Biology subjects

MacArthur, D. G.

Publications and source records attributed to MacArthur, D. G..

8 recordsLinked to original sources

bioRxiv2018

Response to Shah et al: Using high-resolution variant frequencies empowers clinical genome interpretation and enables investigation of genetic architecture

Main text Main text Supplemental Data description Declaration of Interests Web Resources References Recent work by Shah and colleagues1 demonstrated that many variants in the ClinVar database2 are misclassified, and that disease-specific allele frequency (AF) thresholds can identify wrongly classified alleles by flagging variants that are too prevalent in the population to be causative of rare penetrant disease. While we agree with the main conclusions of this work, the authors compare their AF filtering approach to our recently published method3, concluding that the method we advanced \"may be prone to removing potentially pathogenic variants\". This is incorrect. Here we demonstrate that our approach is robust, and further illustrate the power of di ...

genomics↗

bioRxiv2018

The Genetic Landscape of Diamond-Blackfan Anemia

Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 1 in 100,000 to 200,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this genetically heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole exome sequencing (WES). Overall, we identified rare and predicted damaging mutations in likely causal genes for 78% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and in one of 19 previously reported genes encoding for a diverse set of ribosomal proteins (RPs). Using WES exon coverage estimates, we were able to identify and validate 31 deletions in DBA associated genes. We also observed an enrichment for extended splice site mutations and validated the diverse effects of these mutations using RNA sequencing in patientderived cell lines. Leveraging the size of our cohort, we observed several robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. In addition to comprehensively identifying mutations in known genes, we further identified rare mutations in 7 previously unreported RP genes that may cause DBA. We also identified several distinct disorders that appear to phenocopy DBA, including 9 individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain > 5% of DBA cases. Overall, this comprehensive report should not only inform clinical practice for DBA patients, but also the design and analysis of future rare variant studies for heterogeneous Mendelian disorders.

genetics↗

bioRxiv2017

Scaling accurate genetic variant discovery to tens of thousands of samples

Comprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel assembly-based approach to variant calling, the GATK HaplotypeCaller (HC) and Reference Confidence Model (RCM), that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously. We show by calling over 90,000 samples from the Exome Aggregation Consortium (ExAC) that, in contrast to other algorithms, the HC-RCM scales efficiently to very large sample sizes without loss in accuracy; and that the accuracy of indel variant calling is superior in comparison to other algorithms. More importantly, the HC-RCM produces a fully squared-off matrix of genotypes across all samples at every genomic position being investigated. The HC-RCM is a novel, scalable, assembly-based algorithm with abundant applications for population genetics and clinical studies.

genomics↗

bioRxiv2017

Regional missense constraint improves variant deleteriousness prediction

Given increasing numbers of patients who are undergoing exome or genome sequencing, it is critical to establish tools and methods to interpret the impact of genetic variation. While the ability to predict deleteriousness for any given variant is limited, missense variants remain a particularly challenging class of variation to interpret, since they can have drastically different effects depending on both the precise location and specific amino acid substitution of the variant. In order to better evaluate missense variation, we leveraged the exome sequencing data of 60,706 individuals from the Exome Aggregation Consortium (ExAC) dataset to identify sub-genic regions that are depleted of missense variation. We further used this depletion as part of a novel missense deleteriousness metric named MPC. We applied MPC to de novo missense variants and identified a category of de novo missense variants with the same impact on neurodevelopmental disorders as truncating mutations in intolerant genes, supporting the value of incorporating regional missense constraint in variant interpretation.

genomics↗

bioRxiv2017

Base-Specific Mutational Intolerance Near Splice-Sites Clarifies Role Of Non-Essential Splice Nucleotides

Variation in RNA splicing (i.e., alternative splicing) plays an important role in many diseases. Variants near 5' and 3' splice sites often affect splicing, but the effects of these variants on splicing and disease have not been fully characterized beyond the 2 \"essential\" splice nucleotides flanking each exon. Here we provide quantitative measurements of tolerance to mutational disruptions by position and reference allele-alternative allele combination. We show that certain reference alleles are particularly sensitive to mutations, regardless of the alternative alleles into which they are mutated. Using public RNA-seq data, we demonstrate that individuals carrying such variants have significantly lower levels of the correctly spliced transcript compared to individuals without them, and confirm that these specific substitutions are highly enriched for known Mendelian mutations. Our results propose a more refined definition of the \"splice region\" and offer a new way to prioritize and provide functional interpretation of variants identified in diagnostic sequencing and association studies.

genomics↗

bioRxiv2017

New mutations, old statistical challenges

Based on targeted sequencing of 208 genes in 11,730 neurodevelopmental disorder cases, Stessman et al. report the identification of 91 genes associated (at a False Discovery Rate [FDR] of 0.1) with autism spectrum disorders (ASD), intellectual disability (ID), and developmental delay (DD)--including what they characterize as 38 novel genes, not previously reported as connected with these diseases1.\n\nIf true, this would represent a substantial step forward. Unfortunately, each of the two discovery analyses (1. De novo mutation analysis and, 2. a comparison of private mutations with public control data) contain critical statistical flaws. When one accounts for these problems, fewer than half of the genes--and very few, if any, of the novel findings--survive. These errors have implications for how future analyses should be conducted, for understanding the genetic basis of these disorders, and for genomic medicine.\n\nWe discuss the two main ana ...

genetics↗

bioRxiv2017

Determining the impact of putative loss-of-function variants in protein-coding genes

Variants predicted to result in the loss of function (LoF) of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (Annotation of Loss-of-Function Transcripts), a method to annotate and predict the disease-causing potential of LoF variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between LoF variants deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo pLoF variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in > 6,500 cancer exomes shows that pLoF variants predicted to be deleterious by ALoFT are enriched in known driver genes.

genomics↗

bioRxiv2016

Pathogenic ASXL1 somatic variants in reference databases complicate germline variant interpretation for Bohring-Opitz Syndrome

The interpretation of genetic variants identified during clinical sequencing has come to rely heavily on reference population databases such as the Exome Aggregation Consortium (ExAC). Genuinely pathogenic variants, particularly in genes associated with severe autosomal dominant conditions, are assumed to be absent or extremely rare in these databases. Clinical exome sequencing of a six-year-old female patient with seizures, global developmental delay, dysmorphic features and failure to thrive identified an ASXL1 variant that was previously reported as causative of Bohring-Opitz syndrome (BOS). Surprisingly, the variant was observed seven times in the ExAC database, presumably in individuals without BOS. Although the BOS phenotype matched the presentation of the patient, the presence of the variant in reference population databases introduced ambiguity in result interpretation. Interrogation of the literature revealed that acquired somatic mosaicism of ASXL1 variants (including known pathogenic variants) during hematopoietic clonal expansion may be concomitant with aging in healthy individuals. We examined all high quality ASXL1 predicted truncating variant calls in the ExAC database and determined the majority could be attributed to this phenomenon. Failure to consider somatic mosaicism may lead to the inaccurate assumption that conditions like Bohring-Opitz syndrome have reduced penetrance, or the misclassification of potentially pathogenic variants.

genetics↗