Long-read genome sequencing and variant reanalysis increase diagnostic yield in neurodevelopmental disorders
- Susan M. Hiatt1,
- James M.J. Lawlor1,
- Lori H. Handley1,
- Donald R. Latner1,
- Zachary T. Bonnstetter1,
- Candice R. Finnila1,
- Michelle L. Thompson1,
- Lori Beth Boston1,
- Melissa Williams1,
- Ivan Rodriguez Nunez1,
- Jerry Jenkins1,
- Whitley V. Kelley1,
- E. Martina Bebin2,
- Michael A. Lopez2,3,4,
- Anna C.E. Hurst4,
- Bruce R. Korf4,
- Jeremy Schmutz1,
- Jane Grimwood1 and
- Gregory M. Cooper1
- 1HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA;
- 2Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama 35924, USA;
- 3Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama 35924, USA;
- 4Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35924, USA
Abstract
Variant detection from long-read genome sequencing (lrGS) has proven to be 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 diseases 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, nine of which (8/96, ∼9.4%) harbored pathogenic or likely pathogenic variants. Nine probands (∼9.4%) had variants that were accurately called in both srGS and lrGS and represent changes to clinical interpretation, mostly from recently published gene-disease associations. Seven cases included variants that were only correctly interpreted in lrGS, including copy-number variants (CNVs), 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 srGS 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 data sets grow allowing for better variant-frequency annotation, the additional lrGS-only rare disease yield will grow over time.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.279227.124.
- Received February 29, 2024.
- Accepted August 19, 2024.
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see https://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
