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A temporal switch model for estimating transcriptional activity in gene expression
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Jenkins, Dafyd J., Finkenstädt, Bärbel and Rand, D. A. (David A.) (2013) A temporal switch model for estimating transcriptional activity in gene expression. Bioinformatics, Volume 29 (Number 9). pp. 1158-1165. doi:10.1093/bioinformatics/btt111 ISSN 1367-4803.
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WRAP_Finkenstadt_Temporal_switch_Bioinformatics-2013-Jenkins-1158-65.pdf - Published Version Available under License Creative Commons Attribution. Download (604Kb) | Preview |
Official URL: http://dx.doi.org/10.1093/bioinformatics/btt111
Abstract
Motivation: The analysis and mechanistic modelling of time series gene expression data provided by techniques such as microarrays, NanoString, reverse transcription–polymerase chain reaction and advanced sequencing are invaluable for developing an understanding of the variation in key biological processes. We address this by proposing the estimation of a flexible dynamic model, which decouples temporal synthesis and degradation of mRNA and, hence, allows for transcriptional activity to switch between different states.
Results: The model is flexible enough to capture a variety of observed transcriptional dynamics, including oscillatory behaviour, in a way that is compatible with the demands imposed by the quality, time-resolution and quantity of the data. We show that the timing and number of switch events in transcriptional activity can be estimated alongside individual gene mRNA stability with the help of a Bayesian reversible jump Markov chain Monte Carlo algorithm. To demonstrate the methodology, we focus on modelling the wild-type behaviour of a selection of 200 circadian genes of the model plant Arabidopsis thaliana. The results support the idea that using a mechanistic model to identify transcriptional switch points is likely to strongly contribute to efforts in elucidating and understanding key biological processes, such as transcription and degradation.
| Item Type: | Journal Article | ||||
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| Subjects: | Q Science > QA Mathematics Q Science > QH Natural history > QH301 Biology Q Science > QH Natural history > QH426 Genetics |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics Faculty of Science, Engineering and Medicine > Science > Statistics |
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| Library of Congress Subject Headings (LCSH): | Gene expression, Genomics , Messenger RNA, Oscillating chemical reactions, Chemical reactions, Bayesian statistical decision theory, Arabidopsis thaliana | ||||
| Journal or Publication Title: | Bioinformatics | ||||
| Publisher: | Oxford University Press | ||||
| ISSN: | 1367-4803 | ||||
| Official Date: | 1 May 2013 | ||||
| Dates: |
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| Volume: | Volume 29 | ||||
| Number: | Number 9 | ||||
| Page Range: | pp. 1158-1165 | ||||
| DOI: | 10.1093/bioinformatics/btt111 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||
| Date of first compliant deposit: | 1 August 2016 | ||||
| Date of first compliant Open Access: | 1 August 2016 | ||||
| Funder: | Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC) , Engineering and Physical Sciences Research Council (EPSRC) | ||||
| Grant number: | BB/F005806/1 (BBSRC) ; EP/C544587/1 (EPSRC) |
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