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Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup

RNA剪接 计算生物学 生物 选择性拼接 医学遗传学 基因组学 遗传学 计算机科学 基因组 核糖核酸 基因 外显子
作者
Logan C. Walker,Miguel de la Hoya,George A. R. Wiggins,Amanda Lindy,Lisa M. Vincent,Michael T. Parsons,Daffodil M. Canson,Dana M. Bis-Brewer,Ashley Cass,Alexander Tchourbanov,Heather Zimmermann,Alicia Byrne,Tina Pesaran,Rachid Karam,Steven M. Harrison,Amanda B. Spurdle,Leslie G. Biesecker,Steven M. Harrison,Ahmad Abou Tayoun,Jonathan S. Berg,Steven E. Brenner,Garry R. Cutting,Sian Ellard,Marc S. Greenblatt,Peter B. Kang,Izabela Karbassi,Rachel Karchin,Jessica L. Mester,Anne O’Donnell‐Luria,Tina Pesaran,Sharon E. Plon,Heidi L. Rehm,Natasha T. Strande,Sean V. Tavtigian,Scott Topper
出处
期刊:American Journal of Human Genetics [Elsevier BV]
卷期号:110 (7): 1046-1067 被引量:30
标识
DOI:10.1016/j.ajhg.2023.06.002
摘要

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

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