Abstract
Over 80% of the aquaculture production in Europe originates from selective breeding programs aiming to improve several traits simultaneously. Selecting for increased feed efficiency combines economic benefits and a reduced environmental impact. Additionally, disease outbreaks pose serious challenges for organic aquaculture with limited therapeutic agents. Therefore, selective breeding comprises a valuable tool combined with strict biosecurity and effective management practices. Phenotypic sex is labile in fish exhibiting sexual dimorphism in a range of traits of interest. Identified genomic regions concerning sex determination demonstrates the importance of selective breeding. The existence of GxE interactions imply that fish derived from the single nucleus might show lower-than-expected genetic gains in different environments. Understanding their key contribution among different environments is critical for the optimization of a selective breeding program. Next-generation sequencing (NGS) techniques have resulted in the annotation of many teleost genomes, and omics are becoming a powerful multidisciplinary strategy (genomics, transcriptomics, proteomics, and metabolomics). Given the importance of selective breeding programs, particular attention should be paid to the continuous enhancement and development of scientific knowledge, so that the EU legislative framework on organic aquaculture is always up to new challenges toward sustainability increasing the organic logo credibility for the consumers.
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References
Bentsen HB, Gjerde B, Nguyen NH, Rye M, Ponzoni RW, Palada de Vera MS et al (2012) Genetic improvement of farmed tilapias: genetic parameters for body weight at harvest in Nile tilapia (Oreochromis niloticus) during five generations of testing in multiple environments. Aquaculture 338–341:56–65
Bishop SC, Woolliams JA (2014) Genomics and disease resistance studies in livestock. Livest Sci 166:190–198
Chapman RW, Reading BJ, Sullivan CV (2014) Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis. PLoS One 9:e96818
Chavanne H, Janssen K, Hofherr J, Contini F, Haffray P et al (2016) A comprehensive survey on selective breeding programs and seed market in the European aquaculture fish industry. Aquac Int 24:1287–1307
Chiasson M, Quinton M, Pelletier C, Danzmann R, Ferguson M (2013) Family x environment interactions in the growth and survival of Arctic charr (Salvelinus alpinus) grown in brackish and fresh water. Aquac Res 45:1953–1963
Correa K, Bangera R, Figueroa R, Lhorente JP, Yanez JM (2017) The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar). Genet Sel Evol: GSE 49:15
Daulé S, Vandeputte M, Vergnet A, Guinand B, Grima L et al (2014) Effect of selection for fasting tolerance on feed intake, growth and feed efficiency in the European sea bass Dicentrarchus labrax. Aquaculture 420–421:S42–S49
David P (1998) Heterozygosity-fitness correlations: new perspectives on old problems. Heredity 80:531–537
de Verdal H, Komen H, Quillet E, Chatain B, Allal F et al (2017) Improving feed efficiency in fish using selective breeding: a review. Rev Aquacult 10:833–851
Domingos JA, Smith-Keune C, Robinson N, Loughnan S, Harrison P, Jerry DR (2013) Heritability of harvest growth traits and genotype-environment interactions in barramundi, Lates calcarifer (Bloch). Aquaculture 402–403:66–75
Dupont-Nivet M, Karahan-Nomm B, Vergnet A, Merdy O, Haffray P, Chavanne H et al (2010) Genotype by environment interactions for growth in European seabass (Dicentrarchus labrax) are large when growth rate rather than weight is considered. Aquaculture 306:365–368
Eshel O, Shirak A, Weller JI, Hulata G, Ron M (2012) Linkage and physical mapping of sex region on LG23 of Nile Tilapia (Oreochromis niloticus). G3 Genes|Genome|Genetics 2:35–42
Evans S, Langdon C (2006) Effects of genotype x environment interactions on the selection of broadly adapted Pacific oysters (Crassostrea gigas). Aquaculture 261:522–534
Falconer, D. S., Mackay, T. F. C., 1996 Introduction to quantitative genetics. Longman, Essex
Gitterle T, Salte R, Gjerde B, Cock J, Johansen H et al (2005) Genetic (co)variation in resistance to white spot syndrome virus (WSSV) and harvest weight in Penaeus (Litopenaeus) vannamei. Aquaculture 246:139–149
Gjedrem T (2010) The first family-based breeding program in aquaculture. Rev Aquac 2:2–15
Gjedrem T, Robinson N (2014) Advances by selective breeding for aquatic species: a review. Agric Sci 5:1152–1158
Gjedrem T, Rye M (2016) Selection response in fish and shellfish: a review. Rev Aquacult 10:168–179
Gonen S, Baranski M, Thorland I, Norris A, Grove H et al (2015) Mapping and validation of a major QTL affecting resistance to pancreas disease (salmonid alphavirus) in Atlantic salmon (Salmo salar). Heredity:1–10
Guan J, Hu Y, Wang M, Wang W, Kong J, Luan S (2016) Estimating genetic parameters and genotype-by-environment interactions in body traits of turbot in two different rearing environments. Aquaculture 450:321–327
Hammond J (1947) Animal breeding in relation to nutrition and environmental conditions. Biol Rev 22:195–213
Henderson CR (1975) Best linear unbiased estimation and prediction under a selection model. Biometrics 31:423–447
Houston RD, Haley CS, Hamilton A, Guy DR, Tinch AE et al (2008) Major quantitative trait loci affect resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar). Genetics 178:1109–1115
Irvine RJ (2006) Parasites and the dynamics of wild mammal populations. Anim Sci 82:775–781
Janssen K, Saatkamp H, Komen H (2018) Cost-benefit analysis of aquaculture breeding programs. Genet Sel Evol 50:2
Kause A, Ritola O, Paananen T, Mantysaari E, Eskelinen U (2003) Selection against early maturity in large rainbow trout Oncorhynchus mykiss: the quantitative genetics of sexual dimorphism and genotype-by-environment interactions. Aquaculture 228:53–68
Kavouras M, Tsilika K, Exadactylos A (2017) A computer algebra system approach in gene expression analysis. Prog Ind Ecol 11(1):49–60
Kolstad K, Thorland I, Refstie T, Gjerde B (2006) Genetic variation and genotype by location interaction in body weight, spinal deformity and sexual maturity in Atlantic cod (Gadus morhua) reared at different locations off Norway. Aquaculture 259:66–73
Le Boucher R, Vandeputte M, Dupont-Nivet M, Quillet E, Ruelle F, Vergnet A et al (2013) Genotype by diet interactions in European sea bass (Dicentrarchus labrax L.): nutritional challenge with totally plant-based diets. J Anim Sci 91:44–56. https://doi.org/10.2527/jas.2012-5311.
Lee B-Y, Coutanceau J-P, Ozouf-Costaz C, D’Cotta H, Baroiller J-F et al (2011) Genetic and physical mapping of sex-linked AFLP markers in Nile tilapia (Oreochromis niloticus). Mar Biotechnol 13:557–562
Li W, Luan S, Luo K, Sui J, Xu X, Tan J, Kong J (2015) Genetic parameters and genotype by environment interaction for cold tolerance, body weight and survival of the Pacific white shrimp Penaeus vannamei at different temperatures. Aquaculture 441:8–15. https://doi.org/10.1016/j.aquaculture.2015.02.013
Lin CY, Togashi K (2002) Genetic improvement in the presence of genotype by environment interaction. J Anim Sci 73:3–11
Lu X, Luan S, Cao B, Meng X, Sui J, Dai P et al (2017) Estimation of genetic parameters and genotype-by-environment interactions related to acute ammonia stress in Pacific white shrimp (Litopenaeus vannamei) juveniles at two different salinity levels. PLoS One 12(3):e0173835. https://doi.org/10.1371/journal.pone.0173835
Luan TD, Olesen I, Ødegård J, Kolstad K, Dan NC (2008) Genotype by environment interaction for harvest body weight and survival of Nile tilapia (Oreochromis niloticus) in brackish and fresh water ponds. In: Proceedings of the 8th international symposium on Tilapia in aquaculture. Cairo, Egypt, October 12–14, 2008. Cited 21 January 2013. Available from URL: http://ag.arizona.edu/azaqua/ista/ISTA8/ProceedingsISTA8.htm
Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland
Mair GC, Abucay JS, a Abella T, a Beardmore J, Skibinski DOF (1997) Genetic manipulation of sex ratio for the large-scale production of all-male tilapia Oreochromis niloticus. Can J Fish Aquat Sci 54:396–404
Mas-Muñoz J, Blonk R, Schrama JW, van Arendonk J, Komen H (2013) Genotype by environment interaction for growth of sole (Solea solea) reared in an intensive aquaculture system and in a semi-natural environment. Aquaculture 410–411:230–235
Meuwissen THE, Woolliams JA (1994) Effective sizes of livestock populations to prevent a decline in fitness. Theor Appl Genet 89(7–8):1019–1026
Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829
Moen T, Baranski M, Sonesson AK, Kjøglum S (2009) Confirmation and fine-mapping of a major QTL for resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar): population-level associations between markers and trait. BMC Genomics 10:368
Navarro A, Zamorano MJ, Hildebrandt S, Ginés R, Aguilera C, Afonso JM (2009) Estimates of heritabilities and genetic correlations for growth and carcass traits in gilthead seabream (Sparus auratus L.), under industrial conditions. Aquaculture 289:225–230
Nguyen NH (2016) Genetic improvement for important farmed aquaculture species with a reference to carp, tilapia and prawns in Asia: achievements, lessons and challenges. Fish Fish 17:483–506. https://doi.org/10.1111/faf.12122
Nilsson J, Brännäs E, Eriksson L-O (2010) The Swedish Arctic charr breeding programme. Hydrobiologia 650:275–282
Ødegård J, Baranski M, Gjerde B, Gjedrem T (2011) Methodology for genetic evaluation of disease resistance in aquaculture species: challenges and future prospects. Aquac Res 42:103–114
Ødegård J, Moen T, Santi N, Korsvoll SA, Kjøglum S et al (2014) Genomic prediction in an admixed population of Atlantic salmon (Salmo salar). Front Genet 5:402
Palaiokostas C, Houston R (2018) Genome-wide approaches to understanding and improving complex traits in aquaculture species. CAB Rev: Perspect Agric Vet Sci Nutr Nat Res. https://doi.org/10.1079/pavsnnr201712055
Palaiokostas C, Bekaert M, Khan MGQ, Taggart JB, Gharbi K et al (2013) Mapping and validation of the major sex-determining region in Nile Tilapia (Oreochromis niloticus L.) using RAD sequencing. PLoS One 8:e68389
Palaiokostas C, Bekaert M, Khan MGQM, Taggart JBJ, Gharbi K et al (2015) A novel sex-determining QTL in Nile tilapia (Oreochromis niloticus). BMC Genomics 16:171
Palaiokostas C, Ferraresso S, Franch R, Houston RD, Bargelloni L (2016) Genomic prediction of resistance to pasteurellosis in gilthead sea bream (Sparus aurata) using 2b-RAD sequencing. G3 6(11):3693–3700
Palaiokostas C, Cariou S, Bestin A, Bruant J-S, Haffray P et al (2018) Genome-wide association and genomic prediction of resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax) using RAD sequencing. Genet Sel Evol 50:30
Ponzoni RW, Nguyen NH, Khaw HL, Ninh NH (2008) Accounting for genotype by environment interaction in economic appraisal of genetic improvement programs in common carp Cyprinus carpio. Aquaculture 285:47–55
Robledo D, Palaiokostas C, Bargelloni L, Martínez P, Houston R (2017) Applications of genotyping by sequencing in aquaculture breeding and genetics. Rev Aquac 0:1–13
Sae-Lim P, Komen H, Kause A, Mulder H (2014) Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Oncorhynchus mykiss): reaction norm and factor analytic models. Genet Sel Evol 46:16
Sae-Lim P, Gjerde B, Nielsen HM, Mulder H, Kause A (2016) A review of genotype-by-environment interaction and micro-environmental sensitivity in aquaculture species. Rev Aquac 8:369–393
Saillant E, Dupont-Nivet M, Haffray P, Chatain B (2006) Estimates of heritability and genotype-environment interactions for body weight in sea bass (Dicentrarchus labrax L.) raised under communal rearing conditions. Aquaculture 254:139–147
Savorani F, Picone G, Badiani A, Fagioli P, Capozzi F, Engelsen S (2010) Metabolic profiling and aquaculture differentiation of gilthead sea bream by 1H NMR metabonomics. Food Chem 120:907. https://doi.org/10.1016/j.foodchem.2009.10.071
Trọng TQ, Mulder HA, van Arendonk JAM, Komen H (2013) Heritability and genotype by environment interaction estimates for harvest weight, growth rate, and shape of Nile tilapia (Oreochromis niloticus) grown in river cage and VAC in Vietnam. Aquaculture 384–387:119–127
Tsai H-Y, Hamilton A, Tinch AE, Guy DR, Bron JE et al (2016) Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations. Genet Sel Evol 48:47
Turra EM, Toral FLB, Alvarenga ER, Raidan FSS, Fernandes AFA, Alves GFO (2016) Genotype × environment interaction for growth traits of Nile tilapia in biofloc technology, recirculating water and Cage systems. Aquaculture 460:98–104. https://doi.org/10.1016/j.aquaculture.2016.04.020
Vallejo RL, Leeds TD, Fragomeni BO, Gao G, Hernandez AG et al (2016) Evaluation of genome-enabled selection for bacterial cold water disease resistance using progeny performance data in rainbow trout: insights on genotyping methods and genomic prediction models. Front Genet 7:96
Vallejo RL, Leeds TD, Gao G, Parsons JE, Martin KE et al (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. Genet Sel Evol 49:17
Vandeputte M, Dupont-Nivet M, Chavanne H, Chatain B (2007) A polygenic hypothesis for sex determination in the European sea bass Dicentrarchus labrax. Genetics 176:1049–1057
Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10(1):57–63
Wang L, Liu P, Huang S, Ye B, Chua E et al (2017) Genome-wide association study identifies loci associated with resistance to viral nervous necrosis disease in Asian seabass. Mar Biotechnol 19:255–265
Wessels S, Krause I, Floren C, Schütz E, Beck J et al (2017) ddRADseq reveals determinants for temperature-dependent sex reversal in Nile tilapia on LG23. BMC Genomics 18:531
Young T, Alfaro AC, Villas-Bôas SG (2016) Metabolic profiling of mussel larvae: effect of handling and culture conditions. Aquac Int 24:843. https://doi.org/10.1007/s10499-015-9945-0
Zhou T, Liu S, Geng X, Jin Y, Jiang C et al (2017) GWAS analysis of QTL for enteric septicemia of catfish and their involved genes suggest evolutionary conservation of a molecular mechanism of disease resistance. Mol Gen Genomics 292:231–242
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Martsikalis, P.V., Gkafas, G.A., Palaiokostas, C., Exadactylos, A. (2019). Genomics Era on Breeding Aquaculture Stocks. In: Lembo, G., Mente, E. (eds) Organic Aquaculture . Springer, Cham. https://doi.org/10.1007/978-3-030-05603-2_4
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