Manzanilla-Pech Coralia Ines Valentina, Stephansen Rasmus Bak, Difford Gareth Frank, Løvendahl Peter, Lassen Jan
Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Department of Animal and Aquacultural Sciences, Faculty of Biosciences, Norwegian University of Life Sciences, As, Norway.
Front Genet. 2022 May 26;13:885932. doi: 10.3389/fgene.2022.885932. eCollection 2022.
In the last decade, several countries have included feed efficiency (as residual feed intake; RFI) in their breeding goal. Recent studies showed that RFI is favorably correlated with methane emissions. Thus, selecting for lower emitting animals indirectly through RFI could be a short-term strategy in order to achieve the intended reduction set by the EU Commission (-55% for 2030). The objectives were to 1) estimate genetic parameters for six methane traits, including genetic correlations between methane traits, production, and feed efficiency traits, 2) evaluate the expected correlated response of methane traits when selecting for feed efficiency with or without including methane, 3) quantify the impact of reducing methane emissions in dairy cattle using the Danish Holstein population as an example. A total of 26,664 CH breath records from 647 Danish Holstein cows measured over 7 years in a research farm were analyzed. Records on dry matter intake (DMI), body weight (BW), and energy corrected milk (ECM) were also available. Methane traits were methane concentration (MeC, ppm), methane production (MeP; g/d), methane yield (MeY; g CH/kg DMI), methane intensity (MeI; g CH/kg ECM), residual methane concentration (RMeC), residual methane production (RMeP, g/d), and two definitions of residual feed intake with or without including body weight change (RFI1, RFI2). The estimated heritability of MeC was 0.20 ± 0.05 and for MeP, it was 0.21 ± 0.05, whereas heritability estimates for MeY and MeI were 0.22 ± 0.05 and 0.18 ± 0.04, and for the RMeC and RMeP, they were 0.23 ± 0.06 and 0.16 ± 0.02, respectively. Genetic correlations between methane traits ranged from moderate to highly correlated (0.48 ± 0.16-0.98 ± 0.01). Genetic correlations between methane traits and feed efficiency were all positive, ranging from 0.05 ± 0.20 (MeI-RFI2) to 0.76 ± 0.09 (MeP-RFI2). Selection index calculations showed that selecting for feed efficiency has a positive impact on reducing methane emissions' expected response, independently of the trait used (MeP, RMeP, or MeI). Nevertheless, adding a negative economic value for methane would accelerate the response and help to reach the reduction goal in fewer generations. Therefore, including methane in the breeding goal seems to be a faster way to achieve the desired methane emission reductions in dairy cattle.
在过去十年中，几个国家已将饲料效率（以剩余采食量；RFI表示）纳入其育种目标。最近的研究表明，RFI与甲烷排放呈正相关。因此，通过RFI间接选择低排放动物可能是一项短期策略，以实现欧盟委员会设定的预期减排目标（到2030年减排55%）。目标是：1）估计六个甲烷性状的遗传参数，包括甲烷性状、生产性状和饲料效率性状之间的遗传相关性；2）评估在选择饲料效率时，无论是否纳入甲烷，甲烷性状的预期相关反应；3）以丹麦荷斯坦牛群体为例，量化降低奶牛甲烷排放的影响。分析了一个研究农场7年间对647头丹麦荷斯坦奶牛测量的总共26664条CH呼吸记录。还获得了干物质采食量（DMI）、体重（BW）和能量校正乳（ECM）的记录。甲烷性状包括甲烷浓度（MeC，ppm）、甲烷产量（MeP；g/d）、甲烷产率（MeY；g CH/kg DMI）、甲烷强度（MeI；g CH/kg ECM）、剩余甲烷浓度（RMeC）、剩余甲烷产量（RMeP，g/d），以及包含或不包含体重变化的剩余采食量的两种定义（RFI1、RFI2）。MeC的估计遗传力为0.20±0.05，MeP的为0.21±0.05，而MeY和MeI的遗传力估计值分别为0.22±0.05和0.18±0.04，RMeC和RMeP的分别为0.23±0.06和0.16±0.02。甲烷性状之间的遗传相关性从中等相关到高度相关（0.48±0.16 - 0.98±0.01）。甲烷性状与饲料效率之间的遗传相关性均为正，范围从0.05±0.20（MeI - RFI2）到0.76±0.09（MeP - RFI2）。选择指数计算表明，选择饲料效率对降低甲烷排放的预期反应有积极影响，与所使用的性状（MeP、RMeP或MeI）无关。然而，为甲烷添加负经济价值将加速反应，并有助于在更少的世代中实现减排目标。因此，将甲烷纳入育种目标似乎是在奶牛中实现所需甲烷减排的更快途径。
