12
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Discovery of a DFR gene that controls anthocyanin accumulation in the spiny Solanum group: roles of a natural promoter variant and alternative splicing

      Read this article at

      ScienceOpenPublisherPubMed
      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

          Anthocyanins are important pigments that impart color in plants. In Solanum, different species display various fruit or flower colors due to varying degrees of anthocyanin accumulation. Here we identified two anthocyanin-free mutants from an ethylmethane sulfonate-induced mutant library and naturally occurring mutants in Solanum melongena, with mutations in the 5' splicing site of the second intron of dihydroflavonol-4-reductase (DFR) - leading to altered splicing. Further study revealed that alternative splicing of the second intron was closely related to anthocyanin accumulation in 17 accessions from three cultivated species: S. melongena, Solanum macrocarpon and Solanum aethiopicum, and their wild related species. Analysis of natural variations of DFR, using an expanded population including 282 accessions belonging to the spiny Solanum group, identified a single-nucleotide polymorphism in the MYB recognition site in the promoter region, which causes differential expression of DFR and affects anthocyanin accumulation in fruits of the detected accessions. Our study suggests that, owing to years of domestication, the natural variation in the DFR promoter region and the alternative splicing of the DFR gene account for altered anthocyanin accumulation during spiny Solanum domestication.

          Related collections

          Most cited references57

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

          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

            Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A framework for variation discovery and genotyping using next-generation DNA sequencing data

              Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.
                Bookmark

                Author and article information

                Contributors
                Journal
                The Plant Journal
                The Plant Journal
                Wiley
                0960-7412
                1365-313X
                August 2022
                July 18 2022
                August 2022
                : 111
                : 4
                : 1096-1109
                Affiliations
                [1 ]Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, College of Horticulture Hebei Agricultural University Baoding China
                [2 ]College of Life Sciences Hebei Agricultural University Baoding China
                [3 ]Plant Breeding Wageningen University & Research Wageningen The Netherlands
                Article
                10.1111/tpj.15877
                35749258
                80725d19-9f74-4ca3-8fd0-d6103110b022
                © 2022

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

                History

                Comments

                Comment on this article