A review of bioinformatics tools for bio-prospecting from metagenomic sequence data

Despoina Roumpeka; R. John Wallace; Frank Escalettes; Ian Fotheringham; Michael Watson

doi:10.3389/fgene.2017.00023

A review of bioinformatics tools for bio-prospecting from metagenomic sequence data

Despoina Roumpeka, R. John Wallace, Frank Escalettes, Ian Fotheringham, Michael Watson

Research output: Contribution to journal › Literature review › peer-review

Abstract

The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such "bioprospecting" requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes.

Original language	English
Journal	Frontiers in Genetics
Volume	8
Issue number	23
Early online date	16 Feb 2017
DOIs	https://doi.org/10.3389/fgene.2017.00023
Publication status	E-pub ahead of print - 16 Feb 2017

Keywords / Materials (for Non-textual outputs)

metagenomics
bioinformatics
next generation sequencing
assembly
gene prediction
bioprospecting

Access to Document

10.3389/fgene.2017.00023

A Review of Bioinformatics Tools for Bio-Prospecting from Metagenomic Sequence Data
Copyright © 2017 Roumpeka, Wallace, Escalettes, Fotheringham and Watson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Final published version, 952 KBLicence: Creative Commons: Attribution (CC-BY)

ISP 3 2017/22 Improving Animal Health and Welfare
Meddle, S.
BBSRC
1/04/17 → 31/03/22
Project: Research
Understanding the functional and genomic architecture of the rumen microbiome affecting performance traits in bovines
Watson, M.
BBSRC
1/12/16 → 30/11/19
Project: Research
Microbiome and Metagenomic study of the rumen microbial population and their microbial enzyme genes
Watson, M.
UK central government bodies/local authorities, health and hospital authorities
1/04/16 → 31/03/22
Project: Research

Cite this

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title = "A review of bioinformatics tools for bio-prospecting from metagenomic sequence data",

abstract = "The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such {"}bioprospecting{"} requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes.",

keywords = "metagenomics, bioinformatics, next generation sequencing, assembly, gene prediction, bioprospecting",

author = "Despoina Roumpeka and Wallace, {R. John} and Frank Escalettes and Ian Fotheringham and Michael Watson",

year = "2017",

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day = "16",

doi = "10.3389/fgene.2017.00023",

language = "English",

volume = "8",

journal = "Frontiers in Genetics",

issn = "1664-8021",

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TY - JOUR

T1 - A review of bioinformatics tools for bio-prospecting from metagenomic sequence data

AU - Roumpeka, Despoina

AU - Wallace, R. John

AU - Escalettes, Frank

AU - Fotheringham, Ian

AU - Watson, Michael

PY - 2017/2/16

Y1 - 2017/2/16

N2 - The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such "bioprospecting" requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes.

AB - The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such "bioprospecting" requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes.

KW - metagenomics

KW - bioinformatics

KW - next generation sequencing

KW - assembly

KW - gene prediction

KW - bioprospecting

U2 - 10.3389/fgene.2017.00023

DO - 10.3389/fgene.2017.00023

M3 - Literature review

SN - 1664-8021

VL - 8

JO - Frontiers in Genetics

JF - Frontiers in Genetics

IS - 23

ER -

A review of bioinformatics tools for bio-prospecting from metagenomic sequence data

Abstract

Keywords / Materials (for Non-textual outputs)

Access to Document

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Projects

ISP 3 2017/22 Improving Animal Health and Welfare

Understanding the functional and genomic architecture of the rumen microbiome affecting performance traits in bovines

Microbiome and Metagenomic study of the rumen microbial population and their microbial enzyme genes

Cite this