Transcriptional regulation of protein complexes and biological pathways
Title | Transcriptional regulation of protein complexes and biological pathways |
Publication Type | Journal Articles |
Year of Publication | 2003 |
Authors | Hannenhalli S, Levy S |
Journal | Mammalian Genome |
Volume | 14 |
Issue | 9 |
Pagination | 611 - 619 |
Date Published | 2003/// |
ISBN Number | 0938-8990 |
Abstract | The cis-element profile (or cis-profile) of a gene refers to the collection of transcription factor binding sites (TFBS) regulating the transcription of the gene. Underlying the various published studies that attempt to discover cis-elements in the vicinity of co-expressed genes via pattern detection algorithms, there is an implicit assumption that a correlation exists between co-expressed genes and their cis-profiles. In this study, we show that the cis-similarity, defined as the proportion of shared TFBS between two cis-element profiles, is higher for functionally linked interacting proteins as well as for members of a signal transduction pathway. A similar analysis of the enzymes catalyzing the conversion of adjacent substrates to products in a collection of metabolic pathways, did not reveal higher cis-similarity. The analysis is based on three distinct sources of publicly available data, namely, 1) the BIND database of interacting proteins, 2) known interactions in NMDAR protein complex, 3) the apoptosis pathway and nine pathways related to metabolism of cofactors and vitamins all from KEGG. Additionally, we analyze the cis-element profiles of all the genes in the glutamate receptor (GR) sub-complex of NMDAR complex to detect a set of cis-elements that occur adjacent to a majority of the genes. We show that most of the corresponding transcription factors are known to be involved in GR regulation by comparing our findings with the published biomedical literature. In addition, we were able to detect transcripts whose gene products associate with GR by searching for transcripts that share the same regulatory signals as those detected for GR. This suggests a novel computational methodology for constructing high-order gene regulatory models and detecting co-regulated gene products. |
URL | http://dx.doi.org/10.1007/s00335-002-2260-x |