Bayesian analysis of selection for greater weaning weight while maintaining birth weight in beef cattle. 2009

L M Melucci, and A N Birchmeier, and E P Cappa, and R J C Cantet
Unidad Integrada Balcarce, Universidad Nacional de Mar del Plata - EEA INTA, 7620 Balcarce, Argentina

An experimental Hereford herd established in 1960 was used from 1986 to 2006 to select for increased weaning weight (W) without increasing birth weight (B). Data were B and W collected over the 47 yr from 2,124 calves. Including ancestors, the pedigree file had 2,369 animals. Selection was practiced only in males. In the first stage (1986 to 1993), mass-selected bulls were chosen with the index I = B + 9374.76 RDG (relative daily gain). From 1994 to 2006, the selection criterion for bull i was I(i) = BLUP(i)(WD) - 2.33 BLUP(i)(BD), where the BLUP were for the direct BV of B (BD) and W (WD), respectively. Predictions were obtained from a 2-trait animal model with B having only BD, and W with WD and WM (maternal additive effects). Selection response was estimated using a Bayesian approach by means of the Gibbs sampler for a 2-trait animal model including BD, BM (maternal BV for B), WD, and WM. Estimated heritabilities for BD, BM, WD, and WM were 0.40, 0.23, 0.05, and 0.23, respectively. The correlation between BD and BM was close to zero (0.01), and between WD and WM was positive (0.37). The correlation between BD and WD was 0.07, and between BM and WM was 0.58. The 2 methods used to estimate selection response gave similar results. In both periods BD decreased, whereas BM increased. The reduction of BD due to selection was slightly larger in the second period than in the first one. The regression of BV for W increased due to selection in both stages, but selection response was 21.6% larger from 1986 to 1992 than from 1993 to 2006. The maternal effect, WM increased more than 3 times compared with WD in the first period, but ended up being almost the same value as WD in period 2. The Bulmer effect was manifested by the decrease in magnitude of all (co)variance components during selection. It is concluded that selection to increase BW at weaning in beef cattle, although not increasing BW at birth, was moderately effective.

UI MeSH Term Description Entries
D008297 Male Males
D008957 Models, Genetic Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment. Genetic Models,Genetic Model,Model, Genetic
D001724 Birth Weight The mass or quantity of heaviness of an individual at BIRTH. It is expressed by units of pounds or kilograms. Birthweight,Birth Weights,Birthweights,Weight, Birth,Weights, Birth
D001835 Body Weight The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms. Body Weights,Weight, Body,Weights, Body
D002417 Cattle Domesticated bovine animals of the genus Bos, usually kept on a farm or ranch and used for the production of meat or dairy products or for heavy labor. Beef Cow,Bos grunniens,Bos indicus,Bos indicus Cattle,Bos taurus,Cow,Cow, Domestic,Dairy Cow,Holstein Cow,Indicine Cattle,Taurine Cattle,Taurus Cattle,Yak,Zebu,Beef Cows,Bos indicus Cattles,Cattle, Bos indicus,Cattle, Indicine,Cattle, Taurine,Cattle, Taurus,Cattles, Bos indicus,Cattles, Indicine,Cattles, Taurine,Cattles, Taurus,Cow, Beef,Cow, Dairy,Cow, Holstein,Cows,Dairy Cows,Domestic Cow,Domestic Cows,Indicine Cattles,Taurine Cattles,Taurus Cattles,Yaks,Zebus
D005260 Female Females
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D000831 Animals, Newborn Refers to animals in the period of time just after birth. Animals, Neonatal,Animal, Neonatal,Animal, Newborn,Neonatal Animal,Neonatal Animals,Newborn Animal,Newborn Animals
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D012641 Selection, Genetic Differential and non-random reproduction of different genotypes, operating to alter the gene frequencies within a population. Natural Selection,Genetic Selection,Selection, Natural

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