Reanalysis and optimisation of bioinformatic pipelines is critical for mutation detection

Hum Mutat. 2019 Apr;40(4):374-379. doi: 10.1002/humu.23699. Epub 2019 Jan 31.

Abstract

Rapid advances in genomic technologies have facilitated the identification pathogenic variants causing human disease. We report siblings with developmental and epileptic encephalopathy due to a novel, shared heterozygous pathogenic 13 bp duplication in SYNGAP1 (c.435_447dup, p.(L150Vfs*6)) that was identified by whole genome sequencing (WGS). The pathogenic variant had escaped earlier detection via two methodologies: whole exome sequencing and high-depth targeted sequencing. Both technologies had produced reads carrying the variant, however, they were either not aligned due to the size of the insertion or aligned to multiple major histocompatibility complex (MHC) regions in the hg19 reference genome, making the critical reads unavailable for variant calling. The WGS pipeline followed different protocols, including alignment of reads to the GRCh37 reference genome, which lacks the additional MHC contigs. Our findings highlight the benefit of using orthogonal clinical bioinformatic pipelines and all relevant inheritance patterns to re-analyze genomic data in undiagnosed patients.

Keywords: clinical bioinformatics, de novo; developmental and epileptic encephalopathy, whole genome sequencing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • DNA Mutational Analysis / methods*
  • Genetic Association Studies / methods
  • Genome, Human
  • Genomics / methods
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Mutation*
  • Phenotype