ESPE Abstracts (2015) 84 P-2-536

Ultra-Deep Next-Generation Sequencing: A reliable Method for the Molecular Diagnosis of McCune Albright Syndrome

Delphine Mallet-Motáka, Florence Roucher-Bouleza,c, Marc Nicolinoa,b & Yves Morela,c


aMolecular Endocrinology and Rares Diseases, Centre de Biologie et de Pathologie Est, Hospices Civils de Lyon, Bron, France; bPediatric Endocrinology, Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France; cUniversité Claude Bernard Lyon 1, Lyon, France


Background: The molecular diagnosis of McCune Albright syndrome (MAS) is difficult because the detection of somatic GNAS1 mutations is usually performed in blood, in which the fraction of mutated allele could be barely detectable. To improve the usual techniques (selective enrichment, either with nested PCR and enzymatic digestion or with use of peptide nucleic acid probes), and to avoid technical problems like contamination, a new approach using next generation sequencing was tested.

Objective and hypotheses: We tested the ability of ultra-deep sequencing on an Ion Torrent PGM™ System to detect and to quantify GNAS1 mutations in MAS.

Method: Using primer fusion technique, we designed an amplicon targeting the two prevalent mutations, p.R201C and p.R201H. In each run, 11 samples were multiplexed on a 314 chip: eight patients, one control sample with the p.R201C mutation, one control sample with the p.R201H mutation and one negative control without mutation. Detection of mutations was performed with the Variant Caller developed in the Torrent Suite™ software,

Results: We tested 23 samples, for which we previously studied GNAS1 with the selective enrichment method. 15 of them were known to be mutation carriers, whereas for the eight other, no mutation was detected in the previous study. Due to the high depth of sequencing we were able to quantify the fraction of mutated allele. The presence of the mutation was confirmed in the 15 patients, whereas no additional mutation was detected in the eight negative samples. The mutant allele frequency of the most abundant mutation was about 30%, and the rarest mutated allele had a frequency of about 0.3%

Conclusion: Ultra-deep sequencing on PGM™ is a reliable technique to detect GNAS1 somatic mutations, allowing mutant allele quantification. The previous techniques could be used to confirm the identification of a mutation.

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