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. 2015 Sep;36(9):861-72.
doi: 10.1002/humu.22819. Epub 2015 Jul 24.

Amplicon Resequencing Identified Parental Mosaicism for Approximately 10% of "de novo" SCN1A Mutations in Children with Dravet Syndrome

Xiaojing Xu  1 , Xiaoxu Yang  2 , Qixi Wu  3 , Aijie Liu  1 , Xiaoling Yang  1 , Adam Yongxin Ye  2   4   5 , August Yue Huang  3 , Jiarui Li  2 , Meng Wang  2 , Zhe Yu  3 , Sheng Wang  3   6 , Zhichao Zhang  7 , Xiru Wu  1 , Liping Wei  2   3 , Yuehua Zhang  1
Affiliations

Amplicon Resequencing Identified Parental Mosaicism for Approximately 10% of "de novo" SCN1A Mutations in Children with Dravet Syndrome

Xiaojing Xu et al. Hum Mutat. 2015 Sep.

Abstract

The majority of children with Dravet syndrome (DS) are caused by de novo SCN1A mutations. To investigate the origin of the mutations, we developed and applied a new method that combined deep amplicon resequencing with a Bayesian model to detect and quantify allelic fractions with improved sensitivity. Of 174 SCN1A mutations in DS probands which were considered "de novo" by Sanger sequencing, we identified 15 cases (8.6%) of parental mosaicism. We identified another five cases of parental mosaicism that were also detectable by Sanger sequencing. Fraction of mutant alleles in the 20 cases of parental mosaicism ranged from 1.1% to 32.6%. Thirteen (65% of 20) mutations originated paternally and seven (35% of 20) maternally. Twelve (60% of 20) mosaic parents did not have any epileptic symptoms. Their mutant allelic fractions were significantly lower than those in mosaic parents with epileptic symptoms (P = 0.016). We identified mosaicism with varied allelic fractions in blood, saliva, urine, hair follicle, oral epithelium, and semen, demonstrating that postzygotic mutations could affect multiple somatic cells as well as germ cells. Our results suggest that more sensitive tools for detecting low-level mosaicism in parents of families with seemingly "de novo" mutations will allow for better informed genetic counseling.

Keywords: Dravet syndrome; SCN1A; de novo; mosaic; next-generation sequencing; somatic mutation.

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Figures

Figure 1
Figure 1
SCN1A mutation profiles in 363 Chinese Dravet Syndrome (DS) probands. A: The plot shows the numbers (in the shaded rectangles) and percentages (x and y axes) of DS probands with and without functional mutations in SCN1A and the transmission pattern of the mutations determined by Sanger sequencing. B: The pie chart shows the proportions of different types of functional mutations in SCN1A in the DS probands.
Figure 2
Figure 2
Evaluation of the performance of PASM. A: Comparison of the PASM‐measured fractions of mutant alleles with the theoretical values (both were negative log10‐transformed) in the serial dilution benchmarking test. Technical replicates are shown as dots with the same colors. B: Stability of PASM with different PCR cycles. PCR cycles ranging from 20 to 40 (x axis) for a sample with a heterozygous mutation c.4351C>A in SCN1A (NM_001165963.1). The fractions of mutant alleles measured by PASM are shown on the y axis. C: Stability of PASM with different amounts of input template DNA. Input template DNA (x axis) from 20 to 80 ng were tested in a 50 μL PCR system. The fractions of mutant alleles measured by PASM are shown on the y axis.
Figure 3
Figure 3
Confirmation of five cases of parental mosaicism detected by Sanger sequencing. A: Pedigrees of these five families and results from Sanger sequencing of the mutations in probands, mosaic parents, and negative normal controls. Arrows below the sequencing results indicate the mutation sites. B: Fractions of mutant alleles measured by PASM in probands, mosaic parents, non‐carrier normal parents, and non‐carrier normal unrelated controls. Blood samples were unavailable for the non‐carrier normal parents in DS002, DS003, and DS005. Technical replicates were carried out to generate the variations. Table in the lower panel shows the maximum‐a‐posteriori estimator for the fractions of mutant alleles and the standard deviations. C: Comparison of the fractions of mutant alleles measured by PASM (y axis) against those measured by two other quantitative technologies (x axis) including pyrosequencing (DS002, DS003, DS004, and DS005) and RainDrop digital PCR (DS001 and DS004). Standard deviations of the fractions of mutant alleles were calculated from two to six technical replicates using PASM. Detailed results are shown in Supp. Figs. S2 and S3.
Figure 4
Figure 4
Features of SCN1A mutations and genotype–phenotype correlations. A: Locations of the mutations on the domain structures of SCN1A protein. B: Proportions of epileptic phenotypes among parents with heterozygous mutations, mosaic mutations, and no detectable mutations in SCN1A, respectively. C: Comparison of the fractions of mutant alleles in mosaic parents with and without epileptic phenotypes. The difference was statistically significant (P = 0.016, single‐tail Wilcoxon rank sum test). D: Predicted level of changes in the local coil secondary structure caused by SCN1A mutations in mosaic parent with and without epileptic phenotype. The difference was statistically significant (P = 0.031, single‐tail Wilcoxon rank sum test).
Figure 5
Figure 5
Fractions of mutant alleles in multiple samples from the same mosaic parents, measured by Sanger sequencing and PASM. A: DS004 mother, measured by Sanger sequencing. B: DS004 mother, measured by PASM. C: DS001 father, measured by Sanger sequencing. D: DS001 father, measured by PASM. Standard deviations were calculated by technical replicates.
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