Diana Mandelker1,2, Ryan J Schmidt1, Arunkanth Ankala3, Kristin McDonald Gibson4,2, Mark Bowser5, Himanshu Sharma5, Elizabeth Duffy5, Madhuri Hegde6, Avni Santani4, Matthew Lebo1,5, Birgit Funke5,7. 1. Department of Pathology, Harvard Medical School/Brigham and Women's Hospital, Boston, Massachusetts, USA. 2. Current affiliation: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA (D.M.); Medical Genetics, Invitae Corporation, San Francisco, California, USA (K.M.G.). 3. Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA. 4. Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. 5. Partners HealthCare Personalized Medicine, Laboratory for Molecular Medicine, Cambridge, Massachusetts, USA. 6. Emory Genetics Lab, Emory University School of Medicine, Atlanta, Georgia, USA. 7. Department of Pathology, Harvard Medical School/Massachusetts General Hospital, Boston, Massachusetts, USA.
Abstract
PURPOSE: Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. METHODS: This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. RESULTS: Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. CONCLUSION: This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.
PURPOSE: Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. METHODS: This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. RESULTS: Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. CONCLUSION: This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.
Authors: Mary Elizabeth Mathyer; Ashley M Quiggle; X F Colin C Wong; Simon L I J Denil; Monique G Kumar; Heather M Ciliberto; Susan J Bayliss; John E Common; Cristina de Guzman Strong Journal: Exp Dermatol Date: 2018-06-28 Impact factor: 3.960
Authors: David J Margolis; Nandita Mitra; Heather Gochnauer; Bradley Wubbenhorst; Kurt D'Andrea; Adam Kraya; Ole Hoffstad; Jayanta Gupta; Brian Kim; Albert Yan; Zelma Chiesa Fuxench; Katherine L Nathanson Journal: J Invest Dermatol Date: 2018-02-08 Impact factor: 8.551
Authors: Brian K Mannakee; Uthra Balaji; Agnieszka K Witkiewicz; Ryan N Gutenkunst; Erik S Knudsen Journal: Bioinformatics Date: 2018-05-15 Impact factor: 6.937