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Computational Prediction and Experimental Verification of HVA1-like Abscisic Acid Responsive Promoters in Rice (Oryza sativa)

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Abstract

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 barley HVA1 and it rice orthologue 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 a model 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 model has generated a partial list of genes in rice that have a high likelihood of being involved in the ABA signaling network. The ABA inducibility of some of the rice genes identified was validated with quantitative reverse transcription PCR (QPCR). By limiting our input data to known enhancer modules and experimentally derived rules, we have generated a high confidence subset of ABA-regulated genes. 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 transcription. The large fraction of putative regulatory genes carrying HVA1-like enhancer modules in their promoters suggests the ABA signal enters at multiple points into a complex regulatory network that remains largely unmapped.

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Acknowledgments

The authors are in debt to Dr. Robin Buell at the Institute of Genome Research for making the annotated rice data available to us. We would also like to thank Drs. Helen Wing, Eduardo Robleto and Brian Hedlund for reviewing this manuscript and Kate Shen for her technical advice on quantitative RT-PCR. We also appreciate the advice of Drs. Chih-Hsiang Ho and Roy Ogawa on statistical analyses. This work is supported by a NIH BRIN (P20RR016464) seed grant to Q.J. Shen, a NIH INBRE Grant (P20RR016463) to the Bioinformatics Core at UNLV, a UNLV start-up grant to Dr. Ronald Yasbin, and a UNLV Planning Initiative Award to Q.J. Shen, R. Ogawa and C. H. Ho.

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  1. Bioinformatics Core, Department of Biological Sciences, University of Nevada, Las Vegas, NV, 89154, USA

    Christian Ross & Qingxi J. Shen

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Correspondence to Qingxi J. Shen.

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Ross, C., Shen, Q.J. Computational Prediction and Experimental Verification of HVA1-like Abscisic Acid Responsive Promoters in Rice (Oryza sativa). Plant Mol Biol 62, 233–246 (2006). https://doi.org/10.1007/s11103-006-9017-y

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