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      Identification and Validation of Reference Genes in Clostridium beijerinckii NRRL B-598 for RT-qPCR Using RNA-Seq Data

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          Abstract

          Gene expression analysis through reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) depends on correct data normalization by reference genes with stable expression. Although Clostridium beijerinckii NRRL B-598 is a promising Gram-positive bacterium for the industrial production of biobutanol, validated reference genes have not yet been reported. In this study, we selected 160 genes with stable expression based on an RNA sequencing (RNA-Seq) data analysis, and among them, seven genes ( zmp, rpoB1, rsmB, greA, rpoB2, topB2, and rimO) were selected for experimental validation by RT-qPCR and gene ontology (GO) enrichment analysis. According to statistical analyses, zmp and greA were the most stable and suitable reference genes for RT-qPCR normalization. Furthermore, our methodology can be useful for selection of the reference genes in other strains of C. beijerinckii and it also suggests that the RNA-Seq data can be used for the initial selection of novel reference genes, however, their validation is required.

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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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            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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              The Sequence Alignment/Map format and SAMtools

              Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                18 March 2021
                2021
                : 12
                : 640054
                Affiliations
                [1] 1Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology , Brno, Czechia
                [2] 2Department of Biotechnology, University of Chemistry and Technology Prague , Prague, Czechia
                Author notes

                Edited by: Krishnaveni Mishra, University of Hyderabad, India

                Reviewed by: Yi Wang, Auburn University, Auburn, United States; Peter-Dürre, University of Ulm, Ulm, Germany

                *Correspondence: Karel Sedlar, sedlar@ 123456vut.cz

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.640054
                8012504
                33815328
                6fe4d05a-434b-452d-afe6-9cd3d037ee17
                Copyright © 2021 Jureckova, Raschmanova, Kolek, Vasylkivska, Branska, Patakova, Provaznik and Sedlar.

                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
                : 10 December 2020
                : 17 February 2021
                Page count
                Figures: 2, Tables: 7, Equations: 0, References: 57, Pages: 10, Words: 0
                Funding
                Funded by: Grantová Agentura České Republiky 10.13039/501100001824
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                hkg,housekeeping genes,non-model organisms,biofuel,clostridium
                Microbiology & Virology
                hkg, housekeeping genes, non-model organisms, biofuel, clostridium

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