Whole-genome tiling array analysis in normal human bronchial/tracheal epithelial cells (NHBE)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE9655 | GEO | 2007/11/22
SECONDARY ACCESSION(S): PRJNA103527
REPOSITORIES: GEO
Similar Datasets
Project description:The majority of all genes have so far been identified and annotated systematically through in silico gene finding. Here we report the finding of 3,217 strand-specific Transcriptionally Active Regions (TARs) in the genome of Bacillus subtilis by the use of tiling arrays. We have measured the genome-wide expression during mid-exponential growth on rich (LB) and minimal (M9) medium. The identified TARs account for 81.5% of the genes as they are currently annotated and additionally we find 44 novel protein-coding genes, 85 putative non-coding RNAs (ncRNAs) and 184 antisense transcripts. Hybridization of labeled genomic DNA (gDNA) has revealed a few thousand regions giving rise to very low signals. These are mostly caused by sequence errors, as is observed in the highly degenerate trp operon and the folding of stable structures such as the regions containing Rho-independent terminators. Through this work we have discovered a group of membrane-associated genes, among these having a long conserved 3â UnTranslated Region (UTR) predicted to fold into a large and highly stable structure. Among these are YwbN, a target of the twin-arginine translocase (Tat) protein translocation system. The transcriptionally active regions were determined at two different conditions, rich medium (Luria Broth) and minimal medium (M9). Cells were harvested at mid-exponential phase (OD600 = 0.5) and each condition were replicated three times. From each replicate RNA was extracted using FastRNA pro blue kit (Qbiogene) and labelled with Cy3 using a strand-specific protocol. The cDNA was hybridized to 385K NimbleGen tiling arrays 'BaSysBio Bsub T1' covering the entire genome with 45-65 nt isothermal probes, spaced by 22 nt on each strand. Additionally genomic DNA was extracted from 4 replicates at OD600 = 0.5, labelled and hybridized to the tiling arrays. These serve as a reference for the mRNA hybridizations. The normalized RNA hybridization signals were used to create segments using a structural change model (Huber et al, 2006) and transcriptionally active regions were identified by a segment joining-scheme.
2010-05-18 | E-GEOD-16086 | biostudies-arrayexpress
Project description:The majority of all genes have so far been identified and annotated systematically through in silico gene finding. Here we report the finding of 3,217 strand-specific Transcriptionally Active Regions (TARs) in the genome of Bacillus subtilis by the use of tiling arrays. We have measured the genome-wide expression during mid-exponential growth on rich (LB) and minimal (M9) medium. The identified TARs account for 81.5% of the genes as they are currently annotated and additionally we find 44 novel protein-coding genes, 85 putative non-coding RNAs (ncRNAs) and 184 antisense transcripts. Hybridization of labeled genomic DNA (gDNA) has revealed a few thousand regions giving rise to very low signals. These are mostly caused by sequence errors, as is observed in the highly degenerate trp operon and the folding of stable structures such as the regions containing Rho-independent terminators. Through this work we have discovered a group of membrane-associated genes, among these having a long conserved 3’ UnTranslated Region (UTR) predicted to fold into a large and highly stable structure. Among these are YwbN, a target of the twin-arginine translocase (Tat) protein translocation system.
2009-06-10 | GSE16086 | GEO
Project description:Although Candida albicans and Candida dubliniensis are most closely related, both species significantly behave differently with respect to morphogenesis and virulence. In order to gain further insight into the divergent routes for morphogenetic adaptation in both species, we investigated qualitative along with quantitative differences in the transcriptomes of both organisms by cDNA deep sequencing. Following genome-associated assembly of sequence reads we were able to generate experimentally verified databases containing 6016 and 5972 genes for C. albicans and C. dubliniensis, respectively. About 95% of the transcriptionally active regions (TARs) contain open reading frames while the remaining TARs most likely represent non-coding RNAs. Comparison of our annotations with publically available gene models for C. albicans and C. dubliniensis confirmed approximately 95% of already predicted genes, but also revealed so far unknown novel TARs in both species. Qualitative cross-species analysis of these databases revealed in addition to 5802 orthologs also 399 and 49 species-specific protein coding genes for C. albicans and C. dubliniensis, respectively. Furthermore, quantitative transcriptional profiling using RNA-Seq revealed significant differences in the expression of orthologs across both species. We defined a core subset of 84 hyphal-specific genes required for both species, as well as a set of 42 genes that seem to be specifically induced during hyphal morphogenesis in C. albicans. Species specific adaptation in C. albicans and C. dubliniensis is governed by individual genetic repertoires but also by altered regulation of conserved orthologs on the transcriptional level.
2013-04-17 | GSE41749 | GEO
Project description:Although Candida albicans and Candida dubliniensis are most closely related, both species significantly behave differently with respect to morphogenesis and virulence. In order to gain further insight into the divergent routes for morphogenetic adaptation in both species, we investigated qualitative along with quantitative differences in the transcriptomes of both organisms by cDNA deep sequencing. Following genome-associated assembly of sequence reads we were able to generate experimentally verified databases containing 6016 and 5972 genes for C. albicans and C. dubliniensis, respectively. About 95% of the transcriptionally active regions (TARs) contain open reading frames while the remaining TARs most likely represent non-coding RNAs. Comparison of our annotations with publically available gene models for C. albicans and C. dubliniensis confirmed approximately 95% of already predicted genes, but also revealed so far unknown novel TARs in both species. Qualitative cross-species analysis of these databases revealed in addition to 5802 orthologs also 399 and 49 species-specific protein coding genes for C. albicans and C. dubliniensis, respectively. Furthermore, quantitative transcriptional profiling using RNA-Seq revealed significant differences in the expression of orthologs across both species. We defined a core subset of 84 hyphal-specific genes required for both species, as well as a set of 42 genes that seem to be specifically induced during hyphal morphogenesis in C. albicans. Species specific adaptation in C. albicans and C. dubliniensis is governed by individual genetic repertoires but also by altered regulation of conserved orthologs on the transcriptional level. We investigated qualitative along with quantitative differences in the transcriptomes of both organisms by cDNA deep sequencing. In a first step, we reevaluated the in silico predicted gene models by collecting experimental data using FLX - technology for sequencing strand-specific and normalized cDNA libraries derived from blastospores and hyphae. In the second step, quantitative RNA-Seq (GAIIX) was applied to C. albicans hyphal cells and C. dubliniensis blastospore and hyphal cells to complement reevaluation of the gene models with FLX data as well as to measure differential gene expression across the species with two biological replicates.
2013-04-17 | E-GEOD-41749 | biostudies-arrayexpress
Project description:Experiments conducted on this tiling array are used to (1) validate the frozen gene sets of the current genome annotation, (2) improve the predicted gene structures by empirically determining UTRs and intron-exon boundaries, identifying missing upstream, internal, and downstream exons and alternative transcripts, (3) propose gene structure models in transcribed regions containing no predicted genes and (4) delineate transcriptionally active regions of the genome from intergenic, intronic and genic regions. Signal to background ratios were determined by first calling probes that fluoresced at intensities greater than 99% of the random probes’ signal intensities; therefore only 1% of fluorescing experimental probes should be false positives. We conducted two-color competitive hybridizations that measure differential expression from three replicates, each using RNA from independent biological extractions. Transcriptional active regions (TARs) were defined by stringing together overlapping probes showing fluorescence above a 1% false positive rate (FPR). Positive probes were joined into a TAR if they were adjacent (maxgap=0, no intermittent non-positive probe) and a TAR’s length had to be at least 45 bp (minrun=45, mid-point first positive probe to mid-point last positive probe, resulting in at least 3 adjacent positive probes for a TAR). Transcriptional active regions (TARs) were defined by stringing together overlapping probes showing fluorescence above a 1% false positive rate (FPR). The data analysis to measure differential expression of genes and of unannotated TARs was performed using the statistical software package R and Bioconductor with additions and modifications. The signal distributions across chips, samples and replicates were adjusted to be equal according to the mean fluorescence of the random probes on each array. All probes including random probes were quantile-normalized across replicates. Expression-level scores were assigned for each predicted gene based on the median log2 fluorescence over background intensity of probes falling within the exon boundaries.
2011-02-01 | E-GEOD-25856 | biostudies-arrayexpress
Project description:Although evidence accumulates on the role of plant peptides in the response to external conditions, the number of peptide-encoding genes in the genome is still underestimated. In order to identify novel oxidative stress-induced peptides in Arabidopsis thaliana a tiling array analysis (GeneChipM-BM-. Arabidopsis Tiling 1.0R Arrays ) was performed on mRNA extracted from leaves treated with paraquat (PQ), an reactive oxygen species inducer and water (control), resulting in the identification of 92,844 and 86,272 transcriptionally active regions (TARs), respectively. Normalized log signals were obtained using the Affymetrix Tiling Analysis Software - Version 1.1, Build 2. ON and OFF probes were selected using a treshold, based on positive controls. Next, groups of 4-13 successive ON probes were combined into short TARs and a selection was made of TARs having an average signal intensity at least 2.6-fold higher after PQ treatment compared to the control treatment, resulting in 176 TARS induced by PQ. paraquat treated A. thaliana leaves (2 replicates) vs control (water) treated A. thaliana leaves (2 replicates), (4 samples in total)
2013-08-31 | E-GEOD-49001 | biostudies-arrayexpress
Project description:Although evidence accumulates on the role of plant peptides in the response to external conditions, the number of peptide-encoding genes in the genome is still underestimated. In order to identify novel oxidative stress-induced peptides in Arabidopsis thaliana a tiling array analysis (GeneChip® Arabidopsis Tiling 1.0R Arrays ) was performed on mRNA extracted from leaves treated with paraquat (PQ), an reactive oxygen species inducer and water (control), resulting in the identification of 92,844 and 86,272 transcriptionally active regions (TARs), respectively. Normalized log signals were obtained using the Affymetrix Tiling Analysis Software - Version 1.1, Build 2. ON and OFF probes were selected using a treshold, based on positive controls. Next, groups of 4-13 successive ON probes were combined into short TARs and a selection was made of TARs having an average signal intensity at least 2.6-fold higher after PQ treatment compared to the control treatment, resulting in 176 TARS induced by PQ.
2013-08-31 | GSE49001 | GEO
Project description:Experiments conducted on this tiling array are used to (1) validate the frozen gene sets of the current genome annotation, (2) improve the predicted gene structures by empirically determining UTRs and intron-exon boundaries, identifying missing upstream, internal, and downstream exons and alternative transcripts, (3) propose gene structure models in transcribed regions containing no predicted genes and (4) delineate transcriptionally active regions of the genome from intergenic, intronic and genic regions. Signal to background ratios were determined by first calling probes that fluoresced at intensities greater than 99% of the random probes’ signal intensities; therefore, only 1% of fluorescing experimental probes should be false positives. We conducted two-color competitive hybridizations that measure differential expression from three replicates, each using RNA from independent biological extractions. Transcriptional active regions (TARs) were defined by stringing together overlapping probes showing fluorescence above a 1% false positive rate (FPR). Positive probes were joined into a TAR if they were adjacent (maxgap=0, no intermittent non-positive probe) and a TAR’s length had to be at least 45 bp (minrun=45, mid-point first positive probe to mid-point last positive probe, resulting in at least 3 adjacent positive probes for a TAR). The data analysis to measure differential expression of genes and of unannotated TARs was performed using the statistical software package R and Bioconductor with additions and modifications. The signal distributions across chips, samples and replicates were adjusted to be equal according to the mean fluorescence of the random probes on each array. All probes including random probes were quantile-normalized across replicates. Expression-level scores were assigned for each predicted gene based on the median log2 fluorescence over background intensity of probes falling within the exon boundaries.
2011-02-01 | E-GEOD-25852 | biostudies-arrayexpress
Project description:Experiments conducted on this tiling array are used to (1) validate the frozen gene sets of the current genome annotation, (2) improve the predicted gene structures by empirically determining UTRs and intron-exon boundaries, identifying missing upstream, internal, and downstream exons and alternative transcripts, (3) propose gene structure models in transcribed regions containing no predicted genes and (4) delineate transcriptionally active regions of the genome from intergenic, intronic and genic regions. Signal to background ratios were determined by first calling probes that fluoresced at intensities greater than 99% of the random probes’ signal intensities; therefore only 1% of fluorescing experimental probes should be false positives. We conducted two-color competitive hybridizations that measure differential expression from three replicates, each using RNA from independent biological extractions. Transcriptional active regions (TARs) were defined by stringing together overlapping probes showing fluorescence above a 1% false positive rate (FPR). Positive probes were joined into a TAR if they were adjacent (maxgap=0, no intermittent non-positive probe) and a TAR’s length had to be at least 45 bp (minrun=45, mid-point first positive probe to mid-point last positive probe, resulting in at least 3 adjacent positive probes for a TAR).The data analysis to measure differential expression of genes and of unannotated TARs was performed using the statistical software package R and Bioconductor with additions and modifications. The signal distributions across chips, samples and replicates were adjusted to be equal according to the mean fluorescence of the random probes on each array. All probes including random probes were quantile-normalized across replicates. Expression-level scores were assigned for each predicted gene based on the median log2 fluorescence over background intensity of probes falling within the exon boundaries.
2011-02-01 | E-GEOD-25855 | biostudies-arrayexpress
Project description:Seb1 is recruited co-transcriptionally to non-coding regions to drive transcriptional interference
| PRJNA360639 | ENA