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Binary transcriptional control of pattern formation in development

Lammers, Nicholas C. and Galstyan, Vahe and Reimer, Armando and Medin, Sean A. and Wiggins, Chris H. and Garcia, Hernan G. (2018) Binary transcriptional control of pattern formation in development. . (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20181030-124711523

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Abstract

During development, stochastic promoter switching between active and inactive states results in transcriptional bursts. We tested whether burst kinetics are sufficient to quantitatively recapitulate the formation of patterns of accumulated mRNA in Drosophila embryos by dissecting the transcriptional dynamics of even-skipped stripe 2. Using a novel memory-adjusted hidden Markov model, single-cell live imaging and theoretical modeling, we show that the regulation of bursting in space and time alone is insufficient to predict stripe formation. In addition to bursting, we discovered that the duration of the window of time over which genes transcribe is regulated, and that this binary (on/off) control of where and when gene expression occurs, not transcriptional bursting, is the main regulatory strategy governing stripe formation. Thus, a quantitative description of the regulation of both bursting and the transcriptional time window are necessary to capture the full complement of molecular rules governing the transcriptional control of pattern formation.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/335919DOIDiscussion Paper
ORCID:
AuthorORCID
Lammers, Nicholas C.0000-0001-6832-6152
Galstyan, Vahe0000-0001-7073-9175
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. bioRxiv preprint first posted online May. 31, 2018. We thank Thomas Gregor and Lev Barinov for discussion about an initial implementation of the mHMM approach, Florian Jug for help with the spot segmentation using machine learning, and Elizabeth Eck, Maryam Kazemzadeh-Atou1 and Jonathan Liu for the P2 data used in the absolute MS2 calibration. We are also grateful to Jack Bateman, Jane Kondev, Rob Phillips, Allyson Sgro and Donald Rio for comments and discussion on the manuscript. HGG was supported by the Burroughs Wellcome Fund Career Award at the Scientific Interface, the Sloan Research Foundation, the Human Frontiers Science Program, the Searle Scholars Program, the Shurl & Kay Curci Foundation, the Hellman Foundation, the NIH Director’s New Innovator Award (DP2 OD024541-01), and an NSF CAREER Award (1652236). NL was supported by NIH Genomics and Computational Biology training grant 5T32HG000047-18. CW was supported by the NIH/NIC (U54 CA193313), CUNY (RFCUNY 640D14-A), and the NSF (IIS-1344668).
Funders:
Funding AgencyGrant Number
Burroughs Wellcome FundUNSPECIFIED
Alfred P. Sloan FoundationUNSPECIFIED
Human Frontier Science ProgramUNSPECIFIED
Searle Scholars ProgramUNSPECIFIED
Shurl and Kay Curci FoundationUNSPECIFIED
Hellman FoundationUNSPECIFIED
NIHDP2 OD024541-01
NSFPHY-1652236
NIH Predoctoral Fellowship5T32HG000047-18
NIHU54 CA193313
Columbia University, New YorkRFCUNY 640D14-A
NSFIIS-1344668
Record Number:CaltechAUTHORS:20181030-124711523
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181030-124711523
Official Citation:Binary transcriptional control of pattern formation in development. Nicholas C Lammers, Vahe Galstyan, Armando Reimer, Sean A Medin, Chris H Wiggins, Hernan G Garcia. bioRxiv 335919; doi: https://doi.org/10.1101/335919
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90504
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:30 Oct 2018 20:04
Last Modified:30 Oct 2018 20:04

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