Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

被引:49
作者
Rowlands, Charlie [1 ,2 ]
Thomas, Huw B. [1 ,2 ]
Lord, Jenny [3 ]
Wai, Htoo A. [3 ]
Arno, Gavin [4 ,5 ,6 ]
Beaman, Glenda [1 ,2 ]
Sergouniotis, Panagiotis [1 ,2 ]
Gomes-Silva, Beatriz [2 ]
Campbell, Christopher [1 ]
Gossan, Nicole [1 ]
Hardcastle, Claire [1 ]
Webb, Kevin [7 ]
O'Callaghan, Christopher [8 ,9 ,10 ,11 ]
Hirst, Robert A. [11 ]
Ramsden, Simon [1 ]
Jones, Elizabeth [1 ]
Clayton-Smith, Jill [1 ,2 ]
Webster, Andrew R. [4 ,5 ]
Douglas, Andrew G. L. [3 ,12 ]
O'Keefe, Raymond T. [2 ]
Newman, William G. [1 ,2 ]
Baralle, Diana [3 ,12 ]
Black, Graeme C. M. [1 ,2 ]
Ellingford, Jamie M. [1 ,2 ]
机构
[1] Manchester Univ Hosp NHS Fdn Trust, St Marys Hosp, Manchester Ctr Genom Med, North West Genom Lab Hub, Manchester, Lancs, England
[2] Univ Manchester, Fac Biol Med & Hlth, Sch Biol Sci, Div Evolut & Genom Sci,Neurosci & Mental Hlth Dom, Manchester, Lancs, England
[3] Univ Southampton, Fac Med, Human Dev & Hlth, Southampton, Hants, England
[4] UCL, Inst Ophthalmol, London, England
[5] Moorfields Eye Hosp NHS Fdn Trust, London, England
[6] Great Ormond St Hosp NHS Fdn Trust, London, England
[7] Manchester Univ Hosp NHS Fdn Trust, Manchester Adult Cyst Fibrosis Ctr, Manchester, Lancs, England
[8] UCL Great Ormond St Inst Child Hlth, Resp Crit Care & Anaesthesia, London, England
[9] Great Ormond St Childrens Hosp, London, England
[10] NIHR Great Ormond St Hosp, Biomed Res Ctr, London, England
[11] Univ Leicester, Ctr PCD Diag & Res, Dept Infect Immun & Inflammat, RKCSB, Leicester, Leics, England
[12] Univ Hosp Southampton NHS Fdn Trust, Wessex Clin Genet Serv, Southampton, Hants, England
基金
英国惠康基金; 英国医学研究理事会;
关键词
GENERATION; MUTATIONS; ELEMENTS; YIELD;
D O I
10.1038/s41598-021-99747-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being 'pathogenic' or 'benign' is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as `pathogenic' or ` likely pathogenic'; one in five of these cases could lead to new or refined diagnoses.
引用
收藏
页数:11
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