Back

Identification and characterization of a biphasic/bidirectional wound-inducible RHA3B gene promoter from Arabidopsis thaliana

Rao, V.; Virupapuram, V.

2021-01-28 plant biology
10.1101/2021.01.28.428589 bioRxiv
Show abstract

Conditional promoters such as wound inducible are important tools for plant biotechnology to selectively express agronomically important genes. From a set of Enhancer trap (DsE-uidA) transposant lines we identified wound inducible ET1075 line by injuring leaf blade and screening for Ds linked GUS gene expression. Earliest GUS stain detected at petiolar region at 2hrs post injury with a progressive attainment of maximum visual intensity between 12 and 24hrs wherein, the transcript expression induced in a bidirectional manner. DsE was found to be inserted in the intergenic region between AT4G35480 and AT4G35490. To find the essential transcriptional regulatory region, deletion constructs comprising upstream sequences of pRHA3B fused to GUS reporter gene were functionally tested in Arabidopsis plants by generating stable transgenics. A 481 bp of upstream sequence from ATG is found to be sufficient to promote wound inducible gene expression. Sequence analysis revealed the presence of several regulatory elements implicated in wound inducible gene expression. Comparative analysis with similar wound inducible promoters revealed the presence of common cis-regulatory elements. This promoter can essentially be used in pest control and in molecular pharming to conditionally express agronomically/commercially important genes in plants. HighlightsO_LIDsE enhancer trap transposant lines were generated. C_LIO_LIIdentified a novel wound inducible promoter line ET1075. C_LIO_LIWound inducible promoter pRHA3B is bidirectional and induces the expression of RHA3B and MRPL11 genes. C_LIO_LIWound responsive key cis-elements WRKY, W-box, FORCA are present in the pRHA3B promoter. C_LI

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.