Dataset Information

Interactions and CCAAT-binding of Arabidopsis thaliana NF-Y subunits.

ABSTRACT:

Background

NF-Y is a transcription factor that recognizes with high specificity and affinity the widespread CCAAT box promoter element. It is formed by three subunits: NF-YA and the NF-YB/NF-YC- heterodimer containing histone fold domains (HFDs). We previously identified a large NF-Y gene family in Arabidopsis thaliana, composed of 29 members, and characterized their expression patterns in various plant tissues.

Methods

We used yeast Two-hybrids assays (Y2H), pull-down and Electrophoretic Mobility Shift Assay (EMSA) in vitro experiments with recombinant proteins to dissect AtNF-YB/AtNF-YC interactions and DNA-binding with different AtNF-YAs.

Results

Consistent with robust conservation within HFDs, we show that heterodimerization is possible among all histone-like subunits, including the divergent and related LEC1/AtNF-YB9 and L1L/AtNF-YB6 required for embryo development. DNA-binding to a consensus CCAAT box was investigated with specific AtNF-YB/AtNF-YC combinations and observed with some, but not all AtNF-YA subunits.

Conclusions

Our results highlight (i) the conserved heterodimerization capacity of AtNF-Y histone-like subunits, and (ii) the different affinities of AtNF-YAs for the CCAAT sequence. Because of the general expansion of NF-Y genes in plants, these results most likely apply to other species.

SUBMITTER: Calvenzani V

PROVIDER: S-EPMC3422339 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Interactions and CCAAT-binding of Arabidopsis thaliana NF-Y subunits.

Calvenzani Valentina V Testoni Barbara B Gusmaroli Giuliana G Lorenzo Mariangela M Gnesutta Nerina N Petroni Katia K Mantovani Roberto R Tonelli Chiara C

PloS one 20120817 8

<h4>Background</h4>NF-Y is a transcription factor that recognizes with high specificity and affinity the widespread CCAAT box promoter element. It is formed by three subunits: NF-YA and the NF-YB/NF-YC- heterodimer containing histone fold domains (HFDs). We previously identified a large NF-Y gene family in Arabidopsis thaliana, composed of 29 members, and characterized their expression patterns in various plant tissues.<h4>Methods</h4>We used yeast Two-hybrids assays (Y2H), pull-down and Electro ...[more]

PMID: 22912760

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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

Interactions and CCAAT-binding of Arabidopsis thaliana NF-Y subunits.

Background

Methods

Results

Conclusions

Publications

Interactions and CCAAT-binding of Arabidopsis thaliana NF-Y subunits.

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