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An automated system for evaluation of the potential functionome: MAPLE version 2.1.0.

Hideto Takami1, Takeaki Taniguchi2, Wataru Arai1

  • 1Microbial Genome Research Group, Yokohama Institute, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Kanagawa 236-0001 Japan.

DNA Research : an International Journal for Rapid Publication of Reports on Genes and Genomes
|July 5, 2016
PubMed
Summary

The Metabolic and Physiological Potential Evaluator (MAPLE) system now offers enhanced analysis of genomic and metagenomic data. MAPLE version 2.1.0 reveals significant functional differences in ocean microbial communities.

Keywords:
MAPLEglobal ocean sampling (GOS)metabolic pathwaymetagenome

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Area of Science:

  • Genomics
  • Metagenomics
  • Bioinformatics

Background:

  • The Metabolic and Physiological Potential Evaluator (MAPLE) is a system for assessing the functional potential (functionome) within genomic and metagenomic data.
  • MAPLE utilizes KEGG Orthology (KO) assignments to map genes to KEGG functional modules and calculates the Module Completion Ratio (MCR) to characterize the functionome.

Purpose of the Study:

  • To introduce new functionalities in MAPLE for calculating module abundance and Q-values.
  • To enable more detailed comparative genomic and metagenomic analyses by assessing functional abundance and statistical significance.

Main Methods:

  • Integration of module abundance and Q-value calculations into MAPLE.
  • Application of the enhanced MAPLE system to analyze four metagenomic datasets from the Global Ocean Sampling expedition.

Main Results:

  • MAPLE version 2.1.0 identified significant variations in potential functionome, functional abundance, and diversity among the analyzed ocean metagenomic datasets.
  • The updated system provides a more comprehensive characterization of microbial community functions.

Conclusions:

  • MAPLE version 2.1.0 offers advanced capabilities for comparative functional analysis of genomic and metagenomic data.
  • The system effectively highlights functional heterogeneity within environmental microbial communities.