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      Diurnal metabolic regulation of isoflavones and soyasaponins in soybean roots

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          Abstract

          Isoflavones and soyasaponins are major specialized metabolites accumulated in soybean roots and secreted into the rhizosphere. Unlike the biosynthetic pathway, the transporters involved in metabolite secretion remain unknown. The developmental regulation of isoflavone and soyasaponin secretions has been recently reported, but the diurnal regulation of their biosynthesis and secretion still needs to be further studied. To address these challenges, we conducted transcriptome and metabolite analysis using hydroponically grown soybean plants at 6‐hr intervals for 48 hr in a 12‐hr‐light/12‐hr‐dark condition. Isoflavone and soyasaponin biosynthetic genes showed opposite patterns in the root tissues; that is, the former genes are highly expressed in the daytime, while the latter ones are strongly induced at nighttime. GmMYB176 encoding a transcription factor of isoflavone biosynthesis was upregulated from ZT0 (6:00 a.m.) to ZT6 (12:00 a.m.), followed by the induction of isoflavone biosynthetic genes at ZT6. The isoflavone aglycone content in the roots accordingly increased from ZT6 to ZT18 (0:00 a.m.). The isoflavone aglycone content in root exudates was kept consistent throughout the day, whereas that of glucosides increased at ZT6, which reflected the decreased expression of the gene encoding beta‐glucosidase involved in the hydrolysis of apoplast‐localized isoflavone conjugates. Co‐expression analysis revealed that those isoflavone and soyasaponin biosynthetic genes formed separate clusters, which exhibited a correlation to ABC and MATE transporter genes. In summary, the results in this study indicated the diurnal regulation of isoflavone biosynthesis in soybean roots and the putative transporter genes responsible for isoflavone and soyasaponin transport.

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            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              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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                Author and article information

                Contributors
                akifumi_sugiyama@rish.kyoto-u.ac.jp
                Journal
                Plant Direct
                Plant Direct
                10.1002/(ISSN)2475-4455
                PLD3
                Plant Direct
                John Wiley and Sons Inc. (Hoboken )
                2475-4455
                18 November 2020
                November 2020
                : 4
                : 11 ( doiID: 10.1002/pld3.v4.11 )
                : e00286
                Affiliations
                [ 1 ] Research Institute for Sustainable Humanosphere Kyoto University Gokasho, Uji Japan
                [ 2 ] Tohoku Medical Megabank Organization Tohoku University Sendai Japan
                [ 3 ] Faculty of Agriculture Ryukoku University Otsu Japan
                Author notes
                [*] [* ] Correspondence

                Akifumi Sugiyama, Laboratory of Plant Gene Expression, Research Institute for Sustainable Humanosphere, Kyoto University, Uji 611‐0011, Japan.

                Email: akifumi_sugiyama@ 123456rish.kyoto-u.ac.jp

                Author information
                https://orcid.org/0000-0002-5271-6583
                https://orcid.org/0000-0003-0824-5873
                https://orcid.org/0000-0002-9643-6639
                Article
                PLD3286
                10.1002/pld3.286
                7673354
                33241173
                7469738d-1ca4-4a98-aef1-b48d1c015bf6
                © 2020 The Authors. Plant Direct published by American Society of Plant Biologists, Society for Experimental Biology and John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 23 April 2020
                : 23 September 2020
                : 14 October 2020
                Page count
                Figures: 12, Tables: 1, Pages: 15, Words: 8038
                Funding
                Funded by: JST‐CREST
                Award ID: JPMJCR17O2
                Award ID: JPMJCR15O2
                Funded by: JSPS KAKENHI
                Award ID: 18H02313
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                November 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.4 mode:remove_FC converted:18.11.2020

                diurnal variability,isoflavones,soyasaponins,soybean roots,transcriptome analysis,transporters

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