InFusion: Advancing Discovery of Fusion Genes and Chimeric Transcripts from Deep RNA-Sequencing Data

Gene structure alterations, such as chromosomal rearrangements that develop fusion genes, often contribute to tumorigenesis. It has been shown that the fusion genes identified in public RNA-sequencing datasets are mainly derived from intrachromosomal rearrangements. In this study, we explored fusion transcripts in clinical ovarian cancer specimens based on our RNA-sequencing data. We successfully identified an in-frame fusion transcript SPON1-TRIM29 in chromosome 11 from a recurrent tumor specimen of high-grade serous carcinoma (HGSC), which was not detected in the corresponding primary carcinoma, and validated the expression of the identical fusion transcript in another tumor from a distinct HGSC patient. Ovarian cancer A2780 cells stably expressing SPON1-TRIM29 exhibited an increase in cell growth, whereas a decrease in apoptosis was observed, even in the presence of anticancer drugs. The siRNA-mediated silencing of SPON1-TRIM29 fusion transcript substantially impaired the enhanced growth of A2780 cells expressing the chimeric gene treated with anticancer drugs. Moreover, a subcutaneous xenograft model using athymic mice indicated that SPON1-TRIM29-expressing A2780 cells rapidly generated tumors in vivo compared to control cells, whose growth was significantly repressed by the fusion-specific siRNA administration. Overall, the SPON1-TRIM29 fusion gene could be involved in carcinogenesis and chemotherapy resistance in ovarian cancer, and offers potential use as a diagnostic and therapeutic target for the disease with the fusion transcript.

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FusionCatcher - a tool for finding somatic fusion genes in paired-end RNA-sequencing data

10.1101/011650 ◽

2014 ◽

Cited By ~ 118

Author(s):

Daniel Nicorici ◽

Mihaela Satalan ◽

Henrik Edgren ◽

Sara Kangaspeska ◽

Astrid Murumagi ◽

...

Keyword(s):

Real Time ◽

Tumor Cells ◽

Rna Sequencing ◽

Real Time Pcr ◽

Software Tool ◽

Fusion Genes ◽

Sequencing Data ◽

Detection Rates ◽

Somatic Fusion

FusionCatcher is a software tool for finding somatic fusion genes in paired-end RNA-sequencing data from human or other vertebrates. FusionCatcher achieves competitive detection rates and real-time PCR validation rates in RNA-sequencing data from tumor cells. FusionCatcher is available at http://code.google.com/p/fusioncatcher

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Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data

Molecular Genetics and Genomics ◽

10.1007/s00438-018-1454-1 ◽

2018 ◽

Vol 293 (5) ◽

pp. 1217-1229

Author(s):

Sakrapee Paisitkriangkrai ◽

Kelly Quek ◽

Eva Nievergall ◽

Anissa Jabbour ◽

Andrew Zannettino ◽

...

Keyword(s):

Rna Sequencing ◽

Analysis Tool ◽

Fusion Genes ◽

Sequencing Data ◽

New Class ◽

Class Discovery

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Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms

PLoS ONE ◽

10.1371/journal.pone.0048745 ◽

2012 ◽

Vol 7 (10) ◽

pp. e48745 ◽

Cited By ~ 40

Author(s):

Sara Kangaspeska ◽

Susanne Hultsch ◽

Henrik Edgren ◽

Daniel Nicorici ◽

Astrid Murumägi ◽

...

Keyword(s):

Rna Sequencing ◽

Fusion Genes ◽

Sequencing Data

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

Nucleic Acids Research ◽

10.1093/nar/gks1041 ◽

2012 ◽

Vol 41 (D1) ◽

pp. D142-D151 ◽

Cited By ~ 29

Author(s):

Milana Frenkel-Morgenstern ◽

Alessandro Gorohovski ◽

Vincent Lacroix ◽

Mark Rogers ◽

Kristina Ibanez ◽

...

Keyword(s):

Rna Sequencing ◽

Fruit Fly ◽

Sequencing Data ◽

Chimeric Transcripts

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HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Genes ◽

10.3390/genes12010120 ◽

2021 ◽

Vol 12 (1) ◽

pp. 120

Author(s):

Yiyun Sun ◽

Dandan Xu ◽

Chundong Zhang ◽

Yitao Wang ◽

Lian Zhang ◽

...

Keyword(s):

Rna Sequencing ◽

Squamous Cell ◽

Gene Pair ◽

Gene List ◽

Ectopic Expression ◽

Lung Squamous Cell Carcinoma ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Gene Set

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.

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RNA Sequencing Data from Human Intracranial Aneurysm Tissue Reveals a Complex Inflammatory Environment Associated with Rupture

Molecular Diagnosis & Therapy ◽

10.1007/s40291-021-00552-4 ◽

2021 ◽

Author(s):

Vincent M. Tutino ◽

Haley R. Zebraski ◽

Hamidreza Rajabzadeh-Oghaz ◽

Lee Chaves ◽

Adam A. Dmytriw ◽

...

Keyword(s):

Intracranial Aneurysm ◽

Rna Sequencing ◽

Sequencing Data

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Mixed Distribution Models Based on Single-Cell RNA Sequencing Data

Interdisciplinary Sciences Computational Life Sciences ◽

10.1007/s12539-021-00427-6 ◽

2021 ◽

Author(s):

Min Wu ◽

Junhua Xu ◽

Tao Ding ◽

Jie Gao

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Sequencing Data ◽

Distribution Models ◽

Mixed Distribution ◽

Single Cell Rna Sequencing

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In-depth transcriptomic analysis of human retina reveals molecular mechanisms underlying diabetic retinopathy

Scientific Reports ◽

10.1038/s41598-021-88698-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kolja Becker ◽

Holger Klein ◽

Eric Simon ◽

Coralie Viollet ◽

Christian Haslinger ◽

...

Keyword(s):

Diabetic Retinopathy ◽

Rna Sequencing ◽

Molecular Mechanisms ◽

Vision Loss ◽

Ganglion Cells ◽

Expression Profiles ◽

Cell Types ◽

Sequencing Data ◽

Disease Stages ◽

Post Transcriptional Regulation

AbstractDiabetic Retinopathy (DR) is among the major global causes for vision loss. With the rise in diabetes prevalence, an increase in DR incidence is expected. Current understanding of both the molecular etiology and pathways involved in the initiation and progression of DR is limited. Via RNA-Sequencing, we analyzed mRNA and miRNA expression profiles of 80 human post-mortem retinal samples from 43 patients diagnosed with various stages of DR. We found differentially expressed transcripts to be predominantly associated with late stage DR and pathways such as hippo and gap junction signaling. A multivariate regression model identified transcripts with progressive changes throughout disease stages, which in turn displayed significant overlap with sphingolipid and cGMP–PKG signaling. Combined analysis of miRNA and mRNA expression further uncovered disease-relevant miRNA/mRNA associations as potential mechanisms of post-transcriptional regulation. Finally, integrating human retinal single cell RNA-Sequencing data revealed a continuous loss of retinal ganglion cells, and Müller cell mediated changes in histidine and β-alanine signaling. While previously considered primarily a vascular disease, attention in DR has shifted to additional mechanisms and cell-types. Our findings offer an unprecedented and unbiased insight into molecular pathways and cell-specific changes in the development of DR, and provide potential avenues for future therapeutic intervention.

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COVID-19 Severity Potentially Modulated by Cardiovascular-Disease-Associated Immune Dysregulation

Viruses ◽

10.3390/v13061018 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1018

Author(s):

Abby C. Lee ◽

Grant Castaneda ◽

Wei Tse Li ◽

Chengyu Chen ◽

Neil Shende ◽

...

Keyword(s):

Rna Sequencing ◽

Mononuclear Cells ◽

Human Peripheral Blood ◽

Expression Profiles ◽

Immune Dysregulation ◽

Left Ventricular ◽

Recurrent Event ◽

Healthy Controls ◽

Sequencing Data ◽

Peripheral Blood Mononuclear

Patients with underlying cardiovascular conditions are particularly vulnerable to severe COVID-19. In this project, we aimed to characterize similarities in dysregulated immune pathways between COVID-19 patients and patients with cardiomyopathy, venous thromboembolism (VTE), or coronary artery disease (CAD). We hypothesized that these similarly dysregulated pathways may be critical to how cardiovascular diseases (CVDs) exacerbate COVID-19. To evaluate immune dysregulation in different diseases, we used four separate datasets, including RNA-sequencing data from human left ventricular cardiac muscle samples of patients with dilated or ischemic cardiomyopathy and healthy controls; RNA-sequencing data of whole blood samples from patients with single or recurrent event VTE and healthy controls; RNA-sequencing data of human peripheral blood mononuclear cells (PBMCs) from patients with and without obstructive CAD; and RNA-sequencing data of platelets from COVID-19 subjects and healthy controls. We found similar immune dysregulation profiles between patients with CVDs and COVID-19 patients. Interestingly, cardiomyopathy patients display the most similar immune landscape to COVID-19 patients. Additionally, COVID-19 patients experience greater upregulation of cytokine- and inflammasome-related genes than patients with CVDs. In all, patients with CVDs have a significant overlap of cytokine- and inflammasome-related gene expression profiles with that of COVID-19 patients, possibly explaining their greater vulnerability to severe COVID-19.

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