Edinburgh Research Explorer

A network analysis of methane and feed conversion genes in the rumen microbial community

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Fiona Browne
  • Haiying Wang
  • Huiru Zheng
  • Rainer Roehe
  • Richard J. Dewhurst
  • Paul Walsh

Related Edinburgh Organisations

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1477-1484
Number of pages8
ISBN (Print)9781509016105
DOIs
Publication statusPublished - 17 Jan 2017
Event2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, China
Duration: 15 Dec 201618 Dec 2016

Conference

Conference2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
CountryChina
CityShenzhen
Period15/12/1618/12/16

Abstract

Metagenomics involves the genetic analysis of microbial DNA extracted from communities in an environment sample. Advent and falling costs of next-generation sequencing technologies has accelerated metagenomics research providing an improved understanding of microbial communities. In this study we investigate if the traits methane production and feed conversion rates in the rumen microbial community overlap with top genes ranked by topological metrics in a co-abundance network. A co-abundance network was constructed from abundance values of 1570 microbial genes in rumen samples of 8 cattle identified in a metagenomics study at the Beef and Sheep Research Centre of Scotland's Rural College. We used 4 different topological measures: Degree Centrality, Betweenness Centrality, Bonacich Power Centrality and PageRank to the network. Using permutation testing, we discovered, methane production trait genes significantly overlapped with top ranked genes obtained using the metrics PageRank and Bonacich Power Centrality. Feed conversion trait genes overlapped with top ranked genes using Bonacich Power Centrality and Betweenness. Furthermore, we observed the top ranked genes from PageRank and Bonacich Power Centrality significantly overlapped with genes involved in the KEGG methane metabolism pathway and ranked highly key methanogenesis genes such as mcrA and fmdB. Identified functional clusters containing most methane and feed conversion genes were also analyzed in terms of overlap with top ranked genes from topological metrics.

    Research areas

  • Co-abundance network, Metagenomics, Rumen microbial analysis, Topological analysis

Event

2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

15/12/1618/12/16

Shenzhen, China

Event: Conference

ID: 31828658