Insight into Differential Responses of Upland and Paddy Rice to Drought Stress by Comparative Expression Profiling Analysis
AbstractIn this study, the drought responses of two genotypes, IRAT109 and Zhenshan 97 (ZS97), representing upland and paddy rice, respectively, were systematically compared at the morphological, physiological and transcriptional levels. IRAT109 has better performance in traits related to drought avoidance, such as leaf rolling, root volumes, the ratio of leaf water loss and relative conductivity. At the transcriptional level, more genes were induced by drought in IRAT109 at the early drought stage, but more genes had dynamic expression patterns in ZS97 at different drought degrees. Under drought conditions, more genes related to reproductive development and establishment of localization were repressed in IRAT109, but more genes involved in degradation of cellular components were induced in ZS97. By checking the expression patterns of 36 drought-responsive genes (located in 14 quantitative trail loci [QTL] intervals) in ZS97, IRAT109 and near isogenic lines (NILs) of the QTL intervals, we found that more than half of these genes had their expression patterns or expression levels changed in the NILs when compared to that in ZS97 or IRAT109. Our results may provide valuable information for dissecting the genetic bases of traits related to drought resistance, as well as for narrowing the candidate genes for the traits. View Full-Text
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Ding, X.; Li, X.; Xiong, L. Insight into Differential Responses of Upland and Paddy Rice to Drought Stress by Comparative Expression Profiling Analysis. Int. J. Mol. Sci. 2013, 14, 5214-5238.
Ding X, Li X, Xiong L. Insight into Differential Responses of Upland and Paddy Rice to Drought Stress by Comparative Expression Profiling Analysis. International Journal of Molecular Sciences. 2013; 14(3):5214-5238.Chicago/Turabian Style
Ding, Xipeng; Li, Xiaokai; Xiong, Lizhong. 2013. "Insight into Differential Responses of Upland and Paddy Rice to Drought Stress by Comparative Expression Profiling Analysis." Int. J. Mol. Sci. 14, no. 3: 5214-5238.