Locus heterogeneity characterizes a variety of skeletal dysplasias often due to interacting or overlapping signaling pathways. Robinow syndrome is a skeletal disorder historically refractory to molecular diagnosis, potentially stemming from substantial genetic heterogeneity. All current known pathogenic variants reside in genes within the noncanonical Wnt signaling pathway including ROR2, WNT5A, and more recently, DVL1 and DVL3. However, $70% of autosomal-dominant Robinow syndrome cases remain molecularly unsolved. To investigate this missing heritability, we recruited 21 families with at least one family member clinically diagnosed with Robinow or Robinow-like phenotypes and performed genetic and genomic studies. In total, four families with variants in FZD2 were identified as well as three individuals from two families with biallelic variants in NXN that co-segregate with the phenotype. Importantly, both FZD2 and NXN are relevant protein partners in the WNT5A interactome, supporting their role in skeletal development. In addition to confirming that clustered -1 frameshifting variants in DVL1 and DVL3 are the main contributors to dominant Robinow syndrome, we also found likely pathogenic variants in candidate genes GPC4 and RAC3, both linked to the Wnt signaling pathway. These data support an initial hypothesis that Robinow syndrome results from perturbation of the Wnt/PCP pathway, suggest specific relevant domains of the proteins involved, and reveal key contributors in this signaling cascade during human embryonic development. Contrary to the view that non-allelic genetic heterogeneity hampers gene discovery, this study demonstrates the utility of rare disease genomic studies to parse gene function in human developmental pathways.

PurposeMultilocus variation-pathogenic variants in two or more disease genes-can potentially explain the underlying genetic basis for apparent phenotypic expansion in cases for which the observed clinical features extend beyond those reported in association with a "known" disease gene.MethodsAnalyses focused on 106 patients, 19 for whom apparent phenotypic expansion was previously attributed to variation at known disease genes. We performed a retrospective computational reanalysis of whole-exome sequencing data using stringent Variant Call File filtering criteria to determine whether molecular diagnoses involving additional disease loci might explain the observed expanded phenotypes.ResultsMultilocus variation was identified in 31.6% (6/19) of families with phenotypic expansion and 2.3% (2/87) without phenotypic expansion. Intrafamilial clinical variability within two families was explained by multilocus variation identified in the more severely affected sibling.ConclusionOur findings underscore the role of multiple rare variants at different loci in the etiology of genetically and clinically heterogeneous cohorts. Intrafamilial phenotypic and genotypic variability allowed a dissection of genotype-phenotype relationships in two families. Our data emphasize the critical role of the clinician in diagnostic genomic analyses and demonstrate that apparent phenotypic expansion may represent blended phenotypes resulting from pathogenic variation at more than one locus.Genetics in Medicine advance online publication, 26 April 2018; doi:10.1038/gim.2018.33.

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.