Reproductive performance as affected by lactation status and body fat in beef cows.

Seventy-one mature Brangus cows, 38 nonlactating (NL) and 33 in late stage of lactation (L) were fed for 192 days (Phase I) a low energy diet (L). During Phase II (65 days) 19 NL and 17 L cows were fed a high energy diet (H). The other nonlactating (19) and lactating (16) cows remained on the low energy diet. Energy restriction during Phase I did not affect (P> 0.05) cyclic ovarian activity although losses in body weight and condition were substantial. Rapid changes in body weight, condition, and percent empty body lipe (EBLP) during Phase II did not substantially influencefertility, although a five-fold difference in EBLP was observed (NL0H vs. L-L). Treatment groups did not differ (P> 0.05) in conception rate, days from the beginning of the breeding season to breeding and to conception, conception at first service, and number of services per conception. Values observed for these parameters for NL-H, L-H, NL-L, and L-L groups were respectively: 68,4%, `3,.2, 23.3, 36.8% and 1.68; 82,4% 12.7, 19.5, 58.8% and 1.29; 68.4%, 10.2, 17.4, 47.4%, and 1.41; 68.8%, 12.4, 19.5, 43.7%, and 1.50.

Factor analysis applied to genome prediction for high-dimensional phenotypes in pigs.

The aim of the present study was to propose and evaluate the use of factor analysis (FA) in obtaining latent variables (factors) that represent a set of pig traits simultaneously, for use in genome-wide selection (GWS) studies. We used crosses between outbred F2 populations of Brazilian Piau X commercial pigs. Data were obtained on 345 F2 pigs, genotyped for 237 SNPs, with 41 traits. FA allowed us to obtain four biologically interpretable factors: ?weight?, ?fat?, ?loin?, and ?performance?. These factors were used as dependent variables in multiple regression models of genomic selection (Bayes A, Bayes B, RR-BLUP, and Bayesian LASSO). The use of FA is presented as an interesting alternative to select individuals for multiple variables simultaneously in GWS studies; accuracy measurements of the factors were similar to those obtained when the original traits were considered individually. The similarities between the top 10% of individuals selected by the factor, and those selected by the individual traits, were also satisfactory. Moreover, the estimated markers effects for the traits were similar to those found for the relevant factor.