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The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed by computational detection tools. During the last decade, a plethora of 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 were used and detected over 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were empirically validated using three orthogonal methods. Generally, tool-specific precision values are 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 tool differentiators. Furthermore, we demonstrate the complementarity of tools through the increase in detection sensitivity by considering the union of highly-precise tool combinations while keeping the number of false discoveries low. Finally, based on the benchmarking results, recommendations are put forward for circRNA detection and validation.

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.

Background Circular RNAs (circRNAs) are transcripts with covalently joined 3' and 5' ends. They play critical regulatory roles, are involved in disease and cancer mechanisms, and are promising biomarkers. CircRNA differential abundance in high-throughput sequencing transcriptomics (RNA-seq) studies is commonly analysed using differential expression assessment methods (DEMs) devised for bulk RNA-seq. However, circRNA expression data from RNA-seq have a high proportion of small and zero counts that might hamper commonly used DEMs. Importantly, DEMs' performance has never been evaluated on circRNA data. Results We compared 38 DEM pipelines on circRNA expression data, exploring DEMs' parameter configurations conceived for small counts. We also evaluated single-cell RNA-seq (scRNA-seq) and metagenomics DEMs designed to handle sparse data. In general, the DEMs performed poorly on data sets of typical size. Widely used bulk RNA-seq 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 and, as well as SAMseq, reasonably balanced false discovery and recall rates. A few scRNA-seq DEMs obtained results comparable to the best performing bulk RNA-seq tools. Almost all DEMs' performance improved when increasing the number of replicates. Conclusions CircRNA expression data have particular characteristics distinguished from traditional bulk RNA-seq, requiring careful study design, choice of DEM, and DEM configuration. This study can guide scientists in selecting the appropriate tools for circRNA comparative RNA-seq analyses.

Circular RNAs (circRNAs) are a large class of covalently closed RNA molecules that originate 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 characterised by low discovery rates and performance dependent on the analysed data set. We developed a new automated computational pipeline, CirComPara2 (https://github.com/egaffo/CirComPara2), that 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 transcriptomics characterisation.

Circular RNAs (circRNAs) are stable RNA molecules generated by backsplicing that play regulatory functions through interaction with other RNA and proteins, as well as by encoding peptides. Dysregulation of circRNA expression can drive cancer development and progression with different mechanisms. CircRNAs are currently regarded as extremely attractive molecules in cancer research for the identification of new and possibly targetable disease regulatory networks and for the development of biomarkers for cancer diagnosis, prognosis definition, and monitoring. Using specific experimental and computational protocols, circRNAs can be identified through RNA-seq by spotting the reads spanning backsplice junctions, which are specific to circular molecules. In this chapter, we report a state-of-the-art computational protocol for a genome-wide analysis of circRNAs from RNA-seq data, which considers circRNA detection, quantification, and differential expression testing. Finally, we indicate how to determine circular transcript sequences and the resources for an in silico functional characterization of circRNAs.

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.

Circular RNAs (circRNAs) are stable RNA molecules generated by backsplicing that play regulatory functions through interaction with other RNA and proteins, as well as by encoding peptides. Dysregulation of circRNA expression can drive cancer development and progression with different mechanisms. CircRNAs are currently regarded as extremely attractive molecules in cancer research for the identification of new and possibly targetable disease regulatory networks and for the development of biomarkers for cancer diagnosis, prognosis definition, and monitoring. Using specific experimental and computational protocols, circRNAs can be identified through RNA-seq by spotting the reads spanning backsplice junctions, which are specific to circular molecules. In this chapter, we report a state-of-the-art computational protocol for a genome-wide analysis of circRNAs from RNA-seq data, which considers circRNA detection, quantification, and differential expression testing. Finally, we indicate how to determine circular transcript sequences and the resources for an in silico functional characterization of circRNAs.

Plasma exosomal microRNAs (miRNAs) are considered as valid circulating biomarkers for cancer diagnosis and prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR), the most commonly used technique to assess circulating miRNA levels, requires a normalization step involving uniformly expressed endogenous miRNAs. However, there is still no consensus on reference miRNAs for plasma exosomal miRNA abundance normalization. In this study, we identified a panel of miRNAs with stable abundance by analyzing public plasma exosome RNA-seq data and selected miR-486-5p, miR-26a-5p, miR-423-5p and miR191-5p as candidate normalizers. Next, we tested the abundance variation of these miRNAs by qRT-PCR in plasma exosomes of healthy donors and pediatric patients with anaplastic large cell lymphoma, Burkitt lymphoma, Hodgkin lymphoma and mature B-cell acute lymphoblastic leukemia. MiR-486-5p and miR-26a-5p showed the most stable levels, both between healthy controls and patients and among the malignancies analyzed. In light of previous reports on miRNA stability in different exosome isolation methods, our data indicated that miR-26a-5p is a bona fide reference miRNA for qRT-PCR normalization to evaluate miRNA abundance from circulating plasma exosomes in studies of hematological malignancies.

Juvenile myelomonocytic leukemia (JMML), a rare myelodysplastic/myeloproliferative neoplasm of early childhood, is characterized by clonal growth of RAS signaling addicted stem cells. JMML subtypes are defined by specific RAS pathway mutations and display distinct gene, microRNA (miRNA) and long non-coding RNA expression profiles. Here we zoom in on circular RNAs (circRNAs), molecules that, when abnormally expressed, may participate in malignant deviation of cellular processes. CirComPara software was used to annotate and quantify circRNAs in RNA-seq data of a “discovery cohort” comprising 19 JMML patients and 3 healthy donors (HD). In an independent set of 12 JMML patients and 6 HD, expression of 27 circRNAs was analyzed by qRT-PCR. CircRNA-miRNA-gene networks were reconstructed using circRNA function prediction and gene expression data. We identified 119 circRNAs dysregulated in JMML and 59 genes showing an imbalance of the circular and linear products. Our data indicated also circRNA expression differences among molecular subgroups of JMML. Validation of a set of deregulated circRNAs in an independent cohort of JMML patients confirmed the down-regulation of circOXNAD1 and circATM, and a marked up-regulation of circLYN, circAFF2, and circMCTP1. A new finding in JMML links up-regulated circMCTP1 with known tumor suppressor miRNAs. This and other predicted interactions with miRNAs connect dysregulated circRNAs to regulatory networks. In conclusion, this study provides insight into the circRNAome of JMML and paves the path to elucidate new molecular disease mechanisms putting forward circMCTP1 up-regulation as a robust example.

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&amp, moRe2, the first bioinformatics method to consistently characterize microRNAs, moRNAs, and their isoforms from small RNA sequencing data. To illustrate miR&amp, moRe2 discovery power, we applied it to several published datasets. MoRNAs identified by miR&amp, moRe2 were in agreement with previous research findings. Moreover, we observed that moRNAs and new microRNAs predicted by miR&amp, 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&amp, 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.

Circular RNAs (circRNAs) are stable RNA molecules that can drive cancer through interactions with microRNAs and proteins and by the expression of circRNA encoded peptides. The aim of the study was to define the circRNA landscape and potential impact in T-cell acute lymphoblastic leukemia (T-ALL). Analysis by CirComPara of RNA-sequencing data from 25 T-ALL patients, immature, HOXA overexpressing, TLX1, TLX3, TAL1, or LMO2 rearranged, and from thymocyte populations of human healthy donors disclosed 68 554 circRNAs. Study of the top 3447 highly expressed circRNAs identified 944 circRNAs with significant differential expression between malignant T cells and normal counterparts, with most circRNAs displaying increased expression in T-ALL. Next, we defined subtype-specific circRNA signatures in molecular genetic subgroups of human T-ALL. In particular, circZNF609, circPSEN1, circKPNA5, and circCEP70 were upregulated in immature, circTASP1, circZBTB44, and circBACH1 in TLX3, circHACD1, and circSTAM in HOXA, circCAMSAP1 in TLX1, and circCASC15 in TAL-LMO. Backsplice sequences of 14 circRNAs ectopically expressed in T-ALL were confirmed, and overexpression of circRNAs in T-ALL with specific oncogenic lesions was substantiated by quantification in a panel of 13 human cell lines. An oncogenic role of circZNF609 in T-ALL was indicated by decreased cell viability upon silencing in vitro. Furthermore, functional predictions identified circRNA-microRNA gene axes informing modes of circRNA impact in molecular subtypes of human T-ALL.

T-cell large granular lymphocyte leukemia (T-LGLL) is a rare disease characterized by clonal proliferation of CD3+ lymphocytes whose pathogenesis is not completely understood. LGL resistance to the activation-induced cell death is sustained by anti-apoptotic pathways, mainly due to constitutive activation of the JAK-STAT axis by activating somatic mutations of STAT3 or STAT5B genes or epigenetic disturbances. STAT3 mutations are peculiar to CD8+ T-LGLL and are associated with cytopenias, treatment requirement, and reduced survival. STAT5B lesions are mostly found in CD4+ T-LGLL, a disorder presenting with a mild clinical course. A similar behaviour has been observed also in both STAT wild type (WT) CD8+ and CD4+ forms. The link between STAT3-dependent miR-146b repression and neutropenia exemplifies the role that the pathogenetic effect of somatic mutations can exert through complex axes, also involving non-coding RNAs. Since in the most symptomatic form of LGLL an urgent need to discover new mechanisms in place is demanded, we focused on additional regulatory molecules such as circular RNAs (circRNAs), single-stranded covalently closed RNA molecules generated by backsplicing (Figure 1A). CircRNAs' oncogenic potential is linked to their activity as miRNA sponges, modulators of RNA-binding protein activity, and their ability to encode oncogenic peptides. The study group includes 20 patients recruited at the Hematology Unit of Padua University Hospital (Italy) and diagnosed with T-LGLL according to the WHO criteria, plus 5 healthy controls (CTR). Patient leukemic clones were equally distributed among CD8+ WT and STAT3-mutated and CD4+ WT and STAT5B-mutated. RNA-seq of ribodepleted RNA from immunomagnetically purified CD57+ leukemic clones and CD8+ cells from CTR was obtained to study circRNAs. CircRNAs were identified and quantified from RNA-seq data by CirComPara v0.6.3. Differential expression was assessed by edgeR with robust estimation of dispersion. The circular to linear proportion (CLP), indicating the relative abundance of each circRNA with respect to all the overlapping host gene transcripts, was calculated, and differential CLP across conditions was assessed with CircTest. We detected 68.619 circRNAs and focused on 5.948 with high expression. These were expressed from 2,940 loci, mostly from annotated genes (99.95%). We identified 28 circRNAs derived from genomic regions without known genes. About one-half of circRNA host genes expressed multiple, up to 20, circular isoforms. About 4% of circRNAs had a CLP of at least 0.25, with 95 circRNAs more expressed than the linear counterpart, including circGUSBP2, circSHOC1, circTCEANC, circZNF609, and circKLHL8. Unsupervised analysis of circRNA expression showed a clear separation of T-LGLL from CTR samples, pointing toward circRNA dysregulation in T-LGLL, particularly for the CD8+ STAT3 mutated group, which diverged from the other subtypes (Figure 1B). The direct comparison between the CD8+ STAT3-mutated, the three molecular subtypes as a single group (OTH), and the CTR samples identified differences in circRNA expression specifically linked to the most symptomatic group with STAT3 lesions and those commonly observed in T-LGLL. In STAT3-mutated, 500 circRNAs were dysregulated with an excess (71%) of upregulation compared to CTR (Figure 1C). Most circRNAs commonly altered in both LGLL groups had a more marked dysregulation in patients with STAT3 mutations, as observed for circIKZF2 and a newly discovered intergenic circRNA. Most circRNAs with a significantly varied CLP (96%) showed an increased expression of the circular than linear transcripts in T-LGLL compared to CTR, uncovering genes with an imbalance of circular to linear transcripts proportion in leukemic cells (Figure 1D). The ongoing validation of the differential circRNA expression in an extended cohort of 40 LGLL patients is prioritizing circRNAs for functional investigation. The integration of computational predictions and in vitro functional screening through specific circRNA silencing will attempt to understand the link between circRNAs dysregulated in T-LGLL and disease mechanisms, unveiling possible circRNA-involving axes governed by hyperactivating STAT3 somatic variants that contribute to the malignant LGL phenotypes. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Circular RNAs (circRNAs) are transcripts generated by back-splicing. CircRNAs might regulate cellular processes by different mechanisms, including interaction with miRNAs and RNA-binding proteins. CircRNAs are pleiotropic molecules whose dysregulation has been linked to human diseases and can drive cancer by impacting gene expression and signaling pathways. The detection of circRNAs aberrantly expressed in disease conditions calls for the investigation of their functions. Here, we propose CircIMPACT, a bioinformatics tool for the integrative analysis of circRNA and gene expression data to facilitate the identification and visualization of the genes whose expression varies according to circRNA expression changes. This tool can highlight regulatory axes potentially governed by circRNAs, which can be prioritized for further experimental study. The usefulness of CircIMPACT is exemplified by a case study analysis of bladder cancer RNA-seq data. The link between circHIPK3 and heparanase (HPSE) expression, due to the circHIPK3-miR558-HPSE regulatory axis previously determined by experimental studies on cell lines, was successfully detected. CircIMPACT is freely available at GitHub.

Circular RNAs (circRNAs) are abundantly expressed in the haematopoietic compartment, but knowledge on their diversity among blood cell types is still limited. Nevertheless, emerging data indicate an array of circRNA functions exerted through interactions with other RNAs and proteins, by translation into peptides, and circRNA involvement as regulatory molecules in many biological processes and cancer mechanisms. Interestingly, the role of specific circRNAs in leukemogenesis has been disclosed by a few studies, mostly in acute myeloid leukemia. In this study, circRNA expression in B-cells, T-cells and monocytes of healthy subjects is described, including putative new circRNA genes. Expression comparison considered 6,228 circRNAs and highlighted cell population-specific expression and exon usage patterns. Differential expression has been confirmed by qRT-PCR for circRNAs specific of B-cells (circPAX5, circAFF3, circIL4R, and circSETBP1) or T-cells (circIKZF1, circTNIK, circTXK, and circFBXW7), and for circRNAs from intronic (circBCL2) and intergenic regions that were overexpressed in lymphocytes. Starting from this resource of circRNA expression in mature blood cell populations, targeted examination identified striking and generalized upregulated expression of circPAX5, circPVT1 and circHIPK3 in pediatric B-precursor acute lymphoblastic leukemia, and disclosed circRNAs with variable expression across cytogenetic subtypes.

Microarray analysis of the multiple myeloma (MM) miRNome has unraveled the differential expression of miRNAs in cytogenetic subgroups, their involvement in the tumor biology and their effectiveness in prognostic models. Herein, the small RNA transcriptional landscape in MM has been investigated exploiting the possibilities offered by small RNA-seq, including accurate quantification of known mature species, discovery and characterization of isomiRs, and miRNA-offset RNAs (moRNAs). Matched small RNA-seq and miRNA GeneChip® microarray expression profiles were obtained in a representative panel of 30 primary MM tumors, fully characterized for genomic aberrations and mutations. RNA-seq and microarray gave concordant estimations of known species. Enhanced analysis of RNA-seq data with the miR&moRe pipeline led to the characterization of 655 known and 17 new mature miRNAs and of 74 moRNAs expressed in the considered cohort, 5 of which (moR-150-3p, moR-24-2-5p, moR-421-5p, moR-21-5p, and moR-6724-5p) at high level. Ectopic expression of miR-135a-3p in t(4;14) patients, upregulation of moR-150-3p and moR-21-5p in t(14;16)/t(14;20) samples, and of moR-6724-1-5p in patients overexpressing CCND1 were uncovered and validated by qRT-PCR. Overall, RNA-seq offered a more complete overview of small non-coding RNA in MM tumors, indicating specific moRNAs that demand further investigations to explore their role in MM biology.

Chromosomal translocations harbored by cancer genomes are important oncogenic drivers. In MLL rearranged acute leukemia (MLLre) MLL/KMT2A fuses with over 90 partner genes. Mechanistic studies provided clues of MLL fusion protein leukemogenic potential, but models failed to fully recapitulate the disease. Recently, expression of oncogenic fusion circular RNAs (f-circ) by MLL-AF9 fusion was proven. This discovery, together with emerging data on the importance and diversity of circRNAs formed the incentive to study the circRNAs of the MLL recombinome. Through interactions with other RNAs, such as microRNAs, and with proteins, circRNAs regulate cellular processes also related to cancer development. CircRNAs can translate into functional peptides too. MLL and most of the 90 MLL translocation partners do express circRNAs and exploration of our RNA-seq dataset of sorted blood cell populations provided new data on alternative circular isoform generation and expression variability of circRNAs of the MLL recombinome. Further, we provided evidence that rearrangements of MLL and three of the main translocation partner genes can impact circRNA expression, supported also by preliminary observations in leukemic cells. The emerging picture underpins the view that circRNAs are worthwhile to be considered when studying MLLre leukemias and provides a new perspective on the impact of chromosomal translocations in cancer cells at large.

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.

Acute lymphoblastic leukemia (ALL) is the most common malignancy of childhood. Relapse is associated with poor prognosis, requiring further investigation on high-risk leukemias. MicroRNAs (miRNAs) are involved in the regulation of physiological processes. Deregulated miRNAs have been described to play a role in the initiation and progression of leukemia. Here, we investigated miRNA expression profiles comparing leukemia samples of patients with good and poor outcome, also characterized by slow or rapid engraftment, respectively, upon transplantation into NOD/SCID mice. We found downregulation of the miR-497~195 cluster in B-cell precursor (BCP)-ALL patient-derived xenograft samples with rapid engraftment and early relapse. Accordingly, in an independent cohort, patients with a high expression of miR-497 or miR-195 showed higher event-free survival. We identified promoter methylation as the mechanism responsible for miR-497~195 downregulation, as it was associated with low miR-497~195 levels in xenografts and treatment with the demethylating agent Decitabine increased miR-497~195 expression in BCP-ALL cell lines. To study the role of miR-497~195 in BCP-ALL, we stably overexpressed the cluster in three xenograft samples. MiR-497~195 overexpression impaired engraftment of leukemic cells in NOD/SCID mice, as compared to control cells, prolonging recipient survival. Gene expression profiling and ex vivo analysis of miR-497~195 overexpressing xenograft cells showed that inhibition of cell proliferation is a mechanism responsible for the miRNA cluster tumor suppressive role. Mechanistically, CDK4 and CCND3 were downregulated at mRNA and protein levels upon miR-497~195 overexpression, leading to decreased RB1 phosphorylation, reduced transcription of E2F target genes, and inhibition of the entry in S phase. CDK4 mediated G1/S transition is also inhibited by CDKN2A and CDKN2B, which are deleted in 20% of BCP-ALL. Deletion of CDKN2A/B and concomitant low miR-497~195 expression were particularly associated with a high proportion of early relapse cases in our cohort, indicating that impaired regulation of G1/S transition is critical for ALL aggressiveness. Importantly, targeting this pathway with the CDK4/CDK6 inhibitor Palbociclib impaired ex vivo growth of BCP-ALL xenograft samples, indicating a possible therapeutic strategy. Altogether, we showed that the tumor-suppressive cluster miR-497~195 is downregulated by epigenetic repression in BCP-ALL and that low expression is associated with early relapse and rapid engraftment. Low miR-497~195 expression might cooperate with deletion of CDKN2A/B promoting tumor progression, through loss of CCND3/CDK4-dependent control of cell cycle regulation. Citation Format: Elena Boldrin, Enrico Gaffo, Judith Boer, Salih Demir, Julia Zinngrebe, Rainer Claus, Christoph Plass, Monique L. den Boer, Klaus-Michael Debatin, Geertruy te Kronnie, Stefania Bortoluzzi, Lüder Hinrich Meyer. MicroRNA-497~195 cluster suppresses acute lymphoblastic leukemia growth by targeting CCND3/CDK4 and inhibiting cell cycle progression [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2541.

Chromosomal translocations harbored by cancer genomes are important oncogenic drivers. In MLL rearranged acute leukemia (MLLre) MLL/KMT2A fuses with over 90 partner genes. Mechanistic studies provided clues of MLL fusion protein leukemogenic potential, but models failed to fully recapitulate the disease. Recently, expression of oncogenic fusion circular RNAs (f-circ) by MLL-AF9 fusion was proven. This discovery, together with emerging data on the importance and diversity of circRNAs formed the incentive to study the circRNAs of the MLL recombinome. Through interactions with other RNAs, such as microRNAs, and with proteins, circRNAs regulate cellular processes also related to cancer development. CircRNAs can translate into functional peptides too. MLL and most of the 90 MLL translocation partners do express circRNAs and exploration of our RNA-seq dataset of sorted blood cell populations provided new data on alternative circular isoform generation and expression variability of circRNAs of the MLL recombinome. Further, we provided evidence that rearrangements of MLL and three of the main translocation partner genes can impact circRNA expression, supported also by preliminary observations in leukemic cells. The emerging picture underpins the view that circRNAs are worthwhile to be considered when studying MLLre leukemias and provides a new perspective on the impact of chromosomal translocations in cancer cells at large.

SummaryThe identification of the molecular mechanisms regulating pathways associated to the potential of fat deposition in pigs can lead to the detection of key genes and markers for the genetic improvement of fat traits. MicroRNAs (miRNAs) interactions with target RNAs regulate gene expression and modulate pathway activation in cells and tissues. In pigs, miRNA discovery is well far from saturation and the knowledge of miRNA expression in backfat tissue and particularly of the impact of miRNA variations are still fragmentary. We characterized by RNAseq the small RNAs (sRNAs) expression profiles in Italian Large White pig backfat tissue. Comparing two groups of pigs divergent for backfat deposition, we detected 31 significant differentially expressed (DE) sRNAs, 14 up-regulated (including ssc-miR-132, ssc-miR-146b, sscmiR-221–5p, ssc-miR-365–5p, and the moRNA ssc-moR-21–5p) and 17 down-regulated (including ssc-miR-136, ssc-miR-195, ssc-miR-199a-5p, and ssc-miR-335). To understand the biological impact of the observed miRNA expression variations, we used the expression correlation of DE miRNA target transcripts expressed in the same samples to define a regulatory network of 193 interactions between DE miRNAs and 40 DE target transcripts showing opposite expression profiles and being involved in specific pathways. Several miRNAs and mRNAs in the network resulted to be expressed from backfat related pig QTLs. These results are informative on the complex mechanisms influencing fat traits, shed light on a new aspect of the genetic regulation of fat deposition in pigs, and facilitate the perspective implementation of innovative strategies of pig genetic improvement based on genomic markers.

Circular RNAs (circRNAs) are generated by backsplicing of immature RNA forming covalently closed loops of intron/exon RNA molecules. Pervasiveness, evolutionary conservation, massive and regulated expression, and posttranscriptional regulatory roles of circRNAs in eukaryotes have been appreciated and described only recently. Moreover, being easily detectable disease markers, circRNAs undoubtedly represent a molecular class with high bearing on molecular pathobiology. CircRNAs can be detected from RNAseq data using appropriate computational methods to identify the sequence reads spanning backsplice junctions that do not colinearly map to the reference genome. To this end, several programs were developed and critical assessment of various strategies and tools suggested the combination of at least two methods as good practice to guarantee robust circRNA detection. Here,we present CirComPara (http://github.com/egaffo/CirComPara), an automated bioinformatics pipeline, to detect, quantify and annotate circRNAs from RNAseq data using in parallel four different methods for backsplice identification. CirComPara also provides quantification of linear RNAs and gene expression, ultimately comparing and correlating circRNA and gene/transcript expression level. We applied our method to RNAseqdata of monocyte and macrophage samples in relation to haploinsufficiency of the RNAbinding splicing factor Quaking (QKI). The biological relevance of the results, in terms of number, types and variations of circRNAs expressed, illustrates CirComPara potential to enlarge the knowledge of the transcriptome, adding details on the circRNAome, and facilitating further computational and experimental studies.

Extracellular vesicles (EVs) secreted from many cell types play important roles in intercellular communication, both as paracrine and endocrine factors, as they can circulate in biological fluids, including plasma. Amid EVs, exosomes are actively secreted vesicles that contain proteins, lipids, soluble factors, and nucleic acids, including microRNAs (miRNAs) and other classes of small RNAs (sRNA). miRNAs are prominent post-transcriptional regulators of gene expression and epigenetic silencers of transcription. We concisely review the roles of miRNAs in cell-fate determination and development and their regulatory activity on almost all the processes and pathways controlling tumor formation and progression. Next, we consider the evidence linking exosomes to tumor progression, particularly to the setting-up of permissive pre-metastatic niches. The study of exosomes in patients with different survival and therapy response can inform on the possible correlations between exosomal cargo and disease features. Moreover, the exploration of circulating exosomes as possible sources of non-invasive biomarkers could give new implements for anti-cancer therapy and metastasis prevention. Since the characterization of sRNAs in exosomes of cancer patients sparks opportunities to better understand their roles in cancer, we briefly present current experimental and computational protocols for sRNAs analysis in circulating exosomes by RNA-seq.

Cell states in hematopoiesis are controlled by master regulators and by complex circuits of a growing family of RNA species impacting cell phenotype maintenance and plasticity. Circular RNAs (circRNAs) are rapidly gaining the status of particularly stable transcriptome members with distinctive qualities. RNA-seq identified thousands of circRNAs with developmental stage- and tissue-specific expression corroborating earlier suggestions that circular isoforms are a natural feature of the cell expression program. CircRNAs are abundantly expressed also in the hematopoietic compartment. There are a number of studies on circRNAs in blood cells, a specific overview is however lacking. In this review we first present current insight in circRNA biogenesis discussing the relevance for hematopoiesis of the highly interleaved processes of splicing and circRNA biogenesis. Regarding molecular functions circRNAs modulate host gene expression, but also compete for binding of microRNAs, RNA-binding proteins or translation initiation and participate in regulatory circuits. We examine circRNA expression in the hematopoietic compartment and in hematologic malignancies and review the recent breakthrough study that identified pathogenic circRNAs derived from leukemia fusion genes. CircRNA high and regulated expression in blood cell types indicate that further studies are warranted to inform the position of these regulators in normal and malignant hematopoiesis.

microRNAs (miRNAs) are relevant in the pathogenesis of primary myelofibrosis (PMF) but our understanding is limited to specific target genes and the overall systemic scenario islacking. By both knowledge-based and ab initio approaches for comparative analysis of CD34+ cells of PMF patients and healthy controls, we identified the deregulated pathways involving miRNAs and genes and new transcriptional and post-transcriptional regulatory circuits in PMF cells. These converge in a unique and integrated cellular process, in which the role of specific miRNAs is to wire, co-regulate and allow a fine crosstalk between the involved processes. The PMF pathway includes Akt signaling, linked to Rho GTPases, CDC42, PLD2, PTEN crosstalk with the hypoxia response and Calcium-linked cellular processes connected to cyclic AMP signaling. Nested on the depicted transcriptional scenario, predicted circuits are reported, opening new hypotheses. Links between miRNAs (miR-106a-5p, miR-20b-5p, miR-20a-5p, miR-17-5p, miR-19b-3p and let-7d-5p) and key transcription factors (MYCN, ATF, CEBPA, REL, IRF and FOXJ2) and their common target genes tantalizingly suggest new path to approach the disease. The study provides a global overview of transcriptional and post-transcriptional deregulations in PMF, and, unifying consolidated and predicted data, could be helpful to identify new combinatorial therapeutic strategy. Interactive PMF network model: http://compgen.bio.unipd.it/pmf-net/.

Fat deposition is a widely studied trait in pigs because of its implications with animal growth efficiency, technological and nutritional characteristics of meat products, but the global framework of the biological and molecular processes regulating fat deposition in pigs is still incomplete. This study describes the backfat tissue transcription profile in Italian Large White pigs and reports genes differentially expressed between fat and lean animals according to RNA-seq data. The backfat transcription profile was characterised by the expression of 23 483 genes, of which 54.1% were represented by known genes. Of 63 418 expressed transcripts, about 80% were non-previously annotated isoforms. By comparing the expression level of fat vs. lean pigs, we detected 86 robust differentially expressed transcripts, 72 more highly expressed (e.g. ACP5, BCL2A1, CCR1, CD163, CD1A, EGR2, ENPP1, GPNMB, INHBB, LYZ, MSR1, OLR1, PIK3AP1, PLIN2, SPP1, SLC11A1, STC1) and 14 lower expressed (e.g. ADSSL1, CDO1, DNAJB1, HSPA1A, HSPA1B, HSPA2, HSPB8, IGFBP5, OLFML3) in fat pigs. The main functional categories enriched in differentially expressed genes were immune system process, response to stimulus, cell activation and skeletal system development, for the overexpressed genes, and unfolded protein binding and stress response, for the underexpressed genes, which included five heat shock proteins. Adipose tissue alterations and impaired stress response are linked to inflammation and, in turn, to adipose tissue secretory activity, similar to what is observed in human obesity. Our results provide the opportunity to identify biomarkers of carcass fat traits to improve the pig production chain and to identify genetic factors that regulate the observed differential expression.

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.