On the Distribution of Transcription Times
Keywords:gene transcription, stochastic model
AbstractA previously studied model of prokaryotic transcription [Roussel and Zhu, Bull. Math. Biol. 68 (2006) 1681--1713] is revisited. The first four moments of the distribution of transcription times are obtained analytically and analyzed. A Gaussian is found to be a poor approximation to this distribution for short transcription units at typical values of the rate constants, but a good approximation for long transcription units. An approximate form of the distribution is obtained in which the slow steps are treated exactly and the fast steps are lumped together into a single lag term. This approximate form might be particularly useful as a function to be fit to experimental transcription time distributions. Multi-polymerase effects are also studied by simulation. We find that the analytic model generally predicts the behavior of the multi-polymerase simulations, often quantitatively, provided termination is not rate-limiting.
The journal Biomath is an open access journal. All published articles are immeditely available online and the respective DOI link activated. All articles can be access for free and no reader registration of any sort is required. No fees are charged to authors for article submission or processing. Online publications are funded through volunteer work, donations and grants.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).