The human mitochondrial transcriptome.

The human mitochondrial genome comprises a distinct genetic system transcribed as precursor polycistronic transcripts that are subsequently cleaved to generate individual mRNAs, tRNAs, and rRNAs. Here, we provide a comprehensive analysis of the human mitochondrial transcriptome across multiple cell lines and tissues. Using directional deep sequencing and parallel analysis of RNA ends, we demonstrate wide variation in mitochondrial transcript abundance and precisely resolve transcript processing and maturation events. We identify previously undescribed transcripts, including small RNAs, and observe the enrichment of several nuclear RNAs in mitochondria. Using high-throughput in vivo DNaseI footprinting, we establish the global profile of DNA-binding protein occupancy across the mitochondrial genome at single-nucleotide resolution, revealing regulatory features at mitochondrial transcription initiation sites and functional insights into disease-associated variants. This integrated analysis of the mitochondrial transcriptome reveals unexpected complexity in the regulation, expression, and processing of mitochondrial RNA and provides a resource for future studies of mitochondrial function (accessed at http://mitochondria.matticklab.com).

RNA regulatory mechanisms controlling TGF-ß signaling and EMT in cancer.

Epithelial-mesenchymal transition (EMT) is a major contributor to metastatic progression and is prominently regulated by TGF-ß signalling. Both EMT and TGF-ß pathway components are tightly controlled by non-coding RNAs - including microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) - that collectively have major impacts on gene expression and resulting cellular states. While miRNAs are the best characterised regulators of EMT and TGF-ß signaling and the miR-200-ZEB1/2 feedback loop plays a central role, important functions for lncRNAs and circRNAs are also now emerging. This review will summarise our current understanding of the roles of non-coding RNAs in EMT and TGF-ß signaling with a focus on their functions in cancer progression.

"Crowd-control" by RNA: a pervasive theme in biology.

As we continue to find new regulatory roles for RNAs, a theme is emerging in which regulation may not be mediated through the actions of a specific RNA, as one typically thinks of a regulator and target, but rather through the collective nature of many RNAs, each contributing a small degree of the regulatory load. This mechanism has been termed "crowd-control" and may apply broadly to miRNAs and to RNAs that bind and regulate protein activity. This provides an alternative way of thinking about how RNAs can act as biological regulators and has repercussions, both for the understanding of biological systems, and for the interpretation of results in which individual members of the "crowd" can replicate the effects of the crowd when overexpressed, but are not individually significant biological regulators.

On the rules of engagement for microRNAs targeting protein coding regions.

MiRNAs post-transcriptionally repress gene expression by binding to mRNA 3'UTRs, but the extent to which they act through protein coding regions (CDS regions) is less well established. MiRNA interaction studies show a substantial proportion of binding occurs in CDS regions, however sequencing studies show much weaker effects on mRNA levels than from 3'UTR interactions, presumably due to competition from the translating ribosome. Consequently, most target prediction algorithms consider only 3'UTR interactions. However, the consequences of CDS interactions may have been underestimated, with the reporting of a novel mode of miRNA-CDS interaction requiring base pairing of the miRNA 3' end, but not the canonical seed site, leading to repression of translation with little effect on mRNA turnover. Using extensive reporter, western blotting and bioinformatic analyses, we confirm that miRNAs can indeed suppress genes through CDS-interaction in special circumstances. However, in contrast to that previously reported, we find repression requires extensive base-pairing, including of the canonical seed, but does not strictly require base pairing of the 3' miRNA terminus and is mediated through reducing mRNA levels. We conclude that suppression of endogenous genes can occur through miRNAs binding to CDS, but the requirement for extensive base-pairing likely limits the regulatory impacts to modest effects on a small subset of targets.

The landscape of alternative polyadenylation during EMT and its regulation by the RNA-binding protein Quaking.

Epithelial-mesenchymal transition (EMT) plays important roles in tumour progression and is orchestrated by dynamic changes in gene expression. While it is well established that post-transcriptional regulation plays a significant role in EMT, the extent of alternative polyadenylation (APA) during EMT has not yet been explored. Using 3' end anchored RNA sequencing, we mapped the alternative polyadenylation (APA) landscape following Transforming Growth Factor (TGF)-ß-mediated induction of EMT in human mammary epithelial cells and found APA generally causes 3'UTR lengthening during this cell state transition. Investigation of potential mediators of APA indicated the RNA-binding protein Quaking (QKI), a splicing factor induced during EMT, regulates a subset of events including the length of its own transcript. Analysis of QKI crosslinked immunoprecipitation (CLIP)-sequencing data identified the binding of QKI within 3' untranslated regions (UTRs) was enriched near cleavage and polyadenylation sites. Following QKI knockdown, APA of many transcripts is altered to produce predominantly shorter 3'UTRs associated with reduced gene expression. These findings reveal the changes in APA that occur during EMT and identify a potential role for QKI in this process.

Transcriptional and post-transcriptional control of epithelial-mesenchymal plasticity: why so many regulators?

The dynamic transition between epithelial-like and mesenchymal-like cell states has been a focus for extensive investigation for decades, reflective of the importance of Epithelial-Mesenchymal Transition (EMT) through development, in the adult, and the contributing role EMT has to pathologies including metastasis and fibrosis. Not surprisingly, regulation of the complex genetic networks that underlie EMT have been attributed to multiple transcription factors and microRNAs. What is surprising, however, are the sheer number of different regulators (hundreds of transcription factors and microRNAs) for which critical roles have been described. This review seeks not to collate these studies, but to provide a perspective on the fundamental question of whether it is really feasible that so many regulators play important roles and if so, what does this tell us about EMT and more generally, the genetic machinery that controls complex biological processes.

miR-200/375 control epithelial plasticity-associated alternative splicing by repressing the RNA-binding protein Quaking.

Members of the miR-200 family are critical gatekeepers of the epithelial state, restraining expression of pro-mesenchymal genes that drive epithelial-mesenchymal transition (EMT) and contribute to metastatic cancer progression. Here, we show that miR-200c and another epithelial-enriched miRNA, miR-375, exert widespread control of alternative splicing in cancer cells by suppressing the RNA-binding protein Quaking (QKI). During EMT, QKI-5 directly binds to and regulates hundreds of alternative splicing targets and exerts pleiotropic effects, such as increasing cell migration and invasion and restraining tumour growth, without appreciably affecting mRNA levels. QKI-5 is both necessary and sufficient to direct EMT-associated alternative splicing changes, and this splicing signature is broadly conserved across many epithelial-derived cancer types. Importantly, several actin cytoskeleton-associated genes are directly targeted by both QKI and miR-200c, revealing coordinated control of alternative splicing and mRNA abundance during EMT These findings demonstrate the existence of a miR-200/miR-375/QKI axis that impacts cancer-associated epithelial cell plasticity through widespread control of alternative splicing.

pDriver: a novel method for unravelling personalized coding and miRNA cancer drivers.

MOTIVATION: Unravelling cancer driver genes is important in cancer research. Although computational methods have been developed to identify cancer drivers, most of them detect cancer drivers at population level. However, two patients who have the same cancer type and receive the same treatment may have different outcomes because each patient has a different genome and their disease might be driven by different driver genes. Therefore new methods are being developed for discovering cancer drivers at individual level, but existing personalized methods only focus on coding drivers while microRNAs (miRNAs) have been shown to drive cancer progression as well. Thus, novel methods are required to discover both coding and miRNA cancer drivers at individual level. RESULTS: We propose the novel method, pDriver, to discover personalized cancer drivers. pDriver includes two stages: (i) constructing gene networks for each cancer patient and (ii) discovering cancer drivers for each patient based on the constructed gene networks. To demonstrate the effectiveness of pDriver, we have applied it to five TCGA cancer datasets and compared it with the state-of-the-art methods. The result indicates that pDriver is more effective than other methods. Furthermore, pDriver can also detect miRNA cancer drivers and most of them have been confirmed to be associated with cancer by literature. We further analyze the predicted personalized drivers for breast cancer patients and the result shows that they are significantly enriched in many GO processes and KEGG pathways involved in breast cancer. AVAILABILITY AND IMPLEMENTATION: pDriver is available at https://github.com/pvvhoang/pDriver. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A network-biology perspective of microRNA function and dysfunction in cancer.

MicroRNAs (miRNAs) participate in most aspects of cellular differentiation and homeostasis, and consequently have roles in many pathologies, including cancer. These small non-coding RNAs exert their effects in the context of complex regulatory networks, often made all the more extensive by the inclusion of transcription factors as their direct targets. In recent years, the increased availability of gene expression data and the development of methodologies that profile miRNA targets en masse have fuelled our understanding of miRNA functions, and of the sources and consequences of miRNA dysregulation. Advances in experimental and computational approaches are revealing not just cancer pathways controlled by single miRNAs but also intermeshed regulatory networks controlled by multiple miRNAs, which often engage in reciprocal feedback interactions with the targets that they regulate.

miRNA length variation during macrophage stimulation confounds the interpretation of results: implications for miRNA quantification by RT-qPCR.

Most microRNAs (miRNAs) are expressed as a mix of length isoforms (referred to as isomiRs). IsomiR stoichiometry can be differentially impacted upon cell stimulation, as recently evidenced by our group in the context of immune responses induced by type-I interferon (IFN). Here, we revisit published RNA-seq data sets of human and mouse macrophages stimulated with bacterial products at the isomiR level. We demonstrate that for several miRNAs, macrophage stimulation induces changes in isomiR stoichiometry. Critically, we find that changes in miRNA expression can be misinterpreted when miRNAs are quantified by RT-qPCR, as primers directed against canonical miRNA sequences may not equally target the different isomiRs that are regulated endogenously. Beyond the case of phagocyte stimulation, our analyses reinforce the concept that analysis of miRNA expression at the isoform level should become standard practice.

DriverGroup: a novel method for identifying driver gene groups.

MOTIVATION: Identifying cancer driver genes is a key task in cancer informatics. Most existing methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesize that there are driver gene groups that work in concert to regulate cancer, and we develop a novel computational method to detect those driver gene groups. RESULTS: We develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (i) constructing the gene network, (ii) discovering critical nodes of the constructed network and (iii) identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify driver groups for breast cancer. The identified driver groups are promising as several group members are confirmed to be related to cancer in literature. We further use the predicted driver groups in survival analysis and the results show that the survival curves of patient subpopulations classified using the predicted driver groups are significantly differentiated, indicating the usefulness of DriverGroup. AVAILABILITY AND IMPLEMENTATION: DriverGroup is available at https://github.com/pvvhoang/DriverGroup. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA).

Epithelial-mesenchymal transition (EMT) has been a subject of intense scrutiny as it facilitates metastasis and alters drug sensitivity. Although EMT-regulatory roles for numerous miRNAs and transcription factors are known, their functions can be difficult to disentangle, in part due to the difficulty in identifying direct miRNA targets from complex datasets and in deciding how to incorporate 'indirect' miRNA effects that may, or may not, represent biologically relevant information. To better understand how miRNAs exert effects throughout the transcriptome during EMT, we employed Exon-Intron Split Analysis (EISA), a bioinformatic technique that separates transcriptional and post-transcriptional effects through the separate analysis of RNA-Seq reads mapping to exons and introns. We find that in response to the manipulation of miRNAs, a major effect on gene expression is transcriptional. We also find extensive co-ordination of transcriptional and post-transcriptional regulatory mechanisms during both EMT and mesenchymal to epithelial transition (MET) in response to TGF-ß or miR-200c respectively. The prominent transcriptional influence of miRNAs was also observed in other datasets where miRNA levels were perturbed. This work cautions against a narrow approach that is limited to the analysis of direct targets, and demonstrates the utility of EISA to examine complex regulatory networks involving both transcriptional and post-transcriptional mechanisms.

miR-222 isoforms are differentially regulated by type-I interferon.

Endogenous microRNAs (miRNAs) often exist as multiple isoforms (known as "isomiRs") with predominant variation around their 3'-end. Increasing evidence suggests that different isomiRs of the same family can have diverse functional roles, as recently demonstrated with the example of miR-222-3p 3'-end variants. While isomiR levels from a same miRNA family can vary between tissues and cell types, change of templated isomiR stoichiometry to stimulation has not been reported to date. Relying on small RNA-sequencing analyses, we demonstrate here that miR-222-3p 3'-end variants >23 nt are specifically decreased upon interferon (IFN) ß stimulation of human fibroblasts, while shorter isoforms are spared. This length-dependent dynamic regulation of long miR-222-3p 3'-isoforms and >40 other miRNA families was confirmed in human monocyte-derived dendritic cells following infection with Salmonella Typhimurium, underlining the breadth of 3'-length regulation by infection, beyond the example of miR-222-3p. We further show that stem-loop miRNA Taqman RT-qPCR exhibits selectivity between 3'-isoforms, according to their length, and that this can lead to misinterpretation of results when these isoforms are differentially regulated. Collectively, and to our knowledge, this work constitutes the first demonstration that the stoichiometry of highly abundant templated 3'-isoforms of a same miRNA family can be dynamically regulated by a stimulus. Given that such 3'-isomiRs can have different functions, our study underlines the need to consider isomiRs when investigating miRNA-based regulation.

CBNA: A control theory based method for identifying coding and non-coding cancer drivers.

A key task in cancer genomics research is to identify cancer driver genes. As these genes initialise and progress cancer, understanding them is critical in designing effective cancer interventions. Although there are several methods developed to discover cancer drivers, most of them only identify coding drivers. However, non-coding RNAs can regulate driver mutations to develop cancer. Hence, novel methods are required to reveal both coding and non-coding cancer drivers. In this paper, we develop a novel framework named Controllability based Biological Network Analysis (CBNA) to uncover coding and non-coding cancer drivers (i.e. miRNA cancer drivers). CBNA integrates different genomic data types, including gene expression, gene network, mutation data, and contains a two-stage process: (1) Building a network for a condition (e.g. cancer condition) and (2) Identifying drivers. The application of CBNA to the BRCA dataset demonstrates that it is more effective than the existing methods in detecting coding cancer drivers. In addition, CBNA also predicts 17 miRNA drivers for breast cancer. Some of these predicted miRNA drivers have been validated by literature and the rest can be good candidates for wet-lab validation. We further use CBNA to detect subtype-specific cancer drivers and several predicted drivers have been confirmed to be related to breast cancer subtypes. Another application of CBNA is to discover epithelial-mesenchymal transition (EMT) drivers. Of the predicted EMT drivers, 7 coding and 6 miRNA drivers are in the known EMT gene lists.

Naturally existing isoforms of miR-222 have distinct functions.

Deep-sequencing reveals extensive variation in the sequence of endogenously expressed microRNAs (termed 'isomiRs') in human cell lines and tissues, especially in relation to the 3' end. From the immunoprecipitation of the microRNA-binding protein Argonaute and the sequencing of associated small RNAs, we observe extensive 3'-isomiR variation, including for miR-222 where the majority of endogenously expressed miR-222 is extended by 1-5 nt compared to the canonical sequence. We demonstrate this 3' heterogeneity has dramatic implications for the phenotype of miR-222 transfected cells, with longer isoforms promoting apoptosis in a size (but not 3' sequence)-dependent manner. The transfection of longer miR-222 isomiRs did not induce an interferon response, but did downregulate the expression of many components of the pro-survival PI3K-AKT pathway including PIK3R3, a regulatory subunit whose knockdown phenocopied the expression of longer 222 isoforms in terms of apoptosis and the inhibition of other PI3K-AKT genes. As this work demonstrates the capacity for 3' isomiRs to mediate differential functions, we contend more attention needs to be given to 3' variance given the prevalence of this class of isomiR.

Genome-wide identification of miR-200 targets reveals a regulatory network controlling cell invasion.

The microRNAs of the miR-200 family maintain the central characteristics of epithelia and inhibit tumor cell motility and invasiveness. Using the Ago-HITS-CLIP technology for transcriptome-wide identification of direct microRNA targets in living cells, along with extensive validation to verify the reliability of the approach, we have identified hundreds of miR-200a and miR-200b targets, providing insights into general features of miRNA target site selection. Gene ontology analysis revealed a predominant effect of miR-200 targets in widespread coordinate control of actin cytoskeleton dynamics. Functional characterization of the miR-200 targets indicates that they constitute subnetworks that underlie the ability of cancer cells to migrate and invade, including coordinate effects on Rho-ROCK signaling, invadopodia formation, MMP activity, and focal adhesions. Thus, the miR-200 family maintains the central characteristics of the epithelial phenotype by acting on numerous targets at multiple levels, encompassing both cytoskeletal effectors that control actin filament organization and dynamics, and upstream signals that locally regulate the cytoskeleton to maintain cell morphology and prevent cell migration.

Assessing the gene regulatory properties of Argonaute-bound small RNAs of diverse genomic origin.

High-throughput sequencing reveals an abundance of microRNA-sized fragments derived from larger non-coding RNAs. Roles for these small RNAs in gene silencing are suggested by their co-precipitation with Argonaute, the microRNA effector protein, though the extent to which they suppress gene expression endogenously remains unclear. To address this, we used luciferase reporters to determine the endogenous functionality of small RNAs from a diverse range of sources. We demonstrate small RNAs derived from snoRNAs have the capacity to act in a microRNA-like manner, though we note the vast majority of these are bound to Argonaute at levels below that required for detectable silencing activity. We show Argonaute exhibits a high degree of selectivity for the small RNAs with which it interacts and note that measuring Argonaute-associated levels is a better indicator of function than measuring total expression. Although binding to Argonaute at sufficient levels is necessary for demonstrating microRNA functionality in our reporter assay, this alone is not enough as some small RNAs derived from other non-coding RNAs (tRNAs, rRNAs, Y-RNAs) are associated with Argonaute at very high levels yet do not serve microRNA-like roles.

IsomiRs--the overlooked repertoire in the dynamic microRNAome.

The development of deep sequencing has enabled the identification of novel microRNAs (miRNAs), leading to a growing appreciation for the fact that individual miRNAs can be heterogeneous in length and/or sequence. These variants, termed isomiRs, can be expressed in a cell-specific manner, and numerous recent studies suggest that at least some isomiRs may affect target selection, miRNA stability, or loading into the RNA-induced silencing complex (RISC). Reports indicating differential functionality for isomiRs are currently confined to several specific variants, and although isomiRs are common, their broader biological significance is yet to be fully resolved. Here we review the growing body of evidence suggesting that isomiRs have functional differences, of which at least some appear biologically relevant, and caution researchers to take miRNA isoforms into consideration in their experiments.

Stimulus-dependent differences in signalling regulate epithelial-mesenchymal plasticity and change the effects of drugs in breast cancer cell lines.

INTRODUCTION: The normal process of epithelial mesenchymal transition (EMT) is subverted by carcinoma cells to facilitate metastatic spread. Cancer cells rarely undergo a full conversion to the mesenchymal phenotype, and instead adopt positions along the epithelial-mesenchymal axis, a propensity we refer to as epithelial mesenchymal plasticity (EMP). EMP is associated with increased risk of metastasis in breast cancer and consequent poor prognosis. Drivers towards the mesenchymal state in malignant cells include growth factor stimulation or exposure to hypoxic conditions. METHODS: We have examined EMP in two cell line models of breast cancer: the PMC42 system (PMC42-ET and PMC42-LA sublines) and MDA-MB-468 cells. Transition to a mesenchymal phenotype was induced across all three cell lines using epidermal growth factor (EGF) stimulation, and in MDA-MB-468 cells by hypoxia. We used RNA sequencing to identify gene expression changes that occur as cells transition to a more-mesenchymal phenotype, and identified the cell signalling pathways regulated across these experimental systems. We then used inhibitors to modulate signalling through these pathways, verifying the conclusions of our transcriptomic analysis. RESULTS: We found that EGF and hypoxia both drive MDA-MB-468 cells to phenotypically similar mesenchymal states. Comparing the transcriptional response to EGF and hypoxia, we have identified differences in the cellular signalling pathways that mediate, and are influenced by, EMT. Significant differences were observed for a number of important cellular signalling components previously implicated in EMT, such as HBEGF and VEGFA. We have shown that EGF- and hypoxia-induced transitions respond differently to treatment with chemical inhibitors (presented individually and in combinations) in these breast cancer cells. Unexpectedly, MDA-MB-468 cells grown under hypoxic growth conditions became even more mesenchymal following exposure to certain kinase inhibitors that prevent growth-factor induced EMT, including the mTOR inhibitor everolimus and the AKT1/2/3 inhibitor AZD5363. CONCLUSIONS: While resulting in a common phenotype, EGF and hypoxia induced subtly different signalling systems in breast cancer cells. Our findings have important implications for the use of kinase inhibitor-based therapeutic interventions in breast cancers, where these heterogeneous signalling landscapes will influence the therapeutic response.