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      Integrated metabolomic and transcriptomic dynamic profiles of endopleura coloration during fruit maturation in three walnut cultivars

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          Abstract

          Background

          The color of endopleura is a vital factor in determining the economic value and aesthetics appeal of nut. Walnuts ( Juglans) are a key source of edible nuts, high in proteins, amino acids, lipids, carbohydrates. Walnut had a variety endopleura color as yellow, red, and purple. However, the regulation of walnut endopleura color remains little known.

          Results

          To understand the process of coloration in endopleura, we performed the integrative analysis of transcriptomes and metabolomes at two developmental stages of walnut endopleura. We obtained total of 4,950 differentially expressed genes (DEGs) and 794 metabolites from walnut endopleura, which are involved in flavonoid and phenolic biosynthesis pathways. The enrichment analysis revealed that the cinnamic acid, coniferyl alcohol, naringenin, and naringenin-7-O-glucoside were important metabolites in the development process of walnut endopleura. Transcriptome and metabolome analyses revealed that the DEGs and differentially regulated metabolites (DRMs) were significantly enriched in flavonoid biosynthesis and phenolic metabolic pathways. Through co-expression analysis, CHS (chalcone synthase), CHI (chalcone isomerase), CCR (cinnamoyl CoA reductase), CAD (cinnamyl alcohol dehydrogenase), COMT (catechol-Omethyl transferase), and 4CL (4-coumaroyl: CoA-ligase) may be the key genes that potentially regulate walnut endopleura color in flavonoid biosynthesis and phenolic metabolic pathways.

          Conclusions

          This study illuminates the metabolic pathways and candidate genes that underlie the endopleura coloration in walnuts, lay the foundation for further study and provides insights into controlling nut’s colour.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12870-024-04790-6.

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          Most cited references79

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              KEGG: kyoto encyclopedia of genes and genomes.

              M Kanehisa (2000)
              KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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                Author and article information

                Contributors
                houna1018@163.com
                pengzhao@nwu.edu.cn
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                14 February 2024
                14 February 2024
                2024
                : 24
                : 109
                Affiliations
                [1 ]GRID grid.412262.1, ISNI 0000 0004 1761 5538, Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, , Northwest University, ; No. 229 Tabi Rd., Xi’an, 710069 China
                [2 ]GRID grid.488196.a, Xi’an Botanical Garden of Shaanxi Province (Institute of Botany of Shaanxi Province), ; Xi’an, 710061 Shaanxi China
                [3 ]Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Karst Mountainous Areas of Southwestern China, Guizhou Academy of Forestry, Guiyang, 55005 China
                Article
                4790
                10.1186/s12870-024-04790-6
                10865529
                38350847
                34eacc94-2496-47e6-9357-defe46fdd54a
                © The Author(s) 2024

                Open Access This 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
                : 26 October 2023
                : 1 February 2024
                Funding
                Funded by: Shaanxi Academy of Science Research Funding Project
                Award ID: 2023K-26
                Funded by: Shaanxi Forestry Science and Technology Innovation Key Project
                Award ID: SXLK2023-02-20
                Funded by: Qinling Hundred Talents Project of Shaanxi Academy of Science
                Award ID: Y23Z619F17
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31860215
                Award ID: 32370386
                Funded by: Guizhou Forestry Bureau Project-Germplasm Innovation and Application of Guizhou Walnut (Guizhou Forestry Science Association
                Award ID: 2022-17
                Funded by: Science Foundation for Distinguished Young Scholars of Shaanxi Province
                Award ID: 2023-JC-JQ-22
                Funded by: Basic Research Project of Shaanxi Academy of Fundamental Science
                Award ID: 22JHZ005
                Funded by: FundRef http://dx.doi.org/10.13039/501100002858, China Postdoctoral Science Foundation;
                Award ID: 2022MD723843
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Plant science & Botany
                metabolism,walnut,multiomics,network analysis,endopleura
                Plant science & Botany
                metabolism, walnut, multiomics, network analysis, endopleura

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