Rumen metagenome profiles are heritable and rank the New Zealand national sheep flock for enteric methane emissions

Abstract

Background: Global targets to reduce greenhouse gas emissions to meet international climate change commitments have driven the livestock industry to develop solutions to reduce methane emission in ruminants while maintaining production. Research has shown that selective breeding for low methane emitting ruminants using genomic selection is one viable solution to meet methane targets at a national level. However, this requires obtaining sufficient measures of methane on individual animals across the national herd. In sheep, one affordable method for measuring methane on-farm to rank animals on their methane emissions is portable accumulation chambers (PAC), although this method is not without its challenges. An alternative is to use a proxy trait that is genetically correlated with PAC methane measures. One such trait that has shown promise is rumen metagenome community (RMC) profiles. In this study, we investigate the potential of using RMC profiles as a proxy trait for methane emissions from PAC using a large sheep dataset consisting of 4585 mixed-sex lambs from several flocks and years across New Zealand.

Results: RMC profiles were generated from rumen samples collected on the animals immediately after being measured through PAC using restriction enzyme-reduced representation sequencing. We predicted methane (CH₄) and carbon dioxide (CO₂) emissions (grams per day), as well as the ratio CH₄/(CO₂ + CH₄) (CH₄Ratio), from the RMC profiles and SNP-array genotype data. Heritability and microbiability estimates were similar to values found in the literature for all traits. The correlation of PAC methane with predicted methane was 1.9- to 2.3-fold (CH₄) and 1.2- to 1.5-fold (CH₄Ratio) greater for RMC profiles compared to host genomics only. The genetic correlation between methane predicted from RMC profiles and PAC methane was 0.75 ± 0.12 for CH₄ and 0.64 ± 0.11 for CH₄Ratio when using a validation set consisting of the animals with the most recent year of birth in the dataset.

Conclusions: RMC profiles are predictive of, and genetically correlated, with PAC methane measures. Therefore, RMC profiles are a suitable proxy trait for determining the genetic merit of an animal's methane emissions and could be incorporated into existing breeding programs to facilitate selective breeding for low methane emitting sheep.

Fig. 1

Principal component analysis (PCA) plot of the genomic relatedness matrix (GRM). The PCA analysis consists of the 4585 animals included in this study and 13,118 animals from the study by Dodds et al. [52]. a PCA plot of the Dodds et al. [52] animals coloured by breed type (Coop = Coopworth, Peren = Perendale, Rom = Romney). b PCA plot with the animals included in this study (black points) overlayed on the animals from the Dodds et al. [52] study (grey points)

Fig. 2

Results of predicting liveweight and methane traits using RMC profiles and host genomics. The predictive accuracy is given along the top row and regression slope is given along the bottom row of host genomics (Genome) and the RMC profiles (metagenome) for predicting the liveweight and methane traits in this study. Points and lines are coloured based on whether the statistics were computing using the forward prediction (FP) approach (red) or using the cross-fold validation (CV) approach (blue). Crosses denote the accuracy/slope for individual cohorts (FP) or folds (CV), circles denote the mean accuracy/slope and the error bars represent one standard error around the mean accuracy/slope (weighted by number of animals in cohort). Note that a value of 1 represents no bias in this context. The accuracy is calculated as the correlation between predicted and trait values adjusted for fixed effects