Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

Systematic benchmarking of statistical methods to assess differential expression of circular RNAs.

Circular RNAs (circRNAs) are covalently closed transcripts involved in critical regulatory axes, cancer pathways and disease mechanisms. CircRNA expression measured with RNA-seq has particular characteristics that might hamper the performance of standard biostatistical differential expression assessment methods (DEMs). We compared 38 DEM pipelines configured to fit circRNA expression data's statistical properties, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq) and metagenomics DEMs. The DEMs performed poorly on data sets of typical size. Widely used DEMs, such as DESeq2, edgeR and Limma-Voom, gave scarce results, unreliable predictions or even contravened the expected behaviour with some parameter configurations. Limma-Voom achieved the most consistent performance throughout different benchmark data sets and, as well as SAMseq, reasonably balanced false discovery rate (FDR) and recall rate. Interestingly, a few scRNA-seq DEMs obtained results comparable with the best-performing bulk RNA-seq tools. Almost all DEMs' performance improved when increasing the number of replicates. CircRNA expression studies require careful design, choice of DEM and DEM configuration. This analysis can guide scientists in selecting the appropriate tools to investigate circRNA differential expression with RNA-seq experiments.

Discovery of fusion circular RNAs in leukemia with KMT2A::AFF1 rearrangements by the new software CircFusion.

Chromosomal translocations in cancer genomes, key players in many types of cancers, generate chimeric proteins that drive oncogenesis. Genomes with chromosomal rearrangements can also produce fusion circular RNAs (f-circRNAs) by backsplicing of chimeric transcripts, as first shown in leukemias with PML::RARα and KMT2A::MLLT3 translocations and later in solid cancers. F-circRNAs contribute to the oncogenic processes and reinforce the oncogenic activity of chimeric proteins. In leukemia with KMT2A::AFF1 (MLL::AF4) fusions, we previously reported specific alterations of circRNA expression, but nothing was known about f-circRNAs. Due to the presence of two chimeric sequences, fusion and backsplice junctions, the identification of f-circRNAs with available tools is challenging, possibly resulting in the underestimation of this RNA species, especially when the breakpoint is not known. We developed CircFusion, a new software tool to detect linear fusion transcripts and f-circRNAs from RNA-seq data, both in samples for which the breakpoints are known and when the information about the joined exons is missing. CircFusion can detect linear and circular chimeric transcripts deriving from the main and reciprocal translocations also in the presence of multiple breakpoints, which are common in malignant cells. Benchmarking tests on simulated and real datasets of cancer samples with previously experimentally determined f-circRNAs showed that CircFusion provides reliable predictions and outperforms available methods for f-circRNA detection. We discovered and validated novel f-circRNAs in acute leukemia harboring KMT2A::AFF1 rearrangements, leading the way to future functional studies aimed to unveil their role in this malignancy.

Sensitive, reliable and robust circRNA detection from RNA-seq with CirComPara2.

Circular RNAs (circRNAs) are a large class of covalently closed RNA molecules originating by a process called back-splicing. CircRNAs are emerging as functional RNAs involved in the regulation of biological processes as well as in disease and cancer mechanisms. Current computational methods for circRNA identification from RNA-seq experiments are characterized by low discovery rates and performance dependent on the analysed data set. We developed CirComPara2 (https://github.com/egaffo/CirComPara2), a new automated computational pipeline for circRNA discovery and quantification, which consistently achieves high recall rates without losing precision by combining multiple circRNA detection methods. In our benchmark analysis, CirComPara2 outperformed state-of-the-art circRNA discovery tools and proved to be a reliable and robust method for comprehensive transcriptome characterization.

CRAFT: a bioinformatics software for custom prediction of circular RNA functions.

Circular RNAs (circRNAs), transcripts generated by backsplicing, are particularly stable and pleiotropic molecules, whose dysregulation drives human diseases and cancer by modulating gene expression and signaling pathways. CircRNAs can regulate cellular processes by different mechanisms, including interaction with microRNAs (miRNAs) and RNA-binding proteins (RBP), and encoding specific peptides. The prediction of circRNA functions is instrumental to interpret their impact in diseases, and to prioritize circRNAs for functional investigation. Currently, circRNA functional predictions are provided by web databases that do not allow custom analyses, while self-standing circRNA prediction tools are mostly limited to predict only one type of function, mainly focusing on the miRNA sponge activity of circRNAs. To solve these issues, we developed CRAFT (CircRNA Function prediction Tool), a freely available computational pipeline that predicts circRNA sequence and molecular interactions with miRNAs and RBP, along with their coding potential. Analysis of a set of circRNAs with known functions has been used to appraise CRAFT predictions and to optimize its setting. CRAFT provides a comprehensive graphical visualization of the results, links to several knowledge databases, and extensive functional enrichment analysis. Moreover, it originally combines the predictions for different circRNAs. CRAFT is a useful tool to help the user explore the potential regulatory networks involving the circRNAs of interest and generate hypotheses about the cooperation of circRNAs into the modulation of biological processes.

iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data.

Whole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variants by three complementary callers (MuTect2, Strelka2 and VarScan2). The results are combined to obtain a single variant call format file for each sample and variants are annotated by integrating a wide range of information extracted from several reference databases, ultimately allowing variant and gene prioritization according to different criteria. iWhale allows users to conduct a complex series of WES analyses with a powerful yet customizable and easy-to-use tool, running on most operating systems (macOs, GNU/Linux and Windows). iWhale code is freely available at https://github.com/alexcoppe/iWhale and the docker image is downloadable from https://hub.docker.com/r/alexcoppe/iwhale.

MicroRNA-497/195 is tumor suppressive and cooperates with CDKN2A/B in pediatric acute lymphoblastic leukemia.

We previously identified an association of rapid engraftment of patient-derived leukemia cells transplanted into NOD/SCID mice with early relapse in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). In a search for the cellular and molecular profiles associated with this phenotype, we investigated the expression of microRNAs (miRNAs) in different engraftment phenotypes and patient outcomes. We found high expression of miR-497 and miR-195 (hereafter miR-497/195) in patient-derived xenograft samples with slow engraftment derived from patients with favorable outcome. In contrast, epigenetic repression and low expression of these miRNAs was observed in rapidly engrafting samples associated with early relapse. Overexpression of miR-497/195 in patient-derived leukemia cells suppressed in vivo growth of leukemia and prolonged recipient survival. Conversely, inhibition of miR-497/195 led to increased leukemia cell growth. Key cell cycle regulators were downregulated upon miR-497/195 overexpression, and we identified cyclin-dependent kinase 4 (CDK4)- and cyclin-D3 (CCND3)-mediated control of G1/S transition as a principal mechanism for the suppression of BCP-ALL progression by miR-497/195. The critical role for miR-497/195-mediated cell cycle regulation was underscored by finding (in an additional independent series of patient samples) that high expression of miR-497/195 together with a full sequence for CDKN2A and CDKN2B (CDKN2A/B) was associated with excellent outcome, whereas deletion of CDKN2A/B together with low expression of miR-497/195 was associated with clearly inferior relapse-free survival. These findings point to the cooperative loss of cell cycle regulators as a new prognostic factor indicating possible therapeutic targets for pediatric BCP-ALL.

miR-142-3p prevents macrophage differentiation during cancer-induced myelopoiesis.

Tumor progression is accompanied by an altered myelopoiesis causing the accumulation of immunosuppressive cells. Here, we showed that miR-142-3p downregulation promoted macrophage differentiation and determined the acquisition of their immunosuppressive function in tumor. Tumor-released cytokines signaling through gp130, the common subunit of the interleukin-6 cytokine receptor family, induced the LAP∗ isoform of C/EBPß transcription factor, promoting macrophage generation. miR-142-3p downregulated gp130 by canonical binding to its messenger RNA (mRNA) 3' UTR and repressed C/EBPß LAP∗ by noncanonical binding to its 5' mRNA coding sequence. Enforced miR expression impaired macrophage differentiation both in vitro and in vivo. Mice constitutively expressing miR-142-3p in the bone marrow showed a marked increase in survival following immunotherapy with tumor-specific T lymphocytes. By modulating a specific miR in bone marrow precursors, we thus demonstrated the feasibility of altering tumor-induced macrophage differentiation as a potent tool to improve the efficacy of cancer immunotherapy.

A survey of software tools for microRNA discovery and characterization using RNA-seq.

Since the small RNA-sequencing (sRNA-seq) technology became available, it allowed the discovery of thousands new microRNAs (miRNAs) in humans and many other species, providing new data on these small RNAs (sRNAs) of high biological and translational relevance. MiRNA discovery has not yet reached saturation, even in the most studied model organisms, and many researchers are using sRNA-seq in studies with different aims in biomedicine, fundamental research and in applied animal sciences. We review several miRNA discovery and characterization software tools that implement different strategies, providing a useful guide for researchers to select the programs best suiting their study objectives and data. After a brief introduction on miRNA biogenesis, function and characteristics, useful to understand the biological background considered by the algorithms, we survey the current state of miRNA discovery bioinformatics discussing 26 different sRNA-seq-based miRNA prediction software and toolkits released in the past 6 years, including 15 methods specific for miRNA prediction and 11 more general-purpose software suites for sRNA-seq data analysis. We highlight the main features of mature miRNAs and miRNA precursors considered by the methods categorizing them according to prediction strategy and implementation. In addition, we describe a typical miRNA prediction and analysis workflow by delineating the objectives, potentialities and main steps of sRNA-seq data analysis projects, from preparatory data processing to miRNA prediction, quantification and diverse downstream analyses. Finally, we outline the caveats affecting sRNA-seq-based prediction tools, and we indicate the possibilities offered by data set pooling and by integration with other types of high-throughput sequencing data.

MiR&moRe2: A Bioinformatics Tool to Characterize microRNAs and microRNA-Offset RNAs from Small RNA-Seq Data.

MicroRNA-offset RNAs (moRNAs) are microRNA-like small RNAs generated by microRNA precursors. To date, little is known about moRNAs and bioinformatics tools to inspect their expression are still missing. We developed miR&moRe2, the first bioinformatics method to consistently characterize microRNAs, moRNAs, and their isoforms from small RNA sequencing data. To illustrate miR&moRe2 discovery power, we applied it to several published datasets. MoRNAs identified by miR&moRe2 were in agreement with previous research findings. Moreover, we observed that moRNAs and new microRNAs predicted by miR&moRe2 were downregulated upon the silencing of the microRNA-biogenesis pathway. Further, in a sizeable dataset of human blood cell populations, tens of novel miRNAs and moRNAs were discovered, some of them with significantly varied expression levels among the cell types. Results demonstrate that miR&moRe2 is a valid tool for a comprehensive study of small RNAs generated from microRNA precursors and could help to investigate their biogenesis and function.

Silencing of miR-182 is associated with modulation of tumorigenesis through apoptosis induction in an experimental model of colorectal cancer.

BACKGROUND: miR-182-5p (miR-182) is an oncogenic microRNA (miRNA) found in different tumor types and one of the most up-regulated miRNA in colorectal cancer (CRC). Although this microRNA is expressed in the early steps of tumor development, its role in driving tumorigenesis is unclear. METHODS: The effects of miR-182 silencing on transcriptomic profile were investigated using two CRC cell lines characterized by different in vivo biological behavior, the MICOL-14h-tert cell line (dormant upon transfer into immunodeficient hosts) and its tumorigenic variant, MICOL-14tum. Apoptosis was studied by annexin/PI staining and cleaved Caspase-3/PARP analysis. The effect of miR-182 silencing on the tumorigenic potential was addressed in a xenogeneic model of MICOL-14tum transplant. RESULTS: Endogenous miR-182 expression was higher in MICOL-14tum than in MICOL-14h-tert cells. Interestingly, miR-182 silencing had a strong impact on gene expression profile, and the positive regulation of apoptotic process was one of the most affected pathways. Accordingly, annexin/PI staining and caspase-3/PARP activation demonstrated that miR-182 treatment significantly increased apoptosis, with a prominent effect in MICOL-14tum cells. Moreover, a significant modulation of the cell cycle profile was exerted by anti-miR-182 treatment only in MICOL-14tum cells, where a significant increase in the fraction of cells in G0/G1 phases was observed. Accordingly, a significant growth reduction and a less aggressive histological aspect were observed in tumor masses generated by in vivo transfer of anti-miR-182-treated MICOL-14tum cells into immunodeficient hosts. CONCLUSIONS: Altogether, these data indicate that increased miR-182 expression may promote cell proliferation, suppress the apoptotic pathway and ultimately confer aggressive traits on CRC cells.

Somatic mutations activating Wiskott-Aldrich syndrome protein concomitant with RAS pathway mutations in juvenile myelomonocytic leukemia patients.

The WAS gene product is expressed exclusively in the cytoplasm of hematopoietic cells and constitutional genetic abrogation of WASP leads to Wiskott-Aldrich syndrome (WAS). Moreover, mutational activation of WASP has been associated with X-linked neutropenia. Although studies reported that patients with constitutional WAS mutations affecting functional WASP expression may present juvenile myelomonocytic leukemia (JMML)-like features, confounding differential diagnosis above all in the copresence of mutated RAS, an activating somatic mutation of WASP has not been previously described in JMML patients. In our ongoing studies on JMML genomics, we at first detected a somatic WAS mutation in a major clone found at two consecutive relapses in one of two twins with JMML. Both twins were treated with hematopoietic stem cell transplantation after diagnosis of JMML. The somatic WAS mutation detected here displayed an activating WASP phenotype. Screening of 46 sporadic JMML patients at disease onset for mutations in the same PBD domain of WAS revealed two additional singleton patients carrying minor mutated clones. This is the first study to associate somatically acquired WASP mutations with a hematopoietic malignancy and increases insight in the complexity of the genomic landscape of JMML that shows low recurrent mutations concomitant with general hyperactivation of RAS pathway signaling.

Somatic mutations in specific and connected subpathways are associated with short neuroblastoma patients' survival and indicate proteins targetable at onset of disease.

Neuroblastoma (NB) is an embryonic malignancy of the sympathetic nervous system with heterogeneous biological, morphological, genetic and clinical characteristics. Although genomic studies revealed the specific biological features of NB pathogenesis useful for new therapeutic approaches, the improvement of high-risk (HR)-NB patients overall survival remains unsatisfactory. To further clarify the biological basis of disease aggressiveness, we used whole-exome sequencing to examine the genomic landscape of HR-NB patients at stage M with short survival (SS) and long survival (LS). Only a few genes, including SMARCA4, SMO, ZNF44 and CHD2, were recurrently and specifically mutated in the SS group, confirming the low recurrence of common mutations in this tumor. A systems biology approach revealed that in the two patient groups, mutations occurred in different pathways. Mutated genes (ARHGEF11, CACNA1G, FGF4, PTPRA, PTK2, ANK3, SMO, NTNG2, VCL and NID2) regulate the MAPK pathway associated with the organization of the extracellular matrix, cell motility through PTK2 signaling and matrix metalloproteinase activity. Moreover, we detected mutations in LAMA2, PTK2, LAMA4, and MMP14 genes, impairing MET signaling, in SFI1 and CHD2 involved in centrosome maturation and chromosome remodeling, in AK7 and SPTLC2, which regulate the metabolism of nucleotides and lipoproteins, and in NALCN, SLC12A1, SLC9A9, which are involved in the transport of small molecules. Notably, connected networks of somatically mutated genes specific for SS patients were identified. The detection of mutated genes present at the onset of disease may help to address an early treatment of HR-NB patients using FDA-approved compounds targeting the deregulated pathways.

miRNA-mRNA integrative analysis in primary myelofibrosis CD34+ cells: role of miR-155/JARID2 axis in abnormal megakaryopoiesis.

Primary myelofibrosis (PMF) is a myeloproliferative neoplasm characterized by megakaryocyte (MK) hyperplasia, bone marrow fibrosis, and abnormal stem cell trafficking. PMF may be associated with somatic mutations in JAK2, MPL, or CALR. Previous studies have shown that abnormal MKs play a central role in the pathophysiology of PMF. In this work, we studied both gene and microRNA (miRNA) expression profiles in CD34(+) cells from PMF patients. We identified several biomarkers and putative molecular targets such as FGR, LCN2, and OLFM4. By means of miRNA-gene expression integrative analysis, we found different regulatory networks involved in the dysregulation of transcriptional control and chromatin remodeling. In particular, we identified a network gathering several miRNAs with oncogenic potential (eg, miR-155-5p) and targeted genes whose abnormal function has been previously associated with myeloid neoplasms, including JARID2, NR4A3, CDC42, and HMGB3. Because the validation of miRNA-target interactions unveiled JARID2/miR-155-5p as the strongest relationship in the network, we studied the function of this axis in normal and PMF CD34(+) cells. We showed that JARID2 downregulation mediated by miR-155-5p overexpression leads to increased in vitro formation of CD41(+) MK precursors. These findings suggest that overexpression of miR-155-5p and the resulting downregulation of JARID2 may contribute to MK hyperplasia in PMF.

Characterization and discovery of novel miRNAs and moRNAs in JAK2V617F-mutated SET2 cells.

To gain insights into a possible role of microRNAs in myeloproliferative neoplasms, we performed short RNA massive sequencing and extensive bioinformatic analysis in the JAK2V617F-mutated SET2 cell line. Overall, 652 known mature miRNAs were detected, of which 21 were highly expressed, thus being responsible of most of miRNA-mediated gene repression. microRNA putative targets were enriched in specific signaling pathways, providing information about cell activities under massive posttranscriptional regulation. The majority of miRNAs were mixtures of sequence variants, called isomiRs, mainly because of alternative, noncanonical processing of hairpin precursors. We also identified 78 novel miRNAs (miRNA*) derived from known hairpin precursors. Both major and minor (*) forms of miRNAs were expressed concurrently from half of expressed hairpins, highlighting the relevance of miRNA* and the complexity of strand selection bias regulation. Finally, we discovered that SET2 cells express a number of miRNA-offset RNAs (moRNAs), short RNAs derived from genomic regions flanking mature miRNAs. We provide novel data about the possible origin of moRNAs, although their functional role remains to be elucidated. Overall, this study shed light on the complexity of microRNA-mediated gene regulation in SET2 cells and represents the basis for future studies in JAK2V617F-mutated cellular models.

miRNome of Italian Large White pig subcutaneous fat tissue: new miRNAs, isomiRs and moRNAs.

Small RNAs, such as micro-RNAs (miRNAs), are decisive regulators of gene expression, and they could determine adipose tissue traits. A better knowledge of porcine fat genomics is relevant given that the pig is a biomedical model for metabolic and cardiovascular human pathologies. Adipose tissue is particularly important for the meat industry. We explored the miRNome of two adult Italian Large White pig backfat samples by Illumina RNA-Seq. Using custom bioinformatic methods, the expressed miRNAs were identified and quantified and the nucleotide sequence variability of miRNA isoforms were analysed. We detected 222 known miRNAs, 68 new miRNAs and 17 miRNA-offset RNAs (moRNAs) expressed from known hairpins, and 312 new miRNAs expressed from 253 new hairpins. Porcine transcripts targeted by the most expressed miRNAs were predicted, showing that these miRNAs may have an impact on Wnt, insulin signalling and axon guidance pathways. The expression of five small RNAs, including moRNA ssc-5'-moR-21 and a miRNA from a new hairpin, was validated by a qRT-PCR assay, thus confirming the robustness of our results. The depicted miRNome complexity suggests that quantitative and qualitative features of miRNAs and non-canonical products of their precursors are worthy of further investigation to clarify their roles in the adipose tissue biology.

MAGIA²: from miRNA and genes expression data integrative analysis to microRNA-transcription factor mixed regulatory circuits (2012 update).

MAGIA(2) (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA(2) performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA(2) tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target.