IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0039547.html
   My bibliography  Save this article

Berry Flesh and Skin Ripening Features in Vitis vinifera as Assessed by Transcriptional Profiling

Author

Listed:
  • Diego Lijavetzky
  • Pablo Carbonell-Bejerano
  • Jérôme Grimplet
  • Gema Bravo
  • Pilar Flores
  • José Fenoll
  • Pilar Hellín
  • Juan Carlos Oliveros
  • José M Martínez-Zapater

Abstract

Background: Ripening of fleshy fruit is a complex developmental process involving the differentiation of tissues with separate functions. During grapevine berry ripening important processes contributing to table and wine grape quality take place, some of them flesh- or skin-specific. In this study, transcriptional profiles throughout flesh and skin ripening were followed during two different seasons in a table grape cultivar ‘Muscat Hamburg’ to determine tissue-specific as well as common developmental programs. Methodology/Principal Findings: Using an updated GrapeGen Affymetrix GeneChip® annotation based on grapevine 12×v1 gene predictions, 2188 differentially accumulated transcripts between flesh and skin and 2839 transcripts differentially accumulated throughout ripening in the same manner in both tissues were identified. Transcriptional profiles were dominated by changes at the beginning of veraison which affect both pericarp tissues, although frequently delayed or with lower intensity in the skin than in the flesh. Functional enrichment analysis identified the decay on biosynthetic processes, photosynthesis and transport as a major part of the program delayed in the skin. In addition, a higher number of functional categories, including several related to macromolecule transport and phenylpropanoid and lipid biosynthesis, were over-represented in transcripts accumulated to higher levels in the skin. Functional enrichment also indicated auxin, gibberellins and bHLH transcription factors to take part in the regulation of pre-veraison processes in the pericarp, whereas WRKY and C2H2 family transcription factors seems to more specifically participate in the regulation of skin and flesh ripening, respectively. Conclusions/Significance: A transcriptomic analysis indicates that a large part of the ripening program is shared by both pericarp tissues despite some components are delayed in the skin. In addition, important tissue differences are present from early stages prior to the ripening onset including tissue-specific regulators. Altogether, these findings provide key elements to understand berry ripening and its differential regulation in flesh and skin.

Suggested Citation

  • Diego Lijavetzky & Pablo Carbonell-Bejerano & Jérôme Grimplet & Gema Bravo & Pilar Flores & José Fenoll & Pilar Hellín & Juan Carlos Oliveros & José M Martínez-Zapater, 2012. "Berry Flesh and Skin Ripening Features in Vitis vinifera as Assessed by Transcriptional Profiling," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-15, June.
  • Handle: RePEc:plo:pone00:0039547
    DOI: 10.1371/journal.pone.0039547
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0039547
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0039547&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0039547?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li Ma & Lingjun Sun & Yinshan Guo & Hong Lin & Zhendong Liu & Kun Li & Xiuwu Guo, 2020. "Transcriptome analysis of table grapes (Vitis vinifera L.) identified a gene network module associated with berry firmness," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-15, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thiemo Fetzer & Samuel Marden, 2017. "Take What You Can: Property Rights, Contestability and Conflict," Economic Journal, Royal Economic Society, vol. 0(601), pages 757-783, May.
    2. Daniel Agness & Travis Baseler & Sylvain Chassang & Pascaline Dupas & Erik Snowberg, 2022. "Valuing the Time of the Self-Employed," Working Papers 2022-2, Princeton University. Economics Department..
    3. Batool, Fatima & Hennig, Christian, 2021. "Clustering with the Average Silhouette Width," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    4. Nicoleta Serban & Huijing Jiang, 2012. "Multilevel Functional Clustering Analysis," Biometrics, The International Biometric Society, vol. 68(3), pages 805-814, September.
    5. Orietta Nicolis & Jean Paul Maidana & Fabian Contreras & Danilo Leal, 2024. "Analyzing the Impact of COVID-19 on Economic Sustainability: A Clustering Approach," Sustainability, MDPI, vol. 16(4), pages 1-30, February.
    6. Li, Pai-Ling & Chiou, Jeng-Min, 2011. "Identifying cluster number for subspace projected functional data clustering," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2090-2103, June.
    7. Yaeji Lim & Hee-Seok Oh & Ying Kuen Cheung, 2019. "Multiscale Clustering for Functional Data," Journal of Classification, Springer;The Classification Society, vol. 36(2), pages 368-391, July.
    8. Forzani, Liliana & Gieco, Antonella & Tolmasky, Carlos, 2017. "Likelihood ratio test for partial sphericity in high and ultra-high dimensions," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 18-38.
    9. Yujia Li & Xiangrui Zeng & Chien‐Wei Lin & George C. Tseng, 2022. "Simultaneous estimation of cluster number and feature sparsity in high‐dimensional cluster analysis," Biometrics, The International Biometric Society, vol. 78(2), pages 574-585, June.
    10. Vojtech Blazek & Michal Petruzela & Tomas Vantuch & Zdenek Slanina & Stanislav Mišák & Wojciech Walendziuk, 2020. "The Estimation of the Influence of Household Appliances on the Power Quality in a Microgrid System," Energies, MDPI, vol. 13(17), pages 1-21, August.
    11. Andrew Clark & Alexander Mihailov & Michael Zargham, 2021. "Complex Systems Modeling of Community Inclusion Currencies," Economics Discussion Papers em-dp2021-06, Department of Economics, University of Reading.
    12. Nicoleta Serban, 2008. "Estimating and clustering curves in the presence of heteroscedastic errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(7), pages 553-571.
    13. Caruso, Germán & Scartascini, Carlos & Tommasi, Mariano, 2015. "Are we all playing the same game? The economic effects of constitutions depend on the degree of institutionalization," European Journal of Political Economy, Elsevier, vol. 38(C), pages 212-228.
    14. Alessandro Crimi & Olivier Commowick & Adil Maarouf & Jean-Christophe Ferré & Elise Bannier & Ayman Tourbah & Isabelle Berry & Jean-Philippe Ranjeva & Gilles Edan & Christian Barillot, 2014. "Predictive Value of Imaging Markers at Multiple Sclerosis Disease Onset Based on Gadolinium- and USPIO-Enhanced MRI and Machine Learning," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.
    15. Mehmet Çağlar & Cem Gürler, 2022. "Sustainable Development Goals: A cluster analysis of worldwide countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8593-8624, June.
    16. Elizabeth Tipton & Robert B. Olsen, "undated". "Enhancing the Generalizability of Impact Studies in Education," Mathematica Policy Research Reports 35d5625333dc480aba9765b3b, Mathematica Policy Research.
    17. Cyril Atkinson-Clement & Eléonore Pigalle, 2021. "What can we learn from Covid-19 pandemic’s impact on human behaviour? The case of France’s lockdown," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    18. Jelle R Dalenberg & Luca Nanetti & Remco J Renken & René A de Wijk & Gert J ter Horst, 2014. "Dealing with Consumer Differences in Liking during Repeated Exposure to Food; Typical Dynamics in Rating Behavior," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    19. Daniel Lewis & Davide Melcangi & Laura Pilossoph, 2019. "Latent Heterogeneity in the Marginal Propensity to Consume," 2019 Meeting Papers 519, Society for Economic Dynamics.
    20. Chun-Xia Zhang & Jiang-She Zhang & Sang-Woon Kim, 2016. "PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection," Computational Statistics, Springer, vol. 31(4), pages 1237-1262, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0039547. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.