%0 Journal Article
%T Metagenomics - a guide from sampling to data analysis
%A Torsten Thomas
%A Jack Gilbert
%A Folker Meyer
%J Microbial Informatics and Experimentation
%D 2012
%I BioMed Central
%R 10.1186/2042-5783-2-3
%X Arguably, one of the most remarkable events in the field of microbial ecology in the past decade has been the advent and development of metagenomics. Metagenomics is defined as the direct genetic analysis of genomes contained with an environmental sample. The field initially started with the cloning of environmental DNA, followed by functional expression screening [1], and was then quickly complemented by direct random shotgun sequencing of environmental DNA [2,3]. These initial projects not only showed proof of principle of the metagenomic approach, but also uncovered an enormous functional gene diversity in the microbial world around us [4].Metagenomics provides access to the functional gene composition of microbial communities and thus gives a much broader description than phylogenetic surveys, which are often based only on the diversity of one gene, for instance the 16S rRNA gene. On its own, metagenomics gives genetic information on potentially novel biocatalysts or enzymes, genomic linkages between function and phylogeny for uncultured organisms, and evolutionary profiles of community function and structure. It can also be complemented with metatranscriptomic or metaproteomic approaches to describe expressed activities [5,6]. Metagenomics is also a powerful tool for generating novel hypotheses of microbial function; the remarkable discoveries of proteorhodopsin-based photoheterotrophy or ammonia-oxidizing Archaea attest to this fact [7,8].The rapid and substantial cost reduction in next-generation sequencing has dramatically accelerated the development of sequence-based metagenomics. In fact, the number of metagenome shotgun sequence datasets has exploded in the past few years. In the future, metagenomics will be used in the same manner as 16S rRNA gene fingerprinting methods to describe microbial community profiles. It will therefore become a standard tool for many laboratories and scientists working in the field of microbial ecology.This review gives an over
%K sampling
%K sequencing
%K assembly
%K binning
%K annotation
%K data storage
%K data sharing
%K DNA extraction
%K microbial ecology
%K microbial diversity
%U http://www.microbialinformaticsj.com/content/2/1/3