Experimental validation of predicted mammalian erythroid cis-regulatory modules
Author(s) -
Hao Wang,
Ying Zhang,
Yong Cheng,
Yuepin Zhou,
David King,
James Taylor,
Francesca Chiaromonte,
Jyotsna Kasturi,
Hanna M. Petrykowska,
Brian Gibb,
Christine M. Dorman,
Webb Miller,
Louis C. Doré,
John J. Welch,
Mitchell J. Weiss,
Ross C. Hardison
Publication year - 2006
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.5353806
Subject(s) - biology , transcription factor , chromatin immunoprecipitation , cis regulatory module , dna binding site , computational biology , binding site , gene , genetics , chromatin , genome , conserved sequence , human genome , regulatory sequence , promoter , enhancer , gene expression , peptide sequence
Multiple alignments of genome sequences are helpful guides to functional analysis, but predicting cis-regulatory modules (CRMs) accurately from such alignments remains an elusive goal. We predict CRMs for mammalian genes expressed in red blood cells by combining two properties gleaned from aligned, noncoding genome sequences: a positive regulatory potential (RP) score, which detects similarity to patterns in alignments distinctive for regulatory regions, and conservation of a binding site motif for the essential erythroid transcription factor GATA-1. Within eight target loci, we tested 75 noncoding segments by reporter gene assays in transiently transfected human K562 cells and/or after site-directed integration into murine erythroleukemia cells. Segments with a high RP score and a conserved exact match to the binding site consensus are validated at a good rate (50%-100%, with rates increasing at higher RP), whereas segments with lower RP scores or nonconsensus binding motifs tend to be inactive. Active DNA segments were shown to be occupied by GATA-1 protein by chromatin immunoprecipitation, whereas sites predicted to be inactive were not occupied. We verify four previously known erythroid CRMs and identify 28 novel ones. Thus, high RP in combination with another feature of a CRM, such as a conserved transcription factor binding site, is a good predictor of functional CRMs. Genome-wide predictions based on RP and a large set of well-defined transcription factor binding sites are available through servers at http://www.bx.psu.edu/.
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