Abstract
Whole-genome shotgun metagenomics experiments produce DNA sequence data from entire ecosystems, and provide a huge amount of novel information. Gene discovery projects require up-to-date information about sequence homology and domain structure for millions of predicted proteins to be presented in a simple, easy-to-use system. There is a lack of simple, open, flexible tools that allow the rapid sharing of metagenomics datasets with collaborators in a format they can easily interrogate. We present Meta4, a flexible and extensible web application that can be used to share and annotate metagenomic gene predictions. Proteins and predicted domains are stored in a simple relational database, with a dynamic front-end which displays the results in an internet browser. Web services are used to provide up-to-date information about the proteins from homology searches against public databases. Information about Meta4 can be found on the project website1, code is available on Github2, a cloud image is available, and an example implementation can be seen at
Highlights
Whole-genome shotgun (WGS) metagenomics can be defined as the application of high-throughput sequencing technologies to whole environmental samples, enabling scientists to assay the genomes of all organisms within a particular ecosystem, be it the human gut microbiome (Yatsunenko et al, 2012), permafrost (Mackelprang et al, 2011), or the Sargasso Sea (Venter et al, 2004)
A web form is provided that allows users to query the database and information is presented in two ways: firstly, data extracted directly from the Meta4 database is presented in the browser; secondly, data extracted from the Meta4 database is provided to a range of web services, and the results of those web services presented in the browser
The role of Meta4 is to allow bioinformaticians to share the results of metagenomic assembly and annotation with collaborators, and to provide those collaborators with a simple web-based interface with which to query and browse the data
Summary
Whole-genome shotgun (WGS) metagenomics can be defined as the application of high-throughput sequencing technologies to whole environmental samples, enabling scientists to assay the genomes of all organisms within a particular ecosystem, be it the human gut microbiome (Yatsunenko et al, 2012), permafrost (Mackelprang et al, 2011), or the Sargasso Sea (Venter et al, 2004). A generalized analysis pipeline for such data is to (i) assemble the genomic data de novo; (ii) predict genes and proteins on the resulting contigs and scaffolds; (iii) assign domains and function to those proteins; (iv) interpret those findings within the biological context. It is not unusual for such studies to generate several million novel genes/proteins – Venter et al (2004) reported over 1.2 million novel genes, and Hess et al (2011) reported over 2.5 million putative genes, 27755 containing a domain of interest: those relevant to biomass degradation. The attempt to simultaneously assemble thousands of different genomes often results in large and
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