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      Transcriptome Analysis of Leaves, Flowers and Fruits Perisperm of Coffea arabica L. Reveals the Differential Expression of Genes Involved in Raffinose Biosynthesis

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          Abstract

          Coffea arabica L. is an important crop in several developing countries. Despite its economic importance, minimal transcriptome data are available for fruit tissues, especially during fruit development where several compounds related to coffee quality are produced. To understand the molecular aspects related to coffee fruit and grain development, we report a large-scale transcriptome analysis of leaf, flower and perisperm fruit tissue development. Illumina sequencing yielded 41,881,572 high-quality filtered reads. De novo assembly generated 65,364 unigenes with an average length of 1,264 bp. A total of 24,548 unigenes were annotated as protein coding genes, including 12,560 full-length sequences. In the annotation process, we identified nine candidate genes related to the biosynthesis of raffinose family oligossacarides (RFOs). These sugars confer osmoprotection and are accumulated during initial fruit development. Four genes from this pathway had their transcriptional pattern validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Furthermore, we identified ~24,000 putative target sites for microRNAs (miRNAs) and 134 putative transcriptionally active transposable elements (TE) sequences in our dataset. This C. arabica transcriptomic atlas provides an important step for identifying candidate genes related to several coffee metabolic pathways, especially those related to fruit chemical composition and therefore beverage quality. Our results are the starting point for enhancing our knowledge about the coffee genes that are transcribed during the flowering and initial fruit development stages.

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          Most cited references32

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          psRNATarget: a plant small RNA target analysis server

          Plant endogenous non-coding short small RNAs (20–24 nt), including microRNAs (miRNAs) and a subset of small interfering RNAs (ta-siRNAs), play important role in gene expression regulatory networks (GRNs). For example, many transcription factors and development-related genes have been reported as targets of these regulatory small RNAs. Although a number of miRNA target prediction algorithms and programs have been developed, most of them were designed for animal miRNAs which are significantly different from plant miRNAs in the target recognition process. These differences demand the development of separate plant miRNA (and ta-siRNA) target analysis tool(s). We present psRNATarget, a plant small RNA target analysis server, which features two important analysis functions: (i) reverse complementary matching between small RNA and target transcript using a proven scoring schema, and (ii) target-site accessibility evaluation by calculating unpaired energy (UPE) required to ‘open’ secondary structure around small RNA’s target site on mRNA. The psRNATarget incorporates recent discoveries in plant miRNA target recognition, e.g. it distinguishes translational and post-transcriptional inhibition, and it reports the number of small RNA/target site pairs that may affect small RNA binding activity to target transcript. The psRNATarget server is designed for high-throughput analysis of next-generation data with an efficient distributed computing back-end pipeline that runs on a Linux cluster. The server front-end integrates three simplified user-friendly interfaces to accept user-submitted or preloaded small RNAs and transcript sequences; and outputs a comprehensive list of small RNA/target pairs along with the online tools for batch downloading, key word searching and results sorting. The psRNATarget server is freely available at http://plantgrn.noble.org/psRNATarget/.
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            Widespread translational inhibition by plant miRNAs and siRNAs.

            High complementarity between plant microRNAs (miRNAs) and their messenger RNA targets is thought to cause silencing, prevalently by endonucleolytic cleavage. We have isolated Arabidopsis mutants defective in miRNA action. Their analysis provides evidence that plant miRNA-guided silencing has a widespread translational inhibitory component that is genetically separable from endonucleolytic cleavage. We further show that the same is true of silencing mediated by small interfering RNA (siRNA) populations. Translational repression is effected in part by the ARGONAUTE proteins AGO1 and AGO10. It also requires the activity of the microtubule-severing enzyme katanin, implicating cytoskeleton dynamics in miRNA action, as recently suggested from animal studies. Also as in animals, the decapping component VARICOSE (VCS)/Ge-1 is required for translational repression by miRNAs, which suggests that the underlying mechanisms in the two kingdoms are related.
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              Classification and comparison of small RNAs from plants.

              Regulatory small RNAs, which range in size from 20 to 24 nucleotides, are ubiquitous components of endogenous plant transcriptomes, as well as common responses to exogenous viral infections and introduced double-stranded RNA (dsRNA). Endogenous small RNAs derive from the processing of helical RNA precursors and can be categorized into several groups based on differences in biogenesis and function. A major distinction can be observed between small RNAs derived from single-stranded precursors with a hairpin structure [referred to here as hairpin RNAs (hpRNAs)] and those derived from dsRNA precursors [small interfering RNAs (siRNAs)]. hpRNAs in plants can be divided into two secondary groups: microRNAs and those that are not microRNAs. The currently known siRNAs fall mostly into one of three secondary groups: heterochromatic siRNAs, secondary siRNAs, and natural antisense transcript siRNAs. Tertiary subdivisions can be identified within many of the secondary classifications as well. Comparisons between the different classes of plant small RNAs help to illuminate key goals for future research.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                9 January 2017
                2017
                : 12
                : 1
                : e0169595
                Affiliations
                [1 ]Programa de Pós-Graduação em Genética e Biologia Molecular, Centro de Ciências Biológicas, Universidade Estadual de Londrina (UEL), Londrina, Brazil
                [2 ]Laboratório de Biotecnologia Vegetal, Instituto Agronômico do Paraná (IAPAR), Londrina, Brazil
                [3 ]Laboratório de Genômica e Expressão, Departamento de Genética, Evolução e Bioagentes, Instituto de Biologia, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
                [4 ]Departamento de Botânica, Instituto de Biociências de Rio Claro, Universidade Estadual Paulista (UNESP), Rio Claro, Brazil
                [5 ]Centre de Coopération Internationale en Recherche Agronomique Pour le Développement, (CIRAD), UMR AGAP, Montpellier, France
                [6 ]Programa de Pós Graduação em Agronomia, Universidade do Oeste Paulista (UNOESTE), Presidente Prudente, Brazil
                [7 ]Empresa Brasileira de Pesquisa Agropecuária (Embrapa Café), Brasília, Brazil
                National Institutes of Health, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: STI ORJ DSD MFC LFPP.

                • Data curation: ORJ MFC GAGP LFPP.

                • Formal analysis: STI ORJ DSD.

                • Funding acquisition: LFPP.

                • Investigation: STI ORJ DSD.

                • Methodology: STI ORJ MFC DSD.

                • Project administration: LFPP.

                • Resources: GAGP LFPP.

                • Validation: STI TBS FFO.

                • Writing – original draft: STI DSD LFPP.

                • Writing – review & editing: STI DSD DP TL LGEV LFPP.

                Author information
                http://orcid.org/0000-0002-4872-6607
                Article
                PONE-D-16-32536
                10.1371/journal.pone.0169595
                5221826
                28068432
                80e10d27-f982-4b95-873a-7c33fa179f06
                © 2017 Ivamoto et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 August 2016
                : 17 December 2016
                Page count
                Figures: 4, Tables: 5, Pages: 17
                Funding
                Funded by: Consórcio Pesquisa Café
                Award Recipient :
                Funded by: Consórcio Pesquisa Café
                Award Recipient :
                Funded by: Center for Computational Engineering and Sciences at Unicamp
                Award Recipient :
                Funded by: Fundação Araucária (BR)
                Award Recipient :
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
                Award Recipient :
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
                Award Recipient :
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
                Award Recipient :
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
                Award Recipient :
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
                Award Recipient :
                Funded by: Financiadora de Estudos e Projetos (FINEP)
                Award Recipient :
                We would like to acknowledge the support of the Brazilian Coffee Research Consortium, National Institute for Coffee Science and Technology (INCT-Café), Coordination for the Improvement of Higher Education Personnel (CAPES), National Council of Technological and Scientific Development (CNPq), Brazilian Innovation Agency (FINEP) and the Center for Computational Engineering and Sciences at Unicamp/SP-Brazil. STI, TBS and FFO acknowledge CAPES and Fundação Araucária (FA) for graduation fellowships. GAGP, DSD, LGEV and LFPP acknowledge CNPq for their research fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Transcriptome Analysis
                Biology and life sciences
                Genetics
                Gene expression
                Gene regulation
                MicroRNAs
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                MicroRNAs
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Fruits
                Biology and Life Sciences
                Organisms
                Plants
                Fruits
                Biology and Life Sciences
                Genetics
                Gene Expression
                Research and Analysis Methods
                Database and Informatics Methods
                Biological Databases
                Genomic Databases
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genomic Databases
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genomic Databases
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Flowers
                Biology and Life Sciences
                Biochemistry
                Biosynthesis
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                RNA sequencing
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                RNA sequencing
                Custom metadata
                RNA-seq data were submitted to NCBI under BioProject accession number PRJNA339585. Transcriptome Sequencing Analysis (TSA) and Sequence Read Arquive (SRA) files are available under GEXP00000000 and SRP082511 accession numbers, respectively.

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