Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR356365_1.fastq.gz | Fastqsanger.gz | |||
| ERR356365_2.fastq.gz | Fastqsanger.gz | |||
| ERR356366_1.fastq.gz | Fastqsanger.gz | |||
| ERR356366_2.fastq.gz | Fastqsanger.gz | |||
| ERR356367_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 28 |
Similar Datasets
Project description:Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.
| PRJEB4771 | ENA
Project description:Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.
| PRJEB4789 | ENA
Project description:ChIP-seq experiment of 14 human lymphoblastoid cell line samples from the 1000 Genomes sample set (http://www.1000genomes.org/). Dataset includes two parent-daughter trios (CEU and YRI populations) and additional eight unrelated individuals (CEU population). This accession contains raw and mapped ChIP-seq read data, other assays in this study are available under accession E-MTAB-1883 (RNA-seq, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1883) and E-MTAB-1885 (GRO-seq, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1885/).
2013-10-17 | E-MTAB-1884 | biostudies-arrayexpress
Project description:Transcriptome sequencing (RNA-seq) experiment of 14 human lymphoblastoid cell line samples from the 1000 Genomes sample set (http://www.1000genomes.org/). Dataset includes two parent-daughter trios (CEU and YRI populations) and additional eight unrelated individuals (CEU population). This accession contains raw and mapped RNA-seq read data, other assays in this study are available under accession E-MTAB-1884 (ChIP-seq, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1884) and E-MTAB-1885 (GRO-seq, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1885).
2013-10-17 | E-MTAB-1883 | biostudies-arrayexpress
Project description:Nascent transcriptome sequencing (GRO-seq) experiment of 3 human lymphoblastoid cell line samples from the 1000 Genomes sample set (http://www.1000genomes.org/). Dataset includes one parent-daughter trio (CEU populations). This accession contains raw, mapped, and processed GRO-seq read data, other assays in this study are available under accession E-MTAB-1884 (ChIP-seq, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1884) and E-MTAB-1883 (RNA-seq, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1883/).
2013-10-17 | E-MTAB-1885 | biostudies-arrayexpress
Project description:DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event.
| S-EPMC5502466 | biostudies-literature
Project description:DNA methylation is an important epigenetic regulator of gene expression. Recent studies have revealed widespread associations between genetic variation and methylation levels. However, the mechanistic links between genetic variation and methylation remain unclear. To begin addressing this gap, we collected methylation data at ~300,000 loci in lymphoblastoid cell lines (LCLs) from 64 HapMap Yoruba individuals, and genome-wide bisulfite sequence data in ten of these individuals. We identified 11,752 methylation QTLs (meQTLs)—i.e., loci in which genetic variation is significantly associated with changes in DNA methylation. We found that meQTLs are frequently associated with changes in methylation at multiple CpGs across regions of up to 3 kb. Interestingly, meQTLs are also frequently associated with variation in other properties of gene regulation, including histone modifications, DNaseI accessibility, chromatin accessibility, and expression levels of nearby genes. These observations suggest a shared and coordinated molecular variation in all of these regulatory phenotypes. One plausible driver of coordinated changes in different regulatory mechanisms is variation in transcription factor (TF) binding. Indeed, we found that both changes in putative TF binding affinity and changes in the strength of TF binding footprints are associated with variation in DNA methylation near the TF binding sites. Considered together, our observations are consistent with a model whereby changes in TF binding may frequently drive coordinated changes in DNA methylation, histone modification, and gene expression levels. Bisulfite converted DNA from 64 individuals was hybridized to the Illumina Infinium HumanMethylation450 BeadChip
2014-05-09 | E-GEOD-57481 | biostudies-arrayexpress
Project description:Most homeodomains are unique within a genome, yet many are highly conserved across vast evolutionary distances, implying strong selection on their precise DNA-binding specificities. We determined the binding preferences of the majority (168) of mouse homeodomains to all possible 8-base sequences, revealing rich and complex patterns of sequence specificity, and showing for the first time that there are at least 65 distinct homeodomain DNA-binding activities. We developed a computational system that successfully predicts binding sites for homeodomain proteins as distant from mouse as Drosophila and C. elegans, and we infer full 8-mer binding profiles for the majority of known animal homeodomains. Our results provide an unprecedented level of resolution in the analysis of this simple domain structure and suggest that variation in sequence recognition may be a factor in its functional diversity and evolutionary success. Keywords: Mouse homeodomain protein binding microarrays
2008-06-20 | GSE11239 | GEO
Project description:In parallel to the genetic code for protein synthesis, a second layer of information is embedded in all RNA transcripts in the form of RNA structure. The ability of RNA to base pair with itself and other nucleic acids endow RNA with the capacity to form extensive structures, which are known to influence practically every step in the gene expression program1. Yet the nature of most RNA structures or effects of sequence variation on structure are not known. Here we report the initial landscape and variation of RNA secondary structures (RSS) in a human family trio, providing a comprehensive RSS map of human coding and noncoding RNAs. We identify unique RSS signatures that demarcate open reading frames, splicing junctions, and define authentic microRNA binding sites. Comparison of native deproteinized RNA isolated from cells versus refolded purified RNA suggests that the majority of the RSS information is encoded within RNA sequence. Over one thousand transcribed single nucleotide variants (~15% of all transcribed SNVs) alter local RNA structure; these “RiboSNitches”2 occur in disease-associated variants. We discover simple sequence and spacing rules that determine the ability of point mutations to impact RSS. Selective depletion of RiboSNitches versus structurally synonymous variants at precise locations suggests selection for specific RNA shapes at thousands of sites, including 3’UTRs, binding sites of miRNAs and RNA binding proteins genome-wide. These results highlight the potentially broad contribution of RNA structure and its variation to gene regulation. RNA structure probing is performed at 37˚C on poly(A)+ selected RNAs from GM12878, GM12891 and GM12892 cell lines, as well as on native proteinized RNAs from GM12878. The structure probed RNAs is then cloned into a sequencing library using modied Ambion RNA sequencing kit compatible with the Illumina platform. The samples were deep sequenced using Illumina's Hi-Seq platform. AGO CLIP was performed as reported. Cells were crosslinked with UV and lysed using published protocols. AGO2 was enriched using immunopurification. The RNA-protein complex was digested with ribonuclease and purified by gel electrophoresis. Purified RNA was reverse transcribed and cDNA molecules were amplified and sequenced as described.
2013-12-19 | E-GEOD-50676 | biostudies-arrayexpress
Project description:In parallel to the genetic code for protein synthesis, a second layer of information is embedded in all RNA transcripts in the form of RNA structure. The ability of RNA to base pair with itself and other nucleic acids endow RNA with the capacity to form extensive structures, which are known to influence practically every step in the gene expression program1. Yet the nature of most RNA structures or effects of sequence variation on structure are not known. Here we report the initial landscape and variation of RNA secondary structures (RSS) in a human family trio, providing a comprehensive RSS map of human coding and noncoding RNAs. We identify unique RSS signatures that demarcate open reading frames, splicing junctions, and define authentic microRNA binding sites. Comparison of native deproteinized RNA isolated from cells versus refolded purified RNA suggests that the majority of the RSS information is encoded within RNA sequence. Over one thousand transcribed single nucleotide variants (~15% of all transcribed SNVs) alter local RNA structure; these “RiboSNitches”2 occur in disease-associated variants. We discover simple sequence and spacing rules that determine the ability of point mutations to impact RSS. Selective depletion of RiboSNitches versus structurally synonymous variants at precise locations suggests selection for specific RNA shapes at thousands of sites, including 3’UTRs, binding sites of miRNAs and RNA binding proteins genome-wide. These results highlight the potentially broad contribution of RNA structure and its variation to gene regulation.
2013-12-19 | GSE50676 | GEO