Biology subjects

Barash, Y.

Publications and source records attributed to Barash, Y..

36 records · Page 2Linked to original sources

bioRxiv2021

The Global Protein-RNA Interaction map of Epithelial Splicing Regulatory Protein 1 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 regulation of a global program of alternative splicing of genes involved in 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 either promote 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.

molecular biology↗

bioRxiv2020

RBMX enables productive RNA processing of ultra-long exons important for genome stability

Previously we showed that the germline-specific RNA binding protein RBMXL2 is essential for male meiosis where it represses cryptic splicing patterns (1). Here we find that its ubiquitously expressed paralog RBMX helps underpin human genome stability by preventing non-productive splicing. In particular, RBMX blocks selection of aberrant splice and polyadenylation sites within some ultra-long exons that would interfere with genes needed for normal replication fork activity. Target exons include within the ETAA1 (Ewings Tumour Associated 1) gene, where RBMX collaborates with its interaction partner Tra2{beta} to enable full-length exon inclusion by blocking selection of an aberrant 3 splice site. Our data reveal a novel group of RNA processing targets potently repressed by RBMX, and help explain why RBMX is associated with gene expression networks in cancer, replication and sensitivity to genotoxic drugs.

molecular biology↗

bioRxiv2020

Disrupting upstream translation in mRNAs leads to loss-of function associated with human disease

Ribosome-profiling has uncovered pervasive translation in 5UTRs, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate new gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals respectively, and demonstrate their impact on gene expression in human cells. Our results establish new mechanisms relating uORF variation to loss-of-function of downstream genes, and demonstrate that translated uORFs are genetically constrained regulatory elements in 40% of human genes.

genomics↗

bioRxiv2020

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

While the effects of confounders on gene expression analysis have been extensively studied there is a lack of equivalent analysis and tools for RNA splicing analysis. Here we assess the effect of confounders in two large public RNA-Seq datasets (TARGET, ENCODE), develop a new method, MOCCASIN, to correct the effect of both known and unknown confounders on RNA splicing quantification, and demonstrate MOCCASINs effectiveness on both synthetic and real data.

genomics↗

bioRxiv2020

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 alternative mechanisms for gene disruption contribute to this disease. Here we find a set of splicing events that disrupt the expression of a subset of AML-associated genes, including EZH2 and ZRSR2, independent of known somatic mutations. Most strikingly, in at least one cohort, aberrant splicing triples the number of patients with a reduction in functional EZH2 as compared to that predicted by somatic mutation of EZH2 alone. Together, these results demonstrate that classical mutation analysis underestimates the burden of functional gene disruption in AML and highlights the importance of assessing the contribution of alternative splicing to gene dysregulation in human disease.

genomics↗

bioRxiv2020

Rapid and scalable profiling of nascent RNA with fastGRO

Genome-wide profiling of nascent RNA has become a fundamental tool to study transcription regulation. Over the past decade, next-generation sequencing has fostered development of a handful of techniques (i.e. GRO-seq, PRO-seq, TT-seq and NET-seq) that map unprocessed transcripts originating from both the coding and the noncoding portion of the genome. Unlike steady-state RNA sequencing, nascent RNA profiling mirrors the real-time activity of RNA Polymerases and provides an accurate readout of transcriptome-wide variations that occur during short time frames (i.e. response to external stimuli or rapid metabolic changes). Some species of nuclear RNAs, albeit functional, have a short half-life and can only be accurately gauged by nascent RNA techniques (i.e. lincRNAs and eRNAs). Furthermore, these techniques capture uncapped post-cleavage RNA at termination sites or promoter-associated antisense RNAs, providing a unique insight into RNAPII dynamics and processivity. Here we present a run-on assay with 4s-UTP labelling, followed by reversible biotinylation and affinity purification via streptavidin. Our protocol allows streamlined sample preparation within less than 3 days. We named the technique fastGRO (fast Global Run-On). We show that fastGRO is highly reproducible and yields a more complete and extensive coverage of nascent RNA than comparable techniques. Importantly, we demonstrate that fastGRO is scalable and can be performed with as few as 0.5x10^6 cells.

genomics↗

bioRxiv2019

Set2-mediated alternative splicing of Srsf11 regulates cocaine reward behavior

Alternative splicing is a key mechanism for neuronal gene regulation, and is grossly altered in mouse brain reward regions following investigator-administered cocaine. It is well established that cocaine epigenetically regulates transcription, yet mechanism(s) by which cocaine-induced epigenetic modifications regulate alternative splicing is largely unexplored. Our group and others have previously identified the histone modification, H3K36me3, as a putative splicing regulator. However, it has not yet been possible to establish the direct causal relevance of this modification to alternative splicing in brain or any other context. We found that mouse cocaine self-administration caused widespread alternative splicing, concomitant with enrichment of H3K36me3 at splice junctions. Differentially spliced genes were enriched in the motif for splice factor, Srsf11, which was both differentially spliced and enriched in H3K36me3. Epigenetic editing led us to conclude that H3K36me3 functions directly in alternative splicing of Srsf11, and that Set2 mediated H3K36me3 bidirectionally regulates cocaine intake.

neuroscience↗

bioRxiv2019

Meta-Analysis of Transcriptomic Variation in T cell Populations Reveals Novel Signatures of Gene Expression and Splicing

Distinct T cell subtypes are typically defined by the expression of distinct gene repertoires. However, there is variability between studies regarding the markers used to define each T cell subtype. Moreover, previous analysis of gene expression in 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 identify transcriptomic features that correlate consistently with subtype. 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 consistently differentiate between subsets, including a few Treg-specific splicing patterns. Together this work highlights the heterogeneity in gene expression between isolates of the same subtype, but also suggests additional markers that can be used to define functional groupings.

immunology↗

bioRxiv2019

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

PurposeRNA-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 non-accessible tissues (non-CATs). We determined how RNA-seq from CATs represent splicing in and across genes and non-CATs.\n\nMethodsWe quantified RNA splicing in 801 RNA-seq samples from 56 different adult and fetal tissues from 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.\n\nResultsIn non-CATs, 39.7% of genes have splicing that is inadequately represented by at least one CAT. 6.2% of genes have splicing inadequately represented by all CATs. A majority (52.8%) of inadequately represented genes are lowly expressed in CATs (TPM < 1), but 6.2% are inadequately represented despite being well expressed (TPM > 10).\n\nConclusionMany 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.

genomics↗

bioRxiv2019

Improving interpretability of deep learning models: splicing codes as a case study

Despite the success and fast adaptation of deep learning models in a wide range of fields, lack of interpretability remains an issue, especially in biomedical domains. A recent promising method to address this limitation is Integrated Gradients (IG), which identifies features associated with a prediction by traversing a linear path from a baseline to a sample. We extend IG with nonlinear paths, embedding in latent space, alternative baselines, and a framework to identify important features which make it suitable for interpretation of deep models for genomics.

bioinformatics↗

bioRxiv2019

Integrative analysis reveals RNA G-Quadruplexes in UTRs are selectively constrained and enriched for functional associations

Identifying regulatory elements in the noncoding genome is a fundamental challenge in biology. G-quadruplex (G4) sequences are abundant in untranslated regions (UTRs) of human messenger RNAs, but their functional importance remains unclear. By integrating multiple sources of genetic and genomic data, we show that putative G-quadruplex forming sequences (pG4) in 5 and 3 UTRs are selectively constrained, and enriched for cis-eQTLs and RNA-binding protein (RBP) interactions. Using over 15,000 whole-genome sequences, we uncover a degree of negative (purifying) selection in UTR pG4s comparable to that of missense variation in protein-coding sequences. In parallel, we identify new proteins with evidence for preferential binding at pG4s from ENCODE annotations, and delineate putative regulatory networks composed of shared binding targets. Finally, by mapping variants in the NIH GWAS Catalogue and ClinVar, we find enrichment for disease-associated variation in 3UTR pG4s. At a GWAS pG4-variant associated with hypertension in HSPB7, we uncover robust allelic imbalance in GTEx RNA-seq across multiple tissues, suggesting that changes in gene expression associated with pG4 disruption underlie the observed phenotypic association. Taken together, our results establish UTR G-quadruplexes as important cis-regulatory features, and point to a putative link between disruption within UTR pG4 and susceptibility to human disease.

genomics↗

bioRxiv2018

LeafCutter vs. MAJIQ and comparing software in the fast-moving field of genomics

In a recent publication, Li et al. introduced LeafCutter, a new method for detecting and quantifying differential splicing of RNA from RNASeq data. In this work, Li et al. first compared LeafCutter to existing methods, then used it for a study of splicing variations and sQTL analysis from a large set of GTEx samples. While the study was elaborate and comprehensive, we want to highlight several issues with the comparative analysis performed by Li et al. We argue these issues created an inaccurate and misleading representation of other tools, namely MAJIQ and rMATS. More broadly, we believe the points we raise regarding the comparative analysis by Li et al. are representative of general issues we all, as authors, editors, and reviewers, are faced with and must address in the current times of fast paced genomics and computational research.

bioinformatics↗

bioRxiv2018

RNA-binding protein A1CF modulates plasma triglyceride levels through posttranscriptional regulation of stress-induced VLDL secretion

BackgroundA recent human exome-chip study on plasma lipids identified a missense mutation in the A1CF (APOBEC1 complementation factor) gene that is associated with elevated triglyceride (TG) levels, but how A1CF, an RNA binding protein, influences plasma TG is unknown.\n\nMethodsWe generated A1cf knockout (A1cf -/-) mice and knock-in mice homozygous for the TG-associated Gly398Ser mutation (A1cfGS/GS), determined lipid phenotypes, and assessed TG physiology through measurements of clearance and secretion. We further identified A1CFs RNA binding targets using enhanced cross-linking and immunoprecipitation sequencing of cultured HepG2 cells and investigated pathways enriched for these targets. Transcriptomic effects of A1CF deficiency were evaluated through RNA sequencing and analyses for differential expression, alternative splicing, and RNA editing.\n\nResultsBoth A1cf -/-and A1cfGS/GS mice exhibited increased fasting plasma TG, establishing that the TG phenotype is due to A1CF loss of function. In vivo TG secretion and clearance studies revealed increased TG secretion without changes in clearance in A1cf -/-mice. Increased VLDL-apoB secretion was also seen in A1cf -/-rat hepatoma cells, but no increase in apoB synthesis was observed. This phenotype was seen without significant shifts in apoB-100/apoB-48 in A1CF deficiency. To discover novel pathways for A1CFs role in TG metabolism, we identified A1CFs RNA binding targets, which were enriched for pathways related to proteasomal catabolism and endoplasmic reticulum (ER) stress. Indeed, proteasomal inhibition led to increased cellular stress in A1cf -/-cells, and higher expression of ER-stress protein GRP78 was observed in resting A1cf -/-cells. RNA-seq of whole livers from wild-type and A1cf -/-mice revealed that pro-inflammatory, not lipogenesis, genes were upregulated as a secondary effect of A1CF deficiency. Differential alternative splicing (AS) analysis and RNA editing analysis revealed that genes involved in cellular stress and metabolism underwent differential changes in A1CF deficiency, and top A1CF binding target proteins with relevance to intracellular stress were differentially expressed on the protein but not mRNA level, implicating multiple mechanisms by which A1CF influences TG secretion.\n\nConclusionsThese data suggest an important role for A1CF in mediating VLDL-TG secretion through regulating intracellular stress.

genomics↗

bioRxiv2017

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 them 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 3UTR was pervasively misspliced, yielding the transcript subject to nonsense-mediated decay. Thus, we knocked it down in B-lymphoblastoid cells, identified 213 hnRNPA1-dependent splicing events, and defined the hnRNPA1 splicing signature in pediatric leukemias. One of its elements was DICER1, a known tumor suppressor gene; its LSVs were consistent with reduced translation of DICER1 mRNA. Additionally, we searched for LSVs in other leukemia and lymphoma drivers and discovered 81 LSVs in 41 genes. 77 LSVs were confirmed using two large independent B-ALL RNA-seq datasets. In fact, the twenty most common B-ALL drivers 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 contribute to disease pathogenesis.

cancer biology↗

bioRxiv2017

MAJIQ-SPEL: Web-Tool To Interrogate Classical And Complex Splicing Variations From RNA-Seq Data

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 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.\n\nAvailability: Program and code will be available at http://majiq.biociphers.org/majiq-spel

bioinformatics↗

bioRxiv2017

Integrative Deep Models for Alternative Splicing

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. 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 and show that it significantly improves model accuracy. Next, we develop a modeling framework 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.\n\nAvailability: code and data will be available on Github following publication.

bioinformatics↗

bioRxiv2017

Outlier detection for improved differential splicing quantification from RNA-Seq experiments withreplicates

A key component in many RNA-Seq based studies is the production of multiple replicates for varying experimental conditions. Such replicates allow to capture underlying biological variability and control for experimental ones. However, during data production researchers often lack clear definitions to what constitutes a \"bad\" replicate which should be discarded and if data from failed replicates is published downstream analysis by groups using this data can be hampered. Here we develop a probability model to weigh a given RNA-Seq experiment as a representative of an experimental condition when performing alternative splicing analysis. Using both synthetic and real life data we demonstrate that this model detects outlier samples which are consistently and significantly different compared to samples from the same condition. Using both synthetic and real life data we perform extensive evaluation of the algorithm in different scenarios involving perturbed samples, mislabeled samples, no-signal groups, and different levels of coverage, and show it compares favorably with current state of the art tools.\n\nAvailabilityProgram and code will be available at majiq.biociphers.org

bioinformatics↗

bioRxiv2017

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 co-regulation 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 co-regulated 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, and Drosophila suggests this antagonism is conserved through evolution.

genomics↗