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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Chromatin Conformation Capture in two biological replicates of K562 cells to identify interactions between tRNA genes in human cells.

ABSTRACT: tRNA genes are believed to form clusters in three-dimensional space in smaller eukaryotes (yeasts). In the course of investigating a cluster of tRNA genes for insulator activity in humans, we addressed whether these tRNA genes clustered with other tRNA genes. We used an anchor point to generate 4C material from a tRNA cluster located on chromosome 17 (hg18 7.962400 MB). We identify interactions occurring within the 300kb region of this point, but only extending in one direction and suggesting these interactions occur between this tRNA cluster and other tRNA gene clusters from this locus. We did not observed any specific interactions outside of this region or on other chromsomes, perhaps due to an low number of mappable reads from our samples. Chromatin Conformation Capture in two biological replicates of K562 cells to identify interactions between tRNA genes in human cells.

ORGANISM(S): Homo sapiens

SUBMITTER: Jesse Raab

PROVIDER: E-GEOD-31105 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Human tRNA genes function as chromatin insulators.

Raab Jesse R JR Chiu Jonathan J Zhu Jingchun J Katzman Sol S Kurukuti Sreenivasulu S Wade Paul A PA Haussler David D Kamakaka Rohinton T RT

The EMBO journal 20111115 2

Insulators help separate active chromatin domains from silenced ones. In yeast, gene promoters act as insulators to block the spread of Sir and HP1 mediated silencing while in metazoans most insulators are multipartite autonomous entities. tDNAs are repetitive sequences dispersed throughout the human genome and we now show that some of these tDNAs can function as insulators in human cells. Using computational methods, we identified putative human tDNA insulators. Using silencer blocking, transge ...[more]

PMID: 22085927

Similar Datasets

Chromatin Conformation Capture in two biological replicates of K562 cells to identify interactions between tRNA genes in human cells.

Project description:tRNA genes are believed to form clusters in three-dimensional space in smaller eukaryotes (yeasts). In the course of investigating a cluster of tRNA genes for insulator activity in humans, we addressed whether these tRNA genes clustered with other tRNA genes. We used an anchor point to generate 4C material from a tRNA cluster located on chromosome 17 (hg18 7.962400 MB). We identify interactions occurring within the 300kb region of this point, but only extending in one direction and suggesting these interactions occur between this tRNA cluster and other tRNA gene clusters from this locus. We did not observed any specific interactions outside of this region or on other chromsomes, perhaps due to an low number of mappable reads from our samples.

2011-10-10 | GSE31105 | GEO

tRNA gene identity acts as a determinant of gene positioning

Project description:Here we report that the spatial organization of yeast tRNA genes depends upon both locus position and tRNA identity; supporting the idea that the genomic organization of tRNA loci utilizes tRNA dependent signals within the nucleoprotein-tRNA complexes that form into clusters. We use high-throughput sequencing coupled to Circular Chromosome Conformation Capture to detect interactions with two wild type tRNAs and these same positions replaced with suppressor tRNAs (SUP4-1). Detect DNA-DNA interactions (Circular chromosome conformation capture; 4C) with two wild type tRNAs and these same positions replaced with suppressor tRNAs (SUP4-1) Supplementary files: Alignment files generated by Topography v1.19 software.

2012-06-13 | E-GEOD-30103 | biostudies-arrayexpress

tRNA gene identity acts as a determinant of gene positioning

2012-06-14 | GSE30103 | GEO

ChIP-seq: Temporal dynamics and developmental memory of 3D chromatin architecture at Hox gene loci

Project description:Hox genes are essential regulators of embryonic development. They are activated in a temporal sequence following their topological order within their genomic clusters. Subsequently, states of activity are fine-tuned and maintained to translate into domains of progressively overlapping gene products. While the mechanisms underlying such temporal and spatial progressions begin to be understood, many of their aspects remain unclear. We have systematically analyzed the 3D chromatin organization of Hox clusters in vivo, during their activation using high-resolution circular chromosome conformation capture (4C-seq). Initially, Hox clusters are organized as single 3D chromatin compartments decorated with bivalent chromatin marks. Their progressive transcriptional activation is associated with a dynamic bi-modal 3D organization, whereby the genes switch one after the other, from an inactive to an active 3D compartment. These local 3D dynamics occur within a larger constitutive framework of interactions within the surrounding Topological Associated Domains, which confirms previous results that regulation of this process in primarily cluster intrinsic. The local step-wise progression in time can be stopped and memorized at various body levels and hence it may accounts for the various chromatin architectures previously described at different anterior to posterior body levels for the same embryo at a later stage. ChIP-seq samples (H3K4me3 and H3K27me3) from mouse ES cells and mouse embryonic stage E8.5 pre-somitic mesoderm. Data based on 4 biological samples.

2014-04-28 | E-GEOD-54955 | biostudies-arrayexpress

The Dynamic Architecture of Hox Gene Clusters

Project description:The spatial and temporal control of Hox gene transcription is essential for patterning the vertebrate body axis. Although this process involves changes in histone posttranslational modifications, the existence of particular three-dimensional (3D) architectures remained to be assessed in vivo. Using high-resolution chromatin conformation capture methodology, we examined the spatial configuration of Hox clusters in embryonic mouse tissues where different Hox genes are active. When the cluster is transcriptionally inactive, Hox genes associate into a single 3D structure delimited from flanking regions. Once transcription starts, Hox clusters switch to a bimodal 3D organization where newly activated genes progressively cluster into a transcriptionally active compartment. This transition in spatial configurations coincides with the dynamics of chromatin marks, which label the progression of the gene clusters from a negative to a positive transcription status. This spatial compartmentalization may be key to process the collinear activation of these compact gene clusters. Examination of gene expression in 3 cell types. Examination of 2 different histone modifications in 2 cell types.

2011-10-12 | E-GEOD-31570 | biostudies-arrayexpress

Global effects of pathway-specific regulator CpkO and CpkN deletion in Streptomyces coelicolor A3(2)

Project description:Relative quantification of protein abundances of S. coelicolor A3(2) parent strain M145 and deletion mutants ∆cpkO and ∆cpkN. This study shows novel insights into the mechanism of coelimycin synthesis regulation and the network of interactions between cpk cluster regulatory proteins and the biosythetic genes of other secondary metabolite clusters.

2021-03-29 | PXD012672 | Pride

H3K4me3 ChIPseq in chicken liver

Project description:This dataset has been generated to identify promoter regions in the chicken genome to distinguish active and inactive genes. We focussed our analyses on actively transcribed tRNA and mRNAs genes. Chicken liver was cross-linked to capture histone-DNA interactions. Sequencing libraries were prepared from H3K4me3-precipitated DNA and input control.

2021-02-04 | E-MTAB-8106 | biostudies-arrayexpress

Comprehensive, high resolution analysis of cis-acting regulatory networks at the alpha globin locus (array)

Project description:We have combined the 4C chromosome conformation capture protocol with high throughput, genome-wide sequence analysis to characterise in full a cis-acting regulatory network at a single locus. In contrast to methods which identify large interacting regions (10-1000kb), the 4C approach provides a comprehensive, high resolution analysis of a specific locus with the aim of defining, in detail, all cis- regulatory elements controlling a single gene or gene cluster. Using the human M-NM-1-globin locus as a model we detected all known local and long-range interactions with this gene cluster. In addition we identified two interactions with genes located 300 kb (NME4) and 625 kb (FAM173a) from the M-NM-1-globin cluster. Using paired-end sequencing it was possible for the first time to identify interactions between specific subsets of cis-regulatory elements in populations of cells and within individual cells. Two biological replicates of 4C amplification from the promoters of the human HBA and HBB genes and B-Cell controls. Quality of B-cell material was confirmed using amplification from a CTCF bound region associated with Human Axin Gene.

2013-06-06 | E-GEOD-42383 | biostudies-arrayexpress

Comparative Transcriptomics of Soybean Near Isogenic Lines in Response to Phytophthora Sojae

Project description:Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is effectively controlled by Rps genes in soybean. Rps genes are race-specific, yet the mechanism of resistance, as well as susceptibility, remains largely unclear. Taking advantage of RNA-seq technology, we sequenced the transcriptomes of 10 near isogenic lines (NIL), each with a unique Rps gene, and the recurrent susceptible parent ‘Williams’. A total of 4330 differentially expressed genes (DEGs) were identified in ‘Williams’ while 2075 to 5499 DEGs were identified in each NIL. Comparisons between the NILs and ‘Williams’ allowed classification of two major groups of DEGs of interest: incompatible reaction associated genes (IRAGs) and compatible reaction associated genes (CRAGs). Hierarchical cluster analysis divided NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6). Heatmap analysis, along with GO analysis suggested that the diversity of clusters for NILs were likely due to variation of the number of DEGs and the intensity of gene expression, rather than functional differentiation. Further analysis suggested that transcription factors might play pivotal role in determination of the cluster pattern, and that WRKY family were strongly associated with incompatible reactions. Analysis of IRAGs and CRAGs with putative functions suggested that the regulation of many phytohormone signaling pathways were associated with incompatible or compatible interactions with potential crosstalk between each other. As such, our study provides an in depth view of both incompatible and compatible interactions between soybean and P. sojae, which provides further insight into the mechanisms involved in host-pathogen interactions. 22 samples were sequenced, 11 inoculated with P. sojae, the other 11 were mock-inoculated

2014-04-16 | E-GEOD-48524 | biostudies-arrayexpress

System OMICs analysis of Mycobacterium tuberculosis Beijing B0/W148 cluster

Project description:Mycobacterium tuberculosis Beijing B0/W148 is one of the most widely distributed clusters in the Russian Federation and in some countries of the former Soviet Union. Recent studies have improved our understanding of the reasons for the “success” of the cluster but this area remains incompletely studied. Here, we focused on the system omics analysis of the RUS_B0 strain belonging to the Beijing B0/W148 cluster. Completed genome sequence of RUS_B0 (CP020093.1) and a collection of WGS for 200 cluster strains from the NCBI were used to describe the main genetic features of the population, as well as the level of resistance. In turn, proteome and transcriptome studies allowed to confirm the genomic data and to identify a number of finds that have not previously been described. Our results demonstrate that expression of the whiB6 which contains cluster-specific polymorphism (T4338371G) increased by more than 50 times in RUS_B0. Additionally, the level of ethA transcripts in RUS_B0 is increased almost 30 times compared to the H37Rv. Start sites for 10 genes were corrected based on the combination of proteomic and transcriptomic data. Additionally, based on the omics approach, we identified 5 new genes.

2020-05-26 | PXD013509 | Pride

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