Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host.

BACKGROUND: Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. RESULTS: Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. CONCLUSIONS: Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Across-Experiment Transcriptomics of Sheep Rumen Identifies Expression of Lipid/Oxo-Acid Metabolism and Muscle Cell Junction Genes Associated With Variation in Methane-Related Phenotypes.

Ruminants are significant contributors to the livestock generated component of the greenhouse gas, methane (CH4). The CH4 is primarily produced by the rumen microbes. Although the composition of the diet and animal intake amount have the largest effect on CH4 production and yield (CH4 production/dry matter intake, DMI), the host also influences CH4 yield. Shorter rumen feed mean retention time (MRT) is associated with higher dry matter intake and lower CH4 yield, but the molecular mechanism(s) by which the host affects CH4 production remain unclear. We integrated rumen wall transcriptome data and CH4 phenotypes from two independent experiments conducted with sheep in Australia (AUS, n = 62) and New Zealand (NZ, n = 24). The inclusion of the AUS data validated the previously identified clusters and gene sets representing rumen epithelial, metabolic and muscular functions. In addition, the expression of the cell cycle genes as a group was consistently positively correlated with acetate and butyrate concentrations (p < 0.05, based on AUS and NZ data together). The expression of a group of metabolic genes showed positive correlations in both AUS and NZ datasets with CH4 production (p < 0.05) and yield (p < 0.01). These genes encode key enzymes in the ketone body synthesis pathway and included members of the poorly characterized aldo-keto reductase 1C (AKR1C) family. Several AKR1C family genes appear to have ruminant specific evolution patterns, supporting their specialized roles in the ruminants. Combining differential gene expression in the rumen wall muscle of the shortest and longest MRT AUS animals (no data available for the NZ animals) with correlation and network analysis, we identified a set of rumen muscle genes involved in cell junctions as potential regulators of MRT, presumably by influencing contraction rates of the smooth muscle component of the rumen wall. Higher rumen expression of these genes, including SYNPO (synaptopodin, p < 0.01) and NEXN (nexilin, p < 0.05), was associated with lower CH4 yield in both AUS and NZ datasets. Unlike the metabolic genes, the variations in the expression of which may reflect the availability of rumen metabolites, the muscle genes are currently our best candidates for causal genes that influence CH4 yield.

Information governance--a view from the NHS.

In this paper, a range of issues influencing and affecting NHS information governance policy and practice will be considered. The expansion of electronic information services within the NHS and with its other information partners has reinforced the need for effective security and confidentiality arrangements to apply at multiple levels and in a variety of different business contexts. Added to these, the need to consistently address issues of data protection, records management and data quality, has resulted in a NHS information governance initiative. This initiative is intended to provide approved tools, methods and guidance that may be applied consistently throughout the NHS and that will be underpinned through appropriate support and helpdesk services. This paper emphasises the need to consider a range of applicable topics when determining a responsible and extensible approach to the governance of information collected, used and shared by healthcare organisations.