AUTHOR=Louw Nadja , Carstens Nadia , Lombard Zané ,  for DDD-Africa as members of the H3Africa Consortium 

TITLE=Incorporating CNV analysis improves the yield of exome sequencing for rare monogenic disorders—an important consideration for resource-constrained settings

JOURNAL=Frontiers in Genetics

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1277784

DOI=10.3389/fgene.2023.1277784

ISSN=1664-8021

ABSTRACT=Exome sequencing is a recommended first-tier diagnostic test for many rare monogenic diseases. It allows for the detection of both single nucleotide variants and copy number variants 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, but the incorporation of copy number variant analysis tools into variant calling pipelines has not yet been implemented routinely and chromosomal microarray is still more widely used to detect copy number variants. Research shows that combined single -and copy number variants 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, but not 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 as a significantly beneficial addition, with relatively low cost implications. Routine implementation in underrepresented populations and low resource settings will promote generation and sharing of CNV datasets and provide momentum to build core centres for this niche within genomic medicine.