Genetic architecture of a composite beef cattle population

Composite breeds are widely used in the beef industry. Composites allow producers to combine desirable traits from the progenitor breeds and simplify herd management, without repeated crossbreeding and maintenance of purebreds. In this study, genomic information was used to evaluate the genetic composition and characteristics of a three-breed beef cattle composite. This composite population referred to as Composite Gene Combination (CGC) consisted of 50% Red Angus, 25% Charolais, 25% Tarentaise. A total of 248 animals were used in this study CGC (n=79), Red Angus (n=61), Charolais (n=79) and Tarentaise (n=29). All animals were genotyped with 777k HD panel. Principal component and ADMIXTURE analyses were carried out to evaluate the genetic structure of CGC animals. The ADMIXTURE revealed the proportion of Tarentaise increased to approximately 57% while Charolais decreased to approximately 5%, and Red Angus decreased to 38% across generations. To evaluate these changes in the genomic composition across different breeds and in CGC across generations runs of homozygosity (ROH) were conducted. This analysis showed Red Angus to have the highest total length of ROH segments per animal with a mean of 349.92 Mb and lowest in CGC with a mean of 141.10 Mb. Furthermore, it showed the formation of new haplotypes in CGC around the sixth generation. Selection signatures were evaluated through Fst and HapFlk analyses. Several selection sweeps in CGC were identified especially in chromosomes 5 and 14 which have previously been reported to be associated with coat color and growth traits. The study supports our previous findings that progenitor combinations are not stable over generations and that either direct or natural selection plays a role in modifying the progenitor proportions. Furthermore, the results showed that Tarentaise contributed useful attributes to the composite in a cool semi-arid environment and suggests a re-exploration of this breed's role may be warranted.

Genotype by environment interaction in response to cold stress in a composite beef cattle breed

Extreme weather conditions such as cold stress influence the productivity and survivability of beef cattle raised on pasture. The objective of this study was to identify and evaluate the extent of the impact of genotype by environment interaction due to cold stress on birth weight (BW) and weaning weight (WW) in a composite beef cattle population. The effect of cold stress was modelled as the accumulation of total cold load (TCL) calculated using the Comprehensive Climate Index units, considering three TCL classes defined based on temperature: less than -5°C (TCL5), -15°C (TCL15) and -25°C (TCL25). A total of 4221 and 4217 records for BW and WW, respectively, were used from a composite beef cattle population (50% Red Angus, 25% Charolais and 25% Tarentaise) between 2002 and 2015. For both BW and WW, a univariate model (ignoring cold stress) and a reaction norm model were implemented. As cold load increased, the direct heritability slightly increased in both BW and WW for TCL5 class; however, this heritability remained consistent across the cold load of TCL25 class. In contrast, the maternal heritability of BW was constant with cold load increase in all TCL classes, although a slight increase of maternal heritability was observed for TCL5 and TCL15. The direct and maternal genetic correlation for BW and maternal genetic correlation for WW across different cold loads between all TCL classes were high (r > 0.99), whereas the lowest direct genetic correlations observed for WW were 0.88 for TCL5 and 0.85 for TCL15. The Spearman rank correlation between the estimated breeding value of top bulls (n = 79) using univariate and reaction norm models across TCL classes showed some re-ranking in direct and maternal effects for both BW and WW particularly for TCL5 and TCL15. In general, cold stress did not have a big impact on direct and maternal genetic effects of BW and WW.

Genomic prediction of continuous and binary fertility traits of females in a composite beef cattle breed

Reproduction efficiency is a major factor in the profitability of the beef cattle industry. Genomic selection (GS) is a promising tool that may improve the predictive accuracy and genetic gain of fertility traits. There is a wide range of traits used to measure fertility in dairy and beef cattle including continuous (days open), discrete (pregnancy status), and count (number of inseminations) responses. In this study, a joint analysis of age of puberty (AOP), age at first calving (AOC), and the heifer pregnancy status (HPS) was performed. Data used in this study consisted of records from 1,365 Composite Gene Combination (CGC; 50% Red Angus, 25% Charolais, 25% Tarentaise) first parity females born between 2002 and 2011. The pedigree file included 5,374 animals. A total of 3,902 animals were genotyped with different density SNP chips (3K to 50K SNP). Animals genotyped with low-density arrays were imputed to higher density (BovineSNP50 BeadChip) using FImpute. Data were analyzed using univariate and multivariate classical quantitative models (pedigree based) and univariate genomic approaches. For the latter, 3 different Bayesian methods (BayesA, BayesB, and BayesCπ) were implemented and compared. Estimates of heritabilities using univariate and multivariate analyses based on pedigree relationships ranged between 0.03 (for AOC) to 0.2 (AOP). Heritability of pregnancy status was 0.15 and 0.09 using the univariate and multivariate analyses, respectively. Genetic correlation between pregnancy status and the other 2 traits was low being 0.08 with age at puberty and -0.10 with age at first calving. Heritability estimates were slightly higher using genomic rather than average additive relationships. The accuracy of genomic prediction was similar across the 3 Bayesian methods with higher accuracies for age of puberty than the age at first calving likely due to the higher heritability of the former. The prediction of the binary pregnancy status measured using the area under the curve increased by 27% to 29% compared to a random classifier. Due to the small size of the data, all estimates have large posterior standard deviations and results should be interpreted with caution.

Genetic relationships between production traits and reproductive performance in Holstein dairy cows

Abstract. In order to estimate genetic parameters for production traits and reproductive performance, 115465 records of production traits and 90942 records of reproductive performance from Iranian Holstein cows that were collected during 1980 to 2004 at Animal Breeding Center of Iran, were used. The estimations were performed using Restricted Maximum Likelihood method (REML) under an animal model by DF-REML and MATVEC software. Estimates of heritabilities for production traits were moderate, from 0.149 for fat yield to 0.26 for milk yield. Heritabilities for reproductive performance were low, and ranged from 0.04 for interval from calving to first service to 0.0743 for gestation length. Genetic correlations between production traits were form −0.505 for milk yield and protein percentage to 0.81 between milk yield with fat yield. Most genetic correlations between reproductive performances were found close to zero. Genetic correlation estimates of production traits with reproductive performance were from −0.513 for open days and protein yield to 0.96 for protein yield and calving interval.