Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-23T04:02:40.830Z Has data issue: false hasContentIssue false
  • English
  • Français

Correlated genetic trends for production and welfare traits in a mouse population divergently selected for birth weight environmental variability

Published online by Cambridge University Press:  12 May 2016

N. Formoso-Rafferty ,
I. Cervantes ,
N. Ibáñez-Escriche  and
J. P. Gutiérrez
N. Formoso-Rafferty
Affiliation:
Departamento de Producción Animal, Facultad de Veterinaria, UCM, Avda, Puerta de Hierro s/n, 28040 Madrid, Spain
I. Cervantes
Affiliation:
Departamento de Producción Animal, Facultad de Veterinaria, UCM, Avda, Puerta de Hierro s/n, 28040 Madrid, Spain
N. Ibáñez-Escriche
Affiliation:
Genètica i Millora Animal – Centre IRTA_Lleida, 25198 Lleida, Spain
J. P. Gutiérrez*
Affiliation:
Departamento de Producción Animal, Facultad de Veterinaria, UCM, Avda, Puerta de Hierro s/n, 28040 Madrid, Spain
*
†E-mail: [email protected]
Get access

Abstract

The objective of this work was to study the changes that, selecting for environmental variability of birth weight (BW), could bring to other interesting traits in livestock such as: survivability at weaning (SW), litter size (LS) and weaning weight (WW), their variability assessed from standard deviations of LS, standard deviation of WW (SDWW) and also the total litter weight at birth (TLBW) and total litter weight at weaning. Data were registered after eight generations of a divergent selection experiment for BW environmental variability in mice. Genetic parameters and phenotypic and genetic evolution were assessed using linear homoscedastic and heteroscedastic models in which the traits were attributed to the female, except BW and WW that were in some models also attributed to the pup. Genetic correlation between the trait and variability levels was −0.81 for LS and −0.33 for WW. Clear divergent phenotypic trends were observed between lines for LS, WW and SDWW. Although animals were heavier in the high line, TLBW and at weaning was greater in the low line. Despite the negative genetic correlation that was obtained, SDWW was also higher in the high line. Heritabilities were 0.21 and 0.06, respectively, for LS and SW. Both phenotypic and genetic trends showed clear superiority of the low line over the high line for these traits, but inferior for WW. Heteroscedastic model performed similar to the homoscedastic model when there was enough information. Considering LS and survival, the low line was preferred from a welfare point of view, but its superiority from the productivity perspective was not clear. Robustness seemed higher as shown by a low variation and having a benefit to the animal welfare, but this still remains unclear. It was concluded that low variation benefits the welfare of animals.

Keywords

canalisationrobustnessgenetic trendsmice
Type
Research Article
Information
animal , Volume 10 , Issue 11 , November 2016 , pp. 1770 - 1777
Copyright
© The Animal Consortium 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bayon, Y, Fuente, LF and San Primitivo, F 1987. Direct and correlated responses to selection for large and small 6-week body weight in mice. Genetics Selection Evolution 19, 445–458.Google Scholar
Bolet, G, Gaffeau, H, Joly, T, Theau-Clement, M, Faheres, J, Hurtaud, J and Bodin, L 2007. Genetic homogenisation of birth weight in rabbits: indirect selection response for uterine horn characteristics. Livestock Science 111, 28–32.CrossRefGoogle Scholar
Cervantes, I, Gutiérrez, JP, Fernández, I and Goyache, F 2010. Genetic relationships among calving ease, gestation length, and calf survival to weaning in the Asturiana de los Valles beef cattle breed. Journal of Animal Science 88, 96–101.Google Scholar
Damgaard, L, Rydhmer, L, Lovendahl, P and Grandinson, K 2003. Genetic parameters for within-litter variation in piglet birth weight and change in within-litter variation during suckling. Journal of Animal Science 81, 604–610.CrossRefGoogle ScholarPubMed
Eisen, EJ 1978. Single-trait and antagonistic index selection for litter size and body weight in mice. Genetics 88, 781–811.CrossRefGoogle ScholarPubMed
Fernández, J, Moreno, A, Gutiérrez, JP, Nieto, B, Piqueras, P and Salgado, C 1998. Direct and correlated selection response for litter size and litter weight at birth in the first parity in mice. Livestock Production Science 53, 217–223.CrossRefGoogle Scholar
Formoso-Rafferty, N, Cervantes, I, Ibáñez-Escriche, N and Gutiérrez, JP 2015. Genetic control of the environmental variance for birth weight in seven generations of a divergent selection experiment in mice. Journal of Animal Breeding and Genetics, doi:10.1111/jbg.12174.Google Scholar
García, ML, Argente, MJ, Muelas, R, Birlanga, V and Blasco, A 2012. Effect of divergent selection for residual variance of litter size on health status and welfare. Proceedings of the 10th World Rabbit Congress, 3–6 September 2012, Sharm El- Sheikh, Egypt, pp. 103–106.Google Scholar
García, M, David, I, Garreau, H, Ibáñez-Escriche, N, Mallard, J, Masson, JP, Pommeret, D, Robert-Granié, C and Bodin, L 2009. Comparisons of three models for canalising selection or genetic robustness. Proceedings of the 60th Annual Meeting of European Association for Animal Production, August 2009, Barcelona, Spain, 599pp.Google Scholar
Gacía, ML, and Baselga, M 2002. Estimation of correlated response on growth traits to selection in litter size of rabbits using a cryopreserved control population and genetic trends. Livestock Production Science 78, 91–98.Google Scholar
Garreau, H, Bolet, G, Larzul, C, Robert-Granie, C, Saleil, G, SanCristobal, M and Bodin, L 2008. Results of four generations of a canalising selection for rabbit birth weight. Livestock Science 119, 55–62.Google Scholar
Gutiérrez, JP, Nieto, B, Piqueras, P, Ibáñez-Escriche, N and Salgado, C 2006. Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genetics Selection Evolution 38, 445–462.Google Scholar
Hill, WG and Caballero, A 2000. Artificial selection experiments. Annual Review of Ecology and Systematics 23, 287–310.Google Scholar
Hill, WG and Mulder, HA 2010. Genetic analysis of environmental variation. Genetics Research 92, 381–395.Google Scholar
Högberg, A and Rydhmer, L 2000. A genetic study of piglet growth and survival. Acta Agriculturae Scandinavica, Section A. Animal Science 50, 300–303.Google Scholar
Ibáñez-Escriche, N, García, M and Sorensen, D 2010. GSEVM v.2: MCMC software to analyze genetically structured environmental variance models. Journal of Animal Breedings and Genetics 127, 249–251.CrossRefGoogle ScholarPubMed
Ibáñez-Escriche, N, Moreno, A, Nieto, B, Piqueras, P, Salgado, C and Gutiérrez, JP 2008. Genetic parameters related to environmental variability of weight traits in a selection experiment for weight gain in mice; signs of correlated canalised response. Genetics Selection Evolution 40, 279–293.Google Scholar
Jaffrezic, F, White, IMS, Thompson, R and Hill, WG 2000. A link function approach to model heterogeneity of residuals variances over time in lactation curve analyses. Journal of Dairy Science 83, 1089–1093.CrossRefGoogle ScholarPubMed
Larzul C, Ducrocq V, Tudela F, Juin H and Garreau H 2014. The length of productive life can be modified through selection: An experimental demonstration in the rabbit. Journal of Animal Science 92, 2395–2401.CrossRefGoogle Scholar
Legarra, A 2008. TM Threshold Model. Retrieved on 16 July 2015 from http://acteon.webs.upv.es/.Google Scholar
Mesa, H, Safranski, TJ, Cammack, KM, Weaber, RL and Lamberson, WR 2006. Genetic and phenotypic relationships of farrowing and weaning survival to birth and placental weights in pigs. Journal of Animal Science 84, 32–40.Google Scholar
Moreno, A, Ibáñez-Escriche, N, Salgado, C, Nieto, B and Gutiérrez, JP 2011. Correlated genetic trend in the environmental variability of weight traits in mice. Livestock Science 148, 189–195.Google Scholar
Mormede, P and Terenina, E 2012. Molecular genetics of the adrenocortical axis and breeding for robustness. Domestic Animal Endocrinology 43, 116–131.Google Scholar
Perrier, G 2003. Influence de l’homogénéité de la portée sur la croissance et la viabilité des lapereaux de faible poids à la naissance. Proceedings of the 10èmes Journées de la recherche cunicole, 19–20 November 2003, Paris, France, pp. 119–122.Google Scholar
Poigner, J, Szendrö, ZS, Levai, A, Radnai, I and Biro-Nemeth, E 2000. Effect of birth weight and litter size on growth and mortality in rabbit. World Rabbit Science 8, 103–109.Google Scholar
Pun, A, Cervantes, I, Nieto, B, Salgado, C, Pérez-Cabal, MA, Ibáñez-Escriche, N and Gutiérrez, JP 2013. Genetic parameters for birth weight environmental variability in mice. Journal of Animal Breeding and Genetics 130, 404–414.CrossRefGoogle ScholarPubMed
SanCristobal-Gaudy, M, Elsen, J, Bodin, L and Chevalet, C 1998. Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genetics Selection Evolution 30, 423–451.Google Scholar
Wolf, J, Žakova, E and Groeneveld, E 2008. Within-litter variation of birth weight in hyperprolific Czech Large White sows and its relation to litter size traits, stillborn piglets and losses until weaning. Livestock Science 115, 195–205.Google Scholar
Zomeño, C, Blasco, A and Hernández, P 2013. Divergent selection for intramuscular fat content in rabbits. I. Divergent selection for intramuscular fat content in rabbits. Journal of Animal Science 91, 4526–4531.Google Scholar