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Wang W, Li Y, Ko S, Feng N, Zhang M, Liu JJ, Zheng S, Ren B, Yu YP, Luo JH, Tseng GC, Liu S. IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.11.593690. [PMID: 38798496 PMCID: PMC11118288 DOI: 10.1101/2024.05.11.593690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong .
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McShane A, Narayanan IV, Paulsen MT, Ashaka M, Blinkiewicz H, Yang NT, Magnuson B, Bedi K, Wilson TE, Ljungman M. Characterizing nascent transcription patterns of PROMPTs, eRNAs, and readthrough transcripts in the ENCODE4 deeply profiled cell lines. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.09.588612. [PMID: 38645116 PMCID: PMC11030308 DOI: 10.1101/2024.04.09.588612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Arising as co-products of canonical gene expression, transcription-associated lincRNAs, such as promoter upstream transcripts (PROMPTs), enhancer RNAs (eRNAs), and readthrough (RT) transcripts, are often regarded as byproducts of transcription, although they may be important for the expression of nearby genes. We identified regions of nascent expression of these lincRNA in 16 human cell lines using Bru-seq techniques, and found distinctly regulated patterns of PROMPT, eRNA, and RT transcription using the diverse biochemical approaches in the ENCODE4 deeply profiled cell lines collection. Transcription of these lincRNAs was influenced by sequence-specific features and the local or 3D chromatin landscape. However, these sequence and chromatin features do not describe the full spectrum of lincRNA expression variability we identify, highlighting the complexity of their regulation. This may suggest that transcription-associated lincRNAs are not merely byproducts, but rather that the transcript itself, or the act of its transcription, is important for genomic function.
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Buerger F, Salmanullah D, Liang L, Gauntner V, Krueger K, Qi M, Sharma V, Rubin A, Ball D, Lemberg K, Saida K, Merz LM, Sever S, Issac B, Sun L, Guerrero-Castillo S, Gomez AC, McNulty MT, Sampson MG, Al-Hamed MH, Saleh MM, Shalaby M, Kari J, Fawcett JP, Hildebrandt F, Majmundar AJ. Recessive variants in the intergenic NOS1AP-C1orf226 locus cause monogenic kidney disease responsive to anti-proteinuric treatment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.17.24303374. [PMID: 38562757 PMCID: PMC10984069 DOI: 10.1101/2024.03.17.24303374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
In genetic disease, an accurate expression landscape of disease genes and faithful animal models will enable precise genetic diagnoses and therapeutic discoveries, respectively. We previously discovered that variants in NOS1AP , encoding nitric oxide synthase 1 (NOS1) adaptor protein, cause monogenic nephrotic syndrome (NS). Here, we determined that an intergenic splice product of N OS1AP / Nos1ap and neighboring C1orf226/Gm7694 , which precludes NOS1 binding, is the predominant isoform in mammalian kidney transcriptional and proteomic data. Gm7694 -/- mice, whose allele exclusively disrupts the intergenic product, developed NS phenotypes. In two human NS subjects, we identified causative NOS1AP splice variants, including one predicted to abrogate intergenic splicing but initially misclassified as benign based on the canonical transcript. Finally, by modifying genetic background, we generated a faithful mouse model of NOS1AP -associated NS, which responded to anti-proteinuric treatment. This study highlights the importance of intergenic splicing and a potential treatment avenue in a mendelian disorder.
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Murali M, Saquing J, Lu S, Gao Z, Jordan B, Wakefield ZP, Fiszbein A, Cooper DR, Castaldi PJ, Korkin D, Sheynkman G. Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585320. [PMID: 38559226 PMCID: PMC10980011 DOI: 10.1101/2024.03.15.585320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5' UTR alternative splicing. Biosurfer's detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed "ragged codons". Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a "snapback" frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfer's comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.
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Affiliation(s)
- Mayank Murali
- Broad Institute of MIT and Harvard University, Cambridge, MA, USA
| | - Jamie Saquing
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Senbao Lu
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
- Computer Science Department, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Ziyang Gao
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
- Computer Science Department, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Ben Jordan
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Zachary Peters Wakefield
- Bioinformatics Program, Boston University, Boston, MA, USA
- Department of Biology, Boston University, Boston, MA, USA
| | - Ana Fiszbein
- Bioinformatics Program, Boston University, Boston, MA, USA
- Department of Biology, Boston University, Boston, MA, USA
| | - David R. Cooper
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Peter J. Castaldi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dmitry Korkin
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
- Computer Science Department, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Gloria Sheynkman
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- UVA Cancer Center, University of Virginia, Charlottesville, VA, USA
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5
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Adams M, Vollmers C. Generation and analysis of a mouse multi-tissue genome annotation atlas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578267. [PMID: 38352519 PMCID: PMC10862843 DOI: 10.1101/2024.01.31.578267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Generating an accurate and complete genome annotation for an organism is complex because the cells within each tissue can express a unique set of transcript isoforms from a unique set of genes. A comprehensive genome annotation should contain information on what tissues express what transcript isoforms at what level. This tissue-level isoform information can then inform a wide range of research questions as well as experiment designs. Long-read sequencing technology combined with advanced full-length cDNA library preparation methods has now achieved throughput and accuracy where generating these types of annotations is achievable. Here, we show this by generating a genome annotation of the mouse (Mus musculus). We used the nanopore-based R2C2 long-read sequencing method to generate 64 million highly accurate full length cDNA consensus reads - averaging 5.4 million reads per tissue for a dozen tissues. Using the Mandalorion tool we processed these reads to generate the Tissue-level Atlas of Mouse Isoforms (TAMI - available at https://genome.ucsc.edu/s/vollmers/TAMI) which we believe will be a valuable complement to conventional, manually curated reference genome annotations.
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Affiliation(s)
- Matthew Adams
- Department of Molecular, Cellular, and Developmental Biology, University of California Santa Cruz
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Jones EF, Howton TC, Flanary VL, Clark AD, Lasseigne BN. Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575219. [PMID: 38260631 PMCID: PMC10802568 DOI: 10.1101/2024.01.11.575219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease. Long-read sequencing enables more accurate quantification of differentially spliced isoform expression than short-read sequencing approaches, and third-generation platforms facilitate high-throughput experiments. To assess differences in AS across the cerebellum, cortex, hippocampus, and striatum by sex, we generated and analyzed Oxford Nanopore Technologies (ONT) long-read RNA sequencing (lrRNA-Seq) C57BL/6J mouse brain cDNA libraries. From >85 million reads that passed quality control metrics, we calculated differential gene expression (DGE), differential transcript expression (DTE), and differential transcript usage (DTU) across brain regions and by sex. We found significant DGE, DTE, and DTU across brain regions and that the cerebellum had the most differences compared to the other three regions. Additionally, we found region-specific differential splicing between sexes, with the most sex differences in DTU in the cortex and no DTU in the hippocampus. We also report on two distinct patterns of sex DTU we observed, sex-divergent and sex-specific, that could potentially help explain sex differences in the prevalence and prognosis of various neurological and psychiatric disorders in future studies. Finally, we built a Shiny web application for researchers to explore the data further. Our study provides a resource for the community; it underscores the importance of AS in biological heterogeneity and the utility of long-read sequencing to better understand AS in the brain.
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Affiliation(s)
- Emma F. Jones
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Timothy C. Howton
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Victoria L. Flanary
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Amanda D. Clark
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Brittany N. Lasseigne
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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Calvo-Roitberg E, Carroll CL, Venev SV, Kim G, Mick ST, Dekker J, Fiszbein A, Pai AA. mRNA initiation and termination are spatially coordinated. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574404. [PMID: 38260419 PMCID: PMC10802295 DOI: 10.1101/2024.01.05.574404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The expression of a precise mRNA transcriptome is crucial for establishing cell identity and function, with dozens of alternative isoforms produced for a single gene sequence. The regulation of mRNA isoform usage occurs by the coordination of co-transcriptional mRNA processing mechanisms across a gene. Decisions involved in mRNA initiation and termination underlie the largest extent of mRNA isoform diversity, but little is known about any relationships between decisions at both ends of mRNA molecules. Here, we systematically profile the joint usage of mRNA transcription start sites (TSSs) and polyadenylation sites (PASs) across tissues and species. Using both short and long read RNA-seq data, we observe that mRNAs preferentially using upstream TSSs also tend to use upstream PASs, and congruently, the usage of downstream sites is similarly paired. This observation suggests that mRNA 5' end choice may directly influence mRNA 3' ends. Our results suggest a novel "Positional Initiation-Termination Axis" (PITA), in which the usage of alternative terminal sites are coupled based on the order in which they appear in the genome. PITA isoforms are more likely to encode alternative protein domains and use conserved sites. PITA is strongly associated with the length of genomic features, such that PITA is enriched in longer genes with more area devoted to regions that regulate alternative 5' or 3' ends. Strikingly, we found that PITA genes are more likely than non-PITA genes to have multiple, overlapping chromatin structural domains related to pairing of ordinally coupled start and end sites. In turn, PITA coupling is also associated with fast RNA Polymerase II (RNAPII) trafficking across these long gene regions. Our findings indicate that a combination of spatial and kinetic mechanisms couple transcription initiation and mRNA 3' end decisions based on ordinal position to define the expression mRNA isoforms.
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Affiliation(s)
| | | | - Sergey V. Venev
- Department of Systems Biology, University Massachusetts Chan Medical School, Worcester, MA
| | - GyeungYun Kim
- Department of Biology, Boston University, Boston, MA
| | | | - Job Dekker
- Department of Systems Biology, University Massachusetts Chan Medical School, Worcester, MA
- Howard Hughes Medical Institute, Chevy Chase, MD
| | - Ana Fiszbein
- Department of Biology, Boston University, Boston, MA
- Center for Computing & Data Sciences, Boston University, Boston, MA
| | - Athma A. Pai
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA
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Audet S, Triassi V, Gelinas M, Legault-Cadieux N, Ferraro V, Duquette A, Tetreault M. Integration of multi-omics technologies for molecular diagnosis in ataxia patients. Front Genet 2024; 14:1304711. [PMID: 38239855 PMCID: PMC10794629 DOI: 10.3389/fgene.2023.1304711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 11/27/2023] [Indexed: 01/22/2024] Open
Abstract
Background: Episodic ataxias are rare neurological disorders characterized by recurring episodes of imbalance and coordination difficulties. Obtaining definitive molecular diagnoses poses challenges, as clinical presentation is highly heterogeneous, and literature on the underlying genetics is limited. While the advent of high-throughput sequencing technologies has significantly contributed to Mendelian disorders genetics, interpretation of variants of uncertain significance and other limitations inherent to individual methods still leaves many patients undiagnosed. This study aimed to investigate the utility of multi-omics for the identification and validation of molecular candidates in a cohort of complex cases of ataxia with episodic presentation. Methods: Eight patients lacking molecular diagnosis despite extensive clinical examination were recruited following standard genetic testing. Whole genome and RNA sequencing were performed on samples isolated from peripheral blood mononuclear cells. Integration of expression and splicing data facilitated genomic variants prioritization. Subsequently, long-read sequencing played a crucial role in the validation of those candidate variants. Results: Whole genome sequencing uncovered pathogenic variants in four genes (SPG7, ATXN2, ELOVL4, PMPCB). A missense and a nonsense variant, both previously reported as likely pathogenic, configured in trans in individual #1 (SPG7: c.2228T>C/p.I743T, c.1861C>T/p.Q621*). An ATXN2 microsatellite expansion (CAG32) in another late-onset case. In two separate individuals, intronic variants near splice sites (ELOVL4: c.541 + 5G>A; PMPCB: c.1154 + 5G>C) were predicted to induce loss-of-function splicing, but had never been reported as disease-causing. Long-read sequencing confirmed the compound heterozygous variants configuration, repeat expansion length, as well as splicing landscape for those pathogenic variants. A potential genetic modifier of the ATXN2 expansion was discovered in ZFYVE26 (c.3022C>T/p.R1008*). Conclusion: Despite failure to identify pathogenic variants through clinical genetic testing, the multi-omics approach enabled the molecular diagnosis in 50% of patients, also giving valuable insights for variant prioritization in remaining cases. The findings demonstrate the value of long-read sequencing for the validation of candidate variants in various scenarios. Our study demonstrates the effectiveness of leveraging complementary omics technologies to unravel the underlying genetics in patients with unresolved rare diseases such as ataxia. Molecular diagnoses not only hold significant promise in improving patient care management, but also alleviates the burden of diagnostic odysseys, more broadly enhancing quality of life.
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Affiliation(s)
- Sebastien Audet
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
| | - Valerie Triassi
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
| | - Myriam Gelinas
- Department of Medicine, University of Montreal Hospital Centre (CHUM), Montreal, QC, Canada
| | - Nab Legault-Cadieux
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
| | - Vincent Ferraro
- Department of Medicine, University of Montreal Hospital Centre (CHUM), Montreal, QC, Canada
| | - Antoine Duquette
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- Neurology Service, Department of Medicine, André-Barbeau Movement Disorders Unit, University of Montreal Hospital (CHUM), Montreal, QC, Canada
- Genetic Service, Department of Medicine, University of Montreal Hospital (CHUM), Montreal, QC, Canada
| | - Martine Tetreault
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
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9
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Taylor DJ, Chhetri SB, Tassia MG, Biddanda A, Battle A, McCoy RC. Sources of gene expression variation in a globally diverse human cohort. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.04.565639. [PMID: 37965206 PMCID: PMC10635147 DOI: 10.1101/2023.11.04.565639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Genetic variation influencing gene expression and splicing is a key source of phenotypic diversity. Though invaluable, studies investigating these links in humans have been strongly biased toward participants of European ancestries, diminishing generalizability and hindering evolutionary research. To address these limitations, we developed MAGE, an open-access RNA-seq data set of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, mirroring variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-eQTLs and cis-sQTLs, respective), identifying >15,000 putatively causal eQTLs and >16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1310 eQTLs and 1657 sQTLs that are largely private to previously underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations and that apparent "population-specific" effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands understanding of gene expression diversity across human populations and provides an inclusive resource for studying the evolution and function of human genomes.
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Affiliation(s)
- Dylan J. Taylor
- Department of Biology, Johns Hopkins University, Baltimore MD, USA
| | - Surya B. Chhetri
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, USA
| | | | - Arjun Biddanda
- Department of Biology, Johns Hopkins University, Baltimore MD, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore MD, USA
- Department of Genetic Medicine, Johns Hopkins University, Baltimore MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore MD, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University, Baltimore MD, USA
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10
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Schertzer MD, Stirn A, Isaev K, Pereira L, Das A, Harbison C, Park SH, Wessels HH, Sanjana NE, Knowles DA. Cas13d-mediated isoform-specific RNA knockdown with a unified computational and experimental toolbox. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.12.557474. [PMID: 37745416 PMCID: PMC10515814 DOI: 10.1101/2023.09.12.557474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Alternative splicing is an essential mechanism for diversifying proteins, in which mature RNA isoforms produce proteins with potentially distinct functions. Two major challenges in characterizing the cellular function of isoforms are the lack of experimental methods to specifically and efficiently modulate isoform expression and computational tools for complex experimental design. To address these gaps, we developed and methodically tested a strategy which pairs the RNA-targeting CRISPR/Cas13d system with guide RNAs that span exon-exon junctions in the mature RNA. We performed a high-throughput essentiality screen, quantitative RT-PCR assays, and PacBio long read sequencing to affirm our ability to specifically target and robustly knockdown individual RNA isoforms. In parallel, we provide computational tools for experimental design and screen analysis. Considering all possible splice junctions annotated in GENCODE for multi-isoform genes and our gRNA efficacy predictions, we estimate that our junction-centric strategy can uniquely target up to 89% of human RNA isoforms, including 50,066 protein-coding and 11,415 lncRNA isoforms. Importantly, this specificity spans all splicing and transcriptional events, including exon skipping and inclusion, alternative 5' and 3' splice sites, and alternative starts and ends.
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Affiliation(s)
- Megan D Schertzer
- New York Genome Center, New York, NY
- Department of Computer Science, Columbia University, New York, NY
| | - Andrew Stirn
- New York Genome Center, New York, NY
- Department of Computer Science, Columbia University, New York, NY
| | - Keren Isaev
- New York Genome Center, New York, NY
- Department of Systems Biology, Columbia University, New York, NY
| | | | - Anjali Das
- New York Genome Center, New York, NY
- Department of Computer Science, Columbia University, New York, NY
| | | | - Stella H Park
- New York Genome Center, New York, NY
- Department of Biomedical Engineering, Columbia University, New York, NY
| | - Hans-Hermann Wessels
- New York Genome Center, New York, NY
- Department of Biology, New York University, New York, NY
| | - Neville E Sanjana
- New York Genome Center, New York, NY
- Department of Biology, New York University, New York, NY
| | - David A Knowles
- New York Genome Center, New York, NY
- Department of Computer Science, Columbia University, New York, NY
- Department of Systems Biology, Columbia University, New York, NY
- Data Science Institute, Columbia University, New York, NY
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11
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Zhang Z, Bae B, Cuddleston WH, Miura P. Coordination of alternative splicing and alternative polyadenylation revealed by targeted long read sequencing. Nat Commun 2023; 14:5506. [PMID: 37679364 PMCID: PMC10484994 DOI: 10.1038/s41467-023-41207-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 08/25/2023] [Indexed: 09/09/2023] Open
Abstract
Nervous system development is associated with extensive regulation of alternative splicing (AS) and alternative polyadenylation (APA). AS and APA have been extensively studied in isolation, but little is known about how these processes are coordinated. Here, the coordination of cassette exon (CE) splicing and APA in Drosophila was investigated using a targeted long-read sequencing approach we call Pull-a-Long-Seq (PL-Seq). This cost-effective method uses cDNA pulldown and Nanopore sequencing combined with an analysis pipeline to quantify inclusion of alternative exons in connection with alternative 3' ends. Using PL-Seq, we identified genes that exhibit significant differences in CE splicing depending on connectivity to short versus long 3'UTRs. Genomic long 3'UTR deletion was found to alter upstream CE splicing in short 3'UTR isoforms and ELAV loss differentially affected CE splicing depending on connectivity to alternative 3'UTRs. This work highlights the importance of considering connectivity to alternative 3'UTRs when monitoring AS events.
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Affiliation(s)
- Zhiping Zhang
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA
- Department of Biology, University of Nevada, Reno, Reno, NV, USA
| | - Bongmin Bae
- Department of Biology, University of Nevada, Reno, Reno, NV, USA
| | | | - Pedro Miura
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA.
- Department of Biology, University of Nevada, Reno, Reno, NV, USA.
- Institute for System Genomics, University of Connecticut, Storrs, CT, USA.
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