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      Comprehensive Biochemical, Physiological, and Transcriptomic Analyses Provide Insights Into Floral Bud Dormancy in Rhododendron delavayi Franch

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          Abstract

          Due to a scarcity of relevant data, the ornamental woody flower Rhododendron delavayi Franch. is examined in the current study for its low temperature-induced floral bud dormancy (late October–end December) aspect. This study used transcriptome data profiling and co-expression network analyses to identify the interplay between endogenous hormones and bud dormancy phases such as pre-dormancy, para-dormancy, endo-dormancy, eco-dormancy, and dormancy release. The biochemical and physiological assays revealed the significance of the abundance of phytohormones (abscisic acid, auxin, zeatin, and gibberellins), carbohydrate metabolism, oxidative species, and proteins (soluble proteins, proline, and malondialdehyde) in the regulatory mechanism of floral bud dormancy. The transcriptome sequencing generated 65,531 transcripts, out of which 504, 514, 307, and 240 expressed transcripts were mapped uniquely to pre-, para-, endo-, and eco-phases of dormancy, showing their roles in the stimulation of dormancy. The transcripts related to LEA29, PGM, SAUR family, RPL9e, ATRX, FLOWERING LOCUS T, SERK1, ABFs, ASR2, and GID1 were identified as potential structural genes involved in floral bud dormancy. The transcription factors, including Zinc fingers, CAD, MADS-box family, MYB, and MYC2, revealed their potential regulatory roles concerning floral bud dormancy . The gene co-expression analysis highlighted essential hub genes involved in cold stress adaptations encoding proteins, viz, SERPIN, HMA, PMEI, LEA_2, TRX, PSBT, and AMAT. We exposed the connection among low temperature-induced dormancy in floral buds, differentially expressed genes, and hub genes via strict screening steps to escalate the confidence in selected genes as being truly putative in the pathways regulating bud dormancy mechanism. The identified candidate genes may prove worthy of further in-depth studies on molecular mechanisms involved in floral bud dormancy of Rhododendron species.

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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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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                17 May 2022
                2022
                : 13
                : 856922
                Affiliations
                [1] 1 Flower Research Institute of Yunnan Academy of Agricultural Sciences , Kunming, China
                [2] 2 National Engineering Research Center for Ornamental Horticulture , Kunming, China
                Author notes

                Edited by: Million Tadege, Oklahoma State University, United States

                Reviewed by: Andrea Miyasaka Almeida, Universidad Mayor, Chile

                Dimiru Tadesse, Brookhaven National Laboratory, United States

                *Correspondence: Shifeng Li, wjh0505@ 123456gmail.com ; Jihua Wang, kylin7023@ 123456126.com
                [ † ]

                These authors have contributed equally to this work

                This article was submitted to Plant Genomics, a section of the journal Frontiers in Genetics

                Article
                856922
                10.3389/fgene.2022.856922
                9152171
                b1ae81b8-0ba6-4828-a400-ff865eec39e2
                Copyright © 2022 Zhang, Song, Peng, Xie, Li and Wang.

                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) and the copyright owner(s) 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.

                History
                : 17 January 2022
                : 19 April 2022
                Categories
                Genetics
                Original Research

                Genetics
                transcriptomics,dormancy,rhododendron delavayi,physiological indices,phytohormones,wgcna
                Genetics
                transcriptomics, dormancy, rhododendron delavayi, physiological indices, phytohormones, wgcna

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