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A-GAME: improving the assembly of pooled functional metagenomics sequence data.

Matteo Chiara1, Antonio Placido2, Ernesto Picardi2,3

  • 1Department of Biosciences, University of Milan, via Celoria 26, 20133, Milan, Italy.

BMC Genomics
|January 14, 2018
PubMed
Summary

A-GAME is a new web service that simplifies the analysis of environmental DNA (eDNA) sequence data for functional metagenomics. It efficiently identifies novel microbial enzymes, reducing costs and manual annotation needs.

Keywords:
AssemblyCandidate genesFunctional annotationFunctional metagenomicsGalaxyWorkflow

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Biotechnology

Background:

  • Functional metagenomics uses environmental DNA (eDNA) to discover novel microbial enzymes.
  • High-throughput sequencing and assembly are key steps in identifying enzyme candidates.
  • Current methods can be laborious and costly.

Purpose of the Study:

  • To present A-GAME, a web service for analyzing eDNA sequence data in functional metagenomics.
  • To provide a streamlined workflow for identifying and characterizing novel microbial enzymes.
  • To improve the efficiency and reduce the cost of functional metagenomics studies.

Main Methods:

  • Development of A-GAME, a web service integrating state-of-the-art bioinformatics tools.
  • Application of A-GAME workflows to real functional metagenomics data.
  • Comparison of A-GAME's performance against alternative metagenomics assemblers.

Main Results:

  • A-GAME offers efficient analysis of pooled eDNA libraries.
  • The service enables rapid identification of candidate genes for biotechnological applications.
  • A-GAME workflows demonstrated superior performance compared to alternative assemblers.

Conclusions:

  • A-GAME is a valuable resource for the functional metagenomics community.
  • The web service streamlines enzyme discovery from eDNA.
  • A-GAME is publicly accessible for broader research use.