from returning to a diploid state. The enrichment of ohnologs in tetrasomic regions compared to disomic regions may suggest that genes located on these regions are essential for salmonid function and development. The salmonid-specific WGD and the development of anadromy The anadromous life cycles of many salmonids has long inspired debate about the potential link between whole-genome duplication and anadromy (Alexandrou et al., 2013; McDowall 2002). The propensity to migrate vs. maintain residency in rainbow trout is associated with genetic polymorphisms, gene expression differences, and differential methylation patterns (Baerwald et al., 2015; Hale et al., 2016, 2013; Hecht et al., 2015, 2012; McKinney et al., 2015; Pearse et al., 2014, 2018). Our GO analysis suggests that genes connected to several metabolic processes, such as oxygen binding and oxidoreductase activity, are located in tetrasomic regions of the rainbow trout genome. Such functions have an obvious connection to life history variation and the development of anadromy. Moreover, Robertson et al. (2017) suggests that several ohnolog pairs involved in hormonal regulation and ion transport including insulin growth factor 1 and thyroid hormone receptor alpha (i.e., processes strongly linked with smoltification) are located in tetrasomic regions of the Atlantic salmon genome. However, many other genes known to be involved in anadromy, including the major chromosomal rearrangement on chromosome Omy05 (Pearse et al. 2018), are not located in tetrasomic regions (e.g., many hormone receptors, genes involved in maintenance of ionic balance, and growth genes). Therefore, any link between anadromy and the salmonid WGD is circumspect, as it is clear that this complex phenotype is caused by many molecular pathways located in different regions of the salmonid genome. Moreover, multiple studies suggest that, at least in rainbow trout, the molecular control of anadromy varies between different populations, suggesting plasticity in the development of different life history strategies making it unlikely that the WGD is, at least currently, a major factor in life history development (e.g., Hale et al., 2013; Hecht et al., 2013, 2012; Nichols et al., 2008). Conclusions Tetrasomic regions of the rainbow trout genome contain a higher density of ohnologs, are more similar in their sequence identity, have lower overall expression, and are expressed more similarly than ohnologs in disomic regions. The conservation of a large portion of ohnologs post-WGD in rainbow trout may be because modification of these ohnologs results in negative effects on the organism. Understanding the effects on genome organization of WGD is hampered by difficulties in identifying ancient autopolyploids. The identification and study of additional teleost polyploid lineages could lead to a more thorough understanding on the fates of genes post-WGD. Why some genes are maintained as duplicates post-WGD, whereas others undergo neofunctionalization are important questions to pursue in the field of polyploidy research. Ultimately, our understanding of such processes is strongly biased toward plants and mammals. Additional research in more lineages of fishes may prove insightful in our understanding of the consequences of WGD and the identification of general outcomes from lineage-specific outcomes. Acknowledgments The authors wish to thank Gareth Gillard, Torgeir R. Hvidsten and Simen R. Sandve for generating the table of rainbow trout ohnologs used in this manuscript. We also would like to thank the editor and two anonymous referees for comments and suggestions that have improved the manuscript. Footnotes Supplemental material available at FigShare: https://doi.org/10.25387/g3.7732358. Communicating editor: D. Liberles Literature Cited Alexandrou M A , Swartz B A, Matzke N J, Oakley T H, 2013   Genome duplication and multiple evolutionary origins of complex migratory behavior in Salmonidae. Mol. Phylogenet. Evol. 69 : 514 – 523 . 10.1016/j.ympev.2013.07.026 Google Scholar Crossref Search ADS PubMed WorldCat Allendorf F W , Thorgaard G, 1984   Tetraploidy and the Evolution of Salmonid Fishes , pp. 1 – 53 in Evolutionary Genetics of Fishes , edited by Turner B Monographs in Evolutionary Biology , Springer, US . 10.1007/978-1-4684-4652-4_1 Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Allendorf F W , Bassham S, Cresko W A, Limborg M T, Seeb L W, Seeb J E, 2015   Effects of crossovers between homeologs on inheritance and population genomics in polyploid-derived salmonid fishes. J. Hered 106 : 217 – 227 . Google Scholar Crossref Search ADS PubMed WorldCat Altschul S F , Gish W, Miller W, Myers E W, Lipman D J, 1990   Basic local alignment search tool. J. Mol. Biol. 215 : 403 – 410 . 10.1016/S0022-2836(05)80360-2 Google Scholar Crossref Search ADS PubMed WorldCat Anders S , Pyl P T, Huber W, 2015   HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31 : 166 – 169 . 10.1093/bioinformatics/btu638 Google Scholar Crossref Search ADS PubMed WorldCat Aury J-M , Jaillon O, Duret L, Noel B, Jubin C et al. , 2006   Global trends of whole-genome duplications revealed by the ciliate Paramecium tetraurelia. Nature 444 : 171 – 178 . 10.1038/nature05230 Google Scholar Crossref Search ADS PubMed WorldCat Baerwald M R , Meek M H, Stephens M R, Nagarajan R P, Goodbla A M et al. , 2015   Migration‐related phenotypic divergence is associated with epigenetic modifications in rainbow trout. Mol. Ecol. 10.1111/mec.13231 Google Scholar OpenURL Placeholder Text WorldCat Crossref Benjamini Y , Hochberg Y, 1995   Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Methodol. 57 : 289 – 300 . Google Scholar OpenURL Placeholder Text WorldCat Berthelot C , Brunet F, Chalopin D, Juanchich A, Bernard M et al. , 2014   The rainbow trout genome provides novel insights into evolution after whole-genome duplication in vertebrates. Nat. Commun. 5 : 3657 . 10.1038/ncomms4657 Google Scholar Crossref Search ADS PubMed WorldCat Blomme T , Vandepoele K, De Bodt S, Simillion C, Maere S et al. , 2006   The gain and loss of genes during 600 million years of vertebrate evolution. Genome Biol. 7 : R43 . 10.1186/gb-2006-7-5-r43 Google Scholar Crossref Search ADS PubMed WorldCat Bolger A M , Lohse M, Usadel B, 2014   Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30 : 2114 – 2120 . 10.1093/bioinformatics/btu170 Google Scholar Crossref Search ADS PubMed WorldCat Braasch I , Bobe J, Guiguen Y, Postlethwait J H, 2018   Reply to: ‘Subfunctionalization vs. neofunctionalization after whole-genome duplication.’ . Nat. Genet. 50 : 910 – 911 . 10.1038/s41588-018-0163-3 Google Scholar Crossref Search ADS PubMed WorldCat Braasch I , Gehrke A R, Smith J J, Kawasaki K, Manousaki T et al. , 2016   The spotted gar genome illuminates vertebrate evolution and facilitates human-teleost comparisons. Nat. Genet. 48 : 427 – 437 . 10.1038/ng.3526 Google Scholar Crossref Search ADS PubMed WorldCat Braasch I , Postlethwait J H, 2012   Polyploidy in fish and the teleost genome duplication , pp. 341 – 383 in Polyploidy and Genome Evolution. , edited by Soltis P S, Soltis D E, Springer , Berlin, Heidelberg . 10.1007/978-3-642-31442-1_17 Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Brieuc MSO , Waters CD, Seeb JE, Naish KA, 2014  A dense linkage map for Chinook salmon (Oncorhynchus tshawytscha) reveals variable chromosomal divergence after an ancestral whole genome duplication event. G3 (Bethesda) 4: 447. 10.1534/g3.113.009316 Crossref Brunet F G , Crollius H R, Paris M, Aury J-M, Gibert P et al. , 2006   Gene loss and evolutionary rates following whole-genome duplication in teleost fishes. Mol. Biol. Evol. 23 : 1808 – 1816 . 10.1093/molbev/msl049 Google Scholar Crossref Search ADS PubMed WorldCat Campbell M A , Ganley A R D, Gabaldón T, Cox M P, 2016   The case of the missing ancient fungal polyploids. Am. Nat. 188 : 602 – 614 . 10.1086/688763 Google Scholar Crossref Search ADS PubMed WorldCat Dean E J , Davis J C, Davis R W, Petrov D A, 2008   Pervasive and persistent redundancy among duplicated genes in yeast. PLoS Genet. 4 : e1000113. 10.1371/journal.pgen.1000113 Google Scholar OpenURL Placeholder Text WorldCat Crossref Dehal P , Boore J L, 2005   Two rounds of whole genome duplication in the ancestral vertebrate. PLoS Biol. 3 : e314. 10.1371/journal.pbio.0030314 Google Scholar OpenURL Placeholder Text WorldCat Crossref Edger P P , Pires J C, 2009   Gene and genome duplications: the impact of dosage-sensitivity on the fate of nuclear genes. Chromosome Res. 17 : 699 – 717 . 10.1007/s10577-009-9055-9 Google Scholar Crossref Search ADS PubMed WorldCat Force A , Lynch M, Pickett F B, Amores A, Yan Y et al. , 1999   Preservation of duplicate genes by complementary, degenerative mutations. Genetics 151 : 1531 – 1545 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Freeling M , Thomas B C, 2006   Gene-balanced duplications, like tetraploidy, provide predictable drive to increase morphological complexity. Genome Res. 16 : 805 – 814 . 10.1101/gr.3681406 Google Scholar Crossref Search ADS PubMed WorldCat Gerstein A C , Otto S P, 2009   Ploidy and the causes of genomic evolution. J. Hered. 100 : 571 – 581 . 10.1093/jhered/esp057 Google Scholar Crossref Search ADS PubMed WorldCat Hale M C , McKinney G J, Thrower F P, Nichols K M, 2016   RNA-seq reveals differential gene expression in the brains of juvenile resident and migratory smolt rainbow trout (Oncorhynchus mykiss). Comp. Biochem. Physiol. Part D Genomics Proteomics 20 : 136 – 150 . 10.1016/j.cbd.2016.07.006 Google Scholar Crossref Search ADS PubMed WorldCat Hale M C , Thrower F P, Berntson E A, Miller M R, Nichols K M, 2013  Evaluating adaptive divergence between migratory and nonmigratory ecotypes of a salmonid fish, Oncorhynchus mykiss. G3 (Bethesda) 3: 1273. 10.1534/g3.113.006817 Crossref Hecht B C , Campbell N R, Holecek D E, Narum S R, 2013   Genome‐wide association reveals genetic basis for the propensity to migrate in wild populations of rainbow and steelhead trout. Mol. Ecol. 22 : 3061 – 3076 . 10.1111/mec.12082 Google Scholar Crossref Search ADS PubMed WorldCat Hecht B C , Matala A P, Hess J E, Narum S R, 2015   Environmental adaptation in Chinook salmon (Oncorhynchus tshawytscha) throughout their North American range. Mol. Ecol. 24 : 5573 – 5595 . 10.1111/mec.13409 Google Scholar Crossref Search ADS PubMed WorldCat Hecht B C , Thrower F P, Hale M C, Miller M R, Nichols K M, 2012  Genetic architecture of migration-related traits in rainbow and steelhead trout, Oncorhynchus mykiss. G3(Bethesda) 2: 1113–1127. 10.1534/g3.112.003137 Crossref Hollister J D , 2015   Polyploidy: adaptation to the genomic environment. New Phytol. 205 : 1034 – 1039 . 10.1111/nph.12939 Google Scholar Crossref Search ADS PubMed WorldCat Howe K , Clark M D, Torroja C F, Torrance J, Berthelot C et al. , 2013   The zebrafish reference genome sequence and its relationship to the human genome. Nature 496 : 498 – 503 . Erratum 2014 505: 248. 10.1038/nature12111 Google Scholar Crossref Search ADS PubMed WorldCat Hughes T , Ekman D, Ardawatia H, Elofsson A, Liberles D A, 2007   Evaluating dosage compensation as a cause of duplicate gene retention in Paramecium tetraurelia. Genome Biol. 8 : 213 . 10.1186/gb-2007-8-5-213 Google Scholar Crossref Search ADS PubMed WorldCat Kassahn K S , Dang V T, Wilkins S J, Perkins A C, Ragan M A, 2009   Evolution of gene function and regulatory control after whole-genome duplication: Comparative analyses in vertebrates. Genome Res. 19 : 1404 – 1418 . 10.1101/gr.086827.108 Google Scholar Crossref Search ADS PubMed WorldCat Kellis M , Birren B W, Lander E S, 2004   Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae. Nature 428 : 617 – 624 . 10.1038/nature02424 Google Scholar Crossref Search ADS PubMed WorldCat Kim D , Langmead B, Salzberg S L, 2015   HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12 : 357 – 360 . 10.1038/nmeth.3317 Google Scholar Crossref Search ADS PubMed WorldCat Kodama M , Brieuc M S O, Devlin R H, Hard J J, Naish K A, 2014  Comparative mapping between coho Salmon (Oncorhynchus kisutch) and three other salmonids suggests a role for chromosomal rearrangements in the retention of duplicated regions following a whole genome duplication event. G3 (Bethesda) 4: 1717. 10.1534/g3.114.012294 Crossref Langham R J , Walsh J, Dunn M, Ko C, Goff S A et al. , 2004   Genomic duplication, fractionation and the origin of regulatory novelty. Genetics 166 : 935 – 945 . 10.1534/genetics.166.2.935 Google Scholar Crossref Search ADS PubMed WorldCat Li H , Handsaker B, Wysoker A, Fennell T, Ruan J et al. , 2009   The sequence alignment/map format and SAMtools. Bioinformatics 25 : 2078 – 2079 . 10.1093/bioinformatics/btp352 Google Scholar Crossref Search ADS PubMed WorldCat Lien S , Gidskehaug L, Moen T, Hayes B J, Berg P R et al. , 2011   A dense SNP-based linkage map for Atlantic salmon (Salmo salar) reveals extended chromosome homeologies and striking differences in sex-specific recombination patterns. BMC Genomics 12 : 615 . 10.1186/1471-2164-12-615 Google Scholar Crossref Search ADS PubMed WorldCat Lien S , Koop B F, Sandve S R, Miller J R, Kent M P et al. , 2016   The Atlantic salmon genome provides insights into rediploidization. Nature 533 : 200 – 205 . 10.1038/nature17164 Google Scholar Crossref Search ADS PubMed WorldCat Love M I , Huber W, Anders S, 2014   Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15 : 550 . 10.1186/s13059-014-0550-8 Google Scholar Crossref Search ADS PubMed WorldCat Lynch M , Conery J S, 2000   The evolutionary fate and consequences of duplicate genes. Science 290 : 1151 – 1155 . 10.1126/science.290.5494.1151 Google Scholar Crossref Search ADS PubMed WorldCat Mable B K , 2004   ‘Why polyploidy is rarer in animals than in plants’: myths and mechanisms. Biol. J. Linn. Soc. Lond. 82 : 453 – 466 . 10.1111/j.1095-8312.2004.00332.x Google Scholar Crossref Search ADS WorldCat Macqueen D J , Johnston I A, 2014   A well-constrained estimate for the timing of the salmonid whole genome duplication reveals major decoupling from species diversification. Proc. Biol. Sci. 281 : 20132881. 10.1098/rspb.2013.2881 Google Scholar OpenURL Placeholder Text WorldCat Crossref Makino T , McLysaght A, 2010   Ohnologs in the human genome are dosage balanced and frequently associated with disease. Proc. Natl. Acad. Sci. USA 107 : 9270 – 9274 . 10.1073/pnas.0914697107 Google Scholar Crossref Search ADS WorldCat Mayrose I , Zhan S H, Rothfels C J, Magnuson-Ford K, Barker M S et al. , 2011   Recently formed polyploid plants diversify at lower rates. Science 333 : 1257 . 10.1126/science.1207205 Google Scholar Crossref Search ADS PubMed WorldCat McDowall R M , 2002   The origin of the salmonid fishes: marine, freshwater... or neither? Rev. Fish Biol. Fish. 11 : 171 – 179 . 10.1023/A:1020370328194 Google Scholar Crossref Search ADS WorldCat McKinney G J , Hale M C, Goetz G, Gribskov M, Thrower F P et al. , 2015   Ontogenetic changes in embryonic and brain gene expression in progeny produced from migratory and resident Oncorhynchus mykiss. Mol. Ecol. 24 : 1792 – 1809 . 10.1111/mec.13143 Google Scholar Crossref Search ADS PubMed WorldCat Muller H J , 1936   Bar duplication. Science 83 : 528 – 530 . 10.1126/science.83.2161.528-a Google Scholar Crossref Search ADS PubMed WorldCat Nakatani Y , Takeda H, Kohara Y, Morishita S, 2007   Reconstruction of the vertebrate ancestral genome reveals dynamic genome reorganization in early vertebrates. Genome Res. 17 : 1254 – 1265 . 10.1101/gr.6316407 Google Scholar Crossref Search ADS PubMed WorldCat Nichols K M , Edo A F, Wheeler P A, Thorgaard G H, 2008   The genetic basis of smoltification-related traits in Oncorhynchus mykiss. Genetics 179 : 1559 – 1575 . 10.1534/genetics.107.084251 Google Scholar Crossref Search ADS PubMed WorldCat Ohno S , 1970   Evolution by gene duplication , Springer-Verlag , New York . 10.1007/978-3-642-86659-3 Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Ohno S , Muramoto J, Christian L, Atkin N B, 1967   Diploid-tetraploid relationship among old-world members of the fish family Cyprinidae. Chromosoma 23 : 1 – 9 . 10.1007/BF00293307 Google Scholar Crossref Search ADS WorldCat Orr H A , 1990   “Why polyploidy is rarer in animals than in plants” revisited. Am. Nat. 136 : 759 – 770 . 10.1086/285130 Google Scholar Crossref Search ADS WorldCat Pearse D E , Barson N, Nome T, Gao G, Campbell M A et al. , 2018   Sex-dependent dominance maintains migration supergene in rainbow trout. bioRxiv . 10.1101/504621 Google Scholar OpenURL Placeholder Text WorldCat Crossref Pearse D E , Miller M R, Abadía-Cardoso A, Garza J C, 2014   Rapid parallel evolution of standing variation in a single, complex, genomic region is associated with life history in steelhead/rainbow trout. Proc. R. Soc. Lond. B Biol. Sci. 281 : 20140012. 10.1098/rspb.2014.0012 Google Scholar OpenURL Placeholder Text WorldCat Crossref Pires J C , Conant G C, 2016   Robust Yet Fragile: Expression noise, protein misfolding, and gene dosage in the evolution of genomes. Annu. Rev. Genet. 50 : 113 – 131 . 10.1146/annurev-genet-120215-035400 Google Scholar Crossref Search ADS PubMed WorldCat Postlethwait J H , Woods I G, Ngo-Hazelett P, Yan Y-L, Kelly P D et al. , 2000   Zebrafish comparative genomics and the origins of vertebrate chromosomes. Genome Res. 10 : 1890 – 1902 . 10.1101/gr.164800 Google Scholar Crossref Search ADS PubMed WorldCat Putnam N H , Butts T, Ferrier D E K, Furlong R F, Hellsten U et al. , 2008   The amphioxus genome and the evolution of the chordate karyotype. Nature 453 : 1064 – 1071 . 10.1038/nature06967 Google Scholar Crossref Search ADS PubMed WorldCat Qian W , Liao B-Y, Chang A Y-F, Zhang J, 2010   Maintenance of duplicate genes and their functional redundancy by reduced expression. Trends Genet. 26 : 425 – 430 . 10.1016/j.tig.2010.07.002 Google Scholar Crossref Search ADS PubMed WorldCat R Development Core Team , 2017   R: A language and environment for statistical computing , R Foundation for Statistical Computing , Vienna, Austria . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Rastogi S , Liberles D A, 2005   Subfunctionalization of duplicated genes as a transition state to neofunctionalization. BMC Evol. Biol. 5 : 28 . 10.1186/1471-2148-5-28 Google Scholar Crossref Search ADS PubMed WorldCat Robertson FM , Gundappa M K, Grammes F, Hvidsten T R, Redmond A K et al. , 2017   Lineage-specific rediploidization is a mechanism to explain time-lags between genome duplication and evolutionary diversification. Genome Bio. 18 : 111 . Google Scholar Crossref Search ADS WorldCat Roux J , Liu J, Robinson-Rechavi M, 2017   Selective constraints on coding sequences of nervous system genes are a major determinant of duplicate gene retention in vertebrates. Mol. Biol. Evol. 34 : 2773 – 2791 . 10.1093/molbev/msx199 Google Scholar Crossref Search ADS PubMed WorldCat Sandve S R , Rohlfs R V, Hvidsten T R, 2018   Subfunctionalization vs. neofunctionalization after whole-genome duplication. Nat. Genet. 50 : 908 – 909 . 10.1038/s41588-018-0162-4 Google Scholar Crossref Search ADS PubMed WorldCat Santini F , Harmon L, Carnevale G, Alfaro M, 2009   Did genome duplication drive the origin of teleosts? A comparative study of diversification in ray-finned fishes. BMC Evol. Biol. 9 : 194 . 10.1186/1471-2148-9-194 Google Scholar Crossref Search ADS PubMed WorldCat Sémon M , Wolfe K H, 2008   Preferential subfunctionalization of slow-evolving genes after allopolyploidization in Xenopus laevis. Proc. Natl. Acad. Sci. USA 105 : 8333 – 8338 . 10.1073/pnas.0708705105 Google Scholar Crossref Search ADS WorldCat Singh P P , Affeldt S, Cascone I, Selimoglu R, Camonis J et al. , 2012   On the expansion of “dangerous” gene repertoires by whole-genome duplications in early vertebrates. Cell Reports 2 : 1387 – 1398 . 10.1016/j.celrep.2012.09.034 Google Scholar Crossref Search ADS PubMed WorldCat Singh P P , Arora J, Isambert H, 2015   Identification of ohnolog genes originating from whole genome duplication in early vertebrates, based on synteny comparison across multiple genomes. PLOS Comput. Biol. 11 : e1004394. 10.1371/journal.pcbi.1004394 Google Scholar OpenURL Placeholder Text WorldCat Crossref Soltis D E , Soltis P S, 1999   Polyploidy: recurrent formation and genome evolution. Trends Ecol. Evol. 14 : 348 – 352 . 10.1016/S0169-5347(99)01638-9 Google Scholar Crossref Search ADS PubMed WorldCat Stoltzfus A , 1999   On the possibility of constructive neutral evolution. J. Mol. Evol. 49 : 169 – 181 . 10.1007/PL00006540 Google Scholar Crossref Search ADS PubMed WorldCat Sutherland B J G , Gosselin T, Normandeau E, Lamothe M, Isabel N et al. , 2016   Salmonid chromosome evolution as revealed by a novel method for comparing RADseq linkage maps. Genome Biol. Evol. 8 : 3600 – 3617 . 10.1093/gbe/evw262 Google Scholar Crossref Search ADS PubMed WorldCat Tischler J , Lehner B, Chen N, Fraser A G, 2006   Combinatorial RNA interference in Caenorhabditis elegans reveals that redundancy between gene duplicates can be maintained for more than 80 million years of evolution. Genome Biol. 7 : R69 . 10.1186/gb-2006-7-8-r69 Google Scholar Crossref Search ADS PubMed WorldCat Uyeno T , Smith G R, 1972   Tetraploid origin of the karyotype of catostomid fishes. Science 175 : 644 – 646 . 10.1126/science.175.4022.644 Google Scholar Crossref Search ADS PubMed WorldCat Van de Peer Y , Mizrachi E, Marchal K, 2017   The evolutionary significance of polyploidy. Nat. Rev. Genet. 18 : 411 – 424 . 10.1038/nrg.2017.26 Google Scholar Crossref Search ADS PubMed WorldCat Vandepoele K , De Vos W, Taylor J S, Meyer A, Van de Peer Y, 2004   Major events in the genome evolution of vertebrates: Paranome age and size differ considerably between ray-finned fishes and land vertebrates. Proc. Natl. Acad. Sci. USA 101 : 1638 – 1643 . 10.1073/pnas.0307968100 Google Scholar Crossref Search ADS WorldCat Vavouri T , Semple J I, Lehner B, 2008   Widespread conservation of genetic redundancy during a billion years of eukaryotic evolution. Trends Genet. 24 : 485 – 488 . 10.1016/j.tig.2008.08.005 Google Scholar Crossref Search ADS PubMed WorldCat Veitia R A , Bottani S, Birchler J A, 2008   Cellular reactions to gene dosage imbalance: genomic, transcriptomic and proteomic effects. Trends Genet. 24 : 390 – 397 . 10.1016/j.tig.2008.05.005 Google Scholar Crossref Search ADS PubMed WorldCat Waples R K , Seeb L W, Seeb J E , 2016  Linkage mapping with paralogs exposes regions of residual tetrasomic inheritance in chum salmon (Oncorhynchus keta). Mol. Ecol. Resour. 16 : 17 – 28 . Crossref Search ADS PubMed Wickham H , 2009   ggplot2: elegant graphics for data analysis. Springer-Verlag , New York . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Wolfe K H , 2001   Yesterday’s polyploids and the mystery of diploidization. Nat. Rev. Genet. 2 : 333 – 341 . 10.1038/35072009 Google Scholar Crossref Search ADS PubMed WorldCat Wolfe K H , Shields D C, 1997   Molecular evidence for an ancient duplication of the entire yeast genome. Nature 387 : 708 – 713 . 10.1038/42711 Google Scholar Crossref Search ADS PubMed WorldCat Wood T E , Takebayashi N, Barker M S, Mayrose I, Greenspoon P B et al. , 2009   The frequency of polyploid speciation in vascular plants. Proc. Natl. Acad. Sci. USA 106 : 13875 – 13879 . 10.1073/pnas.0811575106 Google Scholar Crossref Search ADS WorldCat Woods I G , Wilson C, Friedlander B, Chang P, Reyes D K et al. , 2005   The zebrafish gene map defines ancestral vertebrate chromosomes. Genome Res. 15 : 1307 – 1314 . 10.1101/gr.4134305 Google Scholar Crossref Search ADS PubMed WorldCat Zhan S H , Glick L, Tsigenopoulos C S, Otto S P, Mayrose I, 2014   Comparative analysis reveals that polyploidy does not decelerate diversification in fish. J. Evol. Biol. 27 : 391 – 403 . 10.1111/jeb.12308 Google Scholar Crossref Search ADS PubMed WorldCat Author notes 1 Contributed equally to this work. © 2019 Campbell et al. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) © 2019 Campbell et al. TI - Long-Term Conservation of Ohnologs Through Partial Tetrasomy Following Whole-Genome Duplication in Salmonidae JF - "G3: Genes, Genomes, Genetics" DO - 10.1534/g3.119.400070 DA - 2019-06-01 UR - https://www.deepdyve.com/lp/oxford-university-press/long-term-conservation-of-ohnologs-through-partial-tetrasomy-following-Fn4FTp40Fa SP - 2017 EP - 2028 VL - 9 IS - 6 DP - DeepDyve ER -