Comparative analysis of circular RNA enrichment methods.
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ABSTRACT:
SUBMITTER: Shi H
PROVIDER: S-EPMC8786342 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:RNA sequencing (RNA-Seq) experiments focused on gene expression involve removal of ribosomal RNA (rRNA) because it is the major RNA constituent of cells. This process, called RNA enrichment, is done primarily to reduce cost: without rRNA removal, deeper sequencing must be performed to compensate for the sequencing reads wasted on rRNA. The ideal RNA enrichment method removes all rRNA without affecting other RNA in the sample. We tested the performance of three RNA enrichment methods on RNA isolated from Cryptococcus neoformans, a fungal pathogen of humans. We find that the RNase H depletion method is more efficient in depleting rRNA and more specific in recapitulating non-rRNA levels present in unenriched controls than the commonly-used Poly(A) isolation method. The RNase H depletion method is also more effective than the Ribo-Zero depletion method as measured by rRNA depletion efficiency and recapitulation of protein-coding RNA levels present in unenriched controls, while the Ribo-Zero depletion method more closely recapitulates annotated non-coding RNA (ncRNA) levels. Finally, we leverage these data to accurately map the C. neoformans mitochondrial rRNA genes, and also demonstrate that RNA-Seq data generated with the RNase H and Ribo-Zero depletion methods can be used to explore novel C. neoformans long non-coding RNA genes.
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Project description:BACKGROUND:Pathway enrichment extensively used in the analysis of Omics data for gaining biological insights into the functional roles of pre-defined subsets of genes, proteins and metabolites. A large number of methods have been proposed in the literature for this task. The vast majority of these methods use as input expression levels of the biomolecules under study together with their membership in pathways of interest. The latest generation of pathway enrichment methods also leverages information on the topology of the underlying pathways, which as evidence from their evaluation reveals, lead to improved sensitivity and specificity. Nevertheless, a systematic empirical comparison of such methods is still lacking, making selection of the most suitable method for a specific experimental setting challenging. This comparative study of nine network-based methods for pathway enrichment analysis aims to provide a systematic evaluation of their performance based on three real data sets with different number of features (genes/metabolites) and number of samples. RESULTS:The findings highlight both methodological and empirical differences across the nine methods. In particular, certain methods assess pathway enrichment due to differences both across expression levels and in the strength of the interconnectedness of the members of the pathway, while others only leverage differential expression levels. In the more challenging setting involving a metabolomics data set, the results show that methods that utilize both pieces of information (with NetGSA being a prototypical one) exhibit superior statistical power in detecting pathway enrichment. CONCLUSION:The analysis reveals that a number of methods perform equally well when testing large size pathways, which is the case with genomic data. On the other hand, NetGSA that takes into consideration both differential expression of the biomolecules in the pathway, as well as changes in the topology exhibits a superior performance when testing small size pathways, which is usually the case for metabolomics data.
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Project description:Recent studies have identified circular RNAs (circRNAs) expressed from the Epstein-Barr virus (EBV) and Kaposi's sarcoma herpesvirus (KSHV) human DNA tumor viruses. To gain initial insights into the potential relevance of EBV circRNAs in virus biology and disease, we assessed the circRNAome of the interspecies homologue rhesus macaque lymphocryptovirus (rLCV) in a naturally occurring lymphoma from a simian immunodeficiency virus (SIV)-infected rhesus macaque. This analysis revealed rLCV orthologues of the latency-associated EBV circular RNAs circRPMS1_E4_E3a and circEBNA_U. Also identified in two samples displaying unusually high lytic gene expression was a novel rLCV circRNA that contains both conserved and rLCV-specific RPMS1 exons and whose backsplice junctions flank an rLCV lytic origin of replication (OriLyt). Analysis of a lytic infection model for the murid herpesvirus 68 (MHV68) rhadinovirus identified a cluster of circRNAs near an MHV68 lytic origin of replication, with the most abundant of these, circM11_ORF69, spanning the OriLyt. Lastly, analysis of KSHV latency and reactivation models revealed the latency associated circRNA originating from the vIRF4 gene as the predominant viral circRNA. Together, the results of this study broaden our appreciation for circRNA repertoires in the Lymphocryptovirus and Rhadinovirus genera of gammaherpesviruses and provide evolutionary support for viral circRNA functions in latency and viral replication.IMPORTANCE Infection with oncogenic gammaherpesviruses leads to long-term viral persistence through a dynamic interplay between the virus and the host immune system. Critical for remodeling of the host cell environment after the immune responses are viral noncoding RNAs that modulate host signaling pathways without attracting adaptive immune recognition. Despite the importance of noncoding RNAs in persistent infection, the circRNA class of noncoding RNAs has only recently been identified in gammaherpesviruses. Accordingly, their roles in virus infection and associated oncogenesis are unknown. Here we report evolutionary conservation of EBV-encoded circRNAs determined by assessing the circRNAome in rLCV-infected lymphomas from an SIV-infected rhesus macaque, and we report latent and lytic circRNAs from KSHV and MHV68. These experiments demonstrate utilization of the circular RNA class of RNAs across 4 members of the gammaherpesvirus subfamily, and they identify orthologues and potential homoplastic circRNAs, implying conserved circRNA functions in virus biology and associated malignancies.
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Project description:BackgroundThe analysis of high-throughput gene expression data with respect to sets of genes rather than individual genes has many advantages. A variety of methods have been developed for assessing the enrichment of sets of genes with respect to differential expression. In this paper we provide a comparative study of four of these methods: Fisher's exact test, Gene Set Enrichment Analysis (GSEA), Random-Sets (RS), and Gene List Analysis with Prediction Accuracy (GLAPA). The first three methods use associative statistics, while the fourth uses predictive statistics. We first compare all four methods on simulated data sets to verify that Fisher's exact test is markedly worse than the other three approaches. We then validate the other three methods on seven real data sets with known genetic perturbations and then compare the methods on two cancer data sets where our a priori knowledge is limited.ResultsThe simulation study highlights that none of the three method outperforms all others consistently. GSEA and RS are able to detect weak signals of deregulation and they perform differently when genes in a gene set are both differentially up and down regulated. GLAPA is more conservative and large differences between the two phenotypes are required to allow the method to detect differential deregulation in gene sets. This is due to the fact that the enrichment statistic in GLAPA is prediction error which is a stronger criteria than classical two sample statistic as used in RS and GSEA. This was reflected in the analysis on real data sets as GSEA and RS were seen to be significant for particular gene sets while GLAPA was not, suggesting a small effect size. We find that the rank of gene set enrichment induced by GLAPA is more similar to RS than GSEA. More importantly, the rankings of the three methods share significant overlap.ConclusionThe three methods considered in our study recover relevant gene sets known to be deregulated in the experimental conditions and pathologies analyzed. There are differences between the three methods and GSEA seems to be more consistent in finding enriched gene sets, although no method uniformly dominates over all data sets. Our analysis highlights the deep difference existing between associative and predictive methods for detecting enrichment and the use of both to better interpret results of pathway analysis. We close with suggestions for users of gene set methods.
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Project description:Comparative Analysis of Gammaherpesvirus Circular RNA
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Project description:Strand-specific, massively parallel cDNA sequencing (RNA-seq) is a powerful tool for transcript discovery, genome annotation and expression profiling. There are multiple published methods for strand-specific RNA-seq, but no consensus exists as to how to choose between them. Here we developed a comprehensive computational pipeline to compare library quality metrics from any RNA-seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library-construction protocols, including both published and our own methods. We found marked differences in strand specificity, library complexity, evenness and continuity of coverage, agreement with known annotations and accuracy for expression profiling. Weighing each method's performance and ease, we identified the dUTP second-strand marking and the Illumina RNA ligation methods as the leading protocols, with the former benefitting from the current availability of paired-end sequencing. Our analysis provides a comprehensive benchmark, and our computational pipeline is applicable for assessment of future protocols in other organisms.
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Project description:Specialized RNA-seq methods are required to identify the 5' ends of transcripts, which are critical for studies of gene regulation, but these methods have not been systematically benchmarked. We directly compared six such methods, including the performance of five methods on a single human cellular RNA sample and a new spike-in RNA assay that helps circumvent challenges resulting from uncertainties in annotation and RNA processing. We found that the 'cap analysis of gene expression' (CAGE) method performed best for mRNA and that most of its unannotated peaks were supported by evidence from other genomic methods. We applied CAGE to eight brain-related samples and determined sample-specific transcription start site (TSS) usage, as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.
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Project description:In platelets, splicing and translation occur in the absence of a nucleus. However, the integrity and stability of mRNAs derived from megakaryocyte progenitor cells remain poorly quantified on a transcriptome-wide level. As circular RNAs (circRNAs) are resistant to degradation by exonucleases, their abundance relative to linear RNAs can be used as a surrogate marker for mRNA stability in the absence of transcription. Here we show that circRNAs are enriched in human platelets 17- to 188-fold relative to nucleated tissues and 14- to 26-fold relative to samples digested with RNAse R to selectively remove linear RNA. We compare RNAseq read depths inside and outside circRNAs to provide in silico evidence of transcript circularity, show that exons within circRNAs are enriched on average 12.7 times in platelets relative to nucleated tissues and identify 3162 genes significantly enriched for circRNAs, including some where all RNAseq reads appear to be derived from circular molecules. We also confirm that this is a feature of other anucleate cells through transcriptome sequencing of mature erythrocytes, demonstrate that circRNAs are not enriched in cultured megakaryocytes, and demonstrate that linear RNAs decay more rapidly than circRNAs in platelet preparations. Collectively, these results suggest that circulating platelets have lost >90% of their progenitor mRNAs and that translation in platelets occurs against the backdrop of a highly degraded transcriptome. Finally, we find that transcripts previously classified as products of reverse transcriptase template switching are both enriched in platelets and resistant to decay, countering the recent suggestion that up to 50% of rearranged RNAs are artifacts.
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Project description:Recent studies have identified circular RNAs (circRNAs) expressed from the Epstein-Barr virus (EBV) and Kaposi’s sarcoma herpesvirus (KSHV) human DNA tu- mor viruses. To gain initial insights into the potential relevance of EBV circRNAs in virus biology and disease, we assessed the circRNAome of the interspecies homologue rhesus macaque lymphocryptovirus (rLCV) in a naturally occurring lymphoma from a simian immunodeficiency virus (SIV)-infected rhesus macaque. This analysis revealed rLCV orthologues of the latency-associated EBV circular RNAs circRPMS1_E4_E3a and circEBNA_U. Also identified in two samples displaying unusually high lytic gene expres- sion was a novel rLCV circRNA that contains both conserved and rLCV-specific RPMS1 exons and whose backsplice junctions flank an rLCV lytic origin of replication (OriLyt). Analysis of a lytic infection model for the murid herpesvirus 68 (MHV68) rhadinovirus identified a cluster of circRNAs near an MHV68 lytic origin of replication, with the most abundant of these, circM11_ORF69, spanning the OriLyt. Lastly, analysis of KSHV la- tency and reactivation models revealed the latency associated circRNA originating from the vIRF4 gene as the predominant viral circRNA. Together, the results of this study broaden our appreciation for circRNA repertoires in the Lymphocryptovirus and Rhadinovirus genera of gammaherpesviruses and provide evolutionary support for vi- ral circRNA functions in latency and viral replication.
2019-01-07 | GSE124711 | GEO
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the COVID-19 pandemic. Although other diagnostic methods have been introduced, detection of viral genes on oro- and nasopharyngeal swabs by reverse-transcription real time-PCR (rRT-PCR) assays is still the gold standard. Efficient viral RNA extraction is a prerequisite for downstream performance of rRT-PCR assays. Currently, several automatic methods that include RNA extraction are available. However, due to the growing demand, a shortage in kit supplies could be experienced in several labs. For these reasons, the use of different commercial or in-house protocols for RNA extraction may increase the possibility to analyze high number of samples. Herein, we compared the efficiency of RNA extraction of three different commercial kits and an in-house extraction protocol using synthetic ssRNA standards of SARS-CoV-2 as well as in oro-nasopharyngeal swabs from six COVID-19-positive patients. It was concluded that tested commercial kits can be used with some modifications for the detection of the SARS-CoV-2 genome by rRT-PCR approaches, although with some differences in RNA yields. Conversely, EXTRAzol reagent was the less efficient due to the phase separation principle at the basis of RNA extraction. Overall, this study offers alternative suitable methods to manually extract RNA that can be taken into account for SARS-CoV-2 detection.
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