Journal
AMERICAN JOURNAL OF HUMAN GENETICS
Volume 102, Issue 1, Pages 142-155Publisher
CELL PRESS
DOI: 10.1016/j.ajhg.2017.12.007
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Funding
- Autism Speaks
- Canada Foundation for Innovation
- Canadian Institute for Advanced Research
- University of Toronto McLaughlin Centre
- Genome Canada/Ontario Genomics Institute
- Government of Ontario
- Canadian Institutes of Health Research (CIHR) [FDN-143295]
- Ontario Brain Institute
- Hospital for Sick Children Foundation
- CIHR Banting Postdoctoral Fellowship
- GlaxoSmithKline-CIHR Chair in Genome Sciences at the University of Toronto
- Hospital for Sick Children
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A remaining hurdle to whole-genome sequencing (WGS) becoming a first-tier genetic test has been accurate detection of copy-number variations (CNVs). Here, we used several datasets to empirically develop a detailed workflow for identifying germline CNVs >1 kb from short-read WGS data using read depth-based algorithms. Our workflow is comprehensive in that it addresses all stages of the CNV-detection process, including DNA library preparation, sequencing, quality control, reference mapping, and computational CNV identification. We used our workflow to detect rare, genic CNVs in individuals with autism spectrum disorder (ASD), and 120/120 such CNVs tested using orthogonal methods were successfully confirmed. We also identified 71 putative genic de novo CNVs in this cohort, which had a confirmation rate of 70%; the remainder were incorrectly identified as de novo due to false positives in the proband (7%) or parental false negatives (23%). In individuals with an ASD diagnosis in which both microarray and WGS experiments were performed, our workflow detected all clinically relevant CNVs identified by microarrays, as well as additional potentially pathogenic CNVs < 20 kb. Thus, CNVs of clinical relevance can be discovered from WGS with a detection rate exceeding microarrays, positioning WGS as a single assay for genetic variation detection.
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