Abstract Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4) and dry matter intake (DMI) were individually measured over 4–6 weeks to calculate the CH4 yield (CH4y = CH4/DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH4y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH4y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl‐coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial least‐squares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH4y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH4 emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH4y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane‐reduction selection programmes in the dairy cattle industry provided they are heritable.

中文翻译：

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与荷斯坦奶牛甲烷排放相关的瘤胃微生物生物标志物的鉴定


摘要 减少温室气体排放对于减少反刍动物生产对环境的影响至关重要。在这项研究中，通过结合 16S rRNA 基因和鸟枪法宏基因组测序来表征荷斯坦奶牛的瘤胃微生物组。在 4-6 周内单独测量甲烷产量 (CH4) 和干物质摄入量 (DMI)，以计算每头牛的 CH4 产量 (CH4y = CH4/DMI)。我们实施了聚类、多变量和混合模型分析的组合，以确定一组与 CH4y 和瘤胃微生物群落结构共同相关的操作分类单元 (OTU)。鉴定出三个瘤胃型簇（R1、R2 和 R3），R2 与较高的 CH4y 相关。 R2的分类组成中，Succinivibrionaceae和Methanosphaera丰度较低，而Ruminococcaceae、Christensenellaceae和Lachnospiraceae丰度较高。宏基因组数据证实了 R2 中琥珀弧菌科 (Succinivibrionaceae) 和甲烷球菌 (Methanosphaera) 的丰度较低，并确定了元分类学分析未突出显示的属（纤维杆菌属和未分类的拟杆菌目）。此外，功能宏基因组分析显示，分类在 R2 簇中的样本中编码与产甲烷作用相关的 KEGG 模块的基因过多，其中包括显着相对丰度的甲基辅酶 M 还原酶。基于聚类分配，我们在分类和功能层面应用了稀疏偏最小二乘判别分析。此外，我们利用 CH4y 的表型变异实现了 sPLS 回归模型。 通过结合这两种方法，我们鉴定了 86 个判别性细菌 OTU，特别包括与 CH4 排放相关的科，如 Succinivibrionaceae、Ruminococcaceae、Christensensenellaceae、Lachnospiraceae 和 Rikenellaceae。这些选定的 OTU 解释了 24% 的 CH4y 表型变异，而宿主基因组的贡献约为 14%。总之，我们确定了与奶牛甲烷产生相关的瘤胃微生物生物标志物；如果这些生物标志物具有遗传性，则可用于奶牛行业的有针对性的甲烷减排选择计划。