Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits

Abstract

Background Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3,139 rumen samples, collected from 1,200 dual purpose ewes, using Restriction Enzyme-Reduced Representation Sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (Residual Feed Intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. Results Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. Conclusions This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within Cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Genomic Regions Associated with Wool, Growth and Reproduction Traits in Uruguayan Merino Sheep

“…Nevertheless, candidate genes associated with major wool traits (FD and CFW) have been reported in the Australian and Chinese Merino sheep populations [8,[13][14][15]. Genomic regions related to live weight have also been found in Merino sheep in Australia [9] and New Zealand [16]. A French study reported candidate genes associated with ewes' body condition score (BCS) [17].…”

Practical monitoring of enteric production from individual ruminants

“…Sheep and goats are raised for fibre, meat, milk and hides over a wide range of climatic conditions and production systems, particularly in marginal areas and extensive systems where conventional crop production is infeasible (Alberto et al, 2018;Hristov et al, 2013a). Reducing the CH4 emission from sheep and goats is therefore high on the international research agenda, with strategies spanning multiple disciplines such as animal breeding, nutrition, and microbiology (Hess et al, 2022;Jonker et al, 2018). All disciplines require accurate and precise measurements from which to gauge the response and efficacy of different mitigation strategies.…”