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Deciphering a transcriptional regulatory code: modeling short-range repression in the Drosophila embryo.


ABSTRACT: Systems biology seeks a genomic-level interpretation of transcriptional regulatory information represented by patterns of protein-binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis-regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short-range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy-based modeling uncovered unexpected features of these proteins' activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms.

SUBMITTER: Fakhouri WD 

PROVIDER: S-EPMC2824527 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Deciphering a transcriptional regulatory code: modeling short-range repression in the Drosophila embryo.

Fakhouri Walid D WD   Ay Ahmet A   Sayal Rupinder R   Dresch Jacqueline J   Dayringer Evan E   Arnosti David N DN  

Molecular systems biology 20100119


Systems biology seeks a genomic-level interpretation of transcriptional regulatory information represented by patterns of protein-binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have  ...[more]

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