Genome-wide profiling of highly similar paralogous genes using HiFi sequencing
Xiao Chen, D. N. Baker, Egor Dolzhenko, Joseph M. Devaney, Jessica Noya, April Berlyoung, Rhonda Brandon, Kathleen S. Hruska, Lucas Lochovsky, Paul Kruszka, Scott Newman, Emily Farrow, Isabelle Thiffault, Tomi Pastinen, Dalia Kasperavičiūtė, Christian Gilissen, Lisenka E.L.M. Vissers, Alexander Hoischen, Seth Berger, Éric Vilain, Emmanuèle C. Délot, Andrea J. Cohen, Arthur Ko, Georgia Pitsava, Lightning Auriga, Ya Cui, Changrui Xiao, Charles H. King, Ivan De Dios, Jonathan LoTempio, Miguel Almalvez, Vincent A. Fusaro, Wei Li, Jamie L. Fraser, Meghan Delaney, Leandros Boukas, Bojan Losic, Esther Yun-Hua Hsiao, John Harting, Krista Bluske, Rachid Karam, Sami Belhadj, Michael A. Eberle
Abstract
Variant calling is hindered in segmental duplications by sequence homology. We developed Paraphase, a HiFi-based informatics method that resolves highly similar genes by phasing all haplotypes of paralogous genes together. We applied Paraphase to 160 long (>10 kb) segmental duplication regions across the human genome with high (>99%) sequence similarity, encoding 316 genes. Analysis across five ancestral populations revealed highly variable copy numbers of these regions. We identified 23 paralog groups with exceptionally low within-group diversity, where extensive gene conversion and unequal crossing over contribute to highly similar gene copies. Furthermore, our analysis of 36 trios identified 7 de novo SNVs and 4 de novo gene conversion events, 2 of which are non-allelic. Finally, we summarized extensive genetic diversity in 9 medically relevant genes previously considered challenging to genotype. Paraphase provides a framework for resolving gene paralogs, enabling accurate testing in medically relevant genes and population-wide studies of previously inaccessible genes. Here, the authors present Paraphase, a HiFi-based informatics method that resolves highly similar genes located in segmental duplications. They apply Paraphase to 316 paralogous genes and summarize extensive genetic diversity across populations.