Short communication: Signs of host genetic regulation in the microbiome composition in 2 dairy breeds: Holstein and Brown Swiss
Gonzalez-Recio, O., Zubiria, I., García-Rodríguez, A., Hurtado, A., & Atxaerandio, R. (2018). Short communication: Signs of host genetic regulation in the microbiome composition in 2 dairy breeds: Holstein and Brown Swiss. Journal of Dairy Science, 101(3), 2285–2292. https://doi.org/10.3168/jds.2017-13179
Comparison Between Non-Invasive Methane Measurement Techniques in Cattle
Rey, J., Atxaerandio, R., Ruiz, R., Ugarte, E., González-Recio, O., Garcia-Rodriguez, A., & Goiri, I. (2019). Comparison Between Non-Invasive Methane Measurement Techniques in Cattle. Animals : an open access journal from MDPI, 9(8), 563. doi:10.3390/ani9080563
Enteric methane emissions pose a serious issue to ruminant production and environmental sustainability. To mitigate methane emissions, combined research efforts have been put into animal handling, feeding and genetic improvement strategies. For all research efforts, it is necessary to record methane emissions from individual cows on a large scale under farming conditions. The objective of this trial was to compare two large-scale, non-invasive methods of measuring methane (non-dispersive infrared methane analyzer (NDIR) and laser), in order to see if they can be used interchangeably. For this, paired measurements were taken with both devices on a herd of dairy cows and compared. Significant sources of disagreement were identified between the methods, such that it would not be possible to use both methods interchangeably without first correcting the sources of disagreement.
Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study
, , , et al. Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study. J Anim Breed Genet. 2020; 137: 36– 48. https://doi.org/10.1111/jbg.12444
The advent of metagenomics in animal breeding poses the challenge of statistically modelling the relationship between the microbiome, the host genetics and relevant complex traits. A set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed here to jointly analyse the host–metagenome–phenotype relationship. A non‐recursive bivariate model was set as benchmark to compare the recursive model. The relative abundance of rumen microbes (RA), methane concentration (CH4) and the host genetics was used as a case of study. Data were from 337 Holstein cows from 12 herds in the north and north‐west of Spain. Microbial composition from each cow was obtained from whole metagenome sequencing of ruminal content samples using a MinION device from Oxford Nanopore Technologies. Methane concentration was measured with Guardian® NG infrared gas monitor from Edinburgh Sensors during cow’s visits to the milking automated system. A quarterly average from the methane eructation peaks for each cow was computed and used as phenotype for CH4. Heritability of CH4 was estimated at 0.12 ± 0.01 in both the recursive and bivariate models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH4 ranged from −0.76 to 0.65 in the non‐recursive bivariate model and from −0.68 to 0.69 in the recursive model. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the seven genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. These results suggest that rumen’s whole metagenome recursively regulates methane emissions in dairy cows and that both CH4 and the microbiota compositions are partially controlled by the host genotype.