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BMJ Publishing Group, Journal of Medical Genetics, 4(57), p. 258-268, 2019

DOI: 10.1136/jmedgenet-2019-106249

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Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies

Journal article published in 2019 by Massimo Bogliolo ORCID, Roser Pujol, Miriam Aza-Carmona, Núria Muñoz-Subirana, Benjamin Rodriguez-Santiago, José Antonio Casado, Paula Rio, Christopher Bauser, Judith Reina-Castillón, Marcos Lopez-Sanchez, Lidia Gonzalez-Quereda, Pia Gallano, Albert Catalá, Ana Ruiz-Llobet, Isabel Badell and other authors.
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

PurposePatients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients’ characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies.Methods68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test FANCA missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies.ResultsWe identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two FANCA variants reported in mutations databases as ‘affecting functions’ are SNPs. Deep analysis of sequencing data revealed patients’ true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations)ConclusionWES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.