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.

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.

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.

Alternative splicing redefines landscape of commonly mutated genes in acute myeloid leukemia.

Most genes associated with acute myeloid leukemia (AML) are mutated in less than 10% of patients, suggesting that alternative mechanisms of gene disruption contribute to this disease. Here, we find a set of splicing events that alter the expression of a subset of AML-associated genes independent of known somatic mutations. In particular, aberrant splicing triples the number of patients with reduced functional EZH2 compared with that predicted by somatic mutation alone. In addition, we unexpectedly find that the nonsense-mediated decay factor DHX34 exhibits widespread alternative splicing in sporadic AML, resulting in a premature stop codon that phenocopies the loss-of-function germline mutations observed in familial AML. Together, these results demonstrate that classical mutation analysis underestimates the burden of functional gene disruption in AML and highlight the importance of assessing the contribution of alternative splicing to gene dysregulation in human disease.

Genomic profiling of human vascular cells identifies TWIST1 as a causal gene for common vascular diseases.

Genome-wide association studies have identified multiple novel genomic loci associated with vascular diseases. Many of these loci are common non-coding variants that affect the expression of disease-relevant genes within coronary vascular cells. To identify such genes on a genome-wide level, we performed deep transcriptomic analysis of genotyped primary human coronary artery smooth muscle cells (HCASMCs) and coronary endothelial cells (HCAECs) from the same subjects, including splicing Quantitative Trait Loci (sQTL), allele-specific expression (ASE), and colocalization analyses. We identified sQTLs for TARS2, YAP1, CFDP1, and STAT6 in HCASMCs and HCAECs, and 233 ASE genes, a subset of which are also GTEx eGenes in arterial tissues. Colocalization of GWAS association signals for coronary artery disease (CAD), migraine, stroke and abdominal aortic aneurysm with GTEx eGenes in aorta, coronary artery and tibial artery discovered novel candidate risk genes for these diseases. At the CAD and stroke locus tagged by rs2107595 we demonstrate colocalization with expression of the proximal gene TWIST1. We show that disrupting the rs2107595 locus alters TWIST1 expression and that the risk allele has increased binding of the NOTCH signaling protein RBPJ. Finally, we provide data that TWIST1 expression influences vascular SMC phenotypes, including proliferation and calcification, as a potential mechanism supporting a role for TWIST1 in CAD.

Widespread JNK-dependent alternative splicing induces a positive feedback loop through CELF2-mediated regulation of MKK7 during T-cell activation.

Alternative splicing is prevalent among genes encoding signaling molecules; however, the functional consequence of differential isoform expression remains largely unknown. Here we demonstrate that, in response to T-cell activation, the Jun kinase (JNK) kinase MAP kinase kinase 7 (MKK7) is alternatively spliced to favor an isoform that lacks exon 2. This isoform restores a JNK-docking site within MKK7 that is disrupted in the larger isoform. Consistently, we show that skipping of MKK7 exon 2 enhances JNK pathway activity, as indicated by c-Jun phosphorylation and up-regulation of TNF-α. Moreover, this splicing event is itself dependent on JNK signaling. Thus, MKK7 alternative splicing represents a positive feedback loop through which JNK promotes its own signaling. We further show that repression of MKK7 exon 2 is dependent on the presence of flanking sequences and the JNK-induced expression of the RNA-binding protein CELF2, which binds to these regulatory elements. Finally, we found that ∼25% of T-cell receptor-mediated alternative splicing events are dependent on JNK signaling. Strikingly, these JNK-dependent events are also significantly enriched for responsiveness to CELF2. Together, our data demonstrate a widespread role for the JNK-CELF2 axis in controlling splicing during T-cell activation, including a specific role in propagating JNK signaling.

Missense Mutations in NKAP Cause a Disorder of Transcriptional Regulation Characterized by Marfanoid Habitus and Cognitive Impairment.

NKAP is a ubiquitously expressed nucleoplasmic protein that is currently known as a transcriptional regulatory molecule via its interaction with HDAC3 and spliceosomal proteins. Here, we report a disorder of transcriptional regulation due to missense mutations in the X chromosome gene, NKAP. These mutations are clustered in the C-terminal region of NKAP where NKAP interacts with HDAC3 and post-catalytic spliceosomal complex proteins. Consistent with a role for the C-terminal region of NKAP in embryogenesis, nkap mutant zebrafish with a C-terminally truncated NKAP demonstrate severe developmental defects. The clinical features of affected individuals are highly conserved and include developmental delay, hypotonia, joint contractures, behavioral abnormalities, Marfanoid habitus, and scoliosis. In affected cases, transcriptome analysis revealed the presence of a unique transcriptome signature, which is characterized by the downregulation of long genes with higher exon numbers. These observations indicate the critical role of NKAP in transcriptional regulation and demonstrate that perturbations of the C-terminal region lead to developmental defects in both humans and zebrafish.

Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing.

Human CD4+ T cells are often subdivided into distinct subtypes, including Th1, Th2, Th17, and Treg cells, that are thought to carry out distinct functions in the body. Typically, these T-cell subpopulations are defined by the expression of distinct gene repertoires; however, there is variability between studies regarding the methods used for isolation and the markers used to define each T-cell subtype. Therefore, how reliably studies can be compared to one another remains an open question. Moreover, previous analysis of gene expression in CD4+ T-cell subsets has largely focused on gene expression rather than alternative splicing. Here we take a meta-analysis approach, comparing eleven independent RNA-seq studies of human Th1, Th2, Th17, and/or Treg cells to determine the consistency in gene expression and splicing within each subtype across studies. We find that known master-regulators are consistently enriched in the appropriate subtype; however, cytokines and other genes often used as markers are more variable. Importantly, we also identify previously unknown transcriptomic markers that appear to consistently differentiate between subsets, including a few Treg-specific splicing patterns. Together this work highlights the heterogeneity in gene expression between samples designated as the same subtype, but also suggests additional markers that can be used to define functional groupings.

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 .

Ancient antagonism between CELF and RBFOX families tunes mRNA splicing outcomes.

Over 95% of human multi-exon genes undergo alternative splicing, a process important in normal development and often dysregulated in disease. We sought to analyze the global splicing regulatory network of CELF2 in human T cells, a well-studied splicing regulator critical to T cell development and function. By integrating high-throughput sequencing data for binding and splicing quantification with sequence features and probabilistic splicing code models, we find evidence of splicing antagonism between CELF2 and the RBFOX family of splicing factors. We validate this functional antagonism through knockdown and overexpression experiments in human cells and find CELF2 represses RBFOX2 mRNA and protein levels. Because both families of proteins have been implicated in the development and maintenance of neuronal, muscle, and heart tissues, we analyzed publicly available data in these systems. Our analysis suggests global, antagonistic coregulation of splicing by the CELF and RBFOX proteins in mouse muscle and heart in several physiologically relevant targets, including proteins involved in calcium signaling and members of the MEF2 family of transcription factors. Importantly, a number of these coregulated events are aberrantly spliced in mouse models and human patients with diseases that affect these tissues, including heart failure, diabetes, or myotonic dystrophy. Finally, analysis of exons regulated by ancient CELF family homologs in chicken, Drosophila, and Caenorhabditis elegans suggests this antagonism is conserved throughout evolution.

Mapping RNA splicing variations in clinically accessible and nonaccessible tissues to facilitate Mendelian disease diagnosis using RNA-seq.

PURPOSE: RNA-seq is a promising approach to improve diagnoses by detecting pathogenic aberrations in RNA splicing that are missed by DNA sequencing. RNA-seq is typically performed on clinically accessible tissues (CATs) from blood and skin. RNA tissue specificity makes it difficult to identify aberrations in relevant but nonaccessible tissues (non-CATs). We determined how RNA-seq from CATs represent splicing in and across genes and non-CATs. METHODS: We quantified RNA splicing in 801 RNA-seq samples from 56 different adult and fetal tissues from Genotype-Tissue Expression Project (GTEx) and ArrayExpress. We identified genes and splicing events in each non-CAT and determined when RNA-seq in each CAT would inadequately represent them. We developed an online resource, MAJIQ-CAT, for exploring our analysis for specific genes and tissues. RESULTS: In non-CATs, 40.2% of genes have splicing that is inadequately represented by at least one CAT; 6.3% of genes have splicing inadequately represented by all CATs. A majority (52.1%) of inadequately represented genes are lowly expressed in CATs (transcripts per million (TPM) < 1), but 5.8% are inadequately represented despite being well expressed (TPM > 10). CONCLUSION: Many splicing events in non-CATs are inadequately evaluated using RNA-seq from CATs. MAJIQ-CAT allows users to explore which accessible tissues, if any, best represent splicing in genes and tissues of interest.

Transcriptome analysis of hypoxic cancer cells uncovers intron retention in EIF2B5 as a mechanism to inhibit translation.

Cells adjust to hypoxic stress within the tumor microenvironment by downregulating energy-consuming processes including translation. To delineate mechanisms of cellular adaptation to hypoxia, we performed RNA-Seq of normoxic and hypoxic head and neck cancer cells. These data revealed a significant down regulation of genes known to regulate RNA processing and splicing. Exon-level analyses classified > 1,000 mRNAs as alternatively spliced under hypoxia and uncovered a unique retained intron (RI) in the master regulator of translation initiation, EIF2B5. Notably, this intron was expressed in solid tumors in a stage-dependent manner. We investigated the biological consequence of this RI and demonstrate that its inclusion creates a premature termination codon (PTC), that leads to a 65kDa truncated protein isoform that opposes full-length eIF2Bε to inhibit global translation. Furthermore, expression of 65kDa eIF2Bε led to increased survival of head and neck cancer cells under hypoxia, providing evidence that this isoform enables cells to adapt to conditions of low oxygen. Additional work to uncover -cis and -trans regulators of EIF2B5 splicing identified several factors that influence intron retention in EIF2B5: a weak splicing potential at the RI, hypoxia-induced expression and binding of the splicing factor SRSF3, and increased binding of total and phospho-Ser2 RNA polymerase II specifically at the intron retained under hypoxia. Altogether, these data reveal differential splicing as a previously uncharacterized mode of translational control under hypoxia and are supported by a model in which hypoxia-induced changes to cotranscriptional processing lead to selective retention of a PTC-containing intron in EIF2B5.

Aberrant splicing in B-cell acute lymphoblastic leukemia.

Aberrant splicing is a hallmark of leukemias with mutations in splicing factor (SF)-encoding genes. Here we investigated its prevalence in pediatric B-cell acute lymphoblastic leukemias (B-ALL), where SFs are not mutated. By comparing these samples to normal pro-B cells, we found thousands of aberrant local splice variations (LSVs) per sample, with 279 LSVs in 241 genes present in every comparison. These genes were enriched in RNA processing pathways and encoded ∼100 SFs, e.g. hnRNPA1. HNRNPA1 3'UTR was most pervasively mis-spliced, yielding the transcript subject to nonsense-mediated decay. To mimic this event, we knocked it down in B-lymphoblastoid cells and identified 213 hnRNPA1-regulated exon usage events comprising the hnRNPA1 splicing signature in pediatric leukemia. Some of its elements were LSVs in DICER1 and NT5C2, known cancer drivers. We searched for LSVs in other leukemia and lymphoma drivers and discovered 81 LSVs in 41 additional genes. Seventy-seven LSVs out of 81 were confirmed using two large independent B-ALL RNA-seq datasets, and the twenty most common B-ALL drivers, including NT5C2, showed higher prevalence of aberrant splicing than of somatic mutations. Thus, post-transcriptional deregulation of SF can drive widespread changes in B-ALL splicing and likely contributes to disease pathogenesis.

MAJIQ-SPEL: web-tool to interrogate classical and complex splicing variations from RNA-Seq data.

SUMMARY: Analysis of RNA sequencing (RNA-Seq) data have highlighted the fact that most genes undergo alternative splicing (AS) and that these patterns are tightly regulated. Many of these events are complex, resulting in numerous possible isoforms that quickly become difficult to visualize, interpret and experimentally validate. To address these challenges we developed MAJIQ-SPEL, a web-tool that takes as input local splicing variations (LSVs) quantified from RNA-Seq data and provides users with visualization and quantification of gene isoforms associated with those. Importantly, MAJIQ-SPEL is able to handle both classical (binary) and complex, non-binary, splicing variations. Using a matching primer design algorithm it also suggests to users possible primers for experimental validation by RT-PCR and displays those, along with the matching protein domains affected by the LSV, on UCSC Genome Browser for further downstream analysis. AVAILABILITY AND IMPLEMENTATION: Program and code will be available at http://majiq.biociphers.org/majiq-spel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Outlier detection for improved differential splicing quantification from RNA-Seq experiments with replicates.

Motivation: A key component in many RNA-Seq-based studies is contrasting multiple replicates from different experimental conditions. In this setup, replicates play a key role as they allow to capture underlying biological variability inherent to the compared conditions, as well as experimental variability. However, what constitutes a 'bad' replicate is not necessarily well defined. Consequently, researchers might discard valuable data or downstream analysis may be hampered by failed experiments. Results: Here we develop a probability model to weigh a given RNA-Seq sample as a representative of an experimental condition when performing alternative splicing analysis. We demonstrate that this model detects outlier samples which are consistently and significantly different compared with other samples from the same condition. Moreover, we show that instead of discarding such samples the proposed weighting scheme can be used to downweight samples and specific splicing variations suspected as outliers, gaining statistical power. These weights can then be used for differential splicing (DS) analysis, where the resulting algorithm offers a generalization of the MAJIQ algorithm. Using both synthetic and real-life data, we perform an extensive evaluation of the improved MAJIQ algorithm in different scenarios involving perturbed samples, mislabeled samples, same condition groups, and different levels of coverage, showing it compares favorably to other tools. Overall, this work offers an outlier detection algorithm that can be combined with any splicing pipeline, a generalized and improved version of MAJIQ for DS detection, and evaluation metrics with matching code and data for DS algorithms. Availability and implementation: Software and data are accessible via majiq.biociphers.org/norton_et_al_2017/. Contact: yosephb@upenn.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Phosphoproteomics reveals that glycogen synthase kinase-3 phosphorylates multiple splicing factors and is associated with alternative splicing.

Glycogen synthase kinase-3 (GSK-3) is a constitutively active, ubiquitously expressed protein kinase that regulates multiple signaling pathways. In vitro kinase assays and genetic and pharmacological manipulations of GSK-3 have identified more than 100 putative GSK-3 substrates in diverse cell types. Many more have been predicted on the basis of a recurrent GSK-3 consensus motif ((pS/pT)XXX(S/T)), but this prediction has not been tested by analyzing the GSK-3 phosphoproteome. Using stable isotope labeling of amino acids in culture (SILAC) and MS techniques to analyze the repertoire of GSK-3-dependent phosphorylation in mouse embryonic stem cells (ESCs), we found that ∼2.4% of (pS/pT)XXX(S/T) sites are phosphorylated in a GSK-3-dependent manner. A comparison of WT and Gsk3a;Gsk3b knock-out (Gsk3 DKO) ESCs revealed prominent GSK-3-dependent phosphorylation of multiple splicing factors and regulators of RNA biosynthesis as well as proteins that regulate transcription, translation, and cell division. Gsk3 DKO reduced phosphorylation of the splicing factors RBM8A, SRSF9, and PSF as well as the nucleolar proteins NPM1 and PHF6, and recombinant GSK-3ß phosphorylated these proteins in vitro RNA-Seq of WT and Gsk3 DKO ESCs identified ∼190 genes that are alternatively spliced in a GSK-3-dependent manner, supporting a broad role for GSK-3 in regulating alternative splicing. The MS data also identified posttranscriptional regulation of protein abundance by GSK-3, with ∼47 proteins (1.4%) whose levels increased and ∼78 (2.4%) whose levels decreased in the absence of GSK-3. This study provides the first unbiased analysis of the GSK-3 phosphoproteome and strong evidence that GSK-3 broadly regulates alternative splicing.

Integrative deep models for alternative splicing.

MOTIVATION: Advancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The first involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence. To date, these models have utilized only expression data. In this work, we address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors. RESULTS: We perform a detailed comparison of two previous modeling approaches, Bayesian and Deep Neural networks, dissecting the confounding effects of datasets and target functions. We then develop a new target function for AS prediction in exon skipping events and show it significantly improves model accuracy. Next, we develop a modeling framework that leverages transfer learning to incorporate CLIP-Seq, knockdown and over expression experiments, which are inherently noisy and suffer from missing values. Using several datasets involving key splice factors in mouse brain, muscle and heart we demonstrate both the prediction improvements and biological insights offered by our new models. Overall, the framework we propose offers a scalable integrative solution to improve splicing code modeling as vast amounts of relevant genomic data become available. AVAILABILITY AND IMPLEMENTATION: Code and data available at: majiq.biociphers.org/jha_et_al_2017/. CONTACT: yosephb@upenn.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Deciphering the splicing code.

Alternative splicing has a crucial role in the generation of biological complexity, and its misregulation is often involved in human disease. Here we describe the assembly of a 'splicing code', which uses combinations of hundreds of RNA features to predict tissue-dependent changes in alternative splicing for thousands of exons. The code determines new classes of splicing patterns, identifies distinct regulatory programs in different tissues, and identifies mutation-verified regulatory sequences. Widespread regulatory strategies are revealed, including the use of unexpectedly large combinations of features, the establishment of low exon inclusion levels that are overcome by features in specific tissues, the appearance of features deeper into introns than previously appreciated, and the modulation of splice variant levels by transcript structure characteristics. The code detected a class of exons whose inclusion silences expression in adult tissues by activating nonsense-mediated messenger RNA decay, but whose exclusion promotes expression during embryogenesis. The code facilitates the discovery and detailed characterization of regulated alternative splicing events on a genome-wide scale.