Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-26T18:03:01.190Z Has data issue: false hasContentIssue false

Genetic variability of functional longevity in five rabbit lines

Published online by Cambridge University Press:  22 January 2020

A. G. EL Nagar*
Affiliation:
Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera S/N, 46022Valencia, Spain Department of Animal Production, Faculty of Agriculture at Moshtohor, Benha University, 13736Benha, Egypt
J. P. Sánchez
Affiliation:
Genetica I Millora Animal, Institut de Recerca I Tecnologia Agroalimentàries, Torre Marimon S/N, 08140 Caldes De Montbui, Barcelona, Spain
M. Ragab
Affiliation:
Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera S/N, 46022Valencia, Spain Poultry Production Department, Kafer El-Sheikh University, 33516Kafer El-Sheikh, Egypt
C. Mínguez
Affiliation:
Departamento de Producción Animal y Salud Pública, Facultad de Veterinaria y Ciencias Experimentales, Universidad Católica de Valencia San Vicente Martir, Guillem de Castro 94, 46001Valencia, Spain
M. Baselga
Affiliation:
Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera S/N, 46022Valencia, Spain
*
Get access

Abstract

The objectives of this study were to analyse the differences in the genetic determination of functional longevity in five Spanish lines of rabbits and to check how different systematic factors might affect this genetic determination. Four of the lines were maternal (lines A, V, H and LP), these lines were established selecting base generation animals according to different criteria, but in the subsequent generations all of them were selected for litter size at weaning. The other is the paternal line R, this line was constituted by selecting animals with an outstanding daily growth rate. The trait analysed, length of productive life, was the time in days between the date of the first positive pregnancy test and the date of culling or death of a doe. Four models extended from the Cox proportional hazard model were used to analyse data of each line separately and jointly. The complete model (Model 1) included the fixed effect of year-season (YS) combination, positive palpation order (OPP), that is, reproductive cycle, physiological status of the doe (PS) at service and number of kits born alive (NBA) in each kindling as time-dependent factors. The inbreeding coefficient was fitted as a continuous covariate and the animal’s additive genetic effect was also fitted to the model (Model 1). The other models were identical to Model 1 but excluding OPP (Model 2) or PS (Model 3) or NBA (Model 4), which were explored to assess the consequence on additive variance estimates of not correcting for these animal-dependent factors. Estimated effective heritabilities of longevity were 0.07 ± 0.03, 0.03 ± 0.02, 0.14 ± 0.09, 0.05 ± 0.04, 0.02 ± 0.01 and 0.04 ± 0.01 for lines A, V, H, LP, R and for the merged data set, respectively. Removing the PS from the model led to an increase in the estimated additive genetic variance in all lines (0.17 ± 0.05, 0.05 ± 0.03, 0.29 ± 0.19, 0.29 ± 0.20, 0.07 ± 0.04 and 0.05 ± 0.02 for lines A, V, H, LP, R and the merged data set, respectively). The highest hazard of death and/or culling was observed during the first two parities and decreased as the order of parity progressed. Does non-pregnant-non-lactating had the highest risk of death or culling. The does that had zero kits born alive incurred the highest risk, and this risk decreased as the NBA increased. In conclusion, the consideration of longevity as selection criterion for the studied rabbit lines is not recommended.

Type
Research Article
Copyright
© The Animal Consortium 2020

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

Blasco, A 2001. The Bayesian controversy in animal breeding. Journal of Animal Science 79, 20232046.CrossRefGoogle ScholarPubMed
Boyle, L, Leonard, FC, Lynch, B and Brophy, P 1998. Sow culling patterns and sow welfare. Irish Veterinary Journal 51, 354357.Google Scholar
Casellas, J, Varona, L, Ibáñez-Escriche, N, Quintanilla, R and Noguera, JL 2008. Skew distribution of founder-specific inbreeding depression effects on the longevity of Landrace sows. Genetics Research Cambridge 90, 499508.CrossRefGoogle ScholarPubMed
Cifre, P, Baselga, M, Gacia-Ximenez, F and Vicente, J 1998. Performance of hyperprolific rabbit line. I. Litter size traits. Journal of Animal Breeding and Genetics 115, 131.CrossRefGoogle Scholar
EL Nagar, AG 2015. Genetic analysis of longevity in specialized lines of rabbits. PhD thesis, Universitat Politècnica de València, Valencia, Spain.Google Scholar
Engblom, L, Lundeheim, N, Schneider, MD, Dalin, AM and Andersson, K 2009. Genetics of crossbred sow longevity. Animal 3, 783790.CrossRefGoogle ScholarPubMed
Estany, J, Baselga, M, Blasco, A and Camacho, J 1989. Mixed model methodology for the estimation of genetic response to selection in litter size of rabbits. Livestock Production Science 21, 6775.CrossRefGoogle Scholar
Estany, J, Camacho, J, Baselga, M and Blasco, A 1992. Selection response of growth rate in rabbits for meat production. Genetics Selection Evolution 24, 527537.CrossRefGoogle Scholar
Fernández, EN, Sánchez, JP, Martíez, R, Legarra, A and Baselga, M 2017. Role of inbreeding depression, non-inbred dominance deviations and random year-season effect in genetic trends for prolificacy in closed rabbit lines. Journal of Animal Breeding and Genetics 134, 441452.CrossRefGoogle ScholarPubMed
Friendship, RM, Wilson, MR, Almond, GW, McMillan, I, Hacker, RR, Pieper, R and Swaminathan, SS 1986. Sow wastage: reasons for and effect on productivity. Canadian Journal of Veterinary Research 50, 205208.Google ScholarPubMed
García-Ximénez, F, Vicente, JS, Cifre, P and Baselga, M 1996. Foundation of a maternal rabbit line using hysterectomy and embryo cryopreservation. In Proceedings of the 6th World Rabbit Congress, 9–12 July 1996, Toulouse, France, pp. 285288. Retrieved from https://world-rabbit-science.com/WRSA-Proceedings/Congress-1996-Toulouse/Papers-pdf/05-Genetics/GARCIA-XIMENEZ.pdfGoogle Scholar
Garreau, H, Larzul, C and Ducrocq, V 2001. Analyse de longévité de la souche de lapins INRA 1077. In Proceedings of the 9émes Journées de la Recherche Cunicole, 28–29 Novembre 2001, Paris, France, pp. 217220. Retrieved from http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=14178974Google Scholar
Geweke, J 1992. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In Bayesian statistics 4 (ed. Bernardo, JM, Berger, JO, Dawid, AP and Smith, AFM), pp. 169193. Oxford University Press, Oxford, UK.Google Scholar
Gilks, WR and Wild, P 1992. Adaptive rejection sampling for Gibbs sampling. Applied Statistics 41, 337348.CrossRefGoogle Scholar
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, 23952401.CrossRefGoogle ScholarPubMed
Lenoir, G, Maupin, M, Leloire, C and Garreau, H 2013. Analyse de la longévité des lapines d’une lignée commerciale. In Proceedings of the 15èmes Journées de la Recherche Cunicole, 19–20 Novembre 2013, Le Mans, France, pp. 181184. Retrieved from http://www.cuniculture.info/Docs/Magazine/Magazine2013/fichiers-pdf-JRC/R07-Lenoir.pdfGoogle Scholar
Lucia, T, Dial, GD and Marsh, WE 1996. Patterns of female removal. I. Lifetime productivity for reproduction and performance-related culls. In Proceedings of the 14th International Pig Veterinary Society, 7–10 July 1996, Bologna, Italy, p. 540. https://lib.ugent.be/catalog/rug01:000400386Google Scholar
Mészáros, G, Pálos, J, Ducrocq, V and Sölkner, J 2010. Heritability of longevity in Large White and Landrace sows using continuous time and grouped data models. Journal of Genetics Selection Evolution 42, 113.Google ScholarPubMed
Piles, M, Garreau, H, Rafel, O, Larzul, C, Ramon, J and Ducrocq, V 2006. Survival analysis in two lines of rabbits selected for reproductive traits. Journal of Animal Science 84, 16581665.CrossRefGoogle ScholarPubMed
Plummer, M, Best, N, Cowles, K and Vines, K 2006. CODA: Convergence diagnosis and output analysis for MCMC. R News 6, 711.Google Scholar
Ramon, J and Rafel, O 2002. Diez años de gestión global en España. In Proceedings of the 2th Congreso Internacional de Producción y Sanidad Animal, 5–8 November 2002, Expoaviga, Barcelona, Spain, pp. 113117.Google Scholar
Rinaldo, D and Bolet, G 1988. Effect of selection for litter size at weaning on reproductive life of female rabbits. In Proceedings of the 4th World Rabbit Congress, 10–14 October 1988, Budapest, Hungary, pp. 269275.Google Scholar
Rosell, JM 2003. Health status of commercial rabbitries in the Iberian Peninsula. A practitioners study. World Rabbit Science 11, 157169.Google Scholar
Sánchez, JP, Baselga, M, Peiró, R and Silvestre, MA 2004. Analysis of factors influencing longevity of rabbit does. Livestock Production Science 90, 227234.CrossRefGoogle Scholar
Sánchez, JP, Baselga, M and Ducrocq, V. 2006a. Genetic and environmental correlations between longevity and litter size in rabbits. Journal of Animal Breeding and Genetics 123, 180185.CrossRefGoogle ScholarPubMed
Sánchez, JP, Korsgaard, IR, Damgaard, LH and Baselga, M 2006b. Analysis of rabbit doe longevity using a semiparametric log-Normal animal frailty model with time-dependent covariates. Genetics Selection Evolution 38, 281295.CrossRefGoogle ScholarPubMed
Sánchez, JP, Theilgaard, P, Mínguez, C and Baselga, M 2008. Constitution and evaluation of a long-lived productive rabbit line. Journal of Animal Science 86, 515525.CrossRefGoogle ScholarPubMed
Sánchez, JP, de la Fuente, LF and Rosell, JM 2012. Health and body condition of lactating females on rabbit farms. Journal of Animal Science 90, 23532361.CrossRefGoogle ScholarPubMed
Serenius, T and Stalder, KJ 2004. Genetics of length of productive life and lifetime prolificacy in the Finnish Landrace and Large White pig populations. Journal of Animal Science 82, 31113117.CrossRefGoogle ScholarPubMed
Serenius, T, Stalder, KJ and Puonti, M 2006. Impact of dominance effects on sow longevity. Journal of Animal Breeding and Genetics 123, 355361.CrossRefGoogle ScholarPubMed
Sorensen, D and Gianola, D 2002. Likelihood, Bayesian, and MCMC methods in quantitative genetics. Springer Science and Business Media, New York, USA.CrossRefGoogle Scholar
Tarrés, J, Bidanel, JP, Hofer, A and Ducrocq, V 2006. Analysis of longevity and exterior traits on Large White sows in Switzerland. Journal of Animal Science 84, 29142924.CrossRefGoogle ScholarPubMed
Tudela, F, Hurtaud, J, Garreau, H and Rochambeau, H 2003. Comparaison des performances zootechniques de femelles parentales issues d’une souche témoin et d’une souche sélectionnée sur la productivité numérique. In Proceedings of the 10émes Journées de la Recherche Cunicole, 19–20 November, Paris, France, pp. 5356. http://www.hypharm.fr/media/tudela_jrc_2003__056604300_1453_06092016.pdfGoogle Scholar
Yazdi, M, Rydhmer, L, Ringmar-Cederberg, E, Lundeheim, N and Johansson, K 2000. Genetic study of longevity in Swedish Landrace sows. Livestock Production Science 63, 255264.CrossRefGoogle Scholar
Yazdi, MH, Visscher, PM, Ducrocq, V and Thompson, R 2002. Heritability, reliability of genetic evaluations and response to selection in proportional hazard models. Journal of Dairy Science 85, 15631577.CrossRefGoogle ScholarPubMed