March, 2021

Rumen Microbiome Targets for Low Methane Emission

Study design

The study used data from a publicly available dataset comprised of over 1000 dairy cows across 2 breeds and 5 countries. Genomic data was from 50k and 150k SNP arrays with 86 phenotypes and other data points included in the original dataset. Within these datapoints, rumen microbiome was based on ss rRNA analysis. Illumina reads were mapped to a bacterial 16S sequences database.

The Challenge

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.

Our Solution

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.

0
important order-level taxa
0 %
of important taxa identified are differentially enriched between high and low emitters
0
highly significant taxa for further investigation

The Results

Synomics’ platform was able to identify novel microbiome variants and produce biologically relevant results, for example identifying 21 Order-level taxa that were differentially enriched between high and low emitters (P-value < 0.05). Five of these taxa have a statistically significant relationship with either high- or low-methane emission and are potential targets for functional validation while only one order-level bacteria could be identified as differentially abundant using the publicly available tool ANCOM.  These results show the value the Synomics’ platform has in the emerging sector of microbiome analysis and discovery.

 

Synomics has licensed global use of this proprietary technology platform in bovine exclusively to Vytelle Holdings Inc.

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