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      Genome-Wide Characterization and Expression Analysis of bZIP Gene Family Under Abiotic Stress in Glycyrrhiza uralensis

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          Abstract

          bZIP gene family is one of the largest transcription factor families. It plays an important role in plant growth, metabolic, and environmental response. However, complete genome-wide investigation of bZIP gene family in Glycyrrhiza uralensis remains unexplained. In this study, 66 putative bZIP genes in the genome of G. uralensis were identified. And their evolutionary classification, physicochemical properties, conserved domain, functional differentiation, and the expression level under different stress conditions were further analyzed. All the members were clustered into 13 subfamilies (A–K, M, and S). A total of 10 conserved motifs were found in GubZIP proteins. Members from the same subfamily shared highly similar gene structures and conserved domains. Tandem duplication events acted as a major driving force for the evolution of bZIP gene family in G. uralensis. Cis-acting elements and protein–protein interaction networks showed that GubZIPs in one subfamily are involved in multiple functions, while some GubZIPs from different subfamilies may share the same functional category. The miRNA network targeting GubZIPs showed that the regulation at the transcriptional level may affect protein–protein interaction networks. We suspected that domain-mediated interactions may categorize a protein family into subfamilies in G. uralensis. Furthermore, the tissue-specific gene expression patterns of GubZIPs were analyzed using the public RNA-seq data. Moreover, gene expression level of 66 bZIP family members under abiotic stress treatments was quantified by using qRT-PCR. The results of this study may serve as potential candidates for functional characterization in the future.

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          Most cited references67

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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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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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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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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                05 October 2021
                2021
                : 12
                : 754237
                Affiliations
                [ 1 ]The Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, China
                [ 2 ]Tasly R&D Institute, Tasly Holding Group Co., Ltd., Tianjin, China
                [ 3 ]Institute of Landscape and Plant Ecology, The School of Engineering and Architecture, Zhejiang Sci-tech University, Hangzhou, China
                Author notes

                Edited by: Ashish Kumar Srivastava, Bhabha Atomic Research Centre (BARC), India

                Reviewed by: Xiaojun Nie, Northwest A and F University, China

                Liangliang Gao, Kansas State University, United States

                *Correspondence: Zongsuo Liang, liangzs@ 123456zstu.edu.cn ; Ruilian Han, hanrl@ 123456nwafu.edu.cn

                This article was submitted to Plant Genomics, a section of the journal Frontiers in Genetics

                Article
                754237
                10.3389/fgene.2021.754237
                8525656
                34675967
                175477e0-e507-455a-8522-9713433ba915
                Copyright © 2021 Han, Hou, He, Zhang, Yan, Han and Liang.

                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
                : 06 August 2021
                : 13 September 2021
                Categories
                Genetics
                Original Research

                Genetics
                bzip transcription factor,licorice,abiotic stress,interaction network,expression
                Genetics
                bzip transcription factor, licorice, abiotic stress, interaction network, expression

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