干旱区生态环境知识资源中心(Arid): Use of Random regression model for modeling growth trajectory in Jamunapari goat in the semi-arid region of India

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DOI	10.1016/j.livsci.2021.104713
	Use of Random regression model for modeling growth trajectory in Jamunapari goat in the semi-arid region of India
	Dige, Mahesh Shivanand; Rout, Pramod Kumar; Singh, Manoj Kumar; Bhusan, Saket; Kaushik, Rakesh; Mahala, Sudarshan; Gowane, Gopal Ramdasji
通讯作者	Dige, MS (corresponding author), ICAR Cent Inst Res Goats, Div Anim Genet, Mathura 281122, Uttar Pradesh, India.
来源期刊	LIVESTOCK SCIENCE
ISSN	1871-1413
EISSN	1878-0490
出版年	2021
卷号	253
英文摘要	The objective of the study was to plot the trajectory of the growth curve in Jamunapari goat using B-spline (BS) function and compare it with the Legendre polynomial (LP) function of the random regression model (RRM) and also to assess the genotype and environment interaction for growth traits. The data was collected from 8763 descendants of 1845 dams and 339 sires. The RRM used direct genetic, direct maternal, permanent environment for animal and maternal permanent environmental effects in different orders of fit. The B-spline model (BSL6H5) was more robust compared to LP-RRM. The heritability (h2) estimates were 0.23 +/- 0.03, 0.26 +/- 0.02, 0.22 +/- 0.02, 0.19 +/- 0.02, 0.22 +/- 0.02, respectively for birth weight (BW), three-month weight (3MW), six-month weight (6MW), nine-month weight (9MW) and twelve-month weight (12MW) from the best model. The h2 estimate indicated the further scope of genetic improvement through selection. The maternal proportion of variance was accounting for 3 to 8% variance across growth trajectory indicating the low influence of maternal effects that reduced significantly post-weaning. However, we observed that the animal permanent environment accounted for 45 to 69% of variance across growth trajectory. The genetic correlations between 6MW, 9MW, and 12MW were high and positive indicating scope for early selection. The genetic trends at 3, 6, 9, and 12 months of age were 0.065 kg, 0.082 kg, 0.098 kg, and 0.121 kg per year, respectively, indicating a favorable impact of selection for growth traits. The ranks of the sires at different time points based on breeding values through B-spline RRM were more robust as compared with estimates from the conventional animal model and LP-RRM, where the presence of genotype by environment (GxE) interaction resulted in significant re-ranking of sires for 9MW and 12MW. The B-spline RRM approach resulted in a pragmatic solution for the problem of GxE interaction across growth trajectories. We conclude that the B-spline RRM should be used for genetic evaluation of Jamunapari goats in the future for unbiased, accurate, and consistent prediction of breeding values.
英文关键词	Animal model Genotypes by environment interaction Jamunapari goat Random regression model Sire re-ranking
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000709958800006
WOS关键词	GENETIC EVALUATION ; SHEEP ; TRAITS ; CATTLE ; WEIGHTS ; PARAMETERS ; COMPONENTS ; SELECTION ; VARIANCE ; SPLINES
WOS类目	Agriculture, Dairy & Animal Science
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368238
作者单位	[Dige, Mahesh Shivanand; Rout, Pramod Kumar; Singh, Manoj Kumar; Bhusan, Saket; Kaushik, Rakesh; Mahala, Sudarshan] ICAR Cent Inst Res Goats, Div Anim Genet, Mathura 281122, Uttar Pradesh, India; [Gowane, Gopal Ramdasji] ICAR Natl Dairy Res Inst, Div Anim Genet & Breeding, Karnal 132001, Haryana, India
推荐引用方式 GB/T 7714	Dige, Mahesh Shivanand,Rout, Pramod Kumar,Singh, Manoj Kumar,et al. Use of Random regression model for modeling growth trajectory in Jamunapari goat in the semi-arid region of India[J],2021,253.
APA	Dige, Mahesh Shivanand.,Rout, Pramod Kumar.,Singh, Manoj Kumar.,Bhusan, Saket.,Kaushik, Rakesh.,...&Gowane, Gopal Ramdasji.(2021).Use of Random regression model for modeling growth trajectory in Jamunapari goat in the semi-arid region of India.LIVESTOCK SCIENCE,253.
MLA	Dige, Mahesh Shivanand,et al."Use of Random regression model for modeling growth trajectory in Jamunapari goat in the semi-arid region of India".LIVESTOCK SCIENCE 253(2021).