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

Genetic diversity of Olive flounder (Paralichthys olivaceus) and the impact of selective breeding on Korean populations

This study aimed to identify the population structure and genetic diversity of olive flounder (Paralichthys olivaceus) in Korea and to examine the potential for genetic improvement in aquaculture populations. PCA showed NIFS and FarmA as closely related clusters, while FarmB exhibited moderate differentiation with greater variability. Fst analysis indicated high similarity between NIFS and farmed populations (0.021-0.043) but significant differentiation from wild populations (0.274-0.295). Admixture analysis highlighted a shared ancestral component (over 70%) among NIFS and farmed populations, contrasting with the unique genetic makeup of wild populations. The phylogenetic tree confirmed these patterns, with NIFS and FarmA forming close branches, FarmB showing intermediate placement, and wild populations clustering separately. Additionally, genomic estimated breeding values for body weight showed no significant differences between FarmA and FarmB, while prediction accuracy was higher for FarmA (47%) compared to FarmB (45%), indicating a closer genetic relationship between NIFS and FarmA. These findings emphasize the critical role of selective breeding and gene flow in shaping the genetic structure of farmed populations, offering valuable insights for improving growth traits and maintaining genetic diversity in aquaculture.

Genomic Signatures of Domestication in European Seabass (Dicentrarchus labrax L.) Reveal a Potential Role for Epigenetic Regulation in Adaptation to Captivity

Genome scans provide a comprehensive method to explore genome-wide variation associated with traits under study. However, linking individual genes to broader functional groupings and pathways is often challenging, yet crucial for understanding the evolutionary mechanisms underlying these traits. This task is particularly relevant for multi-trait processes such as domestication, which are influenced by complex interactions between numerous genetic and non-genetic factors, including epigenetic regulation. As various traits within the broader spectrum of domestication are selected in concert over time, this process offers an opportunity to identify broader functional overlaps and understand the integrated genetic architecture underlying these traits. In this study, we analyzed approximately 600,000 SNPs from a Pool-Seq experiment comparing eight natural-origin and 12 farmed populations of European seabass in the Mediterranean Sea region. We implemented two genome scan approaches and focused on genomic regions supported by both methods, resulting in the identification of 96 candidate genes, including nine CpG islands, which highligt potential epigenetic influences. Many of these genes and CpG islands are in linkage groups previously associated with domestication-related traits. The most significantly overrepresented molecular function was "oxidoreductase activity". Furthermore, a dense network of interactions was identified, connecting 22 of the candidate genes. Within this network, the most significantly enriched pathways and central genes were involved in "chromatin organization", highlighting another potential epigenetic mechanism. Altogether, our findings underscore the utility of interactome-assisted pathway analysis in elucidating the genomic architecture of polygenic traits and suggest that epigenetic regulation may play a crucial role in the domestication of European seabass.

Multitrait genetic parameter estimates in a Tenebrio molitor reference population: high potential for breeding gains

To address multiple issues impacting the climate imbalance, insects, and in particular Tenebrio molitor, represent now a promising alternative for producing high-quality protein products with low environmental impact. As with any new species farmed on an industrial scale, insect breeding production must be improved through the accumulation of knowledge on rearing techniques and genetic management. Little information on the inheritance of agronomically interesting traits, dedicated to Tenebrio molitor, is available. This study aims to decipher the genetic parameters (heritability and genetic correlations) of reproduction, larval growth and survival, pupation rate and developmental time from a reference population made up of 1 931 sib-groups reared under pedigree, in controlled and stable environments and generated with single pair mating. Considering all sib-groups, 29 599 offspring have been generated and phenotyped over four generations to support this study and provide enough data to estimate, under linear animal models, the additive genetic and common environmental effects. Phenotypic analyses underlined an important variability among sib-groups and individuals, as for the total oviposition during 4 weeks counting (0-680 eggs, min - max, respectively) or larval body mass 63 days posteclosion (36.3-206.8 mg, min - max, respectively). Moderate to important heritability values have been obtained and ranged from 0.17 to 0.54 for reproduction phenotypes, 0.10-0.44 for growth parameters, 0.06-0.22 for developmental time and 0.10-0.17 for larval survival rates. The proportion of phenotypic variance explained by the environmental part varyies from 0.10 to 0.36 for reproductive traits, from 0.17 to 0.38 for growth parameters, from 0.06 to 0.36 for developmental time and 0.17-0.22 for survival rates. Genetic correlations underline relationships among phenotypes such as the trade-off between developmental time from egg to pupae and pupae weight (r2 = 0.48 ± 0.06). These important phenotypic variations coupled with promising heritability values pave the road for future breeding programs in Tenebrio molitor.

Genome-wide detection of positive and balancing signatures of selection shared by four domesticated rainbow trout populations (Oncorhynchus mykiss)

BACKGROUND

Evolutionary processes leave footprints along the genome over time. Highly homozygous regions may correspond to positive selection of favorable alleles, while maintenance of heterozygous regions may be due to balancing selection phenomena. We analyzed data from 176 fish from four disconnected domestic rainbow trout populations that were genotyped using a high-density Axiom Trout genotyping 665K single nucleotide polymorphism array, including 20 from the US and 156 from three French lines. Using methods based on runs of homozygosity and extended haplotype homozygosity, we detected signatures of selection in these four populations.

RESULTS

Nine genomic regions that included 253 genes were identified as being under positive selection in all four populations Most were located on chromosome 2 but also on chromosomes 12, 15, 16, and 20. In addition, four heterozygous regions that contain 29 genes that are putatively under balancing selection were also shared by the four populations. These were located on chromosomes 10, 13, and 19. Regardless of the homozygous or heterozygous nature of the regions, in each region, we detected several genes that are highly conserved among vertebrates due to their critical roles in cellular and nuclear organization, embryonic development, or immunity. We identified new candidate genes involved in rainbow trout fitness, as well as 17 genes that were previously identified to be under positive selection, 10 of which in other fishes (auts2, atp1b3, zp4, znf135, igf-1α, brd2, col9a2, mrap2, pbx1, and emilin-3).

CONCLUSIONS

Using material from disconnected populations of different origins allowed us to draw a genome-wide map of signatures of positive selection that are shared between these rainbow trout populations, and to identify several regions that are putatively under balancing selection. These results provide a valuable resource for future investigations of the dynamics of genetic diversity and genome evolution during domestication.

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.

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.

Genomic Selection in Aquaculture Species

To date, genomic prediction has been conducted in about 20 aquaculture species, with a preference for intra-family genomic selection (GS). For every trait under GS, the increase in accuracy obtained by genomic estimated breeding values instead of classical pedigree-based estimation of breeding values is very important in aquaculture species ranging from 15% to 89% for growth traits, and from 0% to 567% for disease resistance. Although the implementation of GS in aquaculture is of little additional investment in breeding programs already implementing sib testing on pedigree, the deployment of GS remains sparse, but could be boosted by adaptation of cost-effective imputation from low-density panels. Moreover, GS could help to anticipate the effect of climate change by improving sustainability-related traits such as production yield (e.g., carcass or fillet yields), feed efficiency or disease resistance, and by improving resistance to environmental variation (tolerance to temperature or salinity variation). This chapter synthesized the literature in applications of GS in finfish, crustaceans and molluscs aquaculture in the present and future breeding programs.

Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, the European Sea Bass (Dicentrarchus labrax) and the Gilthead Sea Bream (Sparus aurata)

Disease outbreaks are a major threat to the aquaculture industry, and can be controlled by selective breeding. With the development of high-throughput genotyping technologies, genomic selection may become accessible even in minor species. Training population size and marker density are among the main drivers of the prediction accuracy, which both have a high impact on the cost of genomic selection. In this study, we assessed the impact of training population size as well as marker density on the prediction accuracy of disease resistance traits in European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata). We performed a challenge to nervous necrosis virus (NNV) in two sea bass cohorts, a challenge to Vibrio harveyi in one sea bass cohort and a challenge to Photobacterium damselae subsp. piscicida in one sea bream cohort. Challenged individuals were genotyped on 57K-60K SNP chips. Markers were sampled to design virtual SNP chips of 1K, 3K, 6K, and 10K markers. Similarly, challenged individuals were randomly sampled to vary training population size from 50 to 800 individuals. The accuracy of genomic-based (GBLUP model) and pedigree-based estimated breeding values (EBV) (PBLUP model) was computed for each training population size using Monte-Carlo cross-validation. Genomic-based breeding values were also computed using the virtual chips to study the effect of marker density. For resistance to Viral Nervous Necrosis (VNN), as one major QTL was detected, the opportunity of marker-assisted selection was investigated by adding a QTL effect in both genomic and pedigree prediction models. As training population size increased, accuracy increased to reach values in range of 0.51-0.65 for full density chips. The accuracy could still increase with more individuals in the training population as the accuracy plateau was not reached. When using only the 6K density chip, accuracy reached at least 90% of that obtained with the full density chip. Adding the QTL effect increased the accuracy of the PBLUP model to values higher than the GBLUP model without the QTL effect. This work sets a framework for the practical implementation of genomic selection to improve the resistance to major diseases in European sea bass and gilthead sea bream.