Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes
Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes
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儿童基因组答案：超过 1000 个儿科罕见病基因组的动态分析
DOI：
10.1101/2021.10.07.21264628
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
T. Pastinen
中科院分区：
文献类型：
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作者：
A. Cohen;E. Farrow;A. Abdelmoity;J. Alaimo;S. Amudhavalli;John T. Anderson;Lalit R. Bansal;Lauren E Bartik;P. Baybayan;Bradley Belden;C. Berrios;R. Biswell;P. Buczkowicz;Orion J. Buske;Shreyasee Chakraborty;W. Cheung;Keith A. Coffman;Ashley M. Cooper;L. Cross;Tom Curran;T. T. T. Dang;Mary M. Elfrink;Kendra L. Engleman;Erin Fecske;Cynthia Fieser;Keely Fitzgerald;E. Fleming;Randi N. Gadea;J. Gannon;Rose Gelineau;M. Gibson;Jeffrey Goldstein;E. Grundberg;Kelsee Halpin;Brian S. Harvey;B. Heese;Wendy Hein;Suzanne M. Herd;S. Hughes;M. Ilyas;J. Jacobson;J. Jenkins;Shao Jiang;J. J. Johnston;K. Keeler;J. Korlach;J. Kussmann;Christine C. Lambert;Caitlin E. Lawson;J. Le Pichon;J. S. Leeder;Vicki C. Little;Daniel A. Louiselle;M. Lypka;Brittany McDonald;Neil A. Miller;Ann C. Modrcin;Annapoorna Nair;Shelby H. Neal;C. Oermann;D. Pacicca;Kailash Pawar;N. Posey;Nigel J. Price;L. Puckett;Julio F. Quezada;N. Raje;W. Rowell;E. Rush;V. Sampath;Carol J. Saunders;Caitlin R. Schwager;R. Schwend;Elizabeth Shaffer;Craig Smail;Sarah Soden;Meghan E. Strenk;Bonnie R. Sullivan;Brooke Sweeney;J. Tam;Adam M. Walter;Holly I. Welsh;A. Wenger;L. Willig;Yun Yan;S. Younger;Dihong Zhou;T. Zion;I. Thiffault;T. Pastinen
目的：通过儿童基因组应答(GA4K)计划，在儿科罕见疾病队列中提供全面的诊断和候选分析。方法：对960个可疑遗传病家系进行广泛的分析，包括短读外显子组(ES)和基因组测序(SRGs)；PacBio HiFi长读GS(HiFi-GS)；小核苷酸(SNV)、结构(SV)和重复变异体；机器学习变异体优先顺序。在PhenoTips数据库中存储了结构化表型、按优先顺序排列的变体和系谱，并通过受控访问(DBGaP)共享数据。结果：既往基因测试阴性患者的诊断率从11%到幼稚患者的34.5%不等。在以前未解决的病例中，纳入GS的SVS增加了高达13%的新诊断。HiFi-GS的发现率比SRG高4倍。未知意义的变异和基因(vus/gus)仍然是最常见的发现(58%的非诊断病例)。结论：计算优先顺序是诊断SNV的有效方法。彻底识别非SNV仍然具有挑战性，HIFI-GS测序可以部分缓解这一问题。重要的是，社区研究通过共享实时数据来加速基因验证，并通过提供来自>；1000个人类等位基因的HiFi变体(SNV/SV)资源来支持，以促进用于罕见疾病诊断的新测序平台的实施。
PURPOSE: To provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids (GA4K) program. METHODS: Extensive analyses of 960 families with suspected genetic disorders including short-read exome (ES) and genome sequencing (srGS); PacBio HiFi long-read GS (HiFi-GS); variant calling for small-nucleotide (SNV), structural (SV) and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants and pedigrees are stored in PhenoTips database, with data sharing through controlled access (dbGAP). RESULTS: Diagnostic rates ranged from 11% for cases with prior negative genetic tests to 34.5% in naive patients. Incorporating SVs from GS added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs than srGS. Variants and genes of unknown significance (VUS/GUS) remain the most common finding (58% of non-diagnostic cases). CONCLUSION: Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated by HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation, and by providing HiFi variant (SNV/SV) resources from >1,000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.