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      Histone modification dynamics at H3K27 are associated with altered transcription of in planta induced genes in Magnaporthe oryzae

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      PLoS Genetics
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          Abstract

          Transcriptional dynamic in response to environmental and developmental cues are fundamental to biology, yet many mechanistic aspects are poorly understood. One such example is fungal plant pathogens, which use secreted proteins and small molecules, termed effectors, to suppress host immunity and promote colonization. Effectors are highly expressed in planta but remain transcriptionally repressed ex planta, but our mechanistic understanding of these transcriptional dynamics remains limited. We tested the hypothesis that repressive histone modification at H3-Lys27 underlies transcriptional silencing ex planta, and that exchange for an active chemical modification contributes to transcription of in planta induced genes. Using genetics, chromatin immunoprecipitation and sequencing and RNA-sequencing, we determined that H3K27me3 provides significant local transcriptional repression. We detail how regions that lose H3K27me3 gain H3K27ac, and these changes are associated with increased transcription. Importantly, we observed that many in planta induced genes were marked by H3K27me3 during axenic growth, and detail how altered H3K27 modification influences transcription. ChIP-qPCR during in planta growth suggests that H3K27 modifications are generally stable, but can undergo dynamics at specific genomic locations. Our results support the hypothesis that dynamic histone modifications at H3K27 contributes to fungal genome regulation and specifically contributes to regulation of genes important during host infection.

          Author summary

          Fungal pathogens of crops and humans pose annual threats to our food and health. There are many steps to the host infection process, during which fungal pathogens display unique growth, and use specific genes to cause disease. Despite this knowledge, many aspects of how pathogens regulate their genome to enact this process remain unknown. Here, we demonstrate how chemical modification of lysine residues on the histone H3, which helps organize and control DNA usage, play an important regulatory role in the model fungal pathogen causing rice blast disease. Our analysis shows a significant association between genes important for host infection and H3 lysine 27 methylation. We show that by experimentally changing histone modifications, many fungal genes normally used during plant infection are turned on outside of the host. Furthermore, we detail how histone modifications can change naturally in the fungus during plant infection. These findings help broaden our knowledge of genome regulation for these pathogens, and advances the goal of a more comprehensive understanding of the infection process.

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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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            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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              Fast and accurate short read alignment with Burrows–Wheeler transform

              Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                3 February 2021
                February 2021
                : 17
                : 2
                : e1009376
                Affiliations
                [001]Kansas State University, Department of Plant Pathology, Manhattan, Kansas, United States of America
                Gregor Mendel Institute of Molecular Plant Biology, AUSTRIA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5092-643X
                https://orcid.org/0000-0002-4071-0926
                https://orcid.org/0000-0002-2719-4701
                Article
                PGENETICS-D-20-01354
                10.1371/journal.pgen.1009376
                7886369
                33534835
                ec3ed502-5f9a-48d2-a86b-e00eb6c6e4ec
                © 2021 Zhang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 September 2020
                : 22 January 2021
                Page count
                Figures: 7, Tables: 0, Pages: 29
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100005825, National Institute of Food and Agriculture;
                Award ID: 2018-67013-28492
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000152, Division of Molecular and Cellular Biosciences;
                Award ID: 1936800
                Award Recipient :
                This work was supported in part by the United State Department of Agriculture-National Institute of Food and Agriculture (USDA-NIFA) (award no. 2018-67013-28492) ( https://nifa.usda.gov/), and by the National Science Foundation Division of Molecular and Cellular Biosciences – Systems and Synthetic Biology (award no. 1936800) ( https://www.nsf.gov/bio/mcb/about.jsp) to D.E.C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and life sciences
                Genetics
                Gene expression
                DNA transcription
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Grasses
                Rice
                Research and Analysis Methods
                Animal Studies
                Experimental Organism Systems
                Plant and Algal Models
                Rice
                Biology and Life Sciences
                Genetics
                Fungal Genetics
                Fungal Genomics
                Biology and Life Sciences
                Mycology
                Fungal Genetics
                Fungal Genomics
                Biology and Life Sciences
                Genetics
                Genomics
                Fungal Genomics
                Biology and Life Sciences
                Genetics
                Gene Expression
                Gene Regulation
                Biology and Life Sciences
                Cell Biology
                Chromosome Biology
                Chromatin
                Chromatin Modification
                Histone Modification
                Biology and Life Sciences
                Genetics
                Epigenetics
                Chromatin
                Chromatin Modification
                Histone Modification
                Biology and Life Sciences
                Genetics
                Gene Expression
                Chromatin
                Chromatin Modification
                Histone Modification
                Biology and Life Sciences
                Genetics
                Gene Expression
                Histone Modification
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                Genomic Signal Processing
                Custom metadata
                vor-update-to-uncorrected-proof
                2021-02-16
                Illumina sequence reads have been deposited at the National Center for Biotechnology Information, Short Reads Archive (BioProject accession No. PRJNA646251).

                Genetics
                Genetics

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