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

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.

Genome wide association study of genes controlling resistance to Didymella rabiei Pathotype IV through genotyping by sequencing in chickpeas (Cicer arietinum)

Ascochyta blight (AB) is a major disease in chickpeas (Cicer arietinum L.) that can cause a yield loss of up to 100%. Chickpea germplasm collections at the center of origin offer great potential to discover novel sources of resistance to pests and diseases. Herein, 189 Cicer arietinum samples were genotyped via genotyping by sequencing. This chickpea collection was phenotyped for resistance to an aggressive Turkish Didymella rabiei Pathotype IV isolate. Genome-wide association studies based on different models revealed 19 single nucleotide polymorphism (SNP) associations on chromosomes 1, 2, 3, 4, 7, and 8. Although eight of these SNPs have been previously reported, to the best of our knowledge, the remaining ten were associated with AB resistance for the first time. The regions identified in this study can be addressed in future studies to reveal the genetic mechanism underlying AB resistance and can also be utilized in chickpea breeding programs to improve AB resistance in new chickpea varieties.

Potential of low-density genotype imputation for cost-efficient genomic selection for resistance to Flavobacterium columnare in rainbow trout (Oncorhynchus mykiss)

BACKGROUND

Flavobacterium columnare is the pathogen agent of columnaris disease, a major emerging disease that affects rainbow trout aquaculture. Selective breeding using genomic selection has potential to achieve cumulative improvement of the host resistance. However, genomic selection is expensive partly because of the cost of genotyping large numbers of animals using high-density single nucleotide polymorphism (SNP) arrays. The objective of this study was to assess the efficiency of genomic selection for resistance to F. columnare using in silico low-density (LD) panels combined with imputation. After a natural outbreak of columnaris disease, 2874 challenged fish and 469 fish from the parental generation (n = 81 parents) were genotyped with 27,907 SNPs. The efficiency of genomic prediction using LD panels was assessed for 10 panels of different densities, which were created in silico using two sampling methods, random and equally spaced. All LD panels were also imputed to the full 28K HD panel using the parental generation as the reference population, and genomic predictions were re-evaluated. The potential of prioritizing SNPs that are associated with resistance to F. columnare was also tested for the six lower-density panels.

RESULTS

The accuracies of both imputation and genomic predictions were similar with random and equally-spaced sampling of SNPs. Using LD panels of at least 3000 SNPs or lower-density panels (as low as 300 SNPs) combined with imputation resulted in accuracies that were comparable to those of the 28K HD panel and were 11% higher than the pedigree-based predictions.

CONCLUSIONS

Compared to using the commercial HD panel, LD panels combined with imputation may provide a more affordable approach to genomic prediction of breeding values, which supports a more widespread adoption of genomic selection in aquaculture breeding programmes.

Genetic architecture of acute hyperthermia resistance in juvenile rainbow trout (Oncorhynchus mykiss) and genetic correlations with production traits

BACKGROUND

Selective breeding is a promising solution to reduce the vulnerability of fish farms to heat waves, which are predicted to increase in intensity and frequency. However, limited information about the genetic architecture of acute hyperthermia resistance in fish is available. Two batches of sibs from a rainbow trout commercial line were produced: the first (N = 1382) was phenotyped for acute hyperthermia resistance at nine months of age and the second (N = 1506) was phenotyped for main production traits (growth, body length, muscle fat content and carcass yield) at 20 months of age. Fish were genotyped on a 57 K single nucleotide polymorphism (SNP) array and their genotypes were imputed to high-density based on the parent's genotypes from a 665 K SNP array.

RESULTS

The heritability estimate of resistance to acute hyperthermia was 0.29 ± 0.05, confirming the potential of selective breeding for this trait. Since genetic correlations of acute hyperthermia resistance with the main production traits near harvest age were all close to zero, selecting for acute hyperthermia resistance should not impact the main production traits, and vice-versa. A genome-wide association study revealed that resistance to acute hyperthermia is a highly polygenic trait, with six quantitative trait loci (QTL) detected, but explaining less than 5% of the genetic variance. Two of these QTL, including the most significant one, may explain differences in acute hyperthermia resistance across INRAE isogenic lines of rainbow trout. Differences in mean acute hyperthermia resistance phenotypes between homozygotes at the most significant SNP was 69% of the phenotypic standard deviation, showing promising potential for marker-assisted selection. We identified 89 candidate genes within the QTL regions, among which the most convincing functional candidates are dnajc7, hsp70b, nkiras2, cdk12, phb, fkbp10, ddx5, cygb1, enpp7, pdhx and acly.

CONCLUSIONS

This study provides valuable insight into the genetic architecture of acute hyperthermia resistance in juvenile rainbow trout. We show that the selection potential for this trait is substantial and selection for this trait should not be too detrimental to improvement of other traits of interest. Identified functional candidate genes provide new knowledge on the physiological mechanisms involved in acute hyperthermia resistance, such as protein chaperoning, oxidative stress response, homeostasis maintenance and cell survival.

Evaluation of low-density SNP panels and imputation for cost-effective genomic selection in four aquaculture species

Genomic selection can accelerate genetic progress in aquaculture breeding programmes, particularly for traits measured on siblings of selection candidates. However, it is not widely implemented in most aquaculture species, and remains expensive due to high genotyping costs. Genotype imputation is a promising strategy that can reduce genotyping costs and facilitate the broader uptake of genomic selection in aquaculture breeding programmes. Genotype imputation can predict ungenotyped SNPs in populations genotyped at a low-density (LD), using a reference population genotyped at a high-density (HD). In this study, we used datasets of four aquaculture species (Atlantic salmon, turbot, common carp and Pacific oyster), phenotyped for different traits, to investigate the efficacy of genotype imputation for cost-effective genomic selection. The four datasets had been genotyped at HD, and eight LD panels (300-6,000 SNPs) were generated in silico. SNPs were selected to be: i) evenly distributed according to physical position ii) selected to minimise the linkage disequilibrium between adjacent SNPs or iii) randomly selected. Imputation was performed with three different software packages (AlphaImpute2, FImpute v.3 and findhap v.4). The results revealed that FImpute v.3 was faster and achieved higher imputation accuracies. Imputation accuracy increased with increasing panel density for both SNP selection methods, reaching correlations greater than 0.95 in the three fish species and 0.80 in Pacific oyster. In terms of genomic prediction accuracy, the LD and the imputed panels performed similarly, reaching values very close to the HD panels, except in the pacific oyster dataset, where the LD panel performed better than the imputed panel. In the fish species, when LD panels were used for genomic prediction without imputation, selection of markers based on either physical or genetic distance (instead of randomly) resulted in a high prediction accuracy, whereas imputation achieved near maximal prediction accuracy independently of the LD panel, showing higher reliability. Our results suggests that, in fish species, well-selected LD panels may achieve near maximal genomic selection prediction accuracy, and that the addition of imputation will result in maximal accuracy independently of the LD panel. These strategies represent effective and affordable methods to incorporate genomic selection into most aquaculture settings.

Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus

Common full-sib families (c ² ) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c ² resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values. However, the impacts of common full-sib families on accuracy of genomic prediction for commercial traits of economic importance are not well known in many species, including aquatic animals. This research explored the impacts of common full-sib families on accuracy of genomic prediction for tagging weight in a population of striped catfish comprising 11,918 fish traced back to the base population (four generations), in which 560 individuals had genotype records of 14,154 SNPs. Our single step genomic best linear unbiased prediction (ssGLBUP) showed that the accuracy of genomic prediction for tagging weight was reduced by 96.5%-130.3% when the common full-sib families were included in statistical models. The reduction in the prediction accuracy was to a smaller extent in multivariate analysis than in univariate models. Imputation of missing genotypes somewhat reduced the upward biases in the prediction accuracy for tagging weight. It is therefore suggested that genomic evaluation models for traits recorded during the early phase of growth development should account for the common full-sib families to minimise possible biases in the accuracy of genomic prediction and hence, selection response.

GWAS on Imputed Whole-Genome Sequence Variants Reveal Genes Associated with Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss)

Genome-wide association studies (GWAS) allow the identification of associations between genetic variants and important phenotypes in domestic animals, including disease-resistance traits. Whole Genome Sequencing (WGS) data can help increase the resolution and statistical power of association mapping. Here, we conduced GWAS to asses he facultative intracellular bacterium Piscirickettsia salmonis, which affects farmed rainbow trout, Oncorhynchus mykiss, in Chile using imputed genotypes at the sequence level and searched for candidate genes located in genomic regions associated with the trait. A total of 2130 rainbow trout were intraperitoneally challenged with P. salmonis under controlled conditions and genotyped using a 57K single nucleotide polymorphism (SNP) panel. Genotype imputation was performed in all the genotyped animals using WGS data from 102 individuals. A total of 488,979 imputed WGS variants were available in the 2130 individuals after quality control. GWAS revealed genome-wide significant quantitative trait loci (QTL) in Omy02, Omy03, Omy25, Omy26 and Omy27 for time to death and in Omy26 for binary survival. Twenty-four (24) candidate genes associated with P. salmonis resistance were identified, which were mainly related to phagocytosis, innate immune response, inflammation, oxidative response, lipid metabolism and apoptotic process. Our results provide further knowledge on the genetic variants and genes associated with resistance to intracellular bacterial infection in rainbow trout.

Genome-Wide Association Study Reveals SNPs and Candidate Genes Related to Growth and Body Shape in Bighead Carp (Hypophthalmichthys nobilis)

Growth is an economically important trait in bighead carp and other aquaculture species that affects production efficiency. Interestingly, the head of the bighead carp has a high market value in China; therefore, it is important to study the genetic bases of both growth and body shape traits. A genome-wide association study was performed based on 2b-RAD sequencing of 776 individuals to identify SNPs associated with growth and body shape traits, including body weight, body length, body height, and deheaded body length. In total, 26 significant and 19 suggestive SNPs were identified, and more than half of these significant SNPs were clustered in LG16. Two LGs (LG16 and LG21) contained QTLs associated with body weight. Fourteen SNPs of LG16 and two LG21 SNPs were found to be associated with body length. For body height, 12 significantly associated SNPs were identified in LG16. Additionally, 12 SNPs of LG16 and 3 SNPs of LG21 were found to be associated with deheaded body length. Forty-three genes were significantly or suggestively associated with body shape/growth traits based on GWAS results, 18 of which were candidate genes for all BW, BL, BH, and DBL traits. One of these genes, fndc5b, was selected for further analyses. Association analysis revealed that one SNP (g.245 C > T) in the introns of fndc5b was significantly associated with growth-related traits in growth-extreme samples. The mRNA levels of fndc5b in the brains of the lightweight group were significantly higher than those of the heavy-weight group. This study helps to reveal the genetic structure of growth and body development in fish and provides candidate genes for future molecular marker-assisted selection for fast growth and better body conformation in bighead carp.

Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population

The aim of this study was to investigate the genetic parameters and genetic architectures of six milk production traits in the Shanghai Holstein population. The data used to estimate the genetic parameters consisted of 1,968,589 test-day records for 305,031 primiparous cows. Among the cows with phenotypes, 3,016 cows were genotyped with Illumina Bovine SNP50K BeadChip, GeneSeek Bovine 50K BeadChip, GeneSeek Bovine LD BeadChip v4, GeneSeek Bovine 150K BeadChip, or low-depth whole-genome sequencing. A genome-wide association study was performed to identify quantitative trait loci and genes associated with milk production traits in the Shanghai Holstein population using genotypes imputed to whole-genome sequences and both fixed and random model circulating probability unification and a mixed linear model with rMVP software. Estimated heritabilities (h2) varied from 0.04 to 0.14 for somatic cell score (SCS), 0.07 to 0.22 for fat percentage (FP), 0.09 to 0.27 for milk yield (MY), 0.06 to 0.23 for fat yield (FY), 0.09 to 0.26 for protein yield (PY), and 0.07 to 0.35 for protein percentage (PP), respectively. Within lactation, genetic correlations for SCS, FP, MY, FY, PY, and PP at different stages of lactation estimated in random regression model were ranged from -0.02 to 0.99, 0.18 to 0.99, 0.04 to 0.99, 0.04 to 0.99, 0.01 to 0.99, and 0.33 to 0.99, respectively. The genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. Candidate genes included those related to production traits (DGAT1, MGST1, PTK2, and SCRIB), disease-related (LY6K, COL22A1, TECPR2, and PLCB1), heat stress–related (ITGA9, NDST4, TECPR2, and HSF1), and reproduction-related (7SK and DOCK2) genes. This study has shown that there are differences in the genetic mechanisms of milk production traits at different stages of lactation. Therefore, it is necessary to conduct research on milk production traits at different stages of lactation as different traits. Our results can also provide a theoretical basis for subsequent molecular breeding, especially for the novel genetic loci.

Genomic prediction of growth in a commercially, recreationally, and culturally important marine resource, the Australian snapper (Chrysophrys auratus)

Growth is one of the most important traits of an organism. For exploited species, this trait has ecological and evolutionary consequences as well as economical and conservation significance. Rapid changes in growth rate associated with anthropogenic stressors have been reported for several marine fishes, but little is known about the genetic basis of growth traits in teleosts. We used reduced genome representation data and genome-wide association approaches to identify growth-related genetic variation in the commercially, recreationally, and culturally important Australian snapper (Chrysophrys auratus, Sparidae). Based on 17,490 high-quality single-nucleotide polymorphisms and 363 individuals representing extreme growth phenotypes from 15,000 fish of the same age and reared under identical conditions in a sea pen, we identified 100 unique candidates that were annotated to 51 proteins. We documented a complex polygenic nature of growth in the species that included several loci with small effects and a few loci with larger effects. Overall heritability was high (75.7%), reflected in the high accuracy of the genomic prediction for the phenotype (small vs large). Although the single-nucleotide polymorphisms were distributed across the genome, most candidates (60%) clustered on chromosome 16, which also explains the largest proportion of heritability (16.4%). This study demonstrates that reduced genome representation single-nucleotide polymorphisms and the right bioinformatic tools provide a cost-efficient approach to identify growth-related loci and to describe genomic architectures of complex quantitative traits. Our results help to inform captive aquaculture breeding programs and are of relevance to monitor growth-related evolutionary shifts in wild populations in response to anthropogenic pressures.