Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases.
| Title: | Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases. |
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| Authors: | Tilemis FN; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Marinakis NM; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Research University Institute for the Study and Prevention of Genetic and Malignant Disease of Childhood, St. Sophia's Children's Hospital, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Veltra D; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Research University Institute for the Study and Prevention of Genetic and Malignant Disease of Childhood, St. Sophia's Children's Hospital, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Svingou M; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Kekou K; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Mitrakos A; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Research University Institute for the Study and Prevention of Genetic and Malignant Disease of Childhood, St. Sophia's Children's Hospital, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Tzetis M; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Kosma K; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Makrythanasis P; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Department of Genetic Medicine and Development, Medical School, University of Geneva, 1211 Geneva, Switzerland.; Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece.; Traeger-Synodinos J; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.; Sofocleous C; Laboratory of Medical Genetics, St. Sophia's Children's Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece. |
| Source: | Genes [Genes (Basel)] 2023 Jul 21; Vol. 14 (7). Date of Electronic Publication: 2023 Jul 21. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: MDPI Country of Publication: Switzerland NLM ID: 101551097 Publication Model: Electronic Cited Medium: Internet ISSN: 2073-4425 (Electronic) Linking ISSN: 20734425 NLM ISO Abbreviation: Genes (Basel) Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Basel : MDPI |
| MeSH Terms: | Rare Diseases* ; Algorithms*; DNA Copy Number Variations/genetics ; Humans ; Exome Sequencing ; Data Analysis |
| Abstract: | Whole-Exome Sequencing (WES) has proven valuable in the characterization of underlying genetic defects in most rare diseases (RDs). Copy Number Variants (CNVs) were initially thought to escape detection. Recent technological advances enabled CNV calling from WES data with the use of accurate and highly sensitive bioinformatic tools. Amongst 920 patients referred for WES, 454 unresolved cases were further analysed using the ExomeDepth algorithm. CNVs were called, evaluated and categorized according to ACMG/ClinGen recommendations. Causative CNVs were identified in 40 patients, increasing the diagnostic yield of WES from 50.7% (466/920) to 55% (506/920). Twenty-two CNVs were available for validation and were all confirmed; of these, five were novel. Implementation of the ExomeDepth tool promoted effective identification of phenotype-relevant and/or novel CNVs. Among the advantages of calling CNVs from WES data, characterization of complex genotypes comprising both CNVs and SNVs minimizes cost and time to final diagnosis, while allowing differentiation between true or false homozygosity, as well as compound heterozygosity of variants in AR genes. The use of a specific algorithm for calling CNVs from WES data enables ancillary detection of different types of causative genetic variants, making WES a critical first-tier diagnostic test for patients with RDs. |
| Competing Interests: | The authors declare no conflict of interest. |
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| Contributed Indexing: | Keywords: Copy Number Variants; ExomeDepth; Whole-Exome Sequencing; complex genotypes; diagnostic yield; rare diseases |
| Entry Date(s): | Date Created: 20230729 Date Completed: 20230731 Latest Revision: 20230801 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC10379589 |
| DOI: | 10.3390/genes14071490 |
| PMID: | 37510394 |
| Database: | MEDLINE |
Journal Article