Different strategies for the detection of copy number variations from exome sequencing data

VALLOVÁ, Vladimíra, Kristína HANDZUŠOVÁ, Markéta WAYHELOVÁ, Petr BROŽ, Aneta MIKULÁŠOVÁ, Jan SMETANA, Renata GAILLYOVÁ and Petr KUGLÍK. Different strategies for the detection of copy number variations from exome sequencing data. In 14th European Cytogenomics Conference. 2023.

Basic information

• Original name: Different strategies for the detection of copy number variations from exome sequencing data
• Authors: VALLOVÁ, Vladimíra (703 Slovakia, guarantor, belonging to the institution), Kristína HANDZUŠOVÁ (703 Slovakia, belonging to the institution), Markéta WAYHELOVÁ (203 Czech Republic, belonging to the institution), Petr BROŽ (203 Czech Republic, belonging to the institution), Aneta MIKULÁŠOVÁ (203 Czech Republic), Jan SMETANA (203 Czech Republic, belonging to the institution), Renata GAILLYOVÁ (203 Czech Republic, belonging to the institution) and Petr KUGLÍK (203 Czech Republic, belonging to the institution).
• Edition: 14th European Cytogenomics Conference, 2023.

Other information

• Original language: English
• Type of outcome: Conference abstract
• Field of Study: 10603 Genetics and heredity
• Country of publisher: Austria
• Confidentiality degree: is not subject to a state or trade secret
• RIV identification code: RIV/00216224:14310/23:00131213
• Organization unit: Faculty of Science
• Keywords in English: exome sequencing; copy-number variations; neurodevelopmental disorders
• Tags: International impact

Abstract

The development of special algorithms has recently brought copy-number variation (CNV) detection by exome sequencing (ES) much more to the forefront. There is no one-size-fits-all approach for reliable detection of CNVs from ES data. On the contrary, many different approaches combining capture kits and bioinformatics approaches are being tested for their detection. Total of fifteen samples with twenty rare CNVs (14,5 kb – 8 Mb) - using high-resolution chromosomal microarray analysis (CMA) as a standard - were selected for comparison of two different capture designs and five different read-depth based CNV calling strategies: Human Core Exome (HCE) from Twist Biosciences (CNVRobot (CNVR), in-house pipeline (IHP)) and SureSelect All Exon v7 (SSEL) from Agilent Technologies (Circular Binary Segmentation (CBS), Hidden Markov Model (HMM), ExomeDepth). Of the twenty rare CNVs tested, three strategies (CNVR and IHP for HCE and ExomeDepth for SSEL) were able to identify all of them. The CBS- and HMM-based strategies (SSEL) missed three and two CNVs, respectively. Differences were observed between the size of CNVs obtained by CMA and by the different ES CNV calling strategies. These differences arise from the different CMA probes and ES targets distributions along with the variable bioinformatics pipeline settings in the case of ES. In addition, ES CNV calling was able to detect intra-exonic rearrangements (in ZC4H2, GRIN2A, BRCA1, RNF125 genes), confirmed by qPCR. In summary, ES is a suitable approach for CNV detection. However, its reliability strongly depends on sequencing quality and data uniformity. In general, the combination of different CNV calling strategies can improve the reliability of CNV detection from ES data. Supported by Ministry of Health of the Czech Republic, grant nr. NU20-07-00145 and by Ministry of Health, Czech Republic - conceptual development of research organization (FNBr, 65269705). All rights reserved.

Links

• NU20-07-00145, research and development project: Name: Úloha patogenních genetických variant detekovaných pomocí exomového sekvenování v etiologii dětských neurovývojových onemocnění

Investor: Ministry of Health of the CR, Subprogram 1 - standard