HGG Advances (Apr 2021)

Long-read genome sequencing for the molecular diagnosis of neurodevelopmental disorders

  • Susan M. Hiatt,
  • James M.J. Lawlor,
  • Lori H. Handley,
  • Ryne C. Ramaker,
  • Brianne B. Rogers,
  • E. Christopher Partridge,
  • Lori Beth Boston,
  • Melissa Williams,
  • Christopher B. Plott,
  • Jerry Jenkins,
  • David E. Gray,
  • James M. Holt,
  • Kevin M. Bowling,
  • E. Martina Bebin,
  • Jane Grimwood,
  • Jeremy Schmutz,
  • Gregory M. Cooper

Journal volume & issue
Vol. 2, no. 2
p. 100023

Abstract

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Summary: Exome and genome sequencing have proven to be effective tools for the diagnosis of neurodevelopmental disorders (NDDs), but large fractions of NDDs cannot be attributed to currently detectable genetic variation. This is likely, at least in part, a result of the fact that many genetic variants are difficult or impossible to detect through typical short-read sequencing approaches. Here, we describe a genomic analysis using Pacific Biosciences circular consensus sequencing (CCS) reads, which are both long (>10 kb) and accurate (>99% bp accuracy). We used CCS on six proband-parent trios with NDDs that were unexplained despite extensive testing, including genome sequencing with short reads. We identified variants and created de novo assemblies in each trio, with global metrics indicating these datasets are more accurate and comprehensive than those provided by short-read data. In one proband, we identified a likely pathogenic (LP), de novo L1-mediated insertion in CDKL5 that results in duplication of exon 3, leading to a frameshift. In a second proband, we identified multiple large de novo structural variants, including insertion-translocations affecting DGKB and MLLT3, which we show disrupt MLLT3 transcript levels. We consider this extensive structural variation likely pathogenic. The breadth and quality of variant detection, coupled to finding variants of clinical and research interest in two of six probands with unexplained NDDs, support the hypothesis that long-read genome sequencing can substantially improve rare disease genetic discovery rates.

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