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In the human genome, there are homozygous regions presenting as sizeable stretches, or ‘runs’ of homozygosity (ROH). The length of these ROH is dependent on the degree of shared parental ancestry, being longer in individuals descending from consanguineous marriages or those from isolated populations. Homozygosity mapping is a powerful tool in clinical genetics. It relies on the assumption that, due to identity-by-descent, individuals affected by a recessive disease are likely to have homozygous markers surrounding the disease locus. Consequently, the analysis of ROH shared by affected individuals in the same kindred often helps to identify the disease-causing gene. However, scanning the entire genome for blocks of homozygosity, especially in sporadic cases, is not a straight-forward task. Whole-exome sequencing (WES) has been shown to be an effective approach for finding pathogenic variants, particularly in highly heterogeneous genetic diseases. Nevertheless, the huge amount of data, especially variants of unknown clinical significance, and the presence of false-positives due to sequencing artifacts, makes WES analysis complex. This paper briefly reviews the different algorithms and bioinformatics tools available for ROH identification. We emphasize the importance of performing ROH analysis using WES data as an effective way to improve diagnostic yield.

Homozygosity Mapping using Whole-Exome Sequencing: A Valuable Approach for Pathogenic Variant Identification in Genetic Diseases