Functional characterization vs in silico prediction for TBX5 missense and splice variants in Holt-Oram syndrome

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Vanlerberghe, Clemence | Jourdain, Anne-Sophie | Frenois, Frederic | Ait-Yahya, Émilie | Bamshad, Mike | Dieux, Anne | Dufour, William | Leduc, Fiona | Manouvrier, Sylvie | Patterson, Karynne | Ghoumid, Jamal | Escande, Fabienne | Smol, Thomas | Brunelle, Perrine | Petit, Florence

Edité par CCSD ; Nature Publishing Group -

International audience. PurposePredicting effects of genomic variants has become a real challenge in the diagnosis of rare human diseases. Holt-Oram syndrome is an autosomal condition characterized by the association of radial and heart defects, due to variants in TBX5. Most variants are predicted to be truncating and result in haploinsufficiency. The pathogenicity of missense or splice variants is harder to demonstrate.MethodsFourteen TBX5 variants of uncertain significance (5 missense, 9 splice) and 6 likely pathogenic missense variants were selected for functional testing, depending on the variant-type (immunolocalization, western blot, reporter assays, minigene splice assays, and reverse transcription-polymerase chain reaction). Results were compared with in silico predictions.ResultsFunctional tests allowed to reclassify 9/14 variants of uncertain significance in TBX5 as likely pathogenic, confirming their role in Holt-Oram syndrome. We demonstrated loss of function (n = 8) or gain of function (n = 1) for 9 of the 11 missense variants, whereas no functional impact was shown for the 2 variants: p.(Gly195Ala) and p.(Ser261Cys), as suggested by contradictory predictions of in silico approaches. Of 9 splice variants predicted to affect splicing by SpliceAI, we observed partial or complete exon skipping (n = 6), intron retention (n = 2) or exon shortening (n = 1), inducing frame shifting with premature stop codons.ConclusionBioinformatic and biological approaches are complementary, together with a good knowledge of clinical conditions, for accurate American College of Medical Genetics and Genomics classification in human rare diseases.

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