RESUMEN
Foxa2 (HNF3 beta) is a one of three, closely related transcription factors that are critical to the development and function of the mouse liver. We have used chromatin immunoprecipitation and massively parallel Illumina 1G sequencing (ChIP-Seq) to create a genome-wide profile of in vivo Foxa2-binding sites in the adult liver. More than 65% of the approximately 11.5 k genomic sites associated with Foxa2 binding, mapped to extended gene regions of annotated genes, while more than 30% of intragenic sites were located within first introns. 20.5% of all sites were further than 50 kb from any annotated gene, suggesting an association with novel gene regions. QPCR analysis demonstrated a strong positive correlation between peak height and fold enrichment for Foxa2-binding sites. We measured the relationship between Foxa2 and liver gene expression by overlapping Foxa2-binding sites with a SAGE transcriptome profile, and found that 43.5% of genes expressed in the liver were also associated with Foxa2 binding. We also identified potential Foxa2-interacting transcription factors whose motifs were enriched near Foxa2-binding sites. Our comprehensive results for in vivo Foxa2-binding sites in the mouse liver will contribute to resolving transcriptional regulatory networks that are important for adult liver function.
Asunto(s)
Factor Nuclear 3-beta del Hepatocito/metabolismo , Hígado/metabolismo , Elementos Reguladores de la Transcripción , Animales , Sitios de Unión , Inmunoprecipitación de Cromatina , Biología Computacional , Femenino , Expresión Génica , Redes Reguladoras de Genes , Genómica , Factor Nuclear 3-beta del Hepatocito/antagonistas & inhibidores , Ratones , Ratones Endogámicos C57BL , Interferencia de ARN , Análisis de Secuencia de ADN , Factores de Transcripción/metabolismoRESUMEN
ORegAnno is an open-source, open-access database and literature curation system for community-based annotation of experimentally identified DNA regulatory regions, transcription factor binding sites and regulatory variants. The current release comprises 30 145 records curated from 922 publications and describing regulatory sequences for over 3853 genes and 465 transcription factors from 19 species. A new feature called the 'publication queue' allows users to input relevant papers from scientific literature as targets for annotation. The queue contains 4438 gene regulation papers entered by experts and another 54 351 identified by text-mining methods. Users can enter or 'check out' papers from the queue for manual curation using a series of user-friendly annotation pages. A typical record entry consists of species, sequence type, sequence, target gene, binding factor, experimental outcome and one or more lines of experimental evidence. An evidence ontology was developed to describe and categorize these experiments. Records are cross-referenced to Ensembl or Entrez gene identifiers, PubMed and dbSNP and can be visualized in the Ensembl or UCSC genome browsers. All data are freely available through search pages, XML data dumps or web services at: http://www.oreganno.org.
Asunto(s)
Bases de Datos de Ácidos Nucleicos , Elementos Reguladores de la Transcripción , Factores de Transcripción/metabolismo , Acceso a la Información , Animales , Sitios de Unión , Humanos , Internet , Interfaz Usuario-ComputadorRESUMEN
We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes. By ChIP-seq, using 15.1 and 12.9 million uniquely mapped sequence reads, and an estimated false discovery rate of less than 0.001, we identified 41,582 and 11,004 putative STAT1-binding regions in stimulated and unstimulated cells, respectively. Of the 34 loci known to contain STAT1 interferon-responsive binding sites, ChIP-seq found 24 (71%). ChIP-seq targets were enriched in sequences similar to known STAT1 binding motifs. Comparisons with two ChIP-PCR data sets suggested that ChIP-seq sensitivity was between 70% and 92% and specificity was at least 95%.