9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genome-Wide Identification of GRAS Gene Family and Their Responses to Abiotic Stress in Medicago sativa

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Alfalfa ( Medicago sativa) is a high-quality legume forage crop worldwide, and alfalfa production is often threatened by abiotic environmental stresses. GRAS proteins are important transcription factors that play a vital role in plant development, as well as in response to environmental stress. In this study, the availability of alfalfa genome “Zhongmu No.1” allowed us to identify 51 GRAS family members, i.e., MsGRAS. MsGRAS proteins could be classified into nine subgroups with distinct conserved domains, and tandem and segmental duplications were observed as an expansion strategy of this gene family. In RNA-Seq analysis, 14 MsGRAS genes were not expressed in the leaf or root, 6 GRAS genes in 3 differentially expressed gene clusters were involved in the salinity stress response in the leaf. Moreover, qRT-PCR results confirmed that MsGRAS51 expression was induced under drought stress and hormone treatments (ABA, GA and IAA) but down-regulated in salinity stress. Collectively, our genome-wide characterization, evolutionary, and expression analysis suggested that the MsGRAS proteins might play crucial roles in response to abiotic stresses and hormonal cues in alfalfa. For the breeding of alfalfa, it provided important information on stress resistance and functional studies on MsGRAS and hormone signaling.

          Related collections

          Most cited references68

          • Record: found
          • Abstract: found
          • Article: not found

          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            TBtools - an integrative toolkit developed for interactive analyses of big biological data

            The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                20 July 2021
                July 2021
                : 22
                : 14
                : 7729
                Affiliations
                [1 ]College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China; hanzhang003@ 123456cau.edu.cn (H.Z.); b20183040361@ 123456cau.edu.cn (X.L.); xuemeng.wang@ 123456cau.edu.cn (X.W.); sunmiir@ 123456cau.edu.cn (M.S.); ruisong2021@ 123456cau.edu.cn (R.S.)
                [2 ]Key Laboratory of Pratacultural Science, Beijing Municipality, China Agricultural University, Beijing 100193, China
                Author notes
                [* ]Correspondence: maops@ 123456cau.edu.cn (P.M.); shangang.jia@ 123456cau.edu.cn (S.J.); Tel.: +86-010-62733311 (P.M.); +86-010-62731451 (S.J.)
                Author information
                https://orcid.org/0000-0003-3261-0949
                https://orcid.org/0000-0002-3306-7637
                Article
                ijms-22-07729
                10.3390/ijms22147729
                8304046
                34299352
                e27e27bc-772a-485b-8b26-b35f91cee23a
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 31 May 2021
                : 16 July 2021
                Categories
                Article

                Molecular biology
                medicago sativa,gras genes,phylogeny,salinity and drought stresses,expression
                Molecular biology
                medicago sativa, gras genes, phylogeny, salinity and drought stresses, expression

                Comments

                Comment on this article