WormBase: a multi-species resource for nematode biology and genomics

WormBase (http://www.wormbase.org/) is the central data repository for information about Caenorhabditis elegans and related nematodes. As a model organism database, WormBase extends beyond the genomic sequence, integrating experimental results with extensively annotated views of the genome. The WormBase Consortium continues to expand the biological scope and utility of WormBase with the inclusion of large-scale genomic analyses, through active data and literature curation, through new analysis and visualization tools, and through refinement of the user interface. Over the past year, the nearly complete genomic sequence and comparative analyses of the closely related species Caenorhabditis briggsae have been integrated into WormBase, including gene predictions, ortholog assignments and a new synteny viewer to display the relationships between the two species. Extensive site-wide refinement of the user interface now provides quick access to the most frequently accessed resources and a consistent browsing experience across the site. Unified single-page views now provide complete summaries of commonly accessed entries like genes. These advances continue to increase the utility of WormBase for C.elegans researchers, as well as for those researchers exploring problems in functional and comparative genomics in the context of a powerful genetic system

Identification of PKD1L1 Gene Variants in Children with the Biliary Atresia Splenic Malformation Syndrome

Biliary atresia (BA) is the most common cause of end‐stage liver disease in children and the primary indication for pediatric liver transplantation, yet underlying etiologies remain unknown. Approximately 10% of infants affected by BA exhibit various laterality defects (heterotaxy) including splenic abnormalities and complex cardiac malformations — a distinctive subgroup commonly referred to as the biliary atresia splenic malformation (BASM) syndrome. We hypothesized that genetic factors linking laterality features with the etiopathogenesis of BA in BASM patients could be identified through whole exome sequencing (WES) of an affected cohort. DNA specimens from 67 BASM subjects, including 58 patient‐parent trios, from the NIDDK‐supported Childhood Liver Disease Research Network (ChiLDReN) underwent WES. Candidate gene variants derived from a pre‐specified set of 2,016 genes associated with ciliary dysgenesis and/or dysfunction or cholestasis were prioritized according to pathogenicity, population frequency, and mode of inheritance. Five BASM subjects harbored rare and potentially deleterious bi‐allelic variants in polycystin 1‐like 1, PKD1L1, a gene associated with ciliary calcium signaling and embryonic laterality determination in fish, mice and humans. Heterozygous PKD1L1 variants were found in 3 additional subjects. Immunohistochemical analysis of liver from the one BASM subject available revealed decreased PKD1L1 expression in bile duct epithelium when compared to normal livers and livers affected by other non‐cholestatic diseases. Conclusion WES identified bi‐allelic and heterozygous PKD1L1 variants of interest in 8 BASM subjects from the ChiLDReN dataset. The dual roles for PKD1L1 in laterality determination and ciliary function suggest that PKD1L1 is a new, biologically plausible, cholangiocyte‐expressed candidate gene for the BASM syndrome

Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children: Novel Obesity Loci in Hispanic Children

Perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity

WormBase: a comprehensive data resource for Caenorhabditis biology and genomics

WormBase (http://www.wormbase.org), the model organism database for information about Caenorhabditis elegans and related nematodes, continues to expand in breadth and depth. Over the past year, WormBase has added multiple large-scale datasets including SAGE, interactome, 3D protein structure datasets and NCBI KOGs. To accommodate this growth, the International WormBase Consortium has improved the user interface by adding new features to aid in navigation, visualization of large-scale datasets, advanced searching and data mining. Internally, we have restructured the database models to rationalize the representation of genes and to prepare the system to accept the genome sequences of three additional Caenorhabditis species over the coming year

Deep resequencing reveals excess rare recent variants consistent with explosive population growth

Accurately determining the distribution of rare variants is an important goal of human genetics, but resequencing of a sample large enough for this purpose has been unfeasible until now. Here, we applied Sanger sequencing of genomic PCR amplicons to resequence the diabetes-associated genes KCNJ11 and HHEX in 13,715 people (10,422 European Americans and 3,293 African Americans) and validated amplicons potentially harbouring rare variants using 454 pyrosequencing. We observed far more variation (expected variant-site count ∼578) than would have been predicted on the basis of earlier surveys, which could only capture the distribution of common variants. By comparison with earlier estimates based on common variants, our model shows a clear genetic signal of accelerating population growth, suggesting that humanity harbours a myriad of rare, deleterious variants, and that disease risk and the burden of disease in contemporary populations may be heavily influenced by the distribution of rare variants

Patterns and rates of exonic de novo mutations in autism spectrum disorders

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified1,2. To identify further genetic risk factors, we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n= 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant and the overall rate of mutation is only modestly higher than the expected rate. In contrast, there is significantly enriched connectivity among the proteins encoded by genes harboring de novo missense or nonsense mutations, and excess connectivity to prior ASD genes of major effect, suggesting a subset of observed events are relevant to ASD risk. The small increase in rate of de novo events, when taken together with the connections among the proteins themselves and to ASD, are consistent with an important but limited role for de novo point mutations, similar to that documented for de novo copy number variants. Genetic models incorporating these data suggest that the majority of observed de novo events are unconnected to ASD, those that do confer risk are distributed across many genes and are incompletely penetrant (i.e., not necessarily causal). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5 to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favor of CHD8 and KATNAL2 as genuine autism risk factors

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al

A framework for the interpretation of de novo mutation in human disease

Spontaneously arising (‘de novo’) mutations play an important role in medical genetics. For diseases with extensive locus heterogeneity – such as autism spectrum disorders (ASDs) – the signal from de novo mutations (DNMs) is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. We provide a statistical framework for the analysis of DNM excesses per gene and gene set by calibrating a model of de novo mutation. We applied this framework to DNMs collected from 1,078 ASD trios and – while affirming a significant role for loss-of-function (LoF) mutations – found no excess of de novo LoF mutations in cases with IQ above 100, suggesting that the role of DNMs in ASD may reside in fundamental neurodevelopmental processes. We also used our model to identify ~1,000 genes that are significantly lacking functional coding variation in non-ASD samples and are enriched for de novo LoF mutations identified in ASD cases

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu