Rumen microbiome affects feed efficiency and is associated with host genetics in beef cattle

With our global human population continuing to grow, there is increased competition for resources (e.g., land, water, and cereal grains) between people and livestock, especially beef cattle operations. Improving the feed efficiency of cattle would reduce the amount of feed consumed (especially cereals that could feed humans instead) with equal or higher production performance. Improving feed efficiency can also reduce the negative environmental effects (methane emissions and manure) caused by beef cattle operations.

By applying cutting-edge DNA and RNA sequencing technologies, we explored the rumen microbiome of beef cattle from three breeds on the same diet but divergent in feed efficiency [1]. We aimed to evaluate the breed effect on the rumen microbiome and generate a more conclusive understanding of the role of the rumen microbiome in feed efficiency. We observed differences between the rumen microbiomes of different breeds, as well as microbial features that differed between efficient and inefficient steers. These aspects were also specific to each breed, suggesting that interactions between the host breed and the rumen microbiome influence feed efficiency. We conducted a follow-up study [2], surveying a large cohort of beef cattle (n=709) raised under the same farm environment. Multiple factors, including breed, sex, and diet were identified to determine rumen microbiome profiles. We found that ~34% of rumen microorganisms are heritable elements affected by host genetics and genotypes, that are also associated with host feed efficiency traits and rumen metabolic measures. Therefore, cattle may control their rumen microbiome genetically and consequently influence their rumen fermentation and feed efficiency.

The cattle sampled for these papers were part of the Gentec “Kinsella Cattle Project” (Improvement of cow feed efficiency and the production of consistent quality beef using molecular breeding values for RFI and carcass traits). The Kinsella Project enabled the measurement of feed-efficiency and provided the genotypes and pedigree information for the genome-wide association analysis with rumen microbes.

Overall, our findings highlight a potential to manipulate and obtain a desirable and efficient rumen microbiome using genetic selection and breeding. It could be a useful strategy to further improve feed efficiency and optimize rumen fermentation through targeting both cattle and their rumen microbiome.

The work, funded by Alberta Livestock and Meat Agency, Alberta Agriculture and Forestry, NSERC, and an Alberta Innovates-Technology Futures Graduate Student Scholarship, brought together researchers in beef production, rumen microbiology, functional genomics, quantitative and statistical genomics. Notably, Agriculture and Agri-Food Canada scientists Changxi Li and Carolyn Fitzsimmons, both co-located at UAlberta, were essential in providing these elements for Fuyong’s analysis.

“Rumen microbe composition and abundance are novel quantitative traits in beef cattle. Characterizing variations of rumen microbes among animals and estimating their genetic parameters will also allow us to incorporate rumen microbe measurements into a multiple trait selection index to improve beef production efficiency” says Changxi Li.

The EC project on Ruminomics led by Prof. John Wallace in the UK subsequently reported similar results in dairy cattle.

The Gentec team is now investigating the genetic links of rumen microbes with other beef performance traits.

Fuyong’s papers are:

  1. Li, F., Hitch TCA, Chen Y, Creevey CJ, Guan LL. 2019. Comparative metagenomic and metatranscriptomic analyses reveal the breed effect on the rumen microbiome and its associations with feed efficiency in beef cattleMicrobiome7:6.
  2. Li, F., Li, C., Chen, Y., Liu, J., Zhang, C., Irving, B., Fitzsimmons, C., Plastow, G., Guan, L.L. (2019) Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle. Microbiome, 7:92.
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