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MoDATS SIGNED

Model-based Data Analysis of Transcription and Splicing

Total Cost €

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EC-Contrib. €

0

Partnership

0

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 MoDATS project word cloud

Explore the words cloud of the MoDATS project. It provides you a very rough idea of what is the project "MoDATS" about.

genome    experimentalists    resolved    integrating    underlying    kinetics    dna    acute    quantify    transcribed    biology    data    gene    ing    observations    polymerase    interactions    transcription    polymerization    components    interplay    talk    statistical    coupled    phenomenon    cross    unknown    constitutive    models    cells    nascent    probability    biologists    functional    splicing    protein    formulated    fundamental    sequencing    mrnas    labeling    give    previously    noisy    simultaneously    thousands    scientists    gigabytes    regulates    paradigm    collect    rna    generation    template    genes    effect    genomic    coding    time    completion    shows    biological    stochastic    distributions    multiple    removal    modern    produces    expression    ways    partial    machinery    intermediate    mrna    estimate    transcripts    mechanisms    eukaryotic    mechanism    types    encoding    struggle    decades    molecular    proposes    framework    molecules    yielded    ngs    regions    elongation    model    messenger    spliced    interrogate    complicates    analyze   

Project "MoDATS" data sheet

The following table provides information about the project.

Coordinator
THE UNIVERSITY OF EDINBURGH 

Organization address
address: OLD COLLEGE, SOUTH BRIDGE
city: EDINBURGH
postcode: EH8 9YL
website: www.ed.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://ewallace.github.io/
 Total cost 195˙454 €
 EC max contribution 195˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2014
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2016
 Duration (year-month-day) from 2016-01-05   to  2018-01-19

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF EDINBURGH UK (EDINBURGH) coordinator 195˙454.00

Map

 Project objective

Gene expression is the fundamental process that in all cells produces functional protein from a genomic DNA template using a messenger RNA (mRNA) intermediate. Eukaryotic gene expression involves transcription--the polymerization of mRNA--and splicing--the removal of non-coding regions from the mRNA. Recent evidence shows that nascent mRNAs are spliced while still being transcribed, not after completion of transcription, and that splicing machinery regulates transcription. This cross-talk complicates understanding of gene expression, as its mechanism and consequences are not understood. This project proposes using model-based data analysis, applied to multiple types of data, to study the kinetics of coupled transcription and splicing.

Model-based data analysis is a statistical framework in which models are formulated as probability distributions encoding the stochastic interactions between components, including observed data. Knowledge of the underlying mechanism--here, biological--is used to quantify both the phenomenon, and the uncertainty resulting from partial knowledge and noisy observations. The need for such analysis is acute in modern biology: decades of molecular biology have yielded detailed information on specific molecules and pathways, and now next-generation sequencing (NGS) allows scientists to collect gigabytes of data on thousands of distinct molecules simultaneously. Yet, integrating these approaches is challenging: biologists struggle to analyze NGS data in ways that give insight into known--and previously unknown--biological mechanisms.

Here, the model-based data analysis paradigm will be used to interrogate the interplay of transcription and splicing, using state-of the art data including time-resolved NGS measurements of RNA processing. Working with experimentalists, we will quantify the kinetics of splicing in constitutive genes by labeling nascent transcripts, and estimate the effect of splicing on polymerase elongation genome-wide.

 Publications

year authors and title journal last update
List of publications.
2017 Edward W.J. Wallace, Jean D. Beggs
Extremely fast and incredibly close: cotranscriptional splicing in budding yeast
published pages: 601-610, ISSN: 1355-8382, DOI: 10.1261/rna.060830.117
RNA 23/5 2019-06-18
2017 Oana Carja, Tongji Xing, Edward W. J. Wallace, Joshua B. Plotkin, Premal Shah
riboviz: analysis and visualization of ribosome profiling datasets
published pages: , ISSN: 1471-2105, DOI: 10.1186/s12859-017-1873-8
BMC Bioinformatics 18/1 2019-06-18

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