Department of Animal and Dairy Sciences, University of Wisconsin, 1675 Observatory Dr, Madison, WI, 53706, USA.
Department of Population Health and Reproduction, University of California, Davis, 95616, USA.
Sci Rep. 2024 Oct 30;14(1):26060. doi: 10.1038/s41598-024-77782-z.
Ruminants have the ability to digest human-inedible plant materials, due to the symbiotic relationship with the rumen microbiota. Rumen microbes supply short chain fatty acids, amino acids, and vitamins to dairy cows that are used for maintenance, growth, and lactation functions. The main goal of this study was to investigate gene-microbiome networks underlying feed efficiency traits by integrating genotypic, microbial, and phenotypic data from lactating dairy cows. Data consisted of dry matter intake (DMI), net energy secreted in milk, and residual feed intake (RFI) records, SNP genotype, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows. We first assessed marginal associations between genotypes and phenotypic and microbial traits through genomic scans, and then, in regions with multiple significant hits, we assessed gene-microbiome-phenotype networks using causal structural learning algorithms. We found significant regions co-localizing the rumen microbiome and feed efficiency traits. Interestingly, we found three types of network relationships: (1) the cow genome directly affects both rumen microbial abundances and feed efficiency traits; (2) the cow genome (Chr3: 116.5 Mb) indirectly affects RFI, mediated by the abundance of Syntrophococcus, Prevotella, and an unknown genus of Class Bacilli; and (3) the cow genome (Chr7: 52.8 Mb and Chr11: 6.1-6.2 Mb) affects the abundance of Rikenellaceae RC9 gut group mediated by DMI. Our findings shed light on how the host genome acts directly and indirectly on the rumen microbiome and feed efficiency traits and the potential benefits of the inclusion of specific microbes in selection indexes or as correlated traits in breeding programs. Overall, the multistep approach described here, combining whole-genome scans and causal network reconstruction, allows us to reveal the relationship between genome and microbiome underlying dairy cow feed efficiency.
反刍动物具有消化人类不可食用植物材料的能力,这是由于它们与瘤胃微生物群的共生关系。瘤胃微生物为奶牛提供短链脂肪酸、氨基酸和维生素,这些物质用于维持、生长和泌乳功能。本研究的主要目的是通过整合泌乳奶牛的基因型、微生物和表型数据,研究与饲料效率性状相关的基因-微生物组网络。数据包括干物质采食量(DMI)、乳中净能分泌量和剩余采食量(RFI)记录、SNP 基因型和 16S rRNA 瘤胃微生物丰度,来自 448 头泌乳中期荷斯坦奶牛。我们首先通过基因组扫描评估基因型与表型和微生物性状之间的边缘关联,然后在多个显著命中区域,使用因果结构学习算法评估基因-微生物-表型网络。我们发现与瘤胃微生物组和饲料效率性状共定位的显著区域。有趣的是,我们发现了三种类型的网络关系:(1)牛基因组直接影响瘤胃微生物丰度和饲料效率性状;(2)牛基因组(Chr3:116.5 Mb)通过瘤胃微生物属的丰度间接影响 RFI,间接影响 RFI 的瘤胃微生物包括梭菌属、普雷沃氏菌属和一个未知的芽孢杆菌纲属;(3)牛基因组(Chr7:52.8 Mb 和 Chr11:6.1-6.2 Mb)通过 DMI 影响厚壁菌门 Rikenellaceae RC9 肠道群的丰度。我们的研究结果揭示了宿主基因组如何直接和间接作用于瘤胃微生物组和饲料效率性状,以及在选择指数中包含特定微生物或作为选育计划中的相关性状的潜在益处。总的来说,这里描述的多步骤方法,结合全基因组扫描和因果网络重建,使我们能够揭示奶牛饲料效率的基因组和微生物组之间的关系。