Motif Mapper Version 3.2.1

VBA-WsH Author: Kenneth W Berendzen
Web page and content: Kenneth W Berendzen
Date: Copyright 2002 - 2004, Max-Planck Institute for Breeding Research, Cologne Germany.

Short Description:

Motif Mapper is ideal for the Frequency and Distribution Analysis of elements in:

• Genomic pseudomolecules (i.e. chromosomes)
  
• Specific sequence sets (e.g. promoters) including frequency-distribution curves
  

The Motif Mapper VBA-WsH package is an association of independent scripts to assist in the analysis of the distribution and frequency of DNA elements. The scripts are are command line driven and written in the Visual Basic and Windows Scripting language recognized by the Microsoft Word's Macro Compiler (Editor). All output and input files are ASCII-text files whose data can be manipulated and viewed using array based spreadsheet applications.

Usage Introduction

Motif Mapper is a tool for frequency analysis. Frequency analysis is the study of how often a particular motif occurs in a specific sequence set.

In other words, you can ask and answer these questions :

• How often does my motif occur in the genome I am studying?
• How often does my motif occur in the set of promoters that I am studying?
• How often does the motif occur in other data sets?
• Where in my promoter(s) do my motifs occur relative to the ATG, to the transcription start site or to another element (dyad analysis)?

Suggested data sets

• Known network pathway promoters
• Promoter sets of interest
• Random Promoter sets
• exons, intons, UTRs
• first intron, exon; second intron, exon, etc.
• intons in UTRs
• intergenic regions

The advantage of learning Motif Mapper.

Motif Mapper handles multiple data sets against a lists of motif queries. The limit of the number of files and the number of queries is up to you. This approach allows one to screen different sequence sets with the same group of motifs. There are two output files, one for each motif and sequence and a summary file which considers the entire data set together as one. The frequency output from Motif Mapper is precise and can be used to compare different sets effectively. By comparing different sequence sets, you establish a biological statistic instead of relying on a mathematical approximation.

Since long lists of motifs can be used to query sequence sets one can think about conducting mutation or permutation analysis. For example, you have a motif and would like to know what is the probability of there being an "A" at the 5' flank compared to the other three nucleotides you could enter four motifs with each of the four DNA nucleotides at the 5' end and check to see. Motif Mapper comes with some computational tools for conducting permutation/mutation analysis under the MotifList_Generator Module.

Defining motifs

Identifying motifs is not an easy task. Often information is lacking and only very well characterized elements can be trusted to be functional. If you have a set of promoters that you feel should be co-regulated one can try MEME, but we highly recommend the pattern discovery programs from Regulatory Sequence Analysis Tools (RSAT). RSAT is the most sophisticated frequency based analysis tool available. If you work with plants, then you might want to examine the cis-element databases that are routinely maintained; PLACE is an excellent source as is PlantCARE. Other cis-element sources can be found under External Links from TAIR.

Establishing significance

1. Trust the significance values provided by the programs you used to identify motifs. It is up to you to read up on everything you can find explaining what the statistics mean.

2. Consider known biological information, does it make sense as to what type of motifs have been discovered? Is there an element that is missing that you know has a conserved function in at least some of the promoters you are analyzing? Are your search criteria too stringent or have you excluded DNA regions that may contain the elements you are looking for? If so, go back and repeat with either less stringent screening parameters or maybe you should take more flanking sequence and annotate by hand. MMfasta and MMGraphicP allows you to map elements from FASTA formatted sequences. Example output from MMfasta is included in the Getting Started page.

3. For elements that are quite frequent, then you might consider making frequency-distribution curves with IUPAC words or a Position Point Matrix, or looking for linked motifs by indulging dyad analysis. Or, you might also want to experiment with mutation analysis to see what changes occur in the curve shape.

4. Establish your own statistic with assistance from Motif Mapper.

Final Word

Motif Mapper was created to be modular, simple and as flexible as possible so that the effectiveness is dependent on what questions you ask and how you go about answering them. Give yourself time to get used to the package setup. If there are any suggestions, questions, comments or contributions please contact me.