Sepulveda B J, González-Recio O, Chamberlain A J, Khansefid M, Cocks B G, Wang J, Prowse-Wilkins C P, Marett L C, Williams S R O, Jacobs J L, García-Rodríguez A, Jiménez-Montero J A, Pryce J E
Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia.
Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid 28040, Spain.
J Dairy Sci. 2025 Aug;108(8):8619-8636. doi: 10.3168/jds.2024-25436.
Ruminant digestion emits methane, a potent greenhouse gas contributing to global warming and reducing feed efficiency. Reducing enteric methane emissions (EME) through breeding decisions is theoretically possible, yet measuring these emissions on commercial farms is currently challenging and costly. It is common for EME to be measured using different technologies, which may show weak correlations between them, complicating the combination of reference populations, especially between countries. Here, using the same sequencing strategy, we identified a group of ruminant metagenomic features (a core) present in at least 90% of 410 dairy cows in Australia and 434 in Spain. With subsets of this core (the breeding core subsets) we estimated larger reductions on EME than using direct selection on EME. A combination of direct selection on EME and indirect selection on the breeding core subsets was estimated to produce even larger reductions. Combining the principal components of the core with some genera, Kyoto Encyclopedia of Genes and Genomes ontology and Clusters of Orthologous Groups could enhance EME reductions in breeding programs. We estimated an EME reduction of 0.41 phenotypic standard deviations per generation by selecting the top 30% of individuals with desirable ruminal microbiota profiles. An R Shiny application to estimate those reductions is provided. Additionally, the breeding core subsets could predict EME irrespective of each population's EME trait (sulfur hexafluoride in Australia and sniffers in Spain). These results suggest that rumen metagenome features could be used as selection criteria for genomic selection programs to reduce EME, as many of these features are heritable and correlated with EME. Features in the core could connect EME from different cattle populations, irrespective of the methane phenotype used in those populations. We propose that our methodology should be applied to much larger datasets to improve the accuracy of identifying a breeding core. Therefore, we propose a global effort to validate a common core of EME-associated ruminal features.
反刍动物消化会排放甲烷，这是一种强效温室气体，会加剧全球变暖并降低饲料效率。从理论上讲，通过育种决策来减少肠道甲烷排放（EME）是可行的，但目前在商业农场测量这些排放具有挑战性且成本高昂。通常使用不同技术来测量EME，而这些技术之间的相关性可能较弱，这使得参考群体的组合变得复杂，尤其是在不同国家之间。在这里，我们采用相同的测序策略，在澳大利亚的410头奶牛和西班牙的434头奶牛中，识别出一组至少存在于90%个体中的反刍动物宏基因组特征（一个核心）。利用这个核心的子集（育种核心子集），我们估计在减少EME方面比直接选择EME能取得更大的成效。估计将直接选择EME和对育种核心子集进行间接选择相结合能产生更大幅度的减少。将核心的主成分与一些属、京都基因与基因组百科全书本体以及直系同源簇相结合，可以在育种计划中进一步减少EME。通过选择具有理想瘤胃微生物群特征的前30%个体，我们估计每代EME减少0.41个表型标准差。我们提供了一个用于估计这些减少量的R Shiny应用程序。此外，无论每个群体的EME特征如何（澳大利亚使用六氟化硫，西班牙使用嗅探器），育种核心子集都可以预测EME。这些结果表明，瘤胃宏基因组特征可作为基因组选择计划的选择标准，以减少EME，因为其中许多特征是可遗传的且与EME相关。核心中的特征可以将不同牛群的EME联系起来，而与这些群体中使用的甲烷表型无关。我们建议将我们的方法应用于更大的数据集，以提高识别育种核心的准确性。因此，我们提议开展一项全球行动，以验证与EME相关的瘤胃特征的共同核心。
