Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that selection for lower MPR may have undesired effect on animal productivity. On the other hand, MY and the RMPR were either not genetically correlated or weakly correlated with BWT, YWT, and FWT (-0.06 to 0.23) and body composition traits (-0.18 to 0.18). Therefore, selection for lower MY or RMPR would lead to lower MPR without impacting animal productivity. Where the use of a ratio trait (e.g., MY) is not desirable, selection on any of the forms of RMP would be an alternative.
Ruminants contribute up to 80% of greenhouse gas (GHG) emissions from livestock, and enteric methane production by ruminants is the main source of these GHG emissions. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data from 2 performance-recording research herds of Angus cattle were used to evaluate a number of methane measures that target methane production (MPR) independent of feed intake and to examine their phenotypic relationships with growth and body composition. The data comprised 777 young bulls and heifers that were fed a roughage diet (ME of 9 MJ/kg DM) at 1.2 times their maintenance energy requirements and measured for MP in open circuit respiration chambers for 48 h. Methane traits evaluated included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means (± SD) of 6.2 ± 1.4 kg/d, 187 ± 38 L/d, and 30.4 ± 3.5 L/kg, respectively. Four forms of residual MPR (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMPR), predicted MPR was obtained by regression of MPR on DMI. Growth traits evaluated were BW at birth, weaning (200 d of age), yearling age (400 d of age), and 600 d of age, with means (± SD) of 34 ± 4.6, 238 ± 37, 357 ± 45, and 471 ± 53 kg, respectively. Body composition traits included ultrasound measures (600 d of age) of rib fat, rump fat, and eye muscle area, with means (± SD) of 3.8 ± 2.6 mm, 5.4 ± 3.8 mm, and 61 ± 7.7 cm(2), respectively. Methane production was positively correlated (r ± SE) with DMI (0.65 ± 0.02), MY (0.72 ± 0.02), the RMP traits (r from 0.65 to 0.79), the growth traits (r from 0.19 to 0.57), and the body composition traits (r from 0.13 to 0.29). Methane yield was, however, not correlated (r ± SE) with DMI (-0.02 ± 0.04) as well as the growth (r from -0.03 to 0.11) and body composition (r from 0.01 to 0.06) traits. All the RMP traits were strongly correlated to MY (r from 0.82 to 0.95). These results indicate that reducing MPR per se can have a negative impact on growth and body composition of cattle. Reducing MY, however, will likely have the effect of reducing MPR without impacting productivity. Where a ratio trait is undesirable, as in animal breeding, any of the RMP traits can be used instead of MY. However, where independence from DMI is desired, RMPR should be a trait worth considering.
Methane (CH) is a product of enteric fermentation in ruminants, and it represents around 17% of global CH emissions. There has been substantial effort from the livestock scientific community toward tools that can help reduce this percentage. One approach is to select for lower emitting animals. To achieve this, accurate genetic parameters and identification of the genomic basis of CH traits are required. Therefore, the objectives of this study were 1) to perform a genomewide association study to identify SNP associated with several CH traits in Angus beef cattle (1,020 animals) and validate them in a lactating Holstein population (population 1 [POP1]; 205 animals); 2) to validate significant SNP for DMI and weight at test (WT) from a second Holstein population, from a previous study (population 2 [POP2]; 903 animals), in an Angus population; and 3) to evaluate 2 different residual CH traits and determine if the genes associated with CH also control residual CH traits. Phenotypes calculated for the genotyped Angus population included CH production (MeP), CH yield (MeY), CH intensity (MI), DMI, and WT. The Holstein population (POP1) was multiparous, with phenotypes on CH traits (MeP, MeY, and MI) plus genotypes. Additionally, 2 CH traits, residual genetic CH (RGM) and residual phenotypic CH (RPM), were calculated by adjusting MeP for DMI and WT. Estimated heritabilities in the Angus population were 0.30, 0.19, and 0.15 for MeP, RGM, and RPM, respectively, and genetic correlations of MeP with DMI and WT were 0.83 and 0.80, respectively. Estimated heritabilities in Holstein POP1 were 0.23, 0.30, and 0.42 for MeP, MeY, and MI, respectively. Strong associations with MeP were found on chromosomes 4, 12, 14, 20, and 30 at < 0.001, and those chromosomes also had significant SNP for DMI in Holstein POP1. In the Angus population, the number of significant SNP for MeP at < 0.005 was 3,304, and approximately 630 of those SNP also were important for DMI and WT. When a set (approximately 3,300) of significant SNP for DMI and WT in the Angus population was used to estimate genetic parameters for MeP and MeY in Holstein POP1, the genetic variance and, consequently, the heritability slightly increased, meaning that most of the genetic variation is largely captured by these SNP. Residual traits could be a good option to include in the breeding goal, as this would facilitate selection for lower emitting animals without compromising DMI and WT.
Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.
Weaning weights from 83 389 Limousin calves born between 1993 and 2002 in France and the Trans-Tasman block (Australia/New Zealand) were analysed to compare different strategies for running an international genetic evaluation for the breed. These records were a subset of the complete data for both countries and comprised a sample of herds that had recorded progeny of sires used across both countries. Genetic and phenotypic parameters for weaning weight were estimated within the countries. The estimates of direct genetic heritabilities were higher in France than in the Trans-Tasman block (0.31 vs. 0.22), while direct-maternal genetic correlations were less negative in the Trans-Tasman block (-0.10) than in France (-0.21). Different strategies for an international evaluation were studied, and the correlations between the estimated breeding values (EBV) of national evaluations and these strategies were derived. The international evaluation strategies were a) an animal model on raw performance data with non unity genetic correlations and heterogeneous residual and genetic variances across countries; b) the same animal model applied to pre-corrected (for fixed effects) performance data; and c) a sire model on de-regressed proofs (MACE). Estimates of the genetic correlations between weaning weight in both countries were 0.86 (0.80) for direct (maternal) genetic effects for the first strategy. Estimation of variance components by MACE appeared to be very sensitive to the sample of bulls and their reliability approximations. Variance component estimates obtained using pre-corrected data were inconsistent with estimates on raw data. However, the EBV predicted using pre-corrected data and parameters estimated from the raw data were similar to those predicted from raw data. Correlations between national and international EBV were always high (> 0.90) for sires, whichever genetic effect (direct or maternal) or international evaluation model was considered. The ranking of the bulls in the top 100 is of primary interest in terms of international genetic evaluation. In this study, some re-ranking of sires was observed for the top 100 bulls between countries and between the three international evaluation models. Thus, the origin of top sires may vary according to the implemented international evaluation strategy.
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