Transcriptional and physiological study of the response of Burma mangrove (Bruguiera gymnorhiza) to salt and osmotic stress
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We investigated the transcriptional response of Burma mangrove (Bruguiera gymnorhiza) to high salinity (salt stress; 500 mM NaCl) and hyperosmotic stress (osmotic stress; 1 M sorbitol) by microarray analysis. ANOVA (P < 0.05) and significant analysis of microarray (SAM; FDR < 5%) revealed that 865 of 11,997 genes showed significant differential expression under salt and osmotic stress. Scatter plot analysis revealed that the expression level of genes changed at 6 h after salt stress treatment, but recovered at 24 h, while the change at 6 h after osmotic stress treatment diverged at 24 h. Hierarchical clustering of the 865 genes showed that expression profiles under salt stress were distinctly different from those under osmotic stress. Comparison of gene ontology (GO) categories of differentially expressed genes under the stress conditions revealed that the adaptation of Burma mangrove to salt stress was accompanied by the up-regulation of genes categorized for “cell communication,” “signal transduction,” “lipid metabolic process,” “photosynthesis,” “multicellular organismal development,” and “transport,” and by down-regulation of genes categorized for “catabolic process.” Burma mangrove maintained its leaf water potential and recovered from its photosynthesis rate that declined temporarily under salt stress, but not under osmotic stress. These results demonstrated a fundamental difference between the response to salt and osmotic stress. Ion and sugar content analysis suggested that salt tolerance of Burma mangrove might be attributed to their ability to accumulate high concentrations of Na+ and Cl−, even under non-stressed conditions; to uptake additional Na+ and Cl− for use as osmolytes; and to maintain K+ homeostasis under salt stress.
KeywordsBurma mangrove Gene ontology analysis Microarray Osmotic stress Salt tolerance Transcriptional response
Analysis of variance
Expressed sequence tag
False discovery rate
Significant analysis of microarray
We thank Noriko Someya for her excellent technical assistance. This work was supported by MEXT (the Ministry of Education, Culture, Sports, Science and Technology of Japan), “University-Industry Joint Research” Project 2003–2007.
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