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      Fillable and unfillable gaps in plant transcriptome under field and controlled environments

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          Abstract

          The differences between plants grown in field and in controlled environments have long been recognized. However, few studies have addressed the underlying molecular mechanisms. To evaluate plant responses to fluctuating environments using laboratory equipment, we developed SmartGC, a high‐performance growth chamber that reproduces the fluctuating irradiance, temperature and humidity of field environments. We analysed massive transcriptome data of rice plants grown under field and SmartGC conditions to clarify the differences in plant responses to field and controlled environments. Rice transcriptome dynamics in SmartGC mimicked those in the field, particularly during the morning and evening but those in conventional growth chamber conditions did not. Further analysis revealed that fluctuation of irradiance affects transcriptome dynamics in the morning and evening, while fluctuation of temperature affects transcriptome dynamics only in the morning. We found upregulation of genes related to biotic and abiotic stress, and their expression was affected by environmental factors that cannot be mimicked by SmartGC. Our results reveal fillable and unfillable gaps in the transcriptomes of rice grown in field and controlled environments and can accelerate the understanding of plant responses to field environments for both basic biology and agricultural applications.

          Summary Statement

          Diurnal transcriptome dynamics of rice grown in fluctuating field and controlled environments are different mainly in the morning and evening, which are affected by light and temperature in the morning, while only by light in the evening. We also found field‐specific gene expression.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

              Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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                Author and article information

                Contributors
                anagano@agr.ryukoku.ac.jp
                Journal
                Plant Cell Environ
                Plant Cell Environ
                10.1111/(ISSN)1365-3040
                PCE
                Plant, Cell & Environment
                John Wiley and Sons Inc. (Hoboken )
                0140-7791
                1365-3040
                21 June 2022
                August 2022
                : 45
                : 8 ( doiID: 10.1111/pce.v45.8 )
                : 2410-2427
                Affiliations
                [ 1 ] Faculty of Agriculture Takasaki University of Health and Welfare Takasaki Gunma Japan
                [ 2 ] Research Institute for Food and Agriculture Ryukoku University Otsu Shiga Japan
                [ 3 ] Faculty of Agriculture Ryukoku University Otsu Shiga Japan
                [ 4 ] College of Science and Engineering Aoyama Gakuin University Sagamihara Kanagawa Japan
                [ 5 ] Institute for Advanced Biosciences Keio University Tsuruoka Yamagata Japan
                Author notes
                [*] [* ] Correspondence Atsushi J. Nagano, Faculty of Agriculture, Ryukoku University, 1‐5 Yokotani, Seta Oe‐cho, Otsu, Shiga 520‐2194, Japan.

                Email: anagano@ 123456agr.ryukoku.ac.jp

                Author information
                http://orcid.org/0000-0001-6129-2308
                http://orcid.org/0000-0002-7492-3161
                http://orcid.org/0000-0002-8888-8678
                http://orcid.org/0000-0002-5803-9747
                http://orcid.org/0000-0002-3953-9033
                http://orcid.org/0000-0003-2056-3663
                http://orcid.org/0000-0001-7891-5049
                Article
                PCE14367
                10.1111/pce.14367
                9544781
                35610174
                f29356cb-b316-45bb-b72e-f1af25d30fd9
                © 2022 The Authors. Plant, Cell & Environment published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 March 2022
                : 17 November 2021
                : 16 May 2022
                Page count
                Figures: 6, Tables: 0, Pages: 18, Words: 11822
                Funding
                Funded by: Japan Science and Technology Agency, Fusion Oriented Research for disruptive Science and Technology
                Award ID: JPMJFR210B
                Funded by: New Energy and Industrial Technology Development Organization, MOONSHOT Research & Development Program
                Award ID: JPNP18016
                Funded by: Japan Science and Technology Agency, Core Research for Evolutional Science and Technology , doi 10.13039/501100003382;
                Award ID: JPMJCR15O2
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                August 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                Plant science & Botany
                biotic and abiotic stress,circadian clock,field,growth chamber,rice,rna‐seq,sugar metabolism,transcriptome

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