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Feng X, Ping J, Gao S, Han D, Song W, Li X, Tao Y, Wang L. Novel JAG1 variants leading to Alagille syndrome in two Chinese cases. Sci Rep 2024; 14:1812. [PMID: 38245625 PMCID: PMC10799942 DOI: 10.1038/s41598-024-52357-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 01/17/2024] [Indexed: 01/22/2024] Open
Abstract
Alagille Syndrome (ALGS) is a complex genetic disorder characterized by cholestasis, congenital cardiac anomalies, and butterfly vertebrae. The variable phenotypic expression of ALGS can lead to challenges in accurately diagnosing affected infants, potentially resulting in misdiagnoses or underdiagnoses. This study highlights novel JAG1 gene mutations in two cases of ALGS. The first case with a novel p.Pro325Leufs*87 variant was diagnosed at 2 months of age and exhibited a favorable prognosis and an unexpected manifestation of congenital hypothyroidism. Before the age of 2, the second patient was incorrectly diagnosed with liver structural abnormalities, necessitating extensive treatment. In addition, he exhibited delays in language acquisition that may have been a result of SNAP25 haploinsufficiency. The identification of ALGS remains challenging, highlighting the importance of early detection and genetic testing for effective patient management. The variant p.Pro325Leufs*87 is distinct from reported variants linked to congenital hypothyroidism in ALGS patients, thereby further confirming the clinical and genetic complexity of ALGS. This emphasizes the critical need for individualized and innovative approaches to diagnosis and medical interventions, uniquely intended to address the complexity of this syndrome.
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Affiliation(s)
- Xiufang Feng
- Department of Pediatrics, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China
| | - Jiangyuan Ping
- Department of Pediatrics, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China
| | - Shan Gao
- Department of Pediatrics, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China
| | - Dong Han
- Medical Genetic Center, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China
| | - Wenxia Song
- Obstetrics Department, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China
| | - Xiaoze Li
- Medical Genetic Center, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China
| | - Yilun Tao
- Medical Genetic Center, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China.
- Precision Medicine Research Division, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China.
| | - Lihong Wang
- Department of Pediatrics, Changzhi Maternal and Child Health Care Hospital, Changzhi, Shanxi, China.
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Louw N, Carstens N, Lombard Z. Incorporating CNV analysis improves the yield of exome sequencing for rare monogenic disorders-an important consideration for resource-constrained settings. Front Genet 2023; 14:1277784. [PMID: 38155715 PMCID: PMC10753787 DOI: 10.3389/fgene.2023.1277784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 11/22/2023] [Indexed: 12/30/2023] Open
Abstract
Exome sequencing (ES) is a recommended first-tier diagnostic test for many rare monogenic diseases. It allows for the detection of both single-nucleotide variants (SNVs) and copy number variants (CNVs) in coding exonic regions of the genome in a single test, and this dual analysis is a valuable approach, especially in limited resource settings. Single-nucleotide variants are well studied; however, the incorporation of copy number variant analysis tools into variant calling pipelines has not been implemented yet as a routine diagnostic test, and chromosomal microarray is still more widely used to detect copy number variants. Research shows that combined single and copy number variant analysis can lead to a diagnostic yield of up to 58%, increasing the yield with as much as 18% from the single-nucleotide variant only pipeline. Importantly, this is achieved with the consideration of computational costs only, without incurring any additional sequencing costs. This mini review provides an overview of copy number variant analysis from exome data and what the current recommendations are for this type of analysis. We also present an overview on rare monogenic disease research standard practices in resource-limited settings. We present evidence that integrating copy number variant detection tools into a standard exome sequencing analysis pipeline improves diagnostic yield and should be considered a significantly beneficial addition, with relatively low-cost implications. Routine implementation in underrepresented populations and limited resource settings will promote generation and sharing of CNV datasets and provide momentum to build core centers for this niche within genomic medicine.
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Affiliation(s)
- Nadja Louw
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Nadia Carstens
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Genomics Platform, South African Medical Research Council, Cape Town, South Africa
| | - Zané Lombard
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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Song X, Li X, Liu X, Zhang Z, Ding X, Chai Y, Li Z, Wang H, Li J, Liang H, Sun X, Yang G, Qi Z, Chen F, Shi Q, Wang E, Ru B, Lei C, Chen H, Liu W, Huang Y. Copy number variation of the ZNF679 gene in cattle and its association analysis with growth traits. Anim Biotechnol 2023; 34:4680-4686. [PMID: 37093180 DOI: 10.1080/10495398.2023.2185628] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Copy number variation (CNV) is an important member of genetic structural variation that exists widely in animal genomes and is between 50 bp and several Mb in length and widely used in research's of animal genetics and breeding. ZNF679 is an important transcription factor, which has been found association with diseases in the human genome many times. This gene has also been found to be associated with cattle growth traits in previous re-sequencing studies. We tested the CNVs of the ZNF679 gene in 809 individuals from 7 Chinese cattle breeds and tested the association between the CNVs and growth traits in 552 individuals from 5 breeds. The results demonstrated the correlation the correlation between the CNVs of the ZNF679 gene and some Chinese cattle (QC cattle and XN cattle) growth traits. To sum up, this study indicated that ZNF679-CNVs can be used as a candidate gene for molecular genetic marker-assisted selection breeding for cattle growth traits to contribute to the development of genetic improvement of Chinese cattle.
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Affiliation(s)
- Xingya Song
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Xinmiao Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, People's Republic of China
| | - Xian Liu
- Henan Provincial Animal Husbandry General Station, Zhengzhou, Henan, People's Republic of China
| | - Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Xiaoting Ding
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Yanan Chai
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Zhiming Li
- Henan Provincial Animal Husbandry General Station, Zhengzhou, Henan, People's Republic of China
| | - Hongli Wang
- Jiaxian Animal Husbandry Bureau, Jiaxian Henan, People's Republic of China
| | - Jungang Li
- Jiaxian Animal Husbandry Bureau, Jiaxian Henan, People's Republic of China
| | - Huifeng Liang
- Jiaxian Animal Husbandry Bureau, Jiaxian Henan, People's Republic of China
| | - Xiaoyan Sun
- Jiaxian Animal Husbandry Bureau, Jiaxian Henan, People's Republic of China
| | - Guojie Yang
- Jiaxian Animal Husbandry Bureau, Jiaxian Henan, People's Republic of China
| | - Zengfang Qi
- Jiaxian Animal Husbandry Bureau, Jiaxian Henan, People's Republic of China
| | - Fuying Chen
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Qiaoting Shi
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Eryao Wang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Baorui Ru
- Henan Provincial Animal Husbandry General Station, Zhengzhou, Henan, People's Republic of China
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Hong Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Wujun Liu
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, People's Republic of China
| | - Yongzhen Huang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
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Brownstein CA, Douard E, Haynes RL, Koh HY, Haghighi A, Keywan C, Martin B, Alexandrescu S, Haas EA, Vargas SO, Wojcik MH, Jacquemont S, Poduri AH, Goldstein RD, Holm IA. Copy Number Variation and Structural Genomic Findings in 116 Cases of Sudden Unexplained Death between 1 and 28 Months of Age. ADVANCED GENETICS (HOBOKEN, N.J.) 2023; 4:2200012. [PMID: 36910592 PMCID: PMC10000288 DOI: 10.1002/ggn2.202200012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 08/31/2022] [Indexed: 11/09/2022]
Abstract
In sudden unexplained death in pediatrics (SUDP) the cause of death is unknown despite an autopsy and investigation. The role of copy number variations (CNVs) in SUDP has not been well-studied. Chromosomal microarray (CMA) data are generated for 116 SUDP cases with age at death between 1 and 28 months. CNVs are classified using the American College of Medical Genetics and Genomics guidelines and CNVs in our cohort are compared to an autism spectrum disorder (ASD) cohort, and to a control cohort. Pathogenic CNVs are identified in 5 of 116 cases (4.3%). Variants of uncertain significance (VUS) favoring pathogenic CNVs are identified in 9 cases (7.8%). Several CNVs are associated with neurodevelopmental phenotypes including seizures, ASD, developmental delay, and schizophrenia. The structural variant 47,XXY is identified in two cases (2/69 boys, 2.9%) not previously diagnosed with Klinefelter syndrome. Pathogenicity scores for deletions are significantly elevated in the SUDP cohort versus controls (p = 0.007) and are not significantly different from the ASD cohort. The finding of pathogenic or VUS favoring pathogenic CNVs, or structural variants, in 12.1% of cases, combined with the observation of higher pathogenicity scores for deletions in SUDP versus controls, suggests that CMA should be included in the genetic evaluation of SUDP.
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Abstract
Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed a wide variety of cytogenetic and molecular methods with different detection capabilities to detect clinically relevant CNVs. In this review, we summarize methodological progress from conventional approaches to current state of the art techniques capable of detecting CNVs from a few bases up to several megabases. Although the recent rapid progress of sequencing methods has enabled precise detection of CNVs, determining their functional effect on cellular and whole-body physiology remains a challenge. Here, we provide a comprehensive list of databases and bioinformatics tools that may serve as useful assets for researchers, laboratory diagnosticians, and clinical geneticists facing the challenge of CNV detection and interpretation.
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