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Ibeh N, Kusuma P, Crenna Darusallam C, Malik SG, Sudoyo H, McCarthy DJ, Gallego Romero I. Profiling genetically driven alternative splicing across the Indonesian archipelago. Am J Hum Genet 2024; 111:2458-2477. [PMID: 39383868 DOI: 10.1016/j.ajhg.2024.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 09/11/2024] [Accepted: 09/12/2024] [Indexed: 10/11/2024] Open
Abstract
One of the regulatory mechanisms influencing the functional capacity of genes is alternative splicing (AS). Previous studies exploring the splicing landscape of human tissues have shown that AS has contributed to human biology, especially in disease progression and the immune response. Nonetheless, this phenomenon remains poorly characterized across human populations, and it is unclear how genetic and environmental variation contribute to AS. Here, we examine a set of 115 Indonesian samples from three traditional island populations spanning the genetic ancestry cline that characterizes Island Southeast Asia. We conduct a global AS analysis between islands to ascertain the degree of functionally significant AS events and their consequences. Using an event-based statistical model, we detected over 1,500 significant differential AS events across all comparisons. Additionally, we identify over 6,000 genetic variants associated with changes in splicing (splicing quantitative trait loci [sQTLs]), some of which are driven by Papuan-like genetic ancestry, and only show partial overlap with other publicly available sQTL datasets derived from other populations. Computational predictions of RNA binding activity reveal that a fraction of these sQTLs directly modulate the binding propensity of proteins involved in the splicing regulation of immune genes. Overall, these results contribute toward elucidating the role of genetic variation in shaping gene regulation in one of the most diverse regions in the world.
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Affiliation(s)
- Neke Ibeh
- School of BioSciences, University of Melbourne, Parkville, VIC 3010, Australia; Melbourne Integrative Genomics, University of Melbourne, Parkville, VIC 3010, Australia; Bioinformatics and Cellular Genomics, St Vincents Institute of Medical Research, Fitzroy, VIC 3065, Australia; Human Genomics and Evolution, St Vincent's Institute of Medical Research, Fitzroy, VIC 3065, Australia
| | - Pradiptajati Kusuma
- Genome Diversity and Disease Laboratory, Mochtar Riady Institute of Nanotechnology, Tangerang 15811, Indonesia
| | - Chelzie Crenna Darusallam
- Genome Diversity and Disease Laboratory, Mochtar Riady Institute of Nanotechnology, Tangerang 15811, Indonesia
| | - Safarina G Malik
- Genome Diversity and Disease Laboratory, Mochtar Riady Institute of Nanotechnology, Tangerang 15811, Indonesia
| | - Herawati Sudoyo
- Genome Diversity and Disease Laboratory, Mochtar Riady Institute of Nanotechnology, Tangerang 15811, Indonesia
| | - Davis J McCarthy
- Melbourne Integrative Genomics, University of Melbourne, Parkville, VIC 3010, Australia; Bioinformatics and Cellular Genomics, St Vincents Institute of Medical Research, Fitzroy, VIC 3065, Australia; School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Parkville, VIC 3010, Australia
| | - Irene Gallego Romero
- School of BioSciences, University of Melbourne, Parkville, VIC 3010, Australia; Melbourne Integrative Genomics, University of Melbourne, Parkville, VIC 3010, Australia; Human Genomics and Evolution, St Vincent's Institute of Medical Research, Fitzroy, VIC 3065, Australia; Centre for Genomics, Evolution and Medicine, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia.
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2
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Méndez-Albelo NM, Sandoval SO, Xu Z, Zhao X. An in-depth review of the function of RNA-binding protein FXR1 in neurodevelopment. Cell Tissue Res 2024; 398:63-77. [PMID: 39155323 DOI: 10.1007/s00441-024-03912-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 07/30/2024] [Indexed: 08/20/2024]
Abstract
FMR1 autosomal homolog 1 (FXR1) is an RNA-binding protein that belongs to the Fragile X-related protein (FXR) family. FXR1 is critical for development, as its loss of function is intolerant in humans and results in neonatal death in mice. Although FXR1 is expressed widely including the brain, functional studies on FXR1 have been mostly performed in cancer cells. Limited studies have demonstrated the importance of FXR1 in the brain. In this review, we will focus on the roles of FXR1 in brain development and pathogenesis of brain disorders. We will summarize the current knowledge in FXR1 in the context of neural biology, including structural features, isoform diversity and nomenclature, expression patterns, post-translational modifications, regulatory mechanisms, and molecular functions. Overall, FXR1 emerges as an important regulator of RNA metabolism in the brain, with strong implications in neurodevelopmental and psychiatric disorders.
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Affiliation(s)
- Natasha M Méndez-Albelo
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Molecular Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Soraya O Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Zhiyan Xu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Graduate Program in Cellular and Molecular Biology, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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3
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Wang J, Zhu QW, Mai JH, Zhang S, Wang Y, Liang J, Zhou JY. A multi-omics study of brain tissue transcription and DNA methylation revealing the genetic pathogenesis of ADHD. Brief Bioinform 2024; 25:bbae502. [PMID: 39406522 PMCID: PMC11479714 DOI: 10.1093/bib/bbae502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 08/02/2024] [Accepted: 10/01/2024] [Indexed: 10/20/2024] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a chronic psychiatric disease that often affects a patient's whole life. Research has found that genetics plays an important role in the development of ADHD. However, there is still a lack of knowledge about the tissue-specific causal effects of biological processes beyond gene expression, such as alternative splicing (AS) and DNA methylation (DNAm), on ADHD. In this paper, a multi-omics study was conducted to investigate the causal effects of the transcription and the DNAm on ADHD, by integrating ADHD genome-wide association data with quantitative trait loci data of gene expression, AS, and DNAm across 14 different brain tissues. The causal effects were estimated using four different two-sample Mendelian randomization methods. Finally, we also prioritized the expression of 866 genes showing significant causal effects, including COMMD5, ENSG00000271904, HYAL3, etc., within at least one brain tissue. We prioritized 966 unique genes that have statistically significant causal AS events, within at least one of the 14 different brain tissues. These genes include PPP1R16A, GGT7, TREM2, etc. Furthermore, through mediation analysis, 106 regulatory pathways were inferred where DNAm influences ADHD through gene expression or AS processes. Our research findings provide guidance for future experimental studies on the molecular mechanisms of ADHD development, and also put forward valuable knowledge for the prevention, diagnosis, and treatment of ADHD.
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Affiliation(s)
- Jingkai Wang
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Qiu-Wen Zhu
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jia-Hao Mai
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Shun Zhang
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Yuqing Wang
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jiatong Liang
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Ji-Yuan Zhou
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
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4
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Abood A, Mesner LD, Jeffery ED, Murali M, Lehe MD, Saquing J, Farber CR, Sheynkman GM. Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease. Am J Hum Genet 2024; 111:1914-1931. [PMID: 39079539 PMCID: PMC11393689 DOI: 10.1016/j.ajhg.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 08/07/2024] Open
Abstract
A major fraction of loci identified by genome-wide association studies (GWASs) mediate alternative splicing, but mechanistic interpretation is hindered by the technical limitations of short-read RNA sequencing (RNA-seq), which cannot directly link splicing events to full-length protein isoforms. Long-read RNA-seq represents a powerful tool to characterize transcript isoforms, and recently, infer protein isoform existence. Here, we present an approach that integrates information from GWASs, splicing quantitative trait loci (sQTLs), and PacBio long-read RNA-seq in a disease-relevant model to infer the effects of sQTLs on the ultimate protein isoform products they encode. We demonstrate the utility of our approach using bone mineral density (BMD) GWAS data. We identified 1,863 sQTLs from the Genotype-Tissue Expression (GTEx) project in 732 protein-coding genes that colocalized with BMD associations (H4PP ≥ 0.75). We generated PacBio Iso-Seq data (N = ∼22 million full-length reads) on human osteoblasts, identifying 68,326 protein-coding isoforms, of which 17,375 (25%) were unannotated. By casting the sQTLs onto protein isoforms, we connected 809 sQTLs to 2,029 protein isoforms from 441 genes expressed in osteoblasts. Overall, we found that 74 sQTLs influenced isoforms likely impacted by nonsense-mediated decay and 190 that potentially resulted in the expression of unannotated protein isoforms. Finally, we functionally validated colocalizing sQTLs in TPM2, in which siRNA-mediated knockdown in osteoblasts showed two TPM2 isoforms with opposing effects on mineralization but exhibited no effect upon knockdown of the entire gene. Our approach should be to generalize across diverse clinical traits and to provide insights into protein isoform activities modulated by GWAS loci.
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Affiliation(s)
- Abdullah Abood
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Larry D Mesner
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Erin D Jeffery
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Mayank Murali
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Micah D Lehe
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Jamie Saquing
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
| | - Gloria M Sheynkman
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA; UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA, USA.
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5
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Hervoso JL, Amoah K, Dodson J, Choudhury M, Bhattacharya A, Quinones-Valdez G, Pasaniuc B, Xiao X. Splicing-specific transcriptome-wide association uncovers genetic mechanisms for schizophrenia. Am J Hum Genet 2024; 111:1573-1587. [PMID: 38925119 PMCID: PMC11339621 DOI: 10.1016/j.ajhg.2024.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 05/28/2024] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area.
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Affiliation(s)
- Jonatan L Hervoso
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kofi Amoah
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jack Dodson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mudra Choudhury
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Giovanni Quinones-Valdez
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Xinshu Xiao
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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6
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van Haaren MJH, Steller LB, Vastert SJ, Calis JJA, van Loosdregt J. Get Spliced: Uniting Alternative Splicing and Arthritis. Int J Mol Sci 2024; 25:8123. [PMID: 39125692 PMCID: PMC11311815 DOI: 10.3390/ijms25158123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 07/21/2024] [Accepted: 07/22/2024] [Indexed: 08/12/2024] Open
Abstract
Immune responses demand the rapid and precise regulation of gene protein expression. Splicing is a crucial step in this process; ~95% of protein-coding gene transcripts are spliced during mRNA maturation. Alternative splicing allows for distinct functional regulation, as it can affect transcript degradation and can lead to alternative functional protein isoforms. There is increasing evidence that splicing can directly regulate immune responses. For several genes, immune cells display dramatic changes in isoform-level transcript expression patterns upon activation. Recent advances in long-read RNA sequencing assays have enabled an unbiased and complete description of transcript isoform expression patterns. With an increasing amount of cell types and conditions that have been analyzed with such assays, thousands of novel transcript isoforms have been identified. Alternative splicing has been associated with autoimmune diseases, including arthritis. Here, GWASs revealed that SNPs associated with arthritis are enriched in splice sites. In this review, we will discuss how alternative splicing is involved in immune responses and how the dysregulation of alternative splicing can contribute to arthritis pathogenesis. In addition, we will discuss the therapeutic potential of modulating alternative splicing, which includes examples of spliceform-based biomarkers for disease severity or disease subtype, splicing manipulation using antisense oligonucleotides, and the targeting of specific immune-related spliceforms using antibodies.
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Affiliation(s)
- Maurice J. H. van Haaren
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Levina Bertina Steller
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Sebastiaan J. Vastert
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Division of Pediatric Rheumatology and Immunology, Wilhelmina Children’s Hospital, 3584 CX Utrecht, The Netherlands
| | - Jorg J. A. Calis
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Jorg van Loosdregt
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
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7
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Moakley DF, Campbell M, Anglada-Girotto M, Feng H, Califano A, Au E, Zhang C. Reverse engineering neuron type-specific and type-orthogonal splicing-regulatory networks using single-cell transcriptomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.597128. [PMID: 38915499 PMCID: PMC11195221 DOI: 10.1101/2024.06.13.597128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Cell type-specific alternative splicing (AS) enables differential gene isoform expression between diverse neuron types with distinct identities and functions. Current studies linking individual RNA-binding proteins (RBPs) to AS in a few neuron types underscore the need for holistic modeling. Here, we use network reverse engineering to derive a map of the neuron type-specific AS regulatory landscape from 133 mouse neocortical cell types defined by single-cell transcriptomes. This approach reliably inferred the regulons of 350 RBPs and their cell type-specific activities. Our analysis revealed driving factors delineating neuronal identities, among which we validated Elavl2 as a key RBP for MGE-specific splicing in GABAergic interneurons using an in vitro ESC differentiation system. We also identified a module of exons and candidate regulators specific for long- and short-projection neurons across multiple neuronal classes. This study provides a resource for elucidating splicing regulatory programs that drive neuronal molecular diversity, including those that do not align with gene expression-based classifications.
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Affiliation(s)
- Daniel F Moakley
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
| | - Melissa Campbell
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
- Present address: Department of Neurosciences, University of California, San Diego, USA
| | - Miquel Anglada-Girotto
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Present address: Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Huijuan Feng
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
- Present address: Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Andrea Califano
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Edmund Au
- Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA
- Columbia Translational Neuroscience Initiative Scholar, New York, NY 10032, USA
| | - Chaolin Zhang
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
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8
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Hao RH, Zhang TP, Jiang F, Liu JH, Dong SS, Li M, Guo Y, Yang TL. Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression. Nat Commun 2024; 15:4890. [PMID: 38849352 PMCID: PMC11161590 DOI: 10.1038/s41467-024-49263-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 05/29/2024] [Indexed: 06/09/2024] Open
Abstract
The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.
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Affiliation(s)
- Ruo-Han Hao
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Tian-Pei Zhang
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Feng Jiang
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Jun-Hui Liu
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Shan-Shan Dong
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, P. R. China
| | - Yan Guo
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China.
| | - Tie-Lin Yang
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China.
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, P. R. China.
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9
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Patowary A, Zhang P, Jops C, Vuong CK, Ge X, Hou K, Kim M, Gong N, Margolis M, Vo D, Wang X, Liu C, Pasaniuc B, Li JJ, Gandal MJ, de la Torre-Ubieta L. Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms. Science 2024; 384:eadh7688. [PMID: 38781356 DOI: 10.1126/science.adh7688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 03/13/2024] [Indexed: 05/25/2024]
Abstract
RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders; yet, the role of cell type-specific splicing and transcript-isoform diversity during human brain development has not been systematically investigated. In this work, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone and cortical plate regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 distinct isoforms, of which 72.6% were novel (not previously annotated in Gencode version 33), and uncovered a substantial contribution of transcript-isoform diversity-regulated by RNA binding proteins-in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to reprioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.
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Affiliation(s)
- Ashok Patowary
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Intellectual and Developmental Disabilities Research Center, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Pan Zhang
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Intellectual and Developmental Disabilities Research Center, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Connor Jops
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute at Penn Med and the Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Celine K Vuong
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Intellectual and Developmental Disabilities Research Center, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Xinzhou Ge
- Department of Statistics, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Minsoo Kim
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Naihua Gong
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael Margolis
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Daniel Vo
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute at Penn Med and the Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Xusheng Wang
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38103, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
- Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Bogdan Pasaniuc
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jingyi Jessica Li
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Statistics, University of California Los Angeles, Los Angeles, CA 90095, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Biostatistics, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Michael J Gandal
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Intellectual and Developmental Disabilities Research Center, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute at Penn Med and the Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Luis de la Torre-Ubieta
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
- Intellectual and Developmental Disabilities Research Center, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
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10
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Islam M, Behura SK. Molecular Regulation of Fetal Brain Development in Inbred and Congenic Mouse Strains Differing in Longevity. Genes (Basel) 2024; 15:604. [PMID: 38790233 PMCID: PMC11121069 DOI: 10.3390/genes15050604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 05/04/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
The objective of this study was to investigate gene regulation of the developing fetal brain from congenic or inbred mice strains that differed in longevity. Gene expression and alternative splice variants were analyzed in a genome-wide manner in the fetal brain of C57BL/6J mice (long-lived) in comparison to B6.Cg-Cav1tm1Mls/J (congenic, short-lived) and AKR/J (inbred, short-lived) mice on day(d) 12, 15, and 17 of gestation. The analysis showed a contrasting gene expression pattern during fetal brain development in these mice. Genes related to brain development, aging, and the regulation of alternative splicing were significantly differentially regulated in the fetal brain of the short-lived compared to long-lived mice during development from d15 and d17. A significantly reduced number of splice variants was observed on d15 compared to d12 or d17 in a strain-dependent manner. An epigenetic clock analysis of d15 fetal brain identified DNA methylations that were significantly associated with single-nucleotide polymorphic sites between AKR/J and C57BL/6J strains. These methylations were associated with genes that show epigenetic changes in an age-correlated manner in mice. Together, the finding of this study suggest that fetal brain development and longevity are epigenetically linked, supporting the emerging concept of the early-life origin of longevity.
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Affiliation(s)
- Maliha Islam
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Susanta K. Behura
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Interdisciplinary Reproduction and Health Group, University of Missouri, Columbia, MO 65211, USA
- Interdisciplinary Neuroscience Program, University of Missouri, Columbia, MO 65211, USA
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11
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Yang L, Yin H, Bai L, Yao W, Tao T, Zhao Q, Gao Y, Teng J, Xu Z, Lin Q, Diao S, Pan Z, Guan D, Li B, Zhou H, Zhou Z, Zhao F, Wang Q, Pan Y, Zhang Z, Li K, Fang L, Liu GE. Mapping and functional characterization of structural variation in 1060 pig genomes. Genome Biol 2024; 25:116. [PMID: 38715020 PMCID: PMC11075355 DOI: 10.1186/s13059-024-03253-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. RESULTS We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies. CONCLUSIONS This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.
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Affiliation(s)
- Liu Yang
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Hongwei Yin
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lijing Bai
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Wenye Yao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Tan Tao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Qianyi Zhao
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Jinyan Teng
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhiting Xu
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Qing Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Shuqi Diao
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhangyuan Pan
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Dailu Guan
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Bingjie Li
- Animal and Veterinary Sciences, Scotland's Rural College (SRUC), Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, United Kingdom
| | - Huaijun Zhou
- Department of Animal Science, University of California-Davis, Davis, CA, USA
| | - Zhongyin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Fuping Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qishan Wang
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yuchun Pan
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zhe Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Kui Li
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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12
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Speakman E, Gunaratne GH. On a kneading theory for gene-splicing. CHAOS (WOODBURY, N.Y.) 2024; 34:043125. [PMID: 38579148 DOI: 10.1063/5.0199364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/05/2024] [Indexed: 04/07/2024]
Abstract
Two well-known facets in protein synthesis in eukaryotic cells are transcription of DNA to pre-RNA in the nucleus and the translation of messenger-RNA (mRNA) to proteins in the cytoplasm. A critical intermediate step is the removal of segments (introns) containing ∼97% of the nucleic-acid sites in pre-RNA and sequential alignment of the retained segments (exons) to form mRNA through a process referred to as splicing. Alternative forms of splicing enrich the proteome while abnormal splicing can enhance the likelihood of a cell developing cancer or other diseases. Mechanisms for splicing and origins of splicing errors are only partially deciphered. Our goal is to determine if rules on splicing can be inferred from data analytics on nucleic-acid sequences. Toward that end, we represent a nucleic-acid site as a point in a plane defined in terms of the anterior and posterior sub-sequences of the site. The "point-set" representation expands analytical approaches, including the use of statistical tools, to characterize genome sequences. It is found that point-sets for exons and introns are visually different, and that the differences can be quantified using a family of generalized moments. We design a machine-learning algorithm that can recognize individual exons or introns with 91% accuracy. Point-set distributions and generalized moments are found to differ between organisms.
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Affiliation(s)
- Ethan Speakman
- Department of Physics, University of Houston, Houston, Texas 77204, USA
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13
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Einson J, Minaeva M, Rafi F, Lappalainen T. The impact of genetically controlled splicing on exon inclusion and protein structure. PLoS One 2024; 19:e0291960. [PMID: 38478511 PMCID: PMC10936842 DOI: 10.1371/journal.pone.0291960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 09/08/2023] [Indexed: 03/17/2024] Open
Abstract
Common variants affecting mRNA splicing are typically identified though splicing quantitative trait locus (sQTL) mapping and have been shown to be enriched for GWAS signals by a similar degree to eQTLs. However, the specific splicing changes induced by these variants have been difficult to characterize, making it more complicated to analyze the effect size and direction of sQTLs, and to determine downstream splicing effects on protein structure. In this study, we catalogue sQTLs using exon percent spliced in (PSI) scores as a quantitative phenotype. PSI is an interpretable metric for identifying exon skipping events and has some advantages over other methods for quantifying splicing from short read RNA sequencing. In our set of sQTL variants, we find evidence of selective effects based on splicing effect size and effect direction, as well as exon symmetry. Additionally, we utilize AlphaFold2 to predict changes in protein structure associated with sQTLs overlapping GWAS traits, highlighting a potential new use-case for this technology for interpreting genetic effects on traits and disorders.
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Affiliation(s)
- Jonah Einson
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States of America
- New York Genome Center, New York, NY, United States of America
| | - Mariia Minaeva
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Faiza Rafi
- New York Genome Center, New York, NY, United States of America
- Department of Biotechnology, The City College of New York, New York, NY, United States of America
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, United States of America
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, United States of America
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14
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Hu W, Foord C, Hsu J, Fan L, Corley MJ, Bhatia TN, Xu S, Belchikov N, He Y, Pang AP, Lanjewar SN, Jarroux J, Joglekar A, Milner TA, Ndhlovu LC, Zhang J, Butelman E, Sloan SA, Lee VM, Gan L, Tilgner HU. ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.24.581897. [PMID: 38464236 PMCID: PMC10925193 DOI: 10.1101/2024.02.24.581897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.
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Affiliation(s)
- Wen Hu
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Careen Foord
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Justine Hsu
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Li Fan
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Helen and Robert Appel Alzheimer's Disease Research Institute
| | - Michael J Corley
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY, USA
| | - Tarun N Bhatia
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Natan Belchikov
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics & Systems Biology Program, Weill Cornell Medicine, New York, NY, USA
| | - Yi He
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Alina Ps Pang
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY, USA
| | - Samantha N Lanjewar
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Julien Jarroux
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Anoushka Joglekar
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Teresa A Milner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Lishomwa C Ndhlovu
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Eduardo Butelman
- Neuropsychoimaging of Addiction and Related Conditions Research Program, Dept. of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven A Sloan
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Virginia My Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Li Gan
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Helen and Robert Appel Alzheimer's Disease Research Institute
| | - Hagen U Tilgner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
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15
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Venkatasubramanian M, Schwartz L, Ramachandra N, Bennett J, Subramanian KR, Chen X, Gordon-Mitchell S, Fromowitz A, Pradhan K, Shechter D, Sahu S, Heiser D, Scherle P, Chetal K, Kulkarni A, Myers KC, Weirauch MT, Grimes HL, Starczynowski DT, Verma A, Salomonis N. Broad de-regulated U2AF1 splicing is prognostic and augments leukemic transformation via protein arginine methyltransferase activation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.04.578798. [PMID: 38370617 PMCID: PMC10871255 DOI: 10.1101/2024.02.04.578798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The role of splicing dysregulation in cancer is underscored by splicing factor mutations; however, its impact in the absence of such rare mutations is poorly understood. To reveal complex patient subtypes and putative regulators of pathogenic splicing in Acute Myeloid Leukemia (AML), we developed a new approach called OncoSplice. Among diverse new subtypes, OncoSplice identified a biphasic poor prognosis signature that partially phenocopies U2AF1-mutant splicing, impacting thousands of genes in over 40% of adult and pediatric AML cases. U2AF1-like splicing co-opted a healthy circadian splicing program, was stable over time and induced a leukemia stem cell (LSC) program. Pharmacological inhibition of the implicated U2AF1-like splicing regulator, PRMT5, rescued leukemia mis-splicing and inhibited leukemic cell growth. Genetic deletion of IRAK4, a common target of U2AF1-like and PRMT5 treated cells, blocked leukemia development in xenograft models and induced differentiation. These analyses reveal a new prognostic alternative-splicing mechanism in malignancy, independent of splicing-factor mutations.
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Affiliation(s)
- Meenakshi Venkatasubramanian
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH
| | - Leya Schwartz
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Nandini Ramachandra
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Joshua Bennett
- Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Krithika R. Subramanian
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Xiaoting Chen
- Divisions of Human Genetics and Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Shanisha Gordon-Mitchell
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Ariel Fromowitz
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Kith Pradhan
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - David Shechter
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Srabani Sahu
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Diane Heiser
- Prelude Therapeutics Incorporated, Wilmington, DE
| | | | - Kashish Chetal
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Aishwarya Kulkarni
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH
| | - Kasiani C. Myers
- Division of Bone Marrow Transplantation and Immune Deficiency, Cancer and Blood Diseases Institute, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
| | - Matthew T. Weirauch
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Divisions of Human Genetics and Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
- Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - H. Leighton Grimes
- Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
- Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Division of Immunobiology and Center for Systems Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Daniel T. Starczynowski
- Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Division of Bone Marrow Transplantation and Immune Deficiency, Cancer and Blood Diseases Institute, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Amit Verma
- Blood Cancer Institute, Albert Einstein College of Medicine, Montefiore Medical Center, The Bronx, NY
| | - Nathan Salomonis
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
- Division of Immunobiology and Center for Systems Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
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16
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Yang Y, Yang R, Kang B, Qian S, He X, Zhang X. Single-cell long-read sequencing in human cerebral organoids uncovers cell-type-specific and autism-associated exons. Cell Rep 2023; 42:113335. [PMID: 37889749 PMCID: PMC10842930 DOI: 10.1016/j.celrep.2023.113335] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 09/12/2023] [Accepted: 10/09/2023] [Indexed: 10/29/2023] Open
Abstract
Dysregulation of alternative splicing has been repeatedly associated with neurodevelopmental disorders, but the extent of cell-type-specific splicing in human neural development remains largely uncharted. Here, single-cell long-read sequencing in induced pluripotent stem cell (iPSC)-derived cerebral organoids identifies over 31,000 uncatalogued isoforms and 4,531 cell-type-specific splicing events. Long reads uncover coordinated splicing and cell-type-specific intron retention events, which are challenging to study with short reads. Retained neuronal introns are enriched in RNA splicing regulators, showing shorter lengths, higher GC contents, and weaker 5' splice sites. We use this dataset to explore the biological processes underlying neurological disorders, focusing on autism. In comparison with prior transcriptomic data, we find that the splicing program in autistic brains is closer to the progenitor state than differentiated neurons. Furthermore, cell-type-specific exons harbor significantly more de novo mutations in autism probands than in siblings. Overall, these results highlight the importance of cell-type-specific splicing in autism and neuronal gene regulation.
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Affiliation(s)
- Yalan Yang
- Department of Human Genetics, Neuroscience Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Runwei Yang
- Department of Human Genetics, Neuroscience Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Bowei Kang
- Department of Human Genetics, Neuroscience Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Sheng Qian
- Department of Human Genetics, Neuroscience Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Xin He
- Department of Human Genetics, Neuroscience Institute, The University of Chicago, Chicago, IL 60637, USA.
| | - Xiaochang Zhang
- Department of Human Genetics, Neuroscience Institute, The University of Chicago, Chicago, IL 60637, USA.
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17
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Yuan M, Liu X, Wang M, Li Z, Li H, Leng L, Wang S. A Functional Variant Alters the Binding of Bone morphogenetic protein 2 to the Transcription Factor NF-κB to Regulate Bone morphogenetic protein 2 Gene Expression and Chicken Abdominal Fat Deposition. Animals (Basel) 2023; 13:3401. [PMID: 37958155 PMCID: PMC10650395 DOI: 10.3390/ani13213401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/27/2023] [Accepted: 10/31/2023] [Indexed: 11/15/2023] Open
Abstract
In this study, we employed a dual-luciferase reporter assay and electrophoretic mobility shift analysis (EMSA) in vitro to explore whether a 12-base pair (bp) insertion/deletion (InDel) variant (namely g.14798187_14798188insTCCCTGCCCCCT) within intron 2 of the chicken BMP2 gene, which was significantly associated with chicken abdominal fat weight and abdominal fat percentage, is a functional marker and its potential regulatory mechanism. The reporter analysis demonstrated that the luciferase activity of the deletion allele was extremely significantly higher than that of the insertion allele (p < 0.01). A bioinformatics analysis revealed that compared to the deletion allele, the insertion allele created a transcription factor binding site of nuclear factor-kappa B (NF-κB), which exhibited an inhibitory effect on fat deposition. A dual-luciferase reporter assay demonstrated that the inhibitory effect of NF-κB on the deletion allele was stronger than that on the insertion allele. EMSA indicated that the binding affinity of NF-κB for the insertion allele was stronger than that for the deletion allele. In conclusion, the 12-bp InDel chicken BMP2 gene variant is a functional variant affecting fat deposition in chickens, which may partially regulate BMP2 gene expression by affecting the binding of transcription factor NF-κB to the BMP2 gene.
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Affiliation(s)
- Meng Yuan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
| | - Xin Liu
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
| | - Mengdie Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
| | - Ziwei Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
| | - Li Leng
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
| | - Shouzhi Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin 150030, China; (M.Y.); (X.L.); (M.W.); (Z.L.); (H.L.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin 150030, China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
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18
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Li X, Zhao Y, Kong H, Song C, Liu J, Xia J. Identification of region-specific splicing QTLs in human hippocampal tissue and its distinctive role in brain disorders. iScience 2023; 26:107958. [PMID: 37810239 PMCID: PMC10558811 DOI: 10.1016/j.isci.2023.107958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 06/28/2023] [Accepted: 09/14/2023] [Indexed: 10/10/2023] Open
Abstract
Alternative splicing (AS) regulation has an essential role in complex diseases. However, the AS profiles in the hippocampal (HIPPO) region of human brain are underexplored. Here, we investigated cis-acting sQTLs of HIPPO region in 264 samples and identified thousands of significant sQTLs. By enrichment analysis and functional characterization of these sQTLs, we found that the HIPPO sQTLs were enriched among histone-marked regions, transcription factors binding sites, RNA binding proteins sites, and brain disorders-associated loci. Comparative analyses with the dorsolateral prefrontal cortex revealed the importance of AS regulation in HIPPO (rg = 0.87). Furthermore, we performed a transcriptome-wide association study of Alzheimer's disease and identified 16 significant genes whose genetically regulated splicing levels may have a causal role in Alzheimer. Overall, our study improves our knowledge of the transcriptome gene regulation in the HIPPO region and provides novel insights into elucidating the pathogenesis of potential genes associated with brain disorders.
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Affiliation(s)
- Xiaoyan Li
- Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Yiran Zhao
- Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Hui Kong
- Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Chengcheng Song
- Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Jie Liu
- Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Junfeng Xia
- Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
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19
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Patowary A, Zhang P, Jops C, Vuong CK, Ge X, Hou K, Kim M, Gong N, Margolis M, Vo D, Wang X, Liu C, Pasaniuc B, Li JJ, Gandal MJ, de la Torre-Ubieta L. Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.25.534016. [PMID: 36993726 PMCID: PMC10055310 DOI: 10.1101/2023.03.25.534016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders, yet the role of cell-type-specific splicing or transcript-isoform diversity during human brain development has not been systematically investigated. Here, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 unique isoforms, of which 72.6% are novel (unannotated in Gencode-v33), and uncovered a substantial contribution of transcript-isoform diversity, regulated by RNA binding proteins, in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to re-prioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders. One-Sentence Summary A cell-specific atlas of gene isoform expression helps shape our understanding of brain development and disease. Structured Abstract INTRODUCTION: The development of the human brain is regulated by precise molecular and genetic mechanisms driving spatio-temporal and cell-type-specific transcript expression programs. Alternative splicing, a major mechanism increasing transcript diversity, is highly prevalent in the human brain, influences many aspects of brain development, and has strong links to neuropsychiatric disorders. Despite this, the cell-type-specific transcript-isoform diversity of the developing human brain has not been systematically investigated.RATIONALE: Understanding splicing patterns and isoform diversity across the developing neocortex has translational relevance and can elucidate genetic risk mechanisms in neurodevelopmental disorders. However, short-read sequencing, the prevalent technology for transcriptome profiling, is not well suited to capturing alternative splicing and isoform diversity. To address this, we employed third-generation long-read sequencing, which enables capture and sequencing of complete individual RNA molecules, to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution.RESULTS: We profiled microdissected GZ and CP regions of post-conception week (PCW) 15-17 human neocortex in bulk and at single-cell resolution across six subjects using high-fidelity long-read sequencing (PacBio IsoSeq). We identified 214,516 unique isoforms, of which 72.6% were novel (unannotated in Gencode), and >7,000 novel exons, expanding the proteome by 92,422 putative proteoforms. We uncovered thousands of isoform switches during cortical neurogenesis predicted to impact RNA regulatory domains or protein structure and implicating previously uncharacterized RNA-binding proteins in cellular identity and neuropsychiatric disease. At the single-cell level, early-stage excitatory neurons exhibited the greatest isoform diversity, and isoform-centric single-cell clustering led to the identification of previously uncharacterized cell states. We systematically assessed the contribution of transcriptomic features, and localized cell and spatio-temporal transcript expression signatures across neuropsychiatric disorders, revealing predominant enrichments in dynamic isoform expression and utilization patterns and that the number and complexity of isoforms per gene is strongly predictive of disease. Leveraging this resource, we re-prioritized thousands of rare de novo risk variants associated with autism spectrum disorders (ASD), intellectual disability (ID), and neurodevelopmental disorders (NDDs), more broadly, to potentially more severe consequences and revealed a larger proportion of cryptic splice variants with the expanded transcriptome annotation provided in this study.CONCLUSION: Our study offers a comprehensive landscape of isoform diversity in the human neocortex during development. This extensive cataloging of novel isoforms and splicing events sheds light on the underlying mechanisms of neurodevelopmental disorders and presents an opportunity to explore rare genetic variants linked to these conditions. The implications of our findings extend beyond fundamental neuroscience, as they provide crucial insights into the molecular basis of developmental brain disorders and pave the way for targeted therapeutic interventions. To facilitate exploration of this dataset we developed an online portal ( https://sciso.gandallab.org/ ).
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20
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D'Sa K, Guelfi S, Vandrovcova J, Reynolds RH, Zhang D, Hardy J, Botía JA, Weale ME, Taliun SAG, Small KS, Ryten M. Analysis of subcellular RNA fractions demonstrates significant genetic regulation of gene expression in human brain post-transcriptionally. Sci Rep 2023; 13:13874. [PMID: 37620324 PMCID: PMC10449874 DOI: 10.1038/s41598-023-40324-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.
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Affiliation(s)
- Karishma D'Sa
- Department of Neurodegenerative Disease, University College London, London, WC1N 3BG, UK
- Department of Medical & Molecular Genetics, School of Medical Sciences, King's College London, Guy's Hospital, London, SE1 1UL, UK
- Department of Clinical and Movement Neurosciences, University College London, London, WC1N 3BG, UK
| | - Sebastian Guelfi
- Department of Neurodegenerative Disease, University College London, London, WC1N 3BG, UK
- Verge Genomics, Tower Pl, South San Francisco, CA, 94080, USA
| | - Jana Vandrovcova
- Dept of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Regina H Reynolds
- Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, WC1N 1EH, UK
| | - David Zhang
- Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, WC1N 1EH, UK
| | - John Hardy
- Department of Neurodegenerative Disease, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute at University College London, London, WC1N 3BG, UK
| | - Juan A Botía
- Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, WC1N 1EH, UK
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, 30100, Murcia, Spain
| | - Michael E Weale
- Department of Medical & Molecular Genetics, School of Medical Sciences, King's College London, Guy's Hospital, London, SE1 1UL, UK
- Genomics Plc, Oxford, OX1 1JD, UK
| | - Sarah A Gagliano Taliun
- Department of Medicine, Université de Montréal, Montréal, QC, H3T 1J4, Canada
- Montréal Heart Institute, Montréal, QC, H1T 1C8, Canada
- Department of Neurosciences, Université de Montréal, Montréal, QC, H3T 1J4, Canada
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Mina Ryten
- Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, WC1N 1EH, UK.
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, WC1N 3JH, UK.
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21
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Pan L, Zheng C, Yang Z, Pawitan Y, Vu TN, Shen X. Hidden Genetic Regulation of Human Complex Traits via Brain Isoforms. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:217-227. [PMID: 37325708 PMCID: PMC10260721 DOI: 10.1007/s43657-023-00100-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 06/17/2023]
Abstract
Alternative splicing exists in most multi-exonic genes, and exploring these complex alternative splicing events and their resultant isoform expressions is essential. However, it has become conventional that RNA sequencing results have often been summarized into gene-level expression counts mainly due to the multiple ambiguous mapping of reads at highly similar regions. Transcript-level quantification and interpretation are often overlooked, and biological interpretations are often deduced based on combined transcript information at the gene level. Here, for the most variable tissue of alternative splicing, the brain, we estimate isoform expressions in 1,191 samples collected by the Genotype-Tissue Expression (GTEx) Consortium using a powerful method that we previously developed. We perform genome-wide association scans on the isoform ratios per gene and identify isoform-ratio quantitative trait loci (irQTL), which could not be detected by studying gene-level expressions alone. By analyzing the genetic architecture of the irQTL, we show that isoform ratios regulate educational attainment via multiple tissues including the frontal cortex (BA9), cortex, cervical spinal cord, and hippocampus. These tissues are also associated with different neuro-related traits, including Alzheimer's or dementia, mood swings, sleep duration, alcohol intake, intelligence, anxiety or depression, etc. Mendelian randomization (MR) analysis revealed 1,139 pairs of isoforms and neuro-related traits with plausible causal relationships, showing much stronger causal effects than on general diseases measured in the UK Biobank (UKB). Our results highlight essential transcript-level biomarkers in the human brain for neuro-related complex traits and diseases, which could be missed by merely investigating overall gene expressions. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-023-00100-6.
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Affiliation(s)
- Lu Pan
- Biostatistics Group, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006 China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 Sweden
| | - Chenqing Zheng
- Biostatistics Group, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006 China
| | - Zhijian Yang
- Biostatistics Group, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006 China
| | - Yudi Pawitan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 Sweden
| | - Trung Nghia Vu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 Sweden
| | - Xia Shen
- Biostatistics Group, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006 China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 Sweden
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200433 China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458 China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG UK
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22
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Fabo T, Khavari P. Functional characterization of human genomic variation linked to polygenic diseases. Trends Genet 2023; 39:462-490. [PMID: 36997428 PMCID: PMC11025698 DOI: 10.1016/j.tig.2023.02.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 03/30/2023]
Abstract
The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.
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Affiliation(s)
- Tania Fabo
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Graduate Program in Genetics, Stanford University, Stanford, CA, USA; Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Paul Khavari
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Graduate Program in Genetics, Stanford University, Stanford, CA, USA; Stanford University School of Medicine, Stanford University, Stanford, CA, USA; Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA.
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23
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Dominguez-Alonso S, Carracedo A, Rodriguez-Fontenla C. The non-coding genome in Autism Spectrum Disorders. Eur J Med Genet 2023; 66:104752. [PMID: 37023975 DOI: 10.1016/j.ejmg.2023.104752] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 03/10/2023] [Accepted: 03/19/2023] [Indexed: 04/08/2023]
Abstract
Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. While ASD have been proven to have a strong genetic component, current research largely focuses on coding regions of the genome. However, non-coding DNA, which makes up for ∼99% of the human genome, has recently been recognized as an important contributor to the high heritability of ASD, and novel sequencing technologies have been a milestone in opening up new directions for the study of the gene regulatory networks embedded within the non-coding regions. Here, we summarize current progress on the contribution of non-coding alterations to the pathogenesis of ASD and provide an overview of existing methods allowing for the study of their functional relevance, discussing potential ways of unraveling ASD's "missing heritability".
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Affiliation(s)
- S Dominguez-Alonso
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - A Carracedo
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - C Rodriguez-Fontenla
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain.
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24
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Abood A, Mesner LD, Jeffery ED, Murali M, Lehe M, Saquing J, Farber CR, Sheynkman GM. Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.531557. [PMID: 36993769 PMCID: PMC10055087 DOI: 10.1101/2023.03.17.531557] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
A major fraction of loci identified by genome-wide association studies (GWASs) lead to alterations in alternative splicing, but interpretation of how such alterations impact proteins is hindered by the technical limitations of short-read RNA-seq, which cannot directly link splicing events to full-length transcript or protein isoforms. Long-read RNA-seq represents a powerful tool to define and quantify transcript isoforms, and recently, infer protein isoform existence. Here we present a novel approach that integrates information from GWAS, splicing QTL (sQTL), and PacBio long-read RNA-seq in a disease-relevant model to infer the effects of sQTLs on the ultimate protein isoform products they encode. We demonstrate the utility of our approach using bone mineral density (BMD) GWAS data. We identified 1,863 sQTLs from the Genotype-Tissue Expression (GTEx) project in 732 protein-coding genes which colocalized with BMD associations (H 4 PP ≥ 0.75). We generated deep coverage PacBio long-read RNA-seq data (N=∼22 million full-length reads) on human osteoblasts, identifying 68,326 protein-coding isoforms, of which 17,375 (25%) were novel. By casting the colocalized sQTLs directly onto protein isoforms, we connected 809 sQTLs to 2,029 protein isoforms from 441 genes expressed in osteoblasts. Using these data, we created one of the first proteome-scale resources defining full-length isoforms impacted by colocalized sQTLs. Overall, we found that 74 sQTLs influenced isoforms likely impacted by nonsense mediated decay (NMD) and 190 that potentially resulted in the expression of new protein isoforms. Finally, we identified colocalizing sQTLs in TPM2 for splice junctions between two mutually exclusive exons, and two different transcript termination sites, making it impossible to interpret without long-read RNA-seq data. siRNA mediated knockdown in osteoblasts showed two TPM2 isoforms with opposing effects on mineralization. We expect our approach to be widely generalizable across diverse clinical traits and accelerate system-scale analyses of protein isoform activities modulated by GWAS loci.
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25
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Huggett SB, Ikeda AS, Yuan Q, Benca-Bachman CE, Palmer RHC. Genome- and transcriptome-wide splicing associations with alcohol use disorder. Sci Rep 2023; 13:3950. [PMID: 36894673 PMCID: PMC9998611 DOI: 10.1038/s41598-023-30926-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 03/03/2023] [Indexed: 03/11/2023] Open
Abstract
Genetic mechanisms of alternative mRNA splicing have been shown in the brain for a variety of neuropsychiatric traits, but not substance use disorders. Our study utilized RNA-sequencing data on alcohol use disorder (AUD) in four brain regions (n = 56; ages 40-73; 100% 'Caucasian'; PFC, NAc, BLA and CEA) and genome-wide association data on AUD (n = 435,563, ages 22-90; 100% European-American). Polygenic scores of AUD were associated with AUD-related alternative mRNA splicing in the brain. We identified 714 differentially spliced genes between AUD vs controls, which included both putative addiction genes and novel gene targets. We found 6463 splicing quantitative trait loci (sQTLs) that linked to the AUD differentially spliced genes. sQTLs were enriched in loose chromatin genomic regions and downstream gene targets. Additionally, the heritability of AUD was enriched for DNA variants in and around differentially spliced genes associated with AUD. Our study also performed splicing transcriptome-wide association studies (TWASs) of AUD and other drug use traits that unveiled specific genes for follow-up and splicing correlations across SUDs. Finally, we showed that differentially spliced genes between AUD vs control were also associated with primate models of chronic alcohol consumption in similar brain regions. Our study found substantial genetic contributions of alternative mRNA splicing in AUD.
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Affiliation(s)
- Spencer B Huggett
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Ami S Ikeda
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Qingyue Yuan
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Chelsie E Benca-Bachman
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA.
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26
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Hamanaka K, Yamauchi D, Koshimizu E, Watase K, Mogushi K, Ishikawa K, Mizusawa H, Tsuchida N, Uchiyama Y, Fujita A, Misawa K, Mizuguchi T, Miyatake S, Matsumoto N. Genome-wide identification of tandem repeats associated with splicing variation across 49 tissues in humans. Genome Res 2023; 33:435-447. [PMID: 37307504 PMCID: PMC10078293 DOI: 10.1101/gr.277335.122] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 02/22/2023] [Indexed: 03/29/2023]
Abstract
Tandem repeats (TRs) are one of the largest sources of polymorphism, and their length is associated with gene regulation. Although previous studies reported several tandem repeats regulating gene splicing in cis (spl-TRs), no large-scale study has been conducted. In this study, we established a genome-wide catalog of 9537 spl-TRs with a total of 58,290 significant TR-splicing associations across 49 tissues (false discovery rate 5%) by using Genotype-Tissue expression (GTex) Project data. Regression models explaining splicing variation by using spl-TRs and other flanking variants suggest that at least some of the spl-TRs directly modulate splicing. In our catalog, two spl-TRs are known loci for repeat expansion diseases, spinocerebellar ataxia 6 (SCA6) and 12 (SCA12). Splicing alterations by these spl-TRs were compatible with those observed in SCA6 and SCA12. Thus, our comprehensive spl-TR catalog may help elucidate the pathomechanism of genetic diseases.
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Affiliation(s)
- Kohei Hamanaka
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
| | | | - Eriko Koshimizu
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
| | - Kei Watase
- Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Kaoru Mogushi
- Intractable Disease Research Center, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
| | - Kinya Ishikawa
- The Center for Personalized Medicine for Healthy Aging, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo 113-8510, Japan
| | - Hidehiro Mizusawa
- Department of Neurology, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8551, Japan
| | - Naomi Tsuchida
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
- Department of Rare Disease Genomics, Yokohama City University Hospital, Yokohama, Kanagawa 236-0004, Japan
| | - Yuri Uchiyama
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
- Department of Rare Disease Genomics, Yokohama City University Hospital, Yokohama, Kanagawa 236-0004, Japan
| | - Atsushi Fujita
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
| | - Kazuharu Misawa
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
| | - Takeshi Mizuguchi
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
| | - Satoko Miyatake
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan
- Clinical Genetics Department, Yokohama City University Hospital, Yokohama, Kanagawa 236-0004, Japan
| | - Naomichi Matsumoto
- Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama, Kanagawa 236-0004, Japan;
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27
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Chatterjee D, Beaulieu JM. Inhibition of glycogen synthase kinase 3 by lithium, a mechanism in search of specificity. Front Mol Neurosci 2022; 15:1028963. [PMID: 36504683 PMCID: PMC9731798 DOI: 10.3389/fnmol.2022.1028963] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 10/24/2022] [Indexed: 11/25/2022] Open
Abstract
Inhibition of Glycogen synthase kinase 3 (GSK3) is a popular explanation for the effects of lithium ions on mood regulation in bipolar disorder and other mental illnesses, including major depression, cyclothymia, and schizophrenia. Contribution of GSK3 is supported by evidence obtained from animal and patient derived model systems. However, the two GSK3 enzymes, GSK3α and GSK3β, have more than 100 validated substrates. They are thus central hubs for major biological functions, such as dopamine-glutamate neurotransmission, synaptic plasticity (Hebbian and homeostatic), inflammation, circadian regulation, protein synthesis, metabolism, inflammation, and mitochondrial functions. The intricate contributions of GSK3 to several biological processes make it difficult to identify specific mechanisms of mood stabilization for therapeutic development. Identification of GSK3 substrates involved in lithium therapeutic action is thus critical. We provide an overview of GSK3 biological functions and substrates for which there is evidence for a contribution to lithium effects. A particular focus is given to four of these: the transcription factor cAMP response element-binding protein (CREB), the RNA-binding protein FXR1, kinesin subunits, and the cytoskeletal regulator CRMP2. An overview of how co-regulation of these substrates may result in shared outcomes is also presented. Better understanding of how inhibition of GSK3 contributes to the therapeutic effects of lithium should allow for identification of more specific targets for future drug development. It may also provide a framework for the understanding of how lithium effects overlap with those of other drugs such as ketamine and antipsychotics, which also inhibit brain GSK3.
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Affiliation(s)
| | - Jean Martin Beaulieu
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
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28
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Trifonova EA, Gavrilenko MM, Babovskaya AA, Zarubin AA, Svarovskaya MG, Izhoykina EV, Stepanov IA, Serebrova VN, Kutsenko IG, Stepanov VA. Alternative Splicing Landscape of Placental Decidual Cells during Physiological Pregnancy. RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422100106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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29
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Li Z, Li D, He Y, Wang K, Ma X, Chen X. Cross-Disorder Analysis of Shared Genetic Components Between Cortical Structures and Major Psychiatric Disorders. Schizophr Bull 2022; 48:1145-1154. [PMID: 35265999 PMCID: PMC9434450 DOI: 10.1093/schbul/sbac019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Although large-scale neuroimaging studies have demonstrated similar patterns of structural brain abnormalities across major psychiatric disorders, the underlying genetic etiology behind these similar cross-disorder patterns is not well understood. STUDY DESIGN We quantified the extent of shared genetic components between cortical structures and major psychiatric disorders (CS-MPD) by using genome-wide association study (GWAS) summary statistics of 70 cortical structures (surface area and thickness of the whole cortex and 34 cortical regions) and five major psychiatric disorders, consisting of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). Cross-disorder analyses were then conducted to estimate the degree of similarity in CS-MPD shared genetic components among these disorders. STUDY RESULTS The CS-MPD shared genetic components have medium-to-strong positive correlations in ADHD, BD, MDD, and SCZ (r = 0.415 to r = 0.806) while ASD was significantly correlated with ADHD, BD, and SCZ (r = 0.388 to r = 0.403). These pairwise correlations of CS-MPD shared genetic components among disorders were significantly associated with corresponding cross-disorder similarities in cortical structural abnormalities (r = 0.668), accounting for 44% variance. In addition, one latent shared factor consisted primarily of BD, MDD, and SCZ, explaining 62.47% of the total variance in CS-MPD shared genetic components of all disorders. CONCLUSIONS The current results bridge the gap between shared cross-disorder heritability and shared structural brain abnormalities in major psychiatric disorders, providing important implications for a shared genetic basis of cortical structures in these disorders.
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Affiliation(s)
- Zongchang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - David Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Ying He
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Kangli Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, PR China
| | - Xiaoqian Ma
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiaogang Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
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30
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Raskó T, Pande A, Radscheit K, Zink A, Singh M, Sommer C, Wachtl G, Kolacsek O, Inak G, Szvetnik A, Petrakis S, Bunse M, Bansal V, Selbach M, Orbán TI, Prigione A, Hurst LD, Izsvák Z. A Novel Gene Controls a New Structure: PiggyBac Transposable Element-Derived 1, Unique to Mammals, Controls Mammal-Specific Neuronal Paraspeckles. Mol Biol Evol 2022; 39:6661922. [PMID: 36205081 PMCID: PMC9538788 DOI: 10.1093/molbev/msac175] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Although new genes can arrive from modes other than duplication, few examples are well characterized. Given high expression in some human brain subregions and a putative link to psychological disorders [e.g., schizophrenia (SCZ)], suggestive of brain functionality, here we characterize piggyBac transposable element-derived 1 (PGBD1). PGBD1 is nonmonotreme mammal-specific and under purifying selection, consistent with functionality. The gene body of human PGBD1 retains much of the original DNA transposon but has additionally captured SCAN and KRAB domains. Despite gene body retention, PGBD1 has lost transposition abilities, thus transposase functionality is absent. PGBD1 no longer recognizes piggyBac transposon-like inverted repeats, nonetheless PGBD1 has DNA binding activity. Genome scale analysis identifies enrichment of binding sites in and around genes involved in neuronal development, with association with both histone activating and repressing marks. We focus on one of the repressed genes, the long noncoding RNA NEAT1, also dysregulated in SCZ, the core structural RNA of paraspeckles. DNA binding assays confirm specific binding of PGBD1 both in the NEAT1 promoter and in the gene body. Depletion of PGBD1 in neuronal progenitor cells (NPCs) results in increased NEAT1/paraspeckles and differentiation. We conclude that PGBD1 has evolved core regulatory functionality for the maintenance of NPCs. As paraspeckles are a mammal-specific structure, the results presented here show a rare example of the evolution of a novel gene coupled to the evolution of a contemporaneous new structure.
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Affiliation(s)
- Tamás Raskó
- Max Delbrück Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | | | | | - Annika Zink
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany
| | - Manvendra Singh
- Max Delbrück Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | - Christian Sommer
- Max Delbrück Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | - Gerda Wachtl
- Institute of Enzymology, Research Centre for Natural Sciences, ELKH, Budapest, Hungary,Doctoral School of Biology, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Orsolya Kolacsek
- Institute of Enzymology, Research Centre for Natural Sciences, ELKH, Budapest, Hungary
| | - Gizem Inak
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany
| | - Attila Szvetnik
- Max Delbrück Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | - Spyros Petrakis
- Institute of Applied Biosciences/Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
| | - Mario Bunse
- Max Delbrück Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | - Vikas Bansal
- Biomedical Data Science and Machine Learning Group, German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
| | - Matthias Selbach
- Max Delbrück Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | - Tamás I Orbán
- Institute of Enzymology, Research Centre for Natural Sciences, ELKH, Budapest, Hungary
| | - Alessandro Prigione
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany
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31
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Multi-omics analysis reveals RNA splicing alterations and their biological and clinical implications in lung adenocarcinoma. Signal Transduct Target Ther 2022; 7:270. [PMID: 35989380 PMCID: PMC9393167 DOI: 10.1038/s41392-022-01098-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/18/2022] [Accepted: 06/29/2022] [Indexed: 11/18/2022] Open
Abstract
Alternative RNA splicing is one of the most important mechanisms of posttranscriptional gene regulation, which contributes to protein diversity in eukaryotes. It is well known that RNA splicing dysregulation is a critical mechanism in tumor pathogenesis and the rationale for the promising splice-switching therapeutics for cancer treatment. Although we have a comprehensive understanding of DNA mutations, abnormal gene expression profiles, epigenomics, and proteomics in lung adenocarcinoma (LUAD), little is known about its aberrant alternative splicing profiles. Here, based on the multi-omics data generated from over 1000 samples, we systematically studied the RNA splicing alterations in LUAD and revealed their biological and clinical implications. We identified 3688 aberrant alternative splicing events (AASEs) in LUAD, most of which were alternative promoter and exon skip. The specific regulatory roles of RNA binding proteins, somatic mutations, and DNA methylations on AASEs were comprehensively interrogated. We dissected the functional implications of AASEs and concluded that AASEs mainly affected biological processes related to tumor proliferation and metastasis. We also found that one subtype of LUAD with a particular AASEs pattern was immunogenic and had a better prognosis and response rate to immunotherapy. These findings revealed novel events related to tumorigenesis and tumor immune microenvironment and laid the foundation for the development of splice-switching therapies for LUAD.
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32
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Genetic control of RNA splicing and its distinct role in complex trait variation. Nat Genet 2022; 54:1355-1363. [PMID: 35982161 PMCID: PMC9470536 DOI: 10.1038/s41588-022-01154-4] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 07/08/2022] [Indexed: 12/11/2022]
Abstract
Most genetic variants identified from genome-wide association studies (GWAS) in humans are noncoding, indicating their role in gene regulation. Previous studies have shown considerable links of GWAS signals to expression quantitative trait loci (eQTLs) but the links to other genetic regulatory mechanisms, such as splicing QTLs (sQTLs), are underexplored. Here, we introduce an sQTL mapping method, testing for heterogeneity between isoform-eQTLeffects (THISTLE), with improved power over competing methods. Applying THISTLE together with a complementary sQTL mapping strategy to brain transcriptomic (n = 2,865) and genotype data, we identified 12,794 genes with cis-sQTLs at P < 5 × 10−8, approximately 61% of which were distinct from eQTLs. Integrating the sQTL data into GWAS for 12 brain-related complex traits (including diseases), we identified 244 genes associated with the traits through cis-sQTLs, approximately 61% of which could not be discovered using the corresponding eQTL data. Our study demonstrates the distinct role of most sQTLs in the genetic regulation of transcription and complex trait variation. A powerful method for splicing quantitative trait loci (sQTL) mapping, THISTLE, is presented and applied to a collection of 2,865 brain samples. Integration with GWAS identifies 244 genes associated via cis-sQTLs, of which 61% were not identified using expression QTLs.
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33
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Hardwick SA, Hu W, Joglekar A, Fan L, Collier PG, Foord C, Balacco J, Lanjewar S, Sampson MM, Koopmans F, Prjibelski AD, Mikheenko A, Belchikov N, Jarroux J, Lucas AB, Palkovits M, Luo W, Milner TA, Ndhlovu LC, Smit AB, Trojanowski JQ, Lee VMY, Fedrigo O, Sloan SA, Tombácz D, Ross ME, Jarvis E, Boldogkői Z, Gan L, Tilgner HU. Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue. Nat Biotechnol 2022; 40:1082-1092. [PMID: 35256815 PMCID: PMC9287170 DOI: 10.1038/s41587-022-01231-3] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 01/20/2022] [Indexed: 12/11/2022]
Abstract
Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms. Here we present single-nuclei isoform RNA sequencing (SnISOr-Seq). Using microfluidics, PCR-based artifact removal, target enrichment and long-read sequencing, SnISOr-Seq increased barcoded, exon-spanning long reads 7.5-fold compared to naive long-read single-nuclei sequencing. We applied SnISOr-Seq to adult human frontal cortex and found that exons associated with autism exhibit coordinated and highly cell-type-specific inclusion. We found two distinct combination patterns: those distinguishing neural cell types, enriched in TSS-exon, exon-polyadenylation-site and non-adjacent exon pairs, and those with multiple configurations within one cell type, enriched in adjacent exon pairs. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons, implying that coordination can be rapidly established during evolution. SnISOr-Seq enables cell-type-specific long-read isoform analysis in human brain and in any frozen or hard-to-dissociate sample.
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Affiliation(s)
- Simon A Hardwick
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Wen Hu
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Anoushka Joglekar
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Li Fan
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Helen and Robert Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Paul G Collier
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Careen Foord
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | | | - Samantha Lanjewar
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | | | - Frank Koopmans
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Andrey D Prjibelski
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia
| | - Natan Belchikov
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics & Systems Biology Program, Weill Cornell Medicine, New York, NY, USA
| | - Julien Jarroux
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | | | - Miklós Palkovits
- Human Brain Tissue Bank, Semmelweis University, Budapest, Hungary
| | - Wenjie Luo
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Helen and Robert Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Teresa A Milner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Lishomwa C Ndhlovu
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY, USA
| | - August B Smit
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Virginia M Y Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | | | - Steven A Sloan
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Dóra Tombácz
- Department of Medical Biology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
| | - M Elizabeth Ross
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | | | - Zsolt Boldogkői
- Department of Medical Biology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
| | - Li Gan
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Helen and Robert Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Hagen U Tilgner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA.
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34
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Ji Y, Wei Q, Chen R, Wang Q, Tao R, Li B. Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery. PLoS Genet 2022; 18:e1009814. [PMID: 35771864 PMCID: PMC9278751 DOI: 10.1371/journal.pgen.1009814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 07/13/2022] [Accepted: 05/26/2022] [Indexed: 12/30/2022] Open
Abstract
A common strategy for the functional interpretation of genome-wide association study (GWAS) findings has been the integrative analysis of GWAS and expression data. Using this strategy, many association methods (e.g., PrediXcan and FUSION) have been successful in identifying trait-associated genes via mediating effects on RNA expression. However, these approaches often ignore the effects of splicing, which can carry as much disease risk as expression. Compared to expression data, one challenge to detect associations using splicing data is the large multiple testing burden due to multidimensional splicing events within genes. Here, we introduce a multidimensional splicing gene (MSG) approach, which consists of two stages: 1) we use sparse canonical correlation analysis (sCCA) to construct latent canonical vectors (CVs) by identifying sparse linear combinations of genetic variants and splicing events that are maximally correlated with each other; and 2) we test for the association between the genetically regulated splicing CVs and the trait of interest using GWAS summary statistics. Simulations show that MSG has proper type I error control and substantial power gains over existing multidimensional expression analysis methods (i.e., S-MultiXcan, UTMOST, and sCCA+ACAT) under diverse scenarios. When applied to the Genotype-Tissue Expression Project data and GWAS summary statistics of 14 complex human traits, MSG identified on average 83%, 115%, and 223% more significant genes than sCCA+ACAT, S-MultiXcan, and UTMOST, respectively. We highlight MSG's applications to Alzheimer's disease, low-density lipoprotein cholesterol, and schizophrenia, and found that the majority of MSG-identified genes would have been missed from expression-based analyses. Our results demonstrate that aggregating splicing data through MSG can improve power in identifying gene-trait associations and help better understand the genetic risk of complex traits.
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Affiliation(s)
- Ying Ji
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Qiang Wei
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Rui Chen
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Quan Wang
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
- * E-mail: (RT); (BL)
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
- * E-mail: (RT); (BL)
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35
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Olayinka OA, O'Neill NK, Farrer LA, Wang G, Zhang X. Molecular Quantitative Trait Locus Mapping in Human Complex Diseases. Curr Protoc 2022; 2:e426. [PMID: 35587224 PMCID: PMC9186089 DOI: 10.1002/cpz1.426] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non-coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome-wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP-FGC). The project's ultimate goal is a reference map of Alzheimer's-related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.
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Affiliation(s)
- Oluwatosin A Olayinka
- Bioinformatics Program, Boston University, Boston, Massachusetts
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
| | - Nicholas K O'Neill
- Bioinformatics Program, Boston University, Boston, Massachusetts
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
| | - Lindsay A Farrer
- Bioinformatics Program, Boston University, Boston, Massachusetts
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Gao Wang
- Department of Neurology, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
| | - Xiaoling Zhang
- Bioinformatics Program, Boston University, Boston, Massachusetts
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
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36
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Li YH, Yang YY, Wang ZG, Chen Z. Emerging Function of Ecotype-Specific Splicing in the Recruitment of Commensal Microbiome. Int J Mol Sci 2022; 23:4860. [PMID: 35563250 PMCID: PMC9100151 DOI: 10.3390/ijms23094860] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 04/15/2022] [Accepted: 04/25/2022] [Indexed: 12/20/2022] Open
Abstract
In recent years, host-microbiome interactions in both animals and plants has emerged as a novel research area for studying the relationship between host organisms and their commensal microbial communities. The fitness advantages of this mutualistic interaction can be found in both plant hosts and their associated microbiome, however, the driving forces mediating this beneficial interaction are poorly understood. Alternative splicing (AS), a pivotal post-transcriptional mechanism, has been demonstrated to play a crucial role in plant development and stress responses among diverse plant ecotypes. This natural variation of plants also has an impact on their commensal microbiome. In this article, we review the current progress of plant natural variation on their microbiome community, and discuss knowledge gaps between AS regulation of plants in response to their intimately related microbiota. Through the impact of this article, an avenue could be established to study the biological mechanism of naturally varied splicing isoforms on plant-associated microbiome assembly.
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Affiliation(s)
- Yue-Han Li
- State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Research and Development Center for Fine Chemicals, Guizhou University, Guiyang 550025, China; (Y.-H.L.); (Y.-Y.Y.)
- School of Life Science and Agriculture Forestry, Qiqihar University, Qiqihar 161006, China
- Heilongjiang Provincial Technology Innovation Center of Agromicrobial Preparation Industrialization, Qiqihar 161006, China
| | - Yuan-You Yang
- State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Research and Development Center for Fine Chemicals, Guizhou University, Guiyang 550025, China; (Y.-H.L.); (Y.-Y.Y.)
| | - Zhi-Gang Wang
- School of Life Science and Agriculture Forestry, Qiqihar University, Qiqihar 161006, China
- Heilongjiang Provincial Technology Innovation Center of Agromicrobial Preparation Industrialization, Qiqihar 161006, China
| | - Zhuo Chen
- State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Research and Development Center for Fine Chemicals, Guizhou University, Guiyang 550025, China; (Y.-H.L.); (Y.-Y.Y.)
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37
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Tian J, Chen C, Rao M, Zhang M, Lu Z, Cai Y, Ying P, Li B, Wang H, Wang L, Li Y, Huang J, Fan L, Cai X, Ning C, Li Y, Zhang F, Wang W, Jiang Y, Liu Y, Wang M, Li H, Huang C, Yang Z, Chang J, Zhu Y, Yang X, Miao X. Aberrant RNA splicing is a primary link between genetic variation and pancreatic cancer risk. Cancer Res 2022; 82:2084-2096. [PMID: 35363263 DOI: 10.1158/0008-5472.can-21-4367] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 02/15/2022] [Accepted: 03/30/2022] [Indexed: 11/16/2022]
Abstract
Understanding the genetic variation underlying transcript splicing is essential for fully dissecting the molecular mechanisms of common diseases. The available evidence from splicing quantitative trait locus (sQTL) studies using pancreatic ductal adenocarcinoma (PDAC) tissues have been limited to small sample sizes. Here we present a genome-wide sQTL analysis to identify single nucleotide polymorphisms (SNPs) that control mRNA splicing in 176 PDAC samples from TCGA. From this analysis, 16,175 sQTLs were found to be significantly enriched in RNA binding protein (RBP) binding sites and chromatin regulatory elements and overlapped with known loci from PDAC genome-wide association studies (GWAS). sQTLs and expression QTLs (eQTL) showed mostly non-overlapping patterns, suggesting sQTLs provide additional insights into the etiology of disease. Target genes affected by sQTLs were closely related to cancer signaling pathways, high mutational burden, immune infiltration, and pharmaceutical targets, which will be helpful for clinical applications. Integration of a large-scale population consisting of 2,782 PDAC patients and 7,983 healthy controls identified an sQTL variant rs1785932-T allele that promotes alternative splicing of ELP2 exon 6 and leads to a lower level of the ELP2 full-length isoform (ELP2_V1) and a higher level of a truncated ELP2 isoform (ELP2_V2), resulting in decreased risk of PDAC (OR=0.83, 95%CI=0.77-0.89, P=1.16×10-6). The ELP2_V2 isoform functioned as a potential tumor suppressor gene, inhibiting PDAC cell proliferation by exhibiting stronger binding affinity to JAK1/STAT3 than ELP2_V1 and subsequently blocking the pathological activation of the p-STAT3 pathway. Collectively, these findings provide an informative sQTL resource and insights into the regulatory mechanisms linking splicing variants to PDAC risk.
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Affiliation(s)
| | | | | | - Ming Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zequn Lu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yimin Cai
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Pingting Ying
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Li
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haoxue Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lu Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, Hubei, China
| | - Yao Li
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Sciences and Technology, China
| | - Jinyu Huang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Linyun Fan
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Cai
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Caibo Ning
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yanmin Li
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fuwei Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenzhuo Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | | | | | - Min Wang
- Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Heng Li
- Tongji Hospital, Wuhan, Hubei, China
| | | | | | - Jiang Chang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China
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38
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Rowlands CF, Taylor A, Rice G, Whiffin N, Hall HN, Newman WG, Black GCM, O'Keefe RT, Hubbard S, Douglas AGL, Baralle D, Briggs TA, Ellingford JM. MRSD: A quantitative approach for assessing suitability of RNA-seq in the investigation of mis-splicing in Mendelian disease. Am J Hum Genet 2022; 109:210-222. [PMID: 35065709 PMCID: PMC8874219 DOI: 10.1016/j.ajhg.2021.12.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 12/12/2021] [Indexed: 12/16/2022] Open
Abstract
Variable levels of gene expression between tissues complicates the use of RNA sequencing of patient biosamples to delineate the impact of genomic variants. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA sequencing. This overcomes limitations of using expression values alone as a metric to predict RNA-sequencing utility. We have derived a metric, minimum required sequencing depth (MRSD), that estimates the depth of sequencing required from RNA sequencing to achieve user-specified sequencing coverage of a gene, transcript, or group of genes. We applied MRSD across four human biosamples: whole blood, lymphoblastoid cell lines (LCLs), skeletal muscle, and cultured fibroblasts. MRSD has high precision (90.1%-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that fibroblasts, of these four biosamples, are the optimum source of RNA for 63.1% of gene panels. Using this approach, up to 67.8% of the variants of uncertain significance in ClinVar that are predicted to impact splicing could be assayed by RNA sequencing in at least one of the biosamples. We demonstrate the utility and benefits of MRSD as a metric to inform functional assessment of splicing aberrations, in particular in the context of Mendelian genetic disorders to improve diagnostic yield.
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Affiliation(s)
- Charlie F Rowlands
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Algy Taylor
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Gillian Rice
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Nicola Whiffin
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Hildegard Nikki Hall
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - William G Newman
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Graeme C M Black
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Raymond T O'Keefe
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Simon Hubbard
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Andrew G L Douglas
- Wessex Clinical Genetics Service, Princess Anne Hospital, University Hospital Southampton NHS Foundation Trust, Coxford Rd, Southampton SO16 5YA, UK; Faculty of Medicine, University of Southampton, Duthie Building, Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK
| | - Diana Baralle
- Wessex Clinical Genetics Service, Princess Anne Hospital, University Hospital Southampton NHS Foundation Trust, Coxford Rd, Southampton SO16 5YA, UK; Faculty of Medicine, University of Southampton, Duthie Building, Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK
| | - Tracy A Briggs
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Jamie M Ellingford
- Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK.
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39
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Brotman SM, Raulerson CK, Vadlamudi S, Currin KW, Shen Q, Parsons VA, Iyengar AK, Roman TS, Furey TS, Kuusisto J, Collins FS, Boehnke M, Laakso M, Pajukanta P, Mohlke KL. Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits. Am J Hum Genet 2022; 109:66-80. [PMID: 34995504 PMCID: PMC8764203 DOI: 10.1016/j.ajhg.2021.11.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/23/2021] [Indexed: 01/13/2023] Open
Abstract
Alternate splicing events can create isoforms that alter gene function, and genetic variants associated with alternate gene isoforms may reveal molecular mechanisms of disease. We used subcutaneous adipose tissue of 426 Finnish men from the METSIM study and identified splice junction quantitative trait loci (sQTLs) for 6,077 splice junctions (FDR < 1%). In the same individuals, we detected expression QTLs (eQTLs) for 59,443 exons and 15,397 genes (FDR < 1%). We identified 595 genes with an sQTL and exon eQTL but no gene eQTL, which could indicate potential isoform differences. Of the significant sQTL signals, 2,114 (39.8%) included at least one proxy variant (linkage disequilibrium r2 > 0.8) located within an intron spanned by the splice junction. We identified 203 sQTLs that colocalized with 141 genome-wide association study (GWAS) signals for cardiometabolic traits, including 25 signals for lipid traits, 24 signals for body mass index (BMI), and 12 signals for waist-hip ratio adjusted for BMI. Among all 141 GWAS signals colocalized with an sQTL, we detected 26 that also colocalized with an exon eQTL for an exon skipped by the sQTL splice junction. At a GWAS signal for high-density lipoprotein cholesterol colocalized with an NR1H3 sQTL splice junction, we show that the alternative splice product encodes an NR1H3 transcription factor that lacks a DNA binding domain and fails to activate transcription. Together, these results detect splicing events and candidate mechanisms that may contribute to gene function at GWAS loci.
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Affiliation(s)
- Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Chelsea K Raulerson
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Qiujin Shen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Victoria A Parsons
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Apoorva K Iyengar
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Tamara S Roman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Terrence S Furey
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio 70210, Finland
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio 70210, Finland
| | - Päivi Pajukanta
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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40
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Zhang CY, Xiao X, Zhang Z, Hu Z, Li M. An alternative splicing hypothesis for neuropathology of schizophrenia: evidence from studies on historical candidate genes and multi-omics data. Mol Psychiatry 2022; 27:95-112. [PMID: 33686213 DOI: 10.1038/s41380-021-01037-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 01/08/2021] [Accepted: 01/22/2021] [Indexed: 01/31/2023]
Abstract
Alternative splicing of schizophrenia risk genes, such as DRD2, GRM3, and DISC1, has been extensively described. Nevertheless, the alternative splicing characteristics of the growing number of schizophrenia risk genes identified through genetic analyses remain relatively opaque. Recently, transcriptomic analyses in human brains based on short-read RNA-sequencing have discovered many "local splicing" events (e.g., exon skipping junctions) associated with genetic risk of schizophrenia, and further molecular characterizations have identified novel spliced isoforms, such as AS3MTd2d3 and ZNF804AE3E4. In addition, long-read sequencing analyses of schizophrenia risk genes (e.g., CACNA1C and NRXN1) have revealed multiple previously unannotated brain-abundant isoforms with therapeutic potentials, and functional analyses of KCNH2-3.1 and Ube3a1 have provided examples for investigating such spliced isoforms in vitro and in vivo. These findings suggest that alternative splicing may be an essential molecular mechanism underlying genetic risk of schizophrenia, however, the incomplete annotations of human brain transcriptomes might have limited our understanding of schizophrenia pathogenesis, and further efforts to elucidate these transcriptional characteristics are urgently needed to gain insights into the illness-correlated brain physiology and pathology as well as to translate genetic discoveries into novel therapeutic targets.
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Affiliation(s)
- Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Zhuohua Zhang
- Institute of Molecular Precision Medicine and Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Zhonghua Hu
- Institute of Molecular Precision Medicine and Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China. .,Department of Critical Care Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,Hunan Key Laboratory of Animal Models for Human Diseases, School of Life Sciences, Central South University, Changsha, Hunan, China. .,Eye Center of Xiangya Hospital and Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, Hunan, China. .,National Clinical Research Center on Mental Disorders, Changsha, Hunan, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China. .,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China. .,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
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41
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Leung SK, Jeffries AR, Castanho I, Jordan BT, Moore K, Davies JP, Dempster EL, Bray NJ, O'Neill P, Tseng E, Ahmed Z, Collier DA, Jeffery ED, Prabhakar S, Schalkwyk L, Jops C, Gandal MJ, Sheynkman GM, Hannon E, Mill J. Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing. Cell Rep 2021; 37:110022. [PMID: 34788620 PMCID: PMC8609283 DOI: 10.1016/j.celrep.2021.110022] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 07/30/2021] [Accepted: 10/28/2021] [Indexed: 12/05/2022] Open
Abstract
Alternative splicing is a post-transcriptional regulatory mechanism producing distinct mRNA molecules from a single pre-mRNA with a prominent role in the development and function of the central nervous system. We used long-read isoform sequencing to generate full-length transcript sequences in the human and mouse cortex. We identify novel transcripts not present in existing genome annotations, including transcripts mapping to putative novel (unannotated) genes and fusion transcripts incorporating exons from multiple genes. Global patterns of transcript diversity are similar between human and mouse cortex, although certain genes are characterized by striking differences between species. We also identify developmental changes in alternative splicing, with differential transcript usage between human fetal and adult cortex. Our data confirm the importance of alternative splicing in the cortex, dramatically increasing transcriptional diversity and representing an important mechanism underpinning gene regulation in the brain. We provide transcript-level data for human and mouse cortex as a resource to the scientific community. There is widespread transcript diversity in the cortex and many novel transcripts Some genes display big differences in isoform number between human and mouse cortex There is evidence of differential transcript usage between human fetal and adult cortex There are many novel isoforms of genes associated with human brain disease
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Key Words
- isoform, transcript, expression, brain, cortex, mouse, human, adult, fetal, long-read sequencing, alternative splicing
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Affiliation(s)
| | | | - Isabel Castanho
- University of Exeter, Exeter, UK; Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Ben T Jordan
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | | | | | | | | | | | | | | | | | - Erin D Jeffery
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Shyam Prabhakar
- Genome Institute of Singapore, Agency for Science, Technology and Research (A(∗)STAR), Singapore, Singapore
| | | | - Connor Jops
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael J Gandal
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Gloria M Sheynkman
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; UVA Cancer Center, University of Virginia, Charlottesville, VA, USA
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42
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He Y, Huang L, Tang Y, Yang Z, Han Z. Genome-wide Identification and Analysis of Splicing QTLs in Multiple Sclerosis by RNA-Seq Data. Front Genet 2021; 12:769804. [PMID: 34868258 PMCID: PMC8633104 DOI: 10.3389/fgene.2021.769804] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 10/18/2021] [Indexed: 12/21/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelinating lesions in the central nervous system. Recently, the dysregulation of alternative splicing (AS) in the brain has been found to significantly influence the progression of MS. Moreover, previous studies demonstrate that many MS-related variants in the genome act as the important regulation factors of AS events and contribute to the pathogenesis of MS. However, by far, no genome-wide research about the effect of genomic variants on AS events in MS has been reported. Here, we first implemented a strategy to obtain genomic variant genotype and AS isoform average percentage spliced-in values from RNA-seq data of 142 individuals (51 MS patients and 91 controls). Then, combing the two sets of data, we performed a cis-splicing quantitative trait loci (sQTLs) analysis to identify the cis-acting loci and the affected differential AS events in MS and further explored the characteristics of these cis-sQTLs. Finally, the weighted gene coexpression network and gene set enrichment analyses were used to investigate gene interaction pattern and functions of the affected AS events in MS. In total, we identified 5835 variants affecting 672 differential AS events. The cis-sQTLs tend to be distributed in proximity of the gene transcription initiation site, and the intronic variants of them are more capable of regulating AS events. The retained intron AS events are more susceptible to influence of genome variants, and their functions are involved in protein kinase and phosphorylation modification. In summary, these findings provide an insight into the mechanism of MS.
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Affiliation(s)
| | | | | | | | - Zhijie Han
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
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43
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CYP11B1 variants influence skeletal maturation via alternative splicing. Commun Biol 2021; 4:1274. [PMID: 34754074 PMCID: PMC8578655 DOI: 10.1038/s42003-021-02774-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 09/24/2021] [Indexed: 12/13/2022] Open
Abstract
We performed genome-wide association study meta-analysis to identify genetic determinants of skeletal age (SA) deviating in multiple growth disorders. The joint meta-analysis (N = 4557) in two multiethnic cohorts of school-aged children identified one locus, CYP11B1 (expression confined to the adrenal gland), robustly associated with SA (rs6471570-A; β = 0.14; P = 6.2 × 10-12). rs6410 (a synonymous variant in the first exon of CYP11B1 in high LD with rs6471570), was prioritized for functional follow-up being second most significant and the one closest to the first intron-exon boundary. In 208 adrenal RNA-seq samples from GTEx, C-allele of rs6410 was associated with intron 3 retention (P = 8.11 × 10-40), exon 4 inclusion (P = 4.29 × 10-34), and decreased exon 3 and 5 splicing (P = 7.85 × 10-43), replicated using RT-PCR in 15 adrenal samples. As CYP11B1 encodes 11-β-hydroxylase, involved in adrenal glucocorticoid and mineralocorticoid biosynthesis, our findings highlight the role of adrenal steroidogenesis in SA in healthy children, suggesting alternative splicing as a likely underlying mechanism.
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44
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FXR1 regulation of parvalbumin interneurons in the prefrontal cortex is critical for schizophrenia-like behaviors. Mol Psychiatry 2021; 26:6845-6867. [PMID: 33863995 PMCID: PMC8521570 DOI: 10.1038/s41380-021-01096-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 03/18/2021] [Accepted: 03/31/2021] [Indexed: 12/13/2022]
Abstract
Parvalbumin interneurons (PVIs) are affected in many psychiatric disorders including schizophrenia (SCZ), however the mechanism remains unclear. FXR1, a high confident risk gene for SCZ, is indispensable but its role in the brain is largely unknown. We show that deleting FXR1 from PVIs of medial prefrontal cortex (mPFC) leads to reduced PVI excitability, impaired mPFC gamma oscillation, and SCZ-like behaviors. PVI-specific translational profiling reveals that FXR1 regulates the expression of Cacna1h/Cav3.2 a T-type calcium channel implicated in autism and epilepsy. Inhibition of Cav3.2 in PVIs of mPFC phenocopies whereas elevation of Cav3.2 in PVIs of mPFC rescues behavioral deficits resulted from FXR1 deficiency. Stimulation of PVIs using a gamma oscillation-enhancing light flicker rescues behavioral abnormalities caused by FXR1 deficiency in PVIs. This work unveils the function of a newly identified SCZ risk gene in SCZ-relevant neurons and identifies a therapeutic target and a potential noninvasive treatment for psychiatric disorders.
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45
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Li X, Pan X, Zhou H, Wang P, Gao Y, Shang S, Guo S, Sun J, Xiong Z, Ning S, Zhi H, Li X. Comprehensive characterization genetic regulation and chromatin landscape of enhancer-associated long non-coding RNAs and their implication in human cancer. Brief Bioinform 2021; 23:6375264. [PMID: 34581409 DOI: 10.1093/bib/bbab401] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 08/19/2021] [Accepted: 09/02/2021] [Indexed: 02/06/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) that emanate from enhancer regions (defined as enhancer-associated lncRNAs, or elncRNAs) are emerging as critical regulators in disease progression. However, their biological characteristics and clinical relevance have not been fully portrayed. Here, based on the traditional expression quantitative loci (eQTL) and our optimized residual eQTL method, we comprehensively described the genetic effect on elncRNA expression in more than 300 lymphoblastoid cell lines. Meanwhile, a chromatin atlas of elncRNAs relative to the genetic regulation state was depicted. By applying the maximum likelihood estimate method, we successfully identified causal elncRNAs for protein-coding gene expression reprogramming and showed their associated single nucleotide polymorphisms (SNPs) favor binding of transcription factors. Further epigenome analysis revealed two immune-associated elncRNAs AL662844.4 and LINC01215 possess high levels of H3K27ac and H3K4me1 in human cancer. Besides, pan-cancer analysis of 3D genome, transcriptome, and regulatome data showed they potentially regulate tumor-immune cell interaction through affecting MHC class I genes and CD47, respectively. Moreover, our study showed there exist associations between elncRNA and patient survival. Finally, we made a user-friendly web interface available for exploring the regulatory relationship of SNP-elncRNA-protein-coding gene triplets (http://bio-bigdata.hrbmu.edu.cn/elncVarReg). Our study provides critical mechanistic insights for elncRNA function and illustrates their implications in human cancer.
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Affiliation(s)
- Xin Li
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Xu Pan
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Hanxiao Zhou
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Peng Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Yue Gao
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Shipeng Shang
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Shuang Guo
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Jie Sun
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Zhiying Xiong
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Shangwei Ning
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Hui Zhi
- College of Bioinformatics Science and Technology, Harbin Medical University, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, China
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46
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Aygün N, Elwell AL, Liang D, Lafferty MJ, Cheek KE, Courtney KP, Mory J, Hadden-Ford E, Krupa O, de la Torre-Ubieta L, Geschwind DH, Love MI, Stein JL. Brain-trait-associated variants impact cell-type-specific gene regulation during neurogenesis. Am J Hum Genet 2021; 108:1647-1668. [PMID: 34416157 PMCID: PMC8456186 DOI: 10.1016/j.ajhg.2021.07.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 07/23/2021] [Indexed: 12/21/2022] Open
Abstract
Interpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing quantitative trait locus (e/sQTL) analyses is generally performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements active during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs, and allele-specific expression in cultured cells representing two major developmental stages, primary human neural progenitors (n = 85) and their sorted neuronal progeny (n = 74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptome-wide association, we uncover cell-type-specific regulatory mechanisms underlying risk for brain-relevant traits that are active during neocortical differentiation. Specifically, we identified a progenitor-specific eQTL for CENPW co-localized with common variant associations for cortical surface area and educational attainment.
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Affiliation(s)
- Nil Aygün
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Angela L Elwell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Dan Liang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael J Lafferty
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kerry E Cheek
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kenan P Courtney
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica Mory
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ellie Hadden-Ford
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Oleh Krupa
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Luis de la Torre-Ubieta
- Neurogenetics Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Daniel H Geschwind
- Neurogenetics Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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47
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Abood A, Farber CR. Using "-omics" Data to Inform Genome-wide Association Studies (GWASs) in the Osteoporosis Field. Curr Osteoporos Rep 2021; 19:369-380. [PMID: 34125409 PMCID: PMC8767463 DOI: 10.1007/s11914-021-00684-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/22/2021] [Indexed: 01/12/2023]
Abstract
PURPOSE OF REVIEW Osteoporosis constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 loci influencing bone mineral density (BMD); however, few of the causal genes have been identified. Here, we review approaches that use "-omics" data and genetic- and systems genetics-based analytical strategies to facilitate causal gene discovery. RECENT FINDINGS The bone field is beginning to adopt approaches that are commonplace in other disease disciplines. The slower progress has been due in part to the lack of large-scale "omics" data on bone and bone cells. This is however changing, and approaches such as eQTL colocalization, transcriptome-wide association studies (TWASs), network, and integrative approaches are beginning to provide significant insight into the genes responsible for BMD GWAS associations. The use of "-omics" data to inform BMD GWASs has increased in recent years, leading to the identification of novel regulators of BMD in humans. The ultimate goal will be to use this information to develop more effective therapies to treat and ultimately prevent osteoporosis.
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Affiliation(s)
- Abdullah Abood
- Center for Public Health Genomics, University of Virginia, 800717, Charlottesville, VA, 22908, USA
- Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia, 800717, Charlottesville, VA, 22908, USA.
- Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.
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48
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Ago Y, Asano S, Hashimoto H, Waschek JA. Probing the VIPR2 Microduplication Linkage to Schizophrenia in Animal and Cellular Models. Front Neurosci 2021; 15:717490. [PMID: 34366784 PMCID: PMC8339898 DOI: 10.3389/fnins.2021.717490] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/05/2021] [Indexed: 01/30/2023] Open
Abstract
Pituitary adenylate cyclase-activating polypeptide (PACAP, gene name ADCYAP1) is a multifunctional neuropeptide involved in brain development and synaptic plasticity. With respect to PACAP function, most attention has been given to that mediated by its specific receptor PAC1 (ADCYAP1R1). However, PACAP also binds tightly to the high affinity receptors for vasoactive intestinal peptide (VIP, VIP), called VPAC1 and VPAC2 (VIPR1 and VIPR2, respectively). Depending on innervation patterns, PACAP can thus interact physiologically with any of these receptors. VPAC2 receptors, the focus of this review, are known to have a pivotal role in regulating circadian rhythms and to affect multiple other processes in the brain, including those involved in fear cognition. Accumulating evidence in human genetics indicates that microduplications at 7q36.3, containing VIPR2 gene, are linked to schizophrenia and possibly autism spectrum disorder. Although detailed molecular mechanisms have not been fully elucidated, recent studies in animal models suggest that overactivation of the VPAC2 receptor disrupts cortical circuit maturation. The VIPR2 linkage can thus be potentially explained by inappropriate control of receptor signaling at a time when neural circuits involved in cognition and social behavior are being established. Alternatively, or in addition, VPAC2 receptor overactivity may disrupt ongoing synaptic plasticity during processes of learning and memory. Finally, in vitro data indicate that PACAP and VIP have differential activities on the maturation of neurons via their distinct signaling pathways. Thus perturbations in the balance of VPAC2, VPAC1, and PAC1 receptors and their ligands may have important consequences in brain development and plasticity.
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Affiliation(s)
- Yukio Ago
- Department of Cellular and Molecular Pharmacology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Satoshi Asano
- Department of Cellular and Molecular Pharmacology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Hitoshi Hashimoto
- Laboratory of Molecular Neuropharmacology, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan.,Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan.,Division of Bioscience, Institute for Datability Science, Osaka University, Suita, Japan.,Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - James A Waschek
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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49
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Chang D, Luong P, Li Q, LeBarron J, Anderson M, Barrett L, Lencer WI. Small-molecule modulators of INAVA cytosolic condensate and cell-cell junction assemblies. J Cell Biol 2021; 220:212462. [PMID: 34251416 PMCID: PMC8276315 DOI: 10.1083/jcb.202007177] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 04/01/2021] [Accepted: 05/26/2021] [Indexed: 01/08/2023] Open
Abstract
Epithelial cells lining mucosal surfaces distinctively express the inflammatory bowel disease risk gene INAVA. We previously found that INAVA has dual and competing functions: one at lateral membranes where it affects mucosal barrier function and the other in the cytosol where INAVA enhances IL-1β signal transduction and protein ubiquitination and forms puncta. We now find that IL-1β–induced INAVA puncta are biomolecular condensates that rapidly assemble and physiologically resolve. The condensates contain ubiquitin and the E3 ligase βTrCP2, and their formation correlates with amplified ubiquitination, suggesting function in regulation of cellular proteostasis. Accordingly, a small-molecule screen identified ROS inducers, proteasome inhibitors, and inhibitors of the protein folding chaperone HSP90 as potent agonists for INAVA condensate formation. Notably, inhibitors of the p38α and mTOR pathways enhanced resolution of the condensates, and inhibitors of the Rho–ROCK pathway induced INAVA’s competing function by recruiting INAVA to newly assembled intercellular junctions in cells where none existed before.
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Affiliation(s)
- Denis Chang
- Division of Gastroenterology and Nutrition, Department of Pediatrics, Boston Children's Hospital, Boston, MA.,Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Phi Luong
- Division of Gastroenterology and Nutrition, Department of Pediatrics, Boston Children's Hospital, Boston, MA.,Harvard Digestive Disease Center, Boston, MA.,Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Qian Li
- Division of Gastroenterology and Nutrition, Department of Pediatrics, Boston Children's Hospital, Boston, MA.,Shanghai Children's Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Jamie LeBarron
- Division of Gastroenterology and Nutrition, Department of Pediatrics, Boston Children's Hospital, Boston, MA
| | - Michael Anderson
- Division of Gastroenterology and Nutrition, Department of Pediatrics, Boston Children's Hospital, Boston, MA.,Harvard Digestive Disease Center, Boston, MA
| | - Lee Barrett
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Boston Children's Hospital and Harvard Medical School, Boston, MA
| | - Wayne I Lencer
- Division of Gastroenterology and Nutrition, Department of Pediatrics, Boston Children's Hospital, Boston, MA.,Harvard Digestive Disease Center, Boston, MA.,Department of Pediatrics, Harvard Medical School, Boston, MA
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50
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Takahashi Y, Maynard KR, Tippani M, Jaffe AE, Martinowich K, Kleinman JE, Weinberger DR, Hyde TM. Single molecule in situ hybridization reveals distinct localizations of schizophrenia risk-related transcripts SNX19 and AS3MT in human brain. Mol Psychiatry 2021; 26:3536-3547. [PMID: 33649454 DOI: 10.1038/s41380-021-01046-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 01/20/2021] [Accepted: 02/02/2021] [Indexed: 11/09/2022]
Abstract
Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with schizophrenia risk. Integration of RNA-sequencing data from postmortem human brains with these risk SNPs identified transcripts associated with increased schizophrenia susceptibility, including a class of exon 9-spliced isoforms of Sorting nexin-19 (SNX19d9) and an isoform of Arsenic methyltransferase (AS3MT) splicing out exons 2 and 3 (AS3MTd2d3). However, the biological function of these transcript variants is unclear. Defining the cell types where these risk transcripts are dominantly expressed is an important step to understand function, in prioritizing specific cell types and/or neural pathways in subsequent studies. To identify the cell type-specific localization of SNX19 and AS3MT in the human dorsolateral prefrontal cortex (DLPFC), we used single-molecule in situ hybridization techniques combined with automated quantification and machine learning approaches to analyze 10 postmortem brains of neurotypical individuals. These analyses revealed that both pan-SNX19 and pan-AS3MT were more highly expressed in neurons than non-neurons in layers II/III and VI of DLPFC. Furthermore, pan-SNX19 was preferentially expressed in glutamatergic neurons, while pan-AS3MT was preferentially expressed in GABAergic neurons. Finally, we utilized duplex BaseScope technology, to delineate the localization of SNX19d9 and AS3MTd2d3 splice variants, revealing consistent trends in spatial gene expression among pan-transcripts and schizophrenia risk-related transcript variants. These findings demonstrate that schizophrenia risk transcripts have distinct localization patterns in the healthy human brains, and suggest that SNX19 transcripts might disrupt the normal function of glutamatergic neurons, while AS3MT may lead to disturbances in the GABAergic system in the pathophysiology of schizophrenia.
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Affiliation(s)
- Yoichiro Takahashi
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Legal Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kristen R Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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