Word-based characterization of promoters involved in human DNA repair pathways.
BACKGROUND
DNA repair genes provide an important contribution towards the surveillance and repair of DNA damage. These genes produce a large network of interacting proteins whose mRNA expression is likely to be regulated by similar regulatory factors. Full characterization of promoters of DNA repair genes and the similarities among them will more fully elucidate the regulatory networks that activate or inhibit their expression. To address this goal, the authors introduce a technique to find regulatory genomic signatures, which represents a specific application of the genomic signature methodology to classify DNA sequences as putative functional elements within a single organism.


RESULTS
The effectiveness of the regulatory genomic signatures is demonstrated via analysis of promoter sequences for genes in DNA repair pathways of humans. The promoters are divided into two classes, the bidirectional promoters and the unidirectional promoters, and distinct genomic signatures are calculated for each class. The genomic signatures include statistically overrepresented words, word clusters, and co-occurring words. The robustness of this method is confirmed by the ability to identify sequences that exist as motifs in TRANSFAC and JASPAR databases, and in overlap with verified binding sites in this set of promoter regions.


CONCLUSIONS
The word-based signatures are shown to be effective by finding occurrences of known regulatory sites. Moreover, the signatures of the bidirectional and unidirectional promoters of human DNA repair pathways are clearly distinct, exhibiting virtually no overlap. In addition to providing an effective characterization method for related DNA sequences, the signatures elucidate putative regulatory aspects of DNA repair pathways, which are notably under-characterized.
Lichtenberg
Jens
J
Bioinformatics Laboratory, School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio, USA. lichtenj@ohio.edu
Jacox
Edwin
E
Welch
Joshua D
JD
Kurz
Kyle
K
Liang
Xiaoyu
X
Yang
Mary Qu
MQ
Drews
Frank
F
Ecker
Klaus
K
Lee
Stephen S
SS
Elnitski
Laura
L
Welch
Lonnie R
LR
D001482:Base Composition; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D004260:DNA Repair; D030541:Databases, Genetic; D006801:Humans; D015233:Models, Statistical; D011401:Promoter Regions, Genetic