Framework for microRNA variant annotation and prioritization using human population and disease datasets

iModEst: disentangling -omic impacts on gene expression variation across genes and tissues

Many regulatory factors impact the expression of individual genes including, but not limited, to microRNA, long non-coding RNA (lncRNA), transcription factors (TFs), cis-methylation, copy number variation (CNV), and single-nucleotide polymorphisms (SNPs). While each mechanism can influence gene expression substantially, the relative importance of each mechanism at the level of individual genes and tissues is poorly understood. Here, we present the integrative Models of Estimated gene expression (iModEst), which details the relative contribution of different regulators to the gene expression of 16,000 genes and 21 tissues within The Cancer Genome Atlas (TCGA). Specifically, we derive predictive models of gene expression using tumour data and test their predictive accuracy in cancerous and tumour-adjacent tissues. Our models can explain up to 70% of the variance in gene expression across 43% of the genes within both tumour and tumour-adjacent tissues. We confirm that TF expression best predicts gene expression in both tumour and tumour-adjacent tissue whereas methylation predictive models in tumour tissues does not transfer well to tumour adjacent tissues. We find new patterns and recapitulate previously reported relationships between regulator and gene-expression, such as CNV-predicted FGFR2 expression and SNP-predicted TP63 expression. Together, iModEst offers an interactive, comprehensive atlas of individual regulator-gene-tissue expression relationships as well as relationships between regulators.

In silico prioritisation of microRNA-associated common variants in multiple sclerosis

BACKGROUND

Genome-wide association studies (GWAS) have highlighted over 200 autosomal variants associated with multiple sclerosis (MS). However, variants in non-coding regions such as those encoding microRNAs have not been explored thoroughly, despite strong evidence of microRNA dysregulation in MS patients and model organisms. This study explores the effect of microRNA-associated variants in MS, through the largest publicly available GWAS, which involved 47,429 MS cases and 68,374 controls.

METHODS

We identified SNPs within the coordinates of microRNAs, ± 5-kb microRNA flanking regions and predicted 3'UTR target-binding sites using miRBase v22, TargetScan 7.0 RNA22 v2.0 and dbSNP v151. We established the subset of microRNA-associated SNPs which were tested in the summary statistics of the largest MS GWAS by intersecting these datasets. Next, we prioritised those microRNA-associated SNPs which are among known MS susceptibility SNPs, are in strong linkage disequilibrium with the former or meet a microRNA-specific Bonferroni-corrected threshold. Finally, we predicted the effects of those prioritised SNPs on their microRNAs and 3'UTR target-binding sites using TargetScan v7.0, miRVaS and ADmiRE.

RESULTS

We have identified 30 candidate microRNA-associated variants which meet at least one of our prioritisation criteria. Among these, we highlighted one microRNA variant rs1414273 (MIR548AC) and four 3'UTR microRNA-binding site variants within SLC2A4RG (rs6742), CD27 (rs1059501), MMEL1 (rs881640) and BCL2L13 (rs2587100). We determined changes to the predicted microRNA stability and binding site recognition of these microRNA and target sites.

CONCLUSIONS

We have systematically examined the functional, structural and regulatory effects of candidate MS variants among microRNAs and 3'UTR targets. This analysis allowed us to identify candidate microRNA-associated MS SNPs and highlights the value of prioritising non-coding RNA variation in GWAS. These candidate SNPs could influence microRNA regulation in MS patients. Our study is the first thorough investigation of both microRNA and 3'UTR target-binding site variation in multiple sclerosis using GWAS summary statistics.

MicroRNA Regulatory Network Analysis Using miRNet 2.0

MicroRNAs exert their effects in the context of gene regulatory networks. The recent development of high-throughput experimental approaches and the growing availability of gene expression data have permitted comprehensive functional studies of miRNAs. However, the data interpretation is often challenging due to the fact that miRNAs not only act cooperatively with other miRNAs but also participate in complex networks by interacting with other functional elements, including non-coding RNAs or transcription factors that often have extensive effects on cell biology. This chapter provides detailed practical procedures on how to use miRNet 2.0 ( https://www.mirnet.ca ) to perform miRNA regulatory network analytics to gain functional insights.

MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders

Autism spectrum disorder (ASD) is a childhood neurodevelopmental disorder with a complex and heterogeneous genetic etiology. MicroRNA (miRNA), a class of small non-coding RNAs, could regulate ASD risk genes post-transcriptionally and affect broad molecular pathways related to ASD and associated disorders. Using whole-genome sequencing, we analyzed 272 samples in 73 families in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Families with at least one ASD patient were recruited and were further assessed for language impairment, reading impairment, and other associated phenotypes. A total of 5104 miRNA variants and 1,181,148 3' untranslated region (3' UTR) variants were identified in the dataset. After applying several filtering criteria, including population allele frequency, brain expression, miRNA functional regions, and inheritance patterns, we identified high-confidence variants in five brain-expressed miRNAs (targeting 326 genes) and 3' UTR miRNA target regions of 152 genes. Some genes, such as SCP2 and UCGC, were identified in multiple families. Using Gene Ontology overrepresentation analysis and protein-protein interaction network analysis, we identified clusters of genes and pathways that are important for neurodevelopment. The miRNAs and miRNA target genes identified in this study are potentially involved in neurodevelopmental disorders and should be considered for further functional studies.

OmicsNet 2.0: a web-based platform for multi-omics integration and network visual analytics

Researchers are increasingly seeking to interpret molecular data within a multi-omics context to gain a more comprehensive picture of their study system. OmicsNet (www.omicsnet.ca) is a web-based tool developed to allow users to easily build, visualize, and analyze multi-omics networks to study rich relationships among lists of ‘omics features of interest. Three major improvements have been introduced in OmicsNet 2.0, which include: (i) enhanced network visual analytics with eleven 2D graph layout options and a novel 3D module layout; (ii) support for three new ‘omics types: single nucleotide polymorphism (SNP) list from genetic variation studies; taxon list from microbiome profiling studies, as well as liquid chromatography–mass spectrometry (LC–MS) peaks from untargeted metabolomics; and (iii) measures to improve research reproducibility by coupling R command history with the release of the companion OmicsNetR package, and generation of persistent links to share interactive network views. We performed a case study using the multi-omics data obtained from a recent large-scale investigation on inflammatory bowel disease (IBD) and demonstrated that OmicsNet was able to quickly create meaningful multi-omics context to facilitate hypothesis generation and mechanistic insights.

MiRLog and dbmiR: prioritization and functional annotation tools to study human microRNA sequence variants

The recent identification of noncoding variants with pathogenic effects suggests that these variations could underlie a significant number of undiagnosed cases. Several computational methods have been developed to predict the functional impact of noncoding variants, but they exhibit only partial concordance and are not integrated with functional annotation resources, making the interpretation of these variants still challenging. MicroRNAs (miRNAs) are small noncoding RNA molecules that act as fine regulators of gene expression and play crucial functions in several biological processes, such as cell proliferation and differentiation. An increasing number of studies demonstrate a significant impact of miRNA single nucleotide variants (SNVs) both in Mendelian diseases and complex traits. To predict the functional effect of miRNA SNVs, we implemented a new meta‐predictor, MiRLog, and we integrated it into a comprehensive database, dbmiR, which includes a precompiled list of all possible miRNA allelic SNVs, providing their biological annotations at nucleotide and miRNA levels. MiRLog and dbmiR were used to explore the genetic variability of miRNAs in 15,708 human genomes included in the gnomAD project, finding several ultra‐rare SNVs with a potentially deleterious effect on miRNA biogenesis and function representing putative contributors to human phenotypes.

Analysis of DNA variants in miRNAs and miRNA 3'UTR binding sites in female infertility patients

Early human embryogenesis relies on maternal gene products accumulated during oocyte growth and maturation, until around day-3 post-fertilization when human zygotic genome activation occurs. The maternal-to-zygotic transition (MZT) is a tightly coordinated process of selective maternal transcript clearance and new zygotic transcript production. If MZT is disrupted, it will lead to developmental arrest and pregnancy loss. It is well established that microRNA (miRNA) mutations disrupt regulation of their target transcripts. We hypothesize that some cases of embryonic arrest and pregnancy loss could be explained by the mutations in the maternal genome that affect miRNA-target transcript pairs. To this end, we examined mutations within miRNAs or miRNA binding sites in the 3' untranslated regions (3'UTR) of target transcripts. Using whole-exome sequencing data from 178 women undergoing in vitro fertilization (IVF) procedures, we identified 1197 variants in miRNA genes, including 93 single nucleotide variants (SNVs) and 19 small insertions/deletions (INDELs) within the seed region of 100 miRNAs. Eight miRNA seed-region variants were significantly enriched among our patients when compared to a normal population. Within predicted 3'UTR miRNA binding sites, we identified 7393 SNVs and 1488 INDELs. Between our patients and a normal population, 52 SNVs and 30 INDELs showed significant association in the single-variant testing, whereas 51 genes showed significant association in the gene-burden analysis for genes that are expressed in preimplantation embryos. Interestingly, we found that many genes with disrupted 3'UTR miRNA binding sites follow gene expression patterns resembling MZT. In addition, some of these variants showed dramatic allele frequency difference between the patient and the normal group, offering potential utility as biomarkers for screening patients prior to IVF procedures.

A pan-cancer atlas of somatic mutations in miRNA biogenesis genes

It is a well-known and intensively studied phenomenon that the levels of many miRNAs are differentiated in cancer. miRNA biogenesis and functional expression are complex processes orchestrated by many proteins cumulatively called miRNA biogenesis proteins. To characterize cancer somatic mutations in the miRNA biogenesis genes and investigate their potential impact on the levels of miRNAs, we analyzed whole-exome sequencing datasets of over 10 000 cancer/normal sample pairs deposited within the TCGA repository. We identified and characterized over 3600 somatic mutations in 29 miRNA biogenesis genes and showed that some of the genes are overmutated in specific cancers and/or have recurrent hotspot mutations (e.g. SMAD4 in PAAD, COAD and READ; DICER1 in UCEC; PRKRA in OV and LIN28B in SKCM). We identified a list of miRNAs whose level is affected by particular types of mutations in either SMAD4, SMAD2 or DICER1 and showed that hotspot mutations in the RNase domains in DICER1 not only decrease the level of 5p-miRNAs but also increase the level of 3p-miRNAs, including many well-known cancer-related miRNAs. We also showed an association of the mutations with patient survival. Eventually, we created an atlas/compendium of miRNA biogenesis alterations providing a useful resource for different aspects of biomedical research.

MicroRNAs Regulating Autophagy in Neurodegeneration

Social and economic impacts of neurodegenerative diseases (NDs) become more prominent in our constantly aging population. Currently, due to the lack of knowledge about the aetiology of most NDs, only symptomatic treatment is available for patients. Hence, researchers and clinicians are in need of solid studies on pathological mechanisms of NDs. Autophagy promotes degradation of pathogenic proteins in NDs, while microRNAs post-transcriptionally regulate multiple signalling networks including autophagy. This chapter will critically discuss current research advancements in the area of microRNAs regulating autophagy in NDs. Moreover, we will introduce basic strategies and techniques used in microRNA research. Delineation of the mechanisms contributing to NDs will result in development of better approaches for their early diagnosis and effective treatment.

MiRNA and LncRNA as Potential Biomarkers in Triple-Negative Breast Cancer: A Review

Noncoding RNAs (ncRNAs) include a diverse range of RNA species, including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). MiRNAs, ncRNAs of approximately 19-25 nucleotides in length, are involved in gene expression regulation either via degradation or silencing of the messenger RNAs (mRNAs) and have roles in multiple biological processes, including cell proliferation, differentiation, migration, angiogenesis, and apoptosis. LncRNAs, which are longer than 200 nucleotides, comprise one of the largest and most heterogeneous RNA families. LncRNAs can activate or repress gene expression through various mechanisms, acting alone or in combination with miRNAs and other molecules as part of various pathways. Until recently, most research has focused on individual lncRNA and miRNA functions as regulators, and there is limited available data on ncRNA interactions relating to the tumor growth, metastasis, and therapy of cancer, acting either on mRNA alone or as competing endogenous RNA (ceRNA) networks. Triple-negative breast cancer (TNBC) represents approximately 10%-20% of all breast cancers (BCs) and is highly heterogenous and more aggressive than other types of BC, for which current targeted treatment options include hormonotherapy, PARP inhibitors, and immunotherapy; however, no targeted therapies for TNBC are available, partly because of a lack of predictive biomarkers. With advances in proteomics, new evidence has emerged demonstrating the implications of dysregulation of ncRNAs in TNBC etiology. Here, we review the roles of lncRNAs and miRNAs implicated in TNBC, including their interactions and regulatory networks. Our synthesis provides insight into the mechanisms involved in TNBC progression and has potential to aid the discovery of new diagnostic and therapeutic strategies.

Pan-cancer analysis of somatic mutations in miRNA genes

Background

miRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied.

Methods

Here, based on the analysis of large genomic datasets, mostly the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we undertook an analysis of somatic mutations in miRNA genes.

Findings

We identified and characterized over 10,000 somatic mutations and showed that some of the miRNA genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival.

Interpretation

Our study is the first comprehensive Pan-Cancer study of cancer somatic mutations in miRNA genes. It may help to understand the consequences of mutations in miRNA genes and the identification of miRNA functional mutations. The results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.

Funding

This work was supported by research grants from the Polish National Science Centre 2016/22/A/NZ2/00184 and 2015/17/N/NZ3/03629.

miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology

miRNet is an easy-to-use, web-based platform designed to help elucidate microRNA (miRNA) functions by integrating users' data with existing knowledge via network-based visual analytics. Since its first release in 2016, miRNet has been accessed by >20 000 researchers worldwide, with ∼100 users on a daily basis. While version 1.0 was focused primarily on miRNA-target gene interactions, it has become clear that in order to obtain a global view of miRNA functions, it is necessary to bring other important players into the context during analysis. Driven by this concept, in miRNet version 2.0, we have (i) added support for transcription factors (TFs) and single nucleotide polymorphisms (SNPs) that affect miRNAs, miRNA-binding sites or target genes, whilst also greatly increased (>5-fold) the underlying knowledgebases of miRNAs, ncRNAs and disease associations; (ii) implemented new functions to allow creation and visual exploration of multipartite networks, with enhanced support for in situ functional analysis and (iii) revamped the web interface, optimized the workflow, and introduced microservices and web application programming interface (API) to sustain high-performance, real-time data analysis. The underlying R package is also released in tandem with version 2.0 to allow more flexible data analysis for R programmers. The miRNet 2.0 website is freely available at https://www.mirnet.ca.

Human Brain Shows Recurrent Non-Canonical MicroRNA Editing Events Enriched for Seed Sequence with Possible Functional Consequence

RNA editing is a post-transcriptional modification, which can provide tissue-specific functions not encoded in DNA. Adenosine-to-inosine is the predominant editing event and, along with cytosine-to-uracil changes, constitutes canonical editing. The rest is non-canonical editing. In this study, we have analysed non-canonical editing of microRNAs in the human brain. We have performed massively parallel small RNA sequencing of frontal cortex (FC) and corpus callosum (CC) pairs from nine normal individuals (post-mortem). We found 113 and 90 unique non-canonical editing events in FC and CC samples, respectively. More than 70% of events were in the miRNA seed sequence—implicating an altered set of target mRNAs and possibly resulting in a functional consequence. Up to 15% of these events were recurring and found in at least three samples, also supporting the biological relevance of such variations. Two specific sequence variations, C-to-A and G-to-U, accounted for over 80% of non-canonical miRNA editing events—and revealed preferred sequence motifs. Our study is one of the first reporting non-canonical editing in miRNAs in the human brain. Our results implicate miRNA non-canonical editing as one of the contributing factors towards transcriptomic diversity in the human brain.

Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Common Solid Tumors: Focus on Lung, Breast, Prostate Cancers, and Osteosarcoma

An early cancer diagnosis is essential to treat and manage patients, but it is difficult to achieve this goal due to the still too low specificity and sensitivity of classical methods (imaging, actual biomarkers), together with the high invasiveness of tissue biopsies. The discovery of novel, reliable, and easily collectable cancer markers is a topic of interest, with human biofluids, especially blood, as important sources of minimal invasive biomarkers such as circulating microRNAs (miRNAs), the most promising. MiRNAs are small non-coding RNAs and known epigenetic modulators of gene expression, with specific roles in cancer development/progression, which are next to be implemented in the clinical routine as biomarkers for early diagnosis and the efficient monitoring of tumor progression and treatment response. Unfortunately, several issues regarding their validation process are still to be resolved. In this review, updated findings specifically focused on the clinical relevance of circulating miRNAs as prognostic and diagnostic biomarkers for the most prevalent cancer types (breast, lung, and prostate cancers in adults, and osteosarcoma in children) are described. In addition, deep analysis of pre-analytical, analytical, and post-analytical issues still affecting the circulation of miRNAs' validation process and routine implementation is included.

Somatic Mutations in miRNA Genes in Lung Cancer-Potential Functional Consequences of Non-Coding Sequence Variants

A growing body of evidence indicates that miRNAs may either drive or suppress oncogenesis. However, little is known about somatic mutations in miRNA genes. To determine the frequency and potential consequences of miRNA gene mutations, we analyzed whole exome sequencing datasets of 569 lung adenocarcinoma (LUAD) and 597 lung squamous cell carcinoma (LUSC) samples generated in The Cancer Genome Atlas (TCGA) project. Altogether, we identified 1091 somatic sequence variants affecting 522 different miRNA genes and showed that half of all cancers had at least one such somatic variant/mutation. These sequence variants occurred in most crucial parts of miRNA precursors, including mature miRNA and seed sequences. Due to our findings, we hypothesize that seed mutations may affect miRNA:target interactions, drastically changing the pool of predicted targets. Mutations may also affect miRNA biogenesis by changing the structure of miRNA precursors, DROSHA and DICER cleavage sites, and regulatory sequence/structure motifs. We identified 10 significantly overmutated hotspot miRNA genes, including the miR-379 gene in LUAD enriched in mutations in the mature miRNA and regulatory sequences. The occurrence of mutations in the hotspot miRNA genes was also shown experimentally. We present a comprehensive analysis of somatic variants in miRNA genes and show that some of these genes are mutational hotspots, suggesting their potential role in cancer.