+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Transcriptional Responses in Root and Leaf of Prunus persica under Drought Stress Using RNA Sequencing

      Read this article at

          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.


          Prunus persica L. Batsch, or peach, is one of the most important crops and it is widely established in irrigated arid and semi-arid regions. However, due to variations in the climate and the increased aridity, drought has become a major constraint, causing crop losses worldwide. The use of drought-tolerant rootstocks in modern fruit production appears to be a useful method of alleviating water deficit problems. However, the transcriptomic variation and the major molecular mechanisms that underlie the adaptation of drought-tolerant rootstocks to water shortage remain unclear. Hence, in this study, high-throughput sequencing (RNA-seq) was performed to assess the transcriptomic changes and the key genes involved in the response to drought in root tissues (GF677 rootstock) and leaf tissues (graft, var. Catherina) subjected to 16 days of drought stress. In total, 12 RNA libraries were constructed and sequenced. This generated a total of 315 M raw reads from both tissues, which allowed the assembly of 22,079 and 17,854 genes associated with the root and leaf tissues, respectively. Subsets of 500 differentially expressed genes (DEGs) in roots and 236 in leaves were identified and functionally annotated with 56 gene ontology (GO) terms and 99 metabolic pathways, which were mostly associated with aminobenzoate degradation and phenylpropanoid biosynthesis. The GO analysis highlighted the biological functions that were exclusive to the root tissue, such as “locomotion,” “hormone metabolic process,” and “detection of stimulus,” indicating the stress-buffering role of the GF677 rootstock. Furthermore, the complex regulatory network involved in the drought response was revealed, involving proteins that are associated with signaling transduction, transcription and hormone regulation, redox homeostasis, and frontline barriers. We identified two poorly characterized genes in P. persica: growth-regulating factor 5 (GRF5), which may be involved in cellular expansion, and AtHB12, which may be involved in root elongation. The reliability of the RNA-seq experiment was validated by analyzing the expression patterns of 34 DEGs potentially involved in drought tolerance using quantitative reverse transcription polymerase chain reaction. The transcriptomic resources generated in this study provide a broad characterization of the acclimation of P. persica to drought, shedding light on the major molecular responses to the most important environmental stressor.

          Related collections

          Most cited references 69

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

          Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

          Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            High-throughput functional annotation and data mining with the Blast2GO suite

            Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.
              • Record: found
              • Abstract: found
              • Article: not found

              WEGO: a web tool for plotting GO annotations

              Unified, structured vocabularies and classifications freely provided by the Gene Ontology (GO) Consortium are widely accepted in most of the large scale gene annotation projects. Consequently, many tools have been created for use with the GO ontologies. WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO annotation results. Different from other commercial software for creating chart, WEGO is designed to deal with the directed acyclic graph structure of GO to facilitate histogram creation of GO annotation results. WEGO has been used widely in many important biological research projects, such as the rice genome project and the silkworm genome project. It has become one of the daily tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. WEGO, along with the two other tools, namely External to GO Query and GO Archive Query, are freely available for all users at . There are two available mirror sites at and . Any suggestions are welcome at

                Author and article information

                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                23 November 2016
                : 7
                1Department of Pomology, Estación Experimental de Aula Dei-Consejo Superior de Investigaciones Científicas Zaragoza, Spain
                2Department of Biological Sciences, Clemson University, Clemson SC, USA
                3Laboratory of Computational and Structural Biology, Department of Genetics and Plant Production, Estación Experimental de Aula Dei – Consejo Superior de Investigaciones Científicas Zaragoza, Spain
                4Fundación ARAID Zaragoza, Spain
                Author notes

                Edited by: Maren Müller, University of Barcelona, Spain

                Reviewed by: Rui Shi, North Carolina State University, USA; Soulaiman Sakr, Agrocampus Ouest, France

                *Correspondence: Yolanda Gogorcena, aoiz@ Bruno Contreras-Moreira, bcontreras@

                Present address: Sergio Jiménez, Bayer AG, CropScience Division, Development, Environmental Science, Monheim, Germany

                These authors have contributed equally to this work.

                This article was submitted to Plant Physiology, a section of the journal Frontiers in Plant Science

                Copyright © 2016 Ksouri, Jiménez, Wells, Contreras-Moreira and Gogorcena.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 7, Tables: 2, Equations: 0, References: 70, Pages: 19, Words: 0
                Funded by: Ministerio de Economía y Competitividad 10.13039/501100003329
                Award ID: AGL-2008-00283, AGL2011-24576,AGL2014-52063
                Plant Science
                Original Research

                Plant science & Botany

                drought, peach, rna sequencing, leaf, root, rootstock, gf677, catherina


                Comment on this article