Comparison of in silico strategies to prioritize rare genomic variants....pdf (1.74 MB)
Download file

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

Download (1.74 MB)
journal contribution
posted on 18.11.2022, 16:39 authored by C Rowlands, HB Thomas, J Lord, HA Wai, G Arno, G Beaman, P Sergouniotis, B Gomes-Silva, C Campbell, N Gossan, C Hardcastle, K Webb, C O’Callaghan, RA Hirst, S Ramsden, E Jones, J Clayton-Smith, AR Webster, JC Ambrose, P Arumugam, R Bevers, M Bleda, F Boardman-Pretty, CR Boustred, H Brittain, MJ Caulfield, GC Chan, T Fowler, A Giess, A Hamblin, S Henderson, TJP Hubbard, R Jackson, LJ Jones, D Kasperaviciute, M Kayikci, A Kousathanas, L Lahnstein, SEA Leigh, IUS Leong, FJ Lopez, F Maleady-Crowe, M McEntagart, F Minneci, L Moutsianas, M Mueller, N Murugaesu, AC Need, P O’Donovan, CA Odhams, C Patch, D Perez-Gil, MB Pereira, J Pullinger, T Rahim, A Rendon, T Rogers, K Savage, K Sawant, RH Scott, A Siddiq, A Sieghart, SC Smith, A Sosinsky, A Stuckey, M Tanguy, AL Taylor Tavares, ERA Thomas, SR Thompson, A Tucci, MJ Welland, E Williams, K Witkowsa, SM Wood, AGL Douglas, RT O’Keefe, WG Newman, D Baralle, GCM Black, JM Ellingford
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.

Funding

We acknowledge funding from the Wellcome Trust Transforming Genomic Medicine Initiative (200990/Z/16/Z), and personal support from Health Education England (Ellingford), Medical Research Council (Rowlands) and the Wellcome Trust (Baralle, RP-2016-07-011).

History

Citation

Rowlands, C., Thomas, H.B., Lord, J. et al. Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders. Sci Rep 11, 20607 (2021). https://doi.org/10.1038/s41598-021-99747-2

Author affiliation

Department of Infection, Immunity and Inflammation

Version

VoR (Version of Record)

Published in

Scientific Reports

Volume

11

Pagination

20607

Publisher

Springer Science and Business Media LLC

eissn

2045-2322

Acceptance date

13/09/2021

Copyright date

2021

Available date

18/11/2022

Language

en

Usage metrics

Categories

Licence

Exports