7,801 research outputs found
A novel computational system for identification of biological processes from multi-dimensional high-throughput genomic data
Identifying potential toxicity signaling pathways could guide future animal studies and support human risk assessment and intervention efforts. This thesis describes a novel computational approach for identifying biological processes and pathways that are significantly associated with a disease pathology from time series, dose response, gene expression data.;Our system employs a novel constrained non-negative matrix factorization algorithm and Monte Carlo Markov chain simulation to identify underlying patterns in mRNA gene expression data. Quantitative pathology can be used as a pattern constraint. The found patterns can be thought of as functions that influence a gene\u27s expression. Using a database of curated gene sets, we can identify biological processes that are significantly related to a pathology.;We also developed a computational model for integrating miRNA with mRNA time series microarray data along with disease pathology. The dynamic temporal regulatory effects of miRNA are not well known and a single miRNA may regulate many mRNA. The integrated analysis includes identifying both mRNA and miRNA that are significantly similar to the quantitative pathology. Potential regulatory miRNA/mRNA target pairs are then identified through databases of both predicted and validated pairs. Finally, potential target pairs are filtered, keeping only pairs that demonstrate regulatory effects in the expression data.;Multi-walled carbon nanotubes (MWCNT) are known for their transient inflammatory and progressive fibrotic pulmonary effects; however, the mechanisms underlying these pathologies are unknown. In this thesis, we used time series microarray data of global lung mRNA and miRNA expression isolated from 160 C57BL/6J mice exposed by pharyngeal aspiration to vehicle or 10, 20, 40, or 80 mug MWCNT at 1, 7, 28, or 56 days post-exposure. Quantitative pathology patterns of MWCNT-induced inflammation (bronchoalveolar lavage score) and fibrosis (Sirius Red staining, quantitative morphometric analysis) were obtained from separate studies.;Understanding the regulatory networks between mRNA and miRNA in different stages would be beneficial for understanding the complex path of disease development. These identified genes and pathways may be useful for determining biomarkers of MWCNT-induced lung inflammation and fibrosis for early detection of disease. Our computational approach detects biologically relevant processes with and without pathology information. The identified significant processes and genes are supported by evidence in the literature and with biological validation
On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles
Dysregulated microRNA (miRNA) expression is a well-established feature of
human cancer. However, the role of specific miRNAs in determining cancer
outcomes remains unclear. Using Level 3 expression data from the Cancer Genome
Atlas (TCGA), we identified 61 miRNAs that are associated with overall survival
in 469 ovarian cancers profiled by microarray (p<0.01). We also identified 12
miRNAs that are associated with survival when miRNAs were profiled in the same
specimens using Next Generation Sequencing (miRNA-Seq) (p<0.01). Surprisingly,
only 1 miRNA transcript is associated with ovarian cancer survival in both
datasets. Our analyses indicate that this discrepancy is due to the fact that
miRNA levels reported by the two platforms correlate poorly, even after
correcting for potential issues inherent to signal detection algorithms.
Further investigation is warranted
Differential expression of microRNAs in bovine papillomavirus type 1 transformed equine cells
Bovine papillomavirus (BPV) types 1 and 2 play an important role in the pathogenesis of equine sarcoids (ES), the most common cutaneous tumour affecting horses. MicroRNAs (miRNAs), small non-coding RNAs that regulate essential biological and cellular processes, have been found dysregulated in a wide range of tumours. The aim of this study was to identify miRNAs associated with ES. Differential expression of miRNAs was assessed in control equine fibroblasts (EqPalFs) and EqPalFs transformed with the BPV-1 genome (S6-2 cells). Using a commercially available miRNA microarray, 492 mature miRNAs were interrogated. In total, 206 mature miRNAs were differentially expressed in EqPalFs compared with S6-2 cells. Aberrant expression of these miRNAs in S6-2 cells can be attributed to the presence of BPV-1 genomes. Furthermore, we confirm the presence of 124 miRNAs previously computationally predicted in the horse. Our data supports the involvement of miRNAs in the pathogenesis of ES
Maternal recognition of pregnancy in the horse : are MicroRNAs the secret messengers?
The signal for maternal recognition of pregnancy (MRP) has still not been identified in the horse. High-throughput molecular biology at the embryo-maternal interface has substantially contributed to the knowledge on pathways affected during MRP, but an integrated study in which proteomics, transcriptomics and miRNA expression can be linked directly is currently lacking. The aim of this study was to provide such analysis. Endometrial biopsies, uterine fluid, embryonic tissues, and yolk sac fluid were collected 13 days after ovulation during pregnant and control cycles from the same mares. Micro-RNA-Sequencing was performed on all collected samples, mRNA-Sequencing on the same tissue samples and mass spectrometry was conducted previously on the same fluid samples. Differential expression of miRNA, mRNA and proteins showed high conformity with literature and confirmed involvement in pregnancy establishment, embryo quality, steroid synthesis and prostaglandin regulation, but the link between differential miRNAs and their targets was limited and did not indicate the identity of an unequivocal signal for MRP in the horse. Differential expression at the embryo-maternal interface was prominent, highlighting a potential role of miRNAs in embryo-maternal communication during early pregnancy in the horse. These data provide a strong basis for future targeted studies
MMpred: functional miRNA – mRNA interaction analyses by miRNA expression prediction
Background: MicroRNA (miRNA) directed gene repression is an important mechanism of posttranscriptional
regulation. Comprehensive analyses of how microRNA influence biological processes requires paired
miRNA-mRNA expression datasets. However, a review of both GEO and ArrayExpress repositories revealed few
such datasets, which was in stark contrast to the large number of messenger RNA (mRNA) only datasets. It is of
interest that numerous primary miRNAs (precursors of microRNA) are known to be co-expressed with coding
genes (host genes).
Results: We developed a miRNA-mRNA interaction analyses pipeline. The proposed solution is based on two
miRNA expression prediction methods – a scaling function and a linear model. Additionally, miRNA-mRNA anticorrelation
analyses are used to determine the most probable miRNA gene targets (i.e. the differentially
expressed genes under the influence of up- or down-regulated microRNA). Both the consistency and accuracy
of the prediction method is ensured by the application of stringent statistical methods. Finally, the predicted
targets are subjected to functional enrichment analyses including GO, KEGG and DO, to better understand the
predicted interactions.
Conclusions: The MMpred pipeline requires only mRNA expression data as input and is independent of third
party miRNA target prediction methods. The method passed extensive numerical validation based on the
binding energy between the mature miRNA and 3’ UTR region of the target gene. We report that MMpred is
capable of generating results similar to that obtained using paired datasets. For the reported test cases we
generated consistent output and predicted biological relationships that will help formulate further testable
hypotheses
Integration of microRNA changes in vivo identifies novel molecular features of muscle insulin resistance in type 2 diabetes
Skeletal muscle insulin resistance (IR) is considered a critical component of type II diabetes, yet to date IR has evaded characterization at the global gene expression level in humans. MicroRNAs (miRNAs) are considered fine-scale rheostats of protein-coding gene product abundance. The relative importance and mode of action of miRNAs in human complex diseases remains to be fully elucidated. We produce a global map of coding and non-coding RNAs in human muscle IR with the aim of identifying novel disease biomarkers. We profiled >47,000 mRNA sequences and >500 human miRNAs using gene-chips and 118 subjects (n = 71 patients versus n = 47 controls). A tissue-specific gene-ranking system was developed to stratify thousands of miRNA target-genes, removing false positives, yielding a weighted inhibitor score, which integrated the net impact of both up- and down-regulated miRNAs. Both informatic and protein detection validation was used to verify the predictions of in vivo changes. The muscle mRNA transcriptome is invariant with respect to insulin or glucose homeostasis. In contrast, a third of miRNAs detected in muscle were altered in disease (n = 62), many changing prior to the onset of clinical diabetes. The novel ranking metric identified six canonical pathways with proven links to metabolic disease while the control data demonstrated no enrichment. The Benjamini-Hochberg adjusted Gene Ontology profile of the highest ranked targets was metabolic (P < 7.4 × 10-8), post-translational modification (P < 9.7 × 10-5) and developmental (P < 1.3 × 10-6) processes. Protein profiling of six development-related genes validated the predictions. Brain-derived neurotrophic factor protein was detectable only in muscle satellite cells and was increased in diabetes patients compared with controls, consistent with the observation that global miRNA changes were opposite from those found during myogenic differentiation. We provide evidence that IR in humans may be related to coordinated changes in multiple microRNAs, which act to target relevant signaling pathways. It would appear that miRNAs can produce marked changes in target protein abundance in vivo by working in a combinatorial manner. Thus, miRNA detection represents a new molecular biomarker strategy for insulin resistance, where micrograms of patient material is needed to monitor efficacy during drug or life-style interventions
Insights into the regulation of intrinsically disordered proteins in the human proteome by analyzing sequence and gene expression data
Background:
Disordered proteins need to be expressed to carry out specified functions; however, their accumulation in the cell can potentially cause major problems through protein misfolding and aggregation. Gene expression levels, mRNA decay rates, microRNA (miRNA) targeting and ubiquitination have critical roles in the degradation and disposal of human proteins and transcripts. Here, we describe a study examining these features to gain insights into the regulation of disordered proteins.
Results:
In comparison with ordered proteins, disordered proteins have a greater proportion of predicted ubiquitination sites. The transcripts encoding disordered proteins also have higher proportions of predicted miRNA target sites and higher mRNA decay rates, both of which are indicative of the observed lower gene expression levels. The results suggest that the disordered proteins and their transcripts are present in the cell at low levels and/or for a short time before being targeted for disposal. Surprisingly, we find that for a significant proportion of highly disordered proteins, all four of these trends are reversed. Predicted estimates for miRNA targets, ubiquitination and mRNA decay rate are low in the highly disordered proteins that are constitutively and/or highly expressed.
Conclusions:
Mechanisms are in place to protect the cell from these potentially dangerous proteins. The evidence suggests that the enrichment of signals for miRNA targeting and ubiquitination may help prevent the accumulation of disordered proteins in the cell. Our data also provide evidence for a mechanism by which a significant proportion of highly disordered proteins (with high expression levels) can escape rapid degradation to allow them to successfully carry out their function
Hepatic microRNA profiles offer predictive and mechanistic insights after exposure to genotoxic and epigenetic hepatocarcinogens.
In recent years, accumulating evidence supports the importance of microRNAs in liver physiology and disease; however, few studies have examined the involvement of these noncoding genes in chemical hepatocarcinogenesis. Here, we examined the liver microRNA profile of male Fischer rats exposed through their diet to genotoxic (2-acetylaminofluorene) and epigenetic (phenobarbital, diethylhexylphthalate, methapyrilene HCL, monuron, and chlorendic acid) chemical hepatocarcinogens, as well as to non-hepatocarcinogenic treatments (benzophenone, and diethylthiourea) for 3 months. The effects of these treatments on liver pathology, plasma clinical parameters, and liver mRNAs were also determined. All hepatocarcinogens affected the expression of liver mRNAs, while the hepatic microRNA profiles were associated with the mode of action of the chemical treatments and corresponded to chemical carcinogenicity. The three nuclear receptor-activating chemicals (phenobarbital, benzophenone, and diethylhexylphthalate) were characterized by the highly correlated induction of the miR-200a/200b/429, which is involved in protecting the epithelial status of cells and of the miR-96/182 clusters. The four non-nuclear receptor-activating hepatocarcinogens were characterized by the early, persistent induction of miR-34, which was associated with DNA damage and oxidative stress in vivo and in vitro. Repression of this microRNA in a hepatoma cell line led to increased cell growth; thus, miR-34a could act to block abnormal cell proliferation in cells exposed to DNA damage or oxidative stress. This study supports the proposal that hepatic microRNA profiles could assist in the earlier evaluation and identification of hepatocarcinogens, especially those acting by epigenetic mechanisms. © The Author 2012. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved
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