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      Subgenome evolutionary dynamics in allotetraploid ferns: insights from the gene expression patterns in the allotetraploid species Phegopteris decursivepinnata (Thelypteridacea, Polypodiales)

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          Abstract

          Allopolyploidization often leads to disruptive conflicts among more than two sets of subgenomes, leading to genomic modifications and changes in gene expression. Although the evolutionary trajectories of subgenomes in allopolyploids have been studied intensely in angiosperms, the dynamics of subgenome evolution remain poorly understood in ferns, despite the prevalence of allopolyploidization. In this study, we have focused on an allotetraploid fern— Phegopteris decursivepinnata—and its diploid parental species, P. koreana ( K) and P. taiwaniana ( T). Using RNA-seq analyses, we have compared the gene expression profiles for 9,540 genes among parental species, synthetic F 1 hybrids, and natural allotetraploids. The changes in gene expression patterns were traced from the F 1 hybrids to the natural allopolyploids. This study has revealed that the expression patterns observed in most genes in the F 1 hybrids are largely conserved in the allopolyploids; however, there were substantial differences in certain genes between these groups. In the allopolyploids compared with the F 1 hybrids, the number of genes showing a transgressive pattern in total expression levels was increased. There was a slight reduction in T-dominance and a slight increase in K-dominance, in terms of expression level dominance. Interestingly, there is no obvious bias toward the T- or K-subgenomes in the number and expression levels overall, showing the absence of subgenome dominance. These findings demonstrated the impacts of the substantial transcriptome change after hybridization and the moderate modification during allopolyploid establishment on gene expression in ferns and provided important insights into subgenome evolution in polyploid ferns.

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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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            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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              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
                URI : https://loop.frontiersin.org/people/2425944Role: Role: Role: Role: Role: Role:
                Role: Role: Role:
                Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2425974Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2259982Role: Role: Role: Role: Role: Role: Role:
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                09 January 2024
                2023
                : 14
                : 1286320
                Affiliations
                [1] 1 Department of Biological Sciences, Graduate School of Science, The University of Tokyo , Tokyo, Japan
                [2] 2 Department of Biology, Faculty of Science, Chiba University , Chiba, Japan
                [3] 3 Department of Biology, Graduate School of Science, Chiba University , Chiba, Japan
                [4] 4 Center for Molecular Biodiversity Research, National Museum of Nature and Science , Tsukuba, Ibaraki, Japan
                Author notes

                Edited by: Li-Yaung Kuo, National Tsing Hua University, Taiwan

                Reviewed by: David Wickell, University of Connecticut, United States

                Rie Shimizu-Inatsugi, University of Zurich, Switzerland

                Cheng Li, Chinese Academy of Agricultural Sciences (CAAS), China

                *Correspondence: Tao Fujiwara, tao.fujiwara@ 123456gmail.com
                Article
                10.3389/fpls.2023.1286320
                10803465
                38264021
                18ead96e-04d5-41f8-8029-92444106bd9e
                Copyright © 2024 Katayama, Yamamoto, Aiuchi, Watano and Fujiwara

                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
                : 31 August 2023
                : 13 December 2023
                Page count
                Figures: 5, Tables: 3, Equations: 0, References: 103, Pages: 15, Words: 8840
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by a grant-in-aid from the Japan Society for the Promotion of Science (JSPS) KAKENHI (22K15178), awarded to TF.
                Categories
                Plant Science
                Original Research
                Custom metadata
                Plant Systematics and Evolution

                Plant science & Botany
                allopolyploid,cytonuclear coordination,expression level dominance,genome evolution,homoeolog expression bias,pteridophyte,subgenome dominance,transcriptome shock

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