Computational Methods for MicroRNA Target Prediction

microRNA Isolation, Expression Profiling, and Target Identification for Neuroprotection in Alzheimer's Disease

Millions of people throughout the world are affected by neurodegenerative disorders like Alzheimer's disease (AD), making them a major public health concern. To create successful medicines, early diagnosis and illness monitoring are required. Emerging as possible diagnostic and treatment tools for neurodegenerative illnesses are biomarkers such as microRNAs (miRNAs). In the realm of neuroscience, miRNAs have been discovered to function as essential regulators of gene expression, with roles spanning development, differentiation, and illness. Several neurodegenerative diseases, including AD, have been linked to miRNA dysregulation. As high-throughput methods have been developed for monitoring miRNA expression and identifying miRNA targets, miRNAs have become a prime candidate for use in diagnostics and therapy. The techniques for isolating miRNAs and the most up-to-date computational methods for finding miRNA target transcripts are both described in this chapter. This chapter will be a helpful reference for anyone investigating the role of miRNAs in AD and related neurodegenerative illnesses.

Up-Regulated Interleukin-10 Induced by E2F Transcription Factor 2-MicroRNA-17-5p Circuitry in Extrafollicular Effector B Cells Contributes to Autoantibody Production in Systemic Lupus Erythematosus

OBJECTIVE

Elevated interleukin-10 (IL-10) levels in patients with systemic lupus erythematosus (SLE) have B cell-promoting effects, contributing to autoantibody production and tissue damage. We aimed to characterize up-regulated IL-10+ B cell subsets and dysregulated IL10 expression in SLE B cells for new therapeutic options.

METHODS

Proportions of Th10 and IL-10+ B cell subsets in peripheral blood mononuclear cells (PBMCs) were assessed using flow cytometry. The IL10 3'-untranslated region (3'-UTR) dual-luciferase vector was constructed and cotransfected with small interfering RNA (siRNA), microRNA (miRNA) mimics, or miRNA inhibitors into Raji cells. Transcript levels were quantified using TaqMan assays.

RESULTS

Culture conditions that induced IL-10+ Breg cells in healthy controls resulted in expansion of IL-10+ double-negative 2 (DN2; IgD-CD27-CD21-CD11c+) B cells in SLE PBMCs. Proportions of IL-10+ DN2, but not those of IL-10- DN2, correlated with disease activity and levels of antibodies to double-stranded DNA (dsDNA) (r = 0.60, P = 0.03 for cohort 1; r = 0.38, P = 0.03 for cohort 2), and were associated with high levels or seropositivity of anti-Sm (P = 0.03 for cohort 1; P = 0.01 for cohort 2) and IgG anticardiolipin (P < 0.01 for cohort 1; P = 0.02 for cohort 2) in SLE patients from 2 cohorts, of mainly African American subjects (cohort 1) and of Asian subjects (cohort 2). Proportions of Th10 (CD45RA-CXCR5-CXCR3+PD-1^high CD4+) cells correlated with IL-10+ DN2 frequencies (r = 0.60, P < 0.01 for cohort 2), antinuclear antibody titers (r = 0.52, P = 0.01 for cohort 2), and proteinuria levels (r = 0.72, P < 0.01 for cohort 2) in SLE patients. Screening of predicted IL10 3'-UTR-targeting miRNAs in SLE B cells identified miRNA-17-5p (miR-17-5p) and miR-20a-5p, with their levels inversely correlated with IL10 (r = -0.47, P < 0.01 for miR-17-5p; r = -0.37, P = 0.03 for miR-20-5p) and transcription factor E2F2 (r = -0.48, P = 0.04 for miR-17-5p; r = -0.45, P = 0.05 for miR-20-5p). In Raji cells, knockdown of E2F2 expression resulted in increased levels of miR-17-5p and miR-20a-5p and decreased IL10 messenger RNA (mRNA) and protein levels, and overexpression and inhibition of miR-17-5p down-regulated and up-regulated, respectively, IL10 mRNA levels, suggesting regulation of IL10 expression by an E2F2-miR-17-5p loop.

CONCLUSION

IL-10 promotes extrafollicular autoimmune responses in patients with active SLE, which might be dampened by targeting the E2F2-miR-17-5p circuitry.

Conservation and Divergence of SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) Gene Family between Wheat and Rice

The SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) gene family affects plant architecture, panicle structure, and grain development, representing key genes for crop improvements. The objective of the present study is to utilize the well characterized SPLs' functions in rice to facilitate the functional genomics of TaSPL genes. To achieve these goals, we combined several approaches, including genome-wide analysis of TaSPLs, comparative genomic analysis, expression profiling, and functional study of TaSPL3 in rice. We established the orthologous relationships of 56 TaSPL genes with the corresponding OsSPLs, laying a foundation for the comparison of known SPL functions between wheat and rice. Some TaSPLs exhibited different spatial-temporal expression patterns when compared to their rice orthologs, thus implicating functional divergence. TaSPL2/6/8/10 were identified to respond to different abiotic stresses through the combination of RNA-seq and qPCR expression analysis. Additionally, ectopic expression of TaSPL3 in rice promotes heading dates, affects leaf and stem development, and leads to smaller panicles and decreased yields per panicle. In conclusion, our work provides useful information toward cataloging of the functions of TaSPLs, emphasized the conservation and divergence between TaSPLs and OsSPLs, and identified the important SPL genes for wheat improvement.

Recent development of bioinformatics tools for microRNA target prediction

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. High-throughput experimental approaches for miRNA target identification are costly and time-consuming, depending on various factors. It is vitally important to develop the bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies specially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

miRNAs in SARS-CoV 2: A Spoke in the Wheel of Pathogenesis

INTRODUCTION

The rapid emergence of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-- CoV-2) has resulted in an increased mortality rate across the globe. However, the underlying mechanism of SARS-CoV-2 altering human immune response is still elusive. The existing literature on miRNA mediated pathogenesis of RNA virus viz. Dengue virus, West Nile virus, etc. raises a suspicion that miRNA encoded by SARS-CoV-2 might facilitate virus replication and regulate the host's gene expression at the post-transcriptional level.

METHODS

We investigated this possibility via computational prediction of putative miRNAs encoded by the SARS-CoV-2 genome using a novel systematic pipeline that predicts putative mature-miRNA and their targeted genes transcripts. To trace down if viral-miRNAs targeted the genes critical to the immune pathway, we assessed whether mature miRNA transcripts exhibit effective hybridization with the 3'UTR region of human gene transcripts. Conversely, we also tried to study human miRNA-mediated viral gene regulation to get insight into the miRNA mediated offense and defense mechanism of virus and its host organisms in toto.

RESULTS

Our analysis led us to shortlist six putative miRNAs that target, majorly, genes related to cell proliferation/ differentiation/signaling, and senescence. Nonetheless, they also target immune-related genes that directly/ indirectly orchestrate immune pathways like TNF (Tumor Necrosis Factor) signaling and Chemokine signaling pathways putatively serving as the nucleus to cytokine storms.

CONCLUSION

Besides, these six miRNAs were found to be conserved so far across 80 complete genomes of SARS-CoV-2 (NCBI Virus, last assessed 12 April 2020) including Indian strains that are also targeted by 7 human miRNAs and can, therefore, be exploited to develop MicroRNA-Attenuated Vaccines.

miRNAs as Therapeutic Tools and Biomarkers for Prostate Cancer

Prostate cancer (PCa) is the fifth cause of tumor-related deaths in man worldwide. Despite the considerable improvement in the clinical management of PCa, several limitations emerged both in the screening for early diagnosis and in the medical treatment. The use of prostate-specific antigen (PSA)-based screening resulted in patients' overtreatment and the standard therapy of patients suffering from locally advanced/metastatic tumors (e.g., radical prostatectomy, radiotherapy, and androgen deprivation therapy) showed time-limited efficacy with patients undergoing progression toward the lethal metastatic castration-resistant PCa (mCRPC). Although valuable alternative therapeutic options have been recently proposed (e.g., docetaxel, cabazitaxel, abiraterone, enzalutamide, and sipuleucel-T), mCRPC remains incurable. Based on this background, there is an urgent need to identify new and more accurate prostate-specific biomarkers for PCa diagnosis and prognosis and to develop innovative medical approaches to counteract mCRPC. In this context, microRNA (miRNAs) emerged as potential biomarkers in prostate tissues and biological fluids and appeared to be promising therapeutic targets/tools for cancer therapy. Here we overview the recent literature and summarize the achievements of using miRNAs as biomarkers and therapeutic targets/tools for fighting PCa.

MicroRNA target gene prediction of ischemic stroke by using variational Bayesian inference for Gauss mixture model

MicroRNAs (miRNAs) as biomarkers of numerous diseases, are a novel group of single-stranded, non-coding small RNA molecules, which can regulate the gene expression and transcription or translation of target genes. Therefore, accurately identifying miRNAs and predicting their potential target genes correlated with ischemic stroke contribute to quick understanding and diagnosis of the pathogenesis of ischemic stroke. In order to identify the targets of miRNAs, the differential expression and expression profiling of mRNAs in genome are integrated by using the Gene Expression Omnibus (GEO) database and limma package. Furthermore, the probabilistic scoring approach called TargetScore, is proposed as a promising new technique combined with the expression and sequence information of the known genes. In this study, the priori and posterior probabilities of target genes were obtained by Variational Bayesian-Gaussian Mixture Model (VB-GMM). Consequently, the target genes of miR-124, miR-221 and miR-223, correlated with ischemic stroke, were predicted using the new target prediction algorithm. Ultimately, the comparable downregulation target genes were obtained by integrating the transcendental and posterior values.

Mapping of microRNAs related to cervical cancer in Latin American human genomic variants

Background: MicroRNAs are related to human cancers, including cervical cancer (CC) caused by HPV. In 2018, approximately 56.075 cases and 28.252 deaths from this cancer were registered in Latin America and the Caribbean according to GLOBOCAN reports. The main molecular mechanism of HPV in CC is related to integration of viral DNA into the hosts' genome. However, the different variants in the human genome can result in different integration mechanisms, specifically involving microRNAs (miRNAs). Methods: The miRNAs associated with CC were obtained from literature, the miRNA sequences and four human genome variants (HGV) from Latin American populations were obtained from miRBase and 1000 Genomes Browser, respectively. HPV integration sites near cell cycle regulatory genes were identified. miRNAs were mapped on HGV. miRSNPs were identified in the miRNA sequences located at HPV integration sites on the Latin American HGV.  Results: Two hundred seventy-two miRNAs associated with CC were identified in 139 reports from different geographic locations. By mapping with Blast-Like Alignment Tool (BLAT), 2028 binding sites were identified from these miRNAs on the human genome (version GRCh38/hg38); 42 miRNAs were located on unique integration sites; and miR-5095, miR-548c-5p and miR-548d-5p were involved with multiple genes related to the cell cycle. Thirty-seven miRNAs were mapped on the Latin American HGV (PUR, MXL, CLM and PEL), but only miR-11-3p, miR-31-3p, miR-107, miR-133a-3p, miR-133a-5p, miR-133b, miR-215-5p, miR-491-3p, miR-548d-5p and miR-944 were conserved. Conclusions: Ten miRNAs were conserved in the four HGV. In the remaining 27 miRNAs, substitutions, deletions or insertions were observed. These variation patterns can imply differentiated mechanisms towards each genomic variant in human populations because of specific genomic patterns and geographic features. These findings may help in determining susceptibility for CC development. Further identification of cellular genes and signalling pathways involved in CC progression could lead new therapeutic strategies based on miRNAs.

CRISPR/Cas9-based genome engineering of zebrafish using a seamless integration strategy

Numerous feasible methods for inserting large fragments of exogenous DNA sequences into the zebrafish genome have been developed, as has genome editing technology using programmable nucleases. However, the coding sequences of targeted endogenous genes are disrupted, and the expression patterns of inserted exogenous genes cannot completely recapitulate those of endogenous genes. Here we describe the establishment of a novel strategy for endogenous promoter-driven and microhomology-mediated end-joining-dependent integration of a donor vector using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9. We successfully integrated mCherry into the final coding sequence of targeted genes to generate seamless transgenic zebrafish lines with high efficiency. This novel seamless transgenesis technique not only maintained the integrity of the endogenous gene but also did not disrupt the function of targeted gene. Therefore, our microhomology-mediated end-joining-mediated transgenesis strategy may have broader applications in gene therapy. Moreover, this novel seamless gene-editing strategy in zebrafish provides a valuable new transgenesis technique, which was driven by endogenous promoters and in vivo animal reporter modes for translational medicine. It is expected to be a standard gene-editing technique in the field of zebrafish, leading to some important breakthroughs for studies in early embryogenesis.-Luo, J.-J., Bian, W.-P., Liu, Y., Huang, H.-Y., Yin, Q., Yang, X.-J., Pei, D.-S. CRISPR/Cas9-based genome engineering of zebrafish using a seamless integration strategy.

Computational Model for Predicting the Relationship Between Micro-RNAs and Their Target Messenger RNAs in Breast and Colon Cancers

Motivation

Uncovering the relationship between micro-RNAs (miRNAs) and their target messenger RNAs (mRNAs) can provide critical information regarding the mechanisms underlying certain types of cancers. In this context, we have proposed a computational method, referred to as prediction analysis by optimization method (PAOM), to predict miRNA-mRNA relations using data from normal and cancer tissues, and then applying the relevant algorithms to colon and breast cancers. Specifically, we used 26 miRNAs and 26 mRNAs with 676 (= 26 × 26) relationships to be recovered as unknown parameters.

Results

Optimization methods were used to detect 61 relationships in breast cancer and 32 relationships in colon cancer. Using sequence filtering, we detected 18 relationships in breast cancer and 15 relationships in colon cancer. Among the 18 relationships, CD24 is the target gene of let-7a and miR-98, and E2F1 is the target gene of miR-20. In addition, the frequencies of the target genes of miR-223, miR-23a, and miR-20 were significant in breast cancer, and the frequencies of the target genes of miR-17, miR-124, and miR-30a were found to be significant in colon cancer.

Availability

The numerical code is available from the authors on request.

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3' untranslated region (UTR) of target mRNA to inhibit protein translation or in some instances cause mRNA degradation. The binding of the miRNA to the 3' UTR of the target mRNA is mediated by a 2-8 nucleotide seed sequence at the 5' end of miRNA. While the role of miRNAs as cellular regulatory molecules is well established, identification of the target mRNAs with functional relevance remains a challenge. Bioinformatic tools have been employed to predict sequences within the 3' UTR of mRNAs as potential targets for miRNA binding. These tools have also been utilized to determine the evolutionary conservation of such sequences among related species in an attempt to predict functional role. However, these computational methods often generate false positive results and are limited to predicting canonical interaction between miRNA and mRNA. Therefore, experimental procedures that measure direct binding of miRNA to its mRNA target are necessary to establish functional interaction. In this report, we describe a sensitive method for validating direct interaction between the cellular miRNA miR-125b and the 3' UTR of PARP-1 mRNA. We elaborate a protocol in which synthetic biotinylated-miRNA mimics were transfected into mammalian cells and the miRNA-mRNA complex in the cellular lysate was pulled down with streptavidin-coated magnetic beads. Finally, the target mRNA in the pulled-down nucleic acid complex was quantified using a qPCR-based strategy.

Micrornas in prostate cancer: an overview

Prostate cancer is the second highest cause of cancer mortality after lung tumours. In USA it affects about 2.8 million men and the incidence increases with age in many countries. Therefore, early diagnosis is a very important step for patient clinical evaluation and for a selective and efficient therapy. The study of miRNAs' functions and molecular mechanisms has brought new knowledge in biological processes of cancer. In prostate cancer there is a deregulation of several miRNAs that may function as tumour suppressors or oncogenes. The aim of this review is to analyze the progress made to our understanding of the role of miRNA dysregulation in prostate cancer tumourigenesis.

STAT1 Inhibits MiR-181a Expression to Suppress Colorectal Cancer Cell Proliferation Through PTEN/Akt

Signal transducers and activators of transcription 1 (STAT1) exhibits tumor-suppressor properties by inhibiting oncogenic pathways and promoting tumor immunosurveillance. MicroRNAs, a group of non-coding endogenous ones, may regulate gene expression and plays specific roles in tumorigenesis. Recently, miR-181a has been reported to be associated with poor prognosis of colorectal cancer (CRC). Using human colorectal cancer cell lines, we demonstrated that STAT1 suppresses both LoVo and SW480 cell growth by down-regulating miR-181a. STAT1 regulates the expression of miR-181a through binding to the elements in the miR-181a's promoter region. Further, we revealed that miR-181a accelerates CRC cell proliferation through phosphatase and tensin homolog on chromosome ten (PTEN). In addition, PTEN protein was upregulated in response to STAT1 overexpression or miR-181a inhibition, downregulated in response to STAT1 knockdown or miR-181a overexpression. Without changes on the AKT protein level, p-AKT was downregulated by STAT1 overexpression or miR-181a inhibition while upregulated by STAT1 knockdown or miR-181a overexpression, indicating PTEN/Akt pathway activated in STAT1/miR-181a regulation of CRC cell proliferation. Taken together, our findings shed new light on the STAT1/miR-181a/PTEN pathway in colorectal cancer and add new insight regarding the carcinogenesis of colorectal cancer. J. Cell. Biochem. 118: 3435-3443, 2017. © 2017 Wiley Periodicals, Inc.

De novo computational identification of stress-related sequence motifs and microRNA target sites in untranslated regions of a plant translatome

Gene regulation at the transcriptional and translational level leads to diversity in phenotypes and function in organisms. Regulatory DNA or RNA sequence motifs adjacent to the gene coding sequence act as binding sites for proteins that in turn enable or disable expression of the gene. Whereas the known DNA and RNA binding proteins range in the thousands, only a few motifs have been examined. In this study, we have predicted putative regulatory motifs in groups of untranslated regions from genes regulated at the translational level in Arabidopsis thaliana under normal and stressed conditions. The test group of sequences was divided into random subgroups and subjected to three de novo motif finding algorithms (Seeder, Weeder and MEME). In addition to identifying sequence motifs, using an in silico tool we have predicted microRNA target sites in the 3′ UTRs of the translationally regulated genes, as well as identified upstream open reading frames located in the 5′ UTRs. Our bioinformatics strategy and the knowledge generated contribute to understanding gene regulation during stress, and can be applied to disease and stress resistant plant development.

Computational and Experimental Identification of Tissue-Specific MicroRNA Targets

In this chapter we discuss computational methods for the prediction of microRNA (miRNA) targets. More specifically, we consider machine learning-based approaches and explain why these methods have been relatively unsuccessful in reducing the number of false positive predictions. Further we suggest approaches designed to improve their performance by considering tissue-specific target regulation. We argue that the miRNA targetome differs depending on the tissue type and introduce a novel algorithm that predicts miRNA targets specifically for colorectal cancer. We discuss features of miRNAs and target sites that affect target recognition, and how next-generation sequencing data can support the identification of novel miRNAs, differentially expressed miRNAs and their tissue-specific mRNA targets. In addition, we introduce some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA target interactions.

Cytoplasmic male sterility (CMS) in hybrid breeding in field crops

A comprehensive understanding of CMS/Rf system enabled by modern omics tools and technologies considerably improves our ability to harness hybrid technology for enhancing the productivity of field crops. Harnessing hybrid vigor or heterosis is a promising approach to tackle the current challenge of sustaining enhanced yield gains of field crops. In the context, cytoplasmic male sterility (CMS) owing to its heritable nature to manifest non-functional male gametophyte remains a cost-effective system to promote efficient hybrid seed production. The phenomenon of CMS stems from a complex interplay between maternally-inherited (mitochondrion) and bi-parental (nucleus) genomic elements. In recent years, attempts aimed to comprehend the sterility-inducing factors (orfs) and corresponding fertility determinants (Rf) in plants have greatly increased our access to candidate genomic segments and the cloned genes. To this end, novel insights obtained by applying state-of-the-art omics platforms have substantially enriched our understanding of cytoplasmic-nuclear communication. Concomitantly, molecular tools including DNA markers have been implicated in crop hybrid breeding in order to greatly expedite the progress. Here, we review the status of diverse sterility-inducing cytoplasms and associated Rf factors reported across different field crops along with exploring opportunities for integrating modern omics tools with CMS-based hybrid breeding.

Predicting RNA-RNA Interactions Using RNAstructure

RNA-RNA binding is a required step for many regulatory and catalytic processes in the cell. Identifying RNA-RNA hybridization sites is challenging because of the competition between intramolecular and intermolecular structure formation. A complete picture of RNA-RNA binding includes an understanding of single-stranded folding and binding site accessibility, and is strongly concentration-dependent. This chapter provides guidance for using RNAstructure to predict RNA-RNA binding sites and RNA-RNA structures, utilizing free energy minimization and partition function calculations. RNAstructure is freely available at http://rna.urmc.rochester.edu/RNAstructure.html .

AccessFold: predicting RNA-RNA interactions with consideration for competing self-structure

MOTIVATION

There are numerous examples of RNA-RNA complexes, including microRNA-mRNA and small RNA-mRNA duplexes for regulation of translation, guide RNA interactions with target RNA for post-transcriptional modification and small nuclear RNA duplexes for splicing. Predicting the base pairs formed between two interacting sequences remains difficult, at least in part because of the competition between unimolecular and bimolecular structure.

RESULTS

Two algorithms were developed for improved prediction of bimolecular RNA structure that consider the competition between self-structure and bimolecular structure. These algorithms utilize two novel approaches to evaluate accessibility: free energy density minimization and pseudo-energy minimization. Free energy density minimization minimizes the folding free energy change per nucleotide involved in an intermolecular secondary structure. Pseudo-energy minimization (called AccessFold) minimizes the sum of free energy change and a pseudo-free energy penalty for bimolecular pairing of nucleotides that are unlikely to be accessible for bimolecular structure. The pseudo-free energy, derived from unimolecular pairing probabilities, is applied per nucleotide in bimolecular pairs, and this approach is able to predict binding sites that are split by unimolecular structures. A benchmark set of 17 bimolecular RNA structures was assembled to assess structure prediction. Pseudo-energy minimization provides a statistically significant improvement in sensitivity over the method that was found in a benchmark to be the most accurate previously available method, with an improvement from 36.8% to 57.8% in mean sensitivity for base pair prediction.

AVAILABILITY AND IMPLEMENTATION

Pseudo-energy minimization is available for download as AccessFold, under an open-source license and as part of the RNAstructure package, at: http://rna.urmc.rochester.edu/RNAstructure.html

CONTACT

david_mathews@urmc.rochester.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MicroRNA Regulating Glutathione S-Transferase P1 in Prostate Cancer

Glutathione S-transferase P1 (GSTP1), an enzyme involved in detoxification process, is frequently inactivated in prostate cancer due to epigenetic modifications. Through in silico analysis we identified a subset of miRNAs that are putative targets in regulating GSTP1. miRNAs are small endogenous non-coding RNA that are critical regulators of various physiologic and pathologic processes and their level of expression may play a precise role in early diagnosis and prognosis of cancer. These small molecules have been detected in a wide variety of human biological specimens including blood, serum, urine, ejaculate and tissues, which could be utilized as clinically useful biomarker in early detection and prognosis of prostate cancer. The chapter summarizes the current knowledge about miRNA involved in GSTP1 regulation in prostate cancer and their potential as useful biomarkers of disease for early detection and prognosis, along with challenges and limitations in this development.

Introduction to microRNAs: Biogenesis, Action, Relevance of Tissue microRNAs in Disease Pathogenesis, Diagnosis and Therapy-The Concept of Circulating microRNAs

MicroRNAs as the endogenous mediators of RNA interference have principal roles in gene expression regulation. Since their discovery in the early 1990s, their number has steadily grown to approximately 2500 known microRNAs at present in humans. MicroRNAs encoded by distinct genes regulate the expression of about 30-60 % of human protein coding genes by targeting their messenger RNAs (mRNAs) and induce mostly posttranscriptional inhibition, or in some cases enhancement. MicroRNAs, as fine regulators of the gene expression, have important roles in development, the physiological functioning of the organism, e.g. organogenesis, immune functioning, vascular system, etc. The deregulation of microRNA expression has been observed in many disorders, such as in carcinogenesis. Given their tissue specificity and stability, and specific disease-related alterations, tissue microRNAs can be exploited as excellent biomarkers in the diagnosis. Moreover, microRNAs might also be envisaged as novel therapeutic targets. Beside tissue microRNAs, novel data show that microRNAs are also present in body fluids that could further extend their diagnostic utility as minimally invasive biomarkers of various diseases, but also raises intriguing questions regarding their biological relevance. In this introductory chapter, we summarise the most relevant features of microRNAs including their biogenesis, action, the biological, pathological, diagnostic and potential therapeutical relevance of tissue microRNAs.

Delivery and targeting of miRNAs for treating liver fibrosis

Liver fibrosis is a pathological condition originating from liver damage that leads to excess accumulation of extracellular matrix (ECM) proteins in the liver. Viral infection, chronic injury, local inflammatory responses and oxidative stress are the major factors contributing to the onset and progression of liver fibrosis. Multiple cell types and various growth factors and inflammatory cytokines are involved in the induction and progression of this disease. Various strategies currently being tried to attenuate liver fibrosis include the inhibition of HSC activation or induction of their apoptosis, reduction of collagen production and deposition, decrease in inflammation, and liver transplantation. Liver fibrosis treatment approaches are mainly based on small drug molecules, antibodies, oligonucleotides (ODNs), siRNA and miRNAs. MicroRNAs (miRNA or miR) are endogenous noncoding RNA of ~22 nucleotides that regulate gene expression at post transcription level. There are several miRNAs having aberrant expressions and play a key role in the pathogenesis of liver fibrosis. Single miRNA can target multiple mRNAs, and we can predict its targets based on seed region pairing, thermodynamic stability of pairing and species conservation. For in vivo delivery, we need some additional chemical modification in their structure, and suitable delivery systems like micelles, liposomes and conjugation with targeting or stabilizing the moiety. Here, we discuss the role of miRNAs in fibrogenesis and current approaches of utilizing these miRNAs for treating liver fibrosis.

Computational Methods for MicroRNA Target Prediction

MicroRNAs (miRNAs) have been identified as one of the most important molecules that regulate gene expression in various organisms. miRNAs are short, 21–23 nucleotide-long, single stranded RNA molecules that bind to 3' untranslated regions (3' UTRs) of their target mRNAs. In general, they silence the expression of their target genes via degradation of the mRNA or by translational repression. The expression of miRNAs, on the other hand, also varies in different tissues based on their functions. It is significantly important to predict the targets of miRNAs by computational approaches to understand their effects on the regulation of gene expression. Various computational methods have been generated for miRNA target prediction but the resulting lists of candidate target genes from different algorithms often do not overlap. It is crucial to adjust the bioinformatics tools for more accurate predictions as it is equally important to validate the predicted target genes experimentally.

Mechanisms of miRNA-Mediated Gene Regulation from Common Downregulation to mRNA-Specific Upregulation

Discovered in 1993, micoRNAs (miRNAs) are now recognized as one of the major regulatory gene families in eukaryotes. To date, 24521 microRNAs have been discovered and there are certainly more to come. It was primarily acknowledged that miRNAs result in gene expression repression at both the level of mRNA stability by conducting mRNA degradation and the level of translation (at initiation and after initiation) by inhibiting protein translation or degrading the polypeptides through binding complementarily to 3′UTR of the target mRNAs. Nevertheless, some studies revealed that miRNAs have the capability of activating gene expression directly or indirectly in respond to different cell types and conditions and in the presence of distinct cofactors. This reversibility in their posttranslational gene regulatory natures enables the bearing cells to rapidly response to different cell conditions and consequently block unnecessary energy wastage or maintain the cell state. This paper provides an overview of the current understandings of the miRNA characteristics including their genes and biogenesis, as well as their mediated downregulation. We also review up-to-date knowledge of miRNA-mediated gene upregulation through highlighting some notable examples and discuss the emerging concepts of their associations with other posttranscriptional gene regulation processes.

MicroRNAs MiR-218, MiR-125b, and Let-7g predict prognosis in patients with oral cavity squamous cell carcinoma

MicroRNAs (miRNAs) have a major impact on regulatory networks in human carcinogenesis. In this study, we sought to investigate the prognostic significance of miRNAs in patients with oral cavity squamous cell carcinoma (OSCC). In a discovery phase, RNA was extracted from 58 OSCC tumor samples and paired normal tissues. MiRNAs expression was evaluated with TaqMan Array Card and TaqMan MicroRNA assays. The prognostic significance of the miRNA signature identified in the discovery phase was validated by qRT-PCR in a replication set consisting of 141 formalin-fixed, paraffin-embedded (FFPE) samples. We identified a miRNA regulatory network centered on the three hub genes (SP1, MYC, and TP53) that predicted distinct clinical endpoints. Three miRNAs (miR-218, miR-125b, and let-7g) and their downstream response genes had a concordant prognostic significance on disease-free survival and disease-specific survival rates. In addition, patients with a reduced expression of miR-218, miR-125b, and let-7g have a higher risk of poor outcomes in presence of specific risk factors (p-stage III-IV, pT3-4, or pN+). Our findings indicate that specific miRNAs have prognostic significance in OSCC patients and may improve prognostic stratification over traditional risk factors.

Macros in microRNA target identification: a comparative analysis of in silico, in vitro, and in vivo approaches to microRNA target identification

MicroRNAs (miRNAs) are short RNA molecules that modulate post-transcriptional gene expression by partial or incomplete base-pairing to the complementary sequences on their target genes. Sequence-based miRNA target gene recognition enables the utilization of computational methods, which are highly informative in identifying a subset of putative miRNA targets from the genome. Subsequently, single miRNA-target gene binding is evaluated experimentally by in vitro assays to validate and quantify the transcriptional or post-transcriptional effects of miRNA-target gene interaction. Although ex vivo approaches are instructive in providing a basis for further analyses, in vivo genetic studies are critical to determine the occurrence and biological relevance of miRNA targets under physiological conditions. In the present review, we summarize the important features of each of the experimental approaches, their technical and biological limitations, and future challenges in light of the complexity of miRNA target gene recognition.

The miRNA-mediated cross-talk between transcripts provides a novel layer of posttranscriptional regulation

Endogenously expressed transcripts that are posttranscriptionally regulated by the same microRNAs (miRNAs) will, in principle, compete for the binding of their shared small noncoding RNA regulators and modulate each other's abundance. Recently, the levels of some coding as well as noncoding transcripts have indeed been found to be regulated in this way. Transcripts that engage in such regulatory interactions are referred to as competitive endogenous RNAs (ceRNAs). This novel layer of posttranscriptional regulation has been shown to contribute to diverse aspects of organismal and cellular biology, despite the number of functionally characterized ceRNAs being as yet relatively low. Importantly, increasing evidence suggests that the dysregulation of some ceRNA interactions is associated with disease etiology, most preeminently with cancer. Here we review how posttranscriptional regulation by miRNAs contributes to the cross-talk between transcripts and review examples of known ceRNAs by highlighting the features underlying their interactions and what might be their biological relevance.

Efficient computation of minimal perturbation sets in gene regulatory networks

In the last few decades, technological and experimental advancements have enabled a more precise understanding of the mode of action of drugs with respect to human cell signaling pathways and have positively influenced the design of new drug compounds. However, as the design of compounds has become increasingly target-specific, the overall effects of a drug on adjacent cellular signaling pathways remain difficult to predict because of the complexity of the interactions involved. Off-target effects of drugs are known to influence their efficacy and safety. Similarly, drugs which are more target-specific also suffer from lack of efficacy because their scope might be too limited in the context of cellular signaling. Even in situations where the signaling pathways targeted by a drug are known, the presence of point mutations in some of the components of the pathways can render a therapy ineffective in a considerable target subpopulation. Some of these issues can be addressed by predicting Minimal Intervention Sets (MIS) of elements of the signaling pathways that when perturbed give rise to a pre-defined cellular phenotype. These minimal gene perturbation sets can then be further used to screen a library of drug compounds in order to discover effective drug therapies. This manuscript describes algorithms that can be used to discover MIS in a gene regulatory network that can lead to a defined cellular phenotype. Algorithms are implemented in our Boolean modeling toolbox, GenYsis. The software binaries of GenYsis are available for download from http://www.vital-it.ch/software/genYsis/.

An integrative meta-analysis of microRNAs in hepatocellular carcinoma

We aimed to shed new light on the roles of microRNAs (miRNAs) in liver cancer using an integrative in silico bioinformatics analysis. A new protocol for target prediction and functional analysis is presented and applied to the 26 highly differentially deregulated miRNAs in hepatocellular carcinoma. This framework comprises: (1) the overlap of prediction results by four out of five target prediction tools, including TargetScan, PicTar, miRanda, DIANA-microT and miRDB (combining machine-learning, alignment, interaction energy and statistical tests in order to minimize false positives), (2) evidence from previous microarray analysis on the expression of these targets, (3) gene ontology (GO) and pathway enrichment analysis of the miRNA targets and their pathways and (4) linking these results to oncogenesis and cancer hallmarks. This yielded new insights into the roles of miRNAs in cancer hallmarks. Here we presented several key targets and hundreds of new targets that are significantly enriched in many new cancer-related hallmarks. In addition, we also revealed some known and new oncogenic pathways for liver cancer. These included the famous MAPK, TGFβ and cell cycle pathways. New insights were also provided into Wnt signaling, prostate cancer, axon guidance and oocyte meiosis pathways. These signaling and developmental pathways crosstalk to regulate stem cell transformation and implicate a role of miRNAs in hepatic stem cell deregulation and cancer development. By analyzing their complete interactome, we proposed new categorization for some of these miRNAs as either tumor-suppressors or oncomiRs with dual roles. Therefore some of these miRNAs may be addressed as therapeutic targets or used as therapeutic agents. Such dual roles thus expand the view of miRNAs as active maintainers of cellular homeostasis.

Cross-kingdom sequence similarities between human micro-RNAs and plant viruses

Micro-RNAs regulate the expression of cellular and tissue phenotypes at a post-transcriptional level through a complex process involving complementary interactions between micro-RNAs and messenger-RNAs. Similar nucleotide interactions have been shown to occur as cross-kingdom events; for example, between plant viruses and plant micro-RNAs and also between animal viruses and animal micro-RNAs. In this study, this view is expanded to look for cross-kingdom similarities between plant virus and human micro-RNA sequences. A method to identify significant nucleotoide sequence similarities between plant viruses and hsa micro-RNAs was created. Initial analyses demonstrate that plant viruses contain nucleotide sequences which exactly match the seed sequences of human micro-RNAs in both parallel and anti-parallel directions. For example, the bean common mosaic virus strain NL4 from Colombia contains sequences that match exactly the seed sequence for micro-RNA of the hsa-mir-1226 in the parallel direction, which suggests a cross-kingdom conservation. Similarly, the rice yellow stunt viral cRNA contains a sequence that is an exact match in the anti-parallel direction to the seed sequence of hsa-micro-RNA let-7b. The functional implications of these results need to be explored. The finding of these cross-kingdom sequence similarities is a useful starting point in support of bench level investigations.

A quantitative method to identify microRNAs targeting a messenger RNA using a 3'UTR RNA affinity technique

The identification of specific microRNAs (miRNAs) that target a given messenger RNA (mRNA) is essential for studies in gene regulation, but the available bioinformatic software programs are often unreliable. We have developed a unique experimental miRNA affinity assay whereby a 3'UTR RNA is end-labeled with biotin, immobilized, and then used as a bait sequence for affinity pull-down of miRNAs. After washes and release, cloning and sequencing identify the miRNAs. Binding affinity is quantitated by quantitative polymerase chain reaction (qPCR), comparing released and original input concentrations. As an initial demonstration, the TCF8/ZEB1 mRNA affinity pull-down yielded miR-200 family member miRs in the majority of clones, and binding affinity was approximately 100%; virtually all copies of miR-200c bound the immobilized mRNA transcript. For validation in cells, miR-200c strongly inhibited expression of a TCF8 luciferase reporter, native TCF8 mRNA, and protein levels, which contrasted with other recovered miRNAs with lower binding affinities. For Smad4 mRNA, miR-150 (and others) displayed a binding affinity of 39% (or less) yet did not inhibit a Smad4 reporter, native Smad4 mRNA, or protein levels. These results were not predicted by available software. This work demonstrates this miRNA binding affinity assay to be a novel yet facile experimental means of identification of miRNAs targeting a given mRNA.

c-MYC-regulated miR-23a/24-2/27a cluster promotes mammary carcinoma cell invasion and hepatic metastasis by targeting Sprouty2

Emerging evidence indicates that the miR-23a/24-2/27a cluster may possess a causal role in mammary tumorigenesis and function as a novel class of oncogenes. However, the regulatory mechanism of the miR-23a/24-2/27a cluster in mammary carcinoma cell invasion and migration is still largely unknown. We observed that the expression levels of miR-23a, miR-24-2 and miR-27a were significantly higher in breast cancer with lymph node metastasis, compared with that from patients without lymph node metastasis or normal tissue. Forced expression of the miR-23a/24-2/27a cluster promoted mammary carcinoma cell migration, invasion, and hepatic metastasis, through targeting Sprouty2 (SPRY2) and consequent activation of p44/42 MAPK. Epidermal growth factor induced the expression of the transcription factor c-MYC, which promoted the expression of mature miR-23a, miR-24-2, and miR-27a and subsequently decreased expression of SPRY2 and activated p44/42 MAPK to promote mammary carcinoma cell migration and invasion. We therefore suggest a novel link between epidermal growth factor and the miR-23a/24-2/27a cluster via the regulation of c-MYC, providing the potential for the miR-23a/24-2/27a cluster to be used as biomarker in the diagnosis and/or treatment of breast cancer.

Predictive Dynamical Modelling MicroRNAs Role in Complex Networks

The aim of this chapter is to give an extended analytical consideration of mathematical modelling of the microRNA role in cancer networks. For this purpose, ordinary and partial differential equations are used for synthesizing and analyzing the models of gene, microRNAs and mRNAs concentration alterations as time-dependent variables related by functional and differential relations. The architecture of the models and the definitions of their components are inspired by the qualitative theory of differential equations. This chapter’s analysis shows that it is able to ensure the authenticity and validity of the following qualitative conclusions: (a) the rates of protein production decrease with the increasing constant production rate of microRNA at microRNA-mediated target regulation on mRNAs; (b) time delay has a stabilizing role in the interaction between the miRNA-17-92 cluster and the transcription factors E2F and Myc.

Deep sequencing and genome-wide analysis reveals the expansion of MicroRNA genes in the gall midge Mayetiola destructor

BACKGROUND

MicroRNAs (miRNAs) are small non-coding RNAs that play critical roles in regulating post transcriptional gene expression. Gall midges encompass a large group of insects that are of economic importance and also possess fascinating biological traits. The gall midge Mayetiola destructor, commonly known as the Hessian fly, is a destructive pest of wheat and model organism for studying gall midge biology and insect - host plant interactions.

RESULTS

In this study, we systematically analyzed miRNAs from the Hessian fly. Deep-sequencing a Hessian fly larval transcriptome led to the identification of 89 miRNA species that are either identical or very similar to known miRNAs from other insects, and 184 novel miRNAs that have not been reported from other species. A genome-wide search through a draft Hessian fly genome sequence identified a total of 611 putative miRNA-encoding genes based on sequence similarity and the existence of a stem-loop structure for miRNA precursors. Analysis of the 611 putative genes revealed a striking feature: the dramatic expansion of several miRNA gene families. The largest family contained 91 genes that encoded 20 different miRNAs. Microarray analyses revealed the expression of miRNA genes was strictly regulated during Hessian fly larval development and abundance of many miRNA genes were affected by host genotypes.

CONCLUSION

The identification of a large number of miRNAs for the first time from a gall midge provides a foundation for further studies of miRNA functions in gall midge biology and behavior. The dramatic expansion of identical or similar miRNAs provides a unique system to study functional relations among miRNA iso-genes as well as changes in sequence specificity due to small changes in miRNAs and in their mRNA targets. These results may also facilitate the identification of miRNA genes for potential pest control through transgenic approaches.

Finding quasi-modules of human and viral miRNAs: a case study of human cytomegalovirus (HCMV)

Background

MicroRNAs (miRNAs) are important regulators of gene expression encoded by a variety of organisms, including viruses. Although the function of most of the viral miRNAs is currently unknown, there is evidence that both viral and host miRNAs contribute to the interactions between viruses and their hosts. miRNAs constitute a complex combinatorial network, where one miRNA may target many genes and one gene may be targeted by multiple miRNAs. In particular, viral and host miRNAs may also have mutual target genes. Based on published evidence linking viral and host miRNAs there are three modes of mutual regulation: competing, cooperating, and compensating modes.

Results

In this paper we explore the compensating mode of mutual regulation upon Human Cytomegalovirus (HCMV) infection, when host miRNAs are down regulated and viral miRNAs compensate by mimicking their function. To achieve this, we develop a new algorithm which finds groups, called quasi-modules, of viral and host miRNAs and their mutual target genes, and use a new host miRNA expression data for HCMV-infected and uninfected cells. For two of the reported quasi-modules, supporting evidence from biological and medical literature is provided.

Conclusions

The modules found by our method may advance the understanding of the role of miRNAs in host-viral interactions, and the genes in these modules may serve as candidates for further experimental validation.

Identifying miRNAs, targets and functions

microRNAs (miRNAs) are small endogenous non-coding RNAs that function as the universal specificity factors in post-transcriptional gene silencing. Discovering miRNAs, identifying their targets and further inferring miRNA functions have been a critical strategy for understanding normal biological processes of miRNAs and their roles in the development of disease. In this review, we focus on computational methods of inferring miRNA functions, including miRNA functional annotation and inferring miRNA regulatory modules, by integrating heterogeneous data sources. We also briefly introduce the research in miRNA discovery and miRNA-target identification with an emphasis on the challenges to computational biology.

One decade of development and evolution of microRNA target prediction algorithms

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs (miRNAs). The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mechanisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA–mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computational algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of computational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future directions.

Modulation of immune responses following solid organ transplantation by microRNA

Organ transplantation, an accepted treatment for end stage organ failure, is often complicated by allograft rejection and disease recurrence. In this review we will discuss the potential role of microRNAs in allograft immunity especially leading to rejection of the transplanted organ. microRNAs (miRNAs), originally identified in C. elegans, are short non-coding 21-24 nucleotide sequences that bind to its complementary sequences in functional messenger RNAs and inhibits post-translational processes through RNA duplex formation resulting in gene silencing (Lau et al., 2001). Gene specific translational silencing by miRNAs regulates pathways for immune responses such as development of innate immunity, inflammation, T-cell and B-cell differentiation and signaling that are implicated in various stages of allograft rejection. miRNAs also play a role in development of post-transplant complicacies like fibrosis, cirrhosis, carcinogenesis often leading to graft loss and poor patient outcome. Recent advancements in the methods for detecting and quantifying miRNA in tissue biopsies, as well as in serum and urine samples, has led to identification of specific miRNA signatures in patients with allograft rejection and have been utilized to predict allograft status and survival. Therefore, miRNAs play a significant role in post-transplant events including allograft rejection, disease recurrence and tumor development impacting patient outcome.

Computational identification and experimental validation of microRNAs binding to the Alzheimer-related gene ADAM10

Background

MicroRNAs (miRNAs) are post-transcriptional regulators involved in numerous biological processes including the pathogenesis of Alzheimer’s disease (AD). A key gene of AD, ADAM10, controls the proteolytic processing of APP and the formation of the amyloid plaques and is known to be regulated by miRNA in hepatic cancer cell lines. To predict miRNAs regulating ADAM10 expression concerning AD, we developed a computational approach.

Methods

MiRNA binding sites in the human ADAM10 3' untranslated region were predicted using the RNA22, RNAhybrid and miRanda programs and ranked by specific selection criteria with respect to AD such as differential regulation in AD patients and tissue-specific expression. Furthermore, target genes of miR-103, miR-107 and miR-1306 were derived from six publicly available miRNA target site prediction databases. Only target genes predicted in at least four out of six databases in the case of miR-103 and miR-107 were compared to genes listed in the AlzGene database including genes possibly involved in AD. In addition, the target genes were used for Gene Ontology analysis and literature mining. Finally, we used a luciferase assay to verify the potential effect of these three miRNAs on ADAM10 3'UTR in SH-SY5Y cells.

Results

Eleven miRNAs were selected, which have evolutionary conserved binding sites. Three of them (miR-103, miR-107, miR-1306) were further analysed as they are linked to AD and most strictly conserved between different species. Predicted target genes of miR-103 (p-value = 0.0065) and miR-107 (p-value = 0.0009) showed significant overlap with the AlzGene database except for miR-1306. Interactions between miR-103 and miR-107 to genes were revealed playing a role in processes leading to AD. ADAM10 expression in the reporter assay was reduced by miR-1306 (28%), miR-103 (45%) and miR-107 (52%).

Conclusions

Our approach shows the requirement of incorporating specific, disease-associated selection criteria into the prediction process to reduce the amount of false positive predictions. In summary, our method identified three miRNAs strongly suggested to be involved in AD, which possibly regulate ADAM10 expression and hence offer possibilities for the development of therapeutic treatments of AD.

MiR-200c regulates Noxa expression and sensitivity to proteasomal inhibitors

The pro-apoptotic p53 target Noxa is a BH3-only protein that antagonizes the function of selected anti-apoptotic Bcl-2 family members. While much is known regarding the transcriptional regulation of Noxa, its posttranscriptional regulation remains relatively unstudied. In this study, we therefore investigated whether Noxa is regulated by microRNAs. Using a screen combining luciferase reporters, bioinformatic target prediction analysis and microRNA expression profiling, we identified miR-200c as a negative regulator of Noxa expression. MiR-200c was shown to repress basal expression of Noxa, as well as Noxa expression induced by various stimuli, including proteasomal inhibition. Luciferase reporter experiments furthermore defined one miR-200c target site in the Noxa 3′UTR that is essential for this direct regulation. In spite of the miR-200c:Noxa interaction, miR-200c overexpression led to increased sensitivity to the clinically used proteasomal inhibitor bortezomib in several cell lines. This apparently contradictory finding was reconciled by the fact that in cells devoid of Noxa expression, miR-200c overexpression had an even more pronounced positive effect on apoptosis induced by proteasomal inhibition. Together, our data define miR-200c as a potentiator of bortezomib-induced cell death. At the same time, we show that miR-200c is a novel negative regulator of the pro-apoptotic Bcl-2 family member Noxa.

MicroRNA expression is down-regulated and reorganized in prefrontal cortex of depressed suicide subjects

Background

Recent studies suggest that alterations in expression of genes, including those which regulate neural and structural plasticity, may be crucial in the pathogenesis of depression. MicroRNAs (miRNAs) are newly discovered regulators of gene expression that have recently been implicated in a variety of human diseases, including neuropsychiatric diseases.

Methodology/Principal Findings

The present study was undertaken to examine whether the miRNA network is altered in the brain of depressed suicide subjects. Expression of miRNAs was measured in prefrontal cortex (Brodmann Area 9) of antidepressant-free depressed suicide (n = 18) and well-matched non-psychiatric control subjects (n = 17) using multiplex RT-PCR plates. We found that overall miRNA expression was significantly and globally down-regulated in prefrontal cortex of depressed suicide subjects. Using individual tests of statistical significance, 21 miRNAs were significantly decreased at p = 0.05 or better. Many of the down-regulated miRNAs were encoded at nearby chromosomal loci, shared motifs within the 5′-seeds, and shared putative mRNA targets, several of which have been implicated in depression. In addition, a set of 29 miRNAs, whose expression was not pairwise correlated in the normal controls, showed a high degree of co-regulation across individuals in the depressed suicide group.

Conclusions/Significance

The findings show widespread changes in miRNA expression that are likely to participate in pathogenesis of major depression and/or suicide. Further studies are needed to identify whether the miRNA changes lead to altered expression of prefrontal cortex mRNAs, either directly (by acting as miRNA targets) or indirectly (e.g., by affecting transcription factors).

Integrating post-transcriptional regulation into the embryonic stem cell gene regulatory network

Stem cell behavior is orchestrated as a multilayered, concert of gene regulatory mechanisms collectively referred to as the gene regulatory network (GRN). Via cooperative mechanisms, transcriptional, epigenetic, and post-transcriptional regulators activate and repress gene expression to finely regulate stem cell self-renewal and commitment. Due to their tractability, embryonic stem cells (ESCs) serve as the model stem cell to dissect the complexities of the GRN, and discern its relation to stem cell fate. By way of high-throughput genomic analysis, targets of individual gene regulators have been established in ESCs. The compilation of these discrete networks has revealed convergent, multi-dimensional gene regulatory mechanisms involving transcription factors, epigenetic modifiers, non-coding RNA (ncRNA), and RNA-binding proteins. Here we highlight the seminal genomic studies that have shaped our understanding of the ESC GRN and describe alternate post-transcriptional gene regulatory mechanisms that require in depth analyses to draft networks that fully model ESC behavior.

Exploiting microRNAs for cell engineering and therapy

MicroRNAs (miRNAs) form a large class of non-coding RNAs that function in repression of gene expression in eukaryotes. By recognizing short stretches of nucleotides within the untranslated regions of mRNAs, miRNAs recruit partner proteins to individual transcripts, leading to mRNA cleavage or hindering of translation. Bioinformatic predictions and a wealth of data from wet laboratory studies indicate that miRNAs control expression of a large proportion of protein-coding genes, implying involvement of miRNAs in regulation of most biologic processes. In this review we discuss the biology of miRNAs and present examples of how manipulation of miRNA expression or activity can be exploited to attain the desired phenotypic traits in cell engineering as well as achieve therapeutic outcomes in treatment of a diverse set of diseases.

An overview of microRNA methods: expression profiling and target identification

MicroRNAs (miRNAs) are small, single-stranded RNA molecules encoded by genes that are transcribed from DNA but not translated into protein (noncoding RNA). The ability of miRNA to regulate the expression of, as yet, an unknown quantity of targets has recently become an area of huge interest to researchers studying many different areas in many species. Identifying miRNA targets provides functional insights and strategies for therapy. Furthermore, the recent advent of high-throughput methods for profiling miRNA expression and for the identification of miRNA targets has ushered in a new era in the research of gene regulation. miRNA profiling further adds a new dimension of information for the molecular profiling of disease. Summarized herein are the methods used to query the expression of miRNAs at both an individual and global level. We have also described modern computational approaches to identifying miRNA target transcripts.