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      Light response of gametophyte in Adiantum flabellulatum: transcriptome analysis and identification of key genes and pathways

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          Abstract

          Light serves not only as a signaling cue perceived by plant photoreceptors but also as an essential energy source captured by chloroplasts. However, excessive light can impose stress on plants. Fern gametophytes possess the unique ability to survive independently and play a critical role in the alternation of generations. Due to their predominantly shaded distribution under canopies, light availability becomes a limiting factor for gametophyte survival, making it imperative to investigate their response to light. Previous research on fern gametophytes’ light response has been limited to the physiological level. In this study, we examined the light response of Adiantum flabellulatum gametophytes under different photosynthetic photon flux density (PPFD) levels and identified their high sensitivity to low light. We thereby determined optimal and stress-inducing light conditions. By employing transcriptome sequencing, weighted gene co-expression network analysis, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, we identified 10,995 differentially expressed genes (DEGs). Notably, 3 PHYBs and 5 Type 1 CRYs ( CRY1s) were significantly down-regulated at low PPFD (0.1 μmol m -2 s -1). Furthermore, we annotated 927 DEGs to pathways related to photosynthesis and 210 to the flavonoid biosynthesis pathway involved in photoprotection. Additionally, we predicted 34 transcription factor families and identified a close correlation between mTERFs and photosynthesis, as well as a strong co-expression relationship between MYBs and bHLHs and genes encoding flavonoid synthesis enzymes. This comprehensive analysis enhances our understanding of the light response of fern gametophytes and provides novel insights into the mechanisms governing their responses to light.

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          Most cited references51

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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.
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            A new mathematical model for relative quantification in real-time RT-PCR.

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            Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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              MYB transcription factors in Arabidopsis.

              The MYB family of proteins is large, functionally diverse and represented in all eukaryotes. Most MYB proteins function as transcription factors with varying numbers of MYB domain repeats conferring their ability to bind DNA. In plants, the MYB family has selectively expanded, particularly through the large family of R2R3-MYB. Members of this family function in a variety of plant-specific processes, as evidenced by their extensive functional characterization in Arabidopsis (Arabidopsis thaliana). MYB proteins are key factors in regulatory networks controlling development, metabolism and responses to biotic and abiotic stresses. The elucidation of MYB protein function and regulation that is possible in Arabidopsis will provide the foundation for predicting the contributions of MYB proteins to the biology of plants in general. Copyright © 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                07 September 2023
                2023
                : 14
                : 1222414
                Affiliations
                [1] 1 Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants, Ministry of Education, College of Forestry, Hainan University , Haikou, Hainan, China
                [2] 2 College of Ecology and Environment, Hainan University , Haikou, Hainan, China
                [3] 3 Key Laboratory of Germplasm Resources Biology of Tropical Special Ornamental Plants of Hainan Province, College of Forestry, Hainan University , Haikou, China
                [4] 4 Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences , Haikou, Hainan, China
                Author notes

                Edited by: Eleni Tani, Agricultural University of Athens, Greece

                Reviewed by: Sofia D. Carvalho, Independent Researcher, Laramie, WY, United States; Georgios Liakopoulos, Agricultural University of Athens, Greece

                †These authors have contributed equally to this work

                Article
                10.3389/fpls.2023.1222414
                10513451
                37746005
                4d4c3d00-98e9-43c2-8d61-6fee2cb866b6
                Copyright © 2023 Cai, Wang, Xie, Wen, Yu, Xu, Su and Luo

                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
                : 14 May 2023
                : 22 August 2023
                Page count
                Figures: 10, Tables: 0, Equations: 0, References: 51, Pages: 13, Words: 6124
                Funding
                This work was supported by the Major Science and Technology plan of Hainan Province (ZDKJ2021018), the Natural Science Foundation of Hainan Province (No.322RC772; No.321QN316; No.319MS017; No.320RC508), the Program of Hainan Association for Science and Technology Plans to Youth Science and Techonology Talent Innovation (QCQTXM202201), the National Natural Science Foundation of China (No.31660229), the Hainan University Scientific Research Startup Fund Project (No.kyqd1620).
                Categories
                Plant Science
                Original Research
                Custom metadata
                Plant Bioinformatics

                Plant science & Botany
                fern gametophyte,light signal,photosynthesis,photoprotection,weighted gene co-expression network analysis

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