STIFDB - Stress responsive TranscrIption Factor Database is a specialized database that provides information about various Stress responsive genes and Stress inducible Transcription Factor related information from Arabidopsis thaliana.
STIFDB is an online resource of Abiotic Stress Gene Regulation in Arabidopsis, a comprehensive collection of abiotic stress responsive genes in Arabidopsis thaliana, with options to identify probable Transcription Factor Binding Sites in their promoters. In the response to abiotic stresses like drought, cold, salinity, high light, heat, etc, ten specific families of transcription factors are known to be involved. HMM-based models are used to identify binding sites of transcription factors belonging to these families. We have also consulted literature reports to cross-validate the Transcription Factor Binding Sites predicted by the method.
Transcriptional regulation of genes in response to abiotic stresses like drought, cold, salinity, high light, ABA, oxidative stress etc. is an emerging area of plant research.
Stress responsive transcription factors in Arabidopsis are known to belong to AP2/EREBP, ABI3/VP1, ARF, bHLH, bZIP, HB, HSF, MYB, NAC and WRKY families of factors. Transcription factors belonging to different families recognize specific core sequences on the promoters of various stress responsive functional genes, for binding and further transcriptional activation of these target genes. The core binding sites/cis elements to which members of a transcription factor family bind have been characterized. Scanning the abiotic stress responsive promoterome of Arabidopsis for the presence of these cis elements could be of interest in studies on the abiotic stress responses of plants.
STIFDB Data Curation:
STIFDB - The database of stress responsive genes has been compiled from microarray expression data extracted from public microarray databases like NASC Array, DRASTIC, RARGE-MAEDA etc. We have used the STIF method to identify all possible abiotic stress responsive transcription factor binding sites. This database provides an option of scanning the 100bp and 1000bp promoters along with their 5'UTR of known stress responsive genes, for the presence of cis elements identified by stress responsive transcription factors.
A computational method, STIF, has been developed to search for potential transcription factor binding sites of stress-specific transcription factors, starting from Hidden Markov Models of nucleotide binding site patterns of cis-elements that are well-known to respond during stress situations in plants. The 19 models of cis-elements, based on abiotic stress transcription factor families, were built as Hidden Markov Models and were validated using Jackknifing method. We had applied our HMM-based search algorithm, STIF, to search 100 base pairs upstream of the gene with its 5’UTR. We identified 60 abiotic stress genes from well-known microarray databases based on the high stress-induced expression profiles. These genes were known to be upregulated during stress and their validated TFBS information is also clearly available. To evaluate the method further, we also searched against 1000 base pairs with its 5’UTR.
Flowchart of STIF algorithm: