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Bayesian inference of genetic parameters for ultrasound scanning traits of Kivircik lambs

Published online by Cambridge University Press:  11 August 2016

I. Cemal ,
E. Karaman ,
M. Z. Firat ,
O. Yilmaz ,
N. Ata  and
O. Karaca
I. Cemal
Affiliation:
Department of Animal Science, Faculty of Agriculture, Adnan Menderes University, Aydin 09500, Turkey
E. Karaman
Affiliation:
Department of Animal Science, Faculty of Agriculture, Akdeniz University, Antalya 07058, Turkey
M. Z. Firat
Affiliation:
Department of Animal Science, Faculty of Agriculture, Akdeniz University, Antalya 07058, Turkey
O. Yilmaz*
Affiliation:
Department of Animal Science, Faculty of Agriculture, Adnan Menderes University, Aydin 09500, Turkey
N. Ata
Affiliation:
Department of Animal Science, Faculty of Agriculture, Adnan Menderes University, Aydin 09500, Turkey
O. Karaca
Affiliation:
Department of Animal Science, Faculty of Agriculture, Adnan Menderes University, Aydin 09500, Turkey
*
†E-mail: [email protected]
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Abstract

Ultrasound scanning traits have been adapted in selection programs in many countries to improve carcass traits for lean meat production. As the genetic parameters of the traits interested are important for breeding programs, the estimation of these parameters was aimed at the present investigation. The estimated parameters were direct and maternal heritability as well as genetic correlations between the studied traits. The traits were backfat thickness (BFT), skin+backfat thickness (SBFT), eye muscle depth (MD) and live weights at the day of scanning (LW). The breed investigated was Kivircik, which has a high quality of meat. Six different multi-trait animal models were fitted to determine the most suitable model for the data using Bayesian approach. Based on deviance information criterion, a model that includes direct additive genetic effects, maternal additive genetic effects, direct maternal genetic covariance and maternal permanent environmental effects revealed to be the most appropriate for the data, and therefore, inferences were built on the results of that model. The direct heritability estimates for BFT, SBFT, MD and LW were 0.26, 0.26, 0.23 and 0.09, whereas the maternal heritability estimates were 0.27, 0.27, 0.24 and 0.20, respectively. Negative genetic correlations were obtained between direct and maternal effects for BFT, SBFT and MD. Both direct and maternal genetic correlations between traits were favorable, whereas BFT–MD and SBFT–MD had negligible direct genetic correlation. The highest direct and maternal genetic correlations were between BFT and SBFT (0.39) and between MD and LW (0.48), respectively. Our results, in general, indicated that maternal effects should be accounted for in estimation of genetic parameters of ultrasound scanning traits in Kivircik lambs, and SBFT can be used as a selection criterion to improve BFT.

Keywords

Kivirciksheep breedingfat and muscle depthmulti-traitmaternal effect
Type
Research Article
Information
animal , Volume 11 , Issue 3 , March 2017 , pp. 375 - 381
Copyright
© The Animal Consortium 2016 

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References

Bradford, GE 1972. The role of maternal effects in animal breeding: VII. Maternal effects in sheep. Journal of Animal Science 35, 1324–1334.Google Scholar
Cemal, I, Karaca, O, Altin, T, Gokdal, O, Yilmaz, M and Yilmaz, O 2007. Ultrasound measurements of eye muscle properties and backfat thickness in Kivircik lambs. Journal of Biological Sciences 7, 89–94.Google Scholar
David, I, Bouvier, F, Banville, M, Canario, L, Flatres-Grall, L, Balmisse, E and Garreau, H 2015. The direct-maternal genetic correlation has little impact on genetic evaluations. Journal of Animal Science 93, 5639–5647.CrossRefGoogle ScholarPubMed
Ekiz, B, Yilmaz, A, Ozcan, M, Kaptan, C, Hanoglu, H, Erdogan, I and Yalcintan, H 2009. Carcass measurements and meat quality of Turkish Merino, Ramlic, Kivircik, Chios and Imroz lambs raised under an intensive production system. Meat Science 82, 64–70.Google Scholar
Esquivelzeta, C, Casellas, J, Fina, M and Piedrafita, J 2012. Back fat thickness and longissimus dorsi real-time ultrasound measurements in light lambs. Journal of Animal Science 90, 5047–5055.Google Scholar
Ghafouri-Kesbi, F and Baneh, H 2012. Genetic parameters for direct and maternal effects on growth traits of sheep. Archiv fur Tierzucht 55, 603–611.Google Scholar
Gowane, GR, Chopra, A, Prakash, V and Arora, AL 2010. Estimates of (co)variance components and genetic parameters for body weights and first greasy fleece weight in Malpura sheep. Livestock Science 131, 94–101.Google Scholar
Hadfield, JD 2010. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. Journal of Statistical Software 33, 1–22.Google Scholar
Jones, HE, Lewis, RM, Young, MJ and Simm, G 2004. Genetic parameters for carcass composition and muscularity in sheep measured by X-ray computer tomography, ultrasound and dissection. Livestock Production Science 90, 167–179.Google Scholar
Koyuncu, M and Duru, S 2009. Estimates of (co)variance components for direct and maternal effects on birth weight of Karacabey Merino lambs. Turkish Journal of Veterinary and Animal Sciences 33, 235–240.Google Scholar
Kushwaha, BP, Mandal, A, Arora, AL, Kumar, R, Kumar, S and Notter, DR 2009. Direct and maternal (co)variance components and heritability estimates for body weights in Chokla sheep. Journal of Animal Breeding and Genetics 126, 278–287.Google Scholar
Larsgard, AG and Olesen, I 1998. Genetic parameters for direct and maternal effects on weights and ultrasonic muscle and fat depth of lambs. Livestock Production Science 55, 273–278.Google Scholar
Maniatis, N and Pollott, GE 2002. Maternal effects on weight and ultrasonically measured traits of lambs in a small closed Suffolk flock. Small Ruminant Research 45, 235–246.Google Scholar
Maniatis, N and Pollott, GE 2003. The impact of data structure on genetic (co)variance components of early growth in sheep, estimated using an animal model with maternal effects. Journal of Animal Science 81, 101–108.Google Scholar
Maxa, J, Norberg, E, Berg, P and Milerski, M 2007. Genetic parameters for body weight, longissimus muscle depth and fat depth for Suffolk sheep in the Czech Republic. Small Ruminant Research 72, 87–91.CrossRefGoogle Scholar
Maximini, L, Brown, DJ, Baumung, R and Fuerst-Waltl, B 2012. Genetic parameters of ultrasound and computer tomography scan traits in Austrian meat sheep. Livestock Science 146, 168–174.Google Scholar
Mortimer, SI, Swan, AA, Brown, DJ and van der Werf, JHJ 2014. Genetic parameters revisited for ultrasound scanning traits in Australian sheep. Paper presented at the 10th World Congress on Genetics Applied to Livestock Production, 17–22 August 2014, Vancouver, Canada.Google Scholar
Mrode, RA 2014. Linear models for the prediction of animal breeding values, 3rd edition. CABI Publishing, Wallingford, UK.Google Scholar
Puntila, ML, Maki, K and Rintala, O 2002. Assessment of carcass composition based on ultrasonic measurements and EUROP conformation class of live lambs. Journal of Animal Breeding and Genetics 119, 367–378.CrossRefGoogle Scholar
R Development Core Team 2014. A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Rasali, DP, Shrestha, JNB and Crow, GH 2006. Development of composite sheep breeds in the world: a review. Canadian Journal of Animal Science 86, 1–24.Google Scholar
Roden, JA, Merrell, BG, Murray, WA and Haresign, W 2003. Genetic analysis of live weight and ultrasonic fat and muscle traits in hill sheep flock undergoing breed improvement utilizing an embryo transfer programme. Animal Science 76, 367–373.Google Scholar
Safari, E, Fogarty, NM and Gilmour, AR 2005. A review of genetic parameter estimates for wool, growth, meat and reproduction traits in sheep. Livestock Production Science 92, 271–289.Google Scholar
Santos, NPS, Neto, CBO, Sarmento, JLR, Bezerra, LR, Oliveira, RL, dos Santos, GV, Neto, AAR and Biagiotti, D 2014. Carcass traits and growth curve parameters in Santa Inês sheep. Journal of Agricultural Science 6, 180–187.Google Scholar
Sañudo, C, Alfonso, M, Sánchez, A, Delfa, R and Teixeira, A 2000. Carcass and meat quality in light lambs from different fat classes in the EU carcass classification system. Meat Science 56, 89–94.Google Scholar
Simm, G, Lewis, RM, Collins, JE and Nieuwhof, GJ 2001. Use of sire referencing schemes to select for improved carcass composition in sheep. Journal of Animal Science 79, 255–259.Google Scholar
Slosarz, P, Stanisz, M, Boniecki, P, Przybylak, A, Lisiak, D and Ludwiczak, A 2011. Artificial neural network analysis of ultrasound image for the estimation of intramuscular fat content in lamb muscle. African Journal of Biotechnology 10, 11792–11796.Google Scholar
Spiegelhalter, DJ, Best, NG, Carlin, BR and van der Linde, A 2002. Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society: Series B Statistical Methodology 64, 583–616.Google Scholar
Szwaczkowski, T, Wojtowski, J, Stanislawska, E and Gut, A 2006. Estimates of maternal genetic and permanent environmental effects in sheep. Archiv fur Tierzucht 49, 186–192.Google Scholar
Tamioso, PR, Filho, JLA, Dias, LT and de Almeida Teixeira, R 2013. Estimates of (co)variance components and genetic parameters for growth traits in Suffolk lambs. Ciência Rural 43, 2215–2220.Google Scholar
Theriault, M, Pomar, C and Castonguay, FW 2009. Accuracy of real-time ultrasound measurements of total tissue, fat, and muscle depths at different measuring sites in lamb. Journal of Animal Science 87, 1801–1813.Google Scholar
Turkish Statistical Institute 2014. Animal production statistics (annual). Retrieved on 10 August 2015 from http://www.tuik.gov.tr/PreTablo.do?alt_id=1002.Google Scholar
Waldmann, P and Ericsson, T 2006. Comparison of REML and Gibbs sampling estimates of multi-trait genetic parameters in Scots pine. Theoretical and Applied Genetics 112, 1441–1451.Google Scholar
Willham, RL 1972. The role of maternal effects in animal breeding: iii. Biometrical aspects of maternal effects in animals. Journal of Animal Science 35, 1288–1293.Google Scholar
Yarali, E, Yilmaz, O, Cemal, I, Karaca, O and Taskin, T 2014. Meat quality characteristics in Kivircik lambs. Turkish Journal of Veterinary and Animal Sciences 38, 452–458.Google Scholar
Yilmaz, O, Sezenler, T, Alarslan, E, Ata, N, Karaca, O and Cemal, I 2014. Ultrasound measurements of backfat thickness and musculus longissmus dorsi thoracis et lumborum (MLD) depth at the weaning on Karacabey Merino, Karya and Kivircik lambs. The Journal of the Faculty of Veterinary Medicine, University of Kafkas 20, 829–834.Google Scholar