Identification of miRNA regulatory pathways in complex diseases

MicroRNAs, small endogenous non-coding RNAs are one of the most important components in the cell and they play a critical role in many cellular processes and have been linked to the control of signal transduction pathways. Identifying disease related miRNAs and using that knowledge to understand the disease pathogenesis at the molecular level, new molecular tools can be designed for reducing the time and cost of diagnosis, treatment and prevention. Computational models have become very useful and practical in terms of discovering new miRNA disease associations to be used in experimental validations. Omics studies demonstrated that changes in miRNA profiles of various tissues correlate with many complex diseases, such as Alzheimer’s, Parkinson’s or Huntington’s and various cancers. The aim of our study was to identify the potential active TF-miRNA-gene regulatory pathways involved in complex diseases Huntington’s and Parkinson’s, via integrating miRNA and gene expression profiles with known experimentally verified miRNAs/genes and directed signaling network. We downloaded the miRNA and gene expression profiles from gene expression omnibus (GEO) database. We derived the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs). SIGNOR database of causal relationships between signaling entities is used vi as a signed directed network and TF-miRNA-gene bidirectional regulatory network is constructed. Then, DEGs and DEmiRs are mapped to the TF-miRNA-gene regulatory network. We connected the mapped DEGs and DEmiR nodes with their third-degree neighbors, hence, the potential regulatory TF-miRNA-gene subnetwork was built. By using BFS algorithm, the potential disease related TF-miRNA-gene regulatory pathways were identified. In this study, we analyzed Huntington’s and Parkinson’s related mRNA and miRNA expression profiles with transcription factors (TF) and miRNAs known to be related to diseases. miRNA-TF-gene regulatory mechanisms and disease specific TF and miRNA regulatory pathways were aimed to be identified systematically. This study provides bioinformatic support for further research on the molecular mechanism of complex diseases

Bioinformatics Workflows for Genomic Variant Discovery, Interpretation and Prioritization

Next-generation sequencing (NGS) techniques allow high-throughput detection of a vast amount of variations in a cost-efficient manner. However, there still are inconsistencies and debates about how to process and analyse this ‘big data’. To accurately extract clinically relevant information from genomics data, choosing appropriate tools, knowing how to best utilize them and interpreting the results correctly is crucial. This chapter reviews state-of-the-art bioinformatics approaches in clinically relevant genomic variant detection. Best practices of reads-to-variant discovery workflows for germline and somatic short genomic variants are presented along with the most commonly utilized tools for each step. Additionally, methods for detecting structural variations are overviewed. Finally, approaches and current guidelines for clinical interpretation of genomic variants are discussed. As emphasized in this chapter, data processing and variant discovery steps are relatively well-understood. The differences in prioritization algorithms on the other hand can be perplexing, thus creating a bottleneck during interpretation. This review aims to shed light on the pros and cons of these differences to help experts give more informed decisions

In silico analyses and global transcriptional profiling reveal novel putative targets for Pea3 transcription factor related to its function in neurons.

Pea3 transcription factor belongs to the PEA3 subfamily within the ETS domain transcription factor superfamily, and has been largely studied in relation to its role in breast cancer metastasis. Nonetheless, Pea3 plays a role not only in breast tumor, but also in other tissues with branching morphogenesis, including kidneys, blood vasculature, bronchi and the developing nervous system. Identification of Pea3 target promoters in these systems are important for a thorough understanding of how Pea3 functions. Present study particularly focuses on the identification of novel neuronal targets of Pea3 in a combinatorial approach, through curation, computational analysis and microarray studies in a neuronal model system, SH-SY5Y neuroblastoma cells. We not only show that quite a number of genes in cancer, immune system and cell cycle pathways, among many others, are either up- or down-regulated by Pea3, but also identify novel targets including ephrins and ephrin receptors, semaphorins, cell adhesion molecules, as well as metalloproteases such as kallikreins, to be among potential target promoters in neuronal systems. Our overall results indicate that rather than early stages of neurite extension and axonal guidance, Pea3 is more involved in target identification and synaptic maturation

CSF Proteomics Identifies Specific and Shared Pathways for Multiple Sclerosis Clinical Subtypes.

Multiple sclerosis (MS) is an immune-mediated, neuro-inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS) with a heterogeneous clinical presentation and course. There is a remarkable phenotypic heterogeneity in MS, and the molecular mechanisms underlying it remain unknown. We aimed to investigate further the etiopathogenesis related molecular pathways in subclinical types of MS using proteomic and bioinformatics approaches in cerebrospinal fluids of patients with clinically isolated syndrome, relapsing remitting MS and progressive MS (n=179). Comparison of disease groups with controls revealed a total of 151 proteins that are differentially expressed in clinically different MS subtypes. KEGG analysis using PANOGA tool revealed the disease related pathways including aldosterone-regulated sodium reabsorption (p=8.02x10(-5)) which is important in the immune cell migration, renin-angiotensin (p=6.88x10(-5)) system that induces Th17 dependent immunity, notch signaling (p=1.83x10(-10)) pathway indicating the activated remyelination and vitamin digestion and absorption pathways (p=1.73x10(-5)). An emerging theme from our studies is that whilst all MS clinical forms share common biological pathways, there are also clinical subtypes specific and pathophysiology related pathways which may have further therapeutic implications

Assessment of global and gene-specific DNA methylation in rat liver and kidney in response to non-genotoxic carcinogen exposure

Altered expression of tumor suppressor genes and oncogenes, which is regulated in part at the level of DNA methylation, is an important event involved in non-genotoxic carcinogenesis. This may serve as a marker for early detection of non-genotoxic carcinogens. Therefore, we evaluated the effects of non-genotoxic hepatocarcinogens, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), hexachlorobenzene (HCB), methapyrilene (MPY) and male rat kidney carcinogens, d-limonene, p-dichlorobenzene (DCB), chloroform and ochratoxin A (OTA) on global and CpG island promoter methylation in their respective target tissues in rats. No significant dose-related effects on global DNA hypomethylation were observed in tissues of rats compared to vehicle controls using LC-MS/MS in response to short-term non-genotoxic carcinogen exposure. Initial experiments investigating gene-specific methylation using methylation-specific PCR and bisulfite sequencing, revealed partial methylation of p16 in the liver of rats treated with HCB and TCDD. However, no treatment related effects on the methylation status of Cx32, e-cadherin, VHL, c-myc, Igfbp2, and p15 were observed. We therefore applied genome-wide DNA methylation analysis using methylated DNA immunoprecipitation combined with microarrays to identify alterations in gene-specific methylation. Under the conditions of our study, some genes were differentially methylated in response to MPY and TCDD, whereas d-limonene, DCB and chloroform did not induce any methylation changes. 90-day OTA treatment revealed enrichment of several categories of genes important in protein kinase activity and mTOR cell signaling process which are related to OTA nephrocarcinogenicity. (C) 2015 Elsevier Inc. All rights reserved

PANOGA analysis of microarray results.

<p>Data was run 5 times, and genes with statistical significance were reported for occurrence and name. Pathways of interest are indicated in <b>bold</b>.</p

Chromatin immunoprecipitation (ChIP) and Pea3-VP16 binding.

<p>(a) ChIP PCR in untransfected vs Pea3-VP16 overexpressing SH-SY5Y cells, immunoprecipitated with either Flag antibody (Flag IP) or IgG (IgG IP). Dissimilarity score (ds) of selected <i>ets</i> motifs are indicated, and explained further in text; (b) weblogo analysis for genes that were either 2- to 5-fold downregulated or2- to 5-fold upregulated upon Pea3-VP16 expression in SH-SY5Y cells.</p

Analysis of kallikreins as novel targets for Pea3.

<p>(a) q-RT-PCR results for KLK2-9 that were activated upon Pea3-VP16 overexpression in SH-SY5Y cells (grey bars) as compared to pCDNA3-transfected cells (white bars); (b) comparison of fold change in q-RT-PCR assay vs microarray results; (d) analysis of kallikrein promoters for putative Pea3 binding sites.</p

The list of primers used in qRT-PCR analyses (* primer sequences obtained from Pratt and Kinch, 2003).

<p>The list of primers used in qRT-PCR analyses (* primer sequences obtained from Pratt and Kinch, 2003).</p