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      ERF4 and MYB52 transcription factors play antagonistic roles in regulating homogalacturonan de-methylesterification in Arabidopsis seed coat mucilage

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          Abstract

          Homogalacturonan (HG), a component of pectin, is synthesized in the Golgi apparatus in its fully methylesterified form. It is then secreted into the apoplast where it is typically de-methylesterified by pectin methylesterases (PME). Secretion and de-esterification are critical for normal pectin function, yet the underlying transcriptional regulation mechanisms remain largely unknown. Here, we uncovered a mechanism that fine-tunes the degree of HG de-methylesterification (DM) in the mucilage that surrounds Arabidopsis thaliana seeds. We demonstrate that the APETALA2/ETHYLENE RESPONSE FACTOR (AP2/ERF) transcription factor (TF) ERF4 is a transcriptional repressor that positively regulates HG DM. ERF4 expression is confined to epidermal cells in the early stages of seed coat development. The adhesiveness of the erf4 mutant mucilage was decreased as a result of an increased DM caused by a decrease in PME activity. Molecular and genetic analyses revealed that ERF4 positively regulates HG DM by suppressing the expression of three PME INHIBITOR genes (PMEIs) and SUBTILISIN-LIKE SERINE PROTEASE 1.7 (SBT1.7). ERF4 shares common targets with the TF MYB52, which also regulates pectin DM. Nevertheless, the erf4-2 myb52 double mutant seeds have a wild-type mucilage phenotype. We provide evidence that ERF4 and MYB52 regulate downstream gene expression in an opposite manner by antagonizing each other’s DNA-binding ability through a physical interaction. Together, our findings reveal that pectin DM in the seed coat is fine-tuned by an ERF4–MYB52 transcriptional complex.

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          Most cited references76

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          A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding

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            Floral dip: a simplified method forAgrobacterium-mediated transformation ofArabidopsis thaliana

            The Agrobacterium vacuum infiltration method has made it possible to transform Arabidopsis thaliana without plant tissue culture or regeneration. In the present study, this method was evaluated and a substantially modified transformation method was developed. The labor-intensive vacuum infiltration process was eliminated in favor of simple dipping of developing floral tissues into a solution containing Agrobacterium tumefaciens, 5% sucrose and 500 microliters per litre of surfactant Silwet L-77. Sucrose and surfactant were critical to the success of the floral dip method. Plants inoculated when numerous immature floral buds and few siliques were present produced transformed progeny at the highest rate. Plant tissue culture media, the hormone benzylamino purine and pH adjustment were unnecessary, and Agrobacterium could be applied to plants at a range of cell densities. Repeated application of Agrobacterium improved transformation rates and overall yield of transformants approximately twofold. Covering plants for 1 day to retain humidity after inoculation also raised transformation rates twofold. Multiple ecotypes were transformable by this method. The modified method should facilitate high-throughput transformation of Arabidopsis for efforts such as T-DNA gene tagging, positional cloning, or attempts at targeted gene replacement.
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              Is Open Access

              The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

              GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist.
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                Author and article information

                Contributors
                Journal
                The Plant Cell
                Oxford University Press (OUP)
                1532-298X
                February 01 2021
                April 17 2021
                December 14 2020
                February 01 2021
                April 17 2021
                December 14 2020
                : 33
                : 2
                : 381-403
                Affiliations
                [1 ]Key Laboratory of Tobacco Gene Resources, Tobacco Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Qingdao 266101, China
                [2 ]Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences (CAS), Qingdao 266101, China
                [3 ]Tobacco Breeding and Biotechnology Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, China
                [4 ]College of Agronomy, Qingdao Agricultural University, Qingdao 266109, China
                [5 ]Academy of Dongying Efficient Agricultural Technology and Industry on Saline and Alkaline Land in Collaboration with Qingdao Agricultural University, Dongying 257000, China
                [6 ]Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA
                Article
                10.1093/plcell/koaa031
                33709105
                cf669bb7-0cfb-4189-984e-eccc5214d7ac
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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