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      Transcriptome and metabolite profiling analyses provide insight into volatile compounds of the apple cultivar ‘Ruixue’ and its parents during fruit development

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          Abstract

          Background

          Aroma is one the most crucial inherent quality attributes of fruit. ‘Ruixue’ apples were selected from a cross between ‘Pink Lady’ and ‘Fuji’, a later ripening yellow new cultivar. However, there is little known about the content and composition of aroma compounds in ‘Ruixue’ apples or the genetic characters of ‘Ruixue’ and its parents. In addition, the metabolic pathways for biosynthesis of aroma volatiles and aroma-related genes remain poorly understood.

          Results

          Volatile aroma compounds were putatively identified using gas chromatography-mass spectrometry (GC–MS). Our results show that the profile of volatile compounds changes with ripening. Aldehydes were the dominant volatile compounds in early fruit development, with alcohols and esters increasing dramatically during maturation. On the basis of a heatmap dendrogram, these aroma compounds clustered into seven groups. In ripe fruit, esters and terpenoids were the main aroma volatiles in ripening fruit of ‘Pink Lady’ and ‘Fuji’ apples, and they included butyl 2-methylbutanoate; propanoic acid, hexyl ester; propanoic acid, hexyl ester; hexanoic acid, hexyl ester; acetic acid, hexyl ester and (Z, E)-α-farnesene. Interestingly, aldehydes and terpenoids were the dominant volatile aroma compounds in ripening fruit of ‘Ruixue’, and they mainly included hexanal; 2-hexenal; octanal; (E)-2-octenal; nonanal and (Z, E)-α-farnesene. By comparing the transcriptome profiles of ‘Ruixue’ and its parents fruits during development, we identified a large number of aroma-related genes related to the fatty acid, isoleucine and sesquiterpenoid metabolism pathways and transcription factors that may volatile regulate biosynthesis.

          Conclusions

          Our initial study facilitates a better understanding of the volatile compounds that affect fruit flavour as well as the mechanisms underlying differences in flavour between ‘Ruixue’ and its parents.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12870-021-03032-3.

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          Most cited references43

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          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).
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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              TBtools - an integrative toolkit developed for interactive analyses of big biological data

              The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
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                Author and article information

                Contributors
                zhaozy@nwsuaf.edu.cn
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                24 May 2021
                24 May 2021
                2021
                : 21
                : 231
                Affiliations
                GRID grid.144022.1, ISNI 0000 0004 1760 4150, College of Horticulture, , Northwest A&F University, ; Yangling, 712100 Shaanxi China
                Article
                3032
                10.1186/s12870-021-03032-3
                8147058
                34030661
                12557af3-e27d-4e3c-a740-37324da70d89
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 4 August 2020
                : 11 May 2021
                Funding
                Funded by: the Special Project for Building Industrial Technology System of National Modern Agriculture (Apple)
                Award ID: CARS-28
                Award Recipient :
                Funded by: the Modern Agro-industry Technology Research System, China
                Award ID: CARS-27
                Award Recipient :
                Funded by: the Northwest A&F University of Science and Technology
                Award ID: 2014 YB 086
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                Plant science & Botany
                volatile aroma compounds,‘ruixue’ (malus × domestica borkh.),fruit flavour,gas chromatography-mass spectrometry (gc–ms),gene expression

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