Summary Invertebrate model systems are powerful tools for studying human disease owing to their genetic tractability and ease of screening. We conducted a mosaic genetic screen of lethal mutations on the Drosophila X-chromosome to identify genes required for the development, function, and maintenance of the nervous system. We identified 165 genes, most of whose function has not been studied in vivo. In parallel, we investigated rare variant alleles in 1,929 human exomes from families with unsolved Mendelian disease. Genes that are essential in flies and have multiple human homologs were found to be likely to be associated with human diseases. Merging the human datasets with the fly genes allowed us to identify disease-associated mutations in six families and to provide insights into microcephaly associated with brain dysgenesis. This bidirectional synergism between fly genetics and human genomics facilitates the functional annotation of evolutionarily conserved genes involved in human health.

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Rhodopsin recycling via the retromer, rather than degradation through lysosomes, can alleviate light-induced photoreceptor degeneration in Drosophila.

We developed an algorithm, HMZDelFinder, that uses whole exome sequencing (WES) data to identify rare and intragenic homozygous and hemizygous (HMZ) deletions that may represent complete loss-of-function of the indicated gene. HMZDelFinder was applied to 4866 samples in the Baylor–Hopkins Center for Mendelian Genomics (BHCMG) cohort and detected 773 HMZ deletion calls (567 homozygous or 206 hemizygous) with an estimated sensitivity of 86.5% (82% for single-exonic and 88% for multi-exonic calls) and precision of 78% (53% single-exonic and 96% for multi-exonic calls). Out of 773 HMZDelFinder-detected deletion calls, 82 were subjected to array comparative genomic hybridization (aCGH) and/or breakpoint PCR and 64 were confirmed. These include 18 single-exon deletions out of which 8 were exclusively detected by HMZDelFinder and not by any of seven other CNV detection tools examined. Further investigation of the 64 validated deletion calls revealed at least 15 pathogenic HMZ deletions. Of those, 7 accounted for 17–50% of pathogenic CNVs in different disease cohorts where 7.1–11% of the molecular diagnosis solved rate was attributed to CNVs. In summary, we present an algorithm to detect rare, intragenic, single-exon deletion CNVs using WES data; this tool can be useful for disease gene discovery efforts and clinical WES analyses.

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