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Bayesian analysis reveals the influence of maternal effect on pre-weaning body weights in Landlly piglets

Published online by Cambridge University Press:  28 April 2022

Sheikh Firdous Ahmad
Affiliation:
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India
Gyanendra Kumar Gaur*
Affiliation:
Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India
Snehasmita Panda
Affiliation:
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India
Anuj Chauhan
Affiliation:
Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India
Triveni Dutt
Affiliation:
Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India
Bharat Bhushan
Affiliation:
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India
*
Author for correspondence: Gyanendra Kumar Gaur. Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, UP, India. E-mail: gyanendrakg@gmail.com

Summary

The present study was undertaken to estimate the (co)variance components and genetic parameters of body weights recorded in Landlly piglets from birth to weaning at weekly intervals (w0 to w6). The data pertained to body weights of 2462 piglets, born to 91 sires and 159 dams across different generations during a 7-year period from 2014 to 2020. Five animal models (I–V), differentiated by inclusion or exclusion of maternal effects with or without covariance between maternal and direct genetic effects, were fitted on the data using the Bayesian algorithm. The analyses were implemented by Gibbs sampling in the BLUPF90 program and Markov chain Monte Carlo (MCMC) methodology was used to draw samples of posterior distribution pertaining to (co)variance components. Based on deviance information criteria (DIC), model V with inclusion of direct additive genetic, direct maternal genetic and permanent environmental effect of dam as random factors along with covariance between direct additive and maternal effects best fitted the data on pre-weaning traits (w0 to w5). Whereas, model I incorporating only the direct additive genetic effect best fitted the weaning weight (w6) data in Landlly piglets. The posterior mean estimates of direct heritability under the best models for W0 to W6 were 0.13, 0.19, 0.29, 0.13, 0.26, 0.32 and 0.46, respectively. Inclusion of the maternal component helped in better partitioning of variance for different body weights in Landlly piglets. The maternal heritability ranged from 0.06 to 0.14, while the litter heritability ranged from 0.11 to 0.15 for pre-weaning weights (W0 to W5) under the best-fit models. The influence of maternal environment was greater than maternal genetic effect from birth to 4th week of age. The results implied that variations in body weight of Landlly pigs were genetically controlled to moderate levels (especially w2 and w4) with contributions from direct additive and maternal genotype that can be exploited by designing efficient breeding programmes.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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References

Ahmad, S. F., Khan, N. N., Chakraborty, D., Rather, M. A., Shanaz, S., Alam, S. and Ganai, N. A. (2021). Estimation of (co)variance components and genetic parameters of fibre traits in Rambouillet sheep using multi-trait analysis. Tropical Animal Health and Production, 53(1), 190. doi: 10.1007/s11250-021-02637-y CrossRefGoogle ScholarPubMed
Alves, K., Schenkel, F. S., Brito, L. F. and Robinson, A. (2018). Estimation of direct and maternal genetic parameters for individual birth weight, weaning weight, and probe weight in Yorkshire and Landrace pigs. Journal of Animal Science, 96(7), 25672578. doi: 10.1093/jas/sky172 CrossRefGoogle ScholarPubMed
Belkacemi, L., Nelson, D. M., Desai, M. and Ross, M. G. (2010). Maternal undernutrition influences placental-fetal development. Biology of Reproduction, 83(3), 325331. doi: 10.1095/biolreprod.110.084517 CrossRefGoogle ScholarPubMed
Beydoun, H. and Saftlas, A. F. (2008). Physical and mental health outcomes of prenatal maternal stress in human and animal studies: a review of recent evidence. Paediatric and Perinatal Epidemiology, 22(5), 438466. doi: 10.1111/j.1365-3016.2008.00951.x CrossRefGoogle ScholarPubMed
Canario, L., Lundgren, H., Haandlykken, M. and Rydhmer, L. (2010). Genetics of growth in piglets and the association with homogeneity of body weight within litters. Journal of Animal Science, 88(4), 12401247. doi: 10.2527/jas.2009–2056 CrossRefGoogle ScholarPubMed
Carneiro, J. M., De Assis, G.M. L., Euclydes, R. F., Torres, R. de A. and Lopes, P. S. (2007). Estimation of variance components using Bayesian and frequentist inferences considering simulated data under heterogeneity of variance. Revista Brasileira de Zootecnia, 36(5 suppl.), 15391548. doi: 10.1590/s1516-35982007000700012 Google Scholar
Chimonyo, M. and Dzama, K. (2007). Estimation of genetic parameters for growth performance and carcass traits in Mukota pigs. Animal, 1(3), 317323. doi: 10.1017/S1751731107661849 CrossRefGoogle ScholarPubMed
Chimonyo, M., Dzama, K. and Bhebhe, E. (2008). Genetic determination of mothering ability and piglet growth in indigenous Mukota sows of Zimbabwe. Livestock Science, 113(1), 7480. doi: 10.1016/j.livsci.2007.02.014 CrossRefGoogle Scholar
Collier, C. T., Williams, P. N., Carroll, J. A., Welsh, T. H. and Laurenz, J.C. (2011). Effect of maternal restraint stress during gestation on temporal lipopolysaccharide-induced neuroendocrine and immune responses of progeny. Domestic Animal Endocrinology, 40(1), 4050. doi: 10.1016/j.domaniend.2010.08.005 CrossRefGoogle ScholarPubMed
Couret, D., Jamin, A., Kuntz-Simon, G., Prunier, A. and Merlot, E. (2009). Maternal stress during late gestation has moderate but long-lasting effects on the immune system of the piglets. Veterinary Immunology and Immunopathology, 131(1–2), 1724. doi: 10.1016/j.vetimm.2009.03.003 CrossRefGoogle ScholarPubMed
Dong, L., Tan, C., Cai, G., Li, Y., Wu, D. and Wu, Z. (2020). Estimates of variance components and heritability using different animal models for growth, backfat, litter size, and healthy birth ratio in large white pigs. Canadian Journal of Animal Science, 100(2), 330336. doi: 10.1139/cjas-2019-0136 CrossRefGoogle Scholar
Du, W.G. (2006). Phenotypic plasticity in reproductive traits induced by food availability in a lacertid lizard, Takydromus septentrionalis . Oikos, 112(2), 363369. doi: 10.1111/j.0030–1299.2006.13552.x CrossRefGoogle Scholar
Dufrasne, M., Misztal, I., Tsuruta, S., Holl, J., Gray, K. A. and Gengler, N. (2013). Estimation of genetic parameters for birth weight, preweaning mortality, and hot carcass weight of crossbred pigs. Journal of Animal Science, 91(12), 55655571. doi: 10.2527/jas.2013–6684 CrossRefGoogle ScholarPubMed
Dufrasne, M., Wavreille, J., Piedboeuf, M. and Gengler, N. (2014). Genetic parameters for individual birth weight, weaning weight and final weight of crossbred pigs from Piétrain boars. 10th World Congress of Genetics Applied to Livestock Production. Available at: https://orbi.uliege.be/handle/2268/171715 Google Scholar
Ekiz, B., Özcan, M., Yilmaz, A. and Ceyhan, A. (2004). Estimates of genetic parameters for direct and maternal effects with six different models on birth and weaning weights of Turkish merino lambs. Turkish Journal of Veterinary and Animal Sciences, 28(2), 383389.Google Scholar
Feldpausch, J. A., Jourquin, J., Bergstrom, J. R., Bargen, J. L., Bokenkroger, C. D., Davis, D. L., Gonzalez, J. M., Nelssen, J. L., Puls, C. L., Trout, W. E. and Ritter, M.J. (2019). Birth weight threshold for identifying piglets at risk for preweaning mortality. Translational Animal Science, 3(2), 633640. doi: 10.1093/tas/txz076 CrossRefGoogle ScholarPubMed
Godfrey, K. M. and Barker, D.J. (2001). Fetal programming and adult health. Public Health Nutrition, 4(2b), 611624. doi: 10.1079/phn2001145 CrossRefGoogle ScholarPubMed
Grandinson, K., Lund, M. S., Rydhmer, L. and Strandberg, E. (2002). Genetic parameters for the piglet mortality traits crushing, stillbirth and total mortality, and their relation to birth weight. Acta Agriculturae Scandinavica – Section A: Animal Science, 52(4), 167173. doi: 10.1080/090647002762381041 CrossRefGoogle Scholar
Hawe, S. J., Scollan, N., Gordon, A. and Magowan, E. (2020). Impact of sow lactation feed intake on the growth and suckling behavior of low and average birthweight pigs to 10 weeks of age. Translational Animal Science, 4(2), 655665. doi: 10.1093/TAS/TXAA057 CrossRefGoogle ScholarPubMed
Hermesch, S., Luxford, B. G. and Graser, H.-U. (2001). Estimation of variance components for individual piglet weights at birth and 14 days of age. Proceedings of the Association for the Advancement of Animal Breeding and Genetics, 14, 207210.Google Scholar
Hossein-Zadeh, N.G. (2017). Estimates of genetic parameters and genetic trends for production and reproduction traits in Iranian buffaloes (Bubalus bubalis). Animal Production Science, 57(2), 216222. doi: 10.1071/AN15370 CrossRefGoogle Scholar
Ilatsia, E., Githinji, M., Muasya, T., Okeno, T. and Kahi, A. (2008). Genetic parameter estimates for growth traits of large white pigs in Kenya. South African Journal of Animal Science, 38(3), 166173. doi: 10.4314/sajas.v38i3.4131 CrossRefGoogle Scholar
Jarvis, S., Moinard, C., Robson, S. K., Baxter, E., Ormandy, E., Douglas, A. J., Seckl, J. R., Russell, J. A. and Lawrence, A. B. (2006). Programming the offspring of the pig by prenatal social stress: neuroendocrine activity and behaviour. Hormones and Behavior, 49(1), 6880. doi: 10.1016/j.yhbeh.2005.05.004 CrossRefGoogle ScholarPubMed
Kaufmann, D., Hofer, A., Bidanel, J. P. and Künzi, N. (2000). Genetic parameters for individual birth and weaning weight and for litter size of large white pigs. Journal of Animal Breeding and Genetics, 117(2), 121128. doi: 10.1111/j.1439-0388.2000x.00238.x CrossRefGoogle Scholar
Lôbo, A. M. B. O., Lôbo, R. N. B., Paiva, S. R., De Oliveira, S. M. P. and Facó, O. (2009). Genetic parameters for growth, reproductive and maternal traits in a multibreed meat sheep population. Genetics and Molecular Biology, 32(4), 761770. doi: 10.1590/S1415–47572009005000080 CrossRefGoogle Scholar
Lopes, F. B., Ferreira, J. L., Lobo, R. B. and Rosa, G.J.M. (2017). Bayesian analyses of genetic parameters for growth traits in Nellore cattle raised on pasture. Genetics and Molecular Research, 16(3), gmr16039609. doi: 10.4238/gmr16039606 CrossRefGoogle ScholarPubMed
Lynch, S.M. (2007). Evaluating Markov Chain Monte Carlo Algorithms and Model Fit. In Introduction to Applied Bayesian Statistics and Estimation for Social Scientists (pp. 131164). Springer, New York, NY. doi: 10.1007/978-0-387-71265-9_6 CrossRefGoogle Scholar
Magnabosco, C. D. U., Lôbo, R. B. and Famula, T. R. (2000). Bayesian inference for genetic parameter estimation on growth traits for Nelore cattle in Brazil, using the Gibbs sampler. Journal of Animal Breeding and Genetics, 117(3), 169188. doi: 10.1046/j.1439-0388.2000.00248.x CrossRefGoogle Scholar
Malhado, C. H. M., Mendes Malhado, A. C., Amorim Ramos, A., Souza Carneiro, P. L., Siewerdt, F. and Pala, A. (2012). Genetic parameters by Bayesian inference for dual purpose Jaffarabadi buffaloes. Archives Animal Breeding, 55(6), 567576. doi: 10.5194/aab-55-567-2012 CrossRefGoogle Scholar
Mandal, A., Neser, F.W. C., Rout, P. K., Roy, R. and Notter, D.R. (2006). Estimation of direct and maternal (co)variance components for pre-weaning growth traits in Muzaffarnagari sheep. Livestock Science, 99(1), 7989. doi: 10.1016/j.livprodsci.2005.06.001 CrossRefGoogle Scholar
Mondal, S. K., Kumar, A., Dubey, P. P., Sivamani, B. and Dutt, T. (2014). Estimation of variance and genetic parameters for pre-weaning weights of individual Landrace × Desi synthetic piglets. Journal of Applied Animal Research, 42(3), 338344. doi: 10.1080/09712119.2013.875901 CrossRefGoogle Scholar
Mosnier, E., Etienne, M., Ramaekers, P. and Père, M. C. (2010). The metabolic status during the peri partum period affects the voluntary feed intake and the metabolism of the lactating multiparous sow. Livestock Science, 127(2–3), 127136. doi: 10.1016/j.livsci.2009.06.023 CrossRefGoogle Scholar
Nguyen, T. Q., Knap, P. W., Simm, G., Edwards, S. A. and Roehe, R. (2021). Evaluation of direct and maternal responses in reproduction traits based on different selection strategies for postnatal piglet survival in a selection experiment. Genetics Selection Evolution, 53(1), 116. doi: 10.1186/s12711-021-00612-7 CrossRefGoogle Scholar
Okon, B., Ngere, L. and Ibom, L. (2009). Estimates of genetic parameters of body weights of different classes of pigs. Journal of Agriculture, Forestry and the Social Sciences, 6(1). doi: 10.4314/joafss.v6i1.48633 CrossRefGoogle Scholar
Otten, W., Kanitz, E., Couret, D., Veissier, I., Prunier, A. and Merlot, E. (2010). Maternal social stress during late pregnancy affects hypothalamic-pituitary-adrenal function and brain neurotransmitter systems in pig offspring. Domestic Animal Endocrinology, 38(3), 146156. doi: 10.1016/j.domaniend.2009.09.002 CrossRefGoogle ScholarPubMed
Peltoniemi, O. A. T., Björkman, S. and Oliviero, C. (2016). Parturition effects on reproductive health in the gilt and sow. Reproduction in Domestic Animals, 51, 3647. doi: 10.1111/rda.12798 CrossRefGoogle ScholarPubMed
Penasa, M., Cecchinato, A., Dal Zotto, R., Blair, H. T., López-Villalobos, N. and Bittante, G. (2012). Direct and maternal genetic effects for body weight and price of calves sold for veal production. Journal of Animal Science, 90(10), 33853391. doi: 10.2527/jas.2011–4487 CrossRefGoogle Scholar
Prince, L. L. L., Gowane, G. R., Chopra, A. and Arora, A.L. (2010). Estimates of (co)variance components and genetic parameters for growth traits of Avikalin sheep. Tropical Animal Health and Production, 42(6), 10931101. doi: 10.1007/s11250-010-9530-5 CrossRefGoogle ScholarPubMed
Quiniou, N., Dagorn, J. and Gaudré, D. (2002). Variation of piglets’ birth weight and consequences on subsequent performance. Livestock Production Science, 78(1), 6370. doi: 10.1016/S0301-6226(02)00181-1 CrossRefGoogle Scholar
Rehfeldt, C., Stabenow, B., Pfuhl, R., Block, J., Nurnberg, G., Otten, W., Metges, C. C. and Kalbe, C. (2012). Effects of limited and excess protein intakes of pregnant gilts on carcass quality and cellular properties of skeletal muscle and subcutaneous adipose tissue in fattening pigs. Journal of Animal Science, 90(1), 184196. doi: 10.2527/jas.2011–4234 CrossRefGoogle ScholarPubMed
Report, L. C. (2019). Animal Husbandry Statistics. Department of Animal husbandry and Dairying, MoA, GOI.Google Scholar
Roehe, R. (1999). Genetic determination of individual birth weight and its association with sow productivity traits using Bayesian analyses. Journal of Animal Science, 77(2), 330343. doi: 10.2527/1999.772330x CrossRefGoogle ScholarPubMed
Silva, F. F., Viana, J. M. S., Faria, V. R. and de Resende, M. D. V. (2013). Bayesian inference of mixed models in quantitative genetics of crop species. Theoretical and Applied Genetics, 126(7), 17491761. doi: 10.1007/s00122-013-2089-6 CrossRefGoogle Scholar
Solanes, F. X., Grandinson, K., Rydhmer, L., Stern, S., Andersson, K. and Lundeheim, N. (2004). Direct and maternal influences on the early growth, fattening performance, and carcass traits of pigs. Livestock Production Science, 88(3), 199212. doi: 10.1016/j.livprodsci.2003.12.002 CrossRefGoogle Scholar
Sorensen, D. and Gianola, D. (2002). Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics. Springer New York. doi: 10.1007/B98952 CrossRefGoogle Scholar
Spiegelhalter, D. J., Best, N. G., Carlin, B. P. and Van Der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 64(4), 583616. doi: 10.1111/1467–9868.00353 CrossRefGoogle Scholar
Tomiyama, M., Kanetani, T., Tatsukawa, Y., Mori, H. and Oikawa, T. (2010). Genetic parameters for preweaning and early growth traits in Berkshire pigs when creep feeding is used. Journal of Animal Science, 88(3), 879884. doi: 10.2527/jas.2009–2072 CrossRefGoogle ScholarPubMed
Tuchscherer, M., Otten, W., Kanitz, E., Gräbner, M., Tuchscherer, A., Bellmann, O., Rehfeldt, C. and Metges, C.C. (2012). Effects of inadequate maternal dietary protein: Carbohydrate ratios during pregnancy on offspring immunity in pigs. BMC Veterinary Research, 8, 232. doi: 10.1186/1746-6148-8-232 CrossRefGoogle ScholarPubMed
Wolf, J. B. and Wade, M. J. (2009). What are maternal effects (and what are they not)? Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1520), 11071115. doi: 10.1098/rstb.2008.0238 CrossRefGoogle ScholarPubMed
Wolf, J. B. and Wade, M. J. (2016). Evolutionary genetics of maternal effects. Evolution, 70(4), 827839. doi: 10.1111/evo.12905 CrossRefGoogle ScholarPubMed
Zhang, S., Bidanel, J.-P., Burlot, T., Legault, C. and Naveau, J. (2000). Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. I. Genetic parameters. Genetics Selection Evolution, 32(1), 116. doi: 10.1186/1297-9686-32-1-41 Google ScholarPubMed