Comparison of Alternative Splicing Junction Detection Tools Using RNA-Seq Data

Comprehensive splicing analysis of the alternatively spliced CHEK2 exons 8 and 10 reveals three enhancer/silencer-rich regions and 38 spliceogenic variants

Splicing is controlled by a large set of regulatory elements (SREs) including splicing enhancers and silencers, which are involved in exon recognition. Variants at these motifs may dysregulate splicing and trigger loss-of-function transcripts associated with disease. Our goal here was to study the alternatively spliced exons 8 and 10 of the breast cancer susceptibility gene CHEK2. For this purpose, we used a previously published minigene with exons 6-10 that produced the expected minigene full-length transcript and replicated the naturally occurring events of exon 8 [Δ(E8)] and exon 10 [Δ(E10)] skipping. We then introduced 12 internal microdeletions of exons 8 and 10 by mutagenesis in order to map SRE-rich intervals by splicing assays in MCF-7 cells. We identified three minimal (10-, 11-, 15-nt) regions essential for exon recognition: c.863_877del [ex8, Δ(E8): 75%] and c.1073_1083del and c.1083_1092del [ex10, Δ(E10): 97% and 62%, respectively]. Then 87 variants found within these intervals were introduced into the wild-type minigene and tested functionally. Thirty-eight of them (44%) impaired splicing, four of which (c.883G>A, c.883G>T, c.884A>T, and c.1080G>T) induced negligible amounts (<5%) of the minigene full-length transcript. Another six variants (c.886G>A, c.886G>T, c.1075G>A, c.1075G>T, c.1076A>T, and c.1078G>T) showed significantly strong impacts (20-50% of the minigene full-length transcript). Thirty-three of the 38 spliceogenic variants were annotated as missense, three as nonsense, and two as synonymous, underlying the fact that any exonic change is capable of disrupting splicing. Moreover, c.883G>A, c.883G>T, and c.884A>T were classified as pathogenic/likely pathogenic variants according to ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based criteria. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Allele-specific quantification of human leukocyte antigen transcript isoforms by nanopore sequencing

Introduction

While tens of thousands of HLA alleles have been identified by DNA sequencing, the contribution of alternative splicing to HLA diversity is not well characterized. In this study, we sought to determine if long-read sequencing could be used to accurately quantify allele-specific HLA transcripts in primary human lymphocytes.

Methods

cDNA libraries were prepared from peripheral blood lymphocytes from 12 donors and sequenced by nanopore long-read sequencing. HLA reads were aligned to donor-specific reference sequences based on the known type of each donor. Allele-specific exon utilization was calculated as the proportion of reads aligning to each allele containing known exons, and transcript isoforms were quantified based on patterns of exon utilization within individual reads.

Results

Splice variants were rare among class I HLA genes (median exon retention rate 99%-100%), except for several HLA-C alleles with exon 5 spliced out of up to 15% of reads. Splice variants were also rare among class II HLA genes (median exon retention rate 98%-100%), except for HLA-DQB1. Consistent with previous work, exon 5 of HLA-DQB1 was spliced out in alleles with a mutated splice acceptor site at rs28688207. Surprisingly, a 28% loss of exon 5 was also observed in HLA-DQB1 alleles with an intact splice acceptor site at rs28688207.

Discussion

We describe a simple bioinformatic workflow to quantify allele-specific expression of HLA transcript isoforms. Further studies are warranted to characterize the repertoire of HLA transcripts expressed in different cell types and tissues across diverse populations.

Identification of Splice Variants and Isoforms in Transcriptomics and Proteomics

Alternative splicing is pivotal to the regulation of gene expression and protein diversity in eukaryotic cells. The detection of alternative splicing events requires specific omics technologies. Although short-read RNA sequencing has successfully supported a plethora of investigations on alternative splicing, the emerging technologies of long-read RNA sequencing and top-down mass spectrometry open new opportunities to identify alternative splicing and protein isoforms with less ambiguity. Here, we summarize improvements in short-read RNA sequencing for alternative splicing analysis, including percent splicing index estimation and differential analysis. We also review the computational methods used in top-down proteomics analysis regarding proteoform identification, including the construction of databases of protein isoforms and statistical analyses of search results. While many improvements in sequencing and computational methods will result from emerging technologies, there should be future endeavors to increase the effectiveness, integration, and proteome coverage of alternative splicing events.

Role of Epitranscriptomic and Epigenetic Modifications during the Lytic and Latent Phases of Herpesvirus Infections

Herpesviruses are double-stranded DNA viruses occurring at a high prevalence in the human population and are responsible for a wide array of clinical manifestations and diseases, from mild to severe. These viruses are classified in three subfamilies (Alpha-, Beta- and Gammaherpesvirinae), with eight members currently known to infect humans. Importantly, all herpesviruses can establish lifelong latent infections with symptomatic or asymptomatic lytic reactivations. Accumulating evidence suggest that chemical modifications of viral RNA and DNA during the lytic and latent phases of the infections caused by these viruses, are likely to play relevant roles in key aspects of the life cycle of these viruses by modulating and regulating their replication, establishment of latency and evasion of the host antiviral response. Here, we review and discuss current evidence regarding epitranscriptomic and epigenetic modifications of herpesviruses and how these can influence their life cycles. While epitranscriptomic modifications such as m⁶A are the most studied to date and relate to positive effects over the replication of herpesviruses, epigenetic modifications of the viral genome are generally associated with defense mechanisms of the host cells to suppress viral gene transcription. However, herpesviruses can modulate these modifications to their own benefit to persist in the host, undergo latency and sporadically reactivate.

Splice variants denote differences between a cancer stem cell side population of EWSR1‑ERG‑based Ewing sarcoma cells, its main population and EWSR1‑FLI‑based cells

Ewing sarcoma is a challenging cancer entity, which, besides the characteristic presence of a fusion gene, is driven by multiple alternative splicing events. So far, splice variants in Ewing sarcoma cells were mainly analyzed for EWSR1‑FLI1. The present study provided a comprehensive alternative splicing study on CADO‑ES1, an Ewing model cell line for an EWSR1‑ERG fusion gene. Based on a well‑-characterized RNA‑sequencing dataset with extensive control mechanisms across all levels of analysis, the differential spliced genes in Ewing cancer stem cells were ATP13A3 and EPB41, while the main population was defined by ACADVL, NOP58 and TSPAN3. All alternatively spliced genes were further characterized by their Gene Ontology (GO) terms and by their membership in known protein complexes. These results confirm and extend previous studies towards a systematic whole‑transcriptome analysis. A highlight is the striking segregation of GO terms associated with five basic splice events. This mechanistic insight, together with a coherent integration of all observations with prior knowledge, indicates that EWSR1‑ERG is truly a close twin to EWSR1‑FLI1, but still exhibits certain individuality. Thus, the present study provided a measure of variability in Ewing sarcoma, whose understanding is essential both for clinical procedures and basic mechanistic insight.

Trends in biological data integration for the selection of enzymes and transcription factors related to cellulose and hemicellulose degradation in fungi

Fungi are key players in biotechnological applications. Although several studies focusing on fungal diversity and genetics have been performed, many details of fungal biology remain unknown, including how cellulolytic enzymes are modulated within these organisms to allow changes in main plant cell wall compounds, cellulose and hemicellulose, and subsequent biomass conversion. With the advent and consolidation of DNA/RNA sequencing technology, different types of information can be generated at the genomic, structural and functional levels, including the gene expression profiles and regulatory mechanisms of these organisms, during degradation-induced conditions. This increase in data generation made rapid computational development necessary to deal with the large amounts of data generated. In this context, the origination of bioinformatics, a hybrid science integrating biological data with various techniques for information storage, distribution and analysis, was a fundamental step toward the current state-of-the-art in the postgenomic era. The possibility of integrating biological big data has facilitated exciting discoveries, including identifying novel mechanisms and more efficient enzymes, increasing yields, reducing costs and expanding opportunities in the bioprocess field. In this review, we summarize the current status and trends of the integration of different types of biological data through bioinformatics approaches for biological data analysis and enzyme selection.

Alternative RNA splicing in stem cells and cancer stem cells: Importance of transcript-based expression analysis

Alternative ribonucleic acid (RNA) splicing can lead to the assembly of different protein isoforms with distinctive functions. The outcome of alternative splicing (AS) can result in a complete loss of function or the acquisition of new functions. There is a gap in knowledge of abnormal RNA splice variants promoting cancer stem cells (CSCs), and their prospective contribution in cancer progression. AS directly regulates the self-renewal features of stem cells (SCs) and stem-like cancer cells. Notably, octamer-binding transcription factor 4A spliced variant of octamer-binding transcription factor 4 contributes to maintaining stemness properties in both SCs and CSCs. The epithelial to mesenchymal transition pathway regulates the AS events in CSCs to maintain stemness. The alternative spliced variants of CSCs markers, including cluster of differentiation 44, aldehyde dehydrogenase, and doublecortin-like kinase, α6β1 integrin, have pivotal roles in increasing self-renewal properties and maintaining the pluripotency of CSCs. Various splicing analysis tools are considered in this study. LeafCutter software can be considered as the best tool for differential splicing analysis and identification of the type of splicing events. Additionally, LeafCutter can be used for efficient mapping splicing quantitative trait loci. Altogether, the accumulating evidence re-enforces the fact that gene and protein expression need to be investigated in parallel with alternative splice variants.

Alternative splicing dynamics and evolutionary divergence during embryogenesis in wheat species

Among polyploid species with complex genomic architecture, variations in the regulation of alternative splicing (AS) provide opportunities for transcriptional and proteomic plasticity and the potential for generating trait diversities. However, the evolution of AS and its influence on grain development in diploid grass and valuable polyploid wheat crops are poorly understood. To address this knowledge gap, we developed a pipeline for the analysis of alternatively spliced transcript isoforms, which takes the high sequence similarity among polyploid wheat subgenomes into account. Through analysis of synteny and detection of collinearity of homoeologous subgenomes, conserved and specific AS events across five wheat and grass species were identified. A global analysis of the regulation of AS in diploid grass and polyploid wheat grains revealed diversity in AS events not only between the endosperm, pericarp and embryo overdevelopment, but also between subgenomes. Analysis of AS in homoeologous triads of polyploid wheats revealed evolutionary divergence between gene-level and transcript-level regulation of embryogenesis. Evolutionary age analysis indicated that the generation of novel transcript isoforms has occurred in young genes at a more rapid rate than in ancient genes. These findings, together with the development of comprehensive AS resources for wheat and grass species, advance understanding of the evolution of regulatory features of AS during embryogenesis and grain development in wheat.

Computational comparison of common event-based differential splicing tools: practical considerations for laboratory researchers

BACKGROUND

Computational tools analyzing RNA-sequencing data have boosted alternative splicing research by identifying and assessing differentially spliced genes. However, common alternative splicing analysis tools differ substantially in their statistical analyses and general performance. This report compares the computational performance (CPU utilization and RAM usage) of three event-level splicing tools; rMATS, MISO, and SUPPA2. Additionally, concordance between tool outputs was investigated.

RESULTS

Log-linear relations were found between job times and dataset size in all splicing tools and all virtual machine (VM) configurations. MISO had the highest job times for all analyses, irrespective of VM size, while MISO analyses also exceeded maximum CPU utilization on all VM sizes. rMATS and SUPPA2 load averages were relatively low in both size and replicate comparisons, not nearing maximum CPU utilization in the VM simulating the lowest computational power (D2 VM). RAM usage in rMATS and SUPPA2 did not exceed 20% of maximum RAM in both size and replicate comparisons while MISO reached maximum RAM usage in D2 VM analyses for input size. Correlation coefficients of differential splicing analyses showed high correlation (β > 80%) between different tool outputs with the exception of comparisons of retained intron (RI) events between rMATS/MISO and rMATS/SUPPA2 (β < 60%).

CONCLUSIONS

Prior to RNA-seq analyses, users should consider job time, amount of replicates and splice event type of interest to determine the optimal alternative splicing tool. In general, rMATS is superior to both MISO and SUPPA2 in computational performance. Analysis outputs show high concordance between tools, with the exception of RI events.

Genome-wide discovery of natural variation in pre-mRNA splicing and prioritising causal alternative splicing to salt stress response in rice

Pre-mRNA splicing is an essential step for the regulation of gene expression. In order to specifically capture splicing variants in plants for genome-wide association studies (GWAS), we developed a software tool to quantify and visualise Variations of Splicing in Population (VaSP). VaSP can quantify splicing variants from short-read RNA-seq datasets and discover genotype-specific splicing (GSS) events, which can be used to prioritise causal pre-mRNA splicing events in GWAS. We applied our method to an RNA-seq dataset with 328 samples from 82 genotypes from a rice diversity panel exposed to optimal and saline growing conditions. In total, 764 significant GSS events were identified in salt stress conditions. GSS events were used as markers for a GWAS with the shoot Na⁺ accumulation, which identified six GSS events in five genes significantly associated with the shoot Na⁺ content. Two of these genes, OsNUC1 and OsRAD23 emerged as top candidate genes with splice variants that exhibited significant divergence between the variants for shoot growth under salt stress conditions. VaSP is a versatile tool for alternative splicing analysis in plants and a powerful tool for prioritising candidate causal pre-mRNA splicing and corresponding genomic variations in GWAS.

ASpli: Integrative analysis of splicing landscapes through RNA-Seq assays

MOTIVATION

Genome-wide analysis of alternative splicing has been a very active field of research since the early days of Next Generation Sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise comparisons.

RESULTS

In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow considers the same GLM model, applied to different sets of reads and junctions, in order to compute complementary splicing signals.Analyzing simulated and real data we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as non-annotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis algorithms. ASpli is freely available from the Bioconductor project site https://www.bioconductor.org/packages/ASpli.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Comprehensive Comparison of Amnion Stromal Cells and Chorion Stromal Cells by RNA-Seq

Mesenchymal stromal cells derived from the fetal placenta, composed of an amnion membrane, chorion membrane, and umbilical cord, have emerged as promising sources for regenerative medicine. Here, we used next-generation sequencing technology to comprehensively compare amniotic stromal cells (ASCs) with chorionic stromal cells (CSCs) at the molecular and signaling levels. Principal component analysis showed a clear dichotomy of gene expression profiles between ASCs and CSCs. Unsupervised hierarchical clustering confirmed that the biological repeats of ASCs and CSCs were able to respectively group together. Supervised analysis identified differentially expressed genes, such as LMO3, HOXA11, and HOXA13, and differentially expressed isoforms, such as CXCL6 and HGF. Gene Ontology (GO) analysis showed that the GO terms of the extracellular matrix, angiogenesis, and cell adhesion were significantly enriched in CSCs. We further explored the factors associated with inflammation and angiogenesis using a multiplex assay. In comparison with ASCs, CSCs secreted higher levels of angiogenic factors, including angiogenin, VEGFA, HGF, and bFGF. The results of a tube formation assay proved that CSCs exhibited a strong angiogenic function. However, ASCs secreted two-fold more of an anti-inflammatory factor, TSG-6, than CSCs. In conclusion, our study demonstrated the differential gene expression patterns between ASCs and CSCs. CSCs have superior angiogenic potential, whereas ASCs exhibit increased anti-inflammatory properties.

The role of alternative splicing in cancer: From oncogenesis to drug resistance

Alternative splicing is a tightly regulated process whereby non-coding sequences of pre-mRNA are removed and protein-coding segments are assembled in diverse combinations, ultimately giving rise to proteins with distinct or even opposing functions. In the past decade, whole genome/transcriptome sequencing studies revealed the high complexity of splicing regulation, which occurs co-transcriptionally and is influenced by chromatin status and mRNA modifications. Consequently, splicing profiles of both healthy and malignant cells display high diversity and alternative splicing was shown to be widely deregulated in multiple cancer types. In particular, mutations in pre-mRNA regulatory sequences, splicing regulators and chromatin modifiers, as well as differential expression of splicing factors are important contributors to cancer pathogenesis. It has become clear that these aberrations contribute to many facets of cancer, including oncogenic transformation, cancer progression, response to anticancer drug treatment as well as resistance to therapy. In this respect, alternative splicing was shown to perturb the expression a broad spectrum of relevant genes involved in drug uptake/metabolism (i.e. SLC29A1, dCK, FPGS, and TP), activation of nuclear receptor pathways (i.e. GR, AR), regulation of apoptosis (i.e. MCL1, BCL-X, and FAS) and modulation of response to immunotherapy (CD19). Furthermore, aberrant splicing constitutes an important source of novel cancer biomarkers and the spliceosome machinery represents an attractive target for a novel and rapidly expanding class of therapeutic agents. Small molecule inhibitors targeting SF3B1 or splice factor kinases were highly cytotoxic against a wide range of cancer models, including drug-resistant cells. Importantly, these effects are enhanced in specific cancer subsets, such as splicing factor-mutated and c-MYC-driven tumors. Furthermore, pre-clinical studies report synergistic effects of spliceosome modulators in combination with conventional antitumor agents. These strategies based on the use of low dose splicing modulators could shift the therapeutic window towards decreased toxicity in healthy tissues. Here we provide an extensive overview of the latest findings in the field of regulation of splicing in cancer, including molecular mechanisms by which cancer cells harness alternative splicing to drive oncogenesis and evade anticancer drug treatment as well as splicing-based vulnerabilities that can provide novel treatment opportunities. Furthermore, we discuss current challenges arising from genome-wide detection and prediction methods of aberrant splicing, as well as unravelling functional relevance of the plethora of cancer-related splicing alterations.

The Emerging Role of the RBM20 and PTBP1 Ribonucleoproteins in Heart Development and Cardiovascular Diseases

Alternative splicing is a regulatory mechanism essential for cell differentiation and tissue organization. More than 90% of human genes are regulated by alternative splicing events, which participate in cell fate determination. The general mechanisms of splicing events are well known, whereas only recently have deep-sequencing, high throughput analyses and animal models provided novel information on the network of functionally coordinated, tissue-specific, alternatively spliced exons. Heart development and cardiac tissue differentiation require thoroughly regulated splicing events. The ribonucleoprotein RBM20 is a key regulator of the alternative splicing events required for functional and structural heart properties, such as the expression of TTN isoforms. Recently, the polypyrimidine tract-binding protein PTBP1 has been demonstrated to participate with RBM20 in regulating splicing events. In this review, we summarize the updated knowledge relative to RBM20 and PTBP1 structure and molecular function; their role in alternative splicing mechanisms involved in the heart development and function; RBM20 mutations associated with idiopathic dilated cardiovascular disease (DCM); and the consequences of RBM20-altered expression or dysfunction. Furthermore, we discuss the possible application of targeting RBM20 in new approaches in heart therapies.

Visualization and analysis of RNA-Seq assembly graphs

RNA-Seq is a powerful transcriptome profiling technology enabling transcript discovery and quantification. Whilst most commonly used for gene-level quantification, the data can be used for the analysis of transcript isoforms. However, when the underlying transcript assemblies are complex, current visualization approaches can be limiting, with splicing events a challenge to interpret. Here, we report on the development of a graph-based visualization method as a complementary approach to understanding transcript diversity from short-read RNA-Seq data. Following the mapping of reads to a reference genome, a read-to-read comparison is performed on all reads mapping to a given gene, producing a weighted similarity matrix between reads. This is used to produce an RNA assembly graph, where nodes represent reads and edges similarity scores between them. The resulting graphs are visualized in 3D space to better appreciate their sometimes large and complex topology, with other information being overlaid on to nodes, e.g. transcript models. Here we demonstrate the utility of this approach, including the unusual structure of these graphs and how they can be used to identify issues in assembly, repetitive sequences within transcripts and splice variants. We believe this approach has the potential to significantly improve our understanding of transcript complexity.

RBM20 Regulates CaV1.2 Surface Expression by Promoting Exon 9* Inclusion of CACNA1C in Neonatal Rat Cardiomyocytes

The CACNA1C gene encodes for the CaV1.2 protein, which is the pore subunit of cardiac l-type voltage-gated calcium (Ca²⁺) channels (l-channels). Through alternative splicing, CACNA1C encodes for various CaV1.2 isoforms with different electrophysiological properties. Splice variants of CaV1.2 are differentially expressed during heart development or pathologies. The molecular mechanisms of CACNA1C alternative splicing still remain incompletely understood. RNA sequencing analysis has suggested that CACNA1C is a potential target of the splicing factor RNA-binding protein motif 20 (RBM20). Here, we aimed at elucidating the role of RBM20 in the regulation of CACNA1C alternative splicing. We found that in neonatal rat cardiomyocytes (NRCMs), RBM20 overexpression promoted the inclusion of CACNA1C’s exon 9*, whereas the skipping of exon 9* occurred upon RBM20 siRNA knockdown. The splicing of other known alternative exons was not altered by RBM20. RNA immunoprecipitation suggested that RBM20 binds to introns flanking exon 9*. Functionally, in NRCMs, RBM20 overexpression decreased l-type Ca²⁺ currents, whereas RBM20 siRNA knockdown increased l-type Ca²⁺ currents. Finally, we found that RBM20 overexpression reduced CaV1.2 membrane surface expression in NRCMs. Taken together, our results suggest that RBM20 specifically regulates the inclusion of exon 9* in CACNA1C mRNA, resulting in reduced cell-surface membrane expression of l-channels in cardiomyocytes.

Splicing in the pathogenesis, diagnosis and treatment of ciliopathies

Primary cilia are essential signalling organelles found on the apical surface of epithelial cells, where they coordinate chemosensation, mechanosensation and light sensation. Motile cilia play a central role in establishing fluid flow in the respiratory tract, reproductive tract, brain ventricles and ear. Genetic defects affecting the structure or function of cilia can lead to a broad range of developmental and degenerative diseases known as ciliopathies. Splicing contributes to the pathogenesis, diagnosis and treatment of ciliopathies. Tissue-specific alternative splicing contributes to the tissue-specific manifestation of ciliopathy phenotypes, for example the retinal-specific effects of some genetic defects, due to specific transcript expression in the highly specialised ciliated cells of the retina, the photoreceptor cells. Ciliopathies can arise both as a result of genetic variants in spliceosomal proteins, or as a result of variants affecting splicing of specific cilia genes. Here we discuss the opportunities and challenges in diagnosing ciliopathies using RNA sequence analysis and the potential for treating ciliopathies in a relatively mutation-neutral way by targeting splicing. This article is part of a Special Issue entitled: RNA structure and splicing regulation edited by Francisco Baralle, Ravindra Singh and Stefan Stamm.

Altered RNA Processing in Cancer Pathogenesis and Therapy

Major advances in our understanding of cancer pathogenesis and therapy have come from efforts to catalog genomic alterations in cancer. A growing number of large-scale genomic studies have uncovered mutations that drive cancer by perturbing cotranscriptional and post-transcriptional regulation of gene expression. These include alterations that affect each phase of RNA processing, including splicing, transport, editing, and decay of messenger RNA. The discovery of these events illuminates a number of novel therapeutic vulnerabilities generated by aberrant RNA processing in cancer, several of which have progressed to clinical development. SIGNIFICANCE: There is increased recognition that genetic alterations affecting RNA splicing and polyadenylation are common in cancer and may generate novel therapeutic opportunities. Such mutations may occur within an individual gene or in RNA processing factors themselves, thereby influencing splicing of many downstream target genes. This review discusses the biological impact of these mutations on tumorigenesis and the therapeutic approaches targeting cells bearing these mutations.

Event Analysis: Using Transcript Events To Improve Estimates of Abundance in RNA-seq Data

Alternative splicing leverages genomic content by allowing the synthesis of multiple transcripts and, by implication, protein isoforms, from a single gene. However, estimating the abundance of transcripts produced in a given tissue from short sequencing reads is difficult and can result in both the construction of transcripts that do not exist, and the failure to identify true transcripts. An alternative approach is to catalog the events that make up isoforms (splice junctions and exons). We present here the Event Analysis (EA) approach, where we project transcripts onto the genome and identify overlapping/unique regions and junctions. In addition, all possible logical junctions are assembled into a catalog. Transcripts are filtered before quantitation based on simple measures: the proportion of the events detected, and the coverage. We find that mapping to a junction catalog is more efficient at detecting novel junctions than mapping in a splice aware manner. We identify 99.8% of true transcripts while iReckon identifies 82% of the true transcripts and creates more transcripts not included in the simulation than were initially used in the simulation. Using PacBio Iso-seq data from a mouse neural progenitor cell model, EA detects 60% of the novel junctions that are combinations of existing exons while only 43% are detected by STAR. EA further detects ∼5,000 annotated junctions missed by STAR. Filtering transcripts based on the proportion of the transcript detected and the number of reads on average supporting that transcript captures 95% of the PacBio transcriptome. Filtering the reference transcriptome before quantitation, results in is a more stable estimate of isoform abundance, with improved correlation between replicates. This was particularly evident when EA is applied to an RNA-seq study of type 1 diabetes (T1D), where the coefficient of variation among subjects (n = 81) in the transcript abundance estimates was substantially reduced compared to the estimation using the full reference. EA focuses on individual transcriptional events. These events can be quantitate and analyzed directly or used to identify the probable set of expressed transcripts. Simple rules based on detected events and coverage used in filtering result in a dramatic improvement in isoform estimation without the use of ancillary data (e.g., ChIP, long reads) that may not be available for many studies.