Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance

Abstract

Methane produced by methanogenic archaea in ruminants contributes significantly to anthropogenic greenhouse gas emissions. The host genetic link controlling microbial methane production is unknown and appropriate genetic selection strategies are not developed. We used sire progeny group differences to estimate the host genetic influence on rumen microbial methane production in a factorial experiment consisting of crossbred breed types and diets. Rumen metagenomic profiling was undertaken to investigate links between microbial genes and methane emissions or feed conversion efficiency. Sire progeny groups differed significantly in their methane emissions measured in respiration chambers. Ranking of the sire progeny groups based on methane emissions or relative archaeal abundance was consistent overall and within diet, suggesting that archaeal abundance in ruminal digesta is under host genetic control and can be used to genetically select animals without measuring methane directly. In the metagenomic analysis of rumen contents, we identified 3970 microbial genes of which 20 and 49 genes were significantly associated with methane emissions and feed conversion efficiency respectively. These explained 81% and 86% of the respective variation and were clustered in distinct functional gene networks. Methanogenesis genes (e.g. mcrA and fmdB) were associated with methane emissions, whilst host-microbiome cross talk genes (e.g. TSTA3 and FucI) were associated with feed conversion efficiency. These results strengthen the idea that the host animal controls its own microbiota to a significant extent and open up the implementation of effective breeding strategies using rumen microbial gene abundance as a predictor for difficult-to-measure traits on a large number of hosts. Generally, the results provide a proof of principle to use the relative abundance of microbial genes in the gastrointestinal tract of different species to predict their influence on traits e.g. human metabolism, health and behaviour, as well as to understand the genetic link between host and microbiome.

Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions

“…Effects are seen most clearly when the difference in MeP between groups of animals is large; for example, Wallace et al (2015) used treatments that generated a 1.9-fold difference in CH 4 emissions. Roehe et al (2016) observed that the ranking of sire groups for CH 4 emissions measured with respiration chambers was the same as that for ranking on archaea:bacteria ratio, providing further evidence that host control of archaeal abundance contributes to genetic variation in CH 4 emissions, at least in some circumstances. Across a wide geographical range, the methanogenic archaea were shown to be highly conserved across the world .…”

“…One clear limitation of metagenomic predictions compared with genomic predictions is that the microbiome of the host is variable; that is, it may change in response to diet or other environmental factors over time, whereas the host's DNA remains constant. Roehe et al (2016) also conducted rumen metagenomic analysis from 8 beef cattle divergent for CH 4 emissions and demonstrated that 20 microbial genes (out of 3,970 identified) were significantly related to CH 4 emissions. These included genes involved in the first and last steps of methanogenesis: formylmethanofuran dehydrogenase subunit B (fmdB) and methyl-coenzyme M reductase α subunit (mcrA), which were 170 times more abundant in high-emitting cattle.…”

Genetic Determinants of the Gut Microbiome in UK Twins

“…Studies across mammal species (Hackstein and van Alen, 1996) and within bovine lines (Roehe et al, 2016) have also suggested that host genetics influence levels of methanogens. Methanogen carriage has been associated with leanness and with a better metabolic profile in obese humans (Le Chatelier et al, 2013).…”

A glimpse of the future in animal nutrition science. 2. Current and future solutions

“…Although these studies have generated informative single nucleotide polymorphism (SNP), their current utility for selection programs is limited as causative SNP because RFI appear to be breed or population specific (Saatchi et al, 2014). More recent studies (Jami et al, 2014;McCann et al, 2014b;Myer et al, 2015;Roehe et al, 2016) have highlighted interrelationships that exist between host animals with divergent phenotypes for feed efficiency and their rumen microbiome structure. These recent advances in microbiomics, as well as metabolomics (metabolite profiles; Karisa et al, 2014), will drive discovery of more informative genomic markers for more accurate and robust selection for RFI across divergent cattle populations.…”