De Novo Identification of Regulatory Regions in Intergenic Spaces of Prokaryotic Genomes
This project was begun to implement, test, and experimentally validate the results of a novel algorithm for genome-wide identification of candidate transcription-factor binding sites in prokaryotes. Most techniques used to identify regulatory regions rely on conservation between different genomes or have a predetermined sequence motif(s) to perform a genome-wide search. Therefore, such techniques cannot be used with new genome sequences, where information regarding such motifs has not yet been discovered. This project aimed to apply a de novo search algorithm to identify candidate binding-site motifs in intergenic regions of prokaryotic organisms, initially testing the available genomes of the Yersinia genus. We retrofitted existing nucleotide pattern-matching algorithms, analyzed the candidate sites identified by these algorithms as well as their target genes to screen for meaningful patterns. Using properly annotated prokaryotic genomes, this project aimed to develop a set of procedures to identify candidate intergenic sites important for gene regulation. We planned to demonstrate this in Yersinia pestis, a model biodefense, Category A Select Agent pathogen, and then follow up with experimental evidence that these regions are indeed involved in regulation. The ability to quickly characterize transcription-factor binding sites will help lead to a better understanding of how known virulence pathways are modulated in biodefense-related organisms, and will help our understanding and exploration of regulons--gene regulatory networks--and novel pathways for metabolic processes in environmental microbes.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 902275
- Report Number(s):
- UCRL-TR-228471
- Country of Publication:
- United States
- Language:
- English
Similar Records
Genome Scale Identification of Regulons
PhyloScan: identification of transcription factor binding sites using cross-species evidence
RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach
Conference
·
Tue Jun 22 00:00:00 EDT 2004
·
OSTI ID:15017447
PhyloScan: identification of transcription factor binding sites using cross-species evidence
Journal Article
·
Sun Dec 31 19:00:00 EST 2006
· Algorithms for Molecular Biology
·
OSTI ID:1626632
RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach
Journal Article
·
Wed May 26 00:00:00 EDT 2010
· Nucleic Acids Research
·
OSTI ID:986246