Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing
Abstract Background Congenital anomalies (CAs) encompass a wide spectrum of structural and functional abnormalities during fetal development, commonly presenting at birth. Identifying the cause of CA is essential for accurate diagnosis and treatment. Using a target-gene approach, genetic variants co...
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BMC
2025-01-01
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| Series: | Human Genomics |
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| Online Access: | https://doi.org/10.1186/s40246-024-00709-2 |
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| author | Jeong-Min Kim Hye-Won Cho Dong Mun Shin Oc-Hee Kim Jihyun Kim Hyeji Lee Gang-Hee Lee Joon-Yong An Misun Yang Heui Seung Jo Ja-Hyun Jang Yun Sil Chang Hyun-Young Park Mi-Hyun Park |
| author_facet | Jeong-Min Kim Hye-Won Cho Dong Mun Shin Oc-Hee Kim Jihyun Kim Hyeji Lee Gang-Hee Lee Joon-Yong An Misun Yang Heui Seung Jo Ja-Hyun Jang Yun Sil Chang Hyun-Young Park Mi-Hyun Park |
| author_sort | Jeong-Min Kim |
| collection | DOAJ |
| description | Abstract Background Congenital anomalies (CAs) encompass a wide spectrum of structural and functional abnormalities during fetal development, commonly presenting at birth. Identifying the cause of CA is essential for accurate diagnosis and treatment. Using a target-gene approach, genetic variants could be found in certain CA patients. However, some patients were genetically undiagnosed; therefore, it is imperative to identify the causative variants from whole genome sequence (WGS) data of these patients. Results An in-house pipeline utilizing DRAGEN-GATK-Hail was established for trio-based WGS data analysis (n = 18 undiagnosed CA patients and their parents) and thirty-five candidate variants, including SNV/Indel, CNV, and SV were identified. Among them, 10 variants of seven coding genes were selected as possible causal variants by variant pathogenicity, genotype–phenotype analysis, and a multidisciplinary team. Finally, functional validation of six genes including RYR3, NRXN1, FREM2, CSMD1, RARS1, and NOTCH1, revealed various phenotypes in zebrafish models that aligned with those observed in each patient. In addition to the above findings, eleven diagnostic variants initially discovered in a targeted-gene analysis from a previous study were also identified as diagnostic variants and the in-house pipeline demonstrated a significant advantage in accurately and efficiently identifying de novo variants (DNVs), compound heterozygous (CH), and homozygous variants. Conclusions Taken together, the in-house pipeline established in this study provides a highly valuable diagnostic tool for the identification of potential candidate variants in patients with CA. Further research into the molecular mechanisms related to the development of CAs could shed light on the functional aspects of these genetic variations and contribute to the development of therapeutic drugs. |
| format | Article |
| id | doaj-art-ac73b12af07446538524647de58968fd |
| institution | Kabale University |
| issn | 1479-7364 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Human Genomics |
| spelling | doaj-art-ac73b12af07446538524647de58968fd2025-01-12T12:32:09ZengBMCHuman Genomics1479-73642025-01-0119111410.1186/s40246-024-00709-2Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencingJeong-Min Kim0Hye-Won Cho1Dong Mun Shin2Oc-Hee Kim3Jihyun Kim4Hyeji Lee5Gang-Hee Lee6Joon-Yong An7Misun Yang8Heui Seung Jo9Ja-Hyun Jang10Yun Sil Chang11Hyun-Young Park12Mi-Hyun Park13Division of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention AgencyDivision of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention AgencyDivision of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention AgencyDivision of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention AgencyDivision of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention AgencyDepartment of Integrated Biomedical and Life Science, Korea UniversityDepartment of Integrated Biomedical and Life Science, Korea UniversityDepartment of Integrated Biomedical and Life Science, Korea UniversityDepartment of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of MedicineDepartment of Pediatrics, Kangwon National University School Hospital, Kangwon National University School of MedicineDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of MedicineDepartment of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of MedicineKorea National Institute of Health, Korea Disease Control and Prevention AgencyDivision of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention AgencyAbstract Background Congenital anomalies (CAs) encompass a wide spectrum of structural and functional abnormalities during fetal development, commonly presenting at birth. Identifying the cause of CA is essential for accurate diagnosis and treatment. Using a target-gene approach, genetic variants could be found in certain CA patients. However, some patients were genetically undiagnosed; therefore, it is imperative to identify the causative variants from whole genome sequence (WGS) data of these patients. Results An in-house pipeline utilizing DRAGEN-GATK-Hail was established for trio-based WGS data analysis (n = 18 undiagnosed CA patients and their parents) and thirty-five candidate variants, including SNV/Indel, CNV, and SV were identified. Among them, 10 variants of seven coding genes were selected as possible causal variants by variant pathogenicity, genotype–phenotype analysis, and a multidisciplinary team. Finally, functional validation of six genes including RYR3, NRXN1, FREM2, CSMD1, RARS1, and NOTCH1, revealed various phenotypes in zebrafish models that aligned with those observed in each patient. In addition to the above findings, eleven diagnostic variants initially discovered in a targeted-gene analysis from a previous study were also identified as diagnostic variants and the in-house pipeline demonstrated a significant advantage in accurately and efficiently identifying de novo variants (DNVs), compound heterozygous (CH), and homozygous variants. Conclusions Taken together, the in-house pipeline established in this study provides a highly valuable diagnostic tool for the identification of potential candidate variants in patients with CA. Further research into the molecular mechanisms related to the development of CAs could shed light on the functional aspects of these genetic variations and contribute to the development of therapeutic drugs.https://doi.org/10.1186/s40246-024-00709-2Congenital AnomaliesWhole Genome SequencingGenetic VariantRare Disease |
| spellingShingle | Jeong-Min Kim Hye-Won Cho Dong Mun Shin Oc-Hee Kim Jihyun Kim Hyeji Lee Gang-Hee Lee Joon-Yong An Misun Yang Heui Seung Jo Ja-Hyun Jang Yun Sil Chang Hyun-Young Park Mi-Hyun Park Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing Human Genomics Congenital Anomalies Whole Genome Sequencing Genetic Variant Rare Disease |
| title | Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing |
| title_full | Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing |
| title_fullStr | Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing |
| title_full_unstemmed | Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing |
| title_short | Uncovering potential causal genes for undiagnosed congenital anomalies using an in-house pipeline for trio-based whole-genome sequencing |
| title_sort | uncovering potential causal genes for undiagnosed congenital anomalies using an in house pipeline for trio based whole genome sequencing |
| topic | Congenital Anomalies Whole Genome Sequencing Genetic Variant Rare Disease |
| url | https://doi.org/10.1186/s40246-024-00709-2 |
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