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      Transcriptomics reveal core activities of the plant growth-promoting bacterium Delftia acidovorans RAY209 during interaction with canola and soybean roots

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          Abstract

          The plant growth-promoting rhizobacterium Delftia acidovorans RAY209 is capable of establishing strong root attachment during early plant development at 7 days post-inoculation. The transcriptional response of RAY209 was measured using RNA-seq during early (day 2) and sustained (day 7) root colonization of canola plants, capturing RAY209 differentiation from a medium-suspended cell state to a strongly root-attached cell state. Transcriptomic data was collected in an identical manner during RAY209 interaction with soybean roots to explore the putative root colonization response to this globally relevant crop. Analysis indicated there is an increased number of significantly differentially expressed genes between medium-suspended and root-attached cells during early soybean root colonization relative to sustained colonization, while the opposite temporal pattern was observed for canola root colonization. Regardless of the plant host, root-attached RAY209 cells exhibited the least amount of differential gene expression between early and sustained root colonization. Root-attached cells of either canola or soybean roots expressed high levels of a fasciclin gene homolog encoding an adhesion protein, as well as genes encoding hydrolases, multiple biosynthetic processes, and membrane transport. Notably, while RAY209 ABC transporter genes of similar function were transcribed during attachment to either canola or soybean roots, several transporter genes were uniquely differentially expressed during colonization of the respective plant hosts. In turn, both canola and soybean plants expressed genes encoding pectin lyase and hydrolases – enzymes with purported function in remodelling extracellular matrices in response to RAY209 colonization. RAY209 exhibited both a core regulatory response and a planthost-specific regulatory response to root colonization, indicating that RAY209 specifically adjusts its cellular activities to adapt to the canola and soybean root environments. This transcriptomic data defines the basic RAY209 response as both a canola and soybean commercial crop and seed inoculant.

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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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              STAR: ultrafast universal RNA-seq aligner.

              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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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                mgen
                mgen
                Microbial Genomics
                Microbiology Society
                2057-5858
                November 2020
                5 November 2020
                5 November 2020
                : 6
                : 11
                : mgen000462
                Affiliations
                [ 1] departmentDepartment of Biology , University of Regina , Regina, SK, Canada
                [ 2] Lallemand Plant Care North America , Saskatoon, SK, Canada
                [ 3] departmentDepartment of Food and Bioproduct Sciences , University of Saskatchewan , Saskatoon, SK, Canada
                [ 4] departmentAquatic Crop Resource Development , National Research Council , Saskatoon, SK, Canada
                Author notes
                [†]

                These authors contributed equally to this work

                *Correspondence: Christopher K. Yost, christopher.yost@ 123456uregina.ca
                Author information
                https://orcid.org/0000-0001-8961-652X
                https://orcid.org/0000-0001-7005-8492
                https://orcid.org/0000-0002-5623-6237
                https://orcid.org/0000-0001-6791-0904
                https://orcid.org/0000-0001-6350-209X
                https://orcid.org/0000-0002-1760-3698
                https://orcid.org/0000-0001-6118-7225
                Article
                000462
                10.1099/mgen.0.000462
                7725335
                33151138
                7eb5990b-1ffc-47ba-852c-38754e37833c
                © 2020 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution License.

                History
                : 28 May 2020
                : 13 October 2020
                Funding
                Funded by: Natural Sciences and Engineering Research Council of Canada
                Award ID: PDF
                Award Recipient : Jordyn Bergsveinson
                Funded by: Natural Sciences and Engineering Research Council of Canada
                Award ID: CRD
                Award Recipient : Christopher K Yost
                Categories
                Research Article
                Systems Microbiology: Transcriptomics, proteomics, networks
                Custom metadata
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                canola,delftia,inoculant,pgpr,rna-seq,soybean
                canola, delftia, inoculant, pgpr, rna-seq, soybean

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