2016
DOI: 10.1128/jvi.02617-15
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Occupancy of RNA Polymerase II Phosphorylated on Serine 5 (RNAP S5 P ) and RNAP S2 P on Varicella-Zoster Virus Genes 9, 51, and 66 Is Independent of Transcript Abundance and Polymerase Location within the Gene

Abstract: Regulation of gene transcription in varicella-zoster virus (VZV), a ubiquitous human neurotropic alphaherpesvirus, requires coordinated binding of multiple host and virus proteins onto specific regions of the virus genome. Chromatin immunoprecipitation (ChIP) is widely used to determine the location of specific proteins along a genomic region. Since the size range of sheared virus DNA fragments governs the limit of accurate protein localization, particularly for compact herpesvirus genomes, we used a quantitat… Show more

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Cited by 12 publications
(9 citation statements)
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References 55 publications
(56 reference statements)
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“…Samples were submitted to the University of Colorado Cancer Center Microarray and Genomics shared resource for analysis of RNA quality, library preparation, and directional mRNA next-generation sequencing at 50 cycles of single-end reads on an Illumina Hi-Seq 4000 instrument. Sequencing data were processed through a custom computational pipeline consisting of the open-source gSNAP, Cufflinks, and R for alignment and discovery of differential gene expression [ 58 , 59 ]. Fragments per kilobase of exon per million mapped reads (FPKM) were used for comparison of transcript levels, and significant differences in gene expression were calculated using ANOVA in R. Functional annotation analysis was performed using the National Institutes of Health Database for Annotation, Visualization, and Integrated Discovery (DAVID) public on-line tool ( http://david.abcc.ncifcrf.gov/ ) using Biological Process Gene Ontology (GO) terms.…”
Section: Methodsmentioning
confidence: 99%
“…Samples were submitted to the University of Colorado Cancer Center Microarray and Genomics shared resource for analysis of RNA quality, library preparation, and directional mRNA next-generation sequencing at 50 cycles of single-end reads on an Illumina Hi-Seq 4000 instrument. Sequencing data were processed through a custom computational pipeline consisting of the open-source gSNAP, Cufflinks, and R for alignment and discovery of differential gene expression [ 58 , 59 ]. Fragments per kilobase of exon per million mapped reads (FPKM) were used for comparison of transcript levels, and significant differences in gene expression were calculated using ANOVA in R. Functional annotation analysis was performed using the National Institutes of Health Database for Annotation, Visualization, and Integrated Discovery (DAVID) public on-line tool ( http://david.abcc.ncifcrf.gov/ ) using Biological Process Gene Ontology (GO) terms.…”
Section: Methodsmentioning
confidence: 99%
“…1. Pipeline 1: For an initial 'pipeline' to identify mRNA-based gene expression changes between control and DCM mandibular prominences, derived fastq sequences were analyzed by applying a custom computational workflow (Baird et al, 2014;Bradford et al, 2015;Henderson et al, 2015;Maycotte et al, 2015) consisting of the open-source gSNAP (Wu and Nacu, 2010), Cufflinks (Trapnell et al, 2010), and R for sequence alignment and ascertainment of differential gene expression. In short, reads generated were mapped to the mouse genome (Mm10) by gSNAP, expression (FPKM) derived by Cufflinks and differential expression analyzed with ANOVA in R.…”
Section: Data Analysis (Bioinformatic Pipelines)mentioning
confidence: 99%
“…After RNA-seq, derived sequences were analyzed by applying a custom computational pipeline that consisted of the opensource gSNAP, Cufflinks, and R for sequence alignment and ascertainment of differential gene expression. [12][13][14][15] In short, the reads generated were mapped to the human genome (hg10) by gSNAP, expression (fragments per kilobase of transcript per million mapped reads; FPKM) derived by Cufflinks, and differential expression was analyzed with analysis of variance in R. 16,17 Analyses of variance were performed to compare the expression levels of all four control subjects and all four subjects with CRS on a gene-by-gene basis. Once the gene list was formed, data were analyzed by using Ingenuity Pathway Analysis (Qiagen, Redwood City, CA).…”
Section: Discussionmentioning
confidence: 99%