The rumen is a complex, biological system which plays a pivotal role in converting relatively low-quality feed sources into energy to sustain ruminant animals and ultimately provide high-quality protein for human consumption. It is widely published that this process produces material amounts of methane which contribute to global warming.
Whilst it is well-understood that microbial flora within the rumen and ruminant gut play a significant role in the level of methane individual ruminants produce, recent studies could not find significant differences in microbial abundances at various taxonomic levels between high- and low-methane emission.
This case study sought to investigate whether applying Synomics’ combination of a proprietary technology platform and deep industry experience could identify novel targets from the association between rumen microbiome and methane emission.
Phenotypic and metagenomic datasets were analysed in Synomics’ proprietary platform, identifying high-order combinations of taxa at the order, genus and species level. These combinations capture the non-linearity of biological effects and the impact they have on phenotypes much better than existing methods based on single features (e.g. Linear Discriminant Analysis). Networks of bacterial taxa can also be used to understand the community structure and potential biological relationship between low and high abundance bacteria.