A genome-wide analysis of open chromatin in human tracheal epithelial cells reveals novel candidate regulatory elements for lung function
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Ann Harris
PROVIDER: E-GEOD-52181 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Distal cell-type-specific regulatory elements may be located at very large distances from the genes that they control and are often hidden within intergenic regions or in introns of other genes. The development of methods that enable mapping of regions of open chromatin genome wide has greatly advanced the identification and characterisation of these elements. Here we use DNase I hypersensitivity mapping followed by deep sequencing (DNase-seq) to generate a map of open chromatin in primary human tracheal epithelial (HTE) cells and use bioinformatic approaches to characterise the distribution of these sites within the genome and with respect to gene promoters, intronic and intergenic regions. Genes with THE-selective open chromatin at their promoters were associated with multiple pathways of epithelial function and differentiation. The data predict novel cell-type-specific regulatory elements for genes involved in HTE cell function, such as structural proteins and ion channels, and the transcription factors that may interact with them to control gene expression. Moreover, the map of open chromatin can identify the location of potentially critical regulatory elements in genome-wide association studies (GWAS) in which the strongest association is with single nucleotide polymorphisms in non-coding regions of the genome. We demonstrate its relevance to a recent GWAS that identifies modifiers of cystic fibrosis lung disease severity. Since HTE cells have many functional similarities with bronchial epithelial cells and other differentiated cells in the respiratory epithelium, these data are of direct relevance to elucidating the molecular basis of normal lung function and lung disease. To identify cis-regulatory elements for genes expressed in human tracheal epithelial cells we generated genome-wide maps of open chromatin by DNase-seq. HTE cells were isolated from these trachea and grown as described previously (Davis P.B. et al.1990).
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Project description:Distal cell-type-specific regulatory elements may be located at very large distances from the genes that they control and are often hidden within intergenic regions or in introns of other genes. The development of methods that enable mapping of regions of open chromatin genome wide has greatly advanced the identification and characterisation of these elements. Here we use DNase I hypersensitivity mapping followed by deep sequencing (DNase-seq) to generate a map of open chromatin in primary human tracheal epithelial (HTE) cells and use bioinformatic approaches to characterise the distribution of these sites within the genome and with respect to gene promoters, intronic and intergenic regions. Genes with THE-selective open chromatin at their promoters were associated with multiple pathways of epithelial function and differentiation. The data predict novel cell-type-specific regulatory elements for genes involved in HTE cell function, such as structural proteins and ion channels, and the transcription factors that may interact with them to control gene expression. Moreover, the map of open chromatin can identify the location of potentially critical regulatory elements in genome-wide association studies (GWAS) in which the strongest association is with single nucleotide polymorphisms in non-coding regions of the genome. We demonstrate its relevance to a recent GWAS that identifies modifiers of cystic fibrosis lung disease severity. Since HTE cells have many functional similarities with bronchial epithelial cells and other differentiated cells in the respiratory epithelium, these data are of direct relevance to elucidating the molecular basis of normal lung function and lung disease. HTE (human tracheal epithelial) cells were isolated from human trachea postmortem and grown as described previously (Davis P.B. et al.1990). Total RNA was extracted by Trizol and the samples shipped to NimbleGen for gene expression analysis on NimbleGen 4 X 72K HG18 60mer arrays.
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Project description:Investigation of whole genome gene expression level changes of LncRNAs in tumor tissues and paired non-tumor tissues in HBV-positive hapatocellular carcinoma. The different expression genes were further analysised. The human LncRNA microarray analysis of the 10 samples (5 non-tumor tissues and 5 paired tumor tissues) were completed. Total RNA from each sample was quantified using the NanoDrop ND-1000 and RNA integrity was assessed using standard denaturing agarose gel electrophoresis. Total RNA of each sample was used for labeling and array hybridization as the following steps: 1) Reverse transcription with by Invitrogen Superscript ds-cDNA synthesis kit; 2) ds-cDNA labeling with NimbleGen one-color DNA labeling kit; 3) Array hybridization using the NimbleGen Hybridization System and followed by washing with the NimbleGen wash buffer kit; 4) Array scanning using the Agilent Scanner G2505C. Scanned images (TIFF format) were then imported into NimbleScan software (version 2.5) for grid alignment and expression data analysis. Expression data were normalized through quantile normalization and the Robust Multichip Average (RMA) algorithm included in the NimbleScan software. The Probe level (*_norm_RMA.pair) files and mRNA level (*_RMA.calls) files were generated after normalization. All mRNAs level files were imported into Agilent GeneSpring GX software (version 11.5.1) for further analysis.mRNAs that at least 3 out of 6 samples have values greater than or equal to lower cut-off: 50.0 (“All Targets Value”) were chosen for further data analysis. Differentially expressed mRNAs were identified through Volcano Plot filtering. Pathway analysis and GO analysis were applied to determine the roles of these differentially expressed mRNAs played in these biological pathways or GO terms. Finally, Hierarchical Clustering was performed to show the distinguishable mRNAs expression pattern among samples.
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