Publication: Tissue-specific transcriptional regulation of seven heavy metal stress-responsive miRNAs and their putative targets in nickel indicator castor bean (R. communis L.) plants
Akdaş, Enes Yağız
ACADEMIC PRESS INC ELSEVIER SCIENCE, 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA
R.communis L. has high capability to accumulate nickel which is a trace nutrient for higher plants and also an environmental contaminant causes toxicity related symptoms at higher concentrations. MicroRNAs (miRNAs) are known to be important modulators of responses against heavy metal stress for detoxification of the metal. In this study, we experimentally measured and validated the transcript levels of the seven heavy metal stress response-related miRNAs and the expression levels of target genes in both leaf and root tissues of R. communis L. subjected to three different concentrations of nickel stress via qRT-PCR quantification. The results demonstrated differential regulations of heavy metal stress-responsive miRNAs and their putative targets in both tissues in same stress treatments. This dynamic regulation suggest that regulatory processes differ between the tissues under nickel stress. Our data suggest that, miR838 was the most responsive to the Ni2+ stress. miR398 target gene Cu-Zn/SOD was found to be up-regulated in both root and leaf tissues. The relations between TCP and expression levels of miR159 and miR319 were also found statistically significant exclusive to leaf tissues. In leaf tissue, changes in miR395 level and its putative target genes, sulphate transporter and sulphate adenyltransferase gene were found in relation whereas, only expression level of sulphate transporter represented a statistically significant relation in root tissue. The sharp decrease in transcript levels of 2r3 myb gene at lower nickel dose suggest to investigate the role of r2r3 myb and the all MYB family members in primary and secondary metabolisms against nickel stress.
Ricinus communis L, Nickel Tolerance, MiRNA, Tissue Specific Expression, qRT-PCR