Genome-wide association analysis for body weight identifies candidate genes related to development and metabolism in rainbow trout (Oncorhynchus mykiss)

Genome-wide association and transcriptomic analysis and the identification of growth-related genes in Macrobrachium nipponense

Macrobrachium nipponense is a commercially important freshwater species of prawn that is widely distributed across Asian countries. In order to investigate the molecular mechanisms of growth in M. nipponense, and to provide a foundation for molecular breeding, we used genome-wide association analysis (GWAS) and transcriptomic analysis to screen polymorphisms and genes related to growth traits. We recorded the growth traits of 100 adult M. nipponense at the same growth stage, and each individual genotype was evaluated by whole genome resequencing. GWAS of growth traits detected 12 growth-related single-nucleotide polymorphisms (SNPs) and eight growth-related genes from 49 chromosomes. Of the 100 individuals, we sampled muscle tissue from a total of 18 female and male M. nipponense exhibiting large differences in growth rate for RNA-seq. Transcriptome analysis revealed a total of 27,996 unigenes; of these, 33 and 60 differentially expressed genes were identified from males and females, respectively. Of these, 12 genes associated with energy metabolism and cytoskeletal pathways were identified as growth-related genes. Notably, genes from the actin family and the ubiquitin C-terminal hydrolase 2 (UCH2) gene were identified by both GWAS and transcriptomic analysis. Two growth-related SNPs, S40_12327385 and S40_12327391, were found to be mapped to the ACTB gene. The ACTA1 gene, also from the actin family, was up-regulated in fast-growing males and females, while the ACT57B was down-regulated. In addition, the growth associated SNP S7_35313774 was located in the UCH2 gene; transcriptomics analysis revealed that the UCH2 gene was up-regulated in female individuals exhibiting high growth rates. Overall, our results provided a set of markers and candidate genes related to the growth of M. nipponense. These findings could facilitate the breeding management of this species and help us to further understand the genetic mechanisms of growth in crustaceans.

Genetic diversity patterns in farmed rainbow trout (Oncorhynchus mykiss) populations using genome-wide SNP and haplotype data

Rainbow trout is one of the most popular aquaculture species worldwide, with a long history of domestication. However, limited information exists about the genetic diversity of farmed rainbow trout populations globally, with most available reports relying on low-throughput genotyping technologies. Notably, no information exists about the genetic diversity status of farmed rainbow trout in Sweden. Double-digest restriction-site-associated DNA sequencing was performed on more than 500 broodfish from two leading producers in Sweden and from the country's national breeding program. Following the detection of single nucleotide polymorphisms (SNPs), genetic diversity was studied by using either individual SNPs (n = 8680; one SNP retained per 300 bp sequence reads) or through SNP haplotypes (n = 20 558; all SNPs retained in 300 bp sequence reads). Similar amounts of genetic diversity were found amongst the three populations when individual SNPs were used. Furthermore, principal component analysis and discriminant analysis of principal components suggested two genetic clusters with the two industry populations grouped together. Genetic differentiation based on the FST fixation index was ~0.01 between the industry populations and ~0.05 when those were compared with the breeding program. Preliminary estimates of effective population size (Ne ) and inbreeding (based on runs of homozygosity; FROH ) were similar amongst the three populations (Ne  ≈ 50-80; median FROH  ≈ 0.11). Finally, the haplotype-based analysis suggested that animals from the breeding program had higher shared coancestry levels than those from the other two populations. Overall, our study provides novel insights into the genetic diversity and structure of Sweden's three main farmed rainbow trout populations, which could guide their future management.

Transcriptome analysis of the muscle of fast- and slow-growing phoenix barb (Spinibarbus denticulatus denticulatus)

Growth rate is a commercial trait in aquaculture that is influenced by multiple factors, among which genetic composition plays a fundamental role in the growth rate of species. The phoenix barb (Spinibarbus denticulatus denticulatus) is a widely distributed freshwater fish species in South China. Although S. d. denticulatus is reared in South China, the molecular mechanisms underlying the growth rate of the species remain unclear. Here, the authors performed transcriptome analysis of muscle tissues from fast-growing (FG) and slow-growing (SG) S. d. denticulatus at 90, 150, and 300 days after hatch (DAH) to elucidate its growth mechanism. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that differentially expressed genes (DEGs) between the two groups were enriched in pathways related to muscle growth, glycolysis, and energy and lipid metabolism. Nonetheless, a higher number of DEGs were identified in the FG vs. SG groups at 90 and 300 DAH compared with 150 DAH. DEGs identified at 90 DAH were mainly enriched in the GH/IGF axis, PI3K-Akt signalling pathway, AMPK signalling pathway and lipid metabolism highly expressed in FG individuals. DEGs identified at 300 DAH were mainly enriched in PI3K-Akt signalling pathway, glycolysis/gluconeogenesis, gene translation and lipid metabolism. In addition, some genes were expressed during the early growth stage in FG individuals but expressed during the late stage in SG individuals, indicating considerable variations in the expression profiles of growth-related genes at different developmental stages. Overall, these findings contribute to the understanding of the growth mechanism of S. d. denticulatus, which would be useful for the propagation of fast-growing breeds.

Development of a High-Density 665 K SNP Array for Rainbow Trout Genome-Wide Genotyping

Single nucleotide polymorphism (SNP) arrays, also named « SNP chips », enable very large numbers of individuals to be genotyped at a targeted set of thousands of genome-wide identified markers. We used preexisting variant datasets from USDA, a French commercial line and 30X-coverage whole genome sequencing of INRAE isogenic lines to develop an Affymetrix 665 K SNP array (HD chip) for rainbow trout. In total, we identified 32,372,492 SNPs that were polymorphic in the USDA or INRAE databases. A subset of identified SNPs were selected for inclusion on the chip, prioritizing SNPs whose flanking sequence uniquely aligned to the Swanson reference genome, with homogenous repartition over the genome and the highest Minimum Allele Frequency in both USDA and French databases. Of the 664,531 SNPs which passed the Affymetrix quality filters and were manufactured on the HD chip, 65.3% and 60.9% passed filtering metrics and were polymorphic in two other distinct French commercial populations in which, respectively, 288 and 175 sampled fish were genotyped. Only 576,118 SNPs mapped uniquely on both Swanson and Arlee reference genomes, and 12,071 SNPs did not map at all on the Arlee reference genome. Among those 576,118 SNPs, 38,948 SNPs were kept from the commercially available medium-density 57 K SNP chip. We demonstrate the utility of the HD chip by describing the high rates of linkage disequilibrium at 2–10 kb in the rainbow trout genome in comparison to the linkage disequilibrium observed at 50–100 kb which are usual distances between markers of the medium-density chip.

Detecting Local Adaptation between North and South European Atlantic Salmon Populations

Pollution and other anthropogenic effects have driven a decrease in Atlantic salmon (Salmo salar) in the Iberian Peninsula. The restocking effort carried out in the 1980s, with salmon from northern latitudes with the aim of mitigating the decline of native populations, failed, probably due to the deficiency in adaptation of foreign salmon from northern Europe to the warm waters of the Iberian Peninsula. This result would imply that the Iberian populations of Atlantic salmon have experienced local adaptation in their past evolutionary history, as has been described for other populations of this species and other salmonids. Local adaptation can occur by divergent selections between environments, favoring the fixation of alleles that increase the fitness of a population in the environment it inhabits relative to other alleles favored in another population. In this work, we compared the genomes of different populations from the Iberian Peninsula (Atlantic and Cantabric basins) and Scotland in order to provide tentative evidence of candidate SNPs responsible for the adaptive differences between populations, which may explain the failures of restocking carried out during the 1980s. For this purpose, the samples were genotyped with a 220,000 high-density SNP array (Affymetrix) specific to Atlantic salmon. Our results revealed potential evidence of local adaptation for North Spanish and Scottish populations. As expected, most differences concerned the comparison of the Iberian Peninsula with Scotland, although there were also differences between Atlantic and Cantabric populations. A high proportion of the genes identified are related to development and cellular metabolism, DNA transcription and anatomical structure. A particular SNP was identified within the NADP-dependent malic enzyme-2 (_mMEP-2*), previously reported by independent studies as a candidate for local adaptation in salmon from the Iberian Peninsula. Interestingly, the corresponding SNP within the _mMEP-2* region was consistent with a genomic pattern of divergent selection.

Increased accuracy of genomic predictions for growth under chronic thermal stress in rainbow trout by prioritizing variants from GWAS using imputed sequence data

Through imputation of genotypes, genome-wide association study (GWAS) and genomic prediction (GP) using whole-genome sequencing (WGS) data are cost-efficient and feasible in aquaculture breeding schemes. The objective was to dissect the genetic architecture of growth traits under chronic heat stress in rainbow trout (Oncorhynchus mykiss) and to assess the accuracy of GP based on imputed WGS and different preselected single nucleotide polymorphism (SNP) arrays. A total of 192 and 764 fish challenged to a heat stress experiment for 62 days were genotyped using a customized 1 K and 26 K SNP panels, respectively, and then, genotype imputation was performed from a low-density chip to WGS using 102 parents (36 males and 66 females) as the reference population. Imputed WGS data were used to perform GWAS and test GP accuracy under different preselected SNP scenarios. Heritability was estimated for body weight (BW), body length (BL) and average daily gain (ADG). Estimates using imputed WGS data ranged from 0.33 ± 0.05 to 0.55 ± 0.05 for growth traits under chronic heat stress. GWAS revealed that the top five cumulatively SNPs explained a maximum of 0.94%, 0.86% and 0.51% of genetic variance for BW, BL and ADG, respectively. Some important functional candidate genes associated with growth-related traits were found among the most important SNPs, including signal transducer and activator of transcription 5B and 3 (STAT5B and STAT3, respectively) and cytokine-inducible SH2-containing protein (CISH). WGS data resulted in a slight increase in prediction accuracy compared with pedigree-based method, whereas preselected SNPs based on the top GWAS hits improved prediction accuracies, with values ranging from 1.2 to 13.3%. Our results support the evidence of the polygenic nature of growth traits when measured under heat stress. The accuracies of GP can be improved using preselected variants from GWAS, and the use of WGS marginally increases prediction accuracy.

Endoplasmic reticulum stress as a key mechanism in stunted growth of seawater rainbow trout (Oncorhynchus mykiss)

BACKGROUND

Rainbow trout (Oncorhynchus mykiss) is a salmonid species with a complex life-history. Wild populations are naturally divided into freshwater residents and sea-run migrants. Migrants undergo an energy-demanding adaptation for life in seawater, known as smoltification, while freshwater residents display these changes in an attenuated magnitude and rate. Despite this, in seawater rainbow trout farming all fish are transferred to seawater. Under these circumstances, weeks after seawater transfer, a significant portion of the fish die (around 10%) or experience growth stunting (GS; around 10%), which represents an important profitability and welfare issue. The underlying causes leading to GS in seawater-transferred rainbow trout remain unknown. In this study, we aimed at characterising the GS phenotype in seawater-transferred rainbow trout using untargeted and targeted approaches. To this end, the liver proteome (LC-MS/MS) and lipidome (LC-MS) of GS and fast-growing phenotypes were profiled to identify molecules and processes that are characteristic of the GS phenotype. Moreover, the transcription, abundance or activity of key proteins and hormones related to osmoregulation (Gill Na+, K + -ATPase activity), growth (plasma IGF-I, and liver igf1, igfbp1b, ghr1 and ctsl) and stress (plasma cortisol) were measured using targeted approaches.

RESULTS

No differences in Gill Na+, K + -ATPase activity and plasma cortisol were detected between the two groups. However, a significant downregulation in plasma IGF-I and liver igf1 transcription pointed at this growth factor as an important pathomechanism for GS. Changes in the liver proteome revealed reactive-oxygen-species-mediated endoplasmic reticulum stress as a key mechanism underlying the GS phenotype. From the lipidomic analysis, key observations include a reduction in triacylglycerols and elevated amounts of cardiolipins, a characteristic lipid class associated with oxidative stress, in GS phenotype.

CONCLUSION

While the triggers to the activation of endoplasmic reticulum stress are still unknown, data from this study point towards a nutritional deficiency as an underlying driver of this phenotype.

Temporal and region‐specific variations in genome‐wide inbreeding effects on female size and reproduction traits of rainbow trout

Recent studies have shown that current levels of inbreeding, estimated by runs of homozygosity (ROH), are moderate to high in farmed rainbow trout lines. Based on ROH metrics, the aims of our study were to (i) quantify inbreeding effects on female size (postspawning body weight, fork length) and reproduction traits (spawning date, coelomic fluid weight, spawn weight, egg number, average egg weight) in rainbow trout, and (ii) identify both the genomic regions and inbreeding events affecting performance. We analysed the performance of 1346 females under linear animal models including random additive and dominance genetics effects, with fixed covariates accounting for inbreeding effects at different temporal and genomic scales. A significant effect of genome‐wide inbreeding (F) was only observed for spawning date and egg weight, with performance variations of +12.3% and −3.8%, respectively, for 0.1 unit increase in F level. At different local genomic scales, we observed highly variable inbreeding effects on the seven traits under study, ranging from increasing to decreasing trait values. As widely reported in the literature, the main scenario observed during this study was a negative impact of recent inbreeding. However, other scenarios such as positive effects of recent inbreeding or negative impacts of old inbreeding were also observed. Although partial dominance appeared to be the main hypothesis explaining inbreeding depression for all the traits studied, the overdominance hypothesis might also play a significant role in inbreeding depression affecting fecundity (egg number and mass) traits in rainbow trout. These findings suggest that region‐specific inbreeding can strongly impact performance without necessarily observing genome‐wide inbreeding effects. They shed light on the genetic architecture of inbreeding depression and its evolution along the genome over time. The use of region‐specific metrics may enable breeders to more accurately manage the trade‐off between genetic merit and the undesirable side effects associated with inbreeding.

Detection of selection signatures in the genome of a farmed population of anadromous rainbow trout (Oncorhynchus mykiss)

Domestication processes and artificial selection are likely to leave signatures that can be detected at a molecular level in farmed rainbow trout (Oncorhynchus mykiss). These signatures of selection are genomic regions that contain functional genetic variants conferring a higher fitness to their bearers. We genotyped 749 rainbow trout from a commercial population using a rainbow trout Axiom 57 K SNP array panel and identified putative genomic regions under selection using the pcadapt, Composite Likelihood Ratio (CLR) and Integrated Haplotype Score (iHS) methods. After applying quality-control pipelines and statistical analyses, we detected 12, 96 and 16 SNPs putatively under selection, associated with 96, 781 and 115 candidate genes, respectively. Several of these candidate genes were associated with growth, early development, reproduction, behavior and immune system traits. In addition, some of the SNPs were found in interesting regions located in autosomal inversions on Omy05 and Omy20. These findings could represent a genome-wide map of selection signatures in farmed rainbow trout and could be important in explaining domestication and selection for genetic traits of commercial interest.

Growth genes are implicated in the evolutionary divergence of sympatric piscivorous and insectivorous rainbow trout (Oncorhynchus mykiss)

Background

Identifying ecologically significant phenotypic traits and the genomic mechanisms that underly them are crucial steps in understanding traits associated with population divergence. We used genome-wide data to identify genomic regions associated with key traits that distinguish two ecomorphs of rainbow trout (Oncorhynchus mykiss)—insectivores and piscivores—that coexist for the non-breeding portion of the year in Kootenay Lake, southeastern British Columbia. “Gerrards” are large-bodied, rapidly growing piscivores with high metabolic rates that spawn north of Kootenay Lake in the Lardeau River, in contrast to the insectivorous populations that are on average smaller in body size, with lower growth and metabolic rates, mainly forage on aquatic insects, and spawn in tributaries immediately surrounding Kootenay Lake. We used pool-seq data representing ~ 60% of the genome and 80 fish per population to assess the level of genomic divergence between ecomorphs and to identify and interrogate loci that may play functional or selective roles in their divergence.

Results

Genomic divergence was high between sympatric insectivores and piscivores (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST = 0.188), and in fact higher than between insectivorous populations from Kootenay Lake and the Blackwater River (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST = 0.159) that are > 500 km apart. A window-based \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST analysis did not reveal “islands” of genomic differentiation; however, the window with highest \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST estimate did include a gene associated with insulin secretion. Although we explored the use of the “Local score” approach to identify genomic outlier regions, this method was ultimately not used because simulations revealed a high false discovery rate (~ 20%). Gene ontology (GO) analysis identified several growth processes as enriched in genes occurring in the ~ 200 most divergent genomic windows, indicating many loci of small effect involved in growth and growth-related metabolic processes are associated with the divergence of these ecomorphs.

Conclusion

Our results reveal a high degree of genomic differentiation between piscivorous and insectivorous populations and indicate that the large body piscivorous phenotype is likely not due to one or a few loci of large effect. Rather, the piscivore phenotype may be controlled by several loci of small effect, thus highlighting the power of whole-genome resequencing in identifying genomic regions underlying population-level phenotypic divergences.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01795-9.

Toward Genome-Based Selection in Asian Seabass: What Can We Learn From Other Food Fishes and Farm Animals?

Due to the steadily increasing need for seafood and the plateauing output of fisheries, more fish need to be produced by aquaculture production. In parallel with the improvement of farming methods, elite food fish lines with superior traits for production must be generated by selection programs that utilize cutting-edge tools of genomics. The purpose of this review is to provide a historical overview and status report of a selection program performed on a catadromous predator, the Asian seabass (Lates calcarifer, Bloch 1790) that can change its sex during its lifetime. We describe the practices of wet lab, farm and lab in detail by focusing onto the foundations and achievements of the program. In addition to the approaches used for selection, our review also provides an inventory of genetic/genomic platforms and technologies developed to (i) provide current and future support for the selection process; and (ii) improve our understanding of the biology of the species. Approaches used for the improvement of terrestrial farm animals are used as examples and references, as those processes are far ahead of the ones used in aquaculture and thus they might help those working on fish to select the best possible options and avoid potential pitfalls.

Genetic Parameters and Genome-Wide Association Studies of Quality Traits Characterised Using Imaging Technologies in Rainbow Trout, Oncorhynchus mykiss

One of the top priorities of the aquaculture industry is the genetic improvement of economically important traits in fish, such as those related to processing and quality. However, the accuracy of genetic evaluations has been hindered by a lack of data on such traits from a sufficiently large population of animals. The objectives of this study were thus threefold: (i) to estimate genetic parameters of growth-, yield-, and quality-related traits in rainbow trout (Oncorhynchus mykiss) using three different phenotyping technologies [invasive and non-invasive: microwave-based, digital image analysis, and magnetic resonance imaging (MRI)], (ii) to detect quantitative trait loci (QTLs) associated with these traits, and (iii) to identify candidate genes present within these QTL regions. Our study collected data from 1,379 fish on growth, yield-related traits (body weight, condition coefficient, head yield, carcass yield, headless gutted carcass yield), and quality-related traits (total fat, percentage of fat in subcutaneous adipose tissue, percentage of fat in flesh, flesh colour); genotypic data were then obtained for all fish using the 57K SNP Axiom® Trout Genotyping array. Heritability estimates for most of the 14 traits examined were moderate to strong, varying from 0.12 to 0.67. Most traits were clearly polygenic, but our genome-wide association studies (GWASs) identified two genomic regions on chromosome 8 that explained up to 10% of the genetic variance (cumulative effects of two QTLs) for several traits (weight, condition coefficient, subcutaneous and total fat content, carcass and headless gutted carcass yields). For flesh colour traits, six QTLs explained 1-4% of the genetic variance. Within these regions, we identified several genes (htr1, gnpat, ephx1, bcmo1, and cyp2x) that have been implicated in adipogenesis or carotenoid metabolism, and thus represent good candidates for further functional validation. Finally, of the three techniques used for phenotyping, MRI demonstrated particular promise for measurements of fat content and distribution, while the digital image analysis-based approach was very useful in quantifying colour-related traits. This work provides new insights that may aid the development of commercial breeding programmes in rainbow trout, specifically with regard to the genetic improvement of yield and flesh-quality traits as well as the use of invasive and/or non-invasive technologies to predict such traits.

Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia

Background

Body traits are generally controlled by several genes in vertebrates (i.e. polygenes), which in turn make them difficult to identify through association mapping. Increasing the power of association studies by combining approaches such as genotype imputation and multi-trait analysis improves the ability to detect quantitative trait loci associated with polygenic traits, such as body traits.

Results

A multi-trait genome-wide association study (mtGWAS) was performed to identify quantitative trait loci (QTL) and genes associated with body traits in Nile tilapia (Oreochromis niloticus) using genotypes imputed to whole-genome sequences (WGS). To increase the statistical power of mtGWAS for the detection of genetic associations, summary statistics from single-trait genome-wide association studies (stGWAS) for eight different body traits recorded in 1309 animals were used. The mtGWAS increased the statistical power from the original sample size from 13 to 44%, depending on the trait analyzed. The better resolution of the WGS data, combined with the increased power of the mtGWAS approach, allowed the detection of significant markers which were not previously found in the stGWAS. Some of the lead single nucleotide polymorphisms (SNPs) were found within important functional candidate genes previously associated with growth-related traits in other terrestrial species. For instance, we identified SNP within the α1,6-fucosyltransferase (FUT8), solute carrier family 4 member 2 (SLC4A2), A disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and heart development protein with EGF like domains 1 (HEG1) genes, which have been associated with average daily gain in sheep, osteopetrosis in cattle, chest size in goats, and growth and meat quality in sheep, respectively.

Conclusions

The high-resolution mtGWAS presented here allowed the identification of significant SNPs, linked to strong functional candidate genes, associated with body traits in Nile tilapia. These results provide further insights about the genetic variants and genes underlying body trait variation in cichlid fish with high accuracy and strong statistical support.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07341-z.

Genetic architecture and genomic selection of female reproduction traits in rainbow trout

BACKGROUND

Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. The objectives of this study are threefold: to estimate the genetic parameters of female reproduction traits, to determine the genetic architecture of these traits by the identification of quantitative trait loci (QTL), and to assess the expected efficiency of a pedigree-based selection (BLUP) or genomic selection for these traits.

RESULTS

A pedigreed population of 1343 trout were genotyped for 57,000 SNP markers and phenotyped for seven traits at 2 years of age: spawning date, female body weight before and after spawning, the spawn weight and the egg number of the spawn, the egg average weight and average diameter. Genetic parameters were estimated in multi-trait linear animal models. Heritability estimates were moderate, varying from 0.27 to 0.44. The female body weight was not genetically correlated to any of the reproduction traits. Spawn weight showed strong and favourable genetic correlation with the number of eggs in the spawn and individual egg size traits, but the egg number was uncorrelated to the egg size traits. The genome-wide association studies showed that all traits were very polygenic since less than 10% of the genetic variance was explained by the cumulative effects of the QTLs: for any trait, only 2 to 4 QTLs were detected that explained in-between 1 and 3% of the genetic variance. Genomic selection based on a reference population of only one thousand individuals related to candidates would improve the efficiency of BLUP selection from 16 to 37% depending on traits.

CONCLUSIONS

Our genetic parameter estimates made unlikely the hypothesis that selection for growth could induce any indirect improvement for female reproduction traits. It is thus important to consider direct selection for spawn weight for improving egg production traits in rainbow trout breeding programs. Due to the low proportion of genetic variance explained by the few QTLs detected for each reproduction traits, marker assisted selection cannot be effective. However genomic selection would allow significant gains of accuracy compared to pedigree-based selection.

Genomics to accelerate genetic improvement in tilapia

Selective breeding of tilapia populations started in the early 1990s and over the past three decades tilapia has become one of the most important farmed freshwater species, being produced in more than 125 countries around the globe. Although genome assemblies have been available since 2011, most of the tilapia industry still depends on classical selection techniques using mass spawning or pedigree information to select for growth traits with reported genetic gains of up to 20% per generation. The involvement of international breeding companies and research institutions has resulted in the rapid development and application of genomic resources in the last few years. GWAS and genomic selection are expected to contribute to uncovering the genetic variants involved in economically relevant traits and increasing the genetic gain in selective breeding programs, respectively. Developments over the next few years will probably focus on achieving a deep understanding of genetic architecture of complex traits, as well as accelerating genetic progress in the selection for growth-, quality- and robustness-related traits. Novel phenotyping technologies (i.e. phenomics), lower-cost whole-genome sequencing approaches, functional genomics and gene editing tools will be crucial in future developments for the improvement of tilapia aquaculture.

Transcriptomic Response to Selective Breeding for Fast Growth in Rainbow Trout (Oncorhynchus mykiss)

Genetic improvement for faster growth is a conventional approach to increase growth rates in aquaculture species; however, the genetic and physiological factors regulating growth performance in fish are not fully characterized. The objective of this study was to identify physiological mechanisms associated with faster growth rates by comparing the liver and muscle transcriptome of a rainbow trout line selectively bred for fast growth (growth line, GL) and a contemporary randomly mated control line (synthetic control, SC) from the same selective breeding program. A third genetic line from a commercial egg supplier (commercial A, CA) was also included to characterize differences in gene expression profiles between populations. Body weight of the GL at harvest was approximately 20% and 8% heavier (p < 0.05) than SC and CA, respectively. There were 145 and 36 differentially expressed genes (DEG) in liver and white muscle, respectively, between the GL and SC that were enriched for the growth hormone/insulin-like growth factor axis (GH/IGF) and PI3K-Akt, JAK-STAT, MAPK, and cAMP signal transduction pathways. A greater concentration of plasma IGF-I was detected in the GL compared with SC (p < 0.05). A unique gene profile was detected in CA, with 11 and 210 DEG in liver and white muscle; these genes associated with innate immunity, complement systems, and metabolic pathways. Collectively, these findings provide a more extensive characterization of the fast-growth phenotype in fish that furthers knowledge of the physiological basis for genetic variation in growth performance in selectively bred rainbow trout.

Identification of Candidate Growth-Related SNPs and Genes Using GWAS in Brown-Marbled Grouper (Epinephelus fuscoguttatus)

Brown-marbled grouper, Epinephelus fuscoguttatus, is not only an important commercial fish species, but also an important crossbreeding parent in grouper industry. Improvement of growth traits of this species contributes to the development of grouper breeding. Currently, the development of molecular marker associated with growth of brown-marbled grouper is rare. Thus, we performed the first genome-wide association study (GWAS) for five growth traits in 172 brown-marbled groupers with 43,688 SNPs detected by ddRAD-seq. We identified a total of 5 significant and 18 suggestive QTLs located in multiple chromosomes associated with growth traits. In the 20 kb window of the significant SNPs and suggestive SNPs, 5 and 14 potential candidate genes affecting growth were detected, respectively. Five potential candidate genes near the significantly associated SNPs were selected for expression analysis. Among of which, bmp2k, wasf1, and acyp2 involved in bone development, maintenance of mitochondrion structure, and metabolism were differentially expressed. Interestingly, the SNP 23:29601315 located in the intron of bmp2k was significantly associated with body weight, body length, body height, and body thickness and suggestively associated with total length. We verified the locus using another new group including 123 individuals. The results showed that individuals with CC genotype have better growth traits comparing other individuals. Our findings not only contribute to understanding the molecular mechanism of growth regulation, but also promote the advance of marker-assisted selection in brown-marbled grouper.

Genome-wide identification of loci associated with growth in rainbow trout

Background

Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout.

Results

A previously developed 50 K gene-transcribed SNP chip, containing ~ 21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~ 6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R² = 0.09).

Conclusion

The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

High-Throughput Single Nucleotide Polymorphism (SNP) Discovery and Validation Through Whole-Genome Resequencing in Nile Tilapia (Oreochromis niloticus)

Nile tilapia (Oreochromis niloticus) is the second most important farmed fish in the world and a sustainable source of protein for human consumption. Several genetic improvement programs have been established for this species in the world. Currently, the estimation of genetic merit of breeders is typically based on genealogical and phenotypic information. Genome-wide information can be exploited to efficiently incorporate traits that are difficult to measure into the breeding goal. Thus, single nucleotide polymorphisms (SNPs) are required to investigate phenotype-genotype associations and determine the genomic basis of economically important traits. We performed de novo SNP discovery in three different populations of farmed Nile tilapia. A total of 29.9 million non-redundant SNPs were identified through Illumina (HiSeq 2500) whole-genome resequencing of 326 individual samples. After applying several filtering steps, including removing SNP based on genotype and site quality, presence of Mendelian errors, and non-unique position in the genome, a total of 50,000 high-quality SNPs were selected for the development of a custom Illumina BeadChip SNP panel. These SNPs were highly informative in the three populations analyzed showing between 43,869 (94%) and 46,139 (99%) SNPs in Hardy-Weinberg Equilibrium; 37,843 (76%) and 45,171(90%) SNPs with a minor allele frequency (MAF) higher than 0.05; and 43,450 (87%) and 46,570 (93%) SNPs with a MAF higher than 0.01. The 50K SNP panel developed in the current work will be useful for the dissection of economically relevant traits, enhancing breeding programs through genomic selection, as well as supporting genetic studies in farmed populations of Nile tilapia using dense genome-wide information.

Identification of genetic loci associated with growth traits at weaning in yak through a genome-wide association study

A multilocus GWAS was performed to explore the genetic architecture of four growth traits in yak. In total, 354 female yaks for which measurements of body weight (BW), withers height (WH), body length (BL) and chest girth (CG) at weaning were available underwent genotyping with the Illumina BovineHD BeadChip (770K). After quality control, we retained 98 688 SNPs and 354 animals for GWAS analysis. We identified seven, 18, seven and nine SNPs (corresponding to seven, 17, seven and eight candidate genes) associated with BW, WH, BL and CG at weaning respectively. Interestingly, most of these candidate genes were reported to be involved in growth-related processes such as muscle formation, lipid deposition, feed efficiency, carcass composition and development of the central and peripheral nervous system. Our results offer novel insight into the molecular architecture underpinning yak growth traits. Further functional analyses are thus warranted to explore the molecular mechanisms whereby these genes affect these traits of interest.

TSLRF: Two-Stage Algorithm Based on Least Angle Regression and Random Forest in genome-wide association studies

One of the most important tasks in genome-wide association analysis (GWAS) is the detection of single-nucleotide polymorphisms (SNPs) which are related to target traits. With the development of sequencing technology, traditional statistical methods are difficult to analyze the corresponding high-dimensional massive data or SNPs. Recently, machine learning methods have become more popular in high-dimensional genetic data analysis for their fast computation speed. However, most of machine learning methods have several drawbacks, such as poor generalization ability, over-fitting, unsatisfactory classification and low detection accuracy. This study proposed a two-stage algorithm based on least angle regression and random forest (TSLRF), which firstly considered the control of population structure and polygenic effects, then selected the SNPs that were potentially related to target traits by using least angle regression (LARS), furtherly analyzed this variable subset using random forest (RF) to detect quantitative trait nucleotides (QTNs) associated with target traits. The new method has more powerful detection in simulation experiments and real data analyses. The results of simulation experiments showed that, compared with the existing approaches, the new method effectively improved the detection ability of QTNs and model fitting degree, and required less calculation time. In addition, the new method significantly distinguished QTNs and other SNPs. Subsequently, the new method was applied to analyze five flowering-related traits in Arabidopsis. The results showed that, the distinction between QTNs and unrelated SNPs was more significant than the other methods. The new method detected 60 genes confirmed to be related to the target trait, which was significantly higher than the other methods, and simultaneously detected multiple gene clusters associated with the target trait.

Single-Step Genome-Wide Association Study for Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss)

One of the main pathogens affecting rainbow trout (Oncorhynchus mykiss) farming is the facultative intracellular bacteria Piscirickettsia salmonis Current treatments, such as antibiotics and vaccines, have not had the expected effectiveness in field conditions. Genetic improvement by means of selection for resistance is proposed as a viable alternative for control. Genomic information can be used to identify the genomic regions associated with resistance and enhance the genetic evaluation methods to speed up the genetic improvement for the trait. The objectives of this study were to i) identify the genomic regions associated with resistance to P. salmonis; and ii) identify candidate genes associated with the trait in rainbow trout. We experimentally challenged 2,130 rainbow trout with P. salmonis and genotyped them with a 57 K single nucleotide polymorphism (SNP) array. Resistance to P. salmonis was defined as time to death (TD) and as binary survival (BS). Significant heritabilities were estimated for TD and BS (0.48 ± 0.04 and 0.34 ± 0.04, respectively). A total of 2,047 fish and 26,068 SNPs passed quality control for samples and genotypes. Using a single-step genome wide association analysis (ssGWAS) we identified four genomic regions explaining over 1% of the genetic variance for TD and three for BS. Interestingly, the same genomic region located on Omy27 was found to explain the highest proportion of genetic variance for both traits (2.4 and 1.5% for TD and BS, respectively). The identified SNP in this region is located within an exon of a gene related with actin cytoskeletal organization, a protein exploited by P. salmonis during infection. Other important candidate genes identified are related with innate immune response and oxidative stress. The moderate heritability values estimated in the present study show it is possible to improve resistance to P. salmonis through artificial selection in the rainbow trout population studied here. Furthermore, our results suggest a polygenic genetic architecture for the trait and provide novel insights into the candidate genes underpinning resistance to P. salmonis in O. mykiss.

Genome-Wide Association Analysis for Resistance to Infectious Pancreatic Necrosis Virus Identifies Candidate Genes Involved in Viral Replication and Immune Response in Rainbow Trout (Oncorhynchus mykiss)

Infectious pancreatic necrosis (IPN) is a viral disease with considerable negative impact on the rainbow trout (Oncorhynchus mykiss) aquaculture industry. The aim of the present work was to detect genomic regions that explain resistance to infectious pancreatic necrosis virus (IPNV) in rainbow trout. A total of 2,278 fish from 58 full-sib families were challenged with IPNV and 768 individuals were genotyped (488 resistant and 280 susceptible), using a 57K SNP panel Axiom, Affymetrix. A genome-wide association study (GWAS) was performed using the phenotypes time to death (TD) and binary survival (BS), along with the genotypes of the challenged fish using a Bayesian model (Bayes C). Heritabilities for resistance to IPNV estimated using genomic information, were 0.53 and 0.82 for TD and BS, respectively. The Bayesian GWAS detected a SNP located on chromosome 5 explaining 19% of the genetic variance for TD. The proximity of Sentrin-specific protease 5 (SENP5) to this SNP makes it a candidate gene for resistance against IPNV. In case of BS, a SNP located on chromosome 23 was detected explaining 9% of the genetic variance. However, the moderate-low proportion of variance explained by the detected marker leads to the conclusion that the incorporation of all genomic information, through genomic selection, would be the most appropriate approach to accelerate genetic progress for the improvement of resistance against IPNV in rainbow trout.

Genomic organization of the molt-inhibiting hormone gene in the red swamp crayfish Procambarus clarkii and characterization of single-nucleotide polymorphisms associated with growth

Molt-inhibiting hormone (MIH), a neuropeptide synthesized in the eyestalk in crustaceans, is mainly responsible for the molting by negatively controlling the ecdysteroids secretion. Although there are several reports of the isolation and protein sequencing of MIH in the red swamp crayfish, little is known about the nucleotide sequence and gene organization of this neuropeptide, even less about the association of MIH polymorphisms and growth traits. Here, a 1237 bp full-length MIH cDNA was obtained from the crayfish eyestalk, which encodes a putative protein of 106 amino acids, with a 191 bp 5'-UTR and a 728 bp 3'-UTR. The MIH genomic DNA sequence is 4205 bp in length, which includes three exons interrupted by two introns, and a 929 bp 5'-flanking region. Potential transcription initiation site and transcription factor binding sites were identified in the 5'-flanking region, implying a potential role in transcriptional regulation. Seventeen SNPs in the 5'-flanking region and 3'-UTR were identified, and the associations between these SNPs and growth traits were evaluated with a two-stage design. A SNPs g. -12C > G that showed a significant association with body weight was identified. Individuals with GG genotype had a significantly higher body weight than those with CC genotype (43.98 ± 9.82 g vs. 34.27 ± 6.87 g; P ﹤ 0.001), indicating a beneficial effect of the G allele on the growth of red swamp crayfish. The obtained MIH gene, as well as the identified SNPs, may serve as targets for molecular marker-aided selection in growth improvement of the red swamp crayfish in future studies.

Genome-Wide Association Study and Cost-Efficient Genomic Predictions for Growth and Fillet Yield in Nile Tilapia (Oreochromis niloticus)

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in Nile tilapia breeding programs.