Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Christopher Hill
PROVIDER: E-GEOD-52460 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:MicroRNAs are small non-coding molecules that have been shown to repress the translation of thousands of genes. Changes in microRNA expression in a variety of diseases, including cancer, are leading to the development of microRNAs as early indicators of disease, and to their potential use as therapeutic agents. A significant hurdle to the use of microRNAs as therapeutics is our inability to predict the molecular and cellular consequences of perturbations in the levels of specific microRNAs on targeted cells. While the direct gene (mRNA) targets of individual microRNAs can be computationally predicted and are often experimentally validated, assessing the indirect effects of microRNA variation remains a major challenge in molecular systems biology. We present experimental evidence for a computational model that quantifies the extent to which down-regulated transcriptional repressors contribute to the unanticipated upregulation of putative microRNA targets. An appreciation of the effects of these repressors may provide a more complete understanding of the indirect effects of microRNA dysregulation in diseases such as cancer, and to their successful clinical application. mRNA were collected from the surface epithelial cells of 10 normal ovaries and from laser capture microdisection of 10 ovarian tumors. mRNA expression was captured on Affymetrix U133 Plus 2 chips. Present/absent calls were generated using MAS5, while signals were calculated using GCRMA. All signals were then log2 normalized. Expression was compared between miRanda-mirSVR predicted target genes of upregulated microRNAs, non-predicted target genes, and genes putatively targeted by down-regulated transcriptional repressors.
2013-11-05 | E-GEOD-52037 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Data for miR-429, miR-205, miR-200b, and miR-141 were each compared independently to the same negative control data contained in the raw .CEL files nc-miR-1-1.CEL, nc-miR-1-2.CEL and nc-miR-1-3.CEL. For each miRNA, the negative control data were re-normalized together with data only from that specific miRNA. The experiment for M12 was performed at a later date and an independent set of negative control data was collected at that time. Therefore, only M12 data was compared to the negative control data contained in the raw .CEL files nc-miR-2-1.CEL, nc-miR-2-2.CEL, and nc-miR-2-3.CEL.
2015-01-30 | E-GEOD-56973 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt M-bM-^@M-^\seed regionM-bM-^@M-^] mapping to positions 2-8 at the moleculeM-bM-^@M-^Ys 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control. mRNAs were collected from 3 M12 miRNA treated and 3 negative control miRNA treated HEY ovarian cancer cell samples. mRNA expression was captured on Affymetrix U133 Plus 2 chips. To compare mRNA expression pattern between the M12 treated cells and the negative control treated cells, present/absent calls were generated using MAS5, while signals were calculated using GCRMA and then log2 transformed. Expression of differentially expressed genes or down regulated miRanda-mirSVR predicted miRNA target genes was compared between miRNA treated samples.
2015-01-30 | E-GEOD-56972 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt M-bM-^@M-^\seed regionM-bM-^@M-^] mapping to positions 2-8 at the moleculeM-bM-^@M-^Ys 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control. mRNAs were collected from 3 M5 miRNA treated and 3 negative control miRNA treated HEY ovarian cancer cell samples. mRNA expression was captured on Affymetrix U133 Plus 2 chips. To compare mRNA expression pattern between the M5 treated cells and the negative control treated cells, present/absent calls were generated using MAS5, while signals were calculated using GCRMA and then log2 transformed. Expression of differentially expressed genes or down regulated miRanda-mirSVR predicted miRNA target genes was compared between miRNA treated samples.
2015-01-30 | E-GEOD-61229 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt M-bM-^@M-^\seed regionM-bM-^@M-^] mapping to positions 2-8 at the moleculeM-bM-^@M-^Ys 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control. mRNAs were collected from 3 M14 miRNA treated and 3 negative control miRNA treated HEY ovarian cancer cell samples. mRNA expression was captured on Affymetrix U133 Plus 2 chips. To compare mRNA expression pattern between the M14 treated cells and the negative control treated cells, present/absent calls were generated using MAS5, while signals were calculated using GCRMA and then log2 transformed. Expression of differentially expressed genes or down regulated miRanda-mirSVR predicted miRNA target genes was compared between miRNA treated samples.
2015-01-30 | E-GEOD-61230 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt M-bM-^@M-^\seed regionM-bM-^@M-^] mapping to positions 2-8 at the moleculeM-bM-^@M-^Ys 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control. mRNAs were collected from 3 miR-429 treated and 3 negative control miRNA treated HEY ovarian cancer cell samples. mRNA expression was captured on Affymetrix U133 Plus 2 chips. To compare mRNA expression pattern between the miR-429 treated cells and the negative control treated cells, present/absent calls were generated using MAS5, while signals were calculated using GCRMA and then log2 transformed. Expression of differentially expressed genes or down regulated miRanda-mirSVR predicted miRNA target genes was compared between miRNA treated samples.
2015-01-30 | E-GEOD-56967 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci. mRNAs were collected from three laser captured microdissected ovarian cancer epithelial (CEPI) samples. The mRNA expression pattern was compared with five healthy ovarian surface epithelia samples as controls using the Affymetrix U133 Plus 2.0 3' expression array.
2011-07-28 | E-GEOD-23391 | biostudies-arrayexpress
Project description:A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies. Samples were collected from eight subjects, four smokers (Sm)and four nonsmokers (NS). Each cheek was sampled creating an a and b sample for each subject which is reflected in the array name. All samples were isolated separately for total RNA. Each was hybridzed to microarrays to examine for differential gene expression between smokers and nonsmokers. There are 14 total samples in the main dataset (Set 2). One cheek sample failed in microarray analysis for two individuals, 08BCNS23 a and 08BCSm27 a, and so are not included here. A sample set (Set 1) was created which contains the four samples shown in this file. They represent repeated sampling of both cheeks for two individuals to test for reproducibility. There is a separate RMA file and metadata file (this file) for these data. These included samples 08BC11Sm a and b, a smoker, and 08BC12NSa and b a nonsmoker.
2010-03-07 | E-GEOD-16149 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci. miRNAs were collected from three laser captured microdissected ovarian cancer epithelial (CEPI) samples. The miRNA expression pattern was compared with three healthy ovarian surface epithelia samples as controls using a custom-manufactured Affymetrix GeneChip® array.
2011-07-28 | E-GEOD-23383 | biostudies-arrayexpress
Project description:Combining the cytological as well as gene expression changes in the endometrium is required to understand the effects of subclinical endometritis on endometrium as well as embryo. Hence, the present study was aimed to investigate the gene expression profiles of subclinical endometrium as well the effect of the inflamed environment on the gene expression profile of the developing preimplantative embryo. Endometrial samples were collected from each 49 cow using the cytobrush technique, 2 h before insemination (Day 0 of the estrous cycle after superovulation) and immediately before flushing (Day 7 of the estrous cycle after superovulation). The endometrial samples were categorized based on the PMN value as healthy endometrium (HE, PMN = 0) and subclinical endometritis (SE, endometrial PMN > 0). Flushed embryos were snap frozen for later molecular genetic analysis. Finally, endometrial samples were pooled according to the endometrial health status of the donor cows (HE vs. SE) at the time of insemination and at the time of flushing. The corresponding samples were subjected global gene expression profile. Moreover embryos flushed from HE and SE cows were pooled together according to the health status of their donors at time of flushing. Those embryos were also used for global embryonic gene expression analysis in relation to the health status of the donor cows.
2011-11-09 | E-GEOD-33496 | biostudies-arrayexpress