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Ajasa AA, Boison SA, Gjøen HM, Lillehammer M. Accuracy of genomic prediction using multiple Atlantic salmon populations. Genet Sel Evol 2024; 56:38. [PMID: 38750427 PMCID: PMC11094890 DOI: 10.1186/s12711-024-00907-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 05/06/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND The accuracy of genomic prediction is partly determined by the size of the reference population. In Atlantic salmon breeding programs, four parallel populations often exist, thus offering the opportunity to increase the size of the reference set by combining these populations. By allowing a reduction in the number of records per population, multi-population prediction can potentially reduce cost and welfare issues related to the recording of traits, particularly for diseases. In this study, we evaluated the accuracy of multi- and across-population prediction of breeding values for resistance to amoebic gill disease (AGD) using all single nucleotide polymorphisms (SNPs) on a 55K chip or a selected subset of SNPs based on the signs of allele substitution effect estimates across populations, using both linear and nonlinear genomic prediction (GP) models in Atlantic salmon populations. In addition, we investigated genetic distance, genetic correlation estimated based on genomic relationships, and persistency of linkage disequilibrium (LD) phase across these populations. RESULTS The genetic distance between populations ranged from 0.03 to 0.07, while the genetic correlation ranged from 0.19 to 0.99. Nonetheless, compared to within-population prediction, there was limited or no impact of combining populations for multi-population prediction across the various models used or when using the selected subset of SNPs. The estimates of across-population prediction accuracy were low and to some extent proportional to the genetic correlation estimates. The persistency of LD phase between adjacent markers across populations using all SNP data ranged from 0.51 to 0.65, indicating that LD is poorly conserved across the studied populations. CONCLUSIONS Our results show that a high genetic correlation and a high genetic relationship between populations do not guarantee a higher prediction accuracy from multi-population genomic prediction in Atlantic salmon.
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Affiliation(s)
- Afees A Ajasa
- Nofima (Norwegian Institute of Food, Fisheries and Aquaculture Research), PO Box 210, 1431, Ås, Norway.
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1430, Ås, Norway.
| | | | - Hans M Gjøen
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1430, Ås, Norway
| | - Marie Lillehammer
- Nofima (Norwegian Institute of Food, Fisheries and Aquaculture Research), PO Box 210, 1431, Ås, Norway
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Fraslin C, Robledo D, Kause A, Houston RD. Potential of low-density genotype imputation for cost-efficient genomic selection for resistance to Flavobacterium columnare in rainbow trout (Oncorhynchus mykiss). Genet Sel Evol 2023; 55:59. [PMID: 37580697 PMCID: PMC10424455 DOI: 10.1186/s12711-023-00832-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 07/26/2023] [Indexed: 08/16/2023] Open
Abstract
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.
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Affiliation(s)
- Clémence Fraslin
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK.
| | - Diego Robledo
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
| | - Antti Kause
- Natural Resources Institute Finland (Luke), Myllytie 1, 31600, Jokioinen, Finland
| | - Ross D Houston
- Benchmark Genetics, Edinburgh Technopole, 1 Pioneer Building, Penicuik, EH26 0GB, UK
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Delpuech E, Vandeputte M, Morvezen R, Bestin A, Besson M, Brunier J, Bajek A, Imarazene B, François Y, Bouchez O, Cousin X, Poncet C, Morin T, Bruant JS, Chatain B, Haffray P, Phocas F, Allal F. Whole-genome sequencing identifies interferon-induced protein IFI6/IFI27-like as a strong candidate gene for VNN resistance in European sea bass. Genet Sel Evol 2023; 55:30. [PMID: 37143017 PMCID: PMC10161657 DOI: 10.1186/s12711-023-00805-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 04/18/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND Viral nervous necrosis (VNN) is a major disease that affects European sea bass, and understanding the biological mechanisms that underlie VNN resistance is important for the welfare of farmed fish and sustainability of production systems. The aim of this study was to identify genomic regions and genes that are associated with VNN resistance in sea bass. RESULTS We generated a dataset of 838,451 single nucleotide polymorphisms (SNPs) identified from whole-genome sequencing (WGS) in the parental generation of two commercial populations (A: 2371 individuals and B: 3428 individuals) of European sea bass with phenotypic records for binary survival in a VNN challenge. For each population, three cohorts were submitted to a red-spotted grouper nervous necrosis virus (RGNNV) challenge by immersion and genotyped on a 57K SNP chip. After imputation of WGS SNPs from their parents, quantitative trait loci (QTL) were mapped using a Bayesian sparse linear mixed model (BSLMM). We found several QTL regions that were specific to one of the populations on different linkage groups (LG), and one 127-kb QTL region on LG12 that was shared by both populations and included the genes ZDHHC14, which encodes a palmitoyltransferase, and IFI6/IFI27-like, which encodes an interferon-alpha induced protein. The most significant SNP in this QTL region was only 1.9 kb downstream of the coding sequence of the IFI6/IFI27-like gene. An unrelated population of four large families was used to validate the effect of the QTL. Survival rates of susceptible genotypes were 40.6% and 45.4% in populations A and B, respectively, while that of the resistant genotype was 66.2% in population B and 78% in population A. CONCLUSIONS We have identified a genomic region that carries a major QTL for resistance to VNN and includes the ZDHHC14 and IFI6/IFI27-like genes. The potential involvement of the interferon pathway, a well-known anti-viral defense mechanism in several organisms (chicken, human, or fish), in survival to VNN infection is of particular interest. Our results can lead to major improvements for sea bass breeding programs through marker-assisted genomic selection to obtain more resistant fish.
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Affiliation(s)
- Emilie Delpuech
- MARBEC, Univ. Montpellier, CNRS, Ifremer, IRD, INRAE, 34250, Palavas-Les-Flots, France.
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
| | - Marc Vandeputte
- MARBEC, Univ. Montpellier, CNRS, Ifremer, IRD, INRAE, 34250, Palavas-Les-Flots, France
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Romain Morvezen
- SYSAAF, Station LPGP/INRAE, Campus de Beaulieu, 35042, Rennes, France
| | - Anastasia Bestin
- SYSAAF, Station LPGP/INRAE, Campus de Beaulieu, 35042, Rennes, France
| | - Mathieu Besson
- SYSAAF, Station LPGP/INRAE, Campus de Beaulieu, 35042, Rennes, France
| | - Joseph Brunier
- Ecloserie Marine de Gravelines-Ichtus, Gloria Maris Group, 59273, Gravelines, France
| | - Aline Bajek
- Ecloserie Marine de Gravelines-Ichtus, Gloria Maris Group, 59273, Gravelines, France
| | | | - Yoannah François
- SYSAAF, Station LPGP/INRAE, Campus de Beaulieu, 35042, Rennes, France
- ANSES, Unit Virology, Immunology and Ecotoxicology of Fish, Technopôle Brest-Iroise, 29280, Plouzané, France
| | - Olivier Bouchez
- US 1426, GeT-PlaGe, INRAE, Genotoul, Castanet-Tolosan, France
| | - Xavier Cousin
- MARBEC, Univ. Montpellier, CNRS, Ifremer, IRD, INRAE, 34250, Palavas-Les-Flots, France
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Charles Poncet
- INRAE-UCA, UMR 1095 GDEC, 63000, Clermont-Ferrand, France
| | - Thierry Morin
- ANSES, Unit Virology, Immunology and Ecotoxicology of Fish, Technopôle Brest-Iroise, 29280, Plouzané, France
| | | | - Béatrice Chatain
- MARBEC, Univ. Montpellier, CNRS, Ifremer, IRD, INRAE, 34250, Palavas-Les-Flots, France
| | - Pierrick Haffray
- SYSAAF, Station LPGP/INRAE, Campus de Beaulieu, 35042, Rennes, France
| | - Florence Phocas
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - François Allal
- MARBEC, Univ. Montpellier, CNRS, Ifremer, IRD, INRAE, 34250, Palavas-Les-Flots, France
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Robinson NA, Robledo D, Sveen L, Daniels RR, Krasnov A, Coates A, Jin YH, Barrett LT, Lillehammer M, Kettunen AH, Phillips BL, Dempster T, Doeschl‐Wilson A, Samsing F, Difford G, Salisbury S, Gjerde B, Haugen J, Burgerhout E, Dagnachew BS, Kurian D, Fast MD, Rye M, Salazar M, Bron JE, Monaghan SJ, Jacq C, Birkett M, Browman HI, Skiftesvik AB, Fields DM, Selander E, Bui S, Sonesson A, Skugor S, Østbye TK, Houston RD. Applying genetic technologies to combat infectious diseases in aquaculture. REVIEWS IN AQUACULTURE 2023; 15:491-535. [PMID: 38504717 PMCID: PMC10946606 DOI: 10.1111/raq.12733] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/24/2022] [Accepted: 08/16/2022] [Indexed: 03/21/2024]
Abstract
Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies-sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.
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Affiliation(s)
- Nicholas A. Robinson
- Nofima ASTromsøNorway
- Sustainable Aquaculture Laboratory—Temperate and Tropical (SALTT)School of BioSciences, The University of MelbourneMelbourneVictoriaAustralia
| | - Diego Robledo
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghEdinburghUK
| | | | - Rose Ruiz Daniels
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghEdinburghUK
| | | | - Andrew Coates
- Sustainable Aquaculture Laboratory—Temperate and Tropical (SALTT)School of BioSciences, The University of MelbourneMelbourneVictoriaAustralia
| | - Ye Hwa Jin
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghEdinburghUK
| | - Luke T. Barrett
- Sustainable Aquaculture Laboratory—Temperate and Tropical (SALTT)School of BioSciences, The University of MelbourneMelbourneVictoriaAustralia
- Institute of Marine Research, Matre Research StationMatredalNorway
| | | | | | - Ben L. Phillips
- Sustainable Aquaculture Laboratory—Temperate and Tropical (SALTT)School of BioSciences, The University of MelbourneMelbourneVictoriaAustralia
| | - Tim Dempster
- Sustainable Aquaculture Laboratory—Temperate and Tropical (SALTT)School of BioSciences, The University of MelbourneMelbourneVictoriaAustralia
| | - Andrea Doeschl‐Wilson
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghEdinburghUK
| | - Francisca Samsing
- Sydney School of Veterinary ScienceThe University of SydneyCamdenAustralia
| | | | - Sarah Salisbury
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghEdinburghUK
| | | | | | | | | | - Dominic Kurian
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghEdinburghUK
| | - Mark D. Fast
- Atlantic Veterinary CollegeThe University of Prince Edward IslandCharlottetownPrince Edward IslandCanada
| | | | | | - James E. Bron
- Institute of AquacultureUniversity of StirlingStirlingScotlandUK
| | - Sean J. Monaghan
- Institute of AquacultureUniversity of StirlingStirlingScotlandUK
| | - Celeste Jacq
- Blue Analytics, Kong Christian Frederiks Plass 3BergenNorway
| | | | - Howard I. Browman
- Institute of Marine Research, Austevoll Research Station, Ecosystem Acoustics GroupTromsøNorway
| | - Anne Berit Skiftesvik
- Institute of Marine Research, Austevoll Research Station, Ecosystem Acoustics GroupTromsøNorway
| | | | - Erik Selander
- Department of Marine SciencesUniversity of GothenburgGothenburgSweden
| | - Samantha Bui
- Institute of Marine Research, Matre Research StationMatredalNorway
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What Can Genetics Do for the Control of Infectious Diseases in Aquaculture? Animals (Basel) 2022; 12:ani12172176. [PMID: 36077896 PMCID: PMC9454762 DOI: 10.3390/ani12172176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/02/2022] [Accepted: 08/22/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Infectious diseases place an economic burden on aquaculture and a limitation to its growth. This state-of-the-art review describes the application of genetics and genomics as novel tools to control infectious disease in aquaculture. Abstract Infectious diseases place an economic burden on aquaculture and a limitation to its growth. An innovative approach to mitigate their impact on production is breeding for disease resistance: selection for domestication, family-based selection, marker-assisted selection, and more recently, genomic selection. Advances in genetics and genomics approaches to the control of infectious diseases are key to increasing aquaculture efficiency, profitability, and sustainability and to reducing its environmental footprint. Interaction and co-evolution between a host and pathogen can, however, turn breeding to boost infectious disease resistance into a potential driver of pathogenic change. Parallel molecular characterization of the pathogen and its virulence and antimicrobial resistance genes is therefore essential to understand pathogen evolution over time in response to host immunity, and to apply appropriate mitigation strategies.
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Genotyping, the Usefulness of Imputation to Increase SNP Density, and Imputation Methods and Tools. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2467:113-138. [PMID: 35451774 DOI: 10.1007/978-1-0716-2205-6_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Imputation has become a standard practice in modern genetic research to increase genome coverage and improve accuracy of genomic selection and genome-wide association study as a large number of samples can be genotyped at lower density (and lower cost) and, imputed up to denser marker panels or to sequence level, using information from a limited reference population. Most genotype imputation algorithms use information from relatives and population linkage disequilibrium. A number of software for imputation have been developed originally for human genetics and, more recently, for animal and plant genetics considering pedigree information and very sparse SNP arrays or genotyping-by-sequencing data. In comparison to human populations, the population structures in farmed species and their limited effective sizes allow to accurately impute high-density genotypes or sequences from very low-density SNP panels and a limited set of reference individuals. Whatever the imputation method, the imputation accuracy, measured by the correct imputation rate or the correlation between true and imputed genotypes, increased with the increasing relatedness of the individual to be imputed with its denser genotyped ancestors and as its own genotype density increased. Increasing the imputation accuracy pushes up the genomic selection accuracy whatever the genomic evaluation method. Given the marker densities, the most important factors affecting imputation accuracy are clearly the size of the reference population and the relationship between individuals in the reference and target populations.
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Abstract
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.
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Affiliation(s)
- François Allal
- MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France.
| | - Nguyen Hong Nguyen
- School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD, Australia
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