Development and Validation of an Open Access SNP Array for Nile Tilapia (Oreochromis niloticus)

Genetic diversity and population structure of farmed and wild Nile tilapia (Oreochromis niloticus) in Uganda: The potential for aquaculture selection and breeding programs

Nile tilapia is one of the most important aquaculture species globally, providing high-quality animal protein for human nutrition and a source of income to sustain the livelihoods of many people in low- and middle-income countries. This species is native to Africa and nowadays farmed throughout the world. However, the genetic makeup of its native populations remains poorly characterized. Additionally, there has been important introgression and movement of farmed (as well as wild) strains connected to tilapia aquaculture in Africa, yet the relationship between wild and farmed populations is unknown in most of the continent. Genetic characterization of the species in Africa has the potential to support the conservation of the species as well as supporting selective breeding to improve the indigenous strains for sustainable and profitable aquaculture production. In the current study, a total of 382 fish were used to investigate the genetic structure, diversity, and ancestry within and between Ugandan Nile tilapia populations from three major lakes including Lake Albert (L. Albert), Lake Kyoga (L. Kyoga) and Lake Victoria (L. Victoria), and 10 hatchery farms located in the catchment regions of these lakes. Our results showed clear genetic structure of the fish sourced from the lakes, with L. Kyoga and L. Albert populations showing higher genetic similarity. We also observed noticeable genetic structure among farmed populations, with most of them being genetically similar to L. Albert and L. Kyoga fish. Admixture results showed a higher (2.55-52.75%) contribution of L. Albert / L. Kyoga stocks to Uganda's farmed fish than the stock from L. Victoria (2.12-28.02%). We observed relatively high genetic diversity across both wild and farmed populations, but some farms had sizable numbers of highly inbred fish, raising concerns about management practices. In addition, we identified a genomic region on chromosome 5, harbouring the key innate immune gene BPI and the key growth gene GHRH, putatively under selection in the Ugandan Nile tilapia population. This region overlaps with the genomic region previously identified to be associated with growth rate in farmed Nile tilapia.

Genetic differentiation following recent domestication events: A study of farmed Nile tilapia (Oreochromis niloticus) populations

Nile tilapia (Oreochromis niloticus) is among the most farmed finfish worldwide, distributed across different environmental conditions. Its wide distribution has mainly been facilitated by several breeding programs and widespread dissemination of genetically improved strains. In the first Nile tilapia study exploiting a whole-genome pooled sequencing (Poolseq) approach, we identified the genetic structure and signatures of selection in diverse, farmed Nile tilapia populations, with a particular focus on the GIFT strain, developed in the 1980s, and currently managed by WorldFish (GIFTw). We also investigated important farmed strains from The Philippines and Africa. Using both SNP array data and Poolseq SNPs, we characterized the population structure of these samples. We observed the greatest separation between the Asian and African populations and greater admixture in the Asian populations than in the African ones. We also established that the SNP array data were able to successfully resolve relationships between these diverse Nile tilapia populations. The Poolseq data identified genomic regions with high levels of differentiation (F ST) between GIFTw and the other populations. Gene ontology terms associated with mesoderm development were significantly enriched in the genes located in these regions. A region on chromosome Oni06 was genetically differentiated in pairwise comparisons between GIFTw and all other populations. This region contains genes associated with muscle-related traits and overlaps with a previously published QTL for fillet yield, suggesting that these traits may have been direct targets for selection on GIFT. A nearby region was also identified using XP-EHH to detect genomic differentiation using the SNP array data. Genomic regions with high or extended homozygosity within each population were also identified. This study provides putative genomic landmarks associated with the recent domestication process in several Nile tilapia populations, which could help to inform their genetic management and improvement.

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.

SNP discovery and genetic structure in blue mussel species using low coverage sequencing and a medium density 60 K SNP-array

Blue mussels from the genus Mytilus are an abundant component of the benthic community, found in the high latitude habitats. These foundation species are relevant to the aquaculture industry, with over 2 million tonnes produced globally each year. Mussels withstand a wide range of environmental conditions and species from the Mytilus edulis complex readily hybridize in regions where their distributions overlap. Significant effort has been made to investigate the consequences of environmental stress on mussel physiology, reproductive isolation, and local adaptation. Yet our understanding on the genomic mechanisms underlying such processes remains limited. In this study, we developed a multi species medium-density 60 K SNP-array including four species of the Mytilus genus. SNPs included in the platform were called from 138 mussels from 23 globally distributed mussel populations, sequenced using a whole-genome low coverage approach. The array contains polymorphic SNPs which capture the genetic diversity present in mussel populations thriving across a gradient of environmental conditions (~59 K SNPs) and a set of published and validated SNPs informative for species identification and for diagnosis of transmissible cancer (610 SNPs). The array will allow the consistent genotyping of individuals, facilitating the investigation of ecological and evolutionary processes in these taxa. The applications of this array extend to shellfish aquaculture, contributing to the optimization of this industry via genomic selection of blue mussels, parentage assignment, inbreeding assessment and traceability. Further applications such as genome wide association studies (GWAS) for key production traits and those related to environmental resilience are especially relevant to safeguard aquaculture production under climate change.

Chromosome-level genome sequence of the Genetically Improved Farmed Tilapia (GIFT, Oreochromis niloticus) highlights regions of introgression with O. mossambicus

BACKGROUND

The Nile tilapia (Oreochromis niloticus) is the third most important freshwater fish for aquaculture. Its success is directly linked to continuous breeding efforts focusing on production traits such as growth rate and weight. Among those elite strains, the Genetically Improved Farmed Tilapia (GIFT) programme initiated by WorldFish is now distributed worldwide. To accelerate the development of the GIFT strain through genomic selection, a high-quality reference genome is necessary.

RESULTS

Using a combination of short (10X Genomics) and long read (PacBio HiFi, PacBio CLR) sequencing and a genetic map for the GIFT strain, we generated a chromosome level genome assembly for the GIFT. Using genomes of two closely related species (O. mossambicus, O. aureus), we characterised the extent of introgression between these species and O. niloticus that has occurred during the breeding process. Over 11 Mb of O. mossambicus genomic material could be identified within the GIFT genome, including genes associated with immunity but also with traits of interest such as growth rate.

CONCLUSION

Because of the breeding history of elite strains, current reference genomes might not be the most suitable to support further studies into the GIFT strain. We generated a chromosome level assembly of the GIFT strain, characterising its mixed origins, and the potential contributions of introgressed regions to selected traits.

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.

Identification of Genes Related to Cold Tolerance and Novel Genetic Markers for Molecular Breeding in Taiwan Tilapia (Oreochromis spp.) via Transcriptome Analysis

Taiwan tilapia is one of the primary species used in aquaculture practices in Taiwan. However, as a tropical fish, it is sensitive to cold temperatures that can lead to high mortality rates during winter months. Genetic and broodstock management strategies using marker-assisted selection and breeding are the best tools currently available to improve seed varieties for tilapia species. The purpose of this study was to develop molecular markers for cold stress-related genes using digital gene expression analysis of next-generation transcriptome sequencing in Taiwan tilapia (Oreochromis spp.). We constructed and sequenced cDNA libraries from the brain, gill, liver, and muscle tissues of cold-tolerance (CT) and cold-sensitivity (CS) strains. Approximately 35,214,833,100 nucleotides of raw sequencing reads were generated, and these were assembled into 128,147 unigenes possessing a total length of 185,382,926 bp and an average length of 1446 bp. A total of 25,844 unigenes were annotated using five protein databases and Venny analysis, and 38,377 simple sequence repeats (SSRs) and 65,527 single nucleotide polymorphisms (SNPs) were identified. Furthermore, from the 38-cold tolerance-related genes that were identified using differential gene expression analysis in the four tissues, 13 microsatellites and 37 single nucleotide polymorphism markers were identified. The results of the genotype analysis revealed that the selected markers could be used for population genetics. In addition to the diversity assessment, one of the SNP markers was determined to be significantly related to cold-tolerance traits and could be used as a molecular marker to assist in the selection and verification of cold-tolerant populations. The specific genetic markers explored in this study can be used for the identification of genetic polymorphisms and cold tolerance traits in Taiwan tilapia, and they can also be used to further explore the physiological and biochemical molecular regulation pathways of fish that are involved in their tolerance to environmental temperature stress.

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; -0.60 and -0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

A major quantitative trait locus affecting resistance to Tilapia lake virus in farmed Nile tilapia (Oreochromis niloticus)

Enhancing host resistance to infectious disease has received increasing attention in recent years as a major goal of farm animal breeding programs. Combining field data with genomic tools can provide opportunities to understand the genetic architecture of disease resistance, leading to new opportunities for disease control. In the current study, a genome-wide association study was performed to assess resistance to the Tilapia lake virus (TiLV), one of the biggest threats affecting Nile tilapia (Oreochromis niloticus); a key aquaculture species globally. A pond outbreak of TiLV in a pedigreed population of the GIFT strain was observed, with 950 fish classified as either survivor or mortality, and genotyped using a 65 K SNP array. A significant QTL of large effect was identified on chromosome Oni22. The average mortality rate of tilapia homozygous for the resistance allele at the most significant SNP (P value = 4.51E-10) was 11%, compared to 43% for tilapia homozygous for the susceptibility allele. Several candidate genes related to host response to viral infection were identified within this QTL, including lgals17, vps52, and trim29. These results provide a rare example of a major QTL affecting a trait of major importance to a farmed animal. Genetic markers from the QTL region have potential in marker-assisted selection to improve host resistance, providing a genetic solution to an infectious disease where few other control or mitigation options currently exist.

Development and testing of a combined species SNP array for the European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata)

SNP arrays are powerful tools for high-resolution studies of the genetic basis of complex traits, facilitating both selective breeding and population genomic research. The European seabass (Dicentrarchus labrax) and the gilthead seabream (Sparus aurata) are the two most important fish species for Mediterranean aquaculture. While selective breeding programmes increasingly underpin stock supply for this industry, genomic selection is not yet widespread. Genomic selection has major potential to expedite genetic gain, particularly for traits practically impossible to measure on selection candidates, such as disease resistance and fillet characteristics. The aim of our study was to design a combined-species 60 K SNP array for European seabass and gilthead seabream, and to test its performance on farmed and wild populations from numerous locations throughout the species range. To achieve this, high coverage Illumina whole-genome sequencing of pooled samples was performed for 24 populations of European seabass and 27 populations of gilthead seabream. This resulted in a database of ~20 million SNPs per species, which were then filtered to identify high-quality variants and create the final set for the development of the ‘MedFish’ SNP array. The array was then tested by genotyping a subset of the discovery populations, highlighting a high conversion rate to functioning polymorphic assays on the array (92% in seabass; 89% in seabream) and repeatability (99.4–99.7%). The platform interrogates ~30 K markers in each species, includes features such as SNPs previously shown to be associated with performance traits, and is enriched for SNPs predicted to have high functional effects on proteins. The array was demonstrated to be effective at detecting population structure across a wide range of fish populations from diverse geographical origins, and to examine the extent of haplotype sharing among Mediterranean farmed fish populations. In conclusion, the new MedFish array enables efficient and accurate high-throughput genotyping for genome-wide distributed SNPs for each fish species, and will facilitate stock management, population genomics approaches, and acceleration of selective breeding through genomic selection.

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Α 60 K SNP array (MedFish) was designed for European seabass and gilthead seabream from wild and domesticated populations.

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The array exhibited a high conversion rate (92% in seabass; 89% in seabream) and repeatability (99.4 and 99.7%).

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The MedFish array is expected to facilitate stock management and acceleration of selective breeding via genomic selection.

Genetic Dissection of a Precocious Phenotype in Male Tiger Pufferfish (Takifugu rubripes) using Genotyping by Random Amplicon Sequencing, Direct (GRAS-Di)

The novel non-targeted PCR-based genotyping system, namely Genotyping by Random Amplicon Sequencing, Direct (GRAS-Di), is characterized by the simplicity in library construction and robustness against DNA degradation and is expected to facilitate advancements in genetics, in both basic and applied sciences. In this study, we tested the utility of GRAS-Di for genetic analysis in a cultured population of the tiger pufferfish Takifugu rubripes. The genetic analyses included family structure analysis, genetic map construction, and quantitative trait locus (QTL) analysis for the male precocious phenotype using a population consisting of four full-sib families derived from a genetically precocious line. An average of 4.7 million raw reads were obtained from 198 fish. Trimmed reads were mapped onto a Fugu reference genome for genotyping, and 21,938 putative single-nucleotide polymorphisms (SNPs) were obtained. These 22 K SNPs accurately resolved the sibship and parent-offspring pairs. A fine-scale linkage map (total size: 1,949 cM; average interval: 1.75 cM) was constructed from 1,423 effective SNPs, for which the allele inheritance patterns were known. QTL analysis detected a significant locus for testes weight on Chr_14 and three suggestive loci on Chr_1, Chr_8, and Chr_19. The significant QTL was shared by body length and body weight. The effect of each QTL was small (phenotypic variation explained, PVE: 3.1-5.9%), suggesting that the precociousness seen in the cultured pufferfish is polygenic. Taken together, these results indicate that GRAS-Di is a practical genotyping tool for aquaculture species and applicable for molecular breeding programs, such as marker-assisted selection and genomic selection.

Development and Evaluation of a High-Throughput Single-Nucleotide Polymorphism Array for Large Yellow Croaker (Larimichthys crocea)

High-density single-nucleotide polymorphism (SNP) genotyping array is an essential tool for genetic analyses of animals and plants. Large yellow croaker (Larimichthys crocea) is one of the most commercially important marine fish species in China. Although plenty of SNPs have been identified in large yellow croaker, no high-throughput genotyping array is available. In this study, a high-throughput SNP array named NingXin-I with 600K SNPs was developed and evaluated. A set of 82 large yellow croakers were collected from different locations of China and re-sequenced. A total of 9.34M SNPs were identified by mapping sequence reads to the large yellow croaker reference genome. About 1.98M candidate SNPs were selected for further analyses by using criteria such as SNP quality score and conversion performance in the final array. Finally, 579.5K SNPs evenly distributed across the large yellow croaker genome with an average spacing of 1.19 kb were proceeded to array production. The performance of NingXin-I array was evaluated in 96 large yellow croaker individuals from five populations, and 83.38% SNPs on the array were polymorphic sites. A further test of the NingXin-I array in five closely related species in Sciaenidae identified 26.68–56.23% polymorphic SNP rate across species. A phylogenetic tree inferred by using the genotype data generated by NingXin-I confirmed the phylogenetic distance of the species in Sciaenidae. The performance of NingXin-I in large yellow croaker and the other species in Sciaenidae suggested high accuracy and broad application. The NingXin-I array should be valuable for quantitative genetic studies, such as genome-wide association studies (GWASs), high-density linkage map construction, haplotype analysis, and genome-based selection.

Assessing the genetic diversity of farmed and wild Rufiji tilapia (Oreochromis urolepis urolepis) populations using ddRAD sequencing

Rufiji tilapia (Oreochromis urolepis urolepis) is an endemic cichlid in Tanzania. In addition to its importance for biodiversity conservation, Rufiji tilapia is also attractive for farming due to its high growth rate, salinity tolerance, and the production of all-male hybrids when crossed with Nile tilapia (Oreochromis niloticus). The aim of the current study was to assess the genetic diversity and population structure of both wild and farmed Rufiji tilapia populations in order to inform conservation and aquaculture practices. Double-digest restriction-site-associated DNA (ddRAD) libraries were constructed from 195 animals originating from eight wild (Nyamisati, Utete, Mansi, Mindu, Wami, Ruaha, Kibasira, and Kilola) and two farmed (Bwawani and Chemchem) populations. The identified single nucleotide polymorphisms (SNPs; n = 2,182) were used to investigate the genetic variation within and among the studied populations. Genetic distance estimates (F st) were low among populations from neighboring locations, with the exception of Utete and Chemchem populations (F st = 0.34). Isolation-by-distance (IBD) analysis among the wild populations did not detect any significant correlation signal (r = .05; p-value = .4) between the genetic distance and the sampling (Euclidean distance) locations. Population structure and putative ancestry were further investigated using both Bayesian (Structure) and multivariate approaches (discriminant analysis of principal components). Both analysis indicated the existence of three distinct genetic clusters. Two cross-validation scenarios were conducted in order to test the efficiency of the SNP dataset for discriminating between farmed and wild animals or predicting the population of origin. Approximately 95% of the test dataset was correctly classified in the first scenario, while in the case of predicting for the population of origin 68% of the test dataset was correctly classified. Overall, our results provide novel insights regarding the population structure of Rufiji tilapia and a new database of informative SNP markers for both conservation management and aquaculture activities.

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.