Evolutionary impact of chimeric RNAs on generating phenotypic plasticity in human cells.

Chimeric RNAs are generated by the fusion of the exons or introns of two genes. The generation of chimeric RNAs is important for the functional expansion of cells. Here, we describe the functional implications of chimeric RNAs for generating phenotypic plasticity from an evolutionary perspective.

COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics.

The recent outbreak of COVID-19 has generated an enormous amount of Big Data. To date, the COVID-19 Open Research Dataset (CORD-19), lists ∼130,000 articles from the WHO COVID-19 database, PubMed Central, medRxiv, and bioRxiv, as collected by Semantic Scholar. According to LitCovid (11 August 2020), ∼40,300 COVID19-related articles are currently listed in PubMed. It has been shown in clinical settings that the analysis of past research results and the mining of available data can provide novel opportunities for the successful application of currently approved therapeutics and their combinations for the treatment of conditions caused by a novel SARS-CoV-2 infection. As such, effective responses to the pandemic require the development of efficient applications, methods and algorithms for data navigation, text-mining, clustering, classification, analysis, and reasoning. Thus, our COVID19 Drug Repository represents a modular platform for drug data navigation and analysis, with an emphasis on COVID-19-related information currently being reported. The COVID19 Drug Repository enables users to focus on different levels of complexity, starting from general information about (FDA-) approved drugs, PubMed references, clinical trials, recipes as well as the descriptions of molecular mechanisms of drugs' action. Our COVID19 drug repository provide a most updated world-wide collection of drugs that has been repurposed for COVID19 treatments around the world.

ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps.

Chimeric RNA transcripts are formed when exons from two genes fuse together, often due to chromosomal translocations, transcriptional errors or trans-splicing effect. While these chimeric RNAs produce functional proteins only in certain cases, they play a significant role in disease phenotyping and progression. ChiTaRS 5.0 (http://chitars.md.biu.ac.il/) is the latest and most comprehensive chimeric transcript repository, with 111 582 annotated entries from eight species, including 23 167 known human cancer breakpoints. The database includes unique information correlating chimeric breakpoints with 3D chromatin contact maps, generated from public datasets of chromosome conformation capture techniques (Hi-C). In this update, we have added curated information on druggable fusion targets matched with chimeric breakpoints, which are applicable to precision medicine in cancers. The introduction of a new section that lists chimeric RNAs in various cell-lines is another salient feature. Finally, using text-mining techniques, novel chimeras in Alzheimer's disease, schizophrenia, dyslexia and other diseases were collected in ChiTaRS. Thus, this improved version is an extensive catalogue of chimeras from multiple species. It extends our understanding of the evolution of chimeric transcripts in eukaryotes and contributes to the analysis of 3D genome conformational changes and the functional role of chimeras in the etiopathogenesis of cancers and other complex diseases.

ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins.

Tailored therapy aims to cure cancer patients effectively and safely, based on the complex interactions between patients' genomic features, disease pathology and drug metabolism. Thus, the continual increase in scientific literature drives the need for efficient methods of data mining to improve the extraction of useful information from texts based on patients' genomic features. An important application of text mining to tailored therapy in cancer encompasses the use of mutations and cancer fusion genes as moieties that change patients' cellular networks to develop cancer, and also affect drug metabolism. Fusion proteins, which are derived from the slippage of two parental genes, are produced in cancer by chromosomal aberrations and trans-splicing. Given that the two parental proteins for predicted fusion proteins are known, we used our previously developed method for identifying chimeric protein-protein interactions (ChiPPIs) associated with the fusion proteins. Here, we present a validation approach that receives fusion proteins of interest, predicts their cellular network alterations by ChiPPI and validates them by our new method, ProtFus, using an online literature search. This process resulted in a set of 358 fusion proteins and their corresponding protein interactions, as a training set for a Naïve Bayes classifier, to identify predicted fusion proteins that have reliable evidence in the literature and that were confirmed experimentally. Next, for a test group of 1817 fusion proteins, we were able to identify from the literature 2908 PPIs in total, across 18 cancer types. The described method, ProtFus, can be used for screening the literature to identify unique cases of fusion proteins and their PPIs, as means of studying alterations of protein networks in cancers. Availability: http://protfus.md.biu.ac.il/.

Modulation of Cellular CpG DNA Methylation by Kaposi's Sarcoma-Associated Herpesvirus.

Kaposi's sarcoma-associated herpesvirus (KSHV, HHV-8) is a gammaherpesvirus associated with several human malignancies. DNA methylation at CpG dinucleotides is an epigenetic mark dysregulated in many cancer types and in KSHV-infected cells. Several previous studies have analyzed in detail the CpG methylation of the KSHV episomal genomes, but little is known about the impact of KSHV on the human genome. Our knowledge of cellular CpG methylation in the context of KSHV infection is currently limited to four hypermethylated human gene promoters. Therefore, we undertook a comprehensive CpG methylation analysis of the human methylome in KSHV-infected cells and KSHV-associated primary effusion lymphoma (PEL). We performed Infinium HumanMethylation450K and MethylationEpic BeadChip arrays and identified panels of hyper- and hypomethylated cellular promoters in KSHV-infected cells. We combined our genome-wide methylation analysis with high-throughput RNA sequencing (RNA-seq) to add functional outcomes to the virally induced methylation changes. We were able to correlate many downregulated genes with promoter hypermethylation and upregulated genes with hypomethylation. In addition, we show that treating the cells with a demethylating agent leads to reexpression of these downregulated genes, indicating that, indeed, DNA methylation plays a role in the repression of these human genes. Comparison between de novo infection and PEL suggests that the virus induces initial hypermethylation followed by a slow increase in genome-wide hypomethylation. This study extends our understanding of the relationship between epigenetic changes induced by KSHV infection and tumorigenesis.IMPORTANCE In cancer cells, certain promoters become aberrantly methylated, contributing to the phenotype of the tumor. KSHV infection seems to modify cellular CpG methylation, but only a few methylated promoters have been identified in KSHV-infected cells. Here, we investigated the CpG methylation of the human genome in KSHV-associated primary effusion lymphoma (PEL) and KSHV-infected cells. We have identified many hyper- and hypomethylated gene promoters and correlated their methylation with cellular gene expression. These differentially methylated cellular promoters can distinguish KSHV-positive cells from uninfected cells and may serve as the foundation for the use of these differentially methylated regions as potential biomarkers for KSHV-associated malignancies. Drugs that reverse these cancerous methylation patterns have the potential to inhibit tumor growth. Here, we show that treating PEL cells with a demethylating drug (5-aza-2'-deoxycytidine) led to inhibition of cell growth, raising the possibility of testing this drug for the treatment of PEL.

ChiTaRS-3.1-the enhanced chimeric transcripts and RNA-seq database matched with protein-protein interactions.

Discovery of chimeric RNAs, which are produced by chromosomal translocations as well as the joining of exons from different genes by trans-splicing, has added a new level of complexity to our study and understanding of the transcriptome. The enhanced ChiTaRS-3.1 database (http://chitars.md.biu.ac.il) is designed to make widely accessible a wealth of mined data on chimeric RNAs, with easy-to-use analytical tools built-in. The database comprises 34 922: chimeric transcripts along with 11 714: cancer breakpoints. In this latest version, we have included multiple cross-references to GeneCards, iHop, PubMed, NCBI, Ensembl, OMIM, RefSeq and the Mitelman collection for every entry in the 'Full Collection'. In addition, for every chimera, we have added a predicted Chimeric Protein-Protein Interaction (ChiPPI) network, which allows for easy visualization of protein partners of both parental and fusion proteins for all human chimeras. The database contains a comprehensive annotation for 34 922: chimeric transcripts from eight organisms, and includes the manual annotation of 200 sense-antiSense (SaS) chimeras. The current improvements in the content and functionality to the ChiTaRS database make it a central resource for the study of chimeric transcripts and fusion proteins.

ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.

Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein-protein interactions (ChiPPI) that uses the domain-domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF ß), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer.

Transcriptome, genetic editing, and microRNA divergence substantiate sympatric speciation of blind mole rat, Spalax.

Incipient sympatric speciation in blind mole rat, Spalax galili, in Israel, caused by sharp ecological divergence of abutting chalk-basalt ecologies, has been proposed previously based on mitochondrial and whole-genome nuclear DNA. Here, we present new evidence, including transcriptome, DNA editing, microRNA, and codon usage, substantiating earlier evidence for adaptive divergence in the abutting chalk and basalt populations. Genetic divergence, based on the previous and new evidence, is ongoing despite restricted gene flow between the two populations. The principal component analysis, neighbor-joining tree, and genetic structure analysis of the transcriptome clearly show the clustered divergent two mole rat populations. Gene-expression level analysis indicates that the population transcriptome divergence is displayed not only by soil divergence but also by sex. Gene ontology enrichment of the differentially expressed genes from the two abutting soil populations highlights reproductive isolation. Alternative splicing variation of the two abutting soil populations displays two distinct splicing patterns. L-shaped FST distribution indicates that the two populations have undergone divergence with gene flow. Transcriptome divergent genes highlight neurogenetics and nutrition characterizing the chalk population, and energetics, metabolism, musculature, and sensory perception characterizing the abutting basalt population. Remarkably, microRNAs also display divergence between the two populations. The GC content is significantly higher in chalk than in basalt, and stress-response genes mostly prefer nonoptimal codons. The multiple lines of evidence of ecological-genomic and genetic divergence highlight that natural selection overrules the gene flow between the two abutting populations, substantiating the sharp ecological chalk-basalt divergence driving sympatric speciation.

ChiTaRS 2.1--an improved database of the chimeric transcripts and RNA-seq data with novel sense-antisense chimeric RNA transcripts.

Chimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS 2.1 database of chimeric transcripts and RNA-Seq data (http://chitars.bioinfo.cnio.es/) is the second version of the ChiTaRS database and includes improvements in content and functionality. Chimeras from eight organisms have been collated including novel sense-antisense (SAS) chimeras resulting from the slippage of the sense and anti-sense intragenic regions. The new database version collects more than 29,000 chimeric transcripts and indicates the expression and tissue specificity for 333 entries confirmed by RNA-seq reads mapping the chimeric junction sites. User interface allows for rapid and easy analysis of evolutionary conservation of fusions, literature references and experimental data supporting fusions in different organisms. More than 1428 cancer breakpoints have been automatically collected from public databases and manually verified to identify their correct cross-references, genomic sequences and junction sites. As a result, the ChiTaRS 2.1 collection of chimeras from eight organisms and human cancer breakpoints extends our understanding of the evolution of chimeric transcripts in eukaryotes as well as their functional role in carcinogenic processes.

Chimeras taking shape: potential functions of proteins encoded by chimeric RNA transcripts.

Chimeric RNAs comprise exons from two or more different genes and have the potential to encode novel proteins that alter cellular phenotypes. To date, numerous putative chimeric transcripts have been identified among the ESTs isolated from several organisms and using high throughput RNA sequencing. The few corresponding protein products that have been characterized mostly result from chromosomal translocations and are associated with cancer. Here, we systematically establish that some of the putative chimeric transcripts are genuinely expressed in human cells. Using high throughput RNA sequencing, mass spectrometry experimental data, and functional annotation, we studied 7424 putative human chimeric RNAs. We confirmed the expression of 175 chimeric RNAs in 16 human tissues, with an abundance varying from 0.06 to 17 RPKM (Reads Per Kilobase per Million mapped reads). We show that these chimeric RNAs are significantly more tissue-specific than non-chimeric transcripts. Moreover, we present evidence that chimeras tend to incorporate highly expressed genes. Despite the low expression level of most chimeric RNAs, we show that 12 novel chimeras are translated into proteins detectable in multiple shotgun mass spectrometry experiments. Furthermore, we confirm the expression of three novel chimeric proteins using targeted mass spectrometry. Finally, based on our functional annotation of exon organization and preserved domains, we discuss the potential features of chimeric proteins with illustrative examples and suggest that chimeras significantly exploit signal peptides and transmembrane domains, which can alter the cellular localization of cognate proteins. Taken together, these findings establish that some chimeric RNAs are translated into potentially functional proteins in humans.

ChiTaRS: a database of human, mouse and fruit fly chimeric transcripts and RNA-sequencing data.

Chimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS database of Chimeric Transcripts and RNA-Sequencing data (http://chitars.bioinfo.cnio.es/) collects more than 16 000 chimeric RNAs from humans, mice and fruit flies, 233 chimeras confirmed by RNA-seq reads and ∼2000 cancer breakpoints. The database indicates the expression and tissue specificity of these chimeras, as confirmed by RNA-seq data, and it includes mass spectrometry results for some human entries at their junctions. Moreover, the database has advanced features to analyze junction consistency and to rank chimeras based on the evidence of repeated junction sites. Finally, 'Junction Search' screens through the RNA-seq reads found at the chimeras' junction sites to identify putative junctions in novel sequences entered by users. Thus, ChiTaRS is an extensive catalog of human, mouse and fruit fly chimeras that will extend our understanding of the evolution of chimeric transcripts in eukaryotes and can be advantageous in the analysis of human cancer breakpoints.

The UGG Isoacceptor of tRNAPro Is Naturally Prone to Frameshifts.

Native tRNAs often contain post-transcriptional modifications to the wobble position to expand the capacity of reading the genetic code. Some of these modifications, due to the ability to confer imperfect codon-anticodon pairing at the wobble position, can induce a high propensity for tRNA to shift into alternative reading frames. An example is the native UGG isoacceptor of E. coli tRNAPro whose wobble nucleotide U34 is post-transcriptionally modified to cmo5U34 to read all four proline codons (5'-CCA, 5'-CCC, 5'-CCG, and 5'-CCU). Because the pairing of the modified anticodon to CCC codon is particularly weak relative to CCA and CCG codons, this tRNA can readily shift into both the +1 and +2-frame on the slippery mRNA sequence CCC-CG. We show that the shift to the +2-frame is more dominant, driven by the higher stability of the codon-anticodon pairing at the wobble position. Kinetic analysis suggests that both types of shifts can occur during stalling of the tRNA in a post-translocation complex or during translocation from the A to the P-site. Importantly, while the +1-frame post complex is active for peptidyl transfer, the +2-frame complex is a poor peptidyl donor. Together with our recent work, we draw a mechanistic distinction between +1 and +2-frameshifts, showing that while the +1-shifts are suppressed by the additional post-transcriptionally modified m1G37 nucleotide in the anticodon loop, the +2-shifts are suppressed by the ribosome, supporting a role of the ribosome in the overall quality control of reading-frame maintenance.

Novel domain combinations in proteins encoded by chimeric transcripts.

MOTIVATION: Chimeric RNA transcripts are generated by different mechanisms including pre-mRNA trans-splicing, chromosomal translocations and/or gene fusions. It was shown recently that at least some of chimeric transcripts can be translated into functional chimeric proteins. RESULTS: To gain a better understanding of the design principles underlying chimeric proteins, we have analyzed 7,424 chimeric RNAs from humans. We focused on the specific domains present in these proteins, comparing their permutations with those of known human proteins. Our method uses genomic alignments of the chimeras, identification of the gene-gene junction sites and prediction of the protein domains. We found that chimeras contain complete protein domains significantly more often than in random data sets. Specifically, we show that eight different types of domains are over-represented among all chimeras as well as in those chimeras confirmed by RNA-seq experiments. Moreover, we discovered that some chimeras potentially encode proteins with novel and unique domain combinations. Given the observed prevalence of entire protein domains in chimeras, we predict that certain putative chimeras that lack activation domains may actively compete with their parental proteins, thereby exerting dominant negative effects. More generally, the production of chimeric transcripts enables a combinatorial increase in the number of protein products available, which may disturb the function of parental genes and influence their protein-protein interaction network. AVAILABILITY: our scripts are available upon request.

Genes adopt non-optimal codon usage to generate cell cycle-dependent oscillations in protein levels.

The cell cycle is a temporal program that regulates DNA synthesis and cell division. When we compared the codon usage of cell cycle-regulated genes with that of other genes, we discovered that there is a significant preference for non-optimal codons. Moreover, genes encoding proteins that cycle at the protein level exhibit non-optimal codon preferences. Remarkably, cell cycle-regulated genes expressed in different phases display different codon preferences. Here, we show empirically that transfer RNA (tRNA) expression is indeed highest in the G2 phase of the cell cycle, consistent with the non-optimal codon usage of genes expressed at this time, and lowest toward the end of G1, reflecting the optimal codon usage of G1 genes. Accordingly, protein levels of human glycyl-, threonyl-, and glutamyl-prolyl tRNA synthetases were found to oscillate, peaking in G2/M phase. In light of our findings, we propose that non-optimal (wobbly) matching codons influence protein synthesis during the cell cycle. We describe a new mathematical model that shows how codon usage can give rise to cell-cycle regulation. In summary, our data indicate that cells exploit wobbling to generate cell cycle-dependent dynamics of proteins.

Functional and regulatory impact of chimeric RNAs in human normal and cancer cells.

Fusions of two genes can lead to the generation of chimeric RNAs, which may have a distinct functional role from their original molecules. Chimeric RNAs could encode novel functional proteins or serve as novel long noncoding RNAs (lncRNAs). The appearance of chimeric RNAs in a cell could help to generate new functionality and phenotypic diversity that might facilitate this cell to survive against new environmental stress. Several recent studies have demonstrated the functional roles of various chimeric RNAs in cancer progression and are considered as biomarkers for cancer diagnosis and sometimes even drug targets. Further, the growing evidence demonstrated the potential functional association of chimeric RNAs with cancer heterogeneity and drug resistance cancer evolution. Recent studies highlighted that chimeric RNAs also have functional potentiality in normal physiological processes. Several functionally potential chimeric RNAs were discovered in human cancer and normal cells in the last two decades. This could indicate that chimeric RNAs are the hidden layer of the human transcriptome that should be explored from the functional insights to better understand the functional evolution of the genome and disease development that could facilitate clinical practice improvements. This review summarizes the current knowledge of chimeric RNAs and highlights their functional, regulatory, and evolutionary impact on different cancers and normal physiological processes. Further, we will discuss the potential functional roles of a recently discovered novel class of chimeric RNAs named sense-antisense/cross-strand chimeric RNAs generated by the fusion of the bi-directional transcripts of the same gene. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

The landscape of differential splicing and transcript alternations in severe COVID-19 infection.

Viral infections can modulate the widespread alternations of cellular splicing, favouring viral replication within the host cells by overcoming host immune responses. However, how SARS-CoV-2 induces host cell differential splicing and affects the landscape of transcript alternation in severe COVID-19 infection remains elusive. Understanding the differential splicing and transcript alternations in severe COVID-19 infection may improve our molecular insights into the SARS-CoV-2 pathogenesis. In this study, we analysed the publicly available blood and lung transcriptome data of severe COVID-19 patients, blood transcriptome data of recovered COVID-19 patients at 12-, 16- and 24-week postinfection and healthy controls. We identified a significant transcript isoform switching in the individual blood and lung RNA-seq data of severe COVID-19-infected patients and 25 common genes that alter their transcript isoform in both blood and lung samples. Altered transcripts show significant loss of the open reading frame, functional domains and switch from coding to noncoding transcript, impacting normal cellular functions. Furthermore, we identified the expression of several novel recurrent chimeric transcripts in the blood samples from severe COVID-19 patients. Moreover, the analysis of the isoform switching into blood samples from recovered COVID-19 patients highlights that there is no significant isoform switching in 16- and 24-week postinfection, and the levels of expressed chimeric transcripts are reduced. This finding emphasizes that SARS-CoV-2 severe infection induces widespread splicing in the host cells, which could help the virus alter the host immune responses and facilitate the viral replication within the host and the efficient translation of viral proteins.

The Landscape of Expressed Chimeric Transcripts in the Blood of Severe COVID-19 Infected Patients.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 infections has quickly developed into a global public health threat. COVID-19 patients show distinct clinical features, and in some cases, during the severe stage of the condition, the disease severity leads to an acute respiratory disorder. In spite of several pieces of research in this area, the molecular mechanisms behind the development of disease severity are still not clearly understood. Recent studies demonstrated that SARS-CoV-2 alters the host cell splicing and transcriptional response to overcome the host immune response that provides the virus with favorable conditions to replicate efficiently within the host cells. In several disease conditions, aberrant splicing could lead to the development of novel chimeric transcripts that could promote the functional alternations of the cell. As severe SARS-CoV-2 infection was reported to cause abnormal splicing in the infected cells, we could expect the generation and expression of novel chimeric transcripts. However, no study so far has attempted to check whether novel chimeric transcripts are expressed in severe SARS-CoV-2 infections. In this study, we analyzed several publicly available blood transcriptome datasets of severe COVID-19, mild COVID-19, other severe respiratory viral infected patients, and healthy individuals. We identified 424 severe COVID-19 -specific chimeric transcripts, 42 of which were recurrent. Further, we detected 189 chimeric transcripts common to severe COVID-19 and multiple severe respiratory viral infections. Pathway and gene enrichment analysis of the parental genes of these two subsets of chimeric transcripts reveals that these are potentially involved in immune-related processes, interferon signaling, and inflammatory responses, which signify their potential association with immune dysfunction leading to the development of disease severity. Our study provides the first detailed expression landscape of chimeric transcripts in severe COVID-19 and other severe respiratory viral infections.

Dynamic Proteomics: a database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells.

Recent advances allow tracking the levels and locations of a thousand proteins in individual living human cells over time using a library of annotated reporter cell clones (LARC). This library was created by Cohen et al. to study the proteome dynamics of a human lung carcinoma cell-line treated with an anti-cancer drug. Here, we report the Dynamic Proteomics database for the proteins studied by Cohen et al. Each cell-line clone in LARC has a protein tagged with yellow fluorescent protein, expressed from its endogenous chromosomal location, under its natural regulation. The Dynamic Proteomics interface facilitates searches for genes of interest, downloads of protein fluorescent movies and alignments of dynamics following drug addition. Each protein in the database is displayed with its annotation, cDNA sequence, fluorescent images and movies obtained by the time-lapse microscopy. The protein dynamics in the database represents a quantitative trace of the protein fluorescence levels in nucleus and cytoplasm produced by image analysis of movies over time. Furthermore, a sequence analysis provides a search and comparison of up to 50 input DNA sequences with all cDNAs in the library. The raw movies may be useful as a benchmark for developing image analysis tools for individual-cell dynamic-proteomics. The database is available at http://www.dynamicproteomics.net/.

The Landscape of Novel Expressed Chimeric RNAs in Rheumatoid Arthritis.

In cancers and other complex diseases, the fusion of two genes can lead to the production of chimeric RNAs, which are associated with disease development. Several recurrent chimeric RNAs are expressed in different cancers and are thus used for clinical cancer diagnosis. Rheumatoid arthritis (RA) is an immune-mediated joint disorder resulting in synovial inflammation and joint destruction. Despite advances in therapy, many patients do not respond to treatment and present persistent inflammation. Understanding the landscape of chimeric RNA expression in RA patients could provide a better insight into RA pathogenesis, which might provide better treatment strategies and tailored therapies. Accordingly, we analyzed the publicly available RNA-seq data of synovium tissue from 151 RA patients and 28 healthy controls and were able to identify 37 recurrent chimeric RNAs found to be expressed in at least 3 RA samples. Furthermore, the parental genes of these 37 recurrent chimeric RNAs were found to be differentially expressed and enriched in immune-related processes, such as adaptive immune response and the positive regulation of B-cell activation. Interestingly, the appearance of 5 coding and 23 non-coding chimeric RNAs might be associated with regulating their parental gene expression, leading to the generation of dysfunctional immune responses, such as inflammation and bone destruction. Therefore, in this paper, we present the first study to demonstrate the novel chimeric RNAs that are highly expressed and functional in RA.