Abstract
Reducing methane emissions from livestock production is of great importance for the sustainable management of the Earth’s environment. Rumen microbiota play an important role in producing biogenic methane. However, knowledge of how host genetics influences variation in ruminal microbiota and their joint effects on methane emission is limited. We analyzed data from 750 dairy cows, using a Bayesian model to simultaneously assess the impact of host genetics and microbiota on host methane emission. We estimated that host genetics and microbiota explained 24% and 7%, respectively, of variation in host methane levels. In this Bayesian model, one bacterial genus explained up to 1.6% of the total microbiota variance. Further analysis was performed by a mixed linear model to estimate variance explained by host genomics in abundances of microbial genera and operational taxonomic units (OTU). Highest estimates were observed for a bacterial OTU with 33%, for an archaeal OTU with 26%, and for a microbial genus with 41% heritability. However, after multiple testing correction for the number of genera and OTUs modeled, none of the effects remained significant. We also used a mixed linear model to test effects of individual host genetic markers on microbial genera and OTUs. In this analysis, genetic markers inside host genes ABS4 and DNAJC10 were found associated with microbiota composition. We show that a Bayesian model can be utilized to model complex structure and relationship between microbiota simultaneously and their interaction with host genetics on methane emission. The host genome explains a significant fraction of between-individual variation in microbial abundance. Individual microbial taxonomic groups each only explain a small amount of variation in methane emissions. The identification of genes and genetic markers suggests that it is possible to design strategies for breeding cows with desired microbiota composition associated with phenotypes.
Highlights
IntroductionMitigation of greenhouse gas emissions has become a major research objective due to global climate change [1,2,3]
Supplementary information The online version of this article contains supplementary material, which is available to authorized users.Mitigation of greenhouse gas emissions has become a major research objective due to global climate change [1,2,3]
A Bayesian mixture model was used to examine the relative contributions of host genetics and microbiota variation at the operational taxonomic units (OTU) level on methane emission by fitting all effects simultaneously
Summary
Mitigation of greenhouse gas emissions has become a major research objective due to global climate change [1,2,3]. With the development of tools for the measurement of methane emission in the livestock sector, the amount of greenhouse gas such as methane emission from cows can be measured on a large scale [4, 5]. Global livestock production is an important source of greenhouse gasses. Livestock accounts for 10–12% of CO2, and 5% of CH4 of total anthropogenic greenhouse gas emissions [6, 7]. Growing human populations and incomes are fueling demand for animal products, which result in more greenhouse gas emission from livestock production. Reduction of methane emission from livestock production is critical to address the global climate problems. Reducing methane emissions maybe ties to improving feed efficiency
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
