ArticleResearch square2026
Consensus-based Detection of Aetiologic Copy Number Variants For Syndromic Orofacial Clefts Utilising Whole Exome Sequencing of Case Parent Trios.
Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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 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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