Publications by authors named "Matthew R Gazzara"

21 Publications

  • Page 1 of 1

Enhanced Integrated Gradients: improving interpretability of deep learning models using splicing codes as a case study.

Genome Biol 2020 06 19;21(1):149. Epub 2020 Jun 19.

Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, USA.

Despite the success and fast adaptation of deep learning models in biomedical domains, their lack of interpretability remains an issue. Here, we introduce Enhanced Integrated Gradients (EIG), a method to identify significant features associated with a specific prediction task. Using RNA splicing prediction as well as digit classification as case studies, we demonstrate that EIG improves upon the original Integrated Gradients method and produces sets of informative features. We then apply EIG to identify A1CF as a key regulator of liver-specific alternative splicing, supporting this finding with subsequent analysis of relevant A1CF functional (RNA-seq) and binding data (PAR-CLIP).
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http://dx.doi.org/10.1186/s13059-020-02055-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305616PMC
June 2020

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

Nucleic Acids Res 2020 06;48(10):5710-5719

Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

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.
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http://dx.doi.org/10.1093/nar/gkaa295DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261192PMC
June 2020

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

Genome Res 2019 12 14;29(12):2046-2055. Epub 2019 Nov 14.

Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

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.
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http://dx.doi.org/10.1101/gr.248435.119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886501PMC
December 2019

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

Cell Rep 2019 09;28(11):2795-2806.e3

Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Graduate Group in Biochemistry and Molecular Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

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.
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http://dx.doi.org/10.1016/j.celrep.2019.08.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752737PMC
September 2019

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

Elife 2019 01 24;8. Epub 2019 Jan 24.

Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom.

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 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.
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http://dx.doi.org/10.7554/eLife.39304DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345566PMC
January 2019

Aberrant splicing in B-cell acute lymphoblastic leukemia.

Nucleic Acids Res 2018 11;46(21):11357-11369

Department of Pathology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.

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.
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http://dx.doi.org/10.1093/nar/gky946DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277088PMC
November 2018

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

Nat Commun 2018 06 19;9(1):2407. Epub 2018 Jun 19.

Departments of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, 422 Curie Blvd, Philadelphia, PA, 19104, USA.

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.
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http://dx.doi.org/10.1038/s41467-018-04779-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6008300PMC
June 2018

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

Bioinformatics 2018 Jan;34(2):300-302

Department of Genetics, Perelman School of Medicine, Philadelphia, PA, USA.

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.
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http://dx.doi.org/10.1093/bioinformatics/btx565DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263396PMC
January 2018

Integrative deep models for alternative splicing.

Bioinformatics 2017 Jul;33(14):i274-i282

Department of Computer and Information Science, School of Engineering, University of Pennsylvania, Philadelphia, PA, USA.

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.
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http://dx.doi.org/10.1093/bioinformatics/btx268DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870723PMC
July 2017

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

Genome Res 2017 08 16;27(8):1360-1370. Epub 2017 May 16.

Department of Genetics.

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 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, , and suggests this antagonism is conserved throughout evolution.
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http://dx.doi.org/10.1101/gr.220517.117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538552PMC
August 2017

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

Cell Rep 2016 12;17(12):3269-3280

Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne NE1 3BZ, UK. Electronic address:

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.
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http://dx.doi.org/10.1016/j.celrep.2016.12.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5199341PMC
December 2016

Position-dependent activity of CELF2 in the regulation of splicing and implications for signal-responsive regulation in T cells.

RNA Biol 2016 06 20;13(6):569-81. Epub 2016 Apr 20.

a Department of Biochemistry and Biophysics , University of Pennsylvania Perelman School of Medicine , Philadelphia , PA , USA.

CELF2 is an RNA binding protein that has been implicated in developmental and signal-dependent splicing in the heart, brain and T cells. In the heart, CELF2 expression decreases during development, while in T cells CELF2 expression increases both during development and in response to antigen-induced signaling events. Although hundreds of CELF2-responsive splicing events have been identified in both heart and T cells, the way in which CELF2 functions has not been broadly investigated. Here we use CLIP-Seq to identified physical targets of CELF2 in a cultured human T cell line. By comparing the results with known functional targets of CELF2 splicing regulation from the same cell line we demonstrate a generalizable position-dependence of CELF2 activity that is consistent with previous mechanistic studies of individual CELF2 target genes in heart and brain. Strikingly, this general position-dependence is sufficient to explain the bi-directional activity of CELF2 on 2 T cell targets recently reported. Therefore, we propose that the location of CELF2 binding around an exon is a primary predictor of CELF2 function in a broad range of cellular contexts.
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http://dx.doi.org/10.1080/15476286.2016.1176663DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962813PMC
June 2016

A new view of transcriptome complexity and regulation through the lens of local splicing variations.

Elife 2016 Feb 1;5:e11752. Epub 2016 Feb 1.

Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States.

Alternative splicing (AS) can critically affect gene function and disease, yet mapping splicing variations remains a challenge. Here, we propose a new approach to define and quantify mRNA splicing in units of local splicing variations (LSVs). LSVs capture previously defined types of alternative splicing as well as more complex transcript variations. Building the first genome wide map of LSVs from twelve mouse tissues, we find complex LSVs constitute over 30% of tissue dependent transcript variations and affect specific protein families. We show the prevalence of complex LSVs is conserved in humans and identify hundreds of LSVs that are specific to brain subregions or altered in Alzheimer's patients. Amongst those are novel isoforms in the Camk2 family and a novel poison exon in Ptbp1, a key splice factor in neurogenesis. We anticipate the approach presented here will advance the ability to relate tissue-specific splice variation to genetic variation, phenotype, and disease.
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http://dx.doi.org/10.7554/eLife.11752DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801060PMC
February 2016

Convergence of Acquired Mutations and Alternative Splicing of CD19 Enables Resistance to CART-19 Immunotherapy.

Cancer Discov 2015 Dec 29;5(12):1282-95. Epub 2015 Oct 29.

Division of Cancer Pathobiology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. Immunology Graduate Group, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania. Cell & Molecular Biology Graduate Group, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania. Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Unlabelled: The CD19 antigen, expressed on most B-cell acute lymphoblastic leukemias (B-ALL), can be targeted with chimeric antigen receptor-armed T cells (CART-19), but relapses with epitope loss occur in 10% to 20% of pediatric responders. We detected hemizygous deletions spanning the CD19 locus and de novo frameshift and missense mutations in exon 2 of CD19 in some relapse samples. However, we also discovered alternatively spliced CD19 mRNA species, including one lacking exon 2. Pull-down/siRNA experiments identified SRSF3 as a splicing factor involved in exon 2 retention, and its levels were lower in relapsed B-ALL. Using genome editing, we demonstrated that exon 2 skipping bypasses exon 2 mutations in B-ALL cells and allows expression of the N-terminally truncated CD19 variant, which fails to trigger killing by CART-19 but partly rescues defects associated with CD19 loss. Thus, this mechanism of resistance is based on a combination of deleterious mutations and ensuing selection for alternatively spliced RNA isoforms.

Significance: CART-19 yield 70% response rates in patients with B-ALL, but also produce escape variants. We discovered that the underlying mechanism is the selection for preexisting alternatively spliced CD19 isoforms with the compromised CART-19 epitope. This mechanism suggests a possibility of targeting alternative CD19 ectodomains, which could improve survival of patients with B-cell neoplasms.
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http://dx.doi.org/10.1158/2159-8290.CD-15-1020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4670800PMC
December 2015

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

Genes Dev 2015 Oct;29(19):2054-66

Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA; Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennysylvania 19104, USA.

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.
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http://dx.doi.org/10.1101/gad.267245.115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4604346PMC
October 2015

Induced transcription and stability of CELF2 mRNA drives widespread alternative splicing during T-cell signaling.

Proc Natl Acad Sci U S A 2015 Apr 13;112(17):E2139-48. Epub 2015 Apr 13.

Departments of Biochemistry and Biophysics and Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; and

Studies in several cell types have highlighted dramatic and diverse changes in mRNA processing that occur upon cellular stimulation. However, the mechanisms and pathways that lead to regulated changes in mRNA processing remain poorly understood. Here we demonstrate that expression of the splicing factor CELF2 (CUGBP, Elav-like family member 2) is regulated in response to T-cell signaling through combined increases in transcription and mRNA stability. Transcriptional induction occurs within 6 h of stimulation and is dependent on activation of NF-κB. Subsequently, there is an increase in the stability of the CELF2 mRNA that correlates with a change in CELF2 3'UTR length and contributes to the total signal-induced enhancement of CELF2 expression. Importantly, we uncover dozens of splicing events in cultured T cells whose changes upon stimulation are dependent on CELF2 expression, and provide evidence that CELF2 controls a similar proportion of splicing events during human thymic T-cell development. Taken together, these findings expand the physiologic impact of CELF2 beyond that previously documented in developing neuronal and muscle cells to T-cell development and function, identify unappreciated instances of alternative splicing in the human thymus, and uncover novel mechanisms for CELF2 regulation that may broadly impact CELF2 expression across diverse cell types.
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http://dx.doi.org/10.1073/pnas.1423695112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4418860PMC
April 2015

In silico to in vivo splicing analysis using splicing code models.

Methods 2014 May 7;67(1):3-12. Epub 2013 Dec 7.

Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

With the growing appreciation of RNA splicing's role in gene regulation, development, and disease, researchers from diverse fields find themselves investigating exons of interest. Commonly, researchers are interested in knowing if an exon is alternatively spliced, if it is differentially included in specific tissues or in developmental stages, and what regulatory elements control its inclusion. An important step towards the ability to perform such analysis in silico was made with the development of computational splicing code models. Aimed as a practical how-to guide, we demonstrate how researchers can now use these code models to analyze a gene of interest, focusing on Bin1 as a case study. Bridging integrator 1 (BIN1) is a nucleocytoplasmic adaptor protein known to be functionally regulated through alternative splicing in a tissue-specific manner. Specific Bin1 isoforms have been associated with muscular diseases and cancers, making the study of its splicing regulation of wide interest. Using AVISPA, a recently released web tool based on splicing code models, we show that many Bin1 tissue-dependent isoforms are correctly predicted, along with many of its known regulators. We review the best practices and constraints of using the tool, demonstrate how AVISPA is used to generate high confidence novel regulatory hypotheses, and experimentally validate predicted regulators of Bin1 alternative splicing.
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http://dx.doi.org/10.1016/j.ymeth.2013.11.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4321995PMC
May 2014

Contrasting dynamics of a mutator allele in asexual populations of differing size.

Evolution 2012 Jul 4;66(7):2329-34. Epub 2012 Mar 4.

Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6018, USA.

Mutators have been shown to hitchhike in asexual populations when the anticipated beneficial mutation supply rate of the mutator subpopulation, NU(b) (for subpopulation of size N and beneficial mutation rate U(b)) exceeds that of the wild-type subpopulation. Here, we examine the effect of total population size on mutator dynamics in asexual experimental populations of Saccharomyces cerevisiae. Although mutators quickly hitchhike to fixation in smaller populations, mutator fixation requires more and more time as population size increases; this observed delay in mutator hitchhiking is consistent with the expected effect of clonal interference. Interestingly, despite their higher beneficial mutation supply rate, mutators are supplanted by the wild type in very large populations. We postulate that this striking reversal in mutator dynamics is caused by an interaction between clonal interference, the fitness cost of the mutator allele, and infrequent large-effect beneficial mutations in our experimental populations. Our work thus identifies a potential set of circumstances under which mutator hitchhiking can be inhibited in natural asexual populations, despite recent theoretical predictions that such populations should have a net tendency to evolve ever-higher genomic mutation rates.
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http://dx.doi.org/10.1111/j.1558-5646.2011.01577.xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3389705PMC
July 2012

Mutator dynamics in sexual and asexual experimental populations of yeast.

BMC Evol Biol 2011 Jun 7;11:158. Epub 2011 Jun 7.

Department of Biology, University of Pennsylvania, Philadelphia, PA 19104-6018, USA.

Background: In asexual populations, mutators may be expected to hitchhike with associated beneficial mutations. In sexual populations, recombination is predicted to erode such associations, inhibiting mutator hitchhiking. To investigate the effect of recombination on mutators experimentally, we compared the frequency dynamics of a mutator allele (msh2Δ) in sexual and asexual populations of Saccharomyces cerevisiae.

Results: Mutator strains increased in frequency at the expense of wild-type strains in all asexual diploid populations, with some approaching fixation in 150 generations of propagation. Over the same period of time, mutators declined toward loss in all corresponding sexual diploid populations as well as in haploid populations propagated asexually.

Conclusions: We report the first experimental investigation of mutator dynamics in sexual populations. We show that a strong mutator quickly declines in sexual populations while hitchhiking to high frequency in asexual diploid populations, as predicted by theory. We also show that the msh2Δ mutator has a high and immediate realized cost that is alone sufficient to explain its decline in sexual populations. We postulate that this cost is indirect; namely, that it is due to a very high rate of recessive lethal or strongly deleterious mutation. However, we cannot rule out the possibility that msh2Δ also has unknown directly deleterious effects on fitness, and that these effects may differ between haploid asexual and sexual populations. Despite these reservations, our results prompt us to speculate that the short-term cost of highly deleterious recessive mutations can be as important as recombination in preventing mutator hitchhiking in sexual populations.
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http://dx.doi.org/10.1186/1471-2148-11-158DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141426PMC
June 2011