DNA and protein sequences digitally store information about biological function in a complex code that is not yet fully understood. The fundamental unit of this code is the sequence motif, which is defined as a small, recurring DNA or protein sequence pattern. A DNA motif might be involved, for example, in turning on or off the transcription of a gene in response to environmental cues. A protein motif might encode the properties of the binding site that allows the protein to carry out its function. The MEME Suite of motif-based sequence analysis software builds statistical models of DNA and protein motifs, allowing biologists to discover novel motifs, to search for new instances of known motifs, and to compare motifs to one another. This proposal continues to develop and maintain the MEME Suite, which is in regular use by biologists around the world.
The aims of this work are five-fold: (1) to increase the accessiblity, usability and interoperability of the MEME Suite, (2) to expand the MEME Suite to handle epigenetic data regarding histone modifications, methylation, nucleosome positioning and DNaseI hypersensitive sites, (3) to integrate a variety of existing motif-based software tools into the MEME Suite, (4) to augment the algorithms used by the MEME Suite with proven enhancements, and (5) to continue to improve our user support services.

Public Health Relevance

This project will improve existing, widely used software that enables biologists to understand how DNA and protein sequences encode information about biological function. Identifying and accurately char- acterizing functional sequence motifs allows scientists to understand how genes are turned on and off and how proteins carry out their functions in the cell. Such knowledge is fundamental to any model of the basic molecular mechanisms of the cell, and in particular, for molecular-scale models of disease processes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
8R01GM103544-08
Application #
8324604
Study Section
Special Emphasis Panel (ZRG1-BST-Q (01))
Program Officer
Ravichandran, Veerasamy
Project Start
2009-09-28
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2014-08-31
Support Year
8
Fiscal Year
2012
Total Cost
$325,930
Indirect Cost
$69,912
Name
University of Washington
Department
Genetics
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Ma, Wenxiu; Noble, William S; Bailey, Timothy L (2014) Motif-based analysis of large nucleotide data sets using MEME-ChIP. Nat Protoc 9:1428-50
Lesluyes, Tom; Johnson, James; Machanick, Philip et al. (2014) Differential motif enrichment analysis of paired ChIP-seq experiments. BMC Genomics 15:752
Tanaka, Emi; Bailey, Timothy L; Keich, Uri (2014) Improving MEME via a two-tiered significance analysis. Bioinformatics 30:1965-73