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Zhou H, Zeng H, Yan T, Chen S, Fu Y, Qin G, Zhao X, Heng Y, Li J, Lin F, Xu D, Wei N, Deng XW. Light regulates nuclear detainment of intron-retained transcripts through COP1-spliceosome to modulate photomorphogenesis. Nat Commun 2024; 15:5130. [PMID: 38879536 PMCID: PMC11180117 DOI: 10.1038/s41467-024-49571-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 06/10/2024] [Indexed: 06/19/2024] Open
Abstract
Intron retention (IR) is the most common alternative splicing event in Arabidopsis. An increasing number of studies have demonstrated the major role of IR in gene expression regulation. The impacts of IR on plant growth and development and response to environments remain underexplored. Here, we found that IR functions directly in gene expression regulation on a genome-wide scale through the detainment of intron-retained transcripts (IRTs) in the nucleus. Nuclear-retained IRTs can be kept away from translation through this mechanism. COP1-dependent light modulation of the IRTs of light signaling genes, such as PIF4, RVE1, and ABA3, contribute to seedling morphological development in response to changing light conditions. Furthermore, light-induced IR changes are under the control of the spliceosome, and in part through COP1-dependent ubiquitination and degradation of DCS1, a plant-specific spliceosomal component. Our data suggest that light regulates the activity of the spliceosome and the consequent IRT nucleus detainment to modulate photomorphogenesis through COP1.
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Affiliation(s)
- Hua Zhou
- Shenzhen Key Laboratory of Plant Genetic Engineering and Molecular Design, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Haiyue Zeng
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, 61000, Shandong, China
- Peking-Tsinghua Center for Life Sciences, Peking University, 100871, Beijing, China
| | - Tingting Yan
- Shenzhen Key Laboratory of Plant Genetic Engineering and Molecular Design, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Sunlu Chen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Ying Fu
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, 61000, Shandong, China
| | - Guochen Qin
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, 61000, Shandong, China
| | - Xianhai Zhao
- Shenzhen Key Laboratory of Plant Genetic Engineering and Molecular Design, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yueqin Heng
- Shenzhen Key Laboratory of Plant Genetic Engineering and Molecular Design, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Jian Li
- Shenzhen Key Laboratory of Plant Genetic Engineering and Molecular Design, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Fang Lin
- Ministry of Education Key Laboratory of Cell Activities and Stress Adaptations, Lanzhou University, Lanzhou, 730000, China
| | - Dongqing Xu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Ning Wei
- School of Life Sciences, Southwest University, Chongqing, 400715, China
| | - Xing Wang Deng
- Shenzhen Key Laboratory of Plant Genetic Engineering and Molecular Design, Southern University of Science and Technology, Shenzhen, 518055, China.
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, 61000, Shandong, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, 100871, Beijing, China.
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2
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Huang AC, Su JY, Hung YJ, Chiang HL, Chen YT, Huang YT, Yu CHA, Lin HN, Lin CL. SpliceAPP: an interactive web server to predict splicing errors arising from human mutations. BMC Genomics 2024; 25:600. [PMID: 38877417 PMCID: PMC11179192 DOI: 10.1186/s12864-024-10512-x] [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: 03/01/2024] [Accepted: 06/07/2024] [Indexed: 06/16/2024] Open
Abstract
BACKGROUND Splicing variants are a major class of pathogenic mutations, with their severity equivalent to nonsense mutations. However, redundant and degenerate splicing signals hinder functional assessments of sequence variations within introns, particularly at branch sites. We have established a massively parallel splicing assay to assess the impact on splicing of 11,191 disease-relevant variants. Based on the experimental results, we then applied regression-based methods to identify factors determining splicing decisions and their respective weights. RESULTS Our statistical modeling is highly sensitive, accurately annotating the splicing defects of near-exon intronic variants, outperforming state-of-the-art predictive tools. We have incorporated the algorithm and branchpoint information into a web-based tool, SpliceAPP, to provide an interactive application. This user-friendly website allows users to upload any genetic variants with genome coordinates (e.g., chr15 74,687,208 A G), and the tool will output predictions for splicing error scores and evaluate the impact on nearby splice sites. Additionally, users can query branch site information within the region of interest. CONCLUSIONS In summary, SpliceAPP represents a pioneering approach to screening pathogenic intronic variants, contributing to the development of precision medicine. It also facilitates the annotation of splicing motifs. SpliceAPP is freely accessible using the link https://bc.imb.sinica.edu.tw/SpliceAPP . Source code can be downloaded at https://github.com/hsinnan75/SpliceAPP .
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Affiliation(s)
- Ang-Chu Huang
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, Taiwan
| | - Jia-Ying Su
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
- Bioinformatics Program, International Graduate Program, Academia Sinica, Taipei, Taiwan
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Jen Hung
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan
| | - Hung-Lun Chiang
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan
| | - Yi-Ting Chen
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan
| | - Yen-Tsung Huang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
- Bioinformatics Program, International Graduate Program, Academia Sinica, Taipei, Taiwan
| | - Chen-Hsin Albert Yu
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan
| | - Hsin-Nan Lin
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan.
| | - Chien-Ling Lin
- Institute of Molecular Biology, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang District, Taipei City, 115014, Taiwan.
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, Taiwan.
- Bioinformatics Program, International Graduate Program, Academia Sinica, Taipei, Taiwan.
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3
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Pan F, Zhang R, Liu X, Shi X, Xin Q, Qiao D, Li C, Zhang Y, Chen M, Guo W, Luan S, Shao L. Three exonic variants in the PHEX gene cause aberrant splicing in a minigene assay. Front Genet 2024; 15:1353674. [PMID: 38841723 PMCID: PMC11150636 DOI: 10.3389/fgene.2024.1353674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 04/24/2024] [Indexed: 06/07/2024] Open
Abstract
Background: X-linked hypophosphatemia (XLH, OMIM 307800) is a rare phosphorus metabolism disorder caused by PHEX gene variants. Many variants simply classified as missense or nonsense variants were only analyzed at the DNA level. However, growing evidence indicates that some of these variants may alter pre-mRNA splicing, causing diseases. Therefore, this study aimed to use bioinformatics tools and a minigene assay to ascertain the effects of PHEX variations on pre-mRNA splicing. Methods: We analyzed 174 variants in the PHEX gene described as missense or nonsense variants. Finally, we selected eight candidate variants using bioinformatics tools to evaluate their effects on pre-mRNA splicing using a minigene assay system. The complementary DNA (cDNA) sequence for the PHEX gene (RefSeq NM_000444.6) serves as the basis for DNA variant numbering. Results: Of the eight candidate variants, three were found to cause abnormal splicing. Variants c.617T>G p.(Leu206Trp) and c.621T>A p.(Tyr207*) in exon 5 altered the splicing of pre-mRNA, owing to the activation of a cryptic splice site in exon 5, which produced an aberrant transcript lacking a part of exon 5, whereas variant c.1700G>C p.(Arg567Pro) in exon 16 led to the activation of a cryptic splice site in intron 16, resulting in a partial inclusion of intron 16. Conclusion: Our study employed a minigene system, which has a great degree of flexibility to assess abnormal splicing patterns under the circumstances of patient mRNA samples that are not available, to explore the impact of the exonic variants on pre-mRNA splicing. Based on the aforementioned experimental findings, we demonstrated the importance of analyzing exonic variants at the mRNA level.
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Affiliation(s)
- Fengjiao Pan
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
| | - Ruixiao Zhang
- Department of Emergency, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
| | - Xuyan Liu
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
| | - Xiaomeng Shi
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
| | - Qing Xin
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
- Department of Nephrology, The Key Laboratory for the Prevention and Treatment of Chronic Kidney Disease of Chongqing, Chongqing Clinical Research Center of Kidney and Urology Diseases, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Dan Qiao
- Department of Nephrology, Dalian Medical University, Dalian, China
| | - Changying Li
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
| | - Yan Zhang
- Department of Nephrology, Weifang Medical University, Weifang, China
| | - Mengke Chen
- Department of Nephrology, Liaocheng Third People’s Hospital, Liaocheng, China
| | - Wencong Guo
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
- Institute of Nephrology, Zhong Da Hospital, Southeast University School of Medicine, Nanjing, China
| | - Shufang Luan
- Department of Medical Insurance Administration, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
| | - Leping Shao
- Department of Nephrology, The Affiliated Qingdao Municipal Hospital of Qingdao University, Qingdao, China
- Department of Nephrology, The First Affiliated Hospital of Xiamen University, Xiamen, China
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4
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Kumar KR, Cowley MJ, Davis RL. The Next, Next-Generation of Sequencing, Promising to Boost Research and Clinical Practice. Semin Thromb Hemost 2024. [PMID: 38733978 DOI: 10.1055/s-0044-1786756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2024]
Affiliation(s)
- Kishore R Kumar
- Molecular Medicine Laboratory and Department of Neurology, Concord Repatriation General Hospital, Concord Clinical School, University of Sydney, Concord, NSW, Australia
- Genomics and Inherited Disease Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- School of Clinical Medicine, UNSW Sydney, Randwick, NSW, Australia
| | - Mark J Cowley
- School of Clinical Medicine, UNSW Sydney, Randwick, NSW, Australia
- Children's Cancer Institute, UNSW Sydney, Randwick, NSW, Australia
| | - Ryan L Davis
- Genomics and Inherited Disease Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Neurogenetics Research Group, Kolling Institute, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney and Northern Sydney Local Health District, St Leonards, NSW, Australia
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Recinos Y, Ustianenko D, Yeh YT, Wang X, Jacko M, Yesantharao LV, Wu Q, Zhang C. CRISPR-dCas13d-based deep screening of proximal and distal splicing-regulatory elements. Nat Commun 2024; 15:3839. [PMID: 38714659 PMCID: PMC11076525 DOI: 10.1038/s41467-024-47140-8] [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: 06/21/2023] [Accepted: 03/16/2024] [Indexed: 05/10/2024] Open
Abstract
Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is hampered by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically inactive CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identifies not only known SREs but also a previously unknown distal intronic SRE, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.
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Affiliation(s)
- Yocelyn Recinos
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Dmytro Ustianenko
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
- Flagship Pioneering, Cambridge, MA, 02142, USA
| | - Yow-Tyng Yeh
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Xiaojian Wang
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Martin Jacko
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
- Aperture Therapeutics, Inc., San Carlos, CA, 94070, USA
| | - Lekha V Yesantharao
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
- Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Qiyang Wu
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, 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.
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6
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Wu H, Lin JH, Tang XY, Marenne G, Zou WB, Schutz S, Masson E, Génin E, Fichou Y, Le Gac G, Férec C, Liao Z, Chen JM. Combining full-length gene assay and SpliceAI to interpret the splicing impact of all possible SPINK1 coding variants. Hum Genomics 2024; 18:21. [PMID: 38414044 PMCID: PMC10898081 DOI: 10.1186/s40246-024-00586-9] [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: 11/09/2023] [Accepted: 02/13/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Single-nucleotide variants (SNVs) within gene coding sequences can significantly impact pre-mRNA splicing, bearing profound implications for pathogenic mechanisms and precision medicine. In this study, we aim to harness the well-established full-length gene splicing assay (FLGSA) in conjunction with SpliceAI to prospectively interpret the splicing effects of all potential coding SNVs within the four-exon SPINK1 gene, a gene associated with chronic pancreatitis. RESULTS Our study began with a retrospective analysis of 27 SPINK1 coding SNVs previously assessed using FLGSA, proceeded with a prospective analysis of 35 new FLGSA-tested SPINK1 coding SNVs, followed by data extrapolation, and ended with further validation. In total, we analyzed 67 SPINK1 coding SNVs, which account for 9.3% of the 720 possible coding SNVs. Among these 67 FLGSA-analyzed SNVs, 12 were found to impact splicing. Through detailed comparison of FLGSA results and SpliceAI predictions, we inferred that the remaining 653 untested coding SNVs in the SPINK1 gene are unlikely to significantly affect splicing. Of the 12 splice-altering events, nine produced both normally spliced and aberrantly spliced transcripts, while the remaining three only generated aberrantly spliced transcripts. These splice-impacting SNVs were found solely in exons 1 and 2, notably at the first and/or last coding nucleotides of these exons. Among the 12 splice-altering events, 11 were missense variants (2.17% of 506 potential missense variants), and one was synonymous (0.61% of 164 potential synonymous variants). Notably, adjusting the SpliceAI cut-off to 0.30 instead of the conventional 0.20 would improve specificity without reducing sensitivity. CONCLUSIONS By integrating FLGSA with SpliceAI, we have determined that less than 2% (1.67%) of all possible coding SNVs in SPINK1 significantly influence splicing outcomes. Our findings emphasize the critical importance of conducting splicing analysis within the broader genomic sequence context of the study gene and highlight the inherent uncertainties associated with intermediate SpliceAI scores (0.20 to 0.80). This study contributes to the field by being the first to prospectively interpret all potential coding SNVs in a disease-associated gene with a high degree of accuracy, representing a meaningful attempt at shifting from retrospective to prospective variant analysis in the era of exome and genome sequencing.
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Affiliation(s)
- Hao Wu
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Jin-Huan Lin
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Xin-Ying Tang
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
- Department of Prevention and Health Care, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China
| | - Gaëlle Marenne
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France
| | - Wen-Bin Zou
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Sacha Schutz
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France
- Service de Génétique Médicale et de Biologie de La Reproduction, CHRU Brest, Brest, France
| | - Emmanuelle Masson
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France
- Service de Génétique Médicale et de Biologie de La Reproduction, CHRU Brest, Brest, France
| | | | - Yann Fichou
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France
| | - Gerald Le Gac
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France
- Service de Génétique Médicale et de Biologie de La Reproduction, CHRU Brest, Brest, France
| | - Claude Férec
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France
| | - Zhuan Liao
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, 168 Changhai Road, Shanghai, 200433, China.
- Shanghai Institute of Pancreatic Diseases, Shanghai, China.
| | - Jian-Min Chen
- Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France.
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7
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Rinaldi S, Moroni E, Rozza R, Magistrato A. Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation. J Chem Theory Comput 2024; 20:993-1018. [PMID: 38287883 DOI: 10.1021/acs.jctc.3c01239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.
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Affiliation(s)
- Silvia Rinaldi
- National Research Council of Italy (CNR) - Institute of Chemistry of OrganoMetallic Compounds (ICCOM), c/o Area di Ricerca CNR di Firenze Via Madonna del Piano 10, 50019 Sesto Fiorentino, Florence, Italy
| | - Elisabetta Moroni
- National Research Council of Italy (CNR) - Institute of Chemical Sciences and Technologies (SCITEC), via Mario Bianco 9, 20131 Milano, Italy
| | - Riccardo Rozza
- National Research Council of Italy (CNR) - Institute of Material Foundry (IOM) c/o International School for Advanced Studies (SISSA), Via Bonomea, 265, 34136 Trieste, Italy
| | - Alessandra Magistrato
- National Research Council of Italy (CNR) - Institute of Material Foundry (IOM) c/o International School for Advanced Studies (SISSA), Via Bonomea, 265, 34136 Trieste, Italy
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8
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Bagger FO, Borgwardt L, Jespersen AS, Hansen AR, Bertelsen B, Kodama M, Nielsen FC. Whole genome sequencing in clinical practice. BMC Med Genomics 2024; 17:39. [PMID: 38287327 PMCID: PMC10823711 DOI: 10.1186/s12920-024-01795-w] [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: 08/14/2023] [Accepted: 01/01/2024] [Indexed: 01/31/2024] Open
Abstract
Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.
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Affiliation(s)
- Frederik Otzen Bagger
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Line Borgwardt
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Andreas Sand Jespersen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anna Reimer Hansen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Birgitte Bertelsen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Miyako Kodama
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Finn Cilius Nielsen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
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9
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Bartosch AMW, Youth EHH, Hansen S, Wu Y, Buchanan HM, Kaufman ME, Xiao H, Koo SY, Ashok A, Sivakumar S, Soni RK, Dumitrescu LC, Lam TG, Ropri AS, Lee AJ, Klein HU, Vardarajan BN, Bennett DA, Young-Pearse TL, De Jager PL, Hohman TJ, Sproul AA, Teich AF. ZCCHC17 Modulates Neuronal RNA Splicing and Supports Cognitive Resilience in Alzheimer's Disease. J Neurosci 2024; 44:e2324222023. [PMID: 38050142 PMCID: PMC10860597 DOI: 10.1523/jneurosci.2324-22.2023] [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: 12/20/2022] [Revised: 09/22/2023] [Accepted: 11/07/2023] [Indexed: 12/06/2023] Open
Abstract
ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis using data from human autopsy tissue (consisting of males and females) and female human cell lines. Co-immunoprecipitation (co-IP) of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA-splicing proteins. ZCCHC17 knockdown results in widespread RNA-splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4-dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find a significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that the maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.
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Affiliation(s)
- Anne Marie W Bartosch
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Elliot H H Youth
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Shania Hansen
- Department of Neurology, Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Yiyang Wu
- Department of Neurology, Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Heather M Buchanan
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Maria E Kaufman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Harrison Xiao
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - So Yeon Koo
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Archana Ashok
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Sharanya Sivakumar
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Rajesh K Soni
- Proteomics and Macromolecular Crystallography Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York 10032
| | - Logan C Dumitrescu
- Department of Neurology, Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Tiffany G Lam
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Ali S Ropri
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Annie J Lee
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
- Department of Neurology, Center for Translational & Computational Neuroimmunology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York 10032
| | - Hans-Ulrich Klein
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
- Department of Neurology, Center for Translational & Computational Neuroimmunology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York 10032
| | - Badri N Vardarajan
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
- Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York 10032
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois 60612
| | - Tracy L Young-Pearse
- Department of Neurology, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115
- Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts 02138
| | - Philip L De Jager
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
- Department of Neurology, Center for Translational & Computational Neuroimmunology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York 10032
| | - Timothy J Hohman
- Department of Neurology, Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Andrew A Sproul
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
| | - Andrew F Teich
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York 10032
- Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York 10032
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10
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Knill C, Henderson EJ, Johnson C, Wah VY, Cheng K, Forster AJ, Itasaki N. Defects of the spliceosomal gene SNRPB affect osteo- and chondro-differentiation. FEBS J 2024; 291:272-291. [PMID: 37584444 DOI: 10.1111/febs.16934] [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: 03/06/2023] [Revised: 07/25/2023] [Accepted: 08/14/2023] [Indexed: 08/17/2023]
Abstract
Although gene splicing occurs throughout the body, the phenotype of spliceosomal defects is largely limited to specific tissues. Cerebro-costo-mandibular syndrome (CCMS) is one such spliceosomal disease, which presents as congenital skeletal dysmorphism and is caused by mutations of SNRPB gene encoding Small Nuclear Ribonucleoprotein Polypeptides B/B' (SmB/B'). This study employed in vitro cell cultures to monitor osteo- and chondro-differentiation and examined the role of SmB/B' in the differentiation process. We found that low levels of SmB/B' by knockdown or mutations of SNRPB led to suppressed osteodifferentiation in Saos-2 osteoprogenitor-like cells, which was accompanied by affected splicing of Dlx5. On the other hand, low SmB/B' led to promoted chondrogenesis in HEPM mesenchymal stem cells. Consistent with other reports, osteogenesis was promoted by the Wnt/β-catenin pathway activator and suppressed by Wnt and BMP blockers, whereas chondrogenesis was promoted by Wnt inhibitors. Suppressed osteogenic markers by SNRPB knockdown were partly rescued by Wnt/β-catenin pathway activation. Reporter analysis revealed that suppression of SNRPB results in attenuated Wnt pathway and/or enhanced BMP pathway activities. SNRPB knockdown altered splicing of TCF7L2 which impacts Wnt/β-catenin pathway activities. This work helps unravel the mechanism underlying CCMS whereby reduced expression of spliceosomal proteins causes skeletal phenotypes.
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Affiliation(s)
- Chris Knill
- Faculty of Life Sciences, University of Bristol, UK
| | | | - Craig Johnson
- Faculty of Health Sciences, University of Bristol, UK
| | - Vun Yee Wah
- Faculty of Life Sciences, University of Bristol, UK
| | - Kevin Cheng
- Faculty of Life Sciences, University of Bristol, UK
| | | | - Nobue Itasaki
- Faculty of Health Sciences, University of Bristol, UK
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11
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Smith C, Kitzman JO. Benchmarking splice variant prediction algorithms using massively parallel splicing assays. Genome Biol 2023; 24:294. [PMID: 38129864 PMCID: PMC10734170 DOI: 10.1186/s13059-023-03144-z] [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: 05/04/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes. RESULTS We benchmark eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compare experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, is lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieve the best overall performance at distinguishing disruptive and neutral variants, and controlling for overall call rate genome-wide, SpliceAI and Pangolin have superior sensitivity. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues. CONCLUSION SpliceAI and Pangolin show the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.
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Affiliation(s)
- Cathy Smith
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Jacob O Kitzman
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
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12
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Pino MG, Rich KA, Hall NJ, Jones ML, Fox A, Musier-Forsyth K, Kolb SJ. Heterogeneous splicing patterns resulting from KIF5A variants associated with amyotrophic lateral sclerosis. Hum Mol Genet 2023; 32:3166-3180. [PMID: 37593923 DOI: 10.1093/hmg/ddad134] [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: 04/24/2023] [Revised: 07/28/2023] [Accepted: 08/03/2023] [Indexed: 08/19/2023] Open
Abstract
Single-nucleotide variants (SNVs) in the gene encoding Kinesin Family Member 5A (KIF5A), a neuronal motor protein involved in anterograde transport along microtubules, have been associated with amyotrophic lateral sclerosis (ALS). ALS is a rapidly progressive and fatal neurodegenerative disease that primarily affects the motor neurons. Numerous ALS-associated KIF5A SNVs are clustered near the splice-site junctions of the penultimate exon 27 and are predicted to alter the carboxy-terminal (C-term) cargo-binding domain of KIF5A. Mis-splicing of exon 27, resulting in exon exclusion, is proposed to be the mechanism by which these SNVs cause ALS. Whether all SNVs proximal to exon 27 result in exon exclusion is unclear. To address this question, we designed an in vitro minigene splicing assay in human embryonic kidney 293 cells, which revealed heterogeneous site-specific effects on splicing: only 5' splice-site (5'ss) SNVs resulted in exon skipping. We also quantified splicing in select clustered, regularly interspaced, short palindromic repeats-edited human stem cells, differentiated to motor neurons, and in neuronal tissues from a 5'ss SNV knock-in mouse, which showed the same result. Moreover, the survival of representative 3' splice site, 5'ss, and truncated C-term variant KIF5A (v-KIF5A) motor neurons was severely reduced compared with wild-type motor neurons, and overt morphological changes were apparent. While the total KIF5A mRNA levels were comparable across the cell lines, the total KIF5A protein levels were decreased for v-KIF5A lines, suggesting an impairment of protein synthesis or stability. Thus, despite the heterogeneous effect on ribonucleic acid splicing, KIF5A SNVs similarly reduce the availability of the KIF5A protein, leading to axonal transport defects and motor neuron pathology.
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Affiliation(s)
- Megan G Pino
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
- Center for RNA Biology, The Ohio State University, Columbus, OH 43210, United States
- Department of Biological Chemistry & Pharmacology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
| | - Kelly A Rich
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
| | - Nicholas J Hall
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
- Center for RNA Biology, The Ohio State University, Columbus, OH 43210, United States
| | - Meredith L Jones
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
| | - Ashley Fox
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
| | - Karin Musier-Forsyth
- Center for RNA Biology, The Ohio State University, Columbus, OH 43210, United States
- Department of Chemistry & Biochemistry, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
| | - Stephen J Kolb
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
- Center for RNA Biology, The Ohio State University, Columbus, OH 43210, United States
- Department of Biological Chemistry & Pharmacology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
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13
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Shemirani R, Le M, Nakano Y. Mutations Causing X-Linked Amelogenesis Imperfecta Alter miRNA Formation from Amelogenin Exon4. J Dent Res 2023; 102:1210-1219. [PMID: 37563801 PMCID: PMC10548775 DOI: 10.1177/00220345231180572] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023] Open
Abstract
Amelogenin plays a crucial role in tooth enamel formation, and mutations on X-chromosomal amelogenin cause X-linked amelogenesis imperfecta (AI). Amelogenin pre-messenger RNA (mRNA) is highly alternatively spliced, and during alternative splicing, exon4 is mostly skipped, leading to the formation of a microRNA (miR-exon4) that has been suggested to function in enamel and bone formation. While delivering the functional variation of amelogenin proteins, alternative splicing of exon4 is the decisive first step to producing miR-exon4. However, the factors that regulate the splicing of exon4 are not well understood. This study aimed to investigate the association between known mutations in exon4 and exon5 of X chromosome amelogenin that causes X-linked AI, the splicing of exon4, and miR-exon4 formation. Our results showed mutations in exon4 and exon5 of the amelogenin gene, including c.120T>C, c.152C>T, c.155C>G, and c.155delC, significantly affected the splicing of exon4 and subsequent miR-exon4 production. Using an amelogenin minigene transfected in HEK-293 cells, we observed increased inclusion of exon4 in amelogenin mRNA and reduced miR-exon4 production with these mutations. In silico analysis predicted that Ser/Arg-rich RNA splicing factor (SRSF) 2 and SRSF5 were the regulatory factors for exon4 and exon5 splicing, respectively. Electrophoretic mobility shift assay confirmed that SRSF2 binds to exon4 and SRSF5 binds to exon5, and mutations in each exon can alter SRSF binding. Transfection of the amelogenin minigene to LS8 ameloblastic cells suppressed expression of the known miR-exon4 direct targets, Nfia and Prkch, related to multiple pathways. Given the mutations on the minigene, the expression of Prkch has been significantly upregulated with c.155C>G and c.155delC mutations. Together, we confirmed that exon4 splicing is critical for miR-exon4 production, and mutations causing X-linked AI in exon4 and exon5 significantly affect exon4 splicing and following miR-exon4 production. The change in miR-exon4 would be an additional etiology of enamel defects seen in some X-linked AI.
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Affiliation(s)
- R. Shemirani
- Department of Orofacial Sciences, School of Dentistry, University of California, San Francisco, CA, USA
- Oral and Craniofacial Science, Graduate Division, University of California, San Francisco, CA, USA
| | - M.H. Le
- Oral and Craniofacial Science, Graduate Division, University of California, San Francisco, CA, USA
- Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, CA, USA
- College of Dental Medicine, California Northstate University, Elk Grove, CA, USA
| | - Y. Nakano
- Department of Orofacial Sciences, School of Dentistry, University of California, San Francisco, CA, USA
- Center for Children’s Oral Health Research, School of Dentistry, University of California, San Francisco, CA, USA
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14
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Wang R, Helbig I, Edmondson AC, Lin L, Xing Y. Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis. Brief Bioinform 2023; 24:bbad284. [PMID: 37580177 PMCID: PMC10516351 DOI: 10.1093/bib/bbad284] [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: 03/14/2023] [Revised: 07/10/2023] [Accepted: 07/20/2023] [Indexed: 08/16/2023] Open
Abstract
Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.
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Affiliation(s)
- Robert Wang
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ingo Helbig
- The Epilepsy NeuroGenetics Initiative, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew C Edmondson
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Lan Lin
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Yi Xing
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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15
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Recinos Y, Ustianenko D, Yeh YT, Wang X, Jacko M, Yesantharao LV, Wu Q, Zhang C. Deep screening of proximal and distal splicing-regulatory elements in a native sequence context. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.21.554109. [PMID: 37662340 PMCID: PMC10473672 DOI: 10.1101/2023.08.21.554109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is impeded by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically dead CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identified not only known SREs, but also a novel distal intronic splicing enhancer, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.
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Affiliation(s)
- Yocelyn Recinos
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
| | - Dmytro Ustianenko
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
- Present address: Flagship Pioneering, Cambridge, MA 02142, USA
| | - Yow-Tyng Yeh
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
| | - Xiaojian Wang
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
| | - Martin Jacko
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
- Present address: Aperture Therapeutics, Inc., San Carlos, CA 94070, USA
| | - Lekha V. Yesantharao
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
- Present address: Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Qiyang Wu
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
| | - Chaolin Zhang
- Department of Systems Biology, Department of Biochemistry and Molecular Biophysics, Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA
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16
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Zhai R, Ruan K, Perez GF, Kubat M, Liu J, Hofacker I, Wuchty S. MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS): a global mechanism for the regulation of alternative splicing. RESEARCH SQUARE 2023:rs.3.rs-2977025. [PMID: 37546804 PMCID: PMC10402249 DOI: 10.21203/rs.3.rs-2977025/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
While RNA secondary structures are critical to regulate alternative splicing of long-range pre-mRNA, the factors that modulate RNA structure and interfere with the recognition of the splice sites are largely unknown. Previously, we identified a small, non-coding microRNA that sufficiently affects stable stem structure formation of Nmnat pre-mRNA to regulate the outcomes of alternative splicing. However, the fundamental question remains whether such microRNA-mediated interference with RNA secondary structures is a global molecular mechanism for regulating mRNA splicing. We designed and refined a bioinformatic pipeline to predict candidate microRNAs that potentially interfere with pre-mRNA stem-loop structures, and experimentally verified splicing predictions of three different long-range pre-mRNAs in the Drosophila model system. Specifically, we observed that microRNAs can either disrupt or stabilize stem-loop structures to influence splicing outcomes. Our study suggests that MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS) is a novel regulatory mechanism for the transcriptome-wide regulation of alternative splicing, increases the repertoire of microRNA function and further indicates cellular complexity of post-transcriptional regulation.
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Affiliation(s)
| | - Kai Ruan
- University of Miami, Miller School of Medicine
| | | | | | - Jiaqi Liu
- University of Miami Miller School of Medicine
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17
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Ruan K, Perez GF, Liu J, Kubat M, Hofacker I, Wuchty S, Zhai RG. MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS): a global mechanism for the regulation of alternative splicing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.14.536877. [PMID: 37425843 PMCID: PMC10327045 DOI: 10.1101/2023.04.14.536877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
While RNA secondary structures are critical to regulate alternative splicing of long-range pre-mRNA, the factors that modulate RNA structure and interfere with the recognition of the splice sites are largely unknown. Previously, we identified a small, non-coding microRNA that sufficiently affects stable stem structure formation of Nmnat pre-mRNA to regulate the outcomes of alternative splicing. However, the fundamental question remains whether such microRNA-mediated interference with RNA secondary structures is a global molecular mechanism for regulating mRNA splicing. We designed and refined a bioinformatic pipeline to predict candidate microRNAs that potentially interfere with pre-mRNA stem-loop structures, and experimentally verified splicing predictions of three different long-range pre-mRNAs in the Drosophila model system. Specifically, we observed that microRNAs can either disrupt or stabilize stem-loop structures to influence splicing outcomes. Our study suggests that MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS) is a novel regulatory mechanism for the transcriptome-wide regulation of alternative splicing, increases the repertoire of microRNA function and further indicates cellular complexity of post-transcriptional regulation. One-Sentence Summary MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS) is a novel regulatory mechanism for the transcriptome-wide regulation of alternative splicing.
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18
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Naing YT, Sun L. The Role of Splicing Factors in Adipogenesis and Thermogenesis. Mol Cells 2023; 46:268-277. [PMID: 37170770 PMCID: PMC10183792 DOI: 10.14348/molcells.2023.2195] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/27/2023] [Accepted: 03/03/2023] [Indexed: 05/13/2023] Open
Abstract
Obesity is a significant global health risk that can cause a range of serious metabolic problems, such as type 2 diabetes and cardiovascular diseases. Adipose tissue plays a pivotal role in regulating energy and lipid storage. New research has underlined the crucial role of splicing factors in the physiological and functional regulation of adipose tissue. By generating multiple transcripts from a single gene, alternative splicing allows for a greater diversity of the proteome and transcriptome, which subsequently influence adipocyte development and metabolism. In this review, we provide an outlook on the part of splicing factors in adipogenesis and thermogenesis, and investigate how the different spliced isoforms can affect the development and function of adipose tissue.
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Affiliation(s)
- Yadanar Than Naing
- Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore 169857
| | - Lei Sun
- Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore 169857
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19
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Sullivan PJ, Gayevskiy V, Davis RL, Wong M, Mayoh C, Mallawaarachchi A, Hort Y, McCabe MJ, Beecroft S, Jackson MR, Arts P, Dubowsky A, Laing N, Dinger ME, Scott HS, Oates E, Pinese M, Cowley MJ. Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications. Genome Biol 2023; 24:118. [PMID: 37198692 PMCID: PMC10190034 DOI: 10.1186/s13059-023-02936-7] [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: 03/30/2022] [Accepted: 04/10/2023] [Indexed: 05/19/2023] Open
Abstract
Predicting the impact of coding and noncoding variants on splicing is challenging, particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at https://github.com/CCICB/introme .
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Affiliation(s)
- Patricia J Sullivan
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia
- University of New South Wales Centre for Childhood Cancer Research, UNSW Sydney, Sydney, NSW, Australia
| | - Velimir Gayevskiy
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, Australia
| | - Ryan L Davis
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, Australia
- Department of Neurogenetics, Kolling Institute, St. Leonards, NSW, Australia
- Sydney Medical School-Northern, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Marie Wong
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia
| | - Chelsea Mayoh
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia
| | - Amali Mallawaarachchi
- Division of Genomics and Epigenetics, Garvan Institute of Medical Research, Sydney, Australia
- Clinical Genetics Unit, Institute of Precision Medicine and Bioinformatics, Sydney Local Health District, Sydney, Australia
| | - Yvonne Hort
- Division of Genomics and Epigenetics, Garvan Institute of Medical Research, Sydney, Australia
| | - Mark J McCabe
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, Australia
| | - Sarah Beecroft
- Centre for Medical Research, University of Western Australia, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia
| | - Matilda R Jackson
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, An Alliance Between SA Pathology and the University of South Australia, Adelaide, Australia
- Australian Genomics, Parkville, VIC, Australia
| | - Peer Arts
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, An Alliance Between SA Pathology and the University of South Australia, Adelaide, Australia
| | - Andrew Dubowsky
- Department of Genetics and Molecular Pathology, SA Pathology, Adelaide, Australia
| | - Nigel Laing
- Centre for Medical Research, University of Western Australia, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia
| | - Marcel E Dinger
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, Australia
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Hamish S Scott
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, An Alliance Between SA Pathology and the University of South Australia, Adelaide, Australia
- Australian Genomics, Parkville, VIC, Australia
- School of Medicine, University of Adelaide, Adelaide, SA, Australia
- ACRF Cancer Genomics Facility, Centre for Cancer Biology, An Alliance Between SA Pathology and the University of South Australia, Adelaide, SA, Australia
| | - Emily Oates
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Mark Pinese
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia
| | - Mark J Cowley
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia.
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia.
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20
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Smith C, Kitzman JO. Benchmarking splice variant prediction algorithms using massively parallel splicing assays. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.04.539398. [PMID: 37205456 PMCID: PMC10187268 DOI: 10.1101/2023.05.04.539398] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes. Results We benchmarked eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compared experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, was lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieved the best overall performance at distinguishing disruptive and neutral variants. Controlling for overall call rate genome-wide, SpliceAI and Pangolin also showed superior overall sensitivity for identifying SDVs. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues. Conclusion SpliceAI and Pangolin showed the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.
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Affiliation(s)
- Cathy Smith
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Jacob O. Kitzman
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
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21
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Bartosch AMW, Youth EHH, Hansen S, Kaufman ME, Xiao H, Koo SY, Ashok A, Sivakumar S, Soni RK, Dumitrescu LC, Lam TG, Ropri AS, Lee AJ, Klein HU, Vardarajan BN, Bennett DA, Young-Pearse TL, De Jager PL, Hohman TJ, Sproul AA, Teich AF. ZCCHC17 modulates neuronal RNA splicing and supports cognitive resilience in Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.21.533654. [PMID: 36993746 PMCID: PMC10055234 DOI: 10.1101/2023.03.21.533654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's Disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis. Co-immunoprecipitation of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA splicing proteins. ZCCHC17 knockdown results in widespread RNA splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4 dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.
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Affiliation(s)
- Anne Marie W. Bartosch
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Elliot H. H. Youth
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Shania Hansen
- Vanderbilt Memory & Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Maria E. Kaufman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Harrison Xiao
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - So Yeon Koo
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Archana Ashok
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Sharanya Sivakumar
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Rajesh K. Soni
- Proteomics and Macromolecular Crystallography Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, NY 10032
| | - Logan C. Dumitrescu
- Vanderbilt Memory & Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Tiffany G. Lam
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Ali S. Ropri
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Annie J. Lee
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY 10032
| | - Hans-Ulrich Klein
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY 10032
| | - Badri N. Vardarajan
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
- Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY 10032
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL 60612
| | - Tracy L. Young-Pearse
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138
| | - Philip L. De Jager
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY 10032
| | - Timothy J. Hohman
- Vanderbilt Memory & Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Andrew A. Sproul
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
| | - Andrew F. Teich
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032
- Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY 10032
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22
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Barbosa P, Savisaar R, Carmo-Fonseca M, Fonseca A. Computational prediction of human deep intronic variation. Gigascience 2022; 12:giad085. [PMID: 37878682 PMCID: PMC10599398 DOI: 10.1093/gigascience/giad085] [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: 02/21/2023] [Revised: 06/07/2023] [Accepted: 09/20/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND The adoption of whole-genome sequencing in genetic screens has facilitated the detection of genetic variation in the intronic regions of genes, far from annotated splice sites. However, selecting an appropriate computational tool to discriminate functionally relevant genetic variants from those with no effect is challenging, particularly for deep intronic regions where independent benchmarks are scarce. RESULTS In this study, we have provided an overview of the computational methods available and the extent to which they can be used to analyze deep intronic variation. We leveraged diverse datasets to extensively evaluate tool performance across different intronic regions, distinguishing between variants that are expected to disrupt splicing through different molecular mechanisms. Notably, we compared the performance of SpliceAI, a widely used sequence-based deep learning model, with that of more recent methods that extend its original implementation. We observed considerable differences in tool performance depending on the region considered, with variants generating cryptic splice sites being better predicted than those that potentially affect splicing regulatory elements. Finally, we devised a novel quantitative assessment of tool interpretability and found that tools providing mechanistic explanations of their predictions are often correct with respect to the ground - information, but the use of these tools results in decreased predictive power when compared to black box methods. CONCLUSIONS Our findings translate into practical recommendations for tool usage and provide a reference framework for applying prediction tools in deep intronic regions, enabling more informed decision-making by practitioners.
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Affiliation(s)
- Pedro Barbosa
- LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, 1749-016,, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028, Lisboa, Portugal
| | | | - Maria Carmo-Fonseca
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028, Lisboa, Portugal
| | - Alcides Fonseca
- LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, 1749-016,, Lisboa, Portugal
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23
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Segarra-Casas A, Domínguez-González C, Hernández-Laín A, Sanchez-Calvin MT, Camacho A, Rivas E, Campo-Barasoain A, Madruga M, Ortez C, Natera-de Benito D, Nascimento A, Codina A, Rodriguez MJ, Gallano P, Gonzalez-Quereda L. Genetic diagnosis of Duchenne and Becker muscular dystrophy through mRNA analysis: new splicing events. J Med Genet 2022; 60:615-619. [DOI: 10.1136/jmg-2022-108828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/27/2022] [Indexed: 12/24/2022]
Abstract
BackgroundUp to 7% of patients with Duchenne muscular dystrophy (DMD) or Becker muscular dystrophy (BMD) remain genetically undiagnosed after routine genetic testing. These patients are thought to carry deep intronic variants, structural variants or splicing alterations not detected through multiplex ligation-dependent probe amplification or exome sequencing.MethodsRNA was extracted from seven muscle biopsy samples of patients with genetically undiagnosed DMD/BMD after routine genetic diagnosis. RT-PCR of theDMDgene was performed to detect the presence of alternative transcripts. Droplet digital PCR and whole-genome sequencing were also performed in some patients.ResultsWe identified an alteration in the mRNA level in all the patients. We detected three pseudoexons inDMDcaused by deep intronic variants, two of them not previously reported. We also identified a chromosomal rearrangement between Xp21.2 and 8p22. Furthermore, we detected three exon skipping events with unclear pathogenicity.ConclusionThese findings indicate that mRNA analysis of theDMDgene is a valuable tool to reach a precise genetic diagnosis in patients with a clinical and anatomopathological suspicion of dystrophinopathy that remain genetically undiagnosed after routine genetic testing.
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24
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Cormier MJ, Pedersen BS, Bayrak-Toydemir P, Quinlan AR. Combining genetic constraint with predictions of alternative splicing to prioritize deleterious splicing in rare disease studies. BMC Bioinformatics 2022; 23:482. [PMCID: PMC9664736 DOI: 10.1186/s12859-022-05041-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022] Open
Abstract
Abstract
Background
Despite numerous molecular and computational advances, roughly half of patients with a rare disease remain undiagnosed after exome or genome sequencing. A particularly challenging barrier to diagnosis is identifying variants that cause deleterious alternative splicing at intronic or exonic loci outside of canonical donor or acceptor splice sites.
Results
Several existing tools predict the likelihood that a genetic variant causes alternative splicing. We sought to extend such methods by developing a new metric that aids in discerning whether a genetic variant leads to deleterious alternative splicing. Our metric combines genetic variation in the Genome Aggregate Database with alternative splicing predictions from SpliceAI to compare observed and expected levels of splice-altering genetic variation. We infer genic regions with significantly less splice-altering variation than expected to be constrained. The resulting model of regional splicing constraint captures differential splicing constraint across gene and exon categories, and the most constrained genic regions are enriched for pathogenic splice-altering variants. Building from this model, we developed ConSpliceML. This ensemble machine learning approach combines regional splicing constraint with multiple per-nucleotide alternative splicing scores to guide the prediction of deleterious splicing variants in protein-coding genes. ConSpliceML more accurately distinguishes deleterious and benign splicing variants than state-of-the-art splicing prediction methods, especially in “cryptic” splicing regions beyond canonical donor or acceptor splice sites.
Conclusion
Integrating a model of genetic constraint with annotations from existing alternative splicing tools allows ConSpliceML to prioritize potentially deleterious splice-altering variants in studies of rare human diseases.
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25
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Mechanism and modeling of human disease-associated near-exon intronic variants that perturb RNA splicing. Nat Struct Mol Biol 2022; 29:1043-1055. [PMID: 36303034 DOI: 10.1038/s41594-022-00844-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 08/23/2022] [Indexed: 12/24/2022]
Abstract
It is estimated that 10%-30% of disease-associated genetic variants affect splicing. Splicing variants may generate deleteriously altered gene product and are potential therapeutic targets. However, systematic diagnosis or prediction of splicing variants is yet to be established, especially for the near-exon intronic splice region. The major challenge lies in the redundant and ill-defined branch sites and other splicing motifs therein. Here, we carried out unbiased massively parallel splicing assays on 5,307 disease-associated variants that overlapped with branch sites and collected 5,884 variants across the 5' splice region. We found that strong splice sites and exonic features preserve splicing from intronic sequence variation. Whereas the splice-altering mechanism of the 3' intronic variants is complex, that of the 5' is mainly splice-site destruction. Statistical learning combined with these molecular features allows precise prediction of altered splicing from an intronic variant. This statistical model provides the identity and ranking of biological features that determine splicing, which serves as transferable knowledge and out-performs the benchmarking predictive tool. Moreover, we demonstrated that intronic splicing variants may associate with disease risks in the human population. Our study elucidates the mechanism of splicing response of intronic variants, which classify disease-associated splicing variants for the promise of precision medicine.
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26
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Borišek J, Aupič J, Magistrato A. Establishing the catalytic and regulatory mechanism of
RNA
‐based machineries. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Jure Borišek
- Theory Department National Institute of Chemistry Ljubljana Slovenia
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27
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Rozza R, Janoš P, Spinello A, Magistrato A. Role of computational and structural biology in the development of small-molecule modulators of the spliceosome. Expert Opin Drug Discov 2022; 17:1095-1109. [PMID: 35983696 DOI: 10.1080/17460441.2022.2114452] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
INTRODUCTION RNA splicing is a pivotal step of eukaryotic gene expression during which the introns are excised from the precursor (pre-)RNA and the exons are joined together to form mature RNA products (i.e a protein-coding mRNA or long non-coding (lnc)RNAs). The spliceosome, a complex ribonucleoprotein machine, performs pre-RNA splicing with extreme precision. Deregulated splicing is linked to cancer, genetic, and neurodegenerative diseases. Hence, the discovery of small-molecules targeting core spliceosome components represents an appealing therapeutic opportunity. AREA COVERED Several atomic-level structures of the spliceosome and distinct splicing-modulators bound to its protein/RNA components have been solved. Here, we review recent advances in the discovery of small-molecule splicing-modulators, discuss opportunities and challenges for their therapeutic applicability, and showcase how structural data and/or all-atom simulations can illuminate key facets of their mechanism, thus contributing to future drug-discovery campaigns. EXPERT OPINION This review highlights the potential of modulating pre-RNA splicing with small-molecules, and anticipates how the synergy of computer and wet-lab experiments will enrich our understanding of splicing regulation/deregulation mechanisms. This information will aid future structure-based drug-discovery efforts aimed to expand the currently limited portfolio of selective splicing-modulators.
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Affiliation(s)
- Riccardo Rozza
- National Research Council of Italy, Institute of Materials-foundry (CNR-IOM) C/o SISSA, Trieste, Italy
| | - Pavel Janoš
- National Research Council of Italy, Institute of Materials-foundry (CNR-IOM) C/o SISSA, Trieste, Italy
| | - Angelo Spinello
- Department of Biological, Chemical and Pharmaceutical Sciences, University of Palermo, Palermo, Italy
| | - Alessandra Magistrato
- National Research Council of Italy, Institute of Materials-foundry (CNR-IOM) C/o SISSA, Trieste, Italy
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28
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Siebert AE, Corll J, Paige Gronevelt J, Levine L, Hobbs LM, Kenney C, Powell CLE, Battistuzzi FU, Davenport R, Mark Settles A, Brad Barbazuk W, Westrick RJ, Madlambayan GJ, Lal S. Genetic analysis of human RNA binding motif protein 48 (RBM48) reveals an essential role in U12-type intron splicing. Genetics 2022; 222:iyac129. [PMID: 36040194 PMCID: PMC9526058 DOI: 10.1093/genetics/iyac129] [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: 05/13/2022] [Accepted: 08/17/2022] [Indexed: 11/13/2022] Open
Abstract
U12-type or minor introns are found in most multicellular eukaryotes and constitute ∼0.5% of all introns in species with a minor spliceosome. Although the biological significance for the evolutionary conservation of U12-type introns is debated, mutations disrupting U12 splicing cause developmental defects in both plants and animals. In human hematopoietic stem cells, U12 splicing defects disrupt proper differentiation of myeloid lineages and are associated with myelodysplastic syndrome, predisposing individuals to acute myeloid leukemia. Mutants in the maize ortholog of RNA binding motif protein 48 (RBM48) have aberrant U12-type intron splicing. Human RBM48 was recently purified biochemically as part of the minor spliceosome and shown to recognize the 5' end of the U6atac snRNA. In this report, we use CRISPR/Cas9-mediated ablation of RBM48 in human K-562 cells to show the genetic function of RBM48. RNA-seq analysis comparing wild-type and mutant K-562 genotypes found that 48% of minor intron-containing genes have significant U12-type intron retention in RBM48 mutants. Comparing these results to maize rbm48 mutants defined a subset of minor intron-containing genes disrupted in both species. Mutations in the majority of these orthologous minor intron-containing genes have been reported to cause developmental defects in both plants and animals. Our results provide genetic evidence that the primary defect of human RBM48 mutants is aberrant U12-type intron splicing, while a comparison of human and maize RNA-seq data identifies candidate genes likely to mediate mutant phenotypes of U12-type splicing defects.
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Affiliation(s)
- Amy E Siebert
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Jacob Corll
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - J Paige Gronevelt
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Laurel Levine
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Linzi M Hobbs
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Catalina Kenney
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Christopher L E Powell
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Fabia U Battistuzzi
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Ruth Davenport
- Department of Biology and Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - A Mark Settles
- Horticultural Sciences Department and Plant Molecular and Cellular Biology Program, University of Florida, Gainesville, FL 32611, USA
| | - W Brad Barbazuk
- Department of Biology and Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Randal J Westrick
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Gerard J Madlambayan
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
| | - Shailesh Lal
- Department of Biological Sciences, Oakland University, Rochester Hills, MI 48309, USA
- Department of Bioengineering, Oakland University, Rochester Hills, MI 48309, USA
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29
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Li K, Luo T, Zhu Y, Huang Y, Wang A, Zhang D, Dong L, Wang Y, Wang R, Tang D, Yu Z, Shen Q, Lv M, Ling Z, Fang Z, Yuan J, Li B, Xia K, He X, Li J, Zhao G. Performance evaluation of differential splicing analysis methods and splicing analytics platform construction. Nucleic Acids Res 2022; 50:9115-9126. [PMID: 35993808 PMCID: PMC9458456 DOI: 10.1093/nar/gkac686] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 07/01/2022] [Accepted: 08/01/2022] [Indexed: 12/24/2022] Open
Abstract
A proportion of previously defined benign variants or variants of uncertain significance in humans, which are challenging to identify, may induce an abnormal splicing process. An increasing number of methods have been developed to predict splicing variants, but their performance has not been completely evaluated using independent benchmarks. Here, we manually sourced ∼50 000 positive/negative splicing variants from > 8000 studies and selected the independent splicing variants to evaluate the performance of prediction methods. These methods showed different performances in recognizing splicing variants in donor and acceptor regions, reminiscent of different weight coefficient applications to predict novel splicing variants. Of these methods, 66.67% exhibited higher specificities than sensitivities, suggesting that more moderate cut-off values are necessary to distinguish splicing variants. Moreover, the high correlation and consistent prediction ratio validated the feasibility of integration of the splicing prediction method in identifying splicing variants. We developed a splicing analytics platform called SPCards, which curates splicing variants from publications and predicts splicing scores of variants in genomes. SPCards also offers variant-level and gene-level annotation information, including allele frequency, non-synonymous prediction and comprehensive functional information. SPCards is suitable for high-throughput genetic identification of splicing variants, particularly those located in non-canonical splicing regions.
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Affiliation(s)
| | | | - Yan Zhu
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Yuanfeng Huang
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders & Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - An Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Di Zhang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Lijie Dong
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Yujian Wang
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders & Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Rui Wang
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Dongdong Tang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Zhen Yu
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Qunshan Shen
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Mingrong Lv
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Zhengbao Ling
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Zhenghuan Fang
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Jing Yuan
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), No 81 Meishan Road, Hefei 230032, Anhui, China,Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Bin Li
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders & Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Kun Xia
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China,Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Xiaojin He
- Correspondence may also be addressed to Xiaojin He. Tel: +86 731 8975 2406; Fax: +86 731 8432 7332;
| | - Jinchen Li
- To whom correspondence should be addressed. Tel: +86 731 8975 2406; Fax: +86 731 8432 7332;
| | - Guihu Zhao
- Correspondence may also be addressed to Guihu Zhao. Tel: +86 731 8975 2406; Fax: +86 731 8432 7332;
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30
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Müller L, Ptok J, Nisar A, Antemann J, Grothmann R, Hillebrand F, Brillen AL, Ritchie A, Theiss S, Schaal H. Modeling splicing outcome by combining 5'ss strength and splicing regulatory elements. Nucleic Acids Res 2022; 50:8834-8851. [PMID: 35947702 PMCID: PMC9410876 DOI: 10.1093/nar/gkac663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 06/23/2022] [Accepted: 07/27/2022] [Indexed: 12/24/2022] Open
Abstract
Correct pre-mRNA processing in higher eukaryotes vastly depends on splice site recognition. Beyond conserved 5'ss and 3'ss motifs, splicing regulatory elements (SREs) play a pivotal role in this recognition process. Here, we present in silico designed sequences with arbitrary a priori prescribed splicing regulatory HEXplorer properties that can be concatenated to arbitrary length without changing their regulatory properties. We experimentally validated in silico predictions in a massively parallel splicing reporter assay on more than 3000 sequences and exemplarily identified some SRE binding proteins. Aiming at a unified 'functional splice site strength' encompassing both U1 snRNA complementarity and impact from neighboring SREs, we developed a novel RNA-seq based 5'ss usage landscape, mapping the competition of pairs of high confidence 5'ss and neighboring exonic GT sites along HBond and HEXplorer score coordinate axes on human fibroblast and endothelium transcriptome datasets. These RNA-seq data served as basis for a logistic 5'ss usage prediction model, which greatly improved discrimination between strong but unused exonic GT sites and annotated highly used 5'ss. Our 5'ss usage landscape offers a unified view on 5'ss and SRE neighborhood impact on splice site recognition, and may contribute to improved mutation assessment in human genetics.
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Affiliation(s)
| | | | - Azlan Nisar
- Institute of Virology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany,Institute for Bioinformatics and Chemoinformatics, Westphalian University of Applied Sciences, August-Schmidt-Ring 10, Recklinghausen 45665, Germany
| | - Jennifer Antemann
- Institute of Virology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Ramona Grothmann
- Institute of Virology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Frank Hillebrand
- Institute of Virology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Anna-Lena Brillen
- Institute of Virology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Anastasia Ritchie
- Institute of Virology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | | | - Heiner Schaal
- To whom correspondence should be addressed. Tel: +49 211 81 12393; Fax: +49 211 81 10856;
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31
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Zheng Y, Li X, Jiao Y, Wu C. High-Risk Human Papillomavirus Oncogenic E6/E7 mRNAs Splicing Regulation. Front Cell Infect Microbiol 2022; 12:929666. [PMID: 35832386 PMCID: PMC9271614 DOI: 10.3389/fcimb.2022.929666] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 05/19/2022] [Indexed: 11/22/2022] Open
Abstract
High-risk human papillomavirus infection may develop into a persistent infection that is highly related to the progression of various cancers, including cervical cancer and head and neck squamous cell carcinomas. The most common high-risk subtypes are HPV16 and HPV18. The oncogenic viral proteins expressed by high-risk HPVs E6/E7 are tightly involved in cell proliferation, differentiation, and cancerous transformation since E6/E7 mRNAs are derived from the same pre-mRNA. Hence, the alternative splicing in the E6/E7-coding region affects the balance of the E6/E7 expression level. Interrupting the balance of E6 and E7 levels results in cell apoptosis. Therefore, it is crucial to understand the regulation of E6/E7 splice site selection and the interaction of splicing enhancers and silencers with cellular splicing factors. In this review, we concluded the relationship of different E6/E7 transcripts with cancer progression, the known splicing sites, and the identified cis-regulatory elements within high-risk HPV E6/E7-coding region. Finally, we also reviewed the role of various splicing factors in the regulation of high-risk HPV oncogenic E6/E7 mRNA splicing.
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Affiliation(s)
- Yunji Zheng
- School of Pharmacy, Binzhou Medical University, Yantai, China
| | - Xue Li
- School of Pharmacy, Binzhou Medical University, Yantai, China
| | - Yisheng Jiao
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
| | - Chengjun Wu
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
- *Correspondence: Chengjun Wu,
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32
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Anderson SL, Fasih-Ahmad F, Evans AJ, Rubin BY. Carnosol, a diterpene present in rosemary, increases ELP1 levels in familial Dysautonomia (FD) patient-derived cells and healthy adults: a possible therapy for FD. Hum Mol Genet 2022; 31:3521-3538. [PMID: 35708500 DOI: 10.1093/hmg/ddac133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/12/2022] [Accepted: 06/01/2022] [Indexed: 11/13/2022] Open
Abstract
Recent research on Familial Dysautonomia (FD) has focused on the development of therapeutics that facilitate the production of the correctly spliced, exon 20-containing, transcript in cells and individuals bearing the splice-altering, FD-causing, mutation in the ELP1 gene. We report here the ability of carnosol, a diterpene present in plant species of the Lamiaceae family, including rosemary, to enhance the cellular presence of the correctly spliced ELP1 transcript in FD patient-derived fibroblasts by upregulating transcription of the ELP1 gene and correcting the aberrant splicing of the ELP1 transcript. Carnosol treatment also elevates the level of the RBM24 and RBM38 proteins., two multifunctional RNA binding proteins. Transfection-mediated expression of either of these RBMs facilitates the inclusion of exon 20 sequence into the transcript generated from a minigene bearing ELP1 genomic sequence containing the FD-causing mutation. Suppression of the carnosol-mediated induction of either of these RBMs, using targeting siRNAs, limited the carnosol-mediated inclusion of the ELP1 exon 20 sequence. Carnosol treatment of FD patient PBMCs facilitates the inclusion of exon 20 into the ELP1 transcript. Increased levels of the ELP1 and RBM38 transcripts and the alternative splicing of the SIRT2 transcript, a sentinel for exon 20 inclusion in the FD-derived ELP1 transcript, are observed in RNA isolated from whole blood of healthy adults following the ingestion of carnosol-containing rosemary extract. These findings and the excellent safety profile of rosemary together justify an expedited clinical study of the impact of carnosol on the FD patient population.
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Affiliation(s)
- Sylvia L Anderson
- Laboratory for Familial Dysautonomia Research, Department of Biological Sciences, Fordham University, Bronx, NY 10458, USA
| | - Faaria Fasih-Ahmad
- Laboratory for Familial Dysautonomia Research, Department of Biological Sciences, Fordham University, Bronx, NY 10458, USA
| | - Anthony J Evans
- Laboratory for Familial Dysautonomia Research, Department of Biological Sciences, Fordham University, Bronx, NY 10458, USA
| | - Berish Y Rubin
- Laboratory for Familial Dysautonomia Research, Department of Biological Sciences, Fordham University, Bronx, NY 10458, USA
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33
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Therapeutic RNA-silencing oligonucleotides in metabolic diseases. Nat Rev Drug Discov 2022; 21:417-439. [PMID: 35210608 DOI: 10.1038/s41573-022-00407-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/19/2022] [Indexed: 12/14/2022]
Abstract
Recent years have seen unprecedented activity in the development of RNA-silencing oligonucleotide therapeutics for metabolic diseases. Improved oligonucleotide design and optimization of synthetic nucleic acid chemistry, in combination with the development of highly selective and efficient conjugate delivery technology platforms, have established and validated oligonucleotides as a new class of drugs. To date, there are five marketed oligonucleotide therapies, with many more in clinical studies, for both rare and common liver-driven metabolic diseases. Here, we provide an overview of recent developments in the field of oligonucleotide therapeutics in metabolism, review past and current clinical trials, and discuss ongoing challenges and possible future developments.
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34
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Garay-García K, Gaete PV, Mendivil CO. Severe hypertriglyceridemia secondary to splice-site and missense variants in LMF1 in three patients from Ecuador. J Clin Lipidol 2022; 16:277-280. [DOI: 10.1016/j.jacl.2022.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/07/2022] [Accepted: 02/14/2022] [Indexed: 12/20/2022]
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35
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Li J, Wang P, Zhang C, Han S, Xiao H, Liu Z, Wang X, Liu W, Wei B, Ma J, Li H, Guo Y. Characterization of Synonymous BRCA1:c.132C>T as a Pathogenic Variant. Front Oncol 2022; 11:812656. [PMID: 35087763 PMCID: PMC8789006 DOI: 10.3389/fonc.2021.812656] [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: 11/10/2021] [Accepted: 12/08/2021] [Indexed: 11/26/2022] Open
Abstract
Breast cancer gene 1 (BRCA1) and BRCA2 are tumor suppressors involved in DNA damage response and repair. Carriers of germline pathogenic or likely pathogenic variants in BRCA1 or BRCA2 have significantly increased lifetime risks of breast cancer, ovarian cancer, and other cancer types; this phenomenon is known as hereditary breast and ovarian cancer (HBOC) syndrome. Accurate interpretation of BRCA1 and BRCA2 variants is important not only for disease management in patients, but also for determining preventative measures for their families. BRCA1:c.132C>T (p.Cys44=) is a synonymous variant recorded in the ClinVar database with “conflicting interpretations of its pathogenicity”. Here, we report our clinical tests in which we identified this variant in two unrelated patients, both of whom developed breast cancer at an early age with ovarian presentation a few years later and had a family history of relevant cancers. Minigene assay showed that this change caused a four-nucleotide loss at the end of exon 3, resulting in a truncated p.Cys44Tyrfs*5 protein. Reverse transcription-polymerase chain reaction identified two fragments (123 and 119 bp) using RNA isolated from patient blood samples, in consistency with the results of the minigene assay. Collectively, we classified BRCA1:c.132C>T (p.Cys44=) as a pathogenic variant, as evidenced by functional studies, RNA analysis, and the patients’ family histories. By analyzing variants recorded in the BRCA Exchange database, we found synonymous changes at the ends of exons could potentially influence splicing; meanwhile, current in silico tools could not predict splicing changes efficiently if the variants were in the middle of an exon, or in the deep intron region. Future studies should attempt to identify variants that influence gene expression and post-transcription modifications to improve our understanding of BRCA1 and BRCA2, as well as their related cancers.
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Affiliation(s)
- Jun Li
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.,Henan Key Laboratory of Molecular Pathology, Zhengzhou, China.,Henan International Joint Laboratory of Cancer Genetics, Zhengzhou, China
| | - Ping Wang
- Department of Pathophysiology, School of Basic Medical Science, Zhengzhou University, Zhengzhou, China
| | - Cuiyun Zhang
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.,Henan Key Laboratory of Molecular Pathology, Zhengzhou, China.,Henan International Joint Laboratory of Cancer Genetics, Zhengzhou, China
| | - Sile Han
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Han Xiao
- Department of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhiyuan Liu
- Amoy Diagnostics Co., Ltd. (AmoyDx), Xiamen, China
| | - Xiaoyan Wang
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.,Henan Key Laboratory of Molecular Pathology, Zhengzhou, China.,Henan International Joint Laboratory of Cancer Genetics, Zhengzhou, China
| | - Weiling Liu
- Department of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzou, China
| | - Bing Wei
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.,Henan Key Laboratory of Molecular Pathology, Zhengzhou, China.,Henan International Joint Laboratory of Cancer Genetics, Zhengzhou, China
| | - Jie Ma
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.,Henan Key Laboratory of Molecular Pathology, Zhengzhou, China.,Henan International Joint Laboratory of Cancer Genetics, Zhengzhou, China
| | - Hongle Li
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Yongjun Guo
- Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.,Henan Key Laboratory of Molecular Pathology, Zhengzhou, China.,Henan International Joint Laboratory of Cancer Genetics, Zhengzhou, China
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36
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López-Márquez A, Martínez-Pizarro A, Pérez B, Richard E, Desviat LR. Modeling Splicing Variants Amenable to Antisense Therapy by Use of CRISPR-Cas9-Based Gene Editing in HepG2 Cells. Methods Mol Biol 2022; 2434:167-184. [PMID: 35213016 PMCID: PMC9703257 DOI: 10.1007/978-1-0716-2010-6_10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
The field of splice modulating RNA therapy has gained new momentum with FDA approved antisense-based drugs for several rare diseases. In vitro splicing assays with minigenes or patient-derived cells are commonly employed for initial preclinical testing of antisense oligonucleotides aiming to modulate splicing. However, minigenes do not include the full genomic context of the exons under study and patients' samples are not always available, especially if the gene is expressed solely in certain tissues (e.g. liver or brain). This is the case for specific inherited metabolic diseases such as phenylketonuria (PKU) caused by mutations in the liver-expressed PAH gene.Herein we describe the generation of mutation-specific hepatic cellular models of PKU using CRISPR/Cas9 system, which is a versatile and easy-to-use gene editing tool. We describe in detail the selection of the appropriate cell line, guidelines for design of RNA guides and donor templates, transfection procedures and growth and selection of single-cell colonies with the desired variant , which should result in the accurate recapitulation of the splicing defect.
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Affiliation(s)
- Arístides López-Márquez
- Centro de Biología Molecular Severo Ochoa CSIC-UAM, CEDEM, CIBERER (ISCIII), IdiPaz (ISCIII), Universidad Autónoma de Madrid, Madrid, Spain
| | - Ainhoa Martínez-Pizarro
- Centro de Biología Molecular Severo Ochoa CSIC-UAM, CEDEM, CIBERER (ISCIII), IdiPaz (ISCIII), Universidad Autónoma de Madrid, Madrid, Spain
| | - Belén Pérez
- Centro de Biología Molecular Severo Ochoa CSIC-UAM, CEDEM, CIBERER (ISCIII), IdiPaz (ISCIII), Universidad Autónoma de Madrid, Madrid, Spain
| | - Eva Richard
- Centro de Biología Molecular Severo Ochoa CSIC-UAM, CEDEM, CIBERER (ISCIII), IdiPaz (ISCIII), Universidad Autónoma de Madrid, Madrid, Spain
| | - Lourdes R Desviat
- Centro de Biología Molecular Severo Ochoa CSIC-UAM, CEDEM, CIBERER (ISCIII), IdiPaz (ISCIII), Universidad Autónoma de Madrid, Madrid, Spain.
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37
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Jüschke C, Klopstock T, Catarino CB, Owczarek-Lipska M, Wissinger B, Neidhardt J. Autosomal dominant optic atrophy: A novel treatment for OPA1 splice defects using U1 snRNA adaption. MOLECULAR THERAPY. NUCLEIC ACIDS 2021; 26:1186-1197. [PMID: 34853716 PMCID: PMC8604756 DOI: 10.1016/j.omtn.2021.10.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 06/03/2021] [Accepted: 10/19/2021] [Indexed: 11/15/2022]
Abstract
Autosomal dominant optic atrophy (ADOA) is frequently caused by mutations in the optic atrophy 1 (OPA1) gene, with haploinsufficiency being the major genetic pathomechanism. Almost 30% of the OPA1-associated cases suffer from splice defects. We identified a novel OPA1 mutation, c.1065+5G>A, in patients with ADOA. In patient-derived fibroblasts, the mutation led to skipping of OPA1 exon 10, reducing the OPA1 protein expression by approximately 50%. We developed a molecular treatment to correct the splice defect in OPA1 using engineered U1 splice factors retargeted to different locations in OPA1 exon 10 or intron 10. The strongest therapeutic effect was detected when U1 binding was engineered to bind to intron 10 at position +18, a position predicted by bioinformatics to be a promising binding site. We were able to significantly silence the effect of the mutation (skipping of exon 10) and simultaneously increase the expression level of normal transcripts. Retargeting U1 to the canonical splice donor site did not lead to a detectable splice correction. This proof-of-concept study indicates for the first time the feasibility of splice mutation correction as a treatment option for ADOA. Increasing the amount of correctly spliced OPA1 transcripts may suffice to overcome the haploinsufficiency.
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Affiliation(s)
- Christoph Jüschke
- Human Genetics, Faculty of Medicine and Health Sciences, University of Oldenburg, 26129 Oldenburg, Germany
| | - Thomas Klopstock
- Friedrich-Baur Institute, Department of Neurology, University Hospital, LMU Munich, University of Munich, 80336 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
| | - Claudia B. Catarino
- Friedrich-Baur Institute, Department of Neurology, University Hospital, LMU Munich, University of Munich, 80336 Munich, Germany
| | - Marta Owczarek-Lipska
- Human Genetics, Faculty of Medicine and Health Sciences, University of Oldenburg, 26129 Oldenburg, Germany
- Research Center Neurosensory Science, University of Oldenburg, 26129 Oldenburg, Germany
| | - Bernd Wissinger
- Institute for Ophthalmic Research, Center for Ophthalmology, University of Tübingen, 72076 Tübingen, Germany
| | - John Neidhardt
- Human Genetics, Faculty of Medicine and Health Sciences, University of Oldenburg, 26129 Oldenburg, Germany
- Research Center Neurosensory Science, University of Oldenburg, 26129 Oldenburg, Germany
- Joint Research Training Group of the Faculty of Medicine and Health Sciences, University of Oldenburg, 26129 Oldenburg, Germany and University Medical Center Groningen, 9700 RB Groningen, the Netherlands
- Correspondence: John Neidhardt, Human Genetics, Faculty of Medicine and Health Sciences, University of Oldenburg, Ammerländer Heerstrasse 114-118, 26129 Oldenburg, Germany.
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38
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Petersen USS, Doktor TK, Andresen BS. Pseudoexon activation in disease by non-splice site deep intronic sequence variation - wild type pseudoexons constitute high-risk sites in the human genome. Hum Mutat 2021; 43:103-127. [PMID: 34837434 DOI: 10.1002/humu.24306] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 11/02/2021] [Accepted: 11/06/2021] [Indexed: 12/27/2022]
Abstract
Accuracy of pre-messenger RNA (pre-mRNA) splicing is crucial for normal gene expression. Complex regulation supports the spliceosomal distinction between authentic exons and the many seemingly functional splice sites delimiting pseudoexons. Pseudoexons are nonfunctional intronic sequences that can be activated for aberrant inclusion in mRNA, which may cause disease. Pseudoexon activation is very challenging to predict, in particular when activation occurs by sequence variants that alter the splicing regulatory environment without directly affecting splice sites. As pseudoexon inclusion often evades detection due to activation of nonsense-mediated mRNA decay, and because conventional diagnostic procedures miss deep intronic sequence variation, pseudoexon activation is a heavily underreported disease mechanism. Pseudoexon characteristics have mainly been studied based on in silico predicted sequences. Moreover, because recognition of sequence variants that create or strengthen splice sites is possible by comparison with well-established consensus sequences, this type of pseudoexon activation is by far the most frequently reported. Here we review all known human disease-associated pseudoexons that carry functional splice sites and are activated by deep intronic sequence variants located outside splice site sequences. We delineate common characteristics that make this type of wild type pseudoexons distinct high-risk sites in the human genome.
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Affiliation(s)
- Ulrika S S Petersen
- Department of Biochemistry and Molecular Biology and the Villum Center for Bioanalytical Sciences, University of Southern Denmark, Odense M, Denmark
| | - Thomas K Doktor
- Department of Biochemistry and Molecular Biology and the Villum Center for Bioanalytical Sciences, University of Southern Denmark, Odense M, Denmark
| | - Brage S Andresen
- Department of Biochemistry and Molecular Biology and the Villum Center for Bioanalytical Sciences, University of Southern Denmark, Odense M, Denmark
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39
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Abrahams L, Savisaar R, Mordstein C, Young B, Kudla G, Hurst LD. Evidence in disease and non-disease contexts that nonsense mutations cause altered splicing via motif disruption. Nucleic Acids Res 2021; 49:9665-9685. [PMID: 34469537 PMCID: PMC8464065 DOI: 10.1093/nar/gkab750] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 08/17/2021] [Accepted: 08/19/2021] [Indexed: 12/21/2022] Open
Abstract
Transcripts containing premature termination codons (PTCs) can be subject to nonsense-associated alternative splicing (NAS). Two models have been evoked to explain this, scanning and splice motif disruption. The latter postulates that exonic cis motifs, such as exonic splice enhancers (ESEs), are disrupted by nonsense mutations. We employ genome-wide transcriptomic and k-mer enrichment methods to scrutinize this model. First, we show that ESEs are prone to disruptive nonsense mutations owing to their purine richness and paucity of TGA, TAA and TAG. The motif model correctly predicts that NAS rates should be low (we estimate 5–30%) and approximately in line with estimates for the rate at which random point mutations disrupt splicing (8–20%). Further, we find that, as expected, NAS-associated PTCs are predictable from nucleotide-based machine learning approaches to predict splice disruption and, at least for pathogenic variants, are enriched in ESEs. Finally, we find that both in and out of frame mutations to TAA, TGA or TAG are associated with exon skipping. While a higher relative frequency of such skip-inducing mutations in-frame than out of frame lends some credence to the scanning model, these results reinforce the importance of considering splice motif modulation to understand the etiology of PTC-associated disease.
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Affiliation(s)
- Liam Abrahams
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK
| | - Rosina Savisaar
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
| | - Christine Mordstein
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK.,MRC Human Genetics Unit, The University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK.,Aarhus University, Department of Molecular Biology and Genetics, C F Møllers Allé 3, 8000 Aarhus, Denmark
| | - Bethan Young
- MRC Human Genetics Unit, The University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Grzegorz Kudla
- MRC Human Genetics Unit, The University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Laurence D Hurst
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK
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40
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Weisschuh N, Marino V, Schäferhoff K, Richter P, Park J, Haack TB, Dell'Orco D. Mutations at a split codon in the GTPase-encoding domain of OPA1 cause dominant optic atrophy through different molecular mechanisms. Hum Mol Genet 2021; 31:761-774. [PMID: 34559197 PMCID: PMC8895747 DOI: 10.1093/hmg/ddab286] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/06/2021] [Accepted: 09/20/2021] [Indexed: 12/22/2022] Open
Abstract
Exonic (i.e. coding) variants in genes associated with disease can exert pathogenic effects both at the protein and mRNA level, either by altering the amino acid sequence or by affecting pre-mRNA splicing. The latter is often neglected due to the lack of RNA analyses in genetic diagnostic testing. In this study we considered both pathomechanisms and performed a comprehensive analysis of nine exonic nucleotide changes in OPA1, which is the major gene underlying autosomal dominant optic atrophy (DOA) and is characterized by pronounced allelic heterogeneity. We focused on the GTPase-encoding domain of OPA1, which harbors most of the missense variants associated with DOA. Given that the consensus splice sites extend into the exons, we chose a split codon, namely codon 438, for our analyses. Variants at this codon are the second most common cause of disease in our large cohort of DOA patients harboring disease-causing variants in OPA1. In silico splice predictions, heterologous splice assays, analysis of patient’s RNA when available, and protein modeling revealed different molecular outcomes for variants at codon 438. The wildtype aspartate residue at amino acid position 438 is directly involved in the dimerization of OPA1 monomers. We found that six amino acid substitutions at codon 438 (i.e. all substitutions of the first and second nucleotide of the codon) destabilized dimerization while only substitutions of the first nucleotide of the codon caused exon skipping. Our study highlights the value of combining RNA analysis and protein modeling approaches to accurately assign patients to future precision therapies.
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Affiliation(s)
- Nicole Weisschuh
- Institute for Ophthalmic Research, Centre for Ophthalmology, University of Tübingen, Tübingen 72076, Germany
| | - Valerio Marino
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biological Chemistry, University of Verona, Verona 37134, Italy
| | - Karin Schäferhoff
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen 72076, Germany
| | - Paul Richter
- University Eye Hospital, Centre for Ophthalmology, University of Tübingen, Tübingen 72076, Germany
| | - Joohyun Park
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen 72076, Germany
| | - Tobias B Haack
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen 72076, Germany.,Centre for Rare Diseases, University of Tübingen, Tübingen 72076, Germany
| | - Daniele Dell'Orco
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biological Chemistry, University of Verona, Verona 37134, Italy
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41
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Riolo G, Cantara S, Ricci C. What's Wrong in a Jump? Prediction and Validation of Splice Site Variants. Methods Protoc 2021; 4:62. [PMID: 34564308 PMCID: PMC8482176 DOI: 10.3390/mps4030062] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 08/27/2021] [Accepted: 09/03/2021] [Indexed: 02/07/2023] Open
Abstract
Alternative splicing (AS) is a crucial process to enhance gene expression driving organism development. Interestingly, more than 95% of human genes undergo AS, producing multiple protein isoforms from the same transcript. Any alteration (e.g., nucleotide substitutions, insertions, and deletions) involving consensus splicing regulatory sequences in a specific gene may result in the production of aberrant and not properly working proteins. In this review, we introduce the key steps of splicing mechanism and describe all different types of genomic variants affecting this process (splicing variants in acceptor/donor sites or branch point or polypyrimidine tract, exonic, and deep intronic changes). Then, we provide an updated approach to improve splice variants detection. First, we review the main computational tools, including the recent Machine Learning-based algorithms, for the prediction of splice site variants, in order to characterize how a genomic variant interferes with splicing process. Next, we report the experimental methods to validate the predictive analyses are defined, distinguishing between methods testing RNA (transcriptomics analysis) or proteins (proteomics experiments). For both prediction and validation steps, benefits and weaknesses of each tool/procedure are accurately reported, as well as suggestions on which approaches are more suitable in diagnostic rather than in clinical research.
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Affiliation(s)
| | | | - Claudia Ricci
- Department of Medical, Surgical and Neurological Sciences, University of Siena, 53100 Siena, Italy; (G.R.); (S.C.)
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42
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Frederiksen JH, Jensen SB, Tümer Z, Hansen TVO. Classification of MSH6 Variants of Uncertain Significance Using Functional Assays. Int J Mol Sci 2021; 22:ijms22168627. [PMID: 34445333 PMCID: PMC8395337 DOI: 10.3390/ijms22168627] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 07/27/2021] [Indexed: 12/20/2022] Open
Abstract
Lynch syndrome (LS) is one of the most common hereditary cancer predisposition syndromes worldwide. Individuals with LS have a high risk of developing colorectal or endometrial cancer, as well as several other cancers. LS is caused by autosomal dominant pathogenic variants in one of the DNA mismatch repair (MMR) genes MLH1, MSH2, PMS2 or MSH6, and typically include truncating variants, such as frameshift, nonsense or splicing variants. However, a significant number of missense, intronic, or silent variants, or small in-frame insertions/deletions, are detected during genetic screening of the MMR genes. The clinical effects of these variants are often more difficult to predict, and a large fraction of these variants are classified as variants of uncertain significance (VUS). It is pivotal for the clinical management of LS patients to have a clear genetic diagnosis, since patients benefit widely from screening, preventive and personal therapeutic measures. Moreover, in families where a pathogenic variant is identified, testing can be offered to family members, where non-carriers can be spared frequent surveillance, while carriers can be included in cancer surveillance programs. It is therefore important to reclassify VUSs, and, in this regard, functional assays can provide insight into the effect of a variant on the protein or mRNA level. Here, we briefly describe the disorders that are related to MMR deficiency, as well as the structure and function of MSH6. Moreover, we review the functional assays that are used to examine VUS identified in MSH6 and discuss the results obtained in relation to the ACMG/AMP PS3/BS3 criterion. We also provide a compiled list of the MSH6 variants examined by these assays. Finally, we provide a future perspective on high-throughput functional analyses with specific emphasis on the MMR genes.
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Affiliation(s)
- Jane H. Frederiksen
- Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, DK-2100 Copenhagen, Denmark; (S.B.J.); (Z.T.)
- Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, DK-2100 Copenhagen, Denmark
- Correspondence: (J.H.F.); (T.v.O.H.)
| | - Sara B. Jensen
- Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, DK-2100 Copenhagen, Denmark; (S.B.J.); (Z.T.)
| | - Zeynep Tümer
- Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, DK-2100 Copenhagen, Denmark; (S.B.J.); (Z.T.)
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Thomas v. O. Hansen
- Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, DK-2100 Copenhagen, Denmark; (S.B.J.); (Z.T.)
- Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, DK-2100 Copenhagen, Denmark
- Correspondence: (J.H.F.); (T.v.O.H.)
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43
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De Paoli-Iseppi R, Gleeson J, Clark MB. Isoform Age - Splice Isoform Profiling Using Long-Read Technologies. Front Mol Biosci 2021; 8:711733. [PMID: 34409069 PMCID: PMC8364947 DOI: 10.3389/fmolb.2021.711733] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/19/2021] [Indexed: 01/12/2023] Open
Abstract
Alternative splicing (AS) of RNA is a key mechanism that results in the expression of multiple transcript isoforms from single genes and leads to an increase in the complexity of both the transcriptome and proteome. Regulation of AS is critical for the correct functioning of many biological pathways, while disruption of AS can be directly pathogenic in diseases such as cancer or cause risk for complex disorders. Current short-read sequencing technologies achieve high read depth but are limited in their ability to resolve complex isoforms. In this review we examine how long-read sequencing (LRS) technologies can address this challenge by covering the entire RNA sequence in a single read and thereby distinguish isoform changes that could impact RNA regulation or protein function. Coupling LRS with technologies such as single cell sequencing, targeted sequencing and spatial transcriptomics is producing a rapidly expanding suite of technological approaches to profile alternative splicing at the isoform level with unprecedented detail. In addition, integrating LRS with genotype now allows the impact of genetic variation on isoform expression to be determined. Recent results demonstrate the potential of these techniques to elucidate the landscape of splicing, including in tissues such as the brain where AS is particularly prevalent. Finally, we also discuss how AS can impact protein function, potentially leading to novel therapeutic targets for a range of diseases.
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Affiliation(s)
| | | | - Michael B. Clark
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, Australia
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44
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Zea DJ, Laskina S, Baudin A, Richard H, Laine E. Assessing conservation of alternative splicing with evolutionary splicing graphs. Genome Res 2021; 31:1462-1473. [PMID: 34266979 PMCID: PMC8327911 DOI: 10.1101/gr.274696.120] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 06/11/2021] [Indexed: 12/29/2022]
Abstract
Understanding how protein function has evolved and diversified is of great importance for human genetics and medicine. Here, we tackle the problem of describing the whole transcript variability observed in several species by generalizing the definition of splicing graph. We provide a practical solution to construct parsimonious evolutionary splicing graphs where each node is a minimal transcript building block defined across species. We show a clear link between the functional relevance, tissue regulation, and conservation of alternative transcripts on a set of 50 genes. By scaling up to the whole human protein-coding genome, we identify a few thousand genes where alternative splicing modulates the number and composition of pseudorepeats. We have implemented our approach in ThorAxe, an efficient, versatile, robust, and freely available computational tool.
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Affiliation(s)
- Diego Javier Zea
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), 75005 Paris, France
| | - Sofya Laskina
- Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, 13353 Berlin, Germany
| | - Alexis Baudin
- Sorbonne Université, CNRS, LIP6, F-75005 Paris, France
| | - Hugues Richard
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), 75005 Paris, France
- Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, 13353 Berlin, Germany
| | - Elodie Laine
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), 75005 Paris, France
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45
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Takeda JI, Fukami S, Tamura A, Shibata A, Ohno K. IntSplice2: Prediction of the Splicing Effects of Intronic Single-Nucleotide Variants Using LightGBM Modeling. Front Genet 2021; 12:701076. [PMID: 34349788 PMCID: PMC8326971 DOI: 10.3389/fgene.2021.701076] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 06/17/2021] [Indexed: 12/03/2022] Open
Abstract
Prediction of the effect of a single-nucleotide variant (SNV) in an intronic region on aberrant pre-mRNA splicing is challenging except for an SNV affecting the canonical GU/AG splice sites (ss). To predict pathogenicity of SNVs at intronic positions −50 (Int-50) to −3 (Int-3) close to the 3’ ss, we developed light gradient boosting machine (LightGBM)-based IntSplice2 models using pathogenic SNVs in the human gene mutation database (HGMD) and ClinVar and common SNVs in dbSNP with 0.01 ≤ minor allelic frequency (MAF) < 0.50. The LightGBM models were generated using features representing splicing cis-elements. The average recall/sensitivity and specificity of IntSplice2 by fivefold cross-validation (CV) of the training dataset were 0.764 and 0.884, respectively. The recall/sensitivity of IntSplice2 was lower than the average recall/sensitivity of 0.800 of IntSplice that we previously made with support vector machine (SVM) modeling for the same intronic positions. In contrast, the specificity of IntSplice2 was higher than the average specificity of 0.849 of IntSplice. For benchmarking (BM) of IntSplice2 with IntSplice, we made a test dataset that was not used to train IntSplice. After excluding the test dataset from the training dataset, we generated IntSplice2-BM and compared it with IntSplice using the test dataset. IntSplice2-BM was superior to IntSplice in all of the seven statistical measures of accuracy, precision, recall/sensitivity, specificity, F1 score, negative predictive value (NPV), and matthews correlation coefficient (MCC). We made the IntSplice2 web service at https://www.med.nagoya-u.ac.jp/neurogenetics/IntSplice2.
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Affiliation(s)
- Jun-Ichi Takeda
- Division of Neurogenetics, Center for Neurological Diseases and Cancer, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sae Fukami
- Division of Neurogenetics, Center for Neurological Diseases and Cancer, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Akira Tamura
- Division of Neurogenetics, Center for Neurological Diseases and Cancer, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Akihide Shibata
- Division of Neurogenetics, Center for Neurological Diseases and Cancer, Nagoya University Graduate School of Medicine, Nagoya, Japan.,Department of Anesthesiology, Toranomon Hospital, Tokyo, Japan
| | - Kinji Ohno
- Division of Neurogenetics, Center for Neurological Diseases and Cancer, Nagoya University Graduate School of Medicine, Nagoya, Japan
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46
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A Novel Noncanonical Splicing Mutation of ANOS1 Gene in Siblings with Kallmann Syndrome Identified by Whole-Exome Sequencing. Reprod Sci 2021; 29:475-479. [PMID: 34231177 DOI: 10.1007/s43032-021-00672-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 06/14/2021] [Indexed: 10/20/2022]
Abstract
Kallmann syndrome (KS) is a rare genetic disorder that is characterized by idiopathic hypogonadotropic hypogonadism associated with anosmia. Genetic variants in ANOS1 gene are the most common mutations associated with X-linked recessive form of KS. Canonical ± 1 or 2 splice site variants in ANOS1 have been described to be responsible for KS. Here, we identified a novel noncanonical splice site variant (c.1062+4T>C) in ANOS1 gene in two siblings with KS by whole-exome sequencing (WES). Sanger sequencing showed this mutation was inherited from their mother, whose brother was a KS patient as well. Through the functional assay in vitro, we found that this mutation resulted in a 50-bp deletion of exon 7, which caused frameshift mutation leading to a premature termination of translation and a truncated anosmin-1 protein. Our results revealed that this noncanonical splice site variant is involved in KS. Thus, it is suggested that we should pay attention to the noncanonical splice site variants when using molecular genetic diagnostics of KS.
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47
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Functional Evaluation of Splicing for Variants of Uncertain Significance in Patients with Inherited Retinal Diseases. Genes (Basel) 2021; 12:genes12070993. [PMID: 34209753 PMCID: PMC8303747 DOI: 10.3390/genes12070993] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 01/13/2023] Open
Abstract
Inherited retinal diseases (IRD) comprise a heterogeneous set of clinical and genetic disorders that lead to blindness. Given the emerging opportunities in precision medicine and gene therapy, it has become increasingly important to determine whether DNA variants with uncertain significance (VUS) are responsible for patients’ IRD. This research was performed to assess the functional consequence of six VUS identified in patients with IRD. Clinical assessments included an ophthalmic examination, best-corrected visual acuity, and kinetic perimetry. Imaging was acquired with the Optos ultra-widefield camera and spectral domain optical coherence tomography (SD-OCT). Genetic testing was performed by Molecular Vision Laboratories. VUS that were predicted to alter splicing were analyzed with a minigene assay, which revealed that VUS in the genes OPA1, CNGB1, and CLUAP1 altered spicing mechanisms. Due to emerging gene and cell therapies, these results expand the genotype-phenotype correlations for patients diagnosed with an IRD.
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48
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Boussaad I, Obermaier CD, Hanss Z, Bobbili DR, Bolognin S, Glaab E, Wołyńska K, Weisschuh N, De Conti L, May C, Giesert F, Grossmann D, Lambert A, Kirchen S, Biryukov M, Burbulla LF, Massart F, Bohler J, Cruciani G, Schmid B, Kurz-Drexler A, May P, Duga S, Klein C, Schwamborn JC, Marcus K, Woitalla D, Vogt Weisenhorn DM, Wurst W, Baralle M, Krainc D, Gasser T, Wissinger B, Krüger R. A patient-based model of RNA mis-splicing uncovers treatment targets in Parkinson's disease. Sci Transl Med 2021; 12:12/560/eaau3960. [PMID: 32908004 DOI: 10.1126/scitranslmed.aau3960] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 01/24/2020] [Accepted: 06/22/2020] [Indexed: 12/18/2022]
Abstract
Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder with monogenic forms representing prototypes of the underlying molecular pathology and reproducing to variable degrees the sporadic forms of the disease. Using a patient-based in vitro model of PARK7-linked PD, we identified a U1-dependent splicing defect causing a drastic reduction in DJ-1 protein and, consequently, mitochondrial dysfunction. Targeting defective exon skipping with genetically engineered U1-snRNA recovered DJ-1 protein expression in neuronal precursor cells and differentiated neurons. After prioritization of candidate drugs, we identified and validated a combinatorial treatment with the small-molecule compounds rectifier of aberrant splicing (RECTAS) and phenylbutyric acid, which restored DJ-1 protein and mitochondrial dysfunction in patient-derived fibroblasts as well as dopaminergic neuronal cell loss in mutant midbrain organoids. Our analysis of a large number of exomes revealed that U1 splice-site mutations were enriched in sporadic PD patients. Therefore, our study suggests an alternative strategy to restore cellular abnormalities in in vitro models of PD and provides a proof of concept for neuroprotection based on precision medicine strategies in PD.
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Affiliation(s)
- Ibrahim Boussaad
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Carolin D Obermaier
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg.,Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | - Zoé Hanss
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Dheeraj R Bobbili
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Silvia Bolognin
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Enrico Glaab
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Katarzyna Wołyńska
- Department of Medical Genetics, Poznan University of Medical Sciences, 60-806 Poznan, Poland
| | - Nicole Weisschuh
- Molecular Genetics Laboratory, Institute for Ophthalmic Research, University Clinics Tübingen, 72076 Tübingen, Germany
| | - Laura De Conti
- ICGEB-International Centre for Genetic Engineering and Biotechnology, Padriciano 99, 34149 Trieste, Italy
| | - Caroline May
- Medizinisches Proteom-Center, Ruhr-University Bochum, 44801 Bochum, Germany
| | - Florian Giesert
- Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Site Munich, Feodor-Lynen-Str. 17, 81377 Munich, Germany.,Technische Universität München-Weihenstephan, Developmental Genetics, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Dajana Grossmann
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Annika Lambert
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Susanne Kirchen
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Maria Biryukov
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Lena F Burbulla
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Francois Massart
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Jill Bohler
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Gérald Cruciani
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Benjamin Schmid
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | | | - Patrick May
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Stefano Duga
- Department of Biomedical Sciences, Humanitas University, Via Manzoni 113, 20089 Rozzano, Milan, Italy.,Humanitas Clinical and Research center, IRCCS, Via Manzoni 56, 20089 Rozzano, Milan, Italy
| | - Christine Klein
- Institute of Neurogenetics, University of Luebeck, 23562 Luebeck, Germany
| | - Jens C Schwamborn
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg
| | - Katrin Marcus
- Medizinisches Proteom-Center, Ruhr-University Bochum, 44801 Bochum, Germany
| | - Dirk Woitalla
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Daniela M Vogt Weisenhorn
- Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,Technische Universität München-Weihenstephan, Developmental Genetics, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Wolfgang Wurst
- Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Site Munich, Feodor-Lynen-Str. 17, 81377 Munich, Germany.,Technische Universität München-Weihenstephan, Developmental Genetics, c/o Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.,Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Str. 17, 81377 Munich, Germany
| | - Marco Baralle
- ICGEB-International Centre for Genetic Engineering and Biotechnology, Padriciano 99, 34149 Trieste, Italy
| | - Dimitri Krainc
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Thomas Gasser
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), 72076 Tübingen, Germany
| | - Bernd Wissinger
- Molecular Genetics Laboratory, Institute for Ophthalmic Research, University Clinics Tübingen, 72076 Tübingen, Germany
| | - Rejko Krüger
- LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4362 Esch-Sur-Alzette, Luxembourg. .,Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany.,Department of Neurology and Parkinson Research Clinic, Centre Hospitalier de Luxembourg (CHL), 1210 Luxembourg, Luxembourg.,Transversal Translational Medicine, Luxembourg Institute of Health (LIH), 1445 Strassen, Luxembourg
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49
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Lee JS, Lamarche-Vane N, Richard S. Microexon alternative splicing of small GTPase regulators: Implication in central nervous system diseases. WILEY INTERDISCIPLINARY REVIEWS-RNA 2021; 13:e1678. [PMID: 34155820 DOI: 10.1002/wrna.1678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 05/07/2021] [Accepted: 05/25/2021] [Indexed: 12/11/2022]
Abstract
Microexons are small sized (≤51 bp) exons which undergo extensive alternative splicing in neurons, microglia, embryonic stem cells, and cancer cells, giving rise to cell type specific protein isoforms. Due to their small sizes, microexons provide a unique challenge for the splicing machinery. They frequently lack exon splicer enhancers/repressors and require specialized neighboring trans-regulatory and cis-regulatory elements bound by RNA binding proteins (RBPs) for their inclusion. The functional consequences of including microexons within mRNAs have been extensively documented in the central nervous system (CNS) and aberrations in their inclusion have been observed to lead to abnormal processes. Despite the increasing evidence for microexons impacting cellular physiology within CNS, mechanistic details illustrating their functional importance in diseases of the CNS is still limited. In this review, we discuss the unique characteristics of microexons, and how RBPs participate in regulating their inclusion and exclusion during splicing. We consider recent findings of microexon alternative splicing and their implication for regulating the function of small GTPases in the context of the microglia, and we extrapolate these findings to what is known in neurons. We further discuss the emerging evidence for dysregulation of the Rho GTPase pathway in CNS diseases and the consequences contributed by the mis-splicing of microexons. This article is categorized under: RNA Processing > Splicing Mechanisms RNA Processing > Splicing Regulation/Alternative Splicing RNA in Disease and Development > RNA in Disease.
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Affiliation(s)
- Jee-San Lee
- Segal Cancer Center, Lady Davis Institute for Medical Research, Montreal, Quebec, Canada.,Department of Biochemistry, McGill University, Montreal, Quebec, Canada
| | - Nathalie Lamarche-Vane
- Research Institute of the McGill University Health Centre, Cancer Research Program, Montreal, Quebec, Canada.,Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec, Canada
| | - Stéphane Richard
- Segal Cancer Center, Lady Davis Institute for Medical Research, Montreal, Quebec, Canada.,Gerald Bronfman Department of Oncology, McGill University, Montreal, Quebec, Canada.,Department of Biochemistry, McGill University, Montreal, Quebec, Canada
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50
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El Marabti E, Abdel-Wahab O. Therapeutic Modulation of RNA Splicing in Malignant and Non-Malignant Disease. Trends Mol Med 2021; 27:643-659. [PMID: 33994320 DOI: 10.1016/j.molmed.2021.04.005] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 04/11/2021] [Accepted: 04/13/2021] [Indexed: 01/24/2023]
Abstract
RNA splicing is the enzymatic process by which non-protein coding sequences are removed from RNA to produce mature protein-coding mRNA. Splicing is thereby a major mediator of proteome diversity as well as a dynamic regulator of gene expression. Genetic alterations disrupting splicing of individual genes or altering the function of splicing factors contribute to a wide range of human genetic diseases as well as cancer. These observations have resulted in the development of therapies based on oligonucleotides that bind to RNA sequences and modulate splicing for therapeutic benefit. In parallel, small molecules that bind to splicing factors to alter their function or modify RNA processing of individual transcripts are being pursued for monogenic disorders as well as for cancer.
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Affiliation(s)
- Ettaib El Marabti
- Clinical Transplant Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Omar Abdel-Wahab
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
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