Deciphering the RNA landscape by RNAome sequencing

Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods

Vesicle-bound EBV-BART13-3p miRNA in circulation distinguishes nasopharyngeal from other head and neck cancer and asymptomatic EBV-infections

Cell-free microRNA (miRNA) in biofluids released by tumors in either protein or vesicle-bound form, represent promising minimally-invasive cancer biomarkers. However, a highly abundant non-tumor background in human plasma and serum complicates the discovery and detection of tumor-selective circulating miRNAs. We performed small RNA sequencing on serum and plasma RNA from Nasopharyngeal Carcinoma (NPC) patients. Collectively, Epstein Barr virus-encoded miRNAs, more so than endogenous miRNAs, signify presence of NPC. However, RNAseq-based EBV miRNA profiles differ between NPC patients, suggesting inter-tumor heterogeneity or divergent secretory characteristics. We determined with sensitive qRT-PCR assays that EBV miRNAs BART7-3p, BART9-3p and BART13-3p are actively secreted by C666.1 NPC cells bound to extracellular vesicles (EVs) and soluble ribonucleoprotein complexes. Importantly, these miRNAs are expressed in all primary NPC tumor biopsies and readily detected in nasopharyngeal brushings from both early and late-stage NPC patients. Increased levels of BART7-3p, BART9-3p and particularly BART13-3p, distinguish NPC patient sera from healthy controls. Receiver operating characteristic curve analysis using sera from endemic NPC patients, other head and neck cancers and individuals with asymptomatic EBV-infections reveals a superior diagnostic performance of EBV miRNAs over anti-EBNA1 IgA serology and EBV-DNA load (AUC 0.87–0.96 vs 0.86 and 0.66 respectively). The high specificity of circulating EBV-BART13-3p (97%) for NPC detection is in agreement with active secretion from NPC tumor cells. We conclude EV-bound BART13-3p in circulation is a promising, NPC-selective, biomarker that should be considered as part of a screening strategy to identify NPC in endemic regions

Deciphering the RNA landscape by RNAome sequencing

Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods. © Kasper WJ Derks, Branislav Misovic, Mirjam CGN van den Hout, Christel EM Kockx, Cesar Payan Gomez, Rutger WW Brouwer, Harry Vrieling, Jan HJ Hoeijmakers, Wilfred FJ van IJcken, and Joris Pothof

Deciphering the RNA landscape by RNAome sequencing

Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from rRNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods. © Kasper WJ Derks, Branislav Misovic, Mirjam CGN van den Hout, Christel EM Kockx, Cesar Payan Gomez, Rutger WW Brouwer, Harry Vrieling, Jan HJ Hoeijmakers, Wilfred FJ van IJcken, and Joris Pothof

The functional impact of variants of uncertain significance in BRCA2

Hereditary cancer genetic