Development of a multi-species SNP array for serrasalmid fish Colossoma macropomum and Piaractus mesopotamicus

A multiplexed plant-animal SNP array for selective breeding and species conservation applications

Reliable and high-throughput genotyping platforms are of immense importance for identifying and dissecting genomic regions controlling important phenotypes, supporting selection processes in breeding programs, and managing wild populations and germplasm collections. Amongst available genotyping tools, single nucleotide polymorphism arrays have been shown to be comparatively easy to use and generate highly accurate genotypic data. Single-species arrays are the most commonly used type so far; however, some multi-species arrays have been developed for closely related species that share single nucleotide polymorphism markers, exploiting inter-species cross-amplification. In this study, the suitability of a multiplexed plant-animal single nucleotide polymorphism array, including both closely and distantly related species, was explored. The performance of the single nucleotide polymorphism array across species for diverse applications, ranging from intra-species diversity assessments to parentage analysis, was assessed. Moreover, the value of genotyping pooled DNA of distantly related species on the single nucleotide polymorphism array as a technique to further reduce costs was evaluated. Single nucleotide polymorphism performance was generally high, and species-specific single nucleotide polymorphisms proved suitable for diverse applications. The multi-species single nucleotide polymorphism array approach reported here could be transferred to other species to achieve cost savings resulting from the increased throughput when several projects use the same array, and the pooling technique adds another highly promising advancement to additionally decrease genotyping costs by half.

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.

Animal board invited review: Widespread adoption of genetic technologies is key to sustainable expansion of global aquaculture

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The extent of application of genetic technologies to aquaculture production varies widely by species and geography.

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Achieving a more universal application of seed derived from scientifically based breeding programmes is an important goal in order to meet increasing global demands for seafood production.

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This article reviews the status of genetic technologies across the world’s top 10 highly produced species.

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Opportunities and barriers to achieving broad-scale uptake of genetic technologies in global aquaculture are discussed.

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A future outlook for potential disruptive genetic technologies and how they might affect global aquaculture production is given.

Aquaculture production comprises a diverse range of species, geographies, and farming systems. The application of genetics and breeding technologies towards improved production is highly variable, ranging from the use of wild-sourced seed through to advanced family breeding programmes augmented by genomic techniques. This technical variation exists across some of the most highly produced species globally, with several of the top ten global species by volume generally lacking well-managed breeding programmes. Given the well-documented incremental and cumulative benefits of genetic improvement on production, this is a major missed opportunity. This short review focusses on (i) the status of application of selective breeding in the world’s most produced aquaculture species, (ii) the range of genetic technologies available and the opportunities they present, and (iii) a future outlook towards realising the potential contribution of genetic technologies to aquaculture sustainability and global food security.

Genomic selection signatures in farmed Colossoma macropomum from tropical and subtropical regions in South America

Tambaqui or cachama (Colossoma macropomum) is one of the most important neotropical freshwater fish used for aquaculture in South America, and its production is concentrated at low latitudes (close to the Equator, 0°), where the water temperature is warm. Therefore, understanding how selection shapes genetic variations and structure in farmed populations is of paramount importance in evolutionary biology. High‐throughput sequencing to generate genome‐wide data for fish species allows for elucidating the genomic basis of adaptation to local or farmed conditions and uncovering genes that control the phenotypes of interest. The present study aimed to detect genomic selection signatures and analyze the genetic variability in farmed populations of tambaqui in South America using single‐nucleotide polymorphism (SNP) markers obtained with double‐digest restriction site‐associated DNA sequencing. Initially, 199 samples of tambaqui farmed populations from different locations (located in Brazil, Colombia, and Peru), a wild population (Amazon River, Brazil), and the base population of a breeding program (Aquaculture Center, CAUNESP, Jaboticabal, SP, Brazil) were genotyped. Observed and expected heterozygosity was 0.231–0.350 and 0.288–0.360, respectively. Significant genetic differentiation was observed using global FST analyses of SNP loci (FST = 0.064, p < 0.050). Farmed populations from Colombia and Peru that differentiated from the Brazilian populations formed distinct groups. Several regions, particularly those harboring the genes of significance to aquaculture, were identified to be under positive selection, suggesting local adaptation to stress under different farming conditions and management practices. Studies aimed at improving the knowledge of genomics of tambaqui farmed populations are essential for aquaculture to gain deeper insights into the evolutionary history of these fish and provide resources for the establishment of breeding programs.