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Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Consensus-based Detection of Aetiologic Copy Number Variants For Syndromic Orofacial Clefts Utilising Whole Exome
Samuel Kanor Quaynor1, Gideon Okyere Mensah1, Tamara Busch2
1Kwame Nkrumah University of Science and Technology (KNUST).
Background:
Orofacial clefts (OFCs) are the most common craniofacial congenital anomalies, with complex aetiology involving both genetic and environmental factors. Most genetic studies on the condition have focused on the contribution of single nucleotide variants (SNVs) and small insertions and deletions (indels). However, the contribution of copy number variants (CNVs), especially in African populations, remains underexplored despite their known contribution to congenital anomalies. This study aimed to identify high-confidence CNVs contributing to the aetiology of syndromic OFCs in Ghanaian case parent trios using whole exome sequencing (WES) datasets.
Methods:
WES data from Ghanaian case parent trios were processed through a comprehensive five-phase pipeline. Following stringent quality control and preprocessing, CNVs were called using four independent tools, namely, cn.MOPS, CODEX, ExomeDepth, and GATK-gCNV. The called CNVs were merged through a consensus-based approach using BEDtools, requiring support from at least two tools to classify them as true CNVs. AnnotSV was used to annotate and classify CNVs, while VarElect was employed to prioritise CNVs based on clinical phenotypes. High-confidence CNVs were mapped to patient phenotypes and further interrogated for pathogenic potential using databases such as DECIPHER, ClinVar, Mouse Genome Informatics (MGI), and the Alliance of Genome Resources. Gene expression patterns utilized MGI, Zebrahub and CELLxGENE Discover. Finally, pathway enrichment and interaction analyses were performed using g:Profiler, the STRING database, and Cytoscape.
Results:
Several de novo and inherited CNVs were identified, including deletions and duplications involving key genes such as SHH, WBP11, and ADAMTS2, all of which are critically involved in craniofacial morphogenesis. In addition to known OFC-associated genes, the analysis identified novel CNV regions encompassing genes not previously linked to syndromic OFCs in humans, including HYDIN, FLI1, ETS1, RSPH10B2, and CCZ1B. These were prioritised based on their expression patterns in developmental models, suggesting potential functional relevance to OFC pathogenesis. Pathway enrichment analysis further identified significant biological processes associated with craniofacial, neurodevelopmental, and musculoskeletal development.
Conclusion:
This study highlights the value of CNV analysis in studies on the genetic aetiology of OFCs and supports broader inclusion of African genomic data to identify population-specific aetiologic variants, thereby enhancing understanding of pathophysiology and clinical care.
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