Systematic analysis of homozygous autosomal copy number losses in exomes improves diagnostic yield and uncovers ultra-rare recessive disorders.

Systematic analysis of copy number variants (CNVs) in large datasets is challenging, and there are limited studies of homozygous copy number losses in rare disease exomes. Here, we leveraged the genomic uniqueness and relative under-representation of the Indian population in the current public genomic databases and identified 42,386 possible homozygous losses (median 20 per individual) in a heterogeneous cohort of 2021 individuals with suspected Mendelian disorders, who had undergone exome sequencing using 12 different capture kits in a resource-limited setting. Employing a genomic position loss-count-based approach, we filtered 1224 rare homozygous loss calls in 718 individuals (median 1 per individual) for further analysis, thus significantly reducing the analysis burden. Clinical correlation and validation of these rare calls enabled 10 new diagnoses in 240 unsolved individuals. This led to a two-fold increase in diagnosis owing to homozygous deletions. Further analysis of the data and identification of additional affected individuals through collaboration led to identification of biallelic FILIP1 and FAM177A1 variants as causes of a syndromic arthrogryposis and a neuromuscular disorder respectively. Both conditions were recently reported as ultra-rare recessive disorders, thus validating our approach. We also show that biallelic loss-of-function TFCP2L1 variants cause chronic kidney disease and VPS36 variants cause a severe recessive neurodevelopmental disorder characterised by microcephaly, motor delay, agenesis of the corpus callosum, cerebellar atrophy, seizures, hypotonia, spasticity and early death. Overall, these results demonstrate a scalable approach to screen homozygous losses for improving diagnostic yield and discovering disease-genes in large exome cohorts.