Biology subjects

Barash, Y.

Publications and source records attributed to Barash, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Detection of a sequence feature for recursive splicing

RNA splicing is directed by cis-acting sequence signals interacting with trans-acting factors to remove introns from newly transcribed pre-mRNA, joining exons to generate mature mRNA. Splicing happens far more often than observed exon-exon junctions in mRNA. As one contributing process, the spliceosome progressively removes large introns in small segments by recursive splicing, instead of splicing the whole intron at one time. However, the cis-acting sequences associated with recursive splicing have not been identified. Using probabilistic mixture models, we found that recursive splicing occurs more frequently in first introns, which are typically longer, and exhibit a distinct CG-rich sequence feature in the sequences flanking the upstream 5SS, and depletion of CGs in the downstream polypyrimidine tract. Remarkably, recursive splicing is also more frequent in downstream introns of genes containing first introns with these properties. Mechanistically, these data suggest that early events in RNA synthesis and processing influence the prevalence of recursive splicing for the rest of the transcript. Finally, we developed a sequence-dependent classifier for recursive splicing, which we tested with a novel medium-throughput primer extension assay. In summary, the usage of recursive splicing sites is established at the beginning of RNA synthesis through newly-identified sequence motifs flanking both ends of the first intron.

genomics↗

bioRxiv2026

RNA G-quadruplexes mediate cooperativity in HNRNPH binding and splicing regulation

Alternative splicing, regulated by RNA-binding proteins (RBPs), enables the generation of diverse transcript isoforms critical for cellular function. However, how RNA secondary structure impacts RBP binding and function remains poorly understood. Here, we unravel how RNA G-quadruplexes (rG4s) facilitate cooperativity in splicing regulation by the RBP heterogeneous nuclear ribonucleoprotein H (HNRNPH). Through high-throughput in vivo and in vitro studies combined with theoretical modeling, we dissect how rG4s mediate cooperative HNRNPH binding to RNA, ultimately modulating the splicing of hundreds of exons. rG4 unfolding by HNRNPH exposes multiple G-rich binding sites, thereby establishing indirect cooperativity, which is further amplified to achieve switch-like splicing regulation. HNRNPH-mediated regulation is evident in breast cancer patients, with tumors showing rG4-disrupting variants and global HNRNPH alterations, driving distinct splicing patterns that distinguish tumor subtypes. Overall, our findings offer valuable insights into the mechanistic role of RNA secondary structures in cooperative RBP binding and splicing regulation and highlight the clinical relevance of HNRNPH-dependent splicing in cancer. HighlightsO_LIHundreds of cassette exons are cooperatively regulated by HNRNPH. C_LIO_LIUnfolding of RNA G-quadruplexes (rG4s) at HNRNPH binding sites facilitates indirect cooperativity in RNA binding. C_LIO_LIMulti-step splicing amplifies the response into highly switch-like regulation. C_LIO_LIrG4-disrupting variants and changing HNRNPH expression are associated with breast cancer phenotypes. C_LI

molecular biology↗

bioRxiv2025

Integrative analysis of RNA binding proteins identifies DDX55 as a novel regulator of 3'UTR isoform diversity

The 3 untranslated regions (3UTRs) of mRNAs play a critical role in controlling gene expression and function because they contain binding sites for microRNAs and RNA binding proteins (RBPs) that alter mRNA stability, localization, and translation. Most mRNA 3 ends contain multiple polyadenylation sites (PAS) that can be utilized in condition-specific manners, a process known as alternative polyadenylation (APA), however the mechanisms driving the regulation of APA remain poorly characterized. By integrating a large set of over 500 RNA binding protein (RBP) depletion and binding experiments across two cell lines generated by the ENCODE consortium, we uncovered a number of RBPs in each cell type whose depletion leads to widespread alteration of 3 UTR patterns. These include not only known regulators of APA, but also many putative novel regulators of 3UTR isoform expression. We focused analysis on the largely unstudied DEAD box RNA helicase, DDX55, and validate its novel role in 3UTR isoform regulation using molecular assays and targeted 3 end sequencing experiments. Our findings identify DDX55 as a new regulator of APA, particularly at PAS that contain features of RNA secondary structure. Our data also suggest additional previously unrecognized regulators of 3 UTR processing and differential stability.

genomics↗

bioRxiv2025

Generative modeling for RNA splicing predictions and design

Alternative splicing (AS) of pre-mRNA plays a crucial role in tissue-specific gene regulation, with disease implications due to splicing defects. Predicting and manipulating AS can therefore uncover new regulatory mechanisms and aid in therapeutics design. We introduce TrASPr+BOS, a generative AI model with Bayesian Optimization for predicting and designing RNA for tissue-specific splicing outcomes. TrASPr is a multi-transformer model that can handle different types of AS events and generalize to unseen cellular conditions. It then serves as an oracle, generating labeled data to train a Bayesian Optimization for Splicing (BOS) algorithm to design RNA for condition-specific splicing outcomes. We show TrASPr+BOS outperforms existing methods, enhancing tissue-specific AUPRC by up to 1.8 fold and capturing tissue-specific regulatory elements. We validate hundreds of predicted novel tissue-specific splicing variations and confirm new regulatory elements using dCas13. We envision TrASPr+BOS as a light yet accurate method researchers can probe or adopt for specific tasks.

bioinformatics↗

bioRxiv2025

Neuronal cell adhesion molecule (NRCAM) variant defined by microexon skipping is an essential, antigenically distinct, and targetable surface proteoform in high-grade glioma

To overcome the paucity of known tumor-specific surface antigens in pediatric high-grade glioma (pHGG), we contrasted splicing patterns in pHGGs and normal brain samples. Among alternative splicing events affecting extracellular protein domains, the most pervasive alteration was the skipping of [≤]30 nucleotide-long exons. Several of these skipped microexons mapped to L1-IgCAM family members, such as NRCAM. Bulk and single-nuclei short- and long-read RNA-seq revealed uniform skipping of NRCAM microexons 5 and 19 in virtually every pHGG sample. Importantly, the {Delta}ex5{Delta}ex19 (but not the full-length) NRCAM proteoform was essential for pHGG cell migration and invasion in vitro and tumor growth in vivo. We developed a monoclonal antibody selective for {Delta}ex5{Delta}ex19 NRCAM and demonstrated that "painting" of pHGG cells with this antibody enables killing by T cells armed with an FcRI-based universal immune receptor. Thus, pHGG-specific NRCAM and possibly other L1-IgCAM proteoforms are promising and highly selective targets for adoptive immunotherapies.

cancer biology↗

bioRxiv2024

G4mer: An RNA language model for transcriptome-wide identification of G-quadruplexes and disease variants from population-scale genetic data

RNA G-quadruplexes (rG4s) are key regulatory elements in gene expression, yet the effects of genetic variants on rG4 formation remain underexplored. Here, we introduce G4mer, an RNA language model that predicts rG4 formation and evaluates the effects of genetic variants across the transcriptome. G4mer significantly improves accuracy over existing methods, highlighting sequence length and flanking motifs as important rG4 features. Applying G4mer to 5 untranslated region (UTR) variations, we identify variants in breast cancer-associated genes that alter rG4 formation and validate their impact on structure and gene expression. These results demonstrate the potential of integrating computational models with experimental approaches to study rG4 function, especially in diseases where non-coding variants are often overlooked. To support broader applications, G4mer is available as both a web tool and a downloadable model.

genetics↗

bioRxiv2024

Machine learning-optimized targeted detection of alternative splicing

RNA-sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases which hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local Splicing Variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest. Primers are designed using Optimal Prime, a novel machine learning algorithm trained on the performance of thousands of primer sequences. In experimental benchmarks, LSV-seq achieves high on-target capture rates and concordance with RNA-seq, while requiring significantly lower sequencing depth. Leveraging deep learning splicing code predictions, we used LSV-seq to target events with low coverage in GTEx RNA-seq data and newly discover hundreds of tissue-specific splicing events. Our results demonstrate the ability of LSV-seq to quantify splicing of events of interest at high-throughput and with exceptional sensitivity.

genomics↗

bioRxiv2024

A Deep Dive into Statistical Modeling of RNA Splicing QTLs Reveals New Variants that Explain Neurodegenerative Disease

Genome-wide association studies (GWAS) have identified thousands of putative disease causing variants with unknown regulatory effects. Efforts to connect these variants with splicing quantitative trait loci (sQTLs) have provided functional insights, yet sQTLs reported by existing methods cannot explain many GWAS signals. We show current sQTL modeling approaches can be improved by considering alternative splicing representation, model calibration, and covariate integration. We then introduce MAJIQTL, a new pipeline for sQTL discovery. MAJIQTL includes two new statistical methods: a weighted multiple testing approach for sGene discovery and a model for sQTL effect size inference to improve variant prioritization. By applying MAJIQTL to GTEx, we find significantly more sGenes harboring sQTLs with functional significance. Notably, our analysis implicates the novel variant rs582283 in Alzheimers disease. Using antisense oligonucleotides, we validate this variants effect by blocking the implicated YBX3 binding site, leading to exon skipping in the gene MS4A3.

genomics↗

bioRxiv2024

MAJIQ V3 offers improvements in accuracy, performance, and usability for splicing analysis from RNA sequencing

SummaryRNA splicing plays important roles in cell-type-specific expression of gene isoforms and is causally linked to numerous diseases. Previously, our group developed MAJIQ V1 and V2 for RNA splicing detection, quantification, and visualization from RNA sequencing. Here we report an update, MAJIQ V3, that offers several improvements in time, memory, accuracy, and usability. We demonstrate the benefits of MAJIQ V3 using GTEx data for different analysis scenarios involving different dataset sizes.

bioinformatics↗

bioRxiv2023

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.

bioinformatics↗

bioRxiv2023

A Novel Aberrantly Spliced Gain-of-Function NT5C2 Isoform Contributes to Thiopurine Resistance in Acute Lymphoblastic Leukemia

Relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL) is a major cause of pediatric cancer-related deaths. Relapse-specific mutations do not account for all chemotherapy failures in B- ALL patients, suggesting additional mechanisms of resistance. By mining RNA-seq datasets of paired diagnostic/relapse pediatric B-ALL samples, we discovered pervasive alternative splicing (AS) patterns linked to relapse and affecting drivers of resistance to glucocorticoids, anti-folates, and thiopurines. Most splicing variations represented cassette exon skipping, "poison" exon inclusion, and intron retention, phenocopying well-documented loss-of-function mutations. In contrast, relapse-associated AS of NT5C2 mRNA yielded an isoform with the functionally uncharacterized in-frame exon 6a. Incorporation of the 8-amino acid sequence SQVAVQKR into this enzyme created a putative phosphorylation site and resulted in elevated nucleosidase activity, which is a known consequence of gain-of-function mutations in NT5C2 and a common determinant of 6-mercaptopurine (6-MP) resistance. Consistent with this finding, NT5C2ex6a and the R238W hotspot variant conferred comparable levels of resistance to 6-MP in B-ALL cells both in vitro and in vivo. Furthermore, both the NT5C2ex6a and R238W variants induced collateral sensitivity to the inosine monophosphate dehydrogenase (IMPDH) inhibitor mizoribine. These results ascribe an important role for splicing perturbations in chemotherapy resistance in relapsed B-ALL and suggest that IMPDH inhibitors, including the commonly used immunosuppressive agent mycophenolate mofetil, could be a valuable therapeutic option for treating thiopurine-resistant leukemias.

cancer biology↗

bioRxiv2023

An anciently diverged family of RNA binding proteins maintain correct splicing of ultra-long exons through cryptic splice site repression.

We previously showed that the germ cell specific nuclear protein RBMXL2 represses cryptic splicing patterns during meiosis and is required for male fertility. RBMXL2 evolved from the X-linked RBMX gene, which is silenced during meiosis due to sex chromosome inactivation. It has been unknown whether RBMXL2 provides a direct replacement for RBMX in meiosis, or whether RBMXL2 evolved to deal with the transcriptionally permissive environment of meiosis. Here we find that RBMX primarily operates as a splicing repressor in somatic cells, and specifically regulates a distinct class of exons that exceed the median human exon size. RBMX protein-RNA interactions are enriched within ultra-long exons, particularly within genes involved in genome stability, and repress the selection of cryptic splice sites that would compromise gene function. These similarities in overall function suggested that RBMXL2 might replace the function of RBMX during meiosis. To test this prediction we carried out inducible expression of RBMXL2 and the more distantly related RBMY protein in somatic cells, finding each could rescue aberrant patterns of RNA processing caused by RBMX depletion. The C-terminal disordered domain of RBMXL2 is sufficient to rescue proper splicing control after RBMX depletion. Our data indicate that RBMX and RBMXL2 have parallel roles in somatic tissues and the germline that must have been conserved for at least 200 million years of mammalian evolution. We propose RBMX family proteins are particularly important for the splicing inclusion of some ultra-long exons with increased intrinsic susceptibility to cryptic splice site selection.

molecular biology↗

bioRxiv2023

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.

bioinformatics↗

bioRxiv2023

Alternative splicing of its 5' untranslated region controls 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 PointsO_LIIn normal & malignant human B cells, CD20 mRNA is alternatively spliced into four 5-UTR isoforms, some of which are translation-deficient. C_LIO_LIThe balance between translation-deficient and -competent isoforms modulates CD20 protein levels & responses to CD20-directed immunotherapies C_LI Explanation of NoveltyWe 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.

immunology↗

bioRxiv2022

FBXW7β isoform drives transcriptional activation of a proinflammatory TNF cluster in normal and malignant pro-B cells

Non-canonical 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 and tonsil donors, performed RNA-seq, 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 cancer driver in several blood cancers. Surprisingly, we discovered that in normal human pro-B cells, the predominant transcript utilized an alternative first exon to produce the poorly characterized FBXW7{beta} isoform, previously thought to be restricted to neural tissues. The FBXW7{beta} transcript was also abundant in cell lines and primary samples of pediatric B-cell acute lymphoblastic leukemia (B-ALL), which originates in the bone marrow. 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, FBXW7{beta} mRNA was the only FBXW7 isoform enriched in the polyribosome fraction. To shed light on possible functions of FBXW7{beta}, we utilized gain- and loss-of-function approaches and identified an FBXW7{beta}-dependent inflammatory gene signature, apparent in a subset of B-ALL with high FBXW7{beta} expression. This signature contained several members of the TNF superfamily, including those comprising the HLA Class III cluster (LTB, LST1, NCR3, LTA, and NFKBIL1). Our findings suggest that FBXW7{beta} expression drives proinflammatory responses, which could contribute to normal B-cell development, leukemogenesis and responses to anti-cancer therapies. Key pointsO_LIPreviously thought to be restricted to neural tissues, FBXW7{beta} is the predominant FBXW7 isoform in normal and malignant human pro-B cells. C_LIO_LIFBXW7{beta} promotes transcriptional activation of a proinflammatory gene cluster that contains TNF superfamily members. C_LI

cell biology↗

bioRxiv2021

Identifying common transcriptome signatures of cancer by interpreting deep learning models

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, signifying that cancer cases display common hallmark molecular features. 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. Here, in order to agnostically identify transcriptomic features that are commonly shared between cancer types, we used RNA-Seq datasets encompassing thousands of samples from 19 healthy 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 healthy and tumor samples. All three models achieve high precision, recall and accuracy on test sets derived from 13 datasets used during training and on an independent test dataset, indicating that our 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, suggesting that they have important cellular functions. Importantly, we found 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. Finally, our results also highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features across a large array of solid tumor types. The transcriptomic features that we highlight here define cancer signatures that may reflect causal variations or consequences of disease state, or a combination of both.

cancer biology↗

bioRxiv2021

RNA splicing analysis using heterogeneous and large RNA-seq1datasets

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 demonstrate that the approaches in MAJIQ v2 outperform 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 new insights into brain subregion-specific splicing regulation.

bioinformatics↗

bioRxiv2021

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

During 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 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 enhanced CD19 mis-splicing. Our dataset represents a comprehensive resource for potential prognostic factors predicting success of CART-19 therapy. HighlightsO_LIMutations in relapsed CART-19 patients lead to CD19 mis-splicing C_LIO_LIHigh-throughput mutagenesis uncovers ~200 single point mutations with a potential role in CART-19 therapy resistance C_LIO_LIMany mutations generate non-functional CD19 proteins by activating cryptic splice sites C_LIO_LIRNA-binding proteins such as PTBP1 are key to the expression of properly spliced, CART-19 immunotherapy-sensitive isoforms C_LI

molecular biology↗