scholarly journals Comprehensive profiling of the fission yeast transcription start site activity during stress and media response

2018 ◽  
Author(s):  
Malte Thodberg ◽  
Axel Thieffry ◽  
Jette Bornholdt ◽  
Mette Boyd ◽  
Christian Holmberg ◽  
...  
Keyword(s):  
Fission Yeast ◽  
Nucleosome Occupancy ◽  
Model Organism ◽  
Proximal Promoter ◽  
Response Patterns ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
Genome Wide ◽  
Expression Response ◽  
Cap Analysis

AbstractFission yeast, Schizosaccharomyces pombe, is an attractive model organism for transcriptional and chromatin biology research. Such research is contingent on accurate annotation of transcription start sites (TSSs). However, comprehensive genome-wide maps of TSSs and their usage across commonly applied laboratory conditions and treatments for S. pombe are lacking. To this end, we profiled TSS activity genome-wide in S. pombe cultures exposed to heat shock, nitrogen starvation, hydrogen peroxide and two commonly applied media, YES and EMM2, using Cap Analysis of Gene Expression (CAGE). CAGE-based annotation of TSSs is substantially more accurate than existing PomBase annotation; on average, CAGE TSSs fall 50-75 bp downstream of PomBase TSSs and co-localize with nucleosome boundaries. In contrast to higher eukaryotes, S. pombe does not show sharp and dispersed TSS distributions. Our data recapitulate known S. pombe stress expression response patterns and identify stress- and mediaresponsive alternative TSSs. Notably, alteration of growth medium induces changes of similar magnitude as some stressors. We show a link between nucleosome occupancy and genetic variation, and that the proximal promoter region is genetically diverse between S. pombe strains. Our detailed TSS map constitute a central resource for S. pombe gene regulation research.

Cap Analysis of Gene Expression (CAGE): A Quantitative and Genome-Wide Assay of Transcription Start Sites

2020 ◽  
pp. 277-301 ◽  
Author(s):  
Masaki Suimye Morioka ◽  
Hideya Kawaji ◽  
Hiromi Nishiyori-Sueki ◽  
Mitsuyoshi Murata ◽  
Miki Kojima-Ishiyama ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
Genome Wide ◽  
Cap Analysis

scholarly journals CAGEfightR: analysis of 5′-end data using R/Bioconductor

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Malte Thodberg ◽  
Axel Thieffry ◽  
Kristoffer Vitting-Seerup ◽  
Robin Andersson ◽  
Albin Sandelin
Keyword(s):  
Bioconductor Package ◽  
Transcription Start ◽  
Computational Tools ◽  
Transcription Start Sites ◽  
Genome Wide ◽  
Current Availability ◽  
Efficient Prediction ◽  
Downstream Analysis ◽  
Cap Analysis ◽  
Memory Efficient

Abstract Background 5′-end sequencing assays, and Cap Analysis of Gene Expression (CAGE) in particular, have been instrumental in studying transcriptional regulation. 5′-end methods provide genome-wide maps of transcription start sites (TSSs) with base pair resolution. Because active enhancers often feature bidirectional TSSs, such data can also be used to predict enhancer candidates. The current availability of mature and comprehensive computational tools for the analysis of 5′-end data is limited, preventing efficient analysis of new and existing 5′-end data. Results We present CAGEfightR, a framework for analysis of CAGE and other 5′-end data implemented as an R/Bioconductor-package. CAGEfightR can import data from BigWig files and allows for fast and memory efficient prediction and analysis of TSSs and enhancers. Downstream analyses include quantification, normalization, annotation with transcript and gene models, TSS shape statistics, linking TSSs to enhancers via co-expression, identification of enhancer clusters, and genome-browser style visualization. While built to analyze CAGE data, we demonstrate the utility of CAGEfightR in analyzing nascent RNA 5′-data (PRO-Cap). CAGEfightR is implemented using standard Bioconductor classes, making it easy to learn, use and combine with other Bioconductor packages, for example popular differential expression tools such as limma, DESeq2 and edgeR. Conclusions CAGEfightR provides a single, scalable and easy-to-use framework for comprehensive downstream analysis of 5′-end data. CAGEfightR is designed to be interoperable with other Bioconductor packages, thereby unlocking hundreds of mature transcriptomic analysis tools for 5′-end data. CAGEfightR is freely available via Bioconductor: bioconductor.org/packages/CAGEfightR .

scholarly journals Genome-Wide Identification of Transcription Start Sites, Promoters and Transcription Factor Binding Sites in E. coli

PLoS ONE ◽  
2009 ◽  
Vol 4 (10) ◽  
pp. e7526 ◽  
Author(s):  
Alfredo Mendoza-Vargas ◽  
Leticia Olvera ◽  
Maricela Olvera ◽  
Ricardo Grande ◽  
Leticia Vega-Alvarado ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
E Coli ◽  
Factor Binding ◽  
Genome Wide

scholarly journals Genome-Wide Identification of Estrogen Receptor α-Binding Sites in Mouse Liver

2008 ◽  
Vol 22 (1) ◽  
pp. 10-22 ◽  
Author(s):  
Hui Gao ◽  
Susann Fält ◽  
Albin Sandelin ◽  
Jan-Åke Gustafsson ◽  
Karin Dahlman-Wright
Keyword(s):  
Estrogen Receptor ◽  
Binding Sites ◽  
Mouse Liver ◽  
Estrogen Receptor Α ◽  
Estrogen Signaling ◽  
Transcription Start ◽  
Expression Levels ◽  
Transcription Start Sites ◽  
Genome Wide ◽  
Binding Regions

Abstract We report the genome-wide identification of estrogen receptor α (ERα)-binding regions in mouse liver using a combination of chromatin immunoprecipitation and tiled microarrays that cover all nonrepetitive sequences in the mouse genome. This analysis identified 5568 ERα-binding regions. In agreement with what has previously been reported for human cell lines, many ERα-binding regions are located far away from transcription start sites; approximately 40% of ERα-binding regions are located within 10 kb of annotated transcription start sites. Almost 50% of ERα-binding regions overlap genes. The majority of ERα-binding regions lie in regions that are evolutionarily conserved between human and mouse. Motif-finding algorithms identified the estrogen response element, and variants thereof, together with binding sites for activator protein 1, basic-helix-loop-helix proteins, ETS proteins, and Forkhead proteins as the most common motifs present in identified ERα-binding regions. To correlate ERα binding to the promoter of specific genes, with changes in expression levels of the corresponding mRNAs, expression levels of selected mRNAs were assayed in livers 2, 4, and 6 h after treatment with ERα-selective agonist propyl pyrazole triol. Five of these eight selected genes, Shp, Stat3, Pdgds, Pck1, and Pdk4, all responded to propyl pyrazole triol after 4 h treatment. These results extend our previous studies using gene expression profiling to characterize estrogen signaling in mouse liver, by characterizing the first step in this signaling cascade, the binding of ERα to DNA in intact chromatin.

scholarly journals Transcription start sites and epigenetic analysis of the HSD17B10 proximal promoter

2013 ◽  
Vol 14 (1) ◽  
pp. 17 ◽  
Author(s):  
Song-Yu Yang ◽  
Carl Dobkin ◽  
Xue-Ying He ◽  
W Brown
Keyword(s):  
Proximal Promoter ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
Epigenetic Analysis

scholarly journals A heterochromatic histone methyltransferase lowers nucleosome occupancy at euchromatic promoters

2018 ◽  
Author(s):  
H.M. Chen ◽  
T.B. Sackton ◽  
B. Mutlu ◽  
J. Wang ◽  
S. Keppler-Ross ◽  
...  
Keyword(s):  
Nucleosome Occupancy ◽  
Histone H3 ◽  
Nuclear Lamina ◽  
Regulatory Elements ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
C Elegans ◽  
Muscle Gene Expression ◽  
Chromatin Configuration ◽  
Muscle Gene

AbstractH3K9me3 (histone H3 modified with tri-methylation at lysine 9) is a hallmark of transcriptional silencing and heterochromatin. However, its global effects on the genome, including euchromatin, are less well understood. Here we develop Formaldehyde-Assisted Identification of Regulatory Elements (FAIRE) for C. elegans to examine the chromatin configuration of mutants that lack virtually all H3K9me3, while leaving H3K9me1 and H3K9me2 intact. We find that nucleosomes are mildly disrupted, and levels of H3K9me2 and H3K27me3 rise in mutant embryos. In addition to these expected changes, the most dramatic change occurs in euchromatin: many regions encompassing transcription start sites (TSSs) gain an average of two nucleosomes in mutants. The affected regions normally lack H3K9me3, revealing a locus non-autonomous role for H3K9me3. Affected TSSs are associated with genes that are active in epithelia and muscles, and implicated in development, locomotion, morphogenesis and transcription. Mutant embryos develop normally under ideal laboratory conditions but die when challenged, with defects in morphogenesis and development. Our findings reveal that H3K9me3 protects transcription start sites within euchromatin from nucleosome deposition. These results may be relevant to mammals, where diseases that disrupt the nuclear lamina and heterochromatin can alter epithelial and muscle gene expression.

scholarly journals Dynamics of transcription-dependent H3K36me3 marking by the SETD2:IWS1:SPT6 ternary complex

2019 ◽  
Author(s):  
Katerina Cermakova ◽  
Eric A. Smith ◽  
Vaclav Veverka ◽  
H. Courtney Hodges
Keyword(s):  
Ternary Complex ◽  
Spatial Distributions ◽  
Epigenetic Memory ◽  
Dynamic Features ◽  
Transcription Start ◽  
Accurate Representation ◽  
Transcription Start Sites ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Tight Correlation

AbstractSETD2 contributes to gene expression by marking gene bodies with H3K36me3, which is thought to assist in the concentration of transcription machinery at the small portion of the coding genome. Despite extensive genome-wide data revealing the precise localization of H3K36me3 over gene bodies, the physical basis for the accumulation, maintenance, and sharp borders of H3K36me3 over these sites remains rudimentary. Here we propose a model of H3K36me3 marking based on stochastic transcription-dependent placement and transcription-independent spreading. Our analysis of the spatial distributions and dynamic features of these marks indicates that transcription-dependent placement dominates the establishment of H3K36me3 domains compared to transcription-independent spreading processes, and that turnover of H3K36me3 limits its capacity for epigenetic memory. By adding additional terms for asymmetric histone turnover occurring at transcription start sites, our model provides a remarkably accurate representation of H3K36me3 levels and dynamics over gene bodies. Furthermore, we validate our findings by revealing that loss of SPT6 impairs the transcription-coupled activity of the SETD2:IWS1:SPT6 ternary complex, thereby reducing the tight correlation between transcription and H3K36me3 levels at gene bodies.

scholarly journals DChIPRep, an R/Bioconductor package for differential enrichment analysis in chromatin studies

2016 ◽  
Author(s):  
Christophe D Chabbert ◽  
Lars M Steinmetz ◽  
Bernd Klaus
Keyword(s):  
Input Data ◽  
Enrichment Analysis ◽  
Bioconductor Package ◽  
Analytic Framework ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
Genome Wide ◽  
Bioconductor Project ◽  
User Friendly ◽  
Genome Wide Study

The genome–wide study of epigenetic states requires the integrative analysis of histone modification ChIP–seq data. Here, we introduce an easy–to–use analytic framework to compare profiles of enrichment in histone modifications around classes of genomic elements, e.g. transcription start sites (TSS). Our framework is available via the user–friendly R/Bioconductor package DChIPRep. DChIPRep uses biological replicate information as well as chromatin Input data to allow for a rigorous assessment of differential enrichment. DChIPRep is available for download through the Bioconductor project at http://bioconductor.org/packages/DChIPRep. Contact [email protected]

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