RSAT Virtual machine (VM) User Guide

1 Introduction

This tutorial explains the steps to instantiate an RSAT Virtual Machine on the cloud of the French Institute of Bioinformatics IFB cloud and perform some basic operations with regulatory sequences and motifs.

2 Instantiating an RSAT Virtual Machine on the IFB cloud

1. Open a connection to the IFB cloud at http://www.france-bioinformatique.fr/fr/cloud and click on the link Se connecter to access the login window.

Login window

2. Cliquez sur le bouton New Instance.

Click on the button New Instnace to start a new virtual machine.

3. In the dialog box, select the appliance RSAT (2016-06), fill the Name field (for example type *RSAT-VM) and click Run**.

Dialog box for the configuration of a new instance of VM on the IFB cloud.

4. Th new instance will take a couple of minutes to start. Click periodically on Show Instances until your new instance appears with a green light, and the ssh and http links are active.

List of running instances on the IFB cloud. The list is user-specific, for this tutorial you only need the RSAT-VM instance.

5. Click then on the http link for the RSAT-VM instance. This brings you to the home page of your own RSAT server.

Home page of the RSAT virtual machine.

3 A quick tour of the tools: from gene clusters to motifs

We will run a quick tour of some simple modular tools of the RSAT software suite. We will successively run the following analyses:

1. Get the list of supported organisms.
2. Select a group of yeast genes involved in a common biological process (methionine metabolism and transport), which are supposedly co-regulated by some transcription factors.
3. Retrieve the non-coding sequences located upstream of these genes. These upstream sequences contain the gene promoter and the cis-regulatory elements.
4. Apply an ab initio motif discovery approach based on the detection of over-represented k)mers (oligo-analysis) in order to detect motifs potentially involved in the transcriptional response of these genes.
5. Scan the promoter sequences to detect the sites (positions) matching the discovered motifs.
6. Generate a feature-map to inspect the position of these sites.

3.1 Protocol

3.1.1 1. Supported organisms

In the left panel, expland the menu Genomes and genes and click on the tool Supported organisms.

List of supported organisms on the RSAT Virtual Machine of the IFB cloud. The current version (June 2016) supports 1535 species, whose genomes were downloaded from various sources (EnsemblGenomes, NCBI).

3.1.2 2. Getting genes by name

We will now gather the genes involved in methionine metabolism and transport. In the yeast Saccharomyces cerevisiae, these genes are generally named with a prefix MET, followed by one or several numbers.

1. Under Genes and genomes, click Gene information.
2. In the Organism menu, select the species Saccharomyces cerevisiae.
3. In the Query box, enter ‘MET/d+’. This is a regular expression specifying that the gene name should contain the string MET followed by one or several digits ().
4. Click GO.

Query form of the gene-info tool.

After a few seconds, the result form should appear, a table with the genes whose name matched the query, followed by a table of links to the result files, and another table Next Step of possible tools for the next step of the analysis.

Result page of the gene-info tool.

3.1.3 3. Retrieving upstream sequences

1. In the Next step table of the gene-info result, click on the button retrieve sequence. The Retrieve sequence form is displayed, where the organism and gene query box have automatically been filled with the results of your gene-info query.

2. Leave all other parameteres unchanged and click GO. After a few seconds, the result page is displayed.

3. Optionally, in the table Result files, click on the link tot the sequence file (fasta), to inspect the result.

4. Come back to the retrieve-seq result page. In the Next step table which appears at the bottom of this result page, click on the button oligo-analysis.

3.1.4 4. Discovering over-represented k-mers in promoter sequences

oligo-analysis query form.

Primary result of oligo-analysis: list of over-represented k-mers.

Assembly of the over-represented k-mers detedted by oligo-analysis.

Position-specific matrices and logo representations of the motifs discovered. by oligo-analysis

3.1.5 5. Predicting binding sites in promoter sequences

Web form pf hte dna-pattern tool, which allows to scan sequences with string-based motifs (k-mers, consensuses, regular expressions, …).

Matching positions for the over-represented k-mers in the yeast MET genes

3.1.6 6. Displaying the predicted binding sites

Web form of the feature-map tool.

Feature map of the over-represented k-mers discovered by oligo-analysis and matched with dna-pattern in the previous steps. The putative transcription factor bindng sites, which are revealed by clumps of mutually overlapping k-mers, corresponding to different fragments of the motifs.