Alternative 3'UTR expression induced by T cell activation is regulated in a temporal and signal dependent manner.

The length of 3' untranslated regions (3'UTR) is highly regulated during many transitions in cell state, including T cell activation, through the process of alternative polyadenylation (APA). However, the regulatory mechanisms and functional consequences of APA remain largely unexplored. Here we present a detailed analysis of the temporal and condition-specific regulation of APA following activation of primary human CD4+ T cells. We find that global APA changes are regulated temporally and CD28 costimulatory signals enhance a subset of these changes. Most APA changes upon T cell activation involve 3'UTR shortening, although a set of genes enriched for function in the mTOR pathway exhibit 3'UTR lengthening. While upregulation of the core polyadenylation machinery likely induces 3'UTR shortening following prolonged T cell stimulation; a significant program of APA changes occur prior to cellular proliferation or upregulation of the APA machinery. Motif analysis suggests that at least a subset of these early changes in APA are driven by upregulation of RBM3, an RNA-binding protein which competes with the APA machinery for binding. Together this work expands our understanding of the impact and mechanisms of APA in response to T cell activation and suggests new mechanisms by which APA may be regulated.

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.

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.

Alternative splicing of HDAC7 regulates its interaction with 14-3-3 proteins to alter histone marks and target gene expression.

Chromatin regulation and alternative splicing are both critical mechanisms guiding gene expression. Studies have demonstrated that histone modifications can influence alternative splicing decisions, but less is known about how alternative splicing may impact chromatin. Here, we demonstrate that several genes encoding histone-modifying enzymes are alternatively spliced downstream of T cell signaling pathways, including HDAC7, a gene previously implicated in controlling gene expression and differentiation in T cells. Using CRISPR-Cas9 gene editing and cDNA expression, we show that differential inclusion of HDAC7 exon 9 controls the interaction of HDAC7 with protein chaperones, resulting in changes to histone modifications and gene expression. Notably, the long isoform, which is induced by the RNA-binding protein CELF2, promotes expression of several critical T cell surface proteins including CD3, CD28, and CD69. Thus, we demonstrate that alternative splicing of HDAC7 has a global impact on histone modification and gene expression that contributes to T cell development.

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.

Alternative splicing of apoptosis genes promotes human T cell survival.

Alternative splicing occurs in the vast majority of human genes, giving rise to distinct mRNA and protein isoforms. We, and others, have previously identified hundreds of genes that change their isoform expression upon T cell activation via alternative splicing; however, how these changes link activation input with functional output remains largely unknown. Here, we investigate how costimulation of T cells through the CD28 receptor impacts alternative splicing in T cells activated through the T cell receptor (TCR, CD3) and find that while CD28 signaling alone has minimal impact on splicing, it enhances the extent of change for up to 20% of TCR-induced alternative splicing events. Interestingly, a set of CD28-enhanced splicing events occur within genes encoding key components of the apoptotic signaling pathway; namely caspase-9, Bax, and Bim. Using both CRISPR-edited cells and antisense oligos to force expression of specific isoforms, we show for all three of these genes that the isoform induced by CD3/CD28 costimulation promotes resistance to apoptosis, and that changes in all three genes together function combinatorially to further promote cell viability. Finally, we show that the JNK signaling pathway, induced downstream of CD3/CD28 costimulation, is required for each of these splicing events, further highlighting their co-regulation. Together, these findings demonstrate that alternative splicing is a key mechanism by which costimulation of CD28 promotes viability of activated T cells.

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.

Analysis of scientific society honors reveals disparities.

Delivering a keynote talk at a conference organized by a scientific society or being named as a fellow by such a society indicates that a scientist is held in high regard by their colleagues. To explore if the distribution of such indicators of esteem in the field of bioinformatics reflects the composition of this field, we compared the gender, name origin, and country of affiliation of 412 honorees from the "International Society for Computational Biology" (75 fellows and 337 keynote speakers) with over 170,000 last authorships on computational biology papers between 1993 and 2019. The proportion of honors bestowed on women was similar to that of the field's overall last authorship rate. However, names of East Asian origin have been persistently underrepresented among honorees. Moreover, there were roughly twice as many honors bestowed on scientists with an affiliation in the United States as expected based on literature authorship. A record of this paper's transparent peer review process is included in the supplemental information.

Reciprocal regulation of hnRNP C and CELF2 through translation and transcription tunes splicing activity in T cells.

RNA binding proteins (RBPs) frequently regulate the expression of other RBPs in mammalian cells. Such cross-regulation has been proposed to be important to control networks of coordinated gene expression; however, much remains to be understood about how such networks of cross-regulation are established and what the functional consequence is of coordinated or reciprocal expression of RBPs. Here we demonstrate that the RBPs CELF2 and hnRNP C regulate the expression of each other, such that depletion of one results in reduced expression of the other. Specifically, we show that loss of hnRNP C reduces the transcription of CELF2 mRNA, while loss of CELF2 results in decreased efficiency of hnRNP C translation. We further demonstrate that this reciprocal regulation serves to fine tune the splicing patterns of many downstream target genes. Together, this work reveals new activities of hnRNP C and CELF2, provides insight into a previously unrecognized gene regulatory network, and demonstrates how cross-regulation of RBPs functions to shape the cellular transcriptome.

Deep profiling and custom databases improve detection of proteoforms generated by alternative splicing.

Alternative pre-mRNA splicing has long been proposed to contribute greatly to proteome complexity. However, the extent to which mature mRNA isoforms are successfully translated into protein remains controversial. Here, we used high-throughput RNA sequencing and mass spectrometry (MS)-based proteomics to better evaluate the translation of alternatively spliced mRNAs. To increase proteome coverage and improve protein quantitation, we optimized cell fractionation and sample processing steps at both the protein and peptide level. Furthermore, we generated a custom peptide database trained on analysis of RNA-seq data with MAJIQ, an algorithm optimized to detect and quantify differential and unannotated splice junction usage. We matched tandem mass spectra acquired by data-dependent acquisition (DDA) against our custom RNA-seq based database, as well as SWISS-PROT and RefSeq databases to improve identification of splicing-derived proteoforms by 28% compared with use of the SWISS-PROT database alone. Altogether, we identified peptide evidence for 554 alternate proteoforms corresponding to 274 genes. Our increased depth and detection of proteins also allowed us to track changes in the transcriptome and proteome induced by T-cell stimulation, as well as fluctuations in protein subcellular localization. In sum, our data here confirm that use of generic databases in proteomic studies underestimates the number of spliced mRNA isoforms that are translated into protein and provides a workflow that improves isoform detection in large-scale proteomic experiments.

RNA Binding Protein CELF2 Regulates Signal-Induced Alternative Polyadenylation by Competing with Enhancers of the Polyadenylation Machinery.

The 3' UTR (UTR) of human mRNAs plays a critical role in controlling protein expression and function. Importantly, 3' UTRs of human messages are not invariant for each gene but rather are shaped by alternative polyadenylation (APA) in a cell state-dependent manner, including in response to T cell activation. However, the proteins and mechanisms driving APA regulation remain poorly understood. Here we show that the RNA-binding protein CELF2 controls APA of its own message in a signal-dependent manner by competing with core enhancers of the polyadenylation machinery for binding to RNA. We further show that CELF2 binding overlaps with APA enhancers transcriptome-wide, and almost half of 3' UTRs that undergo T cell signaling-induced APA are regulated in a CELF2-dependent manner. These studies thus reveal CELF2 to be a critical regulator of 3' UTR identity in T cells and demonstrate an additional mechanism for CELF2 in regulating polyadenylation site choice.

An ancient germ cell-specific RNA-binding protein protects the germline from cryptic splice site poisoning.

Male germ cells of all placental mammals express an ancient nuclear RNA binding protein of unknown function called RBMXL2. Here we find that deletion of the retrogene encoding RBMXL2 blocks spermatogenesis. Transcriptome analyses of age-matched deletion mice show that RBMXL2 controls splicing patterns during meiosis. In particular, RBMXL2 represses the selection of aberrant splice sites and the insertion of cryptic and premature terminal exons. Our data suggest a Rbmxl2 retrogene has been conserved across mammals as part of a splicing control mechanism that is fundamentally important to germ cell biology. We propose that this mechanism is essential to meiosis because it buffers the high ambient concentrations of splicing activators, thereby preventing poisoning of key transcripts and disruption to gene expression by aberrant splice site selection.

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.

Co-regulatory activity of hnRNP K and NS1-BP in influenza and human mRNA splicing.

Three of the eight RNA segments encoded by the influenza A virus (IAV) undergo alternative splicing to generate distinct proteins. Previously, we found that host proteins hnRNP K and NS1-BP regulate IAV M segment splicing, but the mechanistic details were unknown. Here we show NS1-BP and hnRNP K bind M mRNA downstream of the M2 5' splice site (5'ss). NS1-BP binds most proximal to the 5'ss, partially overlapping the U1 snRNP binding site, while hnRNP K binds further downstream and promotes U1 snRNP recruitment. Mutation of either or both the hnRNP K and NS1-BP-binding sites results in M segment mis-splicing and attenuated IAV replication. Additionally, we show that hnRNP K and NS1-BP regulate host splicing events and that viral infection causes mis-splicing of some of these transcripts. Therefore, our proposed mechanism of hnRNP K/NS1-BP mediated IAV M splicing provides potential targets of antiviral intervention and reveals novel host functions for these proteins.

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.

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.

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.

A SLM2 Feedback Pathway Controls Cortical Network Activity and Mouse Behavior.

The brain is made up of trillions of synaptic connections that together form neural networks needed for normal brain function and behavior. SLM2 is a member of a conserved family of RNA binding proteins, including Sam68 and SLM1, that control splicing of Neurexin1-3 pre-mRNAs. Whether SLM2 affects neural network activity is unknown. Here, we find that SLM2 levels are maintained by a homeostatic feedback control pathway that predates the divergence of SLM2 and Sam68. SLM2 also controls the splicing of Tomosyn2, LysoPLD/ATX, Dgkb, Kif21a, and Cask, each of which are important for synapse function. Cortical neural network activity dependent on synaptic connections between SLM2-expressing-pyramidal neurons and interneurons is decreased in Slm2-null mice. Additionally, these mice are anxious and have a decreased ability to recognize novel objects. Our data reveal a pathway of SLM2 homeostatic auto-regulation controlling brain network activity and behavior.