Systematic identification of mammalian regulatory motifs' target genes and functions.
We developed an algorithm, Lever, that systematically maps metazoan DNA regulatory motifs or motif combinations to sets of genes. Lever assesses whether the motifs are enriched in cis-regulatory modules (CRMs), predicted by our PhylCRM algorithm, in the noncoding sequences surrounding the genes. Lever analysis allows unbiased inference of functional annotations to regulatory motifs and candidate CRMs. We used human myogenic differentiation as a model system to statistically assess greater than 25,000 pairings of gene sets and motifs or motif combinations. We assigned functional annotations to candidate regulatory motifs predicted previously and identified gene sets that are likely to be co-regulated via shared regulatory motifs. Lever allows moving beyond the identification of putative regulatory motifs in mammalian genomes, toward understanding their biological roles. This approach is general and can be applied readily to any cell type, gene expression pattern or organism of interest.
Warner
Jason B
JB
Division of Genetics, Department of Medicine, Harvard Medical School, Harvard Medical School New Research Building, Room 466D, 77 Ave. Louis Pasteur, Boston, Massachusetts 02115, USA.
Philippakis
Anthony A
AA
Jaeger
Savina A
SA
He
Fangxue Sherry
FS
Lin
Jolinta
J
Bulyk
Martha L
ML
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000235:genetics*; D016678:Genome; D006801:Humans; D008969:Molecular Sequence Data; D050436:Regulatory Elements, Transcriptional / Q000235:genetics*; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*; D013045:Species Specificity
D004247:DNA