8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      RNA sequencing and de novo assembly of Solanum trilobatum leaf transcriptome to identify putative transcripts for major metabolic pathways

      research-article
      , ,
      Scientific Reports
      Nature Publishing Group UK

      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

          Solanum trilobatum L. is an important medicinal plant in traditional Indian system of medicine belonging to Solanaceae family. However, non-availability of genomic resources hinders its research at the molecular level. We have analyzed the S. trilobatum leaf transcriptome using high throughput RNA sequencing. The de novo assembly of 136,220,612 reads produced 128,934 non-redundant unigenes with N50 value of 1347 bp. Annotation of unigenes was performed against databases such as NCBI nr database, Gene Ontology, KEGG, Uniprot, Pfam, and plnTFDB. A total of 60,097 unigenes were annotated including 48 Transcription Factor families and 14,490 unigenes were assigned to 138 pathways using KEGG database. The pathway analysis revealed the transcripts involved in the biosynthesis of important secondary metabolites contributing for its medicinal value such as Flavonoids. Further, the transcripts were quantified using RSEM to identify the highly regulated genes for secondary metabolism. Reverse-Transcription PCR was performed to validate the de novo assembled unigenes. The expression profile of selected unigenes from flavonoid biosynthesis pathway was analyzed using qRT-PCR. We have also identified 13,262 Simple Sequence Repeats, which could help in molecular breeding. This is the first report of comprehensive transcriptome analysis in S. trilobatum and this will be an invaluable resource to understand the molecular basis related to the medicinal attributes of S. trilobatum in further studies.

          Related collections

          Most cited references42

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

          Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.).

          A software tool was developed for the identification of simple sequence repeats (SSRs) in a barley ( Hordeum vulgare L.) EST (expressed sequence tag) database comprising 24,595 sequences. In total, 1,856 SSR-containing sequences were identified. Trimeric SSR repeat motifs appeared to be the most abundant type. A subset of 311 primer pairs flanking SSR loci have been used for screening polymorphisms among six barley cultivars, being parents of three mapping populations. As a result, 76 EST-derived SSR-markers were integrated into a barley genetic consensus map. A correlation between polymorphism and the number of repeats was observed for SSRs built of dimeric up to tetrameric units. 3'-ESTs yielded a higher portion of polymorphic SSRs (64%) than 5'-ESTs did. The estimated PIC (polymorphic information content) value was 0.45 +/- 0.03. Approximately 80% of the SSR-markers amplified DNA fragments in Hordeum bulbosum, followed by rye, wheat (both about 60%) and rice (40%). A subset of 38 EST-derived SSR-markers comprising 114 alleles were used to investigate genetic diversity among 54 barley cultivars. In accordance with a previous, RFLP-based, study, spring and winter cultivars, as well as two- and six-rowed barleys, formed separate clades upon PCoA analysis. The results show that: (1) with the software tool developed, EST databases can be efficiently exploited for the development of cDNA-SSRs, (2) EST-derived SSRs are significantly less polymorphic than those derived from genomic regions, (3) a considerable portion of the developed SSRs can be transferred to related species, and (4) compared to RFLP-markers, cDNA-SSRs yield similar patterns of genetic diversity.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            PlnTFDB: updated content and new features of the plant transcription factor database

            The Plant Transcription Factor Database (PlnTFDB; http://plntfdb.bio.uni-potsdam.de/v3.0/) is an integrative database that provides putatively complete sets of transcription factors (TFs) and other transcriptional regulators (TRs) in plant species (sensu lato) whose genomes have been completely sequenced and annotated. The complete sets of 84 families of TFs and TRs from 19 species ranging from unicellular red and green algae to angiosperms are included in PlnTFDB, representing >1.6 billion years of evolution of gene regulatory networks. For each gene family, a basic description is provided that is complemented by literature references, and multiple sequence alignments of protein domains. TF or TR gene entries include information of expressed sequence tags, 3D protein structures of homologous proteins, domain architecture and cross-links to other computational resources online. Moreover, the different species in PlnTFDB are linked to each other by means of orthologous genes facilitating cross-species comparisons.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              PLAZA: a comparative genomics resource to study gene and genome evolution in plants.

              The number of sequenced genomes of representatives within the green lineage is rapidly increasing. Consequently, comparative sequence analysis has significantly altered our view on the complexity of genome organization, gene function, and regulatory pathways. To explore all this genome information, a centralized infrastructure is required where all data generated by different sequencing initiatives is integrated and combined with advanced methods for data mining. Here, we describe PLAZA, an online platform for plant comparative genomics (http://bioinformatics.psb.ugent.be/plaza/). This resource integrates structural and functional annotation of published plant genomes together with a large set of interactive tools to study gene function and gene and genome evolution. Precomputed data sets cover homologous gene families, multiple sequence alignments, phylogenetic trees, intraspecies whole-genome dot plots, and genomic colinearity between species. Through the integration of high confidence Gene Ontology annotations and tree-based orthology between related species, thousands of genes lacking any functional description are functionally annotated. Advanced query systems, as well as multiple interactive visualization tools, are available through a user-friendly and intuitive Web interface. In addition, detailed documentation and tutorials introduce the different tools, while the workbench provides an efficient means to analyze user-defined gene sets through PLAZA's interface. In conclusion, PLAZA provides a comprehensible and up-to-date research environment to aid researchers in the exploration of genome information within the green plant lineage.
                Bookmark

                Author and article information

                Contributors
                purushothaman.n@ktr.srmuniv.ac.in
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 October 2018
                18 October 2018
                2018
                : 8
                : 15375
                Affiliations
                ISNI 0000 0004 0635 5080, GRID grid.412742.6, Department of Genetic Engineering, School of Bioengineering, , SRM Institute of Science and Technology, ; Kattankulathur, 603203 India
                Author information
                http://orcid.org/0000-0002-8888-7157
                Article
                33693
                10.1038/s41598-018-33693-4
                6194071
                30337583
                d01b2431-7e3f-4da6-a54b-d3acc44c2f39
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 March 2018
                : 1 October 2018
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001407, Department of Biotechnology, Ministry of Science and Technology (DBT);
                Award ID: BT/PR12987/INF/22/205/2015
                Award ID: BT/PR12987/INF/22/205/2015
                Award ID: BT/PR12987/INF/22/205/2015
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2018

                Uncategorized
                Uncategorized

                Comments

                Comment on this article