Location: Genetics and Animal BreedingTitle: Genetic relationship between wool shedding in ewe-lambs and ewes
|JURADO, NAPOLEON - University Of Nebraska|
|LEWIS, RONALD - University Of Nebraska|
Submitted to: American Society of Animal Science Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 5/5/2017
Publication Date: 7/8/2017
Citation: Jurado, N.V., Leymaster, K.A., Kuehn, L.A., Lewis, R.M. 2017. Genetic relationship between wool shedding in ewe-lambs and ewes. [abstract] Journal of Animal Science. 95(Supplement 4):94-95. doi:10.2527/asasann.2017.191.
Technical Abstract: Interest in reducing labor costs related to shearing has led to the development of breeds that naturally shed their wool annually. This goal has been achieved by introducing hair-sheep genetics. These developments are relatively recent and thus the genetic underpinnings of wool shedding (WS) are not entirely known. Moreover, in many instances it is desirable to select and cull progeny at young ages based on performance. However, if performance at an early age is not a good predictor of performance at later ages, erroneous selection decisions could be made. The goal of this study was to determine the accuracy of predicting wool shedding in ewes (EWS) using information from the same individuals as lambs (LWS) by estimating the genetic correlation between EWS and LWS. Data from a flock composed of Katahdin, Dorper, and Romanov crosses were available. A total of 1368 records for each trait (LWS and EWS) were used for the analyses. Model selection was performed by initially fitting a cumulative probit link model including age of dam (AOD) and contemporary group (CG; genetic line by year of record) as fixed effects and weaning weight (WW) as a covariate for LWS, and age of record (AGE), contemporary group (CG), and number of lambs born and reared (NBR) as fixed effects for EWS. For both traits, a random sire effect with pedigree relationships was also included. Variance components were estimated by fitting a bivariate threshold animal model, which contained the factors found to have an important effect (P < 0.001) on each trait. Only AGE and CG were included in the analysis of EWS, and only CG for LWS. Additive variances (on the liability scale) were 0.053 ± 0.008 and 0.168 ± 0.027 for EWS and LWS, respectively, while residual variances (also on liability scale) were 0.058 ± 0.005 and 0.209 ± 0.019 for EWS and LWS, respectively. Both traits were found to be moderately heritable and genetically correlated. Heritability of liability was 0.477 ± 0.056 for EWS and 0.444 ± 0.059 for LWS. In addition, the genetic correlation between EWS and LWS was 0.649 ± 0.063, while the phenotypic correlation was 0.450. Based on these genetic parameters, selection to increase shedding can be achieved fairly quickly. In addition, given that the correlation between EWS and LWS is moderately strong, selecting and culling young animals based on their first WS performance may be successfully used as indirect selection on EWS.