Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples

Dysregulation of endothelial colony-forming cell function by a negative feedback loop of circulating miR-146a and -146b in cardiovascular disease patients

Functional impairment of endothelial colony-forming cells (ECFCs), a specific cell lineage of endothelial progenitor cells (EPCs) is highly associated with the severity of coronary artery disease (CAD), the most common type of cardiovascular disease (CVD). Emerging evidence show that circulating microRNAs (miRNAs) in CAD patients’ body fluid hold a great potential as biomarkers. However, our knowledge of the role of circulating miRNA in regulating the function of ECFCs and the progression of CAD is still in its infancy. We showed that when ECFCs from healthy volunteers were incubated with conditioned medium or purified exosomes of cultured CAD ECFCs, the secretory factors from CAD ECFCs dysregulated migration and tube formation ability of healthy ECFCs. It is known that exosomes influence the physiology of recipient cells by introducing RNAs including miRNAs. By using small RNA sequencing (smRNA-seq), we deciphered the circulating miRNome in the plasma of healthy individual and CAD patients, and found that the plasma miRNA spectrum from CAD patients was significantly different from that of healthy control. Interestingly, smRNA-seq of both healthy and CAD ECFCs showed that twelve miRNAs that had a higher expression in the plasma of CAD patients also showed higher expression in CAD ECFCs when compared with healthy control. This result suggests that these miRNAs may be involved in the regulation of ECFC functions. For identification of potential mRNA targets of the differentially expressed miRNA in CAD patients, cDNA microarray analysis was performed to identify the angiogenesis-related genes that were down-regulated in CAD ECFCs and Pearson’s correlation were used to identify miRNAs that were negatively correlated with the identified angiogenesis-related genes. RT-qPCR analysis of the five miRNAs that negatively correlated with the down-regulated angiogenesis-related genes in plasma and ECFC of CAD patients showed miR-146a-5p and miR-146b-5p up-regulation compared to healthy control. Knockdown of miR-146a-5p or miR-146b-5p in CAD ECFCs enhanced migration and tube formation activity in diseased ECFCs. Contrarily, overexpression of miR-146a-5p or miR-146b-5p in healthy ECFC repressed migration and tube formation in ECFCs. TargetScan analysis showed that miR-146a-5p and miR-146b-5p target many of the angiogenesis-related genes that were down-regulated in CAD ECFCs. Knockdown of miR-146a-5p or miR-146b-5p restores CAV1 and RHOJ levels in CAD ECFCs. Reporter assays confirmed the direct binding and repression of miR-146a-5p and miR-146b-5p to the 3’-UTR of mRNA of RHOJ, a positive regulator of angiogenic potential in endothelial cells. Consistently, RHOJ knockdown inhibited the migration and tube formation ability in ECFCs. Collectively, we discovered the dysregulation of miR-146a-5p/RHOJ and miR-146b-5p/RHOJ axis in the plasma and ECFCs of CAD patients that could be used as biomarkers or therapeutic targets for CAD and other angiogenesis-related diseases.

Relevance of Fusion Genes in Pediatric Cancers: Toward Precision Medicine

Pediatric cancers differ from adult tumors, especially by their very low mutational rate. Therefore, their etiology could be explained in part by other oncogenic mechanisms such as chromosomal rearrangements, supporting the possible implication of fusion genes in the development of pediatric cancers. Fusion genes result from chromosomal rearrangements leading to the juxtaposition of two genes. Consequently, an abnormal activation of one or both genes is observed. The detection of fusion genes has generated great interest in basic cancer research and in the clinical setting, since these genes can lead to better comprehension of the biological mechanisms of tumorigenesis and they can also be used as therapeutic targets and diagnostic or prognostic biomarkers. In this review, we discuss the molecular mechanisms of fusion genes and their particularities in pediatric cancers, as well as their relevance in murine models and in the clinical setting. We also point out the difficulties encountered in the discovery of fusion genes. Finally, we discuss future perspectives and priorities for finding new innovative therapies in childhood cancer.

A novel read-through transcript JMJD7-PLA2G4B regulates head and neck squamous cell carcinoma cell proliferation and survival

Recent findings on the existence of oncogenic fusion genes in a wide array of solid tumors, including head and neck squamous cell carcinoma (HNSCC), suggests that fusion genes have become attractive targets for cancer diagnosis and treatment. In this study, we showed for the first time that a read-through fusion gene JMJD7-PLA2G4B is presented in HNSCC, splicing neighboring jumonji domain containing 7 (JMJD7) and phospholipase A2, group IVB (PLA2G4B) genes together. Ablation of JMJD7-PLA2G4B significantly inhibited proliferation of HNSCC cells by promoting G1 cell cycle arrest and increased starvation-induced cell death compared to JMJD7-only knockdown HNSCC cells. Mechanistically, we found that JMJD7-PLA2G4B modulates phosphorylation of Protein Kinase B (AKT) to promote HNSCC cell survival. Moreover, JMJD7-PLA2G4B also regulated an E3 ligase S-phase kinase-associated protein 2 (SKP2) to control the cell cycle progression from G1 phase to S phase by inhibiting Cyclin-dependent kinase inhibitor 1 (p21) and 1B (p27) expression. Our study provides novel insights into the oncogenic control of JMJD7-PLA2G4B in HNSCC cell proliferation and survival, and suggests that JMJD7-PLA2G4B may serve as an important therapeutic target and prognostic marker for HNSCC development and progression.

Overexpression of KLHL23 protein from read-through transcription of PHOSPHO2-KLHL23 in gastric cancer increases cell proliferation

Gene fusion, as a prototypical pathognomonic mutation, contributes to genome complexity, and the cis‐transcription‐induced gene fusions generated by read‐through transcription of adjacent genes have been found to be important for tumor development. We screened read‐through transcription events from stomach adenocarcinoma RNA‐seq data and selected three candidates PHOSPHO2‐KLHL23, RPL17‐C18orf32, and PRR5‐ARHGAP8, to assess their biological role in gastric cancer. The expression of all three read‐through fusion transcripts was confirmed in gastric cancer cell lines and paired normal/tumor gastric cancer tissues by real‐time quantitative reverse transcription polymerase chain reaction and their expression was found to be significantly higher in the tumor (P < 0.05; n = 75). The correlation between the expression level and clinicopathological information was statistically analyzed. The level of the PHOSPHO2‐KLHL23 read‐through fusion transcript correlated with the Lauren classification and was significantly associated with the presence of perineural invasion. Overexpression of KLHL23 from PHOSPHO2‐KLHL23 read‐through transcript led to a significant increase in cell proliferation and resistance to anticancer drug treatment. Silencing of KLHL23 expression decreased cyclin D1 levels. The expression of KLHL23 from prevalent read‐through transcripts of PHOSPHO2‐KLHL23 in gastric cancer may undermine the efficacy of anticancer drug treatment.

Intergenically Spliced Chimeric RNAs in Cancer

Gene fusions and their encoded products (fusion RNAs and proteins) are viewed as one of the hallmarks of cancer. Traditionally, they were thought to be generated solely by chromosomal rearrangements. However, recent discoveries of trans-splicing and cis-splicing events between neighboring genes, suggest that there are other mechanisms to generate chimeric fusion RNAs without corresponding changes in DNA. In addition, chimeric RNAs have been detected in normal physiology, complicating the use of fusions in cancer detection and therapy. On the other hand, "intergenically spliced" fusion RNAs represent a new repertoire of biomarkers and therapeutic targets. Here, we review current knowledge on chimeric RNAs and implications for cancer detection and treatment, and discuss outstanding questions for the advancement of the field.

Cytogenetic and molecular profile of endometrial stromal sarcoma

Recent cytogenetic and molecular investigations have improved our understanding of endometrial stromal tumors, including sarcomas (ESS), and helped redefine their classification into more pathogenetically meaningful categories. Because much more can be gained through such studies, we add information on another 22 ESS examined by karyotyping, PCR analysis, expression array analysis, and transcriptome sequencing. In spite of the known preference for certain pathogenetic pathways, we found considerable genetic heterogeneity in high‐grade (HG) as well as in low‐grade (LG) ESS. Not all HG tumors showed a YWHAE‐NUTM chimeric transcript and as many as six LGESS showed no hitherto known ESS‐related fusions. Among the transcripts identified by transcriptome sequencing and verified by Sanger sequencing, new variants of ZC3H7‐BCOR and its reciprocal BCOR‐ZC3H7 were identified as was involvement of the CREBBP and MLLT4 genes (both well known leukemia‐related genes) in two new fusions. FISH analysis identified a known EPC1‐PHF1 fusion which led to the identification of a new variant at the molecular level. The fact that around 70 genes were found differentially expressed, by microarray analysis, when comparing LGESS showing ESS‐related fusions with LGESS without such transcripts, underscores the biochemical importance of the observed genetic heterogeneity and hints that new subgroups/entities in LGESS still remain undiscovered. © 2016 The Authors. Genes, Chromosomes & Cancer Published by Wiley Periodicals, Inc.

Omics Profiling in Precision Oncology

Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology.

Novel fusion genes and chimeric transcripts in ependymal tumors

We have previously identified two ALK rearrangements in a subset of ependymal tumors using a combination of cytogenetic data and RNA sequencing. The aim of this study was to perform an unbiased search for fusion transcripts in our entire series of ependymal tumors. Fusion analysis was performed using the FusionCatcher algorithm on 12 RNA-sequenced ependymal tumors. Candidate transcripts were prioritized based on the software's filtering and manual visualization using the BLAST (Basic Local Alignment Search Tool) and BLAT (BLAST-like alignment tool) tools. Genomic and reverse transcriptase PCR with subsequent Sanger sequencing was used to validate the potential fusions. Fluorescent in situ hybridization (FISH) using locus-specific probes was also performed. A total of 841 candidate chimeric transcripts were identified in the 12 tumors, with an average of 49 unique candidate fusions per tumor. After algorithmic and manual filtering, the final list consisted of 24 potential fusion events. Raw RNA-seq read sequences and PCR validation supports two novel fusion genes: a reciprocal fusion gene involving UQCR10 and C1orf194 in an adult spinal ependymoma and a TSPAN4-CD151 fusion gene in a pediatric infratentorial anaplastic ependymoma. Our previously reported ALK rearrangements and the RELA and YAP1 fusions found in supratentorial ependymomas were until now the only known fusion genes present in ependymal tumors. The chimeric transcripts presented here are the first to be reported in infratentorial or spinal ependymomas. Further studies are required to characterize the genomic rearrangements causing these fusion genes, as well as the frequency and functional importance of the fusions. © 2016 Wiley Periodicals, Inc.

Open questions in the study of de novo genes: what, how and why

The study of de novo protein-coding genes is maturing from the ad hoc reporting of individual cases to the systematic analysis of extensive genomic data from several species. We identify three key challenges for this emerging field: understanding how best to identify de novo genes, how they arise and why they spread. We highlight the intellectual challenges of understanding how a de novo gene becomes integrated into pre-existing functions and becomes essential. We suggest that, as with protein sequence evolution, antagonistic co-evolution may be key to de novo gene evolution, particularly for new essential genes and new cancer-associated genes.

Recurrent and pathological gene fusions in breast cancer: current advances in genomic discovery and clinical implications

Gene fusions have long been considered principally as the oncogenic events of hematologic malignancies, but have recently gained wide attention in solid tumors due to several milestone discoveries and the advancement of deep sequencing technologies. With the progress in deep sequencing studies of breast cancer transcriptomes and genomes, the discovery of recurrent and pathological gene fusions in breast cancer is on the focus. Recently, driven by new deep sequencing studies, several recurrent or pathological gene fusions have been identified in breast cancer, including ESR1-CCDC170, SEC16A-NOTCH1, SEC22B-NOTCH2, and ESR1-YAP1 etc. More important, most of these gene fusions are preferentially identified in the more aggressive breast cancers, such as luminal B, basal-like, or endocrine-resistant breast cancer, suggesting recurrent gene fusions as additional key driver events in these tumors other than the known drivers such as the estrogen receptor. In this paper, we have comprehensively summarized the newly identified recurrent or pathological gene fusion events in breast cancer, reviewed the contributions of new genomic and deep sequencing technologies to new fusion discovery and the integrative bioinformatics tools to analyze these data, highlighted the biological relevance and clinical implications of these fusion discoveries, and discussed future directions of gene fusion research in breast cancer.

Discovering and understanding oncogenic gene fusions through data intensive computational approaches

Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale computational biology. The computational work on gene fusions has been vastly diverse, and the present state of the literature is fragmented. It will be fruitful to merge three camps of gene fusion bioinformatics that appear to rarely cross over: (i) data-intensive computational work characterizing the molecular biology of gene fusions; (ii) development research on fusion detection tools, candidate fusion prioritization algorithms and dedicated fusion databases and (iii) clinical research that seeks to either therapeutically target fusion transcripts and proteins or leverages advances in detection tools to perform large-scale surveys of gene fusion landscapes in specific cancer types. In this review, we unify these different-yet highly complementary and symbiotic-approaches with the view that increased synergy will catalyze advancements in gene fusion identification, characterization and significance evaluation.

Microseminoprotein-Beta Expression in Different Stages of Prostate Cancer

Microseminoprotein-beta (MSMB, MSMB) is an abundant secretory protein contributed by the prostate, and is implicated as a prostate cancer (PC) biomarker based on observations of its lower expression in cancerous cells compared with benign prostate epithelium. However, as the current literature on MSMB is inconsistent, we assessed the expression of MSMB at the protein and mRNA levels in a comprehensive set of different clinical stages of PC. Immunohistochemistry using monoclonal and polyclonal antibodies against MSMB was used to study protein expression in tissue specimens representing prostatectomies (n = 261) and in diagnostic needle biopsies from patients treated with androgen deprivation therapy (ADT) (n = 100), and in locally recurrent castration-resistant PC (CRPC) (n = 105) and CRPC metastases (n = 113). The transcript levels of MSMB, nuclear receptor co-activator 4 (NCOA4) and MSMB-NCOA4 fusion were examined by qRT-PCR in prostatectomy samples and by RNA-sequencing in benign prostatic hyperplasia, PC, and CRPC samples. We also measured serum MSMB levels and genotyped the single nucleotide polymorphism rs10993994 using DNA from the blood of 369 PC patients and 903 controls. MSMB expression in PC (29% of prostatectomies and 21% of needle biopsies) was more frequent than in CRPC (9% of locally recurrent CRPCs and 9% of CRPC metastases) (p<0.0001). Detection of MSMB protein was inversely correlated with the Gleason score in prostatectomy specimens (p = 0.024). The read-through MSMB-NCOA4 transcript was detected at very low levels in PC. MSMB levels in serum were similar in cases of PC and controls but were significantly associated with PC risk when adjusted for age at diagnosis and levels of free or total PSA (p<0.001). Serum levels of MSMB in both PC patients and controls were significantly associated with the rs10993994 genotype (p<0.0001). In conclusion, decreased expression of MSMB parallels the clinical progression of PC and adjusted serum MSMB levels are associated with PC risk.

Fusion genes in malignant neoplastic disorders of haematopoietic system

OBJECTIVES

The new World Health Organization's (WHO) classification of haematopoietic and lymphoid tissue neoplasms incorporating the recurrent fusion genes as the defining criteria for different haematopoietic malignant phenotypes is reviewed. The recurrent fusion genes incorporated in the new WHO's classification and other chromosomal rearrangements of haematopoietic and lymphoid tissue neoplasms are reviewed.

METHODOLOGY

Cytokines and transcription factors in haematopoiesis and leukaemic mechanisms are described. Genetic features and clinical implications due to the encoded chimeric neoproteins causing malignant haematopoietic disorders are reviewed.

RESULTS AND DISCUSSION

Multiple translocation partner genes are well known for leukaemia such as MYC, MLL, RARA, ALK, and RUNX1. With the advent of more sophisticated diagnostic tools and bioinformatics algorithms, an exponential growth in fusion genes discoveries is likely to increase.

CONCLUSION

Demonstration of fusion genes and their specific translocation breakpoints in malignant haematological disorders are crucial for understanding the molecular pathogenesis and clinical phenotype of cancer, determining prognostic indexes and therapeutic responses, and monitoring residual disease and relapse status.

Novel fusion transcripts in bladder cancer identified by RNA-seq

Urothelial carcinoma (UC) is the most common type of bladder cancer and is the second most frequently diagnosed genitourinary tumor. The identification of fusion genes in bladder cancer might provide new perspectives for its classification and significance. In this study, we present a thorough search on three UC samples for novel fusion transcripts in bladder cancer using high-throughput RNA sequencing. We used stringent requirements for 819 fusion candidates and nominated 10 candidate fusion transcripts. Among them four novel fusion genes SEPT9/CYHR, IGF1R/TTC23, SYT8/TNNI2 and CASZ1/DFFA were validated and characterized in 48 formalin-fixed paraffin-embedded (FFPE) specimens of bladder cancer. Chromosomal rearrangements of regions 17q25, 15q26.3 and 1p36.22 resulting in the fusion transcripts SEPT9/CYHR, IGF1R/TTC23 and CASZ1/DFFA, appeared to be rare or unique events because they were not detected in the 48 UC samples. In contrast, the SYT8/TNNI2 fusion transcript resulting from transcription-induced chimerism by read-through mechanisms was a rather common and tumor-specific event occurring in 37.5% (18/48) of the UC specimens. Further investigation of functional and clinical relevance of novel fusion genes remains to be elucidated to reveal their role in bladder carcinogenesis.

Recurrent chimeric fusion RNAs in non-cancer tissues and cells

Gene fusions and their products (RNA and protein) were once thought to be unique features to cancer. However, chimeric RNAs can also be found in normal cells. Here, we performed, curated and analyzed nearly 300 RNA-Seq libraries covering 30 different non-neoplastic human tissues and cells as well as 15 mouse tissues. A large number of fusion transcripts were found. Most fusions were detected only once, while 291 were seen in more than one sample. We focused on the recurrent fusions and performed RNA and protein level validations on a subset. We characterized these fusions based on various features of the fusions, and their parental genes. They tend to be expressed at higher levels relative to their parental genes than the non-recurrent ones. Over half of the recurrent fusions involve neighboring genes transcribing in the same direction. A few sequence motifs were found enriched close to the fusion junction sites. We performed functional analyses on a few widely expressed fusions, and found that silencing them resulted in dramatic reduction in normal cell growth and/or motility. Most chimeras use canonical splicing sites, thus are likely products of 'intergenic splicing'. We also explored the implications of these non-pathological fusions in cancer and in evolution.

PTESFinder: a computational method to identify post-transcriptional exon shuffling (PTES) events

BACKGROUND

Transcripts, which have been subject to Post-transcriptional exon shuffling (PTES), have an exon order inconsistent with the underlying genomic sequence. These have been identified in a wide variety of tissues and cell types from many eukaryotes, and are now known to be mostly circular, cytoplasmic, and non-coding. Although there is no uniformly ascribed function, several have been shown to be involved in gene regulation. Accurate identification of these transcripts can, however, be difficult due to artefacts from a wide variety of sources.

RESULTS

Here, we present a computational method, PTESFinder, to identify these transcripts from high throughput RNAseq data. Uniquely, it systematically excludes potential artefacts emanating from pseudogenes, segmental duplications, and template switching, and outputs both PTES and canonical exon junction counts to facilitate comparative analyses. In comparison with four existing methods, PTESFinder achieves highest specificity and comparable sensitivity at a variety of read depths. PTESFinder also identifies between 13 % and 41.6 % more structures, compared to publicly available methods recently used to identify human circular RNAs.

CONCLUSIONS

With high sensitivity and specificity, user-adjustable filters that target known sources of false positives, and tailored output to facilitate comparison of transcript levels, PTESFinder will facilitate the discovery and analysis of these poorly understood transcripts.

GMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality

The programs GMAP and GSNAP, for aligning RNA-Seq and DNA-Seq datasets to genomes, have evolved along with advances in biological methodology to handle longer reads, larger volumes of data, and new types of biological assays. The genomic representation has been improved to include linear genomes that can compare sequences using single-instruction multiple-data (SIMD) instructions, compressed genomic hash tables with fast access using SIMD instructions, handling of large genomes with more than four billion bp, and enhanced suffix arrays (ESAs) with novel data structures for fast access. Improvements to the algorithms have included a greedy match-and-extend algorithm using suffix arrays, segment chaining using genomic hash tables, diagonalization using segmental hash tables, and nucleotide-level dynamic programming procedures that use SIMD instructions and eliminate the need for F-loop calculations. Enhancements to the functionality of the programs include standardization of indel positions, handling of ambiguous splicing, clipping and merging of overlapping paired-end reads, and alignments to circular chromosomes and alternate scaffolds. The programs have been adapted for use in pipelines by integrating their usage into R/Bioconductor packages such as gmapR and HTSeqGenie, and these pipelines have facilitated the discovery of numerous biological phenomena.

Fusion transcript loci share many genomic features with non-fusion loci

BACKGROUND

Fusion transcripts are found in many tissues and have the potential to create novel functional products. Here, we investigate the genomic sequences around fusion junctions to better understand the transcriptional mechanisms mediating fusion transcription/splicing. We analyzed data from prostate (cancer) cells as previous studies have shown extensively that these cells readily undergo fusion transcription.

RESULTS

We used the FusionMap program to identify high-confidence fusion transcripts from RNAseq data. The RNAseq datasets were from our (N = 8) and other (N = 14) clinical prostate tumors with adjacent non-cancer cells, and from the LNCaP prostate cancer cell line that were mock-, androgen- (DHT), and anti-androgen- (bicalutamide, enzalutamide) treated. In total, 185 fusion transcripts were identified from all RNAseq datasets. The majority (76%) of these fusion transcripts were 'read-through chimeras' derived from adjacent genes in the genome. Characterization of sequences at fusion loci were carried out using a combination of the FusionMap program, custom Perl scripts, and the RNAfold program. Our computational analysis indicated that most fusion junctions (76%) use the consensus GT-AG intron donor-acceptor splice site, and most fusion transcripts (85%) maintained the open reading frame. We assessed whether parental genes of fusion transcripts have the potential to form complementary base pairing between parental genes which might bring them into physical proximity. Our computational analysis of sequences flanking fusion junctions at parental loci indicate that these loci have a similar propensity as non-fusion loci to hybridize. The abundance of repetitive sequences at fusion and non-fusion loci was also investigated given that SINE repeats are involved in aberrant gene transcription. We found few instances of repetitive sequences at both fusion and non-fusion junctions. Finally, RT-qPCR was performed on RNA from both clinical prostate tumors and adjacent non-cancer cells (N = 7), and LNCaP cells treated as above to validate the expression of seven fusion transcripts and their respective parental genes. We reveal that fusion transcript expression is similar to the expression of parental genes.

CONCLUSIONS

Fusion transcripts maintain the open reading frame, and likely use the same transcriptional machinery as non-fusion transcripts as they share many genomic features at splice/fusion junctions.

NCLscan: accurate identification of non-co-linear transcripts (fusion, trans-splicing and circular RNA) with a good balance between sensitivity and precision

Analysis of RNA-seq data often detects numerous ‘non-co-linear’ (NCL) transcripts, which comprised sequence segments that are topologically inconsistent with their corresponding DNA sequences in the reference genome. However, detection of NCL transcripts involves two major challenges: removal of false positives arising from alignment artifacts and discrimination between different types of NCL transcripts (trans-spliced, circular or fusion transcripts). Here, we developed a new NCL-transcript-detecting method (‘NCLscan’), which utilized a stepwise alignment strategy to almost completely eliminate false calls (>98% precision) without sacrificing true positives, enabling NCLscan outperform 18 other publicly-available tools (including fusion- and circular-RNA-detecting tools) in terms of sensitivity and precision, regardless of the generation strategy of simulated dataset, type of intragenic or intergenic NCL event, read depth of coverage, read length or expression level of NCL transcript. With the high accuracy, NCLscan was applied to distinguishing between trans-spliced, circular and fusion transcripts on the basis of poly(A)- and nonpoly(A)-selected RNA-seq data. We showed that circular RNAs were expressed more ubiquitously, more abundantly and less cell type-specifically than trans-spliced and fusion transcripts. Our study thus describes a robust pipeline for the discovery of NCL transcripts, and sheds light on the fundamental biology of these non-canonical RNA events in human transcriptome.

Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes

Alternative splicing is a widespread process contributing to structural transcript variation and proteome diversity. In cancer, the splicing process is commonly disrupted, resulting in both functional and non-functional end-products. Cancer-specific splicing events are known to contribute to disease progression; however, the dysregulated splicing patterns found on a genome-wide scale have until recently been less well-studied. In this review, we provide an overview of aberrant RNA splicing and its regulation in cancer. We then focus on the executors of the splicing process. Based on a comprehensive catalog of splicing factor encoding genes and analyses of available gene expression and somatic mutation data, we identify cancer-associated patterns of dysregulation. Splicing factor genes are shown to be significantly differentially expressed between cancer and corresponding normal samples, and to have reduced inter-individual expression variation in cancer. Furthermore, we identify enrichment of predicted cancer-critical genes among the splicing factors. In addition to previously described oncogenic splicing factor genes, we propose 24 novel cancer-critical splicing factors predicted from somatic mutations.

The emerging complexity of gene fusions in cancer

Structural chromosome rearrangements may result in the exchange of coding or regulatory DNA sequences between genes. Many such gene fusions are strong driver mutations in neoplasia and have provided fundamental insights into the disease mechanisms that are involved in tumorigenesis. The close association between the type of gene fusion and the tumour phenotype makes gene fusions ideal for diagnostic purposes, enabling the subclassification of otherwise seemingly identical disease entities. In addition, many gene fusions add important information for risk stratification, and increasing numbers of chimeric proteins encoded by the gene fusions serve as specific targets for treatment, resulting in dramatically improved patient outcomes. In this Timeline article, we describe the spectrum of gene fusions in cancer and how the methods to identify them have evolved, and also discuss conceptual implications of current, sequencing-based approaches for detection.

RNA sequencing of sarcomas with simple karyotypes: identification and enrichment of fusion transcripts

Gene fusions are neoplasia-associated mutations arising from structural chromosomal rearrangements. They have a strong impact on tumor development and constitute important diagnostic markers. Malignant soft tissue tumors (sarcomas) constitute a heterogeneous group of neoplasms with >50 distinct subtypes, each of which is rare. In addition, there is considerable morphologic overlap between sarcomas and benign lesions. Several subtypes display distinct gene fusions, serving as excellent biomarkers. The development of methods for deep sequencing of the complete transcriptome (RNA-Seq) has substantially improved the possibilities for detecting gene fusions. With the aim of identifying new gene fusions of biological and clinical relevance, eight sarcomas with simple karyotypes, ie, only one or a few structural rearrangements, were subjected to massively parallel paired-end sequencing of mRNA. Three different algorithms were used to identify fusion transcripts from RNA-Seq data. Three novel (KIAA2026-NUDT11, CCBL1-ARL1, and AFF3-PHF1) and two previously known fusions (FUS-CREB3L2 and HAS2-PLAG1) were found and could be verified by other methods. These findings show that RNA-Seq is a powerful tool for detecting gene fusions in sarcomas but also suggest that it is advisable to use more than one algorithm to analyze the output data as only two of the confirmed fusions were reported by more than one of the gene fusion detection software programs. For all of the confirmed gene fusions, at least one of the genes mapped to a chromosome band implicated by the karyotype, suggesting that sarcomas with simple karyotypes constitute an excellent resource for identifying novel gene fusions.

Splice variants and regulatory networks associated with host resistance to the intestinal worm Cooperia oncophora in cattle

To elucidate the molecular mechanism of host resistance, we characterized the jejunal transcriptome of Angus cattle selected for parasite resistance for over 20 years in response to infection caused by the intestinal worm Cooperia oncophora. The transcript abundance of 56 genes, such as that of mucin 12 (MUC12) and intestinal alkaline phosphatase (ALPI), was significantly higher in resistant cattle. Novel splicing variants, exon skipping events, and gene fusion events, were also detected. An algorithm for the reconstruction of accurate cellular networks (ARACNE) was used to infer de novo regulatory molecular networks in the interactome between the parasite and host. Under a combined cutoff of an error tolerance (ϵ = 0.10) and a stringent P-value threshold of mutual information (1.0 × 10(-5)), a total of 229,100 direct interactions controlled by 20,288 hub genes were identified. Among these hub genes, 7651 genes had ≥ 100 direct neighbors while the top 9778 hub genes controlled more than 50% of total direct interactions. Three lysozyme genes (LYZ1, LYZ2, and LYZ3), which are co-located in bovine chromosome 5 in tandem and are strongly upregulated in resistant cattle, shared a common regulatory network of 55 genes. These ancient antimicrobials were likely involved in regulating host-parasite interactions by affecting host gut microbiome. Notably, ALPI, known as a gut mucosal defense factor, controlled a molecular network consisting 410 genes, including 14 transcription factors (TF) and 10 genes that were significantly regulated in resistant cattle. Several large regulatory networks were controlled by TF, such as STAT6, SREBF1, and ELF4. Gene ontology (GO) processes significantly enriched in the regulatory network controlled by STAT6 included lipid metabolism. Our findings provide insights into the immune regulation of host-parasite interactions and the molecular mechanisms of host resistance in cattle.

JAFFA: High sensitivity transcriptome-focused fusion gene detection

Genomic instability is a hallmark of cancer and, as such, structural alterations and fusion genes are common events in the cancer landscape. RNA sequencing (RNA-Seq) is a powerful method for profiling cancers, but current methods for identifying fusion genes are optimised for short reads. JAFFA (https://github.com/Oshlack/JAFFA/wiki) is a sensitive fusion detection method that outperforms other methods with reads of 100 bp or greater. JAFFA compares a cancer transcriptome to the reference transcriptome, rather than the genome, where the cancer transcriptome is inferred using long reads directly or by de novo assembling short reads.

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.

Functional characterization of BC039389-GATM and KLK4-KRSP1 chimeric read-through transcripts which are up-regulated in renal cell cancer

Background

Chimeric read-through RNAs are transcripts originating from two directly adjacent genes (<10 kb) on the same DNA strand. Although they are found in next-generation whole transcriptome sequencing (RNA-Seq) data on a regular basis, investigating them further has usually been refrained from. Therefore, their expression patterns or functions in general, and in oncogenesis in particular, are poorly understood.

Results

We used paired-end RNA-Seq and a specifically designed computational data analysis pipeline (FusionSeq) to nominate read-through events in a small discovery set of renal cell carcinomas (RCC) and confirmed them in a larger validation cohort.

324 read-through events were called overall; 22/27 (81%) selected nominees passed validation with conventional PCR and were sequenced at the junction region. We frequently identified various isoforms of a given read-through event. 2/22 read-throughs were up-regulated: BC039389-GATM was higher expressed in RCC compared to benign adjacent kidney; KLK4-KRSP1 was expressed in 46/169 (27%) RCCs, but rarely in normal tissue. KLK4-KRSP1 expression was associated with worse clinical outcome in the patient cohort. In cell lines, both read-throughs influenced molecular mechanisms (i.e. target gene expression or migration/invasion) in a way that counteracted the effect of the respective parent transcript GATM or KLK4.

Conclusions

Our data suggests that the up-regulation of read-through RNA chimeras in tumors is not random but causes regulatory effects on cellular mechanisms and may impact patient survival.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1446-z) contains supplementary material, which is available to authorized users.

Human serum amyloid A3 (SAA3) protein, expressed as a fusion protein with SAA2, binds the oxidized low density lipoprotein receptor

Serum amyloid A3 (SAA3) possesses characteristics distinct from the other serum amyloid A isoforms, SAA1, SAA2, and SAA4. High density lipoprotein contains the latter three isoforms, but not SAA3. The expression of mouse SAA3 (mSAA3) is known to be up-regulated extrahepatically in inflammatory responses, and acts as an endogenous ligand for the toll-like receptor 4/MD-2 complex. We previously reported that mSAA3 plays an important role in facilitating tumor metastasis by attracting circulating tumor cells and enhancing hyperpermeability in the lungs. On the other hand, human SAA3 (hSAA3) has long been regarded as a pseudogene, which is in contrast to the abundant expression levels of the other isoforms. Although the nucleotide sequence of hSAA3 is very similar to that of the other SAAs, a single oligonucleotide insertion in exon 2 causes a frame-shift to generate a unique amino acid sequence. In the present study, we identified that hSAA3 was transcribed in the hSAA2-SAA3 fusion transcripts of several human cell lines. In the fusion transcript, hSAA2 exon 3 was connected to hSAA3 exon 1 or hSAA3 exon 2, located approximately 130kb downstream from hSAA2 exon 3 in the genome, which suggested that it is produced by alternative splicing. Furthermore, we succeeded in detecting and isolating hSAA3 protein for the first time by an immunoprecipitation-enzyme linked immune assay system using monoclonal and polyclonal antibodies that recognize the hSAA3 unique amino acid sequence. We also demonstrated that hSAA3 bound oxidized low density lipoprotein receptor (oxLDL receptor, LOX-1) and elevated the phosphorylation of ERK, the intracellular MAP-kinase signaling protein.

Discovery of CTCF-sensitive Cis-spliced fusion RNAs between adjacent genes in human prostate cells

Genes or their encoded products are not expected to mingle with each other unless in some disease situations. In cancer, a frequent mechanism that can produce gene fusions is chromosomal rearrangement. However, recent discoveries of RNA trans-splicing and cis-splicing between adjacent genes (cis-SAGe) support for other mechanisms in generating fusion RNAs. In our transcriptome analyses of 28 prostate normal and cancer samples, 30% fusion RNAs on average are the transcripts that contain exons belonging to same-strand neighboring genes. These fusion RNAs may be the products of cis-SAGe, which was previously thought to be rare. To validate this finding and to better understand the phenomenon, we used LNCaP, a prostate cell line as a model, and identified 16 additional cis-SAGe events by silencing transcription factor CTCF and paired-end RNA sequencing. About half of the fusions are expressed at a significant level compared to their parental genes. Silencing one of the in-frame fusions resulted in reduced cell motility. Most out-of-frame fusions are likely to function as non-coding RNAs. The majority of the 16 fusions are also detected in other prostate cell lines, as well as in the 14 clinical prostate normal and cancer pairs. By studying the features associated with these fusions, we developed a set of rules: 1) the parental genes are same-strand-neighboring genes; 2) the distance between the genes is within 30kb; 3) the 5′ genes are actively transcribing; and 4) the chimeras tend to have the second-to-last exon in the 5′ genes joined to the second exon in the 3′ genes. We then randomly selected 20 neighboring genes in the genome, and detected four fusion events using these rules in prostate cancer and non-cancerous cells. These results suggest that splicing between neighboring gene transcripts is a rather frequent phenomenon, and it is not a feature unique to cancer cells.

Genes are considered the units of hereditary information; thus, neither genes nor their encoded products are expected to mingle with each other unless in some disease situations. However, the genes are not alone in the genome. Genes have neighbors, some close, some far. With RNA-seq, many fusion RNAs involving neighboring genes are being identified. However, little is done to validate and characterize the fusion RNAs. Using one prostate cell line and a discovery pipeline for cis-splicing between adjacent genes (cis-SAGe), we found 16 new such events. We then developed a set of rules based on the characteristics of these fusion RNAs, and applied them to 20 random neighboring gene pairs. Four turned out to be true. The majority of the fusions are found in cancer cells, as well as in non-cancer cells. These results suggest that the genes are “leaky”, and the fusions are not limited to cancer cells.

Chimeric RNAs as potential biomarkers for tumor diagnosis

Cancers claim millions of lives each year. Early detection that can enable a higher chance of cure is of paramount importance to cancer patients. However, diagnostic tools for many forms of tumors have been lacking. Over the last few years, studies of chimeric RNAs as biomarkers have emerged. Numerous reports using bioinformatics and screening methodologies have described more than 30,000 expressed sequence tags (EST) or cDNA sequences as putative chimeric RNAs. While cancer cells have been well known to contain fusion genes derived from chromosomal translocations, rearrangements or deletions, recent studies suggest that trans-splicing in cells may be another source of chimeric RNA production. Unlike cis-splicing, trans-splicing takes place between two pre-mRNA molecules, which are in most cases derived from two different genes, generating a chimeric non-co-linear RNA. It is possible that trans-splicing occurs in normal cells at high frequencies but the resulting chimeric RNAs exist only at low levels. However the levels of certain RNA chimeras may be elevated in cancers, leading to the formation of fusion genes. In light of the fact that chimeric RNAs have been shown to be overrepresented in various tumors, studies of the mechanisms that produce chimeric RNAs and identification of signature RNA chimeras as biomarkers present an opportunity for the development of diagnoses for early tumor detection.

Tandem RNA chimeras contribute to transcriptome diversity in human population and are associated with intronic genetic variants

Chimeric RNAs originating from two or more different genes are known to exist not only in cancer, but also in normal tissues, where they can play a role in human evolution. However, the exact mechanism of their formation is unknown. Here, we use RNA sequencing data from 462 healthy individuals representing 5 human populations to systematically identify and in depth characterize 81 RNA tandem chimeric transcripts, 13 of which are novel. We observe that 6 out of these 81 chimeras have been regarded as cancer-specific. Moreover, we show that a prevalence of long introns at the fusion breakpoint is associated with the chimeric transcripts formation. We also find that tandem RNA chimeras have lower abundances as compared to their partner genes. Finally, by combining our results with genomic data from the same individuals we uncover intronic genetic variants associated with the chimeric RNA formation. Taken together our findings provide an important insight into the chimeric transcripts formation and open new avenues of research into the role of intronic genetic variants in post-transcriptional processing events.

A comparative study of techniques for differential expression analysis on RNA-Seq data

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs) between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.

Chimeric RNAs generated by intergenic splicing in normal and cancer cells

A hallmark of many neoplasias is chromosomal rearrangement, an event that commonly results in the fusion of two separate genes. The RNA and protein resulting from these gene fusions often play critical roles in cancer development, maintenance, and progression. Traditionally, these fusion products are thought to be produced solely due to DNA level changes and are therefore considered unique to cancer. Recent advances in microarray and deep-sequencing have revealed many more fusion transcripts. Surprisingly, some are without detectable rearrangement at the DNA level. Reports have demonstrated that at least some of these chimeric RNAs are generated via intergenic splicing. In this review, we highlight three examples of these noncanonical chimeric transcripts that are formed by trans-splicing or cis-splicing of adjacent genes and summarize the knowledge we have regarding these noncanonical fusions. We discuss the implications of the chimeric RNAs in both cancer and normal physiology, as some of these fusion transcripts are found in normal, noncancerous cells with sequences identical to those generated by canonical chromosomal translocation found in cancer cells. Finally, we present methods that are currently being used to discover additional chimeric RNAs.

Is an observed non-co-linear RNA product spliced in trans, in cis or just in vitro?

Global transcriptome investigations often result in the detection of an enormous number of transcripts composed of non-co-linear sequence fragments. Such ‘aberrant’ transcript products may arise from post-transcriptional events or genetic rearrangements, or may otherwise be false positives (sequencing/alignment errors or in vitro artifacts). Moreover, post-transcriptionally non-co-linear (‘PtNcl’) transcripts can arise from trans-splicing or back-splicing in cis (to generate so-called ‘circular RNA’). Here, we collected previously-predicted human non-co-linear RNA candidates, and designed a validation procedure integrating in silico filters with multiple experimental validation steps to examine their authenticity. We showed that >50% of the tested candidates were in vitro artifacts, even though some had been previously validated by RT-PCR. After excluding the possibility of genetic rearrangements, we distinguished between trans-spliced and circular RNAs, and confirmed that these two splicing forms can share the same non-co-linear junction. Importantly, the experimentally-confirmed PtNcl RNA events and their corresponding PtNcl splicing types (i.e. trans-splicing, circular RNA, or both sharing the same junction) were all expressed in rhesus macaque, and some were even expressed in mouse. Our study thus describes an essential procedure for confirming PtNcl transcripts, and provides further insight into the evolutionary role of PtNcl RNA events, opening up this important, but understudied, class of post-transcriptional events for comprehensive characterization.

Recurrent read-through fusion transcripts in breast cancer

Read-through fusion transcripts that result from the splicing of two adjacent genes in the same coding orientation are a recently discovered type of chimeric RNA. We sought to determine if read-through fusion transcripts exist in breast cancer. We performed paired-end RNA-seq of 168 breast samples, including 28 breast cancer cell lines, 42 triple negative breast cancer primary tumors, 42 estrogen receptor positive (ER+) breast cancer primary tumors, and 56 non-malignant breast tissue samples. We analyzed the sequencing data to identify breast cancer associated read-through fusion transcripts. We discovered two recurrent read-through fusion transcripts that were identified in breast cancer cell lines, confirmed across breast cancer primary tumors, and were not detected in normal tissues (SCNN1A-TNFRSF1A and CTSD-IFITM10). Both fusion transcripts use canonical splice sites to join the last splice donor of the 5′ gene to the first splice acceptor of the 3′ gene, creating an in-frame fusion transcript. Western blots indicated that the fusion transcripts are translated into fusion proteins in breast cancer cells. Custom small interfering RNAs targeting the CTSD-IFITM10 fusion junction reduced expression of the fusion transcript and reduced breast cancer cell proliferation. Read-through fusion transcripts between adjacent genes with different biochemical functions represent a new type of recurrent molecular defect in breast cancer that warrant further investigation as potential biomarkers and therapeutic targets. Both breast cancer associated fusion transcripts identified in this study involve membrane proteins (SCNN1A-TNFRSF1A and CTSD-IFITM10), which raises the possibility that they could be breast cancer-specific cell surface markers.

Sequential combination of karyotyping and RNA-sequencing in the search for cancer-specific fusion genes

Cancer-specific fusion genes are often caused by cytogenetically visible chromosomal rearrangements such as translocations, inversions, deletions or insertions, they can be the targets of molecular therapy, they play a key role in the accurate diagnosis and classification of neoplasms, and they are of prognostic impact. The identification of novel fusion genes in various neoplasms therefore not only has obvious research importance, but is also potentially of major clinical significance. The "traditional" methodology to detect them began with cytogenetic analysis to find the chromosomal rearrangement, followed by utilization of fluorescence in situ hybridization techniques to find the probe which spans the chromosomal breakpoint, and finally molecular cloning to localize the breakpoint more precisely and identify the genes fused by the chromosomal rearrangement. Although laborious, the above-mentioned sequential approach is robust and reliable and a number of fusion genes have been cloned by such means. Next generation sequencing (NGS), mainly RNA sequencing (RNA-Seq), has opened up new possibilities to detect fusion genes even when cytogenetic aberrations are cryptic or information about them is unknown. However, NGS suffers from the shortcoming of identifying as "fusion genes" also many technical, biological and, perhaps in particular, clinical "false positives," thus making the assessment of which fusions are important and which are noise extremely difficult. The best way to overcome this risk of information overflow is, whenever reliable cytogenetic information is at hand, to compare karyotyping and sequencing data and concentrate exclusively on those suggested fusion genes that are found in chromosomal breakpoints. This article is part of a Directed Issue entitled: Rare Cancers.

Next-generation sequencing reveals novel rare fusion events with functional implication in prostate cancer

Gene fusions, mainly between TMPRSS2 and ERG, are frequent early genomic rearrangements in prostate cancer (PCa). In order to discover novel genomic fusion events, we applied whole-genome paired-end sequencing to identify structural alterations present in a primary PCa patient (G089) and in a PCa cell line (PC346C). Overall, we identified over 3800 genomic rearrangements in each of the two samples as compared with the reference genome. Correcting these structural variations for polymorphisms using whole-genome sequences of 46 normal samples, the numbers of cancer-related rearrangements were 674 and 387 for G089 and PC346C, respectively. From these, 192 in G089 and 106 in PC346C affected gene structures. Exclusion of small intronic deletions left 33 intergenic breaks in G089 and 14 in PC346C. Out of these, 12 and 9 reassembled genes with the same orientation, capable of generating a feasible fusion transcript. Using PCR we validated all the reliable predicted gene fusions. Two gene fusions were in-frame: MPP5-FAM71D in PC346C and ARHGEF3-C8ORF38 in G089. Downregulation of FAM71D and MPP5-FAM71D transcripts in PC346C cells decreased proliferation; however, no effect was observed in the RWPE-1-immortalized normal prostate epithelial cells. Together, our data showed that gene rearrangements frequently occur in PCa genomes but result in a limited number of fusion transcripts. Most of these fusion transcripts do not encode in-frame fusion proteins. The unique in-frame MPP5-FAM71D fusion product is important for proliferation of PC346C cells.

Recurrent rearrangements in prostate cancer: causes and therapeutic potential

DNA damage and genetic rearrangements are hallmarks of cancer. However, gene fusions as driver mutations in cancer have classically been a distinction in leukemia and other rare instances until recently with the discovery of gene fusion events occurring in 50 to 75% of prostate cancer patients. The discovery of the TMPRSS2-ERG fusion sparked an onslaught of discovery and innovation resulting in a delineation of prostate cancer via a molecular signature of gene fusion events. The increased commonality of high-throughput sequencing data coupled with improved bioinformatics approaches not only elucidated the molecular underpinnings of prostate cancer progression, but the mechanisms of gene fusion biogenesis. Interestingly, the androgen receptor (AR), already known to play a significant role in prostate cancer tumorigenesis, has recently been implicated in the processes resulting in gene fusions by inducing the spatial proximity of genes involved in rearrangements, promoting the formation of double-strand DNA breaks (DSB), and facilitating the recruitment of proteins for non-homologous end-joining (NHEJ). Our increased understanding of the mechanisms inducing genomic instability may lead to improved diagnostic and therapeutic strategies. To date, the majority of prostate cancer patients can be molecularly stratified based on their gene fusion status thereby increasing the potential for tailoring more specific and effective therapies.

An Island-Based Approach for Differential Expression Analysis

High-throughput mRNA sequencing (also known as RNA-Seq) promises to be the technique of choice for studying transcriptome profiles. This technique provides the ability to develop precise methodologies for transcript and gene expression quantification, novel transcript and exon discovery, and splice variant detection. One of the limitations of current RNA-Seq methods is the dependency on annotated biological features (e.g. exons, transcripts, genes) to detect expression differences across samples. This forces the identification of expression levels and the detection of significant changes to known genomic regions. Any significant changes that occur in unannotated regions will not be captured. To overcome this limitation, we developed a novel segmentation approach, Island-Based (IB), for analyzing differential expression in RNA-Seq and targeted sequencing (exome capture) data without specific knowledge of an isoform. The IB segmentation determines individual islands of expression based on windowed read counts that can be compared across experimental conditions to determine differential island expression. In order to detect differentially expressed genes, the significance of islands (p-values) are combined using Fisher's method. We tested and evaluated the performance of our approach by comparing it to the existing differentially expressed gene (DEG) methods: CuffDiff, DESeq, and edgeR using two benchmark MAQC RNA-Seq datasets. The IB algorithm outperforms all three methods in both datasets as illustrated by an increased auROC.

Comprehensive analysis of transcriptome variation uncovers known and novel driver events in T-cell acute lymphoblastic leukemia

RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations and gene expression perturbations. We asked whether RNA-seq is suitable for the detection of driver mutations in T-cell acute lymphoblastic leukemia (T-ALL). These leukemias are caused by a combination of gene fusions, over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq. First, we optimized the detection of SNVs in RNA-seq data by comparing the results with exome re-sequencing data. We identified known driver genes with recurrent protein altering variations, as well as several new candidates including H3F3A, PTK2B, and STAT5B. Next, we determined accurate gene expression levels from the RNA-seq data through normalizations and batch effect removal, and used these to classify patients into T-ALL subtypes. Finally, we detected gene fusions, of which several can explain the over-expression of key driver genes such as TLX1, PLAG1, LMO1, or NKX2-1; and others result in novel fusion transcripts encoding activated kinases (SSBP2-FER and TPM3-JAK2) or involving MLLT10. In conclusion, we present novel analysis pipelines for variant calling, variant filtering, and expression normalization on RNA-seq data, and successfully applied these for the detection of translocations, point mutations, INDELs, exon-skipping events, and expression perturbations in T-ALL.

The quest for somatic mutations underlying oncogenic processes is a central theme in today's cancer research. High-throughput genomics approaches including amplicon re-sequencing, exome re-sequencing, full genome re-sequencing, and SNP arrays have contributed to cataloguing driver genes across cancer types. Thus far transcriptome sequencing by RNA-seq has been mainly used for the detection of fusion genes, while few studies have assessed its value for the combined detection of SNPs, INDELs, fusions, gene expression changes, and alternative transcript events. Here we apply RNA-seq to 49 T-ALL samples and perform a critical assessment of the bioinformatics pipelines and filters to identify each type of aberration. By comparing to exome re-sequencing, and by exploiting the catalogues of known cancer drivers, we identified many known and several novel driver genes in T-ALL. We also determined an optimal normalization strategy to obtain accurate gene expression levels and used these to identify over-expressed transcription factors that characterize different T-ALL subtypes. Finally, by PCR, cloning, and in vitro cellular assays we uncover new fusion genes that have consequences at the level of gene expression, oncogenic chimaeras, and tumor suppressor inactivation. In conclusion, we present the first RNA-seq data set across T-ALL patients and identify new driver events.

Evolving techniques for gene fusion detection in soft tissue tumours

Chromosomal rearrangements resulting in the fusion of coding parts from two genes or in the exchange of regulatory sequences are present in approximately 20% of all human neoplasms. More than 1000 such gene fusions have now been described, with close to 100 of them in soft tissue tumours. Although little is still known about the functional outcome of many of these gene fusions, it is well established that most of them have a major impact on tumorigenesis. Furthermore, the strong association between type of gene fusion and morphological subtype makes them highly useful diagnostic markers. Until recently, the vast majority of gene fusions were identified through molecular cytogenetic characterization of rearrangements detected at chromosome banding analysis, followed by use of the reverse transcriptase-polymerase chain reaction (RT-PCR) and Sanger sequencing. With the advent of next-generation sequencing (NGS) technologies, notably of whole transcriptomes or all poly-A(+) mRNA molecules, the possibility of detecting new gene fusions has increased dramatically. Already, a large number of novel gene fusions have been identified through NGS approaches and it can be predicted that these technologies soon will become standard diagnostic clinical tools.

Integrative transcriptome sequencing identifies trans-splicing events with important roles in human embryonic stem cell pluripotency

Trans-splicing is a post-transcriptional event that joins exons from separate pre-mRNAs. Detection of trans-splicing is usually severely hampered by experimental artifacts and genetic rearrangements. Here, we develop a new computational pipeline, TSscan, which integrates different types of high-throughput long-/short-read transcriptome sequencing of different human embryonic stem cell (hESC) lines to effectively minimize false positives while detecting trans-splicing. Combining TSscan screening with multiple experimental validation steps revealed that most chimeric RNA products were platform-dependent experimental artifacts of RNA sequencing. We successfully identified and confirmed four trans-spliced RNAs, including the first reported trans-spliced large intergenic noncoding RNA (“tsRMST”). We showed that these trans-spliced RNAs were all highly expressed in human pluripotent stem cells and differentially expressed during hESC differentiation. Our results further indicated that tsRMST can contribute to pluripotency maintenance of hESCs by suppressing lineage-specific gene expression through the recruitment of NANOG and the PRC2 complex factor, SUZ12. Taken together, our findings provide important insights into the role of trans-splicing in pluripotency maintenance of hESCs and help to facilitate future studies into trans-splicing, opening up this important but understudied class of post-transcriptional events for comprehensive characterization.

Common fusion transcripts identified in colorectal cancer cell lines by high-throughput RNA sequencing

Colorectal cancer (CRC) is the third most common cancer disease in the Western world, and about 40% of the patients die from this disease. The cancer cells are commonly genetically unstable, but only a few low-frequency recurrent fusion genes have so far been reported for this disease. In this study, we present a thorough search for novel fusion transcripts in CRC using high-throughput RNA sequencing. From altogether 220 million paired-end sequence reads from seven CRC cell lines, we identified 3391 candidate fused transcripts. By stringent requirements, we nominated 11 candidate fusion transcripts for further experimental validation, of which 10 were positive by reverse transcription-polymerase chain reaction and Sanger sequencing. Six were intrachromosomal fusion transcripts, and interestingly, three of these, AKAP13-PDE8A, COMMD10-AP3S1, and CTB-35F21.1-PSD2, were present in, respectively, 18, 18, and 20 of 21 analyzed cell lines and in, respectively, 18, 61, and 48 (17%-58%) of 106 primary cancer tissues. These three fusion transcripts were also detected in 2 to 4 of 14 normal colonic mucosa samples (14%-28%). Whole-genome sequencing identified a specific genomic breakpoint in COMMD10-AP3S1 and further indicates that both the COMMD10-AP3S1 and AKAP13-PDE8A fusion transcripts are due to genomic duplications in specific cell lines. In conclusion, we have identified AKAP13-PDE8A, COMMD10-AP3S1, and CTB-35F21.1-PSD2 as novel intrachromosomal fusion transcripts and the most highly recurring chimeric transcripts described for CRC to date. The functional and clinical relevance of these chimeric RNA molecules remains to be elucidated.

Inferring the expression variability of human transposable element-derived exons by linear model analysis of deep RNA sequencing data

Background

The exonization of transposable elements (TEs) has proven to be a significant mechanism for the creation of novel exons. Existing knowledge of the retention patterns of TE exons in mRNAs were mainly established by the analysis of Expressed Sequence Tag (EST) data and microarray data.

Results

This study seeks to validate and extend previous studies on the expression of TE exons by an integrative statistical analysis of high throughput RNA sequencing data. We collected 26 RNA-seq datasets spanning multiple tissues and cancer types. The exon-level digital expressions (indicating retention rates in mRNAs) were quantified by a double normalized measure, called the rescaled RPKM (Reads Per Kilobase of exon model per Million mapped reads). We analyzed the distribution profiles and the variability (across samples and between tissue/disease groups) of TE exon expressions, and compared them with those of other constitutive or cassette exons. We inferred the effects of four genomic factors, including the location, length, cognate TE family and TE nucleotide proportion (RTE, see Methods section) of a TE exon, on the exons’ expression level and expression variability. We also investigated the biological implications of an assembly of highly-expressed TE exons.

Conclusion

Our analysis confirmed prior studies from the following four aspects. First, with relatively high expression variability, most TE exons in mRNAs, especially those without exact counterparts in the UCSC RefSeq (Reference Sequence) gene tables, demonstrate low but still detectable expression levels in most tissue samples. Second, the TE exons in coding DNA sequences (CDSs) are less highly expressed than those in 3′ (5′) untranslated regions (UTRs). Third, the exons derived from chronologically ancient repeat elements, such as MIRs, tend to be highly expressed in comparison with those derived from younger TEs. Fourth, the previously observed negative relationship between the lengths of exons and the inclusion levels in transcripts is also true for exonized TEs. Furthermore, our study resulted in several novel findings. They include: (1) for the TE exons with non-zero expression and as shown in most of the studied biological samples, a high TE nucleotide proportion leads to their lower retention rates in mRNAs; (2) the considered genomic features (i.e. a continuous variable such as the exon length or a category indicator such as 3′UTR) influence the expression level and the expression variability (CV) of TE exons in an inverse manner; (3) not only the exons derived from Alu elements but also the exons from the TEs of other families were preferentially established in zinc finger (ZNF) genes.

Oncofuse: a computational framework for the prediction of the oncogenic potential of gene fusions

MOTIVATION

Gene fusions resulting from chromosomal aberrations are an important cause of cancer. The complexity of genomic changes in certain cancer types has hampered the identification of gene fusions by molecular cytogenetic methods, especially in carcinomas. This is changing with the advent of next-generation sequencing, which is detecting a substantial number of new fusion transcripts in individual cancer genomes. However, this poses the challenge of identifying those fusions with greater oncogenic potential amid a background of 'passenger' fusion sequences.

RESULTS

In the present work, we have used some recently identified genomic hallmarks of oncogenic fusion genes to develop a pipeline for the classification of fusion sequences, namely, Oncofuse. The pipeline predicts the oncogenic potential of novel fusion genes, calculating the probability that a fusion sequence behaves as 'driver' of the oncogenic process based on features present in known oncogenic fusions. Cross-validation and extensive validation tests on independent datasets suggest a robust behavior with good precision and recall rates. We believe that Oncofuse could become a useful tool to guide experimental validation studies of novel fusion sequences found during next-generation sequencing analysis of cancer transcriptomes.

AVAILABILITY AND IMPLEMENTATION

Oncofuse is a naive Bayes Network Classifier trained and tested using Weka machine learning package. The pipeline is executed by running a Java/Groovy script, available for download at www.unav.es/genetica/oncofuse.html.

Long-range transcriptome sequencing reveals cancer cell growth regulatory chimeric mRNA

mRNA chimeras from chromosomal translocations often play a role as transforming oncogenes. However, cancer transcriptomes also contain mRNA chimeras that may play a role in tumor development, which arise as transcriptional or post-transcriptional events. To identify such chimeras, we developed a deterministic screening strategy for long-range sequence analysis. High-throughput, long-read sequencing was then performed on cDNA libraries from major tumor histotypes and corresponding normal tissues. These analyses led to the identification of 378 chimeras, with an unexpectedly high frequency of expression (≈2 x 10(-5) of all mRNA). Functional assays in breast and ovarian cancer cell lines showed that a large fraction of mRNA chimeras regulates cell replication. Strikingly, chimeras were shown to include both positive and negative regulators of cell growth, which functioned as such in a cell-type-specific manner. Replication-controlling chimeras were found to be expressed by most cancers from breast, ovary, colon, uterus, kidney, lung, and stomach, suggesting a widespread role in tumor development.