Abstract
Drought tolerance (DT) in rice is known to be controlled by many quantitative trait loci (QTLs) and involved differential expression of large numbers of genes, but linking QTLs with their underlying genes remains the most challenging issue in plant molecular biology. To shed some light on this issue, differential gene expression in response to PEG simulated drought in 3 unique genetic materials (a lowland rice, IR64 and its derived line, PD86 which has 11 introgressed DT QTLs, and a upland rice IRAT109) was investigated using a PCR-based subtractive hybridization strategy. More than 300 unique subtracted cDNA sequences, covering genes of diverse cellular activities and functions, were identified and confirmed by semi-quantitative and quantitative RT-PCR. Detailed bioinformatics analyses of the data revealed two interesting results. First, the levels and mechanisms of DT of the three rice lines were associated with the number and types of differentially expressed genes, suggesting different DT mechanisms in rice are controlled by different sets of genes and different metabolic pathways, and most differentially expressed genes under drought were able to contribute to DT. Second, there appeared a high correspondence in genomic location between DT QTLs and clusters of differentially expressed genes in rice, suggesting some DT QTLs may represent clusters of co-regulated and functionally related genes. Thus, differential gene expression analyses using genetically characterized materials can provide additional insights into the molecular basis of QTLs and convergent evidence to shortlist the candidate genes for target QTLs.
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This study was supported by the National 973 project of Chinese Ministry of Science and Technology (grant no. 2003CB114308) and by a grant (#2005 FS029) from the Rockefeller Foundation.
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Communicated by J.-K. Zhu.
Bin-Ying Fu and Jian-Hua Xiong are contributed to this work equally.
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Fu, BY., Xiong, JH., Zhu, LH. et al. Identification of functional candidate genes for drought tolerance in rice. Mol Genet Genomics 278, 599–609 (2007). https://doi.org/10.1007/s00438-007-0276-3
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DOI: https://doi.org/10.1007/s00438-007-0276-3