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Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data

ABSTRACT: Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites correspond-ing to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-speciﬁc experimental data such as histone modiﬁcations and DNa-seI cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell-types or tissues under diverse conditions.

ORGANISM(S): Homo sapiens

PROVIDER: GSE25341 | GEO | 2010/11/15

SECONDARY ACCESSION(S): PRJNA134875

REPOSITORIES: GEO

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Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data

Project description:Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites correspond-ing to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-speciﬁc experimental data such as histone modiﬁcations and DNa-seI cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell-types or tissues under diverse conditions. DNaseI-Seq on two YRI Hapmap cell lines. Each individual sequenced on 8 lanes of the Illumina Genome Analyzer II

2010-11-15 | E-GEOD-25341 | biostudies-arrayexpress

Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity

Project description:The DNA sequence preferences of the vast majority of eukaryotic transcription factors (TFs) are unknown. Using an approach designed to broadly sample both DNA-binding domain types and eukaryotic clades, we have determined DNA-binding motifs for 1,033 TFs from 131 diverse eukaryotes, encompassing 54 domain types. Closely related orthologs and paralogs typically have very similar sequence preferences; this property allows inference of motifs for roughly one third of the 166,851 known or predicted eukaryotic TFs. While the origins of most motifs can be dated to hundreds of millions of years ago, we also characterize more recent TF expansions. Sequences matching the motifs are enriched upstream of TSS in most eukaryotic lineages, and at informative eQTL SNPs in Arabidopsis promoters, demonstrating their utility in mapping transcriptional networks. The motifs are housed at http://cisbp.ccbr.utoronto.ca Protein binding microarray (PBM) experiments were performed for a set of 1048 diverse eukaryotic transcription factors. Briefly, the PBMs involved binding GST-tagged DNA-binding proteins to two double-stranded 44K Agilent microarrays, each containing a different DeBruijn sequence design, in order to determine their sequence preferences. Details of the PBM protocol are described in Berger et al., Nature Biotechnology 2006.

2014-08-01 | E-GEOD-53348 | biostudies-arrayexpress

Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity

2014-08-01 | GSE53348 | GEO

Genome-wide transcription start site mapping of Bradyrhizobium japonicum free-living cells and bacteroids - a rich resource to identify new transcripts, proteins and to study gene regulation

Project description:Background: During the symbiosis with legumes, Bradyrhizobium japonicum cells infect roots where they induce the formation of root nodules and differentiate into intracellular nitrogen-fixing bacteroids. We used differential RNA-seq (dRNA-seq) for the genome-wide detection of transcriptional start sites (TSSs) in B. japonicum USDA 110 cells grown free-living or as bacteroids in soybean root nodules. Results: A newly developed TSS recognition procedure based on machine learning allowed us to map 15,923 TSSs: 14,360 in free-living bacteria, 4,329 in bacteroids and 2,766 in both living conditions. Using a proteogenomics approach, we provide evidence for the translation of 107 new transcripts including 14 with TSSs in annotated genes. In addition, we provide evidence for 178 shorter or longer proteins, 109 of them with TSS support. Based on our TSS map and a new de novo promoter prediction algorithm, we identified promoter motifs mainly used in nodules (similar to RpoN-dependent promoters) or under both conditions (similar to RpoD-dependent promoters). The data is made available in a generic feature format (GFF) file along with an updated and extended genome annotation comprising promoters, TSSs and terminators. The value of such a TSS and promoter map beyond the identification of novel transcripts and ORFs is illustrated by the experimental analysis of an antisense RNA, which is a by-product of transcriptional interference in a gene encoding a cytochrome P450 highly expressed in nodules. Conclusions: The genome-wide TSS and promoter map along with the extended genome annotation represents a very useful resource for detailed analyses of gene regulation and further systems biology studies on B. japonicum in symbiosis with soybean.

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Identification of tens of thousands of novel gene loci in the human and mouse genomes through targeted full-length long-read RNA sequencing

Project description:The GENCODE project is a long-term international effort to produce a comprehensive and accurate map of genes and transcripts for the human and mouse genomes. While the annotation of protein-coding genes is nearly complete, long non-coding RNAs (lncRNAs) remain poorly characterized, with existing catalogs lacking consistency and experimental support. To address this, GENCODE used a targeted RNA sequencing approach to capture RNA from various human and mouse tissues, employing advanced sequencing technologies (ONT, PacBio, and Illumina). This resulted in the prediction of around half a million transcript models for both species. GENCODE then re-engineered its curation pipeline to handle this data, leading to the annotation of 16,817 new human genes (132,049 transcripts) and 22,210 new mouse genes (131,546 transcripts)—a significant increase in lncRNA annotations. The newly identified genes and transcripts have similar features to previously annotated lncRNAs and are linked to human phenotypes through GWAS and evolutionary conservation. Furthermore, the project has expanded the map of lncRNA orthology between humans and mice, especially for disease-associated lncRNAs. These updates enhance the functional interpretation of the human genome, connecting millions of previously unassigned omics data points (e.g., CAGE tags, ChIP-Seq peaks, genetic variants) to specific transcriptional units and regulatory regions. This marks a significant advancement toward a complete lncRNA catalog for human and mouse genomes.

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