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Longitudinal analysis of residual feed intake and BW in mink using random regression with heterogeneous residual variance

Published online by Cambridge University Press:  08 June 2015

M. Shirali ,
V. H. Nielsen ,
S. H. Møller  and
J. Jensen
M. Shirali*
Affiliation:
Department of Molecular Biology and Genetics, Aarhus University, Blichers Allée 20, 8830 Tjele, Denmark
V. H. Nielsen
Affiliation:
Department of Molecular Biology and Genetics, Aarhus University, Blichers Allée 20, 8830 Tjele, Denmark
S. H. Møller
Affiliation:
Department of Animal Science, Aarhus University, Blichers Allée 20, 8830 Tjele, Denmark
J. Jensen
Affiliation:
Department of Molecular Biology and Genetics, Aarhus University, Blichers Allée 20, 8830 Tjele, Denmark
*
†E-mail: [email protected]
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Abstract

The aim of this study was to determine the genetic background of longitudinal residual feed intake (RFI) and BW gain in farmed mink using random regression methods considering heterogeneous residual variances. The individual BW was measured every 3 weeks from 63 to 210 days of age for 2139 male+female pairs of juvenile mink during the growing-furring period. Cumulative feed intake was calculated six times with 3-week intervals based on daily feed consumption between weighing’s from 105 to 210 days of age. Genetic parameters for RFI and BW gain in males and females were obtained using univariate random regression with Legendre polynomials containing an animal genetic effect and permanent environmental effect of litter along with heterogeneous residual variances. Heritability estimates for RFI increased with age from 0.18 (0.03, posterior standard deviation (PSD)) at 105 days of age to 0.49 (0.03, PSD) and 0.46 (0.03, PSD) at 210 days of age in male and female mink, respectively. The heritability estimates for BW gain increased with age and had moderate to high range for males (0.33 (0.02, PSD) to 0.84 (0.02, PSD)) and females (0.35 (0.03, PSD) to 0.85 (0.02, PSD)). RFI estimates during the growing period (105 to 126 days of age) showed high positive genetic correlations with the pelting RFI (210 days of age) in male (0.86 to 0.97) and female (0.92 to 0.98). However, phenotypic correlations were lower from 0.47 to 0.76 in males and 0.61 to 0.75 in females. Furthermore, BW records in the growing period (63 to 126 days of age) had moderate (male: 0.39, female: 0.53) to high (male: 0.87, female: 0.94) genetic correlations with pelting BW (210 days of age). The result of current study showed that RFI and BW in mink are highly heritable, especially at the late furring period, suggesting potential for large genetic gains for these traits. The genetic correlations suggested that substantial genetic gain can be obtained by only considering the RFI estimate and BW at pelting, however, lower genetic correlations than unity indicate that extra genetic gain can be obtained by including estimates of these traits during the growing period. This study suggests random regression methods are suitable for analysing feed efficiency and BW gain; and genetic selection for RFI in mink is promising.

Keywords

feed efficiencyBW gainlongitudinal analysisgenetic parametersmink
Type
Research Article
Information
animal , Volume 9 , Supplement 10 , October 2015 , pp. 1597 - 1604
Copyright
© The Animal Consortium 2015 

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References

Andersen, S and Pedersen, B 1996. Growth and food intake curves for group-housed gilts and castrated male pigs. Animal Science 63, 457–464.Google Scholar
Basset, CF and Llewellyn, LM 1949. The molting and fur growth pattern in the adult mink. The American Midland Naturalist 42, 751–756.Google Scholar
Berg, P and Lohi, O 1992. Feed consumption and efficiency in paternal progeny groups in mink. Acta Agriculturae Scandinavica, Section A – Animal Science 42, 27–33.CrossRefGoogle Scholar
Cai, W, Casey, DS and Dekkers, JCM 2008. Selection response and genetic parameters for residual feed intake in Yorkshire swine. Journal of Animal Science 86, 287–298.Google Scholar
Charlet-Lery, G, Fiszlewich, M, Morel, MT and Allain, D 1980. Variation in body composition of male mink during growth. Proceedings of the 2nd International Scientific Congress in Fur Animal Production. April 1980. Vedbæk, Denmark. p. 6.Google Scholar
Damgaard, BM, Dalgaard, TS, Larsen, T, Hedemann, MS and Hansen, SW 2012. The effects of feed restriction on physical activity, body weight, physiology, haematology and immunology in female mink. Research in Veterinary Science 93, 936–942.Google Scholar
Drouilhet, L, Gilbert, H, Balmisse, E, Ruesche, J, Tircazes, A, Larzul, C and Garreau, H 2013. Genetic parameters for two selection criteria for feed efficiency in rabbits. Journal of Animal Science 91, 3121–3128.Google Scholar
Gilbert, H, Bidanel, JP, Gruand, J, Caritez, JC, Billon, Y, Guillouet, P, Lagant, H, Noblet, J and Sellier, P 2007. Genetic parameters for residual feed intake in growing pigs, with emphasis on genetic relationships with carcass and meat quality traits. Journal of Animal Science 85, 3182–3188.CrossRefGoogle ScholarPubMed
Gunsett, FC 1984. Linear index selection to improve traits defined as ratios. Journal of Animal Science 59, 1185–1193.Google Scholar
Gunsett, FC 1986. Problems associated with selection for traits defined as a ratio of two component traits. Proceedings of the 3rd World Congress on Genetics Applied to Livestock Production, 16 to 22 July 1986, Lincoln, Nebraska, USA, pp. 437–442.Google Scholar
Hansen, BK 1997. Mink kit growth performance in the suckling period. Part I. Environmental factors affecting body size of kits. Acta Agriculturae Scandinavica, Section A – Animal Science 47, 82–90.Google Scholar
Huisman, AE, Veerkamp, RF and van Arendonk, JAM 2002. Genetic parameters for various random regression models to describe the weight data of pigs. Journal of Animal Science 80, 575–582.Google Scholar
Jensen, J 2001. Genetic evaluation of dairy cattle using test-day models. Journal of Dairy Science 84, 2803–2812.Google Scholar
Kempe, R, Koskinen, N, Mantysaari, E and Stranden, I 2010. The genetics of body condition and leg weakness in the blue fox (Alopex lagopus). Acta Agriculturae Scandinavica, Section A – Animal Science 60, 141–150.Google Scholar
Kirkpatrick, M, Lofsvold, D and Bulmer, M 1990. Analysis of the inheritance, selection and evolution of growth trajectories. Genetics 124, 979–993.Google Scholar
Lagerkvist, G 1997. Economic profit from increased litter size, body weight and pelt quality in mink (Mustela vison). Acta Agriculturae Scandinavica, Section A – Animal Science 47, 57–63.CrossRefGoogle Scholar
Madsen, P and Jensen, J 2010. An User’s guide to DMU: a package for analysing multivariate mixed models. Version 6, release 5.2. Aarhus University, Foulum, Denmark.Google Scholar
Møller, SH 1999. Effects of weight development, pelting time, colour type and farm on skin length in mink. Acta Agriculturae Scandinavica. Section A – Animal Science 49, 121–126.CrossRefGoogle Scholar
Møller, SH and Sørensen, JT 2003. Management problems and tools for strictly synchronised animal production systems exemplified by mink production. Scientifur Reviewed Articles 27, 85–96.Google Scholar
Møller, SH, Hansen, BK and Nielsen, VH 2007. Management of feed conversion rate in different growth phases of mink. Proceedings of the NJF Seminar, 13 to 15 August 2007, Kolding, Denmark, Article No. 403.Google Scholar
Nielsen, VH, Møller, SH, Hansen, BK and Berg, P 2011. Response to selection and genotype-environment interaction in mink (Neovison vison) selected on ad libitum and restricted feeding. Canadian Journal of Animal Science 91, 231–237.Google Scholar
Nielsen, VH, Møller, SH, Hansen, BK and Berg, P 2012. Genetic parameters and effect of selection for body weight in lines of mink (Neovison vison) on ad libitum and restricted feeding. Acta Agriculturae Scandinavica, Section A – Animal Science 62, 24–28.CrossRefGoogle Scholar
Plummer, M, Best, N, Cowles, K and Vines, K 2006. CODA: Convergence Diagnosis and Output Analysis for MCMC. R News 6, 7–11.Google Scholar
Saintilan, R, Merour, I, Brossard, L, Tribout, T, Dourmad, JY, Sellier, P, Bidanel, J, van Milgen, J and Gilbert, H 2013. Genetics of residual feed intake in growing pigs: relationships with production traits, and nitrogen and phosphorus excretion traits. Journal of Animal Science 91, 2542–2554.Google Scholar
Schaeffer, LR 2004. Application of random regression models in animal breeding. Livestock Production Science 86, 35–45.Google Scholar
Shirali, M, Duthie, CA, Doeschl-Wilson, A, Knap, P, Kanis, E, van Arendonk, J and Roehe, R 2013. Novel insight into the genomic architecture of feed and nitrogen efficiency measured by residual energy intake and nitrogen excretion in growing pigs. BMC Genetics 14, 121.Google Scholar
Shirali, M, Doeschl-Wilson, A, Duthie, C, Knap, PW, Kanis, E, van Arendonk, JAM and Roehe, R 2014. Estimation of residual energy intake and its genetic background during the growing period in pigs. Livestock Science 168, 17–25.Google Scholar
Sørensen, K 2002. Selection for feed efficiency in mink (Mustela vison). Thesis PhD, The Royal Veterinary and Agricultural University, Copenhagen, Denmark.Google Scholar
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