Dataset Information

In vivo evidence for homo- and heterodimeric interactions of Arabidopsis thaliana dehydrins AtCOR47, AtERD10, and AtRAB18.

ABSTRACT: Dehydrins (DHNs) are intrinsically disordered proteins that play central roles in plant abiotic stress responses; however, how they work remains unclear. Herein, we report the in planta subcellular localization of Arabidopsis thaliana DHNs AtCOR47, AtERD10, and AtRAB18 through GFP translational fusions. To explore the dimerization ability of the Arabidopsis acidic DHNs AtCOR47 and AtERD10, we conducted an in planta DHN binding assay using the Bimolecular Fluorescence Complementation (BiFC) technique. Our analyses revealed homodimeric interactions for AtCOR47 and AtERD10; interestingly, heterodimeric associations also occurred with these DHNs, and these interactions were observed in the cytosol of tobacco cells. Furthermore, we evaluated whether Arabidopsis basic DHNs, such as AtRAB18, could also interact with itself and/or with AtCOR47 and AtERD10 in the BiFC system. Our data revealed homodimeric RAB18 complexes in the nucleus and cytosol, while heterodimeric associations between AtRAB18 and acidic DHNs occurred only in the cytosol. Finally, we demonstrated the presence of heterodimeric complexes among Arabidopsis AtCOR47, AtERD10, and AtRAB18 DHNs with their acidic ortholog the OpsDHN1 from Opuntia streptacantha; these heterodimeric interactions showed different subcellular distributions. Our results guide DHN research toward a new scenario where DHN/DHN oligomerization could be explored as a part of their molecular mechanism.

SUBMITTER: Hernandez-Sanchez IE

PROVIDER: S-EPMC5719087 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

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In vivo evidence for homo- and heterodimeric interactions of Arabidopsis thaliana dehydrins AtCOR47, AtERD10, and AtRAB18.

Hernández-Sánchez Itzell E IE Maruri-López Israel I Graether Steffen P SP Jiménez-Bremont Juan F JF

Scientific reports 20171206 1

Dehydrins (DHNs) are intrinsically disordered proteins that play central roles in plant abiotic stress responses; however, how they work remains unclear. Herein, we report the in planta subcellular localization of Arabidopsis thaliana DHNs AtCOR47, AtERD10, and AtRAB18 through GFP translational fusions. To explore the dimerization ability of the Arabidopsis acidic DHNs AtCOR47 and AtERD10, we conducted an in planta DHN binding assay using the Bimolecular Fluorescence Complementation (BiFC) techn ...[more]

PMID: 29213048

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Project description:Prediction of transcriptional regulatory mechanisms in Arabidopsis has become increasingly critical with the explosion of genomic data now available for both gene expression and gene sequence composition. We have shown in previous work 1, that a combination of correlation measurements and cis-regulatory element (CRE) detection methods are effective in predicting targets for candidate transcription factors for specific case studies which were validated. However, to date there has been no quantitative assessment as to which correlation measures or CRE detection methods used alone or in combination are most effective in predicting TF-->target relationships on a genome-wide scale.We tested several widely used methods, based on correlation (Pearson and Spearman Rank correlation) and cis-regulatory element (CRE) detection (>or=1 CRE or CRE over-representation), to determine which of these methods individually or in combination is the most effective by various measures for making regulatory predictions. To predict the regulatory targets of a transcription factor (TF) of interest, we applied these methods to microarray expression data for genes that were regulated over treatment and control conditions in wild type (WT) plants. Because the chosen data sets included identical experimental conditions used on TF over-expressor or T-DNA knockout plants, we were able to test the TF-->target predictions made using microarray data from WT plants, with microarray data from mutant/transgenic plants. For each method, or combination of methods, we computed sensitivity, specificity, positive and negative predictive value and the F-measure of balance between sensitivity and positive predictive value (precision). This analysis revealed that the >or=1 CRE and Spearman correlation (used alone or in combination) were the most balanced CRE detection and correlation methods, respectively with regard to their power to accurately predict regulatory-target interactions.These findings provide an approach and guidance for researchers interested in predicting transcriptional regulatory mechanisms using microarray data that they generate (or microarray data that is publically available) combined with CRE detection in promoter sequence data.

Dataset Information

In vivo evidence for homo- and heterodimeric interactions of Arabidopsis thaliana dehydrins AtCOR47, AtERD10, and AtRAB18.

Publications

In vivo evidence for homo- and heterodimeric interactions of Arabidopsis thaliana dehydrins AtCOR47, AtERD10, and AtRAB18.

Similar Datasets

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