Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model.

E.N. Rybakova; A. Tomaszewska; A. van Mourik; J. Blom; H.V. Westerhoff; C. Carlberg; F.J. Bruggeman

doi:10.1093/nar/gku1272

Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model.

E.N. Rybakova, A. Tomaszewska, A. van Mourik, J. Blom, H.V. Westerhoff, C. Carlberg, F.J. Bruggeman

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Changes in transcription factor levels, epigenetic status, splicing kinetics and mRNA degradation can each contribute to changes in the mRNA dynamics of a gene. We present a novel method to identify which of these processes is changed in cells in response to external signals or as a result of a diseased state. The method employs a mathematical model, for which the kinetics of gene regulation, splicing, elongation and mRNA degradation were estimated from experimental data of transcriptional dynamics. The time-dependent dynamics of several species of adipose differentiation-related protein (ADRP) mRNA were measured in response to ligand activation of the transcription factor peroxisome proliferator-activated receptor δ (PPARδ). We validated the method by monitoring the mRNA dynamics upon gene activation in the presence of a splicing inhibitor. Our mathematical model correctly identifies splicing as the inhibitor target, despite the noise in the data.

Original language	English
Article number	1
Pages (from-to)	153-161
Journal	Nucleic Acids Research
Issue number	43
DOIs	https://doi.org/10.1093/nar/gku1272
Publication status	Published - 2015

Access to Document

10.1093/nar/gku1272

Persistent URL (handle)

Copy link address

Cite this

@article{7e7191febec949f0a4b8cd543534029b,

title = "Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model.",

abstract = "Changes in transcription factor levels, epigenetic status, splicing kinetics and mRNA degradation can each contribute to changes in the mRNA dynamics of a gene. We present a novel method to identify which of these processes is changed in cells in response to external signals or as a result of a diseased state. The method employs a mathematical model, for which the kinetics of gene regulation, splicing, elongation and mRNA degradation were estimated from experimental data of transcriptional dynamics. The time-dependent dynamics of several species of adipose differentiation-related protein (ADRP) mRNA were measured in response to ligand activation of the transcription factor peroxisome proliferator-activated receptor δ (PPARδ). We validated the method by monitoring the mRNA dynamics upon gene activation in the presence of a splicing inhibitor. Our mathematical model correctly identifies splicing as the inhibitor target, despite the noise in the data.",

author = "E.N. Rybakova and A. Tomaszewska and {van Mourik}, A. and J. Blom and H.V. Westerhoff and C. Carlberg and F.J. Bruggeman",

year = "2015",

doi = "10.1093/nar/gku1272",

language = "English",

pages = "153--161",

journal = "Nucleic Acids Research",

issn = "0305-1048",

publisher = "Oxford University Press",

number = "43",

}

TY - JOUR

T1 - Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model.

AU - Rybakova, E.N.

AU - Tomaszewska, A.

AU - van Mourik, A.

AU - Blom, J.

AU - Westerhoff, H.V.

AU - Carlberg, C.

AU - Bruggeman, F.J.

PY - 2015

Y1 - 2015

N2 - Changes in transcription factor levels, epigenetic status, splicing kinetics and mRNA degradation can each contribute to changes in the mRNA dynamics of a gene. We present a novel method to identify which of these processes is changed in cells in response to external signals or as a result of a diseased state. The method employs a mathematical model, for which the kinetics of gene regulation, splicing, elongation and mRNA degradation were estimated from experimental data of transcriptional dynamics. The time-dependent dynamics of several species of adipose differentiation-related protein (ADRP) mRNA were measured in response to ligand activation of the transcription factor peroxisome proliferator-activated receptor δ (PPARδ). We validated the method by monitoring the mRNA dynamics upon gene activation in the presence of a splicing inhibitor. Our mathematical model correctly identifies splicing as the inhibitor target, despite the noise in the data.

AB - Changes in transcription factor levels, epigenetic status, splicing kinetics and mRNA degradation can each contribute to changes in the mRNA dynamics of a gene. We present a novel method to identify which of these processes is changed in cells in response to external signals or as a result of a diseased state. The method employs a mathematical model, for which the kinetics of gene regulation, splicing, elongation and mRNA degradation were estimated from experimental data of transcriptional dynamics. The time-dependent dynamics of several species of adipose differentiation-related protein (ADRP) mRNA were measured in response to ligand activation of the transcription factor peroxisome proliferator-activated receptor δ (PPARδ). We validated the method by monitoring the mRNA dynamics upon gene activation in the presence of a splicing inhibitor. Our mathematical model correctly identifies splicing as the inhibitor target, despite the noise in the data.

U2 - 10.1093/nar/gku1272

DO - 10.1093/nar/gku1272

M3 - Article

SN - 0305-1048

SP - 153

EP - 161

JO - Nucleic Acids Research

JF - Nucleic Acids Research

IS - 43

M1 - 1

ER -

Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model.

Abstract

Access to Document

Persistent URL (handle)

Fingerprint

Cite this