Conserved features and diversity attributes of chimeric RNAs across accessions in four plants.

As a non-collinear expression form of genetic information, chimeric RNAs increase the complexity of transcriptome in diverse organisms. Although chimeric RNAs have been identified in plants, few common features have been revealed. Here, we systemically explored the landscape of chimeric RNAs across multi-accession and multi-tissue using pan-genome and transcriptome data of four plants: rice, maize, soybean, and Arabidopsis. Among the four species, conserved characteristics of breakpoints and parental genes were discovered. In each species, chimeric RNAs displayed a high level of diversity among accessions, and the clustering of accessions using chimeric events was generally concordant with clustering based on genomic variants, implying a general relationship between genetic variations and chimeric RNAs. Through mass spectrometry, we confirmed a fusion protein OsNDC1-OsGID1L2 and observed its subcellular localization, which differed from the original proteins. Phenotypic cues in transgenic rice suggest the potential functions of OsNDC1-OsGID1L2. Moreover, an intriguing chimeric event Os01g0216500-Os01g0216900, generated by a large deletion in basmati rice, also exists in another accession without the deletion, demonstrating its convergence in evolution. Our results illuminate the characteristics and hint at the evolutionary implications of plant chimeric RNAs, which serve as a supplement to genetic variations, thus expanding our understanding of genetic diversity.

A Protocol for the Detection of Fusion Transcripts Using RNA-Sequencing Data.

Fusion transcripts are formed when two genes or their mRNAs fuse to produce a novel gene or chimeric transcript. Fusion genes are well-known cancer biomarkers used for cancer diagnosis and as therapeutic targets. Gene fusions are also found in normal physiology and lead to the evolution of novel genes that contribute to better survival and adaptation for an organism. Various in vitro approaches, such as FISH, PCR, RT-PCR, and chromosome banding techniques, have been used to detect gene fusion. However, all these approaches have low resolution and throughput. Due to the development of high-throughput next-generation sequencing technologies, the detection of fusion transcript becomes feasible using whole genome sequencing, RNA-Seq data, and bioinformatics tools. This chapter will overview the general computational protocol for fusion transcript detection from RNA-sequencing datasets.

Cancer fusion transcripts with human non-coding RNAs.

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

Chimeric RNAs reveal putative neoantigen peptides for developing tumor vaccines for breast cancer.

Introduction: We present here a strategy to identify immunogenic neoantigen candidates from unique amino acid sequences at the junctions of fusion proteins which can serve as targets in the development of tumor vaccines for the treatment of breastcancer. Method: We mined the sequence reads of breast tumor tissue that are usually discarded as discordant paired-end reads and discovered cancer specific fusion transcripts using tissue from cancer free controls as reference. Binding affinity predictions of novel peptide sequences crossing the fusion junction were analyzed by the MHC Class I binding predictor, MHCnuggets. CD8+ T cell responses against the 15 peptides were assessed through in vitro Enzyme Linked Immunospot (ELISpot). Results: We uncovered 20 novel fusion transcripts from 75 breast tumors of 3 subtypes: TNBC, HER2+, and HR+. Of these, the NSFP1-LRRC37A2 fusion transcript was selected for further study. The 3833 bp chimeric RNA predicted by the consensus fusion junction sequence is consistent with a read-through transcription of the 5'-gene NSFP1-Pseudo gene NSFP1 (NSFtruncation at exon 12/13) followed by trans-splicing to connect withLRRC37A2 located immediately 3' through exon 1/2. A total of 15 different 8-mer neoantigen peptides discovered from the NSFP1 and LRRC37A2 truncations were predicted to bind to a total of 35 unique MHC class I alleles with a binding affinity of IC50<500nM.); 1 of which elicited a robust immune response. Conclusion: Our data provides a framework to identify immunogenic neoantigen candidates from fusion transcripts and suggests a potential vaccine strategy to target the immunogenic neopeptides in patients with tumors carrying the NSFP1-LRRC37A2 fusion.

Solid-phase synthesis and properties of stereocontrolled boranophosphate/phosphate and phosphorothioate/phosphate chimeric oligouridylates.

This study describes the stereoselective synthesis of boranophosphate/phosphate (PB/PO) and phosphorothioate/phosphate (PS/PO) chimeric oligouridylates using the solid-phase method. Oxazaphospholidine monomer was used to construct the stereodefined PB and PS linkages. The study introduces modifications to oligouridylate derivatives in the intended positions with the intended stereochemistry of phosphorous atoms. Additionally, biophysical and biochemical properties of the synthesized oligomers were evaluated. Notably, it was found that a (Sp)-PB/PO chimeric oligouridylate had higher hybridization ability than the unmodified counterpart to an unmodified oligoadenylate. This is the first report that elucidates the effect of both stereochemistry and type of P-modification (PB and PS) on properties of oligoribonucleotides.

Versatile RNA: overlooked gems of the transcriptome.

The critical role of RNA, its use and targetability concerning different aspects of human health are gaining more attention because our understanding of the versatility of RNA has dramatically evolved over the last decades. We now appreciate that RNA is far more critical than a messenger molecule and possesses many complicated functions. As a multifunctional molecule with its sequence, flexible structures and enzymatic abilities, RNA is genuinely powerful. Mammalian transcriptomes consist of a dynamically regulated plethora of coding and noncoding RNA types. However, some aspects of RNA metabolism remain to be explored. In this Viewpoint, we focus on the transcriptome's unconventional and possibly overlooked aspects to emphasize the importance of RNA in mammalian systems.

Chimeric RNAs and their implication in prostate cancer.

•Chimeric ribonucleic acids (RNAs) form through gene fusion, trans-splicing, or cis-splicing between adjacent genes (cis-SAGe) mechanisms•Chimeric RNAs influence prostate cancer (PCa) progression by acting as long noncoding RNAs (lncRNAs) or circular RNAs (circRNAs), coding fusion proteins, and misregulating parental genes•Misregulated chimeric RNAs represent a novel repertoire for biomarkers and targets for PCa therapy.

Non-Canonical Splicing and Its Implications in Brain Physiology and Cancer.

The advance of experimental and computational techniques has allowed us to highlight the existence of numerous different mechanisms of RNA maturation, which have been so far unknown. Besides canonical splicing, consisting of the removal of introns from pre-mRNA molecules, non-canonical splicing events may occur to further increase the regulatory and coding potential of the human genome. Among these, splicing of microexons, recursive splicing and biogenesis of circular and chimeric RNAs through back-splicing and trans-splicing processes, respectively, all contribute to expanding the repertoire of RNA transcripts with newly acquired regulatory functions. Interestingly, these non-canonical splicing events seem to occur more frequently in the central nervous system, affecting neuronal development and differentiation programs with important implications on brain physiology. Coherently, dysregulation of non-canonical RNA processing events is associated with brain disorders, including brain tumours. Herein, we summarize the current knowledge on molecular and regulatory mechanisms underlying canonical and non-canonical splicing events with particular emphasis on cis-acting elements and trans-acting factors that all together orchestrate splicing catalysis reactions and decisions. Lastly, we review the impact of non-canonical splicing on brain physiology and pathology and how unconventional splicing mechanisms may be targeted or exploited for novel therapeutic strategies in cancer.

The Fusion of CLEC12A and MIR223HG Arises from a trans-Splicing Event in Normal and Transformed Human Cells.

Chimeric RNAs are often associated with chromosomal rearrangements in cancer. In addition, they are also widely detected in normal tissues, contributing to transcriptomic complexity. Despite their prevalence, little is known about the characteristics and functions of chimeric RNAs. Here, we examine the genetic structure and biological roles of CLEC12A-MIR223HG, a novel chimeric transcript produced by the fusion of the cell surface receptor CLEC12A and the miRNA-223 host gene (MIR223HG), first identified in chronic myeloid leukemia (CML) patients. Surprisingly, we observed that CLEC12A-MIR223HG is not just expressed in CML, but also in a variety of normal tissues and cell lines. CLEC12A-MIR223HG expression is elevated in pro-monocytic cells resistant to chemotherapy and during monocyte-to-macrophage differentiation. We observed that CLEC12A-MIR223HG is a product of trans-splicing rather than a chromosomal rearrangement and that transcriptional activation of CLEC12A with the CRISPR/Cas9 Synergistic Activation Mediator (SAM) system increases CLEC12A-MIR223HG expression. CLEC12A-MIR223HG translates into a chimeric protein, which largely resembles CLEC12A but harbours an altered C-type lectin domain altering key disulphide bonds. These alterations result in differences in post-translational modifications, cellular localization, and protein-protein interactions. Taken together, our observations support a possible involvement of CLEC12A-MIR223HG in the regulation of CLEC12A function. Our workflow also serves as a template to study other uncharacterized chimeric RNAs.

Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells.

Gene fusions can give rise to somatic alterations in cancers. Fusion genes have the potential to create chimeric RNAs, which can generate the phenotypic diversity of cancer cells, and could be associated with novel molecular functions related to cancer cell survival and proliferation. The expression of chimeric RNAs in cancer cells might impact diverse cancer-related functions, including loss of apoptosis and cancer cell plasticity, and promote oncogenesis. Due to their recurrence in cancers and functional association with oncogenic processes, chimeric RNAs are considered biomarkers for cancer diagnosis. Several recent studies demonstrated that chimeric RNAs could lead to the generation of new functionality for the resistance of cancer cells against drug therapy. Therefore, targeting chimeric RNAs in drug resistance cancer could be useful for developing precision medicine. So, understanding the functional impact of chimeric RNAs in cancer cells from an evolutionary perspective will be helpful to elucidate cancer evolution, which could provide a new insight to design more effective therapies for cancer patients in a personalized manner.

Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues.

Prolonged detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and recurrence of PCR-positive tests have been widely reported in patients after recovery from COVID-19, but some of these patients do not appear to shed infectious virus. We investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the DNA of human cells in culture and that transcription of the integrated sequences might account for some of the positive PCR tests seen in patients. In support of this hypothesis, we found that DNA copies of SARS-CoV-2 sequences can be integrated into the genome of infected human cells. We found target site duplications flanking the viral sequences and consensus LINE1 endonuclease recognition sequences at the integration sites, consistent with a LINE1 retrotransposon-mediated, target-primed reverse transcription and retroposition mechanism. We also found, in some patient-derived tissues, evidence suggesting that a large fraction of the viral sequences is transcribed from integrated DNA copies of viral sequences, generating viral-host chimeric transcripts. The integration and transcription of viral sequences may thus contribute to the detection of viral RNA by PCR in patients after infection and clinical recovery. Because we have detected only subgenomic sequences derived mainly from the 3' end of the viral genome integrated into the DNA of the host cell, infectious virus cannot be produced from the integrated subgenomic SARS-CoV-2 sequences.

Separation of Nuclear and Cytoplasmic Fractions for Chimeric RNA Characterization.

Cellular organelle fractionation, a basic technique in molecular biology, has been devised to separate various cell components, which can then be purified and analyzed biochemically. Isolation of proteins or RNAs from these fractions provides insight into fraction-specific or even organelle-specific expression, which may indicate potential modes of functionality or likelihood for a transcript to encode a protein. These findings can be further utilized to observe differences in expression between normal and diseased cell states, such as cancer. We utilize these techniques to observe expression of chimeric RNAs in these fractions. Within this chapter we describe the most frequently used cellular fractionation technique: the separation of the cytoplasmic fraction from the nuclear fraction in a cell.

Case Study: Landscape of Chimeric RNAs in Bladder Cancer.

Chimeric RNAs and their products have been shown to be closely associated with tumorigenicity and development in a variety of tumors, making them attractive diagnostic markers and therapeutic targets. In previous chapters, we introduced related research techniques and methods for studying chimeric RNAs. Here, we present an overview of the landscape of chimeric RNAs in bladder cancer and verification of two fusion transcripts which are associated with bladder cancer. We used bioinformatics to analyze the TCGA bladder urothelial carcinoma RNA-sequencing dataset, which contains 414 bladder cancer samples and 19 matched normal samples. We identified 19,547 chimeric RNAs and applied multiple criteria to avoid false positives, reducing this list to 271 high-confidence chimeric RNAs, 13 of which specifically expressed in cancer. We validated 6 of these chimeric in clinical bladder cancer samples, including CHFR-GOLGA3, which was found to be expressed significantly higher in bladder cancer samples in comparison to matched normal samples. We have determined that this chimeric RNA is produced by cis-splicing between adjacent genes (cis-SAGe). Further, we found that CHFR-GOLGA3 is mainly expressed in the nucleus, suggesting that it may not encode chimeric protein and instead act as noncoding RNA. Our findings establish the chimeric landscape of bladder cancer and provide a research strategy for how to conduct chimeric RNA research in other tumors.

Identification of chimeric RNAs in human infant brains and their implications in neural differentiation.

Chimeric RNAs are transcripts composed of RNA fragments from different genes and are traditionally well-known cancer-causing genetic events. Recent studies show chimeric RNAs being present in multiple non-neoplastic tissues and cells, suggesting that at least some may have roles in normal physiology. However, chimeric RNAs and their implications in brain development and neural differentiation have not been formally studied. Here, we firstly characterized the landscape of chimeric RNAs in human infant brain tissues and identified 599 chimeric RNAs. Through a series of filtering, 22 were selected and tested in a neural differentiation process starting from stem cells. Ten were validated experimentally. One of these ten chimeric RNAs, DUS4L-BCAP29, dramatically increased when human umbilical mesenchymal stem cells were induced for neural differentiation. Consistently, we found that overexpressed DUS4L-BCAP29 effectively promoted neural differentiation. Our results support the important role(s) chimeric RNAs play in neural differentiation, and are consistent with the new notion that chimeric RNAs also exist in normal physiology, and likely serve biological purposes.

The landscape of chimeric RNAs in bladder urothelial carcinoma.

BACKGROUND: Gene fusions and products have been identified as oncogenic drivers in many cancers, making them attractive diagnostic markers and therapeutic targets. However, the landscape of fusion transcripts in bladder cancer has not been fully characterized. METHODS: To identify fusion transcripts with potential therapeutic or diagnostic values, TCGA bladder urothelial carcinoma RNA-sequencing dataset was used. In order to avoid false positives, we applied multiple criteria including filtering out fusions detected in normal samples from GTEx dataset. We validated a subset of candidate fusions with a collection of bladder cancer and adjacent normal samples. RESULT: We identified 19,547 high confidence fusion genes from 414 bladder cancer samples. After filtering off M/M fusions, fusions in GTEx normal samples, and occurrence frequency <5, we obtained a list of 271 gene fusions, 13 of which were novel and specific to cancer samples. Six of those fusions were validated using cell lines and clinical samples. We discovered that two chimeric RNAs, BCL2L2-PABPN1 and CHFR-GOLGA3, were detected to be expressed significantly higher in bladder cancer samples compared to adjacent normal samples. Impressively, the wild-type of the parental genes were not differentially expressed. Mechanistically, we demonstrated that these two fusions are generated by cis-splicing between adjacent genes. These two fusions were detected mainly in the fraction of cell nucleus, suggesting a potential long noncoding RNA role. CONCLUSION: Our findings provide a panoramic view of the landscape of chimeric RNAs in bladder cancer. Some frequent chimeric RNAs are generated by intergenic splicing, and represent a new repertoire for potential biomarkers.

RNA-Seq Analysis to Detect Abnormal Fusion Transcripts Linked to Chromothripsis.

RNA-Seq approach enables the detection and characterization of fusion or chimeric transcript associated to complex genome rearrangement. Until now, these events are classically identified at DNA level.Here we describe a complete procedure including a novel way of analyzing reads that combines genomic locations and local coverage to directly infer chimeric junctions with a high sensitivity and specificity, allowing identification of different classes of chimeric RNA events. We also recommend the best practices for the bioinformatics analysis and describe the experimental process for RNA validation using real-time PCR and sequencing.

On the evaluation of the fidelity of supervised classifiers in the prediction of chimeric RNAs.

BACKGROUND: High-throughput sequencing technology and bioinformatics have identified chimeric RNAs (chRNAs), raising the possibility of chRNAs expressing particularly in diseases can be used as potential biomarkers in both diagnosis and prognosis. RESULTS: The task of discriminating true chRNAs from the false ones poses an interesting Machine Learning (ML) challenge. First of all, the sequencing data may contain false reads due to technical artifacts and during the analysis process, bioinformatics tools may generate false positives due to methodological biases. Moreover, if we succeed to have a proper set of observations (enough sequencing data) about true chRNAs, chances are that the devised model can not be able to generalize beyond it. Like any other machine learning problem, the first big issue is finding the good data to build models. As far as we were concerned, there is no common benchmark data available for chRNAs detection. The definition of a classification baseline is lacking in the related literature too. In this work we are moving towards benchmark data and an evaluation of the fidelity of supervised classifiers in the prediction of chRNAs. CONCLUSIONS: We proposed a modelization strategy that can be used to increase the tools performances in context of chRNA classification based on a simulated data generator, that permit to continuously integrate new complex chimeric events. The pipeline incorporated a genome mutation process and simulated RNA-seq data. The reads within distinct depth were aligned and analysed by CRAC that integrates genomic location and local coverage, allowing biological predictions at the read scale. Additionally, these reads were functionally annotated and aggregated to form chRNAs events, making it possible to evaluate ML methods (classifiers) performance in both levels of reads and events. Ensemble learning strategies demonstrated to be more robust to this classification problem, providing an average AUC performance of 95 % (ACC=94 %, Kappa=0.87 %). The resulting classification models were also tested on real RNA-seq data from a set of twenty-seven patients with acute myeloid leukemia (AML).

Hypothesis: Artifacts, Including Spurious Chimeric RNAs with a Short Homologous Sequence, Caused by Consecutive Reverse Transcriptions and Endogenous Random Primers.

Recent RNA-sequencing technology and associated bioinformatics have led to identification of tens of thousands of putative human chimeric RNAs, i.e. RNAs containing sequences from two different genes, most of which are derived from neighboring genes on the same chromosome. In this essay, we redefine "two neighboring genes" as those producing individual transcripts, and point out two known mechanisms for chimeric RNA formation, i.e. transcription from a fusion gene or trans-splicing of two RNAs. By our definition, most putative RNA chimeras derived from canonically-defined neighboring genes may either be technical artifacts or be cis-splicing products of 5'- or 3'-extended RNA of either partner that is redefined herein as an unannotated gene, whereas trans-splicing events are rare in human cells. Therefore, most authentic chimeric RNAs result from fusion genes, about 1,000 of which have been identified hitherto. We propose a hypothesis of "consecutive reverse transcriptions (RTs)", i.e. another RT reaction following the previous one, for how most spurious chimeric RNAs, especially those containing a short homologous sequence, may be generated during RT, especially in RNA-sequencing wherein RNAs are fragmented. We also point out that RNA samples contain numerous RNA and DNA shreds that can serve as endogenous random primers for RT and ensuing polymerase chain reactions (PCR), creating artifacts in RT-PCR.