Literature DB >> 14552368

Genetic evaluation of an index of birth weight and yearling weight to improve efficiency of beef production.

M D MacNeil1.   

Abstract

The CGC population is a stabilized composite of 1/2 Red Angus, 1/4 Charolais, and 1/4 Tarentaise germplasm. The objectives of this research were to estimate genetic parameters for weight traits of CGC and to evaluate genetic responses resulting from selection based on the following index: I = 365-d weight 3.2(birth weight). Phenotypes evaluated were birth weight (n = 5,083), 200-d weight (n = 4,902), 365-d weight (n = 4,626), and the index. In addition, there were 1,433 cows with at least one recorded weight, and 4,375 total observations of cow weight collected at the time their calves were weaned. In 1989, a randomly selected control line and a line selected for greater values of the index were established. Average generation intervals were 3.16 +/- 0.04 and 3.90 +/- 0.08 yr in the index and control lines, respectively. The index selection line (n = 950) accumulated approximately 212 kg more selection differential than the control line over three generations (n = 912). Heritability estimates for direct effects were 0.32 +/- 0.04, 0.49 +/- 0.05, 0.49 +/- 0.05, 0.30 +/- 0.04, and 0.70 +/- 0.04 for the index, birth weight, 365-d weight, 200-d weight, and cow weight, respectively. Heritability estimates for maternal effects were 0.05 +/- 0.02, 0.11 +/- 0.03, 0.04 +/- 0.02, and 0.19 +/- 0.04 for the index, birth weight, 365-d weight, and 200-d weight, respectively. In the control line, direct genetic changes for the index and its components were small. For the index selection line, direct genetic changes for the index, birth weight, 365-d weight, 200-d weight, and cow weight were 6.0 +/- 0.3, 0.45 +/- 0.09, 7.74 +/- 0.55, 3.42 +/- 0.25, and 6.3 +/- 0.9 kg/generation, respectively. Maternal genetic changes were generally small for both the control and index selection lines. Thus, selection for the index produced positive correlated responses for direct genetic effects on BW traits at all ages, with only minor effects on maternal genetic effects. Results demonstrate that despite a genetic antagonism that compromises selection response for decreased birth weight and increased postnatal growth, favorable genetic responses can be achieved with the selection index used in this study.

Entities:  

Mesh:

Year:  2003        PMID: 14552368     DOI: 10.2527/2003.81102425x

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  6 in total

1.  Differential response from selection for high calving ease vs. low birth weight in American Simmental beef cattle.

Authors:  Hamad M Saad; Milton G Thomas; Scott E Speidel; Richard K Peel; W Marshall Frasier; R Mark Enns
Journal:  J Anim Sci       Date:  2020-07-01       Impact factor: 3.159

2.  Genome-wide association study identifies two major loci affecting calving ease and growth-related traits in cattle.

Authors:  Hubert Pausch; Krzysztof Flisikowski; Simone Jung; Reiner Emmerling; Christian Edel; Kay-Uwe Götz; Ruedi Fries
Journal:  Genetics       Date:  2010-11-08       Impact factor: 4.562

3.  Transgenerational propensities for infant birth weight reflect fetal growth history of the mother in rhesus monkeys.

Authors:  Elizabeth A Shirtcliff; Gabriele R Lubach; Reilly Mooney; Robert T Beck; Laurel K Fanning; Christopher L Coe
Journal:  Trends Dev Biol       Date:  2019-12

4.  National genetic evaluation (system) of hanwoo (korean native cattle).

Authors:  B Park; T Choi; S Kim; S-H Oh
Journal:  Asian-Australas J Anim Sci       Date:  2013-02       Impact factor: 2.509

5.  Genetic and Genome-Wide Association Analysis of Yearling Weight Gain in Israel Holstein Dairy Calves.

Authors:  Moran Gershoni; Joel Ira Weller; Ephraim Ezra
Journal:  Genes (Basel)       Date:  2021-05-10       Impact factor: 4.096

6.  Genetic analysis of novel phenotypes for farm animal resilience to weather variability.

Authors:  Enrique Sánchez-Molano; Vanessa V Kapsona; Joanna J Ilska; Suzanne Desire; Joanne Conington; Sebastian Mucha; Georgios Banos
Journal:  BMC Genet       Date:  2019-11-12       Impact factor: 2.797

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.