Missense-depleted regions in population exomes implicate ras superfamily nucleotide-binding protein alteration in patients with brain malformation

Abstract

Genomic sequence interpretation can miss clinically relevant missense variants for several reasons. Rare missense variants are numerous in the exome and difficult to prioritise. Affected genes may also not have existing disease association. To improve variant prioritisation, we leverage population exome data to identify intragenic missense-depleted regions (MDRs) genome-wide that may be important in disease. We then use missense depletion analyses to help prioritise undiagnosed disease exome variants. We demonstrate application of this strategy to identify a novel gene association for human brain malformation. We identified de novo missense variants that affect the GDP/GTP-binding site of ARF1 in three unrelated patients. Corresponding functional analysis suggests ARF1 GDP/GTP-activation is affected by the specific missense mutations associated with heterotopia. These findings expand the genetic pathway underpinning neurologic disease that classically includes FLNA. ARF1 along with ARFGEF2 add further evidence implicating ARF/GEFs in the brain. Using functional ontology, top MDR-containing genes were highly enriched for nucleotide-binding function, suggesting these may be candidates for human disease. Routine consideration of MDR in the interpretation of exome data for rare diseases may help identify strong genetic factors for many severe conditions, infertility/reduction in reproductive capability, and embryonic conditions contributing to preterm loss.

Aggregation of population‐based genetic variation over protein domain homologues and its potential use in genetic diagnostics

“…To quantify genetic tolerance in genes, protein domains and domain homologues (Figure ) we made use of the d N / d S score rather than other well‐established tolerance scores such as pLI (Lek et al., ), RVIS (Petrovski et al., ), and subRVIS (Gussow et al., ). The d N / d S metric was originally intended for detecting selective evolutionary pressure in protein‐coding regions and genomes (Li, Wu, & Luo, ; Yang & Bielawski, ; Yang et al., ), and has previously been used by us and others to measure genetic tolerance and predict disease genes (Ge, Kwok, & Shieh, , ; Gilissen et al., ). Our choice for this score was motivated by the fact that the mentioned tolerance scores typically capture a more general notion of tolerance to genetic variation and are not designed to measure tolerance for any specific genic region of interest.…”

“…Moreover, the authors found that intolerance to genetic variation within genic sub-regions significantly correlates with reported pathogenic mutations. These patterns of region-specific variation in genetic tolerance were also used by Ge et al (2016) to detect missense-depleted regions to confirm the pathogenicity of individual variants of unknown significance.…”

Spatial Clustering of de Novo Missense Mutations Identifies Candidate Neurodevelopmental Disorder-Associated Genes

“…Therefore, we measured tolerance to variation as the ratio of missense over synonymous variation ''d N =d S ,'' which has been used by us and others previously for predicting disease genes. 2,41,42 We downloaded all PASS-filtered single nucleotide variants (SNVs) from ExAC (n ¼ 9,035,134) and constructed a ''d N =d S '' measure by counting the unique missense SNVs missense obs , and the unique synonymous SNVs synonymous obs , while correcting for sequence composition using the total possible unique missense and synonymous SNVs (missense bg and synonymous bg respectively): d N =d S ¼ ððmissense obs =missense bg Þ=ðsynonymous obs = synonymous bg ÞÞ (Table S16). Based on calculations of these scores for the sets of 116 NHI, and 183 HI genes, we indeed find that genes with mutations acting through a NHI mechanism are significantly more intolerant to missense variation than genes with mutations acting though a HI mechanism (p ¼ 2.24e-03; permutation test, Figure 2).…”

Formation of COPI-coated vesicles at a glance

“…Discussion of these roles is beyond the scope of this review (see textbox for some open questions). Based on its fundamental and diverse roles, COPI dysfunction culminates in disease (Bettayeb et al, 2016a,b;Ge et al, 2016;Hamada et al, 2004;Izumi et al, 2016;Watkin et al, 2015;Xu et al, 2010). Here, we address the different stages of COPI vesicle biogenesis and revisit them in the context of striking recent developments in elucidating the structure of the COPI coat.…”