Predicting expression patterns from regulatory sequence in Drosophila segmentation

Eran Segal (), Tali Raveh-Sadka, Mark Schroeder, Ulrich Unnerstall and Ulrike Gaul ()
Additional contact information
Eran Segal: Weizmann Institute of Science
Tali Raveh-Sadka: Weizmann Institute of Science
Mark Schroeder: Laboratory of Developmental Neurogenetics, Rockefeller University, New York, New York 10065, USA
Ulrich Unnerstall: Laboratory of Developmental Neurogenetics, Rockefeller University, New York, New York 10065, USA
Ulrike Gaul: Laboratory of Developmental Neurogenetics, Rockefeller University, New York, New York 10065, USA

Nature, 2008, vol. 451, issue 7178, 535-540

Abstract: Abstract The establishment of complex expression patterns at precise times and locations is key to metazoan development, yet a mechanistic understanding of the underlying transcription control networks is still missing. Here we describe a novel thermodynamic model that computes expression patterns as a function of cis-regulatory sequence and of the binding-site preferences and expression of participating transcription factors. We apply this model to the segmentation gene network of Drosophila melanogaster and find that it predicts expression patterns of cis-regulatory modules with remarkable accuracy, demonstrating that positional information is encoded in the regulatory sequence and input factor distribution. Our analysis reveals that both strong and weaker binding sites contribute, leading to high occupancy of the module DNA, and conferring robustness against mutation; short-range homotypic clustering of weaker sites facilitates cooperative binding, which is necessary to sharpen the patterns. Our computational framework is generally applicable to most protein–DNA interaction systems.

Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.nature.com/articles/nature06496 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:451:y:2008:i:7178:d:10.1038_nature06496

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/nature06496

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().