The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

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The Ensembl Variant Effect Predictor.

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year.

/pdf/prevalence-and-architecture-of-de-novo-mutations-in-256ilqyi82.pdf

Prevalence and architecture of de novo mutations in developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders.

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Large-scale discovery of novel genetic causes of developmental disorders

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(14)61705-0.pdf

Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data

Exome sequencing of parent-offspring trios is a popular strategy for identifying causative genetic variants in children with rare diseases. This method owes its strength to the leveraging of inheritance information, which facilitates de novo variant calling, inference of compound heterozygosity, and the identification of inheritance anomalies. Uniparental disomy describes the inheritance of a homologous chromosome pair from only one parent. This aberration is important to detect in genetic disease studies because it can result in imprinting disorders and recessive diseases. We have developed a software tool to detect uniparental disomy from child-mother-father genotype data that uses a binomial test to identify chromosomes with a significant burden of uniparentally inherited genotypes. This tool is the first to read VCF-formatted genotypes, to perform integrated copy number filtering, and to use a statistical test inherently robust for use in platforms of varying genotyping density and noise characteristics. Simulations demonstrated superior accuracy compared with previously developed approaches. We implemented the method on 1057 trios from the Deciphering Developmental Disorders project, a trio-based rare disease study, and detected six validated events, a significant enrichment compared with the population prevalence of UPD (1 in 3500), suggesting that most of these events are pathogenic. One of these events represents a known imprinting disorder, and exome analyses have identified rare homozygous candidate variants, mainly in the isodisomic regions of UPD chromosomes, which, among other variants, provide targets for further genetic and functional evaluation.

/pdf/a-novel-method-for-detecting-uniparental-disomy-from-trio-3619ymluml.pdf

Ray Miller

Papers

Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data

A novel method for detecting uniparental disomy from trio genotypes identifies a significant excess in children with developmental disorders