medRxivGenetic & Genomic MedicinePreprint
The Refined Recurrence Risk of De Novo variants Due to Parental Mosaicism
Sonja NeuseriD, Natalie Ahmad, Denny Popp, Julia HentscheliD, Johannes R. LemkeiD, Knut KrohniD, Anna-Lisa Schween, Maike KarnstedtiD, Stephan DrukewitziD, John Wiedenhöft, Rami Abou JamraiD
Abstract
Parents of children with genetic disorders due to de novo variants are counselled on a recurrence risk estimate of 1-5% for further affected siblings, while the actual probability varies between 0 and 50%. This discrepancy is well known, but barely investigated. We enrolled 135 families, in which a child had been previously identified with a pathogenic seemingly de novo variant (in 140 genes). Covering two germ layers, we collected blood (n=269), buccal (n=223) and nail samples (n=223) of both parents and paternal semen (n=88). Using Nanopore long read sequencing, variants were phased to the parental allele of origin. We performed deep sequencing with unique molecular identifiers of all samples. We investigated for low mosaicism with plotting identified allele fractions and Bayesian analyses. We confirmed the results individually using amplicon-based, spiked-in deep sequencing. Phasing revealed 22% of variants have occurred on the maternal and 78% on the paternal allele. Median raw target read depth achieved >7,000x, reduced to 523x after collapsing across all tissues (n{approx}130,000 measured values). We identified mosaicism in either the mother (n=2) or the father (n=4): four of them as mixed mosaicism, two cases as paternal gonadal mosaicism. The alternative allele fraction varied from 1.1% to 23%, while the results of the Bayesian model correlated well with amplicon-based sequencing. With 4.4%, we observe a slightly lower number of parental mosaicism compared to the literature. We now apply the amplicon-based sequencing of tissue samples - including semen - to routine counselling of parents with an affected child for individual risk assessment.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- approach: Bayesian inference
- Citations
- 3
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