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Optimised parent selection and minimum inbreeding mating in small aquaculture breeding schemes: a simulation study

Published online by Cambridge University Press:  06 July 2012

F. S. Hely ,
P. R. Amer ,
S. P. Walker  and
J. E. Symonds
F. S. Hely*
Affiliation:
AbacusBio Limited, 442 Moray Place, Dunedin 9058, New Zealand
P. R. Amer
Affiliation:
AbacusBio Limited, 442 Moray Place, Dunedin 9058, New Zealand
S. P. Walker
Affiliation:
National Institute of Water and Atmospheric Research (NIWA), Station Road, Ruakaka 0116, New Zealand
J. E. Symonds
Affiliation:
National Institute of Water and Atmospheric Research (NIWA), Station Road, Ruakaka 0116, New Zealand
*
†E-mail: fhely@abacusbio.co.nz
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Abstract

The effectiveness of low cost breeding scheme designs for small aquaculture breeding programmes were assessed for their ability to achieve genetic gain while managing inbreeding using stochastic simulation. Individuals with trait data were simulated over 15 generations with selection on a single trait. Combinations of selection methods, mating strategies and genetic evaluation options were evaluated with and without the presence of common environmental effects. An Optimal Parent Selection (OPS) method using semi-definite programming was compared with a truncation selection (TS) method. OPS constrains the rate of inbreeding while maximising genetic gain. For either selection method, mating pairs were assigned from the selected parents by either random mating (RM) or Minimum Inbreeding Mating (MIM), which used integer programming to determine mating pairs. Offspring were simulated for each mating pair with equal numbers of offspring per pair and these offspring were the candidates for selection of parents of the next generation. Inbreeding and genetic gain for each generation were averaged over 25 replicates. Combined OPS and MIM led to a similar level of genetic gain to TS and RM, but inbreeding levels were around 75% lower than TS and RM after 15 generations. Results demonstrate that it would be possible to manage inbreeding over 15 generations within small breeding programmes comprised of 30 to 40 males and 30 to 40 females with the use of OPS and MIM. Selection on breeding values computed using Best Linear Unbiased Prediction (BLUP) with all individuals genotyped to obtain pedigree information resulted in an 11% increase in genetic merit and a 90% increase in the average inbreeding coefficient of progeny after 15 generations compared with selection on raw phenotype. Genetic evaluation strategies using BLUP wherein elite individuals by raw phenotype are genotyped to obtain parentage along with a range of different samples of remaining individuals did not increase genetic progress in comparison to selection on raw phenotype. When common environmental effects on full-sib families were simulated, performance of small breeding scheme designs was little affected. This was because the majority of selection must anyway be applied within family due to inbreeding constraints.

Keywords

aquaculturebreeding programmeinbreedingsimulation
Type
Breeding and genetics
Information
animal , Volume 7 , Issue 1 , January 2013 , pp. 1 - 10
Copyright
Copyright © The Animal Consortium 2012

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References

Belonsky, GM, Kennedy, BW 1988. Selection on individual phenotype and best linear unbiased predictor of breeding value in a closed swine herd. Journal of Animal Science 66, 1124–1131.Google Scholar
Bentsen, HB, Olesen, I 2002. Designing aquaculture mass selection programs to avoid high inbreeding rates. Aquaculture 204, 349–359.Google Scholar
Berg, P, Henryon, M 1998. A comparison of mating designs for inference on genetic parameters in fish. Proceedings of the 6th World Congress on Genetics Applied Livestock Production, vol. 27, Armidale, Australia, pp. 115–118.Google Scholar
Blonk, RJ, Komen, J, van Arendonk, JAM 2010. Minimizing genotyping in breeding programs with natural mating. Proceedings of the 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany, CD Rom Paper Number 0190.Google Scholar
Brown, RC, Woolliams, JA, McAndrew, BJ 2005. Factors influencing effective population size in commercial populations of gilthead seabream, Sparus aurata. Aquaculture 247, 219–225.Google Scholar
Caballero, A, Santiago, E, Toro, MA 1996. Systems of mating to reduce inbreeding in selected populations. Animal Science 62, 431–442.Google Scholar
Cécile, M, Blonk, R, Komen, H, de Koning, DJ, Haley, C, van Arendonk, J, Bovenhuis, H 2010. Comparison of selection methods for natural mating mass-spawning species. Proceedings of the 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany, CD Rom Paper Number 0717.Google Scholar
Coman, GJ, Henshall, JM 2010. Maintaining diversity and restricting inbreeding by optimized mating allocation for the giant tiger shrimp. Proceedings of the 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany, CD Rom Paper Number 0945.Google Scholar
Doyle, RW, Herbinger, CM 1994. The use of DNA fingerprinting for high-intensity within-family selection in fish breeding. Proceedings of the 5th World Congress on Genetics Applied to Livestock Production, vol. 19, Guelph, ON, Canada, pp. 364–371.Google Scholar
Dupont-Nivet, M, Haffray, P, Vandeputte, M 2010. Effect of culling on bias of BLUP estimates – case of fish species. Proceedings of the 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany, CD Rom Paper Number 0429.Google Scholar
Dupont-Nivet, M, Vandeputte, M, Haffray, P, Chevassus, B 2006. Effect of different mating designs in inbreeding, genetic variance and response to selection when applying individual selection in fish breeding programs. Aquaculture 252, 161–170.CrossRefGoogle Scholar
Falconer, DS, Mackay, TFC 1996. Introduction to quantitative genetics, 4th edition. Longman House, Essex, UK.Google Scholar
Fauvel, C, Suquet, M, Severe, A, Mylonas, CC, Papandroulakis, N 2008. Slow-release GnRHa treatment prevented atresia during vitellogenesis and induced ovulation of captive wreckfish (Polyprion americanus). Cybium 32 (2 suppl.), 191.Google Scholar
Gallardo, JA, Lhorente, JP, Neira, R 2010. The consequences of including non-additive effects on the genetic evaluations of harvest body weight in Coho salmon (Oncorhynchus kisutch). Genetics Selection Evolution 42, 19.Google Scholar
Garber, AF, Tosh, JJ, Fordham, SE, Hubert, S, Simpson, G, Symonds, JE, Robinson, JAB, Bowman, S, Trippel, EA 2010. Survival and growth traits at harvest of communally reared families of Atlantic cod (Gadus morhua). Aquaculture 307, 12–19.CrossRefGoogle Scholar
Gilmour, AR, Cullis, BR, Welham, SJ, Thompson, R 1999. ASREML reference manual. NSW Agriculture Bulletin No. 3.Google Scholar
Gjerdrem, T, Baranski, M 2009. Selective breeding in aquaculture: an introduction, 1st edition. Springer, London, UK.CrossRefGoogle Scholar
Gjerde, B, Gjøen, HM, Villanueva, B 1996. Optimum designs for fish breeding programmes with constrained inbreeding Mass selection for a normally distributed trait. Livestock Production Science 47, 59–72.CrossRefGoogle Scholar
Henderson, CR 1984. Applications of linear models in animal breeding, 2nd edition. University of Guelph, Guelph, Canada.Google Scholar
Herbinger, CM, Doyle, RW, Pitman, ER, Paquet, D, Mesa, KA, Morris, DB, Wright, JM, Cook, D 1995. DNA fingerprint based analysis of paternal and maternal effects on offspring growth and survival in communally reared rainbow trout. Aquaculture 137, 245–256.Google Scholar
Hill, WG 2000. Maintenance of quantitative genetic variation in animal breeding programmes. Livestock Production Science 63, 99–109.Google Scholar
Kinghorn, BP 2011. An algorithm for efficient constrained mate selection. Genetics Selection Evolution 43, 4.Google Scholar
Leitch, HW, Smith, C, Burnside, EB, Quinton, M 1994. Genetic response and inbreeding with different selection methods and mating designs for nucleus breeding programs of dairy cattle. Journal of Dairy Science 77, 1702–1718.CrossRefGoogle ScholarPubMed
Masuma, S, Takebe, T, Sakakura, Y 2010. A review of the broodstock management and larviculture of the Pacific northern bluefin tuna in Japan. Aquaculture 315, 2–8.Google Scholar
Meuwissen, THE 1997. Maximising the response of selection with a predefined rate of inbreeding. Journal of Animal Science 75, 934–940.Google Scholar
Meuwissen, THE, Luo, Z 1992. Computing inbreeding coefficients in large populations. Genetics Selection Evolution 24, 305–313.Google Scholar
Pong-Wong, R, Woolliams, JA 2007. Optimisation of contribution of candidate parents to maximise genetic gain and restricting inbreeding using semidefinite programming. Genetics Selection Evolution 39, 3–25.Google Scholar
Refstie, T, Steine, TA 1978. Selection experiments with salmon: III. Genetic and environmental sources of variation in length and weight of Atlantic salmon in the freshwater phase. Aquaculture 14, 221–234.Google Scholar
Robertson, A 1961. Inbreeding in artificial selection programmes. Genetics Research 2, 189–194.Google Scholar
Skaarud, A, Woolliams, JA, Gjøen, HM 2011. Strategies for controlling inbreeding in fish breeding programs; an applied approach using optimum contribution (OC) procedures. Aquaculture 311, 110–114.Google Scholar
Sonesson, AK, Meuwissen, THE 2000. Mating schemes for optimum contribution selection with constrained rates of inbreeding. Genetics Selection Evolution 32, 231–248.CrossRefGoogle ScholarPubMed
Toro, MA, Nieto, B, Salgado, C 1988. A note on minimization of inbreeding in small-scale selection programmes. Livestock Production Science 20, 317–323.Google Scholar
Villanueva, B, Woolliams, JA, Simm, G 1994. Strategies for controlling rates of inbreeding in MOET nucleus schemes for beef cattle. Genetics Selection Evolution 26, 517–535.Google Scholar
Winkelman, AM, Peterson, RG 1994. Heritabilities, dominance variation, common environmental effects and genotype by environment interactions for weight and length in chinook salmon. Aquaculture 125, 17–30.Google Scholar
Wray, NR, Simm, G 1990. The use of embryo transfer to accelerate genetic improvement in beef cattle. Proceedings of the 4th World Congress on Genetics Applied to Livestock Production, vol. 15, Edinburgh, UK, pp. 315–318.Google Scholar
Wright, S 1922. Coefficients of inbreeding and relationship. American Naturalist 56, 330–338.Google Scholar