A novel approach for simultaneous detection of structural and single-nucleotide variants based on a combination of chromosome conformation capture and exome sequencing

Author:

Gridina MariaORCID,Lagunov TimofeyORCID,Belokopytova PolinaORCID,Torgunakov NikitaORCID,Nuriddinov MiroslavORCID,Nurislamov ArtemORCID,Nazarenko Lyudmila P,Kashevarova Anna AORCID,Lopatkina Maria EORCID,Belyaeva Elena OORCID,Salyukova Olga A,Cheremnykh Aleksandr DORCID,Suhanova Natalia N.,Minzhenkova Marina E,Markova Zhanna G,Demina Nina A.,Stepanchuk Yana,Khabarova AnnaORCID,Yan AlexandraORCID,Valeev Emil,Koksharova GalinaORCID,Grigor’eva Elena V,Kokh Natalia,Lukjanova Tatiana,Maximova Yulia,Musatova ElizavetaORCID,Shabanova Elena,Kechin Andrey,Khrapov Evgeniy,Boyarskih Uliana,Ryzhkova Oxana,Suntsova Maria,Matrosova Alina,Karoli Mikhail,Manakhov AndreyORCID,Filipenko Maxim,Rogaev EvgenyORCID,Shilova Nadezhda V,Lebedev Igor NORCID,Fishman VeniaminORCID

Abstract

AbstractEffective molecular diagnosis of congenital diseases hinges on comprehensive genomic analysis, traditionally reliant on various methodologies specific to each variant type—whole exome or genome sequencing for single nucleotide variants (SNVs), array CGH for copy-number variants (CNVs), and microscopy for structural variants (SVs). We introduce a novel, integrative approach combining exome sequencing with chromosome conformation capture, termed Exo-C. This method enables the concurrent identification of SNVs in clinically relevant genes and SVs across the genome and allows analysis of heterozygous and mosaic carriers. Enhanced with targeted long-read sequencing, Exo-C evolves into a cost-efficient solution capable of resolving complex SVs at base-pair accuracy. Through several case studies, we demonstrate how Exo-C’s multifaceted application can effectively uncover diverse causative variants and elucidate disease mechanisms in patients with rare disorders.

Publisher

Cold Spring Harbor Laboratory

Reference26 articles.

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4. Charm is a flexible pipeline to simulate chromosomal rearrangements on Hi-C-like data | bioRxiv. https://www.biorxiv.org/content/10.1101/2023.11.22.568374v1.

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