MAJIQlopedia: an encyclopedia of RNA splicing variations in human tissues and cancer.

Quantification of RNA splicing variations based on RNA-Sequencing can reveal tissue- and disease-specific splicing patterns. To study such splicing variations, we introduce MAJIQlopedia, an encyclopedia of splicing variations that encompasses 86 human tissues and 41 cancer datasets. MAJIQlopedia reports annotated and unannotated splicing events for a total of 486 175 alternative splice junctions in normal tissues and 338 317 alternative splice junctions in cancer. This database, available at https://majiq.biociphers.org/majiqlopedia/, includes a user-friendly interface that provides graphical representations of junction usage quantification for each junction across all tissue or cancer types. To demonstrate case usage of MAJIQlopedia, we review splicing variations in genes WT1, MAPT and BIN1, which all have known tissue or cancer-specific splicing variations. We also use MAJIQlopedia to highlight novel splicing variations in FDX1 and MEGF9 in normal tissues, and we uncover a novel exon inclusion event in RPS6KA6 that only occurs in two cancer types. Users can download the database, request the addition of data to the webtool, or install a MAJIQlopedia server to integrate proprietary data. MAJIQlopedia can serve as a reference database for researchers seeking to understand what splicing variations exist in genes of interest, and those looking to understand tissue- or cancer-specific splice isoform usage.

Contrasting and Combining Transcriptome Complexity Captured by Short and Long RNA Sequencing Reads.

Mapping transcriptomic variations using either short or long reads RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, while short reads still provides improved coverage and error rates. Yet how to quantitatively compare the technologies, can we combine those, and what may be the benefit of such a combined view remain open questions. We tackle these questions by first creating a pipeline to assess matched long and short reads data using a variety of transcriptome statistics. We find that across datasets, algorithms and technologies, matched short reads data detects roughly 50% more splice junctions, with 10-30% of the splice junctions included at 20% or more are missed by long reads. In contrast, long reads detect many more intron retention events, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long reads technology or algorithm, and combine it with short reads data for improved transcriptome analysis.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data.

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets.

Alternative splicing of its 5'-UTR limits CD20 mRNA translation and enables resistance to CD20-directed immunotherapies.

Aberrant skipping of coding exons in CD19 and CD22 compromises the response to immunotherapy in B-cell malignancies. Here, we showed that the MS4A1 gene encoding human CD20 also produces several messenger RNA (mRNA) isoforms with distinct 5' untranslated regions. Four variants (V1-4) were detected using RNA sequencing (RNA-seq) at distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma, only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform contained upstream open reading frames and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, whereas V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed chimeric antigen receptor T cells were able to kill both V3- and V1-expressing cells, but the bispecific T-cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on 4 postmosunetuzumab follicular lymphoma relapses and discovered that in 2 of them, the downregulation of CD20 was accompanied by a V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies.

Alternative splicing of its 5'-UTR limits CD20 mRNA translation and enables resistance to CD20-directed immunotherapies.

Aberrant skipping of coding exons in CD19 and CD22 compromises responses to immunotherapy for B-cell malignancies. Here, we show that the MS4A1 gene encoding human CD20 also produces several mRNA isoforms with distinct 5' untranslated regions (5'-UTR). Four variants (V1-4) were detectable by RNA-seq in distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant by far. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform was found to contain upstream open reading frames (uORFs) and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching Morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, while V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed CAR T cells were able to kill both V3- and V1-expressing cells, but the bispecific T cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on four post-mosunetuzumab follicular lymphoma relapses and discovered that in two of them downregulation of CD20 was accompanied by the V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies. Key Points: In normal & malignant human B cells, CD20 mRNA is alternatively spliced into four 5'-UTR isoforms, some of which are translation-deficient.The balance between translation-deficient and -competent isoforms modulates CD20 protein levels & responses to CD20-directed immunotherapies. Explanation of Novelty: We discovered that in normal and malignant B-cells, CD20 mRNA is alternatively spliced to generate four distinct 5'-UTRs, including the longer translation-deficient V1 variant. Cells predominantly expressing V1 were still sensitive to CD20-targeting chimeric antigen receptor T-cells. However, they were resistant to the bispecific anti-CD3/CD20 antibody mosunetuzumab, and the shift to V1 were observed in CD20-negative post-mosunetuzumab relapses of follicular lymphoma.

Parkin Deficiency Suppresses Antigen Presentation to Promote Tumor Immune Evasion and Immunotherapy Resistance.

Parkin is an E3 ubiquitin ligase, which plays a key role in the development of Parkinson disease. Parkin defects also occur in numerous cancers, and a growing body of evidence indicates that Parkin functions as a tumor suppressor that impedes a number of cellular processes involved in tumorigenesis. Here, we generated murine and human models that closely mimic the advanced-stage tumors where Parkin deficiencies are found to provide deeper insights into the tumor suppressive functions of Parkin. Loss of Parkin expression led to aggressive tumor growth, which was associated with poor tumor antigen presentation and limited antitumor CD8+ T-cell infiltration and activation. The effect of Parkin deficiency on tumor growth was lost following depletion of CD8+ T cells. In line with previous findings, Parkin deficiency was linked with mitochondria-associated metabolic stress, PTEN degradation, and enhanced Akt activation. Increased Akt signaling led to dysregulation of antigen presentation, and treatment with the Akt inhibitor MK2206-2HCl restored antigen presentation in Parkin-deficient tumors. Analysis of data from patients with clear cell renal cell carcinoma indicated that Parkin expression was downregulated in tumors and that low expression correlated with reduced overall survival. Furthermore, low Parkin expression correlated with reduced patient response to immunotherapy. Overall, these results identify a role for Parkin deficiency in promoting tumor immune evasion that may explain the poor prognosis associated with loss of Parkin across multiple types of cancer. SIGNIFICANCE: Parkin prevents immune evasion by regulating tumor antigen processing and presentation through the PTEN/Akt network, which has important implications for immunotherapy treatments in patients with Parkin-deficient tumors.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data.

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

The Tumor Suppressor Adenomatous Polyposis Coli (apc) Is Required for Neural Crest-Dependent Craniofacial Development in Zebrafish.

Neural crest (NC) is a unique vertebrate cell type arising from the border of the neural plate and epidermis that gives rise to diverse tissues along the entire body axis. Roberto Mayor and colleagues have made major contributions to our understanding of NC induction, delamination, and migration. We report that a truncating mutation of the classical tumor suppressor Adenomatous Polyposis Coli (apc) disrupts craniofacial development in zebrafish larvae, with a marked reduction in the cranial neural crest (CNC) cells that contribute to mandibular and hyoid pharyngeal arches. While the mechanism is not yet clear, the altered expression of signaling molecules that guide CNC migration could underlie this phenotype. For example, apcmcr/mcr larvae express substantially higher levels of complement c3, which Mayor and colleagues showed impairs CNC cell migration when overexpressed. However, we also observe reduction in stroma-derived factor 1 (sdf1/cxcl12), which is required for CNC migration into the head. Consistent with our previous work showing that APC directly enhances the activity of glycogen synthase kinase 3 (GSK-3) and, independently, that GSK-3 phosphorylates multiple core mRNA splicing factors, we identify 340 mRNA splicing variations in apc mutant zebrafish, including a splice variant that deletes a conserved domain in semaphorin 3f (sema3f), an axonal guidance molecule and a known regulator of CNC migration. Here, we discuss potential roles for apc in CNC development in the context of some of the seminal findings of Mayor and colleagues.

RNA splicing analysis using heterogeneous and large RNA-seq datasets.

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we assess the advantages of MAJIQ v2 compared to existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer insights into brain subregion-specific splicing regulation.

A Bayesian model for unsupervised detection of RNA splicing based subtypes in cancers.

Identification of cancer sub-types is a pivotal step for developing personalized treatment. Specifically, sub-typing based on changes in RNA splicing has been motivated by several recent studies. We thus develop CHESSBOARD, an unsupervised algorithm tailored for RNA splicing data that captures "tiles" in the data, defined by a subset of unique splicing changes in a subset of patients. CHESSBOARD allows for a flexible number of tiles, accounts for uncertainty of splicing quantification, and is able to model missing values as additional signals. We first apply CHESSBOARD to synthetic data to assess its domain specific modeling advantages, followed by analysis of several leukemia datasets. We show detected tiles are reproducible in independent studies, investigate their possible regulatory drivers and probe their relation to known AML mutations. Finally, we demonstrate the potential clinical utility of CHESSBOARD by supplementing mutation based diagnostic assays with discovered splicing profiles to improve drug response correlation.

FBXW7ß isoform drives transcriptional activation of the proinflammatory TNF cluster in human pro-B cells.

Noncanonical exon usage plays many important roles in cellular phenotypes, but its contribution to human B-cell development remains sketchily understood. To fill this gap, we collected various B-cell fractions from bone marrow (BM) and tonsil donors, performed RNA sequencing, and examined transcript variants. We identified 150 genes that harbor local splicing variations in all pairwise comparisons. One of them encodes FBXW7, an E3 ubiquitin ligase implicated as a driver in several blood cancers. Surprisingly, we discovered that in normal human pro-B cells, the predominant transcript used an alternative first exon to produce the poorly characterized FBXW7ß isoform, previously thought to be restricted to neural tissues. The FBXW7ß transcript was also abundant in cell lines and primary samples of pediatric B-cell acute lymphoblastic leukemia (B-ALL), which originates in the BM. When overexpressed in a heterologous cell system, this transcript yielded the expected protein product, as judged by anti-FLAG immunoblotting and mass spectrometry. Furthermore, in REH B-ALL cells, FBXW7ß mRNA was the only FBXW7 isoform enriched in the polyribosome fraction. To shed light on possible functions of FBXW7ß, we used gain- and loss-of-function approaches and identified an FBXW7-dependent inflammatory gene signature, apparent in a subset of B-ALL with high FBXW7ß expression. This signature contained several members of the tumor necrosis factor superfamily, including those comprising the HLA Class III cluster (LTB, LST1, NCR3, LTA, and NFKBIL1). Our findings suggest that FBXW7ß expression drives proinflammatory responses, which could contribute to normal B-cell development, leukemogenesis, and responses to anticancer therapies.

The global Protein-RNA interaction map of ESRP1 defines a post-transcriptional program that is essential for epithelial cell function.

The epithelial splicing regulatory proteins, ESRP1 and ESRP2, are essential for mammalian development through the regulation of a global program of alternative splicing of genes involved in the maintenance of epithelial cell function. To further inform our understanding of the molecular functions of ESRP1, we performed enhanced crosslinking immunoprecipitation coupled with high-throughput sequencing (eCLIP) in epithelial cells of mouse epidermis. The genome-wide binding sites of ESRP1 were integrated with RNA-Seq analysis of alterations in splicing and total gene expression that result from epidermal ablation of Esrp1 and Esrp2. These studies demonstrated that ESRP1 functions in splicing regulation occur primarily through direct binding in a position-dependent manner to promote either exon inclusion or skipping. In addition, we also identified widespread binding of ESRP1 in 3' and 5' untranslated regions (UTRs) of genes involved in epithelial cell function, suggesting that its post-transcriptional functions extend beyond splicing regulation.

High-throughput mutagenesis identifies mutations and RNA-binding proteins controlling CD19 splicing and CART-19 therapy resistance.

Following CART-19 immunotherapy for B-cell acute lymphoblastic leukaemia (B-ALL), many patients relapse due to loss of the cognate CD19 epitope. Since epitope loss can be caused by aberrant CD19 exon 2 processing, we herein investigate the regulatory code that controls CD19 splicing. We combine high-throughput mutagenesis with mathematical modelling to quantitatively disentangle the effects of all mutations in the region comprising CD19 exons 1-3. Thereupon, we identify ~200 single point mutations that alter CD19 splicing and thus could predispose B-ALL patients to developing CART-19 resistance. Furthermore, we report almost 100 previously unknown splice isoforms that emerge from cryptic splice sites and likely encode non-functional CD19 proteins. We further identify cis-regulatory elements and trans-acting RNA-binding proteins that control CD19 splicing (e.g., PTBP1 and SF3B4) and validate that loss of these factors leads to pervasive CD19 mis-splicing. Our dataset represents a comprehensive resource for identifying predictive biomarkers for CART-19 therapy.

The germ cell-specific RNA binding protein RBM46 is essential for spermatogonial differentiation in mice.

Control over gene expression is exerted, in multiple stages of spermatogenesis, at the post-transcriptional level by RNA binding proteins (RBPs). We identify here an essential role in mammalian spermatogenesis and male fertility for 'RNA binding protein 46' (RBM46). A highly evolutionarily conserved gene, Rbm46 is also essential for fertility in both flies and fish. We found Rbm46 expression was restricted to the mouse germline, detectable in males in the cytoplasm of premeiotic spermatogonia and meiotic spermatocytes. To define its requirement for spermatogenesis, we generated Rbm46 knockout (KO, Rbm46-/-) mice; although male Rbm46-/- mice were viable and appeared grossly normal, they were infertile. Testes from adult Rbm46-/- mice were small, with seminiferous tubules containing only Sertoli cells and few undifferentiated spermatogonia. Using genome-wide unbiased high throughput assays RNA-seq and 'enhanced crosslinking immunoprecipitation' coupled with RNA-seq (eCLIP-seq), we discovered RBM46 could bind, via a U-rich conserved consensus sequence, to a cohort of mRNAs encoding proteins required for completion of differentiation and subsequent meiotic initiation. In summary, our studies support an essential role for RBM46 in regulating target mRNAs during spermatogonia differentiation prior to the commitment to meiosis in mice.

Identifying common transcriptome signatures of cancer by interpreting deep learning models.

BACKGROUND: Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types. RESULTS: Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer. CONCLUSIONS: Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.

Identification and characterization of RBM12 as a novel regulator of fetal hemoglobin expression.

The fetal-to-adult hemoglobin transition is clinically relevant because reactivation of fetal hemoglobin (HbF) significantly reduces morbidity and mortality associated with sickle cell disease (SCD) and ß-thalassemia. Most studies on the developmental regulation of the globin genes, including genome-wide genetics screens, have focused on DNA binding proteins, including BCL11A and ZBTB7A/LRF and their cofactors. Our understanding of RNA binding proteins (RBPs) in this process is much more limited. Two RBPs, LIN28B and IGF2BP1, are known posttranscriptional regulators of HbF production, but a global view of RBPs is still lacking. Here, we carried out a CRISPR/Cas9-based screen targeting RBPs harboring RNA methyltransferase and/or RNA recognition motif (RRM) domains and identified RNA binding motif 12 (RBM12) as a novel HbF suppressor. Depletion of RBM12 induced HbF expression and attenuated cell sickling in erythroid cells derived from patients with SCD with minimal detrimental effects on cell maturation. Transcriptome and proteome profiling revealed that RBM12 functions independently of major known HbF regulators. Enhanced cross-linking and immunoprecipitation followed by high-throughput sequencing revealed strong preferential binding of RBM12 to 5' untranslated regions of transcripts, narrowing down the mechanism of RBM12 action. Notably, we pinpointed the first of 5 RRM domains as essential, and, in conjunction with a linker domain, sufficient for RBM12-mediated HbF regulation. Our characterization of RBM12 as a negative regulator of HbF points to an additional regulatory layer of the fetal-to-adult hemoglobin switch and broadens the pool of potential therapeutic targets for SCD and ß-thalassemia.

Modulation of CD22 Protein Expression in Childhood Leukemia by Pervasive Splicing Aberrations: Implications for CD22-Directed Immunotherapies.

Downregulation of surface epitopes causes postimmunotherapy relapses in B-lymphoblastic leukemia (B-ALL). Here we demonstrate that mRNA encoding CD22 undergoes aberrant splicing in B-ALL. We describe the plasma membrane-bound CD22 Δex5-6 splice isoform, which is resistant to chimeric antigen receptor (CAR) T cells targeting the third immunoglobulin-like domain of CD22. We also describe splice variants skipping the AUG-containing exon 2 and failing to produce any identifiable protein, thereby defining an event that is rate limiting for epitope presentation. Indeed, forcing exon 2 skipping with morpholino oligonucleotides reduced CD22 protein expression and conferred resistance to the CD22-directed antibody-drug conjugate inotuzumab ozogamicin in vitro. Furthermore, among inotuzumab-treated pediatric patients with B-ALL, we identified one nonresponder in whose leukemic blasts Δex2 isoforms comprised the majority of CD22 transcripts. In a second patient, a sharp reduction in CD22 protein levels during relapse was driven entirely by increased CD22 exon 2 skipping. Thus, dysregulated CD22 splicing is a major mechanism of epitope downregulation and ensuing resistance to immunotherapy. SIGNIFICANCE: The mechanism(s) underlying downregulation of surface CD22 following CD22-directed immunotherapy remains underexplored. Our biochemical and correlative studies demonstrate that in B-ALL, CD22 expression levels are controlled by inclusion/skipping of CD22 exon 2. Thus, aberrant splicing of CD22 is an important driver/biomarker of de novo and acquired resistance to CD22-directed immunotherapies. See related commentary by Bourcier and Abdel-Wahab, p. 87. This article is highlighted in the In This Issue feature, p. 85.

CYP11B1 variants influence skeletal maturation via alternative splicing.

We performed genome-wide association study meta-analysis to identify genetic determinants of skeletal age (SA) deviating in multiple growth disorders. The joint meta-analysis (N = 4557) in two multiethnic cohorts of school-aged children identified one locus, CYP11B1 (expression confined to the adrenal gland), robustly associated with SA (rs6471570-A; ß = 0.14; P = 6.2 × 10-12). rs6410 (a synonymous variant in the first exon of CYP11B1 in high LD with rs6471570), was prioritized for functional follow-up being second most significant and the one closest to the first intron-exon boundary. In 208 adrenal RNA-seq samples from GTEx, C-allele of rs6410 was associated with intron 3 retention (P = 8.11 × 10-40), exon 4 inclusion (P = 4.29 × 10-34), and decreased exon 3 and 5 splicing (P = 7.85 × 10-43), replicated using RT-PCR in 15 adrenal samples. As CYP11B1 encodes 11-ß-hydroxylase, involved in adrenal glucocorticoid and mineralocorticoid biosynthesis, our findings highlight the role of adrenal steroidogenesis in SA in healthy children, suggesting alternative splicing as a likely underlying mechanism.

CAMPAREE: a robust and configurable RNA expression simulator.

BACKGROUND: The accurate interpretation of RNA-Seq data presents a moving target as scientists continue to introduce new experimental techniques and analysis algorithms. Simulated datasets are an invaluable tool to accurately assess the performance of RNA-Seq analysis methods. However, existing RNA-Seq simulators focus on modeling the technical biases and artifacts of sequencing, rather than on simulating the original RNA samples. A first step in simulating RNA-Seq is to simulate RNA. RESULTS: To fill this need, we developed the Configurable And Modular Program Allowing RNA Expression Emulation (CAMPAREE), a simulator using empirical data to simulate diploid RNA samples at the level of individual molecules. We demonstrated CAMPAREE's use for generating idealized coverage plots from real data, and for adding the ability to generate allele-specific data to existing RNA-Seq simulators that do not natively support this feature. CONCLUSIONS: Separating input sample modeling from library preparation/sequencing offers added flexibility for both users and developers to mix-and-match different sample and sequencing simulators to suit their specific needs. Furthermore, the ability to maintain sample and sequencing simulators independently provides greater agility to incorporate new biological findings about transcriptomics and new developments in sequencing technologies. Additionally, by simulating at the level of individual molecules, CAMPAREE has the potential to model molecules transcribed from the same genes as a heterogeneous population of transcripts with different states of degradation and processing (splicing, editing, etc.). CAMPAREE was developed in Python, is open source, and freely available at https://github.com/itmat/CAMPAREE .

MOCCASIN: a method for correcting for known and unknown confounders in RNA splicing analysis.

The effects of confounding factors on gene expression analysis have been extensively studied following the introduction of high-throughput microarrays and subsequently RNA sequencing. In contrast, there is a lack of equivalent analysis and tools for RNA splicing. Here we first assess the effect of confounders on both expression and splicing quantifications in two large public RNA-Seq datasets (TARGET, ENCODE). We show quantification of splicing variations are affected at least as much as those of gene expression, revealing unwanted sources of variations in both datasets. Next, we develop MOCCASIN, a method to correct the effect of both known and unknown confounders on RNA splicing quantification and demonstrate MOCCASIN's effectiveness on both synthetic and real data. Code, synthetic and corrected datasets are all made available as resources.