A generative model for the behavior of RNA polymerase.
Transcription by RNA polymerase is a highly dynamic process involving multiple distinct points of regulation. Nascent transcription assays are a relatively new set of high throughput techniques that measure the location of actively engaged RNA polymerase genome wide. Hence, nascent transcription is a rich source of information on the regulation of RNA polymerase activity. To fully dissect this data requires the development of stochastic models that can both deconvolve the stages of polymerase activity and identify significant changes in activity between experiments.



We present a generative, probabilistic model of RNA polymerase that fully describes loading, initiation, elongation and termination. We fit this model genome wide and profile the enzymatic activity of RNA polymerase across various loci and following experimental perturbation. We observe striking correlation of predicted loading events and regulatory chromatin marks. We provide principled statistics that compute probabilities reminiscent of traveler's and divergent ratios. We finish with a systematic comparison of RNA Polymerase activity at promoter versus non-promoter associated loci.



Transcription Fit (Tfit) is a freely available, open source software package written in C/C ++ that requires GNU compilers 4.7.3 or greater. Tfit is available from GitHub (https://github.com/azofeifa/Tfit).



robin.dowell@colorado.eduSupplementary information: Supplementary data are available at Bioinformatics online.
Department of Computer Science, University of Colorado, Boulder, CO, USA.
Joseph G
JG
Azofeifa
Department of Computer Science, University of Colorado, Boulder, CO, USA.|Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, CO, USA.|BioFrontiers Institute, University of Colorado, Boulder, CO, USA.
Robin D
RD
Dowell
D002843:Chromatin / Q000378:metabolism; D012321:DNA-Directed RNA Polymerases / Q000378:metabolism*; D056890:Eukaryota / Q000201:enzymology / Q000235:genetics; D008954:Models, Biological; D008958:Models, Molecular; D015233:Models, Statistical; D011401:Promoter Regions, Genetic; D012984:Software
D002843:Chromatin; D012321:DNA-Directed RNA Polymerases
Science. 2008 Mar 28;319(5871):1791-2
18369138
Cell. 2014 Dec 18;159(7):1524-37
25483777
Mol Cell. 2015 Apr 16;58(2):362-70
25801169
J Math Biol. 2017 Jan;74(1-2):77-97
27142882
Nature. 2007 Jun 14;447(7146):799-816
17571346
Nat Genet. 2014 Dec;46(12):1311-20
25383968
Elife. 2014 May 27;3:e02200
24867637
Nat Methods. 2015 May;12(5):433-8
25799441
Genome Res. 2012 Sep;22(9):1775-89
22955988
Curr Opin Genet Dev. 2012 Apr;22(2):110-4
22365496
Cell. 2013 Mar 14;152(6):1237-51
23498934
Cell. 2013 Dec 19;155(7):1581-1595
24360279
Semin Cancer Biol. 2013 Apr;23(2):65-71
22285981
BMC Bioinformatics. 2015 Jul 16;16:222
26173492
Nucleic Acids Res. 2014 Feb;42(4):2433-47
24304890
Elife. 2014 Apr 29;3:e02407
24843027
Genes Dev. 2014 Dec 1;28(23):2663-76
25452276
Mol Cell. 2015 Oct 15;60(2):256-67
26474067
Proc Natl Acad Sci U S A. 2010 Dec 14;107(50):21931-6
21106759
Cell. 2013 Apr 11;153(2):307-19
23582322
Nature. 2009 Sep 10;461(7261):186-92
19741698
Nature. 2012 Sep 6;489(7414):57-74
22955616
IEEE/ACM Trans Comput Biol Bioinform. 2017 Sep-Oct;14 (5):1070-1081
26829802
Genome Biol. 2011 Nov 14;12(11):R113
22082242
Genome Res. 2013 Aug;23(8):1210-23
23636943
Nucleic Acids Res. 2016 Jan 4;44(D1):D164-71
26438538
Nat Struct Mol Biol. 2015 May;22(5):396-403
25849141
Cell. 2015 Apr 23;161(3):526-540
25910207
Trends Genet. 2015 Aug;31(8):426-33
26073855
Nat Rev Genet. 2014 Mar;15(3):163-75
24514444
Annu Rev Genet. 2012;46:1-19
22905871
Nature. 2011 May 15;474(7351):390-4
21572438
Nat Rev Genet. 2016 Apr;17(4):207-23
26948815
PLoS One. 2013 Aug 08;8(8):e71355
23951143
Nat Rev Genet. 2012 Oct;13(10):720-31
22986266
Science. 2013 Feb 22;339(6122):950-3
23430654
Genes Dev. 2006 Sep 1;20(17):2349-54
16951251
Nat Rev Mol Cell Biol. 2015 Mar;16(3):167-77
25693130
Cell. 2009 Jun 26;137(7):1194-211
19563753