Cows are the world's largest source of CH4, which contributes
significantly to global warming. Technologies are now available that
allow us to study the causes and drivers of high CH4 production in cows
at a microbiological and genetic level.
The EU-funded
RUMINOMICS (Connecting the animal genome, gastrointestinal microbiomes and nutrition to improve digestion efficiency and the environmental impacts of ruminant livestock production) project is using state-of-the-art technologies to increase efficiency and decrease the environmental impact of ruminant farming, with a focus on cows. To achieve this, researchers are collecting and scrutinising a large range of data from test sites across Europe.
RUMINOMICS will use the data to identify the genetic causes of high CH4 production, both in ruminants and in their gut microorganisms. The study will identify variation in gut microbiota, desirable traits for breeders, and the effects of feed on both gut microorganisms and overall CH4 production.
Researchers have thus far developed data management systems, designed the experimental setup and standardised all protocols for use in different testing sites. Several partnerships with related research groups have also been established to encourage the sharing of data and expertise.
RUMINOMICS has completed the task of data collection from 1 000 dairy cows. In a massive bioinformatics exercise, the collected genetic data will be related to feed intake, digestion efficiency, milk production/composition and methane emissions. These data will also be compared with the abundance of >300 rumen microbial species.
Other aspects of the project are looking at how reindeer and cow gut microbiomes differ, and, by transferring ruminal digesta between the animals, how important the host species is in determining the composition of the gut microbiota, also the impact of dietary carbohydrate on the microbiome. RUMINOMICS is also devising new, less-invasive ways to study gut microflora in cows.
The RUMINOMICS project will yield a wealth of data on the underlying genetics of CH4 production and N emissions, as well as several tools and system models for future research. These findings have the potential to improve the efficiency of dairy farming, while decreasing greenhouse gas emissions.