Estimates of heritability and repeatability for reproductive traits in Australian beef cattle

1990 ◽  
Vol 25 (1-2) ◽  
pp. 15-30 ◽  
Author(s):  
K Meyer ◽  
K Hammond ◽  
P.F Parnell ◽  
M.J MacKinnon ◽  
S Sivarajasingam
1973 ◽  
Vol 36 (6) ◽  
pp. 1032-1040 ◽  
Author(s):  
D. D. Dearborn ◽  
R. M. Koch ◽  
L. V. Cundiff ◽  
K. E. Gregory ◽  
G. E. Dickerson

2018 ◽  
Vol 47 (0) ◽  
Author(s):  
Marina Rufino Salinas Fortes ◽  
Charmaine Enculescu ◽  
Laercio R. Porto Neto ◽  
Sigrid A. Lehnert ◽  
Russell McCulloch ◽  
...  

2001 ◽  
Vol 31 (1) ◽  
Author(s):  
G.F. Jordaan ◽  
R.R. Van der Westhuizen ◽  
S.J. Schoeman ◽  
G.F. Jordaan ◽  
J.B. Van Wyk

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 47-47
Author(s):  
Roberto D Sainz ◽  
Nayanny Guimarães ◽  
Cláudio U Magnabosco ◽  
Fernando Lopes

Abstract Frame score (FS) systems for beef cattle generally represent the relationships among growth, body composition, reproduction and mature size, in a simple and practical form. This study aimed to: 1) develop a FS system for Nelore cattle that is biologically sound, easy to interpret, and useful for producers; and 2) estimate the genetic parameters of the FS with productive and reproductive traits. An arbitrary scale (1 to 12) was devised so that each unit corresponds to 15 kg of carcass weight (1 @), as this is a common measure used for marketing beef cattle in Brazil. Therefore, ideal carcass weight, defined as having 6 mm of backfat, would be 18 @ (269 kg) and 15 @ (224 kg) for FS = 6 males and females, respectively. Data from 36,030 animals (22,405 males, 13,565 females) raised on pasture were obtained from participating herds of the National Association of Breeders and Researchers (ANCP). Genetic parameters were estimated in uni- and bicharacteristic analyses under an animal model, using the EM-REML algorithm (AIREMLF90) and Bayesian inference (GIBBS1F90). The heritability estimate for the new FS was 0.38, and its additive genetic correlations were 0.70, 0.72, 0.77, 0.33, -0.57, 0.27, and 0.28 with BW at 365 d, BW at 450 d, hip height, longissimus muscle area, subcutaneous fat thickness, scrotal circumference at 450 d, and age at first calving, respectively. The estimated heritability and genetic correlations indicate that there is enough additive genetic variability to allow for genetic response to selection. The estimates support the notion that larger frame animals are taller, heavier, leaner and later maturing, both in body composition as well as sexually. The new frame score may be a useful tool for genetic selection of animals that are best suited to their environment.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Guoyao Zhao ◽  
Yuqiang Liu ◽  
Qunhao Niu ◽  
Xu Zheng ◽  
Tianliu Zhang ◽  
...  

Abstract Background Genomic regions with a high frequency of runs of homozygosity (ROH) are related to important traits in farm animals. We carried out a comprehensive analysis of ROH and evaluated their association with production traits using the BovineHD (770 K) SNP array in Chinese Simmental beef cattle. Results We detected a total of 116,953 homozygous segments with 2.47Gb across the genome in the studied population. The average number of ROH per individual was 99.03 and the average length was 117.29 Mb. Notably, we detected 42 regions with a frequency of more than 0.2. We obtained 17 candidate genes related to body size, meat quality, and reproductive traits. Furthermore, using Fisher’s exact test, we found 101 regions were associated with production traits by comparing high groups with low groups in terms of production traits. Of those, we identified several significant regions for production traits (P < 0.05) by association analysis, within which candidate genes including ECT2, GABRA4, and GABRB1 have been previously reported for those traits in beef cattle. Conclusions Our study explored ROH patterns and their potential associations with production traits in beef cattle. These results may help to better understand the association between production traits and genome homozygosity and offer valuable insights into managing inbreeding by designing reasonable breeding programs in farm animals.


Animals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 2509
Author(s):  
Franziska Weik ◽  
Rebecca E. Hickson ◽  
Stephen T. Morris ◽  
Dorian J. Garrick ◽  
Jason A. Archer

Maternal performance is a major driver of profitability in cow-calf beef cattle enterprises. The aim of this research was to evaluate the inheritance of maternal performance traits and examine the intercorrelation among reproduction, live weight, hip height, body condition and maternal contribution to calf weaning weight in 15-month-old heifers, 2-year-old cows and mature cows in New Zealand beef herds. Data were collected on a total of 14,241 cows and their progeny on five commercial New Zealand hill country farms. Heritabilities were low for reproductive traits in heifers and mature cows (0–0.06) but were greater in 2-year-old cows (0.12–0.21). Body condition scores were lowly (0.15–0.26) and live weights (0.42–0.48) and hip heights (0.47–0.65) highly heritable in heifers, 2-year-old cows and mature cows. Results indicate that 2-year-old cows with higher genetic potential for rebreeding ability may have greater genetic merit for live weight, hip height and body condition as heifers (rg = 0.19–0.54) but are unlikely to be larger cows at maturity (rg = −0.27–−0.10). The maternal genetic effect on weaning weight had a heritability of 0.20 and was negatively genetically correlated with body condition score in lactating cows (rg = −0.55–−0.40) but positively genetically correlated with rebreeding performance (rg = 0.48).


1990 ◽  
Vol 68 (6) ◽  
pp. 1536 ◽  
Author(s):  
A R Williams ◽  
D E Franke ◽  
A M Saxton ◽  
J W Turner

Author(s):  
R.R. Van der Westhuizen ◽  
S.J. Schoeman ◽  
G.F. Jordaan ◽  
J.B. Van Wyk

2020 ◽  
Vol 55 (11) ◽  
pp. 1650-1654 ◽  
Author(s):  
Iara Del Pilar Solar Diaz ◽  
Gregório Miguel Ferreira de Camargo ◽  
Valdecy Aparecida Rocha da Cruz ◽  
Isis da Costa Hermisdorff ◽  
Caio Victor Damasceno Carvalho ◽  
...  

2019 ◽  
Vol 220 ◽  
pp. 152-157 ◽  
Author(s):  
Caio Victor Damasceno Carvalho ◽  
Isis da Costa Hermisdorff ◽  
Isadora Saraiva Souza ◽  
Gleb Strauss Borges Junqueira ◽  
Ana Fabricia Braga Magalhães ◽  
...  

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