title: Integrative analysis of C. elegans modENCODE ChIP-seq data sets to infer gene regulatory interactions.
abstract: The C. elegans modENCODE Consortium has defined in vivo binding sites for a large array of transcription factors by ChIP-seq. In this article, we present examples that illustrate how this compendium of ChIP-seq data can drive biological insights not possible with analysis of individual factors. First, we analyze the number of independent factors bound to the same locus, termed transcription factor complexity, and find that low-complexity sites are more likely to respond to altered expression of a single bound transcription factor. Next, we show that comparison of binding sites for the same factor across developmental stages can reveal insight into the regulatory network of that factor, as we find that the transcription factor UNC-62 has distinct binding profiles at different stages due to distinct cofactor co-association as well as tissue-specific alternative splicing. Finally, we describe an approach to infer potential regulators of gene expression changes found in profiling experiments (such as DNA microarrays) by screening these altered genes to identify significant enrichment for targets of a transcription factor identified in ChIP-seq data sets. After confirming that this approach can correctly identify the upstream regulator on expression data sets for which the regulator was previously known, we applied this approach to identify novel candidate regulators of transcriptional changes with age. The analysis revealed nine candidate aging regulators, of which three were previously known to have a role in longevity. We experimentally showed that two of the new candidate aging regulators can extend lifespan when overexpressed, indicating that this approach can identify novel functional regulators of complex processes.
authors.affiliation: Department of Genetics and Department of Developmental Biology, Stanford University Medical Center, Stanford, California 94305, USA.
authors.forename: Eric L
authors.initials: EL
authors.lastname: Van Nostrand
authors.forename: Stuart K
authors.initials: SK
authors.lastname: Kim
mesh_terms: D000375:Aging / Q000235:genetics; D000818:Animals; D001665:Binding Sites; D017173:Caenorhabditis elegans / Q000235:genetics* / Q000378:metabolism*; D029742:Caenorhabditis elegans Proteins / Q000378:metabolism; D047369:Chromatin Immunoprecipitation; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D059014:High-Throughput Nucleotide Sequencing; D018398:Homeodomain Proteins / Q000378:metabolism; D059372:Nucleotide Motifs; D009928:Organ Specificity / Q000235:genetics; D056510:Position-Specific Scoring Matrices; D011485:Protein Binding; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D029742:Caenorhabditis elegans Proteins; D018398:Homeodomain Proteins; D014157:Transcription Factors; C109537:Unc-62 protein, C elegans