Long-read genome sequencing and variant reanalysis increase diagnostic yield in neurodevelopmental disorders
Susan M. HiattiD, James M.J. LawloriD, Lori H. HandleyiD, Donald R. LatneriD, Zachary T BonnstetteriD, Candice R. FinnilaiD, Michelle L. ThompsoniD, Lori Beth BostoniD, Melissa E. WilliamsiD, Iván Rodríguez-NuneziD, Jerry W. JenkinsiD, Whitley V. Kelley, Elizabeth Martina BebiniD, Michael A. LopeziD, Anna HurstiD, Bruce R. KorfiD, Jeremy SchmutziD, Jane GrimwoodiD, Gregory M. CooperiD
Abstract
Variant detection from long-read genome sequencing (lrGS) has proven to be considerably more accurate and comprehensive than variant detection from short-read genome sequencing (srGS). However, the rate at which lrGS can increase molecular diagnostic yield for rare disease is not yet precisely characterized. We performed lrGS using Pacific Biosciences "HiFi" technology on 96 short-read-negative probands with rare disease that were suspected to be genetic. We generated hg38-aligned variants and de novo phased genome assemblies, and subsequently annotated, filtered, and curated variants using clinical standards. New disease-relevant or potentially relevant genetic findings were identified in 16/96 (16.7%) probands, eight of which (8/96, 8.33%) harbored pathogenic or likely pathogenic variants. Newly identified variants were visible in both srGS and lrGS in nine probands ([~]9.4%) and resulted from changes to interpretation mostly from recent gene-disease association discoveries. Seven cases included variants that were only interpretable in lrGS, including copy-number variants, an inversion, a mobile element insertion, two low-complexity repeat expansions, and a 1 bp deletion. While evidence for each of these variants is, in retrospect, visible in srGS, they were either: not called within srGS data, were represented by calls with incorrect sizes or structures, or failed quality-control and filtration. Thus, while reanalysis of older data clearly increases diagnostic yield, we find that lrGS allows for substantial additional yield (7/96, 7.3%) beyond srGS. We anticipate that as lrGS analysis improves, and as lrGS datasets grow allowing for better variant frequency annotation, the additional lrGS-only rare disease yield will grow over time.
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