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      The bHLH-zip transcription factor SREBP regulates triterpenoid and lipid metabolisms in the medicinal fungus Ganoderma lingzhi

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          Abstract

          Ganoderic acids (GAs) are well recognized as important pharmacological components of the medicinal species belonging to the basidiomycete genus Ganoderma. However, transcription factors directly regulating the expression of GA biosynthesis genes remain poorly understood. Here, the genome of Ganoderma lingzhi is de novo sequenced. Using DNA affinity purification sequencing, we identify putative targets of the transcription factor sterol regulatory element-binding protein (SREBP), including the genes of triterpenoid synthesis and lipid metabolism. Interactions between SREBP and the targets are verified by electrophoretic mobility gel shift assay. RNA-seq shows that SREBP targets, mevalonate kinase and 3-hydroxy-3-methylglutaryl coenzyme A synthetase in mevalonate pathway, sterol isomerase and lanosterol 14-demethylase in ergosterol biosynthesis, are significantly upregulated in the SREBP overexpression (OE::SREBP) strain. In addition, 3 targets involved in glycerophospholipid/glycerolipid metabolism are upregulated. Then, the contents of mevalonic acid, lanosterol, ergosterol and 13 different GAs as well as a variety of lipids are significantly increased in this strain. Furthermore, the effects of SREBP overexpression on triterpenoid and lipid metabolisms are recovered when OE::SREBP strain are treated with exogenous fatostatin, a specific inhibitor of SREBP. Taken together, our genome-wide study clarify the role of SREBP in triterpenoid and lipid metabolisms of G. lingzhi.

          Abstract

          An integration of genomic, DAP-seq, RNA-seq, metabolomic and genetic approaches identifies SREBP as a key transcription factor regulating triterpenoid and lipid metabolisms in the medicinal fungus Ganoderma lingzhi.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                gaoliuedu@csuft.edu.cn
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                3 January 2023
                3 January 2023
                2023
                : 6
                : 1
                Affiliations
                [1 ]GRID grid.440660.0, ISNI 0000 0004 1761 0083, Hunan Provincial Key Laboratory of Forestry Biotechnology, , Central South University of Forestry & Technology, ; Changsha, Hunan 410004 China
                [2 ]GRID grid.440660.0, ISNI 0000 0004 1761 0083, International Cooperation Base of Science and Technology Innovation on Forest Resource Biotechnology of Hunan Province, , Central South University of Forestry & Technology, ; Changsha, Hunan 410004 China
                [3 ]Microbial Variety Creation Center, Yuelushan Laboratory of Seed Industry, Changsha, 410004 China
                Author information
                http://orcid.org/0000-0002-4005-0868
                http://orcid.org/0000-0001-9620-1752
                Article
                4154
                10.1038/s42003-022-04154-6
                9810662
                36596887
                054bdf1e-fb49-4c52-8248-a4cd17103830
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 July 2022
                : 21 October 2022
                Funding
                Funded by: National Natural Science Foundation of China (31900027, 31772374 and 32071673), the China Postdoctoral Science Foundation (2020M682601), the Science and Technology Innovation Program of Hunan Province (2020RC2059 and 2021RC4063), the Natural Science Foundation of Hunan Province (2020JJ5972 and 2021JJ31151), the Scientific Research Fund of Hunan Provincial Education Department, China (NO. 18B167 to Y.N.L).
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                © The Author(s) 2023

                applied microbiology,environmental microbiology,fungal biology

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