Potential of genomic selection for improvement of resistance to ostreid herpesvirus in Pacific oyster (Crassostrea gigas)
A. P. Gutierrez
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
Search for more papers by this authorJ. Symonds
Cawthron Institute, 98 Halifax Street East, Nelson, 7010 New Zealand
Search for more papers by this authorN. King
Cawthron Institute, 98 Halifax Street East, Nelson, 7010 New Zealand
Search for more papers by this authorK. Steiner
Cawthron Institute, 98 Halifax Street East, Nelson, 7010 New Zealand
Search for more papers by this authorT. P. Bean
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
Search for more papers by this authorCorresponding Author
R. D. Houston
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
Address for correspondence
R. D. Houston, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK.
E-mail: ross.houston@roslin.ed.ac.uk
Search for more papers by this authorA. P. Gutierrez
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
Search for more papers by this authorJ. Symonds
Cawthron Institute, 98 Halifax Street East, Nelson, 7010 New Zealand
Search for more papers by this authorN. King
Cawthron Institute, 98 Halifax Street East, Nelson, 7010 New Zealand
Search for more papers by this authorK. Steiner
Cawthron Institute, 98 Halifax Street East, Nelson, 7010 New Zealand
Search for more papers by this authorT. P. Bean
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
Search for more papers by this authorCorresponding Author
R. D. Houston
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
Address for correspondence
R. D. Houston, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK.
E-mail: ross.houston@roslin.ed.ac.uk
Search for more papers by this authorSummary
In genomic selection (GS), genome-wide SNP markers are used to generate genomic estimated breeding values for selection candidates. The application of GS in shellfish looks promising and has the potential to help in dealing with one of the main issues currently affecting Pacific oyster production worldwide, which is the ‘summer mortality syndrome’. This causes periodic mass mortality in farms worldwide and has mainly been attributed to a specific variant of the ostreid herpesvirus (OsHV-1). In the current study, we evaluated the potential of genomic selection for host resistance to OsHV-1 in Pacific oysters, and compared it with pedigree-based approaches. An OsHV-1 disease challenge was performed using an immersion-based virus exposure treatment for oysters for 7 days. A total of 768 samples were genotyped using the medium-density SNP array for oysters. A GWAS was performed for the survival trait using a GBLUP approach in blupf90 software. Heritability ranged from 0.25 ± 0.05 to 0.37 ± 0.05 (mean ± SE) based on pedigree and genomic information respectively. Genomic prediction was more accurate than pedigree prediction, and SNP density reduction had little impact on prediction accuracy until marker densities dropped below approximately 500 SNPs. This demonstrates the potential for GS in Pacific oyster breeding programmes, and importantly, demonstrates that a low number of SNPs might suffice to obtain accurate genomic estimated breeding values, thus potentially making the implementation of GS more cost effective.
Open Research
Data availability
Data are available to non-commercial parties subject to a material transfer agreement.
Supporting Information
Filename | Description |
---|---|
age12909-sup-0001-FigS1.docxWord document, 34.6 KB |
Figure S1 Correlation of survival level observed per family in both the low virus (LV) and high virus (HV) conditions. |
age12909-sup-0002-FigS2.docxWord document, 87.4 KB |
Figure S2 Number of mortalities observed during the length of the challenge for both HV and LV conditions. |
age12909-sup-0003-FigS3.docxWord document, 168.2 KB |
Figure S3 GWAS results for ostreid herpesvirus (OsHV-1) survival based on: (a) single SNP; (b) 10 SNP window; and (c) 20 SNP window. |
age12909-sup-0004-TableS1.xlsxapplication/excel, 8.8 KB |
Table S1 Number of individuals genotyped per family. |
age12909-sup-0005-TableS2.xlsxapplication/excel, 13.4 KB |
Table S2 Number of mortalities observed during the challenge for control, low-virus (LV) and high-virus experiments. |
age12909-sup-0006-TableS3.docxWord document, 17.3 KB |
Table S3 Genomic selection results for analyses based on pedigree (PBLUP), genomic relationship matrix filtered by MAF (GBLUP-MAF) and genomic relationship matrix using random markers (GBLUP-Random). |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- Aguilar I., Misztal I., Johnson D.L., Legarra A., Tsuruta S., Lawlor T.J. (2010) Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science 93, 743–52.
- Aulchenko Y.S., Ripke S., Isaacs A., van Duijn C.M. (2007) GenABEL: an R library for genome-wide association analysis. Bioinformatics 23, 1294–6.
- Azéma P., Lamy J.-B., Boudry P., Renault T., Travers M.-A., Dégremont L. (2017) Genetic parameters of resistance to Vibrio aestuarianus, and OsHV-1 infections in the Pacific oyster, Crassostrea gigas, at three different life stages. Genetics Selection Evolution 49, 23.
- Barría A., Christensen K.A., Yoshida G.M., Correa K., Jedlicki A., Lhorente J.P., Davidson W.S., Yáñez J.M. (2018) Genomic predictions and genome-wide association study of resistance against Piscirickettsia salmonis in coho salmon (Oncorhynchus kisutch) using ddRAD sequencing. G3: Genes|Genomes|Genetics 8, 1183–94.
- Camara M.D., Symonds J.E. (2014) Genetic improvement of New Zealand aquaculture species: programmes, progress and prospects. New Zealand Journal of Marine and Freshwater Research 48, 466–91.
- Camara M.D., Yen S., Kaspar H.F., Kesarcodi-Watson A., King N., Jeffs A.G., Tremblay L.A. (2017) Assessment of heat shock and laboratory virus challenges to selectively breed for ostreid herpesvirus 1 (OsHV-1) resistance in the Pacific oyster, Crassostrea gigas. Aquaculture 469, 50–8.
- Chang C.C., Chow C.C., Tellier L.C., Vattikuti S., Purcell S.M., Lee J.J. (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience 4, 7.
- Dégremont L., Bédier E., Boudry P. (2010) Summer mortality of hatchery-produced Pacific oyster spat (Crassostrea gigas). II. Response to selection for survival and its influence on growth and yield. Aquaculture 299, 21–9.
- Dégremont L., Garcia C., Allen S.K. (2015a) Genetic improvement for disease resistance in oysters: a review. Journal of Invertebrate Pathology 131, 226–41.
- Dégremont L., Lamy J.-B., Pépin J.-F., Travers M.-A., Renault T. (2015b) New insight for the genetic evaluation of resistance to ostreid herpesvirus infection, a worldwide disease, in Crassostrea gigas. PLoS ONE 10, e0127917.
- Dégremont L., Nourry M., Maurouard E. (2015c) Mass selection for survival and resistance to OsHV-1 infection in Crassostrea gigas spat in field conditions: response to selection after four generations. Aquaculture 446, 111–21.
- Dou J., Li X., Fu Q., Jiao W., Li Y., Li T., Wang Y., Hu X., Wang S., Bao Z. (2016) Evaluation of the 2b-RAD method for genomic selection in scallop breeding. Scientific Reports 6, 19244.
- FAO (2018) Food and Agriculture Organization Statistical Yearbook. FAO, Rome, Italy. https://doi.org/10.1186/1471-2164-10-341.
- Fernando R.L., Cheng H., Sun X., Garrick D.J. (2017) A comparison of identity-by-descent and identity-by-state matrices that are used for genetic evaluation and estimation of variance components. Journal of Animal Breeding and Genetics 134, 213–23.
- Gilmour A., Gogel, B., Cullis, B., Welham, S. & Thompson, R. (2015). ASReml User Guide Release 4.1 Structural Specification. Hemel Hempstead, UK, VSN International Ltd.
- Goddard M.E., Hayes B.J. (2007) Genomic selection. Journal of Animal Breeding and Genetics 124, 323–30.
- Gutierrez A.P., Turner F., Gharbi K., Talbot R., Lowe N.R., Peñaloza C., McCullough M., Prodöhl P.A., Bean T.P., Houston R.D. (2017) Development of a medium density combined-species SNP array for Pacific and European oysters (Crassostrea gigas and Ostrea edulis). G3: Genes|Genomes|Genetics 7, 2209–18.
- Gutierrez A.P., Bean T.P., Hooper C., Stenton C.A., Sanders M.B., Paley R.K., Rastas P., Bryrom M., Matika O., Houston R.D. (2018a) A genome-wide association study for host resistance to ostreid herpesvirus in pacific oysters (Crassostrea gigas). G3: Genes|Genomes|Genetics 8, 1273–80.
- Gutierrez A.P., Matika O., Bean T.P., Houston R.D. (2018b) Genomic selection for growth traits in Pacific oyster (Crassostrea gigas): potential of low-density marker panels for breeding value prediction. Frontiers in Genetics 9, 391.
- Hedgecock D., Shin G., Gracey A.Y., Den Berg D.V., Samanta M.P. (2015) Second-generation linkage maps for the pacific oyster Crassostrea gigas reveal errors in assembly of genome scaffolds. G3: Genes|Genomes|Genetics 5, 2007–19.
- Houston R.D. (2017) Future directions in breeding for disease resistance in aquaculture species. Revista Brasileira de Zootecnia 46, 545–51.
- Houston R.D., Taggart J.B., Cézard T. et al. (2014) Development and validation of a high density SNP genotyping array for Atlantic salmon (Salmo salar). BMC Genomics 15, 90.
- Kalinowski S.T., Taper M.L., Marshall T.C. (2007) Revising how the computer program cervus accommodates genotyping error increases success in paternity assignment. Molecular Ecology 16, 1099–106.
- Kirkland P.D., Hick P., Gu X. (2015) Development of a Laboratory Model for Infectious Challenge of Pacific Oysters (Crassostrea gigas) with Ostreid Herpesvirus Type-1. Elizabeth Macarthur Agriculture Institute, Sydney.
- Liu S., Sun L., Li Y. et al. (2014) Development of the catfish 250K SNP array for genome-wide association studies. BMC Research Notes 7, 135.
- de Lorgeril J., Lucasson A., Petton B. et al. (2018) Immune-suppression by OsHV-1 viral infection causes fatal bacteraemia in Pacific oysters. Nature Communications 9, 4215.
- Malham S.K., Cotter E., O'Keeffe S., Lynch S., Culloty S.C., King J.W., Latchford J.W., Beaumont A.R. (2009) Summer mortality of the Pacific oyster, Crassostrea gigas, in the Irish Sea: the influence of temperature and nutrients on health and survival. Aquaculture 287, 128–38.
- Meuwissen T.H.E., Hayes B.J., Goddard M.E. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–29.
- Misztal I., Tsuruta S., Strabel T., Auvray B., Druet T., Lee D. (2002) BLUPF90 and related programs (BGF90). In: Proceedings of the 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France, pp. 743–4.
- Ødegård J., Moen T., Santi N., Korsvoll S.A., Kjøglum S., Meuwissen T.H.E. (2014) Genomic prediction in an admixed population of Atlantic salmon (Salmo salar). Frontiers in Genetics 5, 402.
- Palaiokostas C., Ferraresso S., Franch R., Houston R.D., Bargelloni L. (2016) Genomic prediction of resistance to pasteurellosis in gilthead sea bream (Sparus aurata) using 2b-RAD sequencing. G3: Genes|Genomes|Genetics 6, 3693–700.
- Palaiokostas C., Cariou S., Bestin A., Bruant J.-S., Haffray P., Morin T., Cabon J., Allal F., Vandeputte M., Houston R.D. (2018a) Genome-wide association and genomic prediction of resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax) using RAD sequencing. Genetics Selection Evolution 50, 30.
- Palaiokostas C., Kocour M., Prchal M., Houston R.D. (2018b) Accuracy of genomic evaluations of juvenile growth rate in common carp (Cyprinus carpio) using genotyping by sequencing. Frontiers in Genetics 9, 82.
- Palaiokostas C., Vesely T., Kocour M., Prchal M., Pokorova D., Piackova V., Pojezdal L., Houston R.D. (2019) Optimizing genomic prediction of host resistance to koi herpesvirus disease in carp. Frontiers in Genetics 10, 543.
- Palti Y., Gao G., Liu S., Kent M.P., Lien S., Miller M.R., Rexroad C.E., Moen T. (2015) The development and characterization of a 57K single nucleotide polymorphism array for rainbow trout. Molecular Ecology Resources 15, 662–72.
- Petton B., Bruto M., James A., Labreuche Y., Alunno-Bruscia M., Le Roux F. (2015) Crassostrea gigas mortality in France: the usual suspect, a herpes virus, may not be the killer in this polymicrobial opportunistic disease. Frontiers in Microbiology 6, 686.
- Qi H., Song K., Li C., Wang W., Li B., Li L., Zhang G. (2017) Construction and evaluation of a high-density SNP array for the Pacific oyster (Crassostrea gigas). PLoS ONE 12, e0174007.
- Rastas P. (2017) Lep-MAP3: robust linkage mapping even for low-coverage whole genome sequencing data. Bioinformatics 33, 3726–32.
- Robledo D, Matika O, Hamilton A, Houston RD (2018) Genome-wide association and genomic selection for resistance to amoebic gill disease in Atlantic salmon. G3: Genes|Genomes|Genetics 8, 1195–203.
- Sauvage C., Boudry P., De Koning D.J., Haley C.S., Heurtebise S., Lapègue S. (2010) QTL for resistance to summer mortality and OsHV-1 load in the Pacific oyster (Crassostrea gigas). Animal Genetics 41, 390–9.
- Segarra A., Pépin J.F., Arzul I., Morga B., Faury N., Renault T. (2010) Detection and description of a particular Ostreid herpesvirus 1 genotype associated with massive mortality outbreaks of Pacific oysters, Crassostrea gigas, in France in 2008. Virus Research 153, 92–9.
- Tsai H.-Y., Hamilton A., Tinch A.E., Guy D.R., Gharbi K., Stear M.J., Matika O., Bishop S.C., Houston R.D. (2015) Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array. BMC Genomics 16, 969.
- Vallejo R.L., Leeds T.D., Gao G., Parsons J.E., Martin K.E., Evenhuis J.P., Fragomeni B.O., Wiens G.D., Palti Y. (2017) Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture. Genetics Selection Evolution 49, 17.
- Vallejo R.L., Silva R.M.O., Evenhuis J.P. et al. (2018) Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low-density SNP panels: Evidence that long-range LD is a major contributing factor. Journal of Animal Breeding and Genetics 135, 263–74.
- VanRaden P.M. (2008) Efficient methods to compute genomic predictions. Journal of Dairy Science 91, 4414–23.
- Xu J., Zhao Z., Zhang X. et al. (2014) Development and evaluation of the first high-throughput SNP array for common carp (Cyprinus carpio). BMC Genomics 15, 307.
- Yáñez J.M., Naswa S., López M.E. et al. (2016) Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar): validation in wild and farmed American and European populations. Molecular Ecology Resources 16, 1002–11.
- Yoshida G.M., Lhorente J.P., Carvalheiro R., Yáñez J.M. (2017) Bayesian genome-wide association analysis for body weight in farmed Atlantic salmon (Salmo salar L.). Animal Genetics 48, 698–703.
- Yoshida G.M., Bangera R., Carvalheiro R., Correa K., Figueroa R., Lhorente J.P., Yáñez J.M. (2018) Genomic prediction accuracy for resistance against Piscirickettsia salmonis in farmed rainbow trout. G3: Genes|Genomes|Genetics 8, 719–26.
- Zhang G., Fang X., Guo X. et al. (2012) The oyster genome reveals stress adaptation and complexity of shell formation. Nature 490, 49–54.