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      Genome-Wide Analysis of the GRAS Gene Family and Functional Identification of GmGRAS37 in Drought and Salt Tolerance

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          Abstract

          GRAS genes, which form a plant-specific transcription factor family, play an important role in plant growth and development and stress responses. However, the functions of GRAS genes in soybean ( Glycine max) remain largely unknown. Here, 117 GRAS genes distributed on 20 chromosomes were identified in the soybean genome and were classified into 11 subfamilies. Of the soybean GRAS genes, 80.34% did not have intron insertions, and 54 pairs of genes accounted for 88.52% of duplication events (61 pairs). RNA-seq analysis demonstrated that most GmGRASs were expressed in 14 different soybean tissues examined and responded to multiple abiotic stresses. Results from quantitative real-time PCR analysis of six selected GmGRASs suggested that GmGRAS37 was significantly upregulated under drought and salt stress conditions and abscisic acid and brassinosteroid treatment; therefore, this gene was selected for further study. Subcellular localization analysis revealed that the GmGRAS37 protein was located in the plasma membrane, nucleus, and cytosol. Soybean hairy roots overexpressing GmGRAS37 had improved resistance to drought and salt stresses. In addition, these roots showed increased transcript levels of several drought‐ and salt-related genes. The results of this study provide the basis for comprehensive analysis of GRAS genes and insight into the abiotic stress response mechanism in soybean.

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          Most cited references61

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            MEME Suite: tools for motif discovery and searching

            The MEME Suite web server provides a unified portal for online discovery and analysis of sequence motifs representing features such as DNA binding sites and protein interaction domains. The popular MEME motif discovery algorithm is now complemented by the GLAM2 algorithm which allows discovery of motifs containing gaps. Three sequence scanning algorithms—MAST, FIMO and GLAM2SCAN—allow scanning numerous DNA and protein sequence databases for motifs discovered by MEME and GLAM2. Transcription factor motifs (including those discovered using MEME) can be compared with motifs in many popular motif databases using the motif database scanning algorithm Tomtom. Transcription factor motifs can be further analyzed for putative function by association with Gene Ontology (GO) terms using the motif-GO term association tool GOMO. MEME output now contains sequence LOGOS for each discovered motif, as well as buttons to allow motifs to be conveniently submitted to the sequence and motif database scanning algorithms (MAST, FIMO and Tomtom), or to GOMO, for further analysis. GLAM2 output similarly contains buttons for further analysis using GLAM2SCAN and for rerunning GLAM2 with different parameters. All of the motif-based tools are now implemented as web services via Opal. Source code, binaries and a web server are freely available for noncommercial use at http://meme.nbcr.net.
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              PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences.

              M. Lescot (2002)
              PlantCARE is a database of plant cis-acting regulatory elements, enhancers and repressors. Regulatory elements are represented by positional matrices, consensus sequences and individual sites on particular promoter sequences. Links to the EMBL, TRANSFAC and MEDLINE databases are provided when available. Data about the transcription sites are extracted mainly from the literature, supplemented with an increasing number of in silico predicted data. Apart from a general description for specific transcription factor sites, levels of confidence for the experimental evidence, functional information and the position on the promoter are given as well. New features have been implemented to search for plant cis-acting regulatory elements in a query sequence. Furthermore, links are now provided to a new clustering and motif search method to investigate clusters of co-expressed genes. New regulatory elements can be sent automatically and will be added to the database after curation. The PlantCARE relational database is available via the World Wide Web at http://sphinx.rug.ac.be:8080/PlantCARE/.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                23 December 2020
                2020
                : 11
                : 604690
                Affiliations
                [1] 1College of Agriculture, Yangtze University , Jingzhou, China
                [2] 2Hubei Collaborative Innovation Center for Grain Industry, Yangtze University , Jingzhou, China
                [3] 3Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, Yangtze University , Jingzhou, China
                [4] 4Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/National Key Facility for Crop Gene Resources and Genetic Improvement, Key Laboratory of Biology and Genetic Improvement of Triticeae Crops, Ministry of Agriculture , Beijing, China
                [5] 5Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences , Chengdu, China
                [6] 6State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University , Yangling, China
                Author notes

                Edited by: Magdalena Arasimowicz-Jelonek, Adam Mickiewicz University, Poland

                Reviewed by: Qibin Ma, South China Agricultural University, China; Marcelo Nogueira Do Amaral, Federal University of Pelotas, Brazil

                *Correspondence: Zhao-Shi Xu, xuzhaoshi@ 123456caas.cn

                These authors have contributed equally to this work

                This article was submitted to Plant Abiotic Stress, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2020.604690
                7793673
                33424904
                281eacd0-e0e7-4232-846f-aff579c810f4
                Copyright © 2020 Wang, Yu, Fu, Su, Chen, Zhou, Chen, Guo, Ma, Wei and Xu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 10 September 2020
                : 23 November 2020
                Page count
                Figures: 13, Tables: 1, Equations: 0, References: 61, Pages: 19, Words: 9336
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 31871624
                Funded by: National Transgenic Key Project of the Ministry of Agriculture of China
                Award ID: SQ2019ZD080113
                Funded by: China Postdoctoral Science Foundation 10.13039/501100002858
                Award ID: 2019M660886
                Funded by: Fundamental Research Funds for Central Non-Profit of Institute of Crop Sciences, Chinese Academy of Agricultural Sciences
                Award ID: Y2020PT12
                Award ID: S2020ZC02
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                gras protein,genome-wide analysis,abiotic stress,hairy root assay,soybean
                Plant science & Botany
                gras protein, genome-wide analysis, abiotic stress, hairy root assay, soybean

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