Genetic correlation network prediction of forest soil microbial functional organization View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-10

AUTHORS

Bin Ma, Kankan Zhao, Xiaofei Lv, Weiqin Su, Zhongmin Dai, Jack A. Gilbert, Philip C. Brookes, Karoline Faust, Jianming Xu

ABSTRACT

Soil ecological functions are largely determined by the activities of soil microorganisms, which, in turn, are regulated by relevant interactions between genes and their corresponding pathways. Therefore, the genetic network can theoretically elucidate the functional organization that supports complex microbial community functions, although this has not been previously attempted. We generated a genetic correlation network based on 5421 genes derived from metagenomes of forest soils, identifying 7191 positive and 123 negative correlation relationships. This network consisted of 27 clusters enriched with sets of genes within specific functions, represented with corresponding cluster hubs. The clusters revealed a hierarchical architecture, reflecting the functional organization in the soil metagenomes. Positive correlations mapped functional associations, whereas negative correlations often mapped regulatory processes. The potential functions of uncharacterized genes were predicted based on the functions of located clusters. The global genetic correlation network highlights the functional organization in soil metagenomes and provides a resource for predicting gene functions. We anticipate that the genetic correlation network may be exploited to comprehensively decipher soil microbial community functions. More... »

PAGES

2492-2505

References to SciGraph publications

  • 2004-06. Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast in NATURE
  • 2015-01. Long-term phenotypic evolution of bacteria in NATURE
  • 2011-12. Biological interaction networks are conserved at the module level in BMC SYSTEMS BIOLOGY
  • 2015-12. CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers in BMC GENOMICS
  • 2012-12. Molecular ecological network analyses in BMC BIOINFORMATICS
  • 2009-11. Evolution of biomolecular networks — lessons from metabolic and protein interactions in NATURE REVIEWS MOLECULAR CELL BIOLOGY
  • 2012-02. Using network analysis to explore co-occurrence patterns in soil microbial communities in THE ISME JOURNAL
  • 2014-12. Autotrophy at the thermodynamic limit of life: a model for energy conservation in acetogenic bacteria in NATURE REVIEWS MICROBIOLOGY
  • 2011-07. A genetic interaction network of five genes for human polycystic kidney and liver diseases defines polycystin-1 as the central determinant of cyst formation in NATURE GENETICS
  • 2010-02. One gram of soil: a microbial biochemical gene library in ANTONIE VAN LEEUWENHOEK
  • 2016-08. Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China in THE ISME JOURNAL
  • 2014-12. Software for pre-processing Illumina next-generation sequencing short read sequences in SOURCE CODE FOR BIOLOGY AND MEDICINE
  • 2013-08. Network deconvolution as a general method to distinguish direct dependencies in networks in NATURE BIOTECHNOLOGY
  • 2017-02. Genome reduction in an abundant and ubiquitous soil bacterium ‘Candidatus Udaeobacter copiosus’ in NATURE MICROBIOLOGY
  • 2010-12. Prodigal: prokaryotic gene recognition and translation initiation site identification in BMC BIOINFORMATICS
  • 2015-07. Dispersing misconceptions and identifying opportunities for the use of 'omics' in soil microbial ecology in NATURE REVIEWS MICROBIOLOGY
  • 2014-12. Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types in NATURE COMMUNICATIONS
  • 2009-03. Systems genetics of complex traits in Drosophila melanogaster in NATURE GENETICS
  • 2012-08. Wisdom of crowds for robust gene network inference in NATURE METHODS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41396-018-0232-8

    DOI

    http://dx.doi.org/10.1038/s41396-018-0232-8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1105804736

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30046166


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