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      Genome-wide identification and evolution of WNK kinases in Bambusoideae and transcriptional profiling during abiotic stress in Phyllostachys edulis

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          Abstract

          With-no-lysine (WNK) kinases play vital roles in abiotic stress response, circadian rhythms, and regulation of flowering time in rice, Arabidopsis, and Glycine max. However, there are no previous reports of WNKs in the Bambusoideae, although genome sequences are available for diploid, tetraploid, and hexaploid bamboo species. In the present study, we identified 41 WNK genes in five bamboo species and analysed gene evolution, phylogenetic relationship, physical and chemical properties, cis-elements, and conserved motifs. We predicted the structure of PeWNK proteins of moso bamboo and determined the exposed, buried, structural and functional amino acids. Real-time qPCR analysis revealed that PeWNK5, PeWNK7, PeWNK8, and PeWNK11 genes are involved in circadian rhythms. Analysis of gene expression of different organs at different developmental stages revealed that PeWNK genes are tissue-specific. Analysis of various abiotic stress transcriptome data (drought, salt, SA, and ABA) revealed significant gene expression levels in all PeWNKs except PeWNK11. In particular, PeWNK8 and PeWNK9 were significantly down- and up-regulated, respectively, after abiotic stress treatment. A co-expression network of PeWNK genes also showed that PeWNK2, PeWNK4, PeWNK7, and PeWNK8 were co-expressed with transcriptional regulators related to abiotic stress. In conclusion, our study identified the PeWNKs of moso bamboo involved in circadian rhythms and abiotic stress response. In addition, this study serves as a guide for future functional genomic studies of the WNK genes of the Bambusoideae.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            TBtools - an integrative toolkit developed for interactive analyses of big biological data

            The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
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              ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules

              The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                13 January 2022
                2022
                : 10
                : e12718
                Affiliations
                [1 ]State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University , Lin’an, Zhejiang, China
                [2 ]State Key Laboratory of Subtropical Silviculture, Department of Traditional Chinese Medicine, Zhejiang A & F University , Lin’an, Zhejiang, China
                Article
                12718
                10.7717/peerj.12718
                8761366
                35070502
                589786a2-e8f8-4db5-8702-effb977a7248
                ©2022 Liu et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 6 September 2021
                : 9 December 2021
                Funding
                Funded by: The National Key Research & Development Program of China
                Award ID: 2021YFD2200503
                Funded by: The Research Fund for International Young Scientist, the National Natural Science Foundation of China
                Award ID: 32150410354
                Funded by: The National Natural Science Foundation of China
                Award ID: 31971735
                Funded by: The Natural Science Foundation of Zhejiang Province
                Award ID: LZ20C160002
                Funded by: The State Key Laboratory of Subtropical Silviculture
                Award ID: ZY20180203
                This work was supported by grants from the National Key Research & Development Program of China (2021YFD2200503), the Research Fund for International Young Scientist, the National Natural Science Foundation of China (32150410354), the National Natural Science Foundation of China (31971735), the Natural Science Foundation of Zhejiang Province (LZ20C160002), and the State Key Laboratory of Subtropical Silviculture (ZY20180203). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Agricultural Science
                Bioinformatics
                Plant Science

                wnk,moso bamboo,gene expression,abiotic stress
                wnk, moso bamboo, gene expression, abiotic stress

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