Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome - PubMed (original) (raw)

. 2014 Sep;24(9):1517-25.

doi: 10.1101/gr.168245.113. Epub 2014 Jun 6.

Christina D Moon 2, Sinead C Leahy 2, Dongwan Kang 1, Jeff Froula 1, Sandra Kittelmann 2, Christina Fan 1, Samuel Deutsch 1, Dragana Gagic 2, Henning Seedorf 2, William J Kelly 2, Renee Atua 2, Carrie Sang 2, Priya Soni 2, Dong Li 2, Cesar S Pinares-Patiño 2, John C McEwan 2, Peter H Janssen 2, Feng Chen 1, Axel Visel 3, Zhong Wang 3, Graeme T Attwood 2, Edward M Rubin 4

Affiliations

Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome

Weibing Shi et al. Genome Res. 2014 Sep.

Abstract

Ruminant livestock represent the single largest anthropogenic source of the potent greenhouse gas methane, which is generated by methanogenic archaea residing in ruminant digestive tracts. While differences between individual animals of the same breed in the amount of methane produced have been observed, the basis for this variation remains to be elucidated. To explore the mechanistic basis of this methane production, we measured methane yields from 22 sheep, which revealed that methane yields are a reproducible, quantitative trait. Deep metagenomic and metatranscriptomic sequencing demonstrated a similar abundance of methanogens and methanogenesis pathway genes in high and low methane emitters. However, transcription of methanogenesis pathway genes was substantially increased in sheep with high methane yields. These results identify a discrete set of rumen methanogens whose methanogenesis pathway transcription profiles correlate with methane yields and provide new targets for CH4 mitigation at the levels of microbiota composition and transcriptional regulation.

© 2014 Shi et al.; Published by Cold Spring Harbor Laboratory Press.

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Figures

Figure 1.

Figure 1.

The measurement of CH4 yields in sheep. (A) New Zealand sheep used for this study. (B) CH4 yields from the sheep in grams of CH4/kg dry matter intake (DMI) were measured using open-circuit respiration chambers (

http://www.globalresearchalliance.org

). (C) CH4 yield measurements from 22 sheep (each with two time points) sorted by mean values. Four high (red) and four low (blue) emitters are selected for further study. _P_-value indicates the statistical significance of the differences in CH4 yield between the two selected groups.

Figure 2.

Figure 2.

Comparison of relative abundance of different microbial populations in low and high CH4 yield sheep. (A) Relative abundance of microbial domains in low and high CH4 yield sheep. (B) Relative abundance of methanogenic and nonmethanogenic archaea in low and high CH4 yield sheep. (C) Relative abundance of classes of CH4-producing Euryarchaeota in low and high CH4 yield sheep. (NS) No statistical difference in Wilcoxon rank-sum test in each subgroup.

Figure 3.

Figure 3.

Comparisons of gene and transcript abundance for enzymes involved in methanogenesis between high and low CH4 yield sheep. (A) Diagram of CO2/H2 methanogenesis pathway shows enzymes involved in each biochemical reaction. (B,C) Gene (B) and transcript (C) abundance for each enzyme. (D) Transcriptions per gene for each enzyme. (RPM) Reads per million; (NS) no statistical significance in Wilcoxon rank-sum test; (*) P < 0.05; (**) P < 0.01. Error bars, SE.

Figure 4.

Figure 4.

Phylogenetic analysis of methanogens in sheep rumen. (A) A phylogenetic tree constructed based on full-length methyl coenzyme M reductase alpha subunit (McrA/MrtA) protein sequences. Known McrA/MrtA proteins from NCBI are shown in black; new ones from this study, in color. (B) Genes and transcripts for three groups of identified sheep rumen methanogens. (RPM) Reads per million; (NS) no statistical significance in Wilcoxon rank-sum test; (*) P < 0.05; (**) P < 0.01. Error bars, SE. (C) Relative contribution of each group of sheep rumen methanogens to the overall abundance (RPM) of genes and transcripts in low and high CH4 yield sheep. The sizes of each pie indicate the abundance of genes/transcripts.

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References

    1. Benchaar C, Pomar C, Chiquette J. 2001. Evaluation of dietary strategies to reduce methane production in ruminants: a modelling approach. Can J Anim Sci 81: 563–574
    1. Benjamini Y, Hochberg Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc B Met 57: 289–300
    1. Boone DR, Whitman WB, Rouviere P. 1993. Diversity and taxonomy of methanogens. In Methanogenesis: ecology, physiology, biochemistry and genetics (ed. Ferry JG), pp. 35–80. Chapman and Hall, London, UK.
    1. Browne PD, Cadillo-Quiroz H. 2013. Contribution of transcriptomics to systems-level understanding of methanogenic archaea. Archaea 2013: 586369. - PMC - PubMed
    1. Buddle BM, Denis M, Attwood GT, Altermann E, Janssen PH, Ronimus RS, Pinares-Patino CS, Muetzel S, Wedlock DN. 2011. Strategies to reduce methane emissions from farmed ruminants grazing on pasture. Vet J 188: 11–17 - PubMed

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