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Measuring and mitigating methane (CH 4 ) emissions from livestock is of increasing importance for the environment and for policy making. Potentially, the most sustainable way of reducing enteric CH 4 emission from ruminants is through the estimation of genomic breeding values to facilitate genetic selection. There is potential for adopting genetic selection and in the future genomic selection, for reduced CH 4 emissions from ruminants. From this review it has been observed that both CH 4 emissions and production (g/day) are a heritable and repeatable trait. CH 4 emissions are strongly related to feed intake both in the short term (minutes to several hours) and over the medium term (days). When measured over the medium term, CH 4 yield (MY, g CH 4 /kg dry matter intake) is a heritable and repeatable trait albeit with less genetic variation than for CH 4 emissions. CH 4 emissions of individual animals are moderately repeatable across diets, and across feeding levels, when measured in respiration chambers. Repeatability is lower when short term measurements are used, possibly due to variation in time and amount of feed ingested prior to the measurement. However, while repeated measurements add value; it is preferable the measures be separated by at least 3 to 14 days. This temporal separation of measurements needs to be investigated further. Given the above issue can be resolved, short term (over minutes to hours) measurements of CH 4 emissions show promise, especially on systems where animals are fed ad libitum and frequency of meals is high. However, we believe that for short-term measurements to be useful for genetic evaluation, a number (between 3 and 20) of measurements will be required over an extended period of time (weeks to months). There are opportunities for using short-term measurements in standardised feeding situations such as breath 'sniffers' attached to milking parlours or total mixed ration feeding bins, to measure CH 4 . Genomic selection has the potential to reduce both CH 4 emissions and MY, but measurements on thousands of individuals will be required. This includes the need for combined resources across countries in an international effort, emphasising the need to acknowledge the impact of animal and production systems on measurement of the CH 4 trait during design of experiments.Keywords: genetics, greenhouse gases, enteric methane, ruminants ImplicationMeasuring and mitigating methane (CH 4 ) emissions from livestock is of increasing importance for the environment and for policy making. Potentially, the most sustainable way of reducing enteric CH 4 emission from ruminants is through the estimation of genomic breeding values to facilitate genetic selection. Enteric CH 4 emissions are difficult and expensive to measure, thus genomic prediction could provide significant, † E-mail: Yvette IntroductionClimate change is of growing international concern and it is well established that the release of greenhouse gases (GHG) is the driving factor (IPCC, 2006). Globally, livestock farming contributes...

ABSTRACT:Our objective was to estimate genetic parameters for feed intake, feeding behavior, and ADG in composite ram lambs (¹⁄₂ Columbia, ¹⁄₄ Hampshire, ¹⁄₄ Suffolk). Data were collected from 1986 to 1997 on 1,239 ram lambs from approximately 11 to 17 wk of age at the U.S. Meat Animal Research Center near Clay Center, NE. Feeding equipment consisted of an elevated pen with an entrance chute that permitted access to the feeder by only one ram lamb at a time, with disappearance of feed measured by an electronic weighing system. Ram lambs were grouped 11 per pen from 1986 to 1989, and nine per pen from 1990 to 1997. Data were edited to exclude invalid feeding events, and approximately 80% of the data remained after edits were applied. Traits analyzed were daily feed intake (DFI), event feed intake (EFI), residual feed intake (RFI), daily feeding time (DFT), event feeding time (EFT), number of daily feeding events (DFE), and ADG.

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BackgroundGrazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal’s diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data.ResultsUsing comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host’s metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift.ConclusionWe argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-017-0274-6) contains supplementary material, which is available to authorized users.