Isoform-level microRNA-155 target prediction using RNA-seq

Overview of Computational and Experimental Methods to Identify Tissue-Specific MicroRNA Targets

As ubiquitous posttranscriptional regulators of gene expression, microRNAs (miRNAs) play key roles in cell physiology and function across taxa. In the last two decades, we have gained a good understanding about miRNA biogenesis pathways, modes of action, and consequences of miRNA-mediated gene regulation. More recently, research has focused on exploring causes for miRNA dysregulation, miRNA-mediated crosstalk between genes and signaling pathways, and the role of miRNAs in disease.This chapter discusses methods for the identification of miRNA-target interactions and causes for tissue-specific miRNA-target regulation. Computational approaches for predicting miRNA target sites and assessing tissue-specific target regulation are discussed. Moreover, there is an emphasis on features that affect miRNA target recognition and how high-throughput sequencing protocols can help in assessing miRNA-mediated gene regulation on a genome-wide scale. In addition, this chapter introduces some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA-target interactions.

Expression of SARS-CoV-2 entry factors, electrolyte, and mineral transporters in different mouse intestinal epithelial cell types

Angiotensin-converting enzyme 2 (ACE2) and transmembrane proteases (TMPRSS) are multifunctional proteins required for SARS-CoV-2 infection or for amino acid (AA) transport, and are abundantly expressed in mammalian small intestine, but the identity of the intestinal cell type(s) and sites of expression are unclear. Here we determined expression of SARS-CoV-2 entry factors in different cell types and then compared it to that of representative AA, electrolyte, and mineral transporters. We tested the hypothesis that SARS-CoV-2, AA, electrolyte, and mineral transporters are expressed heterogeneously in different intestinal cell types by making mouse enteroids enriched in enterocytes (ENT), goblet (GOB), Paneth (PAN), or stem (ISC) cells. Interestingly, the expression of ACE2 was apical and modestly greater in ENT, the same pattern observed for its associated AA transporters B0 AT1 and SIT1. TMPRSS2 and TMPRSS4 were more highly expressed in crypt-residing ISC. Expression of electrolyte transporters was dramatically heterogeneous. DRA, NBCe1, and NHE3 were greatest in ENT, while those of CFTR and NKCC1 that play important roles in secretory diarrhea, were mainly expressed in ISC and PAN that also displayed immunohistochemically abundant basolateral NKCC1. Intestinal iron transporters were generally expressed higher in ENT and GOB, while calcium transporters were expressed mainly in PAN. Heterogeneous expression of its entry factors suggests that the ability of SARS-CoV-2 to infect the intestine may vary with cell type. Parallel cell-type expression patterns of ACE2 with B0 AT1 and SIT1 provides further evidence of ACE2's multifunctional properties and importance in AA absorption.

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.

Relative Abundance of Transcripts ( RATs): Identifying differential isoform abundance from RNA-seq

The biological importance of changes in RNA expression is reflected by the wide variety of tools available to characterise these changes from RNA-seq data. Several tools exist for detecting differential transcript isoform usage (DTU) from aligned or assembled RNA-seq data, but few exist for DTU detection from alignment-free RNA-seq quantifications. We present the RATs, an R package that identifies DTU transcriptome-wide directly from transcript abundance estimates. RATs is unique in applying bootstrapping to estimate the reliability of detected DTU events and shows good performance at all replication levels (median false positive fraction < 0.05). We compare RATs to two existing DTU tools, DRIM-Seq & SUPPA2, using two publicly available simulated RNA-seq datasets and a published human RNA-seq dataset, in which 248 genes have been previously identified as displaying significant DTU. RATs with default threshold values on the simulated Human data has a sensitivity of 0.55, a Matthews correlation coefficient of 0.71 and a false discovery rate (FDR) of 0.04, outperforming both other tools. Applying the same thresholds for SUPPA2 results in a higher sensitivity (0.61) but poorer FDR performance (0.33). RATs and DRIM-seq use different methods for measuring DTU effect-sizes complicating the comparison of results between these tools, however, for a likelihood-ratio threshold of 30, DRIM-Seq has similar FDR performance to RATs (0.06), but worse sensitivity (0.47). These differences persist for the simulated drosophila dataset. On the published human RNA-seq dataset the greatest agreement between the tools tested is 53%, observed between RATs and SUPPA2. The bootstrapping quality filter in RATs is responsible for removing the majority of DTU events called by SUPPA2 that are not reported by RATs. All methods, including the previously published qRT-PCR of three of the 248 detected DTU events, were found to be sensitive to annotation differences between Ensembl v60 and v87.

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.

Exosomal MicroRNA Discovery in Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a common condition causing progressive visual impairment, leading to irreversible blindness. Existing diagnostic tools for AMD are limited to clinical signs in the macula and the visual assessment of the patient. The presence of circulating microRNAs (miRNAs) in the peripheral circulatory system with potential as diagnostic, prognostic and/or predictive biomarkers has been reported in a number of conditions/diseases. miRNAs are key regulators of several biological processes, and miRNA dysregulation has been linked with numerous diseases, most remarkably cancer. miRNAs have been shown to be involved in AMD pathology and several miRNAs target genes and signaling pathways were identified in relation to AMD pathogenesis. Exosomes are 50-90 nm membrane micro-vesicles (MVs), released by several cell types. Although exosomal functions are not completely understood, there is much evidence to suggest that exosomes play an essential role in cell-cell communication. They may stimulate target cells by transferring different bioactive molecules such as miRNA. Here we discuss methods to isolate exosome using serum specimens from AMD patients and miRNA profiling for the better understanding of the disease.

Inhibition of the miR-155 target NIAM phenocopies the growth promoting effect of miR-155 in B-cell lymphoma

Several studies have indicated an important role for miR-155 in the pathogenesis of B-cell lymphoma. Highly elevated levels of miR-155 were indeed observed in most B-cell lymphomas with the exception of Burkitt lymphoma (BL). However, the molecular mechanisms that underlie the oncogenic role of miR-155 in B-cell lymphoma are not well understood. To identify the miR-155 targets relevant for B-cell lymphoma, we performed RNA immunoprecipitation of Argonaute 2 in Hodgkin lymphoma (HL) cells upon miR-155 inhibition and in BL cells upon ectopic expression of miR-155. We identified 54 miR-155-specific target genes in BL cells and confirmed miR-155 targeting of DET1, NIAM, TRIM32, HOMEZ, PSIP1 and JARID2. Five of these targets are also regulated by endogenous miR-155 in HL cells. Both overexpression of miR-155 and inhibition of expression of the novel miR-155 target gene NIAM increased proliferation of BL cells. In primary B-cell lymphoma NIAM-positive cases have significant lower levels of miR-155 as compared to NIAM-negative cases, suggesting that NIAM is also regulated by miR-155 in primary B-cell lymphoma. Thus, our data indicate an oncogenic role for miR-155 in B-cell lymphoma which involves targeting the tumor suppressor NIAM.

Critical role of miR-125b in lipogenesis by targeting stearoyl-CoA desaturase-1 (SCD-1)

Alteration of gene expression tightly regulates lipogenesis. Stearoyl-CoA desaturase-1 (SCD-1), a key enzyme in lipogenesis, catalyzes the conversion of SFA to MUFA, and inhibition of its activity impairs lipid synthesis. As posttranscriptional regulators, microRNAs are involved in many pathways of lipid metabolism; however, their effect on SCD-1 has not been reported. In this study, miR-125b was identified as a potential regulator of SCD-1 using bioinformatics analysis. Here, we validated SCD-1 as the target of miR-125b using a dual luciferase assay. During adipogenesis, a synthetic mimic or inhibitor was used to overexpress or reduce the expression of miR-125b in porcine adipocytes. Overexpression of miR-125b reduced the accumulation of lipid droplets and triglycerides concentration and repressed SCD-1 protein expression and MUFA composition. The inhibitor had the reverse effect. Small interfering RNA against tested in adipocytes further proved the direct correlation between miR-125b and SCD-1. Moreover, in vivo experiments in mice showed that injection of miR-125b expression vector decreased the hepatic triglycerides concentration relative to saline. This study indicated that miR-125b regulates lipogenesis by targeting SCD-1; therefore, miR-125b might be applied in therapy of lipid metabolism disorders.

Soy Isoflavone Genistein-Mediated Downregulation of miR-155 Contributes to the Anticancer Effects of Genistein

We previously reported that dietary genistein inhibits mammary tumor growth and metastasis of the highly metastatic MDA-MB-435 cancer cells in immunocompromised mice. The purpose herein was to characterize the role of the novel oncogenic microRNA (miRNA) miR-155 in the anticancer effects of genistein in metastatic breast cancer. The effect of genistein was determined on breast cancer cell viability, apoptosis, and expression of miR-155 and its targets. At low physiologically relevant concentrations, genistein inhibits cell viability and induces apoptosis in metastatic MDA-MB-435 and Hs578t breast cancer cells, without affecting the viability of nonmetastatic MCF-7 breast cancer cells. In parallel with reduced cell viability, miR-155 is downregulated, whereas proapoptotic and anticell proliferative miR-155 targets FOXO3, PTEN, casein kinase, and p27 are upregulated in MDA-MB-435 and Hs578t cells in response to genistein treatment. However, miR-155 levels remain unchanged in response to genistein in the MCF-7 cells. Ectopic expression of miR-155 in MDA-MB-435 and Hs578t cells decreases the effects of genistein on cell viability and abrogates the effects of genistein on apoptosis and expression of proapoptotic genes. Therefore, genistein-mediated downregulation of miR-155 contributes to the anticancer effects of genistein in metastatic breast cancer.

Whole blood transcriptomic analysis to identify clinical biomarkers of drug response

Since most immunological and hematological conditions might be expected to alter whole blood gene expression, its examination can lead to insights into disease processes, and biomarkers to assess molecular phenotypes, disease states, progression and response to therapy. In this chapter we describe collection and storage of RNA from whole blood, techniques to measure gene expression, and analytical approaches to identify the dysregulated gene expression using pathway and clustering analysis, gene set enrichment, heat map approaches, and cell subset deconvolution.

A generalized dSpliceType framework to detect differential splicing and differential expression events using RNA-Seq

Transcriptomes are routinely compared in term of a list of differentially expressed genes followed by functional enrichment analysis. Due to the technology limitations of microarray, the molecular mechanisms of differential expression is poorly understood. Using RNA-seq data, we propose a generalized dSpliceType framework to systematically investigate the synergistic and antagonistic effects of differential splicing and differential expression. We applied the method to two public RNA-seq data sets and compared the transcriptomes between treatment and control conditions. The generalized dSpliceType detects and prioritizes a list of genes that are differentially expressed and/or spliced. In particular, the multivariate dSpliceType is among the fist to utilize sequential dependency of normalized base-wise read coverage signals and capture biological variability among replicates using a multivariate statistical model. We compared dSpliceType with two other methods in terms of five most common types of differential splicing events between two conditions using RNA-Seq. dSpliceType is free, available from http://dsplicetype.sourceforge.net/.

Identifying key regulatory genes in the whole blood of septic patients to monitor underlying immune dysfunctions

There is currently no reliable tool available to measure immune dysfunction in septic patients in the clinical setting. This proof-of-concept study assesses the potential of gene expression profiling of whole blood as a tool to monitor immune dysfunction in critically ill septic patients. Whole-blood samples were collected daily for up to 5 days from patients admitted to the intensive care unit with sepsis. RNA isolated from whole-blood samples was assayed on Illumina HT-12 gene expression microarrays consisting of 48,804 probes. Microarray analysis identified 3,677 genes as differentially expressed across 5 days between septic patients and healthy controls. Of the 3,677 genes, biological pathway analysis identified 86 genes significantly downregulated in the sepsis patients were present in pathways relating to immune response. These 86 genes correspond to known immune pathways implicated in sepsis, including lymphocyte depletion, reduced T-lymphocyte activation, and deficient antigen presentation. Furthermore, expression levels of these genes correlated with clinical severity, with a significantly greater degree of downregulation found in nonsurvivors compared with survivors. The results show that whole-blood gene expression analysis can capture systemic immune dysfunctions in septic patients. Our study provides an experimental basis to support further study on the use of a gene expression-based assay, to assess immunosuppression, and to guide immunotherapy in future clinical trials.

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets

High-throughput RNA sequencing (RNA-seq) has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing (NGS) analysis tools, the analysis of RNA-seq data sets poses a challenge for many biomedical researchers who are not familiar with command-line tools. Here we present RNA CoMPASS, a comprehensive RNA-seq analysis pipeline for the simultaneous analysis of transcriptomes and metatranscriptomes from diverse biological specimens. RNA CoMPASS leverages existing tools and parallel computing technology to facilitate the analysis of even very large datasets. RNA CoMPASS has a web-based graphical user interface with intrinsic queuing to control a distributed computational pipeline. RNA CoMPASS was evaluated by analyzing RNA-seq data sets from 45 B-cell samples. Twenty-two of these samples were derived from lymphoblastoid cell lines (LCLs) generated by the infection of naïve B-cells with the Epstein Barr virus (EBV), while another 23 samples were derived from Burkitt's lymphomas (BL), some of which arose in part through infection with EBV. Appropriately, RNA CoMPASS identified EBV in all LCLs and in a fraction of the BLs. Cluster analysis of the human transcriptome component of the RNA CoMPASS output clearly separated the BLs (which have a germinal center-like phenotype) from the LCLs (which have a blast-like phenotype) with evidence of activated MYC signaling and lower interferon and NF-kB signaling in the BLs. Together, this analysis illustrates the utility of RNA CoMPASS in the simultaneous analysis of transcriptome and metatranscriptome data. RNA CoMPASS is freely available at http://rnacompass.sourceforge.net/.

Methods to study splicing from high-throughput RNA sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data, which could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.

The CYP27B1 variant associated with an increased risk of autoimmune disease is underexpressed in tolerizing dendritic cells

Genome-wide association studies have identified a linkage disequilibrium (LD) block on chromosome 12 associated with multiple sclerosis (MS), type 1 diabetes and other autoimmune diseases. This block contains CYP27B1, which catalyzes the conversion of 25 vitamin D3 (VitD3) to 1,25VitD3. Fine-mapping analysis has failed to identify which of the 17 genes in this block is most associated with MS. We have previously used a functional approach to identify the causal gene. We showed that the expression of several genes in this block in whole blood is highly associated with the MS risk allele, but not CYP27B1. Here, we show that CYP27B1 is predominantly expressed in dendritic cells (DCs). Its expression in these cells is necessary for their response to VitD, which is known to upregulate pathways involved in generating a tolerogenic DC phenotype. Here, we utilize a differentiation protocol to generate inflammatory (DC1) and tolerogenic (DC2) DCs, and show that for the MS risk allele CYP27B1 is underexpressed in DCs, especially DC2s. Of the other Chr12 LD block genes expressed in these cells, only METT21B expression was as affected by the genotype. Another gene associated with autoimmune diseases, CYP24A1, catabolizes 1,25 VitD3, and is predominantly expressed in DCs, but equally between DC1s and DC2s. Overall, these data are consistent with the hypothesis that reduced VitD pathway gene upregulation in DC2s of carriers of the risk haplotype of CYP27B1 contributes to autoimmune diseases. These data support therapeutic approaches aimed at targeting VitD effects on DCs.

Detecting splicing variants in idiopathic pulmonary fibrosis from non-differentially expressed genes

Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease of unknown cause that lacks a proven therapy for altering its high mortality rate. Microarrays have been employed to investigate the pathogenesis of IPF, but are presented mostly at the gene-expression level due to technologic limitations. In as much as, alternative RNA splicing isoforms are increasingly identified as potential regulators of human diseases, including IPF, we propose a new approach with the capacity to detect splicing variants using RNA-seq data. We conducted a joint analysis of differential expression and differential splicing on annotated human genes and isoforms, and identified 122 non-differentially expressed genes with a high degree of "switch" between major and minor isoforms. Three cases with variant mechanisms for alternative splicing were validated using qRT-PCR, among the group of genes in which expression was not significantly changed at the gene level. We also identified 35 novel transcripts that were unique to the fibrotic lungs using exon-exon junction evidence, and selected a representative for qRT-PCR validation. The results of our study are likely to provide new insight into the pathogenesis of pulmonary fibrosis and may eventuate in new treatment targets.

A multi-exon-skipping detection assay reveals surprising diversity of splice isoforms of spinal muscular atrophy genes

Humans have two near identical copies of Survival Motor Neuron gene: SMN1 and SMN2. Loss of SMN1 coupled with the predominant skipping of SMN2 exon 7 causes spinal muscular atrophy (SMA), a neurodegenerative disease. SMA patient cells devoid of SMN1 provide a powerful system to examine splicing pattern of various SMN2 exons. Until now, similar system to examine splicing of SMN1 exons was unavailable. We have recently screened several patient cell lines derived from various diseases, including SMA, Alzheimer’s disease, Parkinson’s disease and Batten disease. Here we report a Batten disease cell line that lacks functional SMN2, as an ideal system to examine pre-mRNA splicing of SMN1. We employ a multiple-exon-skipping detection assay (MESDA) to capture simultaneously skipping of multiple exons. Our results show surprising diversity of splice isoforms and reveal novel splicing events that include skipping of exon 4 and co-skipping of three adjacent exons of SMN. Contrary to the general belief, MESDA captured oxidative-stress induced skipping of SMN1 exon 5 in several cell types, including non-neuronal cells. We further demonstrate that the predominant SMN2 exon 7 skipping induced by oxidative stress is modulated by a combinatorial control that includes promoter sequence, endogenous context, and the weak splice sites. We also show that an 8-mer antisense oligonucleotide blocking a recently described GC-rich sequence prevents SMN2 exon 7 skipping under the conditions of oxidative stress. Our findings bring new insight into splicing regulation of an essential housekeeping gene linked to neurodegeneration and infant mortality.

Preferential star strand biogenesis of pre-miR-24-2 targets PKC-alpha and suppresses cell survival in MCF-7 breast cancer cells

microRNAs (miRNA) are regulators of cellular pathways and alterations of normal miRNA expression levels have been shown to increase tumorigenesis. miR-24 has been demonstrated as having both tumor suppressive and oncogenic properties depending on cell context. Here, we demonstrate a possible role for pre-miR-24-2 as a tumor suppressor in the MCF-7 breast cancer cell line through the preferential processing of mature miR-24-2* over miR-24. Specifically, we show that the ectopic expression of miR-24-2* in MCF-7 breast cancer cells results in a suppression of cellular survival both in vivo and in vitro. Notably, the overexpression of miR-24-2* results in a dampening of cell survival through the targeted suppression of PKCα. In addition, a similar biological change is observed in vivo where MCF-7 cells overexpressing pre-miR-24-2 have decreased tumorigenicity and tumor incidence. Taken together our data demonstrate that when overexpressed biogenesis of the pre-miR-24-2 favors miR-24-2* in the MCF-7 breast cancer cell line and suggests a tumor suppressive role for miR-24-2* observed through the inhibition of PKCα-mediated cellular survival.