Genome sequencing in families with congenital limb malformations
Author
Girisha, Katta M.
Elsner, Jonas
Mensah, Martin A.
Holtgrewe, Manuel
Hertzberg, Jakob
Bigoni, Stefania
Busche, Andreas
Coutelier, Marie
de Silva, Deepthi C.
Elcioglu, Nursel
Filges, Isabel
Gerkes, Erica
Graul-Neumann, Luitgard
Jamsheer, Aleksander
Krawitz, Peter
Kurth, Ingo
Markus, Susanne
Megarbane, Andre
Reis, Andre
Reuter, Miriam S.
Svoboda, Daniel
Teller, Christopher
TÜYSÜZ, Beyhan
Turkmen, Seval
Wilson, Meredith
Woitschach, Rixa
Vater, Inga
Caliebe, Almuth
Hulsemann, Wiebke
Horn, Denise
Mundlos, Stefan
Spielmann, Malte
Metadata
Show full item recordAbstract
The extensive clinical and genetic heterogeneity of congenital limb malformation calls for comprehensive genome-wide analysis of genetic variation. Genome sequencing (GS) has the potential to identify all genetic variants. Here we aim to determine the diagnostic potential of GS as a comprehensive one-test-for-all strategy in a cohort of undiagnosed patients with congenital limb malformations. We collected 69 cases (64 trios, 1 duo, 5 singletons) with congenital limb malformations with no molecular diagnosis after standard clinical genetic testing and performed genome sequencing. We also developed a framework to identify potential noncoding pathogenic variants. We identified likely pathogenic/disease-associated variants in 12 cases (17.4%) including four in known disease genes, and one repeat expansion in HOXD13. In three unrelated cases with ectrodactyly, we identified likely pathogenic variants in UBA2, establishing it as a novel disease gene. In addition, we found two complex structural variants (3%). We also identified likely causative variants in three novel high confidence candidate genes. We were not able to identify any noncoding variants. GS is a powerful strategy to identify all types of genomic variants associated with congenital limb malformation, including repeat expansions and complex structural variants missed by standard diagnostic approaches. In this cohort, no causative noncoding SNVs could be identified.
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