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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.

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

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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