| Abstract Detail
Modeling and Computational Biology Ross, Christian [1], Inzunza, Jose [1], Shen, Jeff [2]. Computational Prediction of Abscisic Acid Responsive Promoters in Rice (Oryza sativa). Abscisic acid (ABA) is one of the central plant hormones, responsible for controlling both maturation and germination in seeds, as well as mediating adaptive responses to desiccation, injury, and pathogen infection in vegetative tissues. Thorough analyses of two barley genes, HVA1 and HVA22, indicate that their response to ABA relies on the interaction of two cis-acting elements in their promoters, an ABA response element (ABRE) and a coupling element (CE). Together, they form an ABA response promoter complex (ABRC). Comparison of promoters of the barley ABA inducible genes and it rice orthologues indicates that the structures and sequences of their ABRCs are highly similar. Prediction of ABA responsive genes in the rice genome is then tractable to a bioinformatics approach based on the structures of the well-defined barley ABRCs. Here we describe models developed based on the consensus, inter-element spacing and orientations of experimentally determined ABREs and CEs. Our search of the rice promoter database for promoters that fit the models has generated a partial list of genes in rice that have a high likelihood of being involved in the ABA signaling network. The results suggest that the pathways by which cereals respond to biotic and abiotic stresses overlap significantly, and that regulation is not confined to the level of transcription. The large fraction of putative regulatory genes carrying HVA1- and HVA22-like enhancer modules in their promoters suggests the ABA signal enters at multiple points into a complex regulatory network that remains largely unmapped.
Log in to add this item to your schedule
Related Links:
Shen Webpage
1 - University of Nevada, School of Life Sciences
2 - University of Nevada, School of Life Sciences, 4505 Maryland Pkwy, Las Vegas, NV, 89154, USA
Keywords:
bioinformatics
rice
ABA
Signaling network
abiotic and biotic stresses
modeling.
Presentation Type: Plant Biology Abstract
Session: P
Location: Exhibit Hall (Northeast, Southwest & Southeast)/Hilton
Date: Sunday, July 8th, 2007
Time: 8:00 AM
Number: P41002
Abstract ID:108 |
