Quaking isoforms cooperate to promote the mesenchymal phenotype.

The RNA-binding protein Quaking (QKI) has widespread effects on mRNA regulation including alternative splicing, stability, translation, and localization of target mRNAs. Recently, QKI was found to be induced during epithelial-mesenchymal transition (EMT), where it promotes a mesenchymal alternative splicing signature that contributes to the mesenchymal phenotype. QKI is itself alternatively spliced to produce three major isoforms, QKI-5, QKI-6, and QKI-7. While QKI-5 is primarily localized to the nucleus where it controls mesenchymal splicing during EMT, the functions of the two predominantly cytoplasmic isoforms, QKI-6 and QKI-7, in this context remain uncharacterized. Here we used CRISPR-mediated depletion of QKI in a human mammary epithelial cell model of EMT and studied the effects of expressing the QKI isoforms in isolation and in combination. QKI-5 was required to induce mesenchymal morphology, while combined expression of QKI-5 with either QKI-6 or QKI-7 further enhanced mesenchymal morphology and cell migration. In addition, we found that QKI-6 and QKI-7 can partially localize to the nucleus and contribute to alternative splicing of QKI target genes. These findings indicate that the QKI isoforms function in a dynamic and cooperative manner to promote the mesenchymal phenotype.

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.

Basonuclin-2 regulates extracellular matrix production and degradation.

Epithelial-mesenchymal transition is essential for tissue patterning and organization. It involves both regulation of cell motility and alterations in the composition and organization of the ECM-a complex environment of proteoglycans and fibrous proteins essential for tissue homeostasis, signaling in response to chemical and biomechanical stimuli, and is often dysregulated under conditions such as cancer, fibrosis, and chronic wounds. Here, we demonstrate that basonuclin-2 (BNC2), a mesenchymal-expressed gene, that is, strongly associated with cancer and developmental defects across genome-wide association studies, is a novel regulator of ECM composition and degradation. We find that at endogenous levels, BNC2 controls the expression of specific collagens, matrix metalloproteases, and other matrisomal components in breast cancer cells, and in fibroblasts that are primarily responsible for the production and processing of the ECM within the tumour microenvironment. In so doing, BNC2 modulates the motile and invasive properties of cancers, which likely explains the association of high BNC2 expression with increasing cancer grade and poor patient prognosis.

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.

"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.

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.

Making use of transcription factor enrichment to identify functional microRNA-regulons.

microRNAs (miRNAs) are important modulators of messenger RNA stability and translation, controlling wide gene networks. Albeit generally modest on individual targets, the regulatory effect of miRNAs translates into meaningful pathway modulation through concurrent targeting of regulons with functional convergence. Identification of miRNA-regulons is therefore essential to understand the function of miRNAs and to help realise their therapeutic potential, but it remains challenging due to the large number of false positive target sites predicted per miRNA. In the current work, we investigated whether genes regulated by a given miRNA were under the transcriptional control of a predominant transcription factor (TF). Strikingly we found that for ~50% of the miRNAs analysed, their targets were significantly enriched in at least one common TF. We leveraged such miRNA-TF co-regulatory networks to identify pathways under miRNA control, and demonstrated that filtering predicted miRNA-target interactions (MTIs) relying on such pathways significantly enriched the proportion of predicted true MTIs. To our knowledge, this is the first description of an in- silico pipeline facilitating the identification of miRNA-regulons, to help understand miRNA function.

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.

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.

Insufficiently complex unique-molecular identifiers (UMIs) distort small RNA sequencing.

The attachment of unique molecular identifiers (UMIs) to RNA molecules prior to PCR amplification and sequencing, makes it possible to amplify libraries to a level that is sufficient to identify rare molecules, whilst simultaneously eliminating PCR bias through the identification of duplicated reads. Accurate de-duplication is dependent upon a sufficiently complex pool of UMIs to allow unique labelling. In applications dealing with complex libraries, such as total RNA-seq, only a limited variety of UMIs are required as the variation in molecules to be sequenced is enormous. However, when sequencing a less complex library, such as small RNAs for which there is a more limited range of possible sequences, we find increased variation in UMIs are required, even beyond that provided in a commercial kit specifically designed for the preparation of small RNA libraries for sequencing. We show that a pool of UMIs randomly varying across eight nucleotides is not of sufficient depth to uniquely tag the microRNAs to be sequenced. This results in over de-duplication of reads and the marked under-estimation of expression of the more abundant microRNAs. Whilst still arguing for the utility of UMIs, this work demonstrates the importance of their considered design to avoid errors in the estimation of gene expression in libraries derived from select regions of the transcriptome or small genomes.

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.

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.

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.

Combinatorial Targeting by MicroRNAs Co-ordinates Post-transcriptional Control of EMT.

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression, functioning in part by facilitating the degradation of target mRNAs. They have an established role in controlling epithelial-mesenchymal transition (EMT), a reversible phenotypic program underlying normal and pathological processes. Many studies demonstrate the role of individual miRNAs using overexpression at levels greatly exceeding physiological abundance. This can influence transcripts with relatively poor targeting and may in part explain why over 130 different miRNAs are directly implicated as EMT regulators. Analyzing a human mammary cell model of EMT we found evidence that a set of miRNAs, including the miR-200 and miR-182/183 family members, co-operate in post-transcriptional regulation, both reinforcing and buffering transcriptional output. Investigating this, we demonstrate that combinatorial treatment altered cellular phenotype with miRNA concentrations much closer to endogenous levels and with less off-target effects. This suggests that co-operative targeting by miRNAs is important for their physiological function and future work classifying miRNAs should consider such combinatorial effects.

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.

MicroRNA-155 expression and function in AML: An evolving paradigm.

Acute myeloid leukemia (AML) arises when immature myeloid blast cells acquire multiple, recurrent genetic and epigenetic changes that result in dysregulated proliferation. Acute leukemia is the most common form of pediatric cancer, with AML accounting for ~20% of all leukemias in children. The genomic aberrations that drive AML inhibit myeloid differentiation and activate signal transduction pathways that drive proliferation. MicroRNAs, a class of small (~22 nucleotide) noncoding RNAs that posttranscriptionally suppress the expression of specifically targeted transcripts, are also frequently dysregulated in AML, which may prove useful for the purposes of disease classification, prognosis, and future therapeutic approaches. MicroRNA expression profiles are associated with patient prognosis and responses to standard chemotherapy, including predicting therapy resistance in AML. miR-155 is the primary focus of this review because it has been repeatedly associated with poorer survival across multiple cohorts of adult and pediatric AML. We discuss some novel features of miR-155 expression in AML, in particular how the levels of expression can critically influence function. Understanding the role of microRNAs in AML and the ways in which microRNA expression influences AML biology is one means to develop novel and more targeted therapies.

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.

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.

Defects in RNA metabolism in mitochondrial disease.

The expression of mitochondrially-encoded genes requires the efficient processing of long precursor RNAs at the 5' and 3' ends of tRNAs, a process which, when disrupted, results in disease. Two such mutations reside within mt-tRNALeu(UUR); a m.3243A>G transition, which is the most common cause of MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes), and m.3302A>G which often causes mitochondrial myopathy (MM). We used parallel analysis of RNA ends (PARE) that captures the 5' terminal end of 5'-monophosphorylated mitochondrial RNAs to compare the effects of the m.3243A>G and m.3302A>G mutations on mitochondrial tRNA processing and downstream RNA metabolism. We confirmed previously identified RNA processing defects, identified common internal cleavage sites and new sites unique to the m.3243A>G mutants that do not correspond to transcript ends. These sites occur in regions of predicted RNA secondary structure, or are in close proximity to such regions, and may identify regions of importance to the processing of mtRNAs.