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Identifying Core Operons in Metagenomic Data

Xiao Hu, View ORCID ProfileIddo Friedberg
doi: https://doi.org/10.1101/2019.12.20.885269
Xiao Hu
Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA 50010, USA
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Iddo Friedberg
Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA 50010, USA
Program in Bioinformatics and Computational Biology, Ames, IA 50010 USA
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  • ORCID record for Iddo Friedberg
  • For correspondence: idoerg@iastate.edu
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Abstract

An operon is a functional unit of DNA whose genes are co-transcribed on polycistronic mRNA, in a co-regulated fashion. Operons are a power-ful mechanism of introducing functional complexity in bacteria, and are therefore of interest in microbial genetics, physiology, biochemistry, and evolution. While several methods have been developed to identify operons in whole genomes, there are few that can identify them in metagenomes. Here we present a Pipeline for Operon Exploration in Metagenomes or POEM. At the heart of POEM lies a neural network that classifies genes as intra- or extra-operonic. POEM then looks for proximity associations between identified intra-operonic genes, to identify core operons in the metagenome. Core operons are operons that may exist in more than one species in the metagenome, and being evolutionarily conserved increases the probability of accurate prediction. We tested POEM using several different assemblers on a simulated metagenome, and we show it to be highly accurate. We also demonstrate its use on a human gut metagenome sample, and discover a putative new operon. We conclude that POEM is a useful tool for analyzing metagenomes beyond the genomic level, and for identifying multi-gene functionalities and possible neofunctionalization in metagenomes

Footnotes

  • https://github.com/Rinoahu/POEM_py3k

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 21, 2019.
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Identifying Core Operons in Metagenomic Data
Xiao Hu, Iddo Friedberg
bioRxiv 2019.12.20.885269; doi: https://doi.org/10.1101/2019.12.20.885269
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Identifying Core Operons in Metagenomic Data
Xiao Hu, Iddo Friedberg
bioRxiv 2019.12.20.885269; doi: https://doi.org/10.1101/2019.12.20.885269

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