Caleb Webber

A radiation hybrid map of the rat genome containing 5,255 markers

A whole-genome radiation hybrid (RH) panel was used to construct a high-resolution map of the rat genome based on microsatellite and gene markers. These include 3,019 new microsatellite markers described here for the first time and 1,714 microsatellite markers with known genetic locations, allowing comparison and integration of maps from different sources. A robust RH framework map containing 1,030 positions ordered with odds of at least 1,000:1 has been defined as a tool for mapping these markers, and for future RH mapping in the rat. More than 500 genes which have been mapped in mouse and/or human were localized with respect to the rat RH framework, allowing the construction of detailed rat-mouse and rat-human comparative maps and illustrating the power of the RH approach for comparative mapping.

Natural genetic variation caused by small insertions and deletions in the human genome

Human genetic variation is expected to play a central role in personalized medicine. Yet only a fraction of the natural genetic variation that is harbored by humans has been discovered to date. Here we report almost 2 million small insertions and deletions (INDELs) that range from 1 bp to 10,000 bp in length in the genomes of 79 diverse humans. These variants include 819,363 small INDELs that map to human genes. Small INDELs frequently were found in the coding exons of these genes, and several lines of evidence indicate that such variation is a major determinant of human biological diversity. Microarray-based genotyping experiments revealed several interesting observations regarding the population genetics of small INDEL variation. For example, we found that many of our INDELs had high levels of linkage disequilibrium (LD) with both HapMap SNPs and with high-scoring SNPs from genome-wide association studies. Overall, our study indicates that small INDEL variation is likely to be a key factor underlying inherited traits and diseases in humans.

Clinical significance of de novo and inherited copy-number variation.

Copy‐number variations (CNVs) are a common cause of intellectual disability and/or multiple congenital anomalies (ID/MCA). However, the clinical interpretation of CNVs remains challenging, especially for inherited CNVs. Well‐phenotyped patients (5,531) with ID/MCA were screened for rare CNVs using a 250K single‐nucleotide polymorphism array platform in order to improve the understanding of the contribution of CNVs to a patients phenotype. We detected 1,663 rare CNVs in 1,388 patients (25.1%; range 0–5 per patient) of which 437 occurred de novo and 638 were inherited. The detected CNVs were analyzed for various characteristics, gene content, and genotype–phenotype correlations. Patients with severe phenotypes, including organ malformations, had more de novo CNVs (P < 0.001), whereas patient groups with milder phenotypes, such as facial dysmorphisms, were enriched for both de novo and inherited CNVs (P < 0.001), indicating that not only de novo but also inherited CNVs can be associated with a clinically relevant phenotype. Moreover, patients with multiple CNVs presented with a more severe phenotype than patients with a single CNV (P < 0.001), pointing to a combinatorial effect of the additional CNVs. In addition, we identified 20 de novo single‐gene CNVs that directly indicate novel genes for ID/MCA, including ZFHX4, ANKH, DLG2, MPP7, CEP89, TRIO, ASTN2, and PIK3C3.

Common variants in left/right asymmetry genes and pathways are associated with relative hand skill

Humans display structural and functional asymmetries in brain organization, strikingly with respect to language and handedness. The molecular basis of these asymmetries is unknown. We report a genome-wide association study meta-analysis for a quantitative measure of relative hand skill in individuals with dyslexia [reading disability (RD)] (n = 728). The most strongly associated variant, rs7182874 (P = 8.68×10−9), is located in PCSK6, further supporting an association we previously reported. We also confirmed the specificity of this association in individuals with RD; the same locus was not associated with relative hand skill in a general population cohort (n = 2,666). As PCSK6 is known to regulate NODAL in the development of left/right (LR) asymmetry in mice, we developed a novel approach to GWAS pathway analysis, using gene-set enrichment to test for an over-representation of highly associated variants within the orthologs of genes whose disruption in mice yields LR asymmetry phenotypes. Four out of 15 LR asymmetry phenotypes showed an over-representation (FDR≤5%). We replicated three of these phenotypes; situs inversus, heterotaxia, and double outlet right ventricle, in the general population cohort (FDR≤5%). Our findings lead us to propose that handedness is a polygenic trait controlled in part by the molecular mechanisms that establish LR body asymmetry early in development.

Reduced purifying selection prevails over positive selection in human copy number variant evolution

Copy number variation is a dominant contributor to genomic variation and may frequently underlie an individuals variable susceptibilities to disease. Here we question our previous proposition that copy number variants (CNVs) are often retained in the human population because of their adaptive benefit. We show that genic biases of CNVs are best explained, not by positive selection, but by reduced efficiency of selection in eliminating deleterious changes from the human population. Of four CNV data sets examined, three exhibit significant increases in protein evolutionary rates. These increases appear to be attributable to the frequent coincidence of CNVs with segmental duplications (SDs) that recombine infrequently. Furthermore, human orthologs of mouse genes, which, when disrupted, result in pre- or postnatal lethality, are unusually depleted in CNVs. Together, these findings support a model of reduced purifying selection (Hill-Robertson interference) within copy number variable regions that are enriched in nonessential genes, allowing both the fixation of slightly deleterious substitutions and increased drift of CNV alleles. Additionally, all four CNV sets exhibited increased rates of interspecies chromosomal rearrangement and nucleotide substitution and an increased gene density. We observe that sequences with high G+C contents are most prone to copy number variation. In particular, frequently duplicated human SD sequence, or CNVs that are large and/or observed frequently, tend to be elevated in G+C content. In contrast, SD sequences that appear fixed in the human population lie more frequently within low G+C sequence. These findings provide an overarching view of how CNVs arise and segregate in the human population.

GAT: a simulation framework for testing the association of genomic intervals.

Motivation: A common question in genomic analysis is whether two sets of genomic intervals overlap significantly. This question arises, for example, when interpreting ChIP-Seq or RNA-Seq data in functional terms. Because genome organization is complex, answering this question is non-trivial. Summary: We present Genomic Association Test (GAT), a tool for estimating the significance of overlap between multiple sets of genomic intervals. GAT implements a null model that the two sets of intervals are placed independently of one another, but allows each set’s density to depend on external variables, for example, isochore structure or chromosome identity. GAT estimates statistical significance based on simulation and controls for multiple tests using the false discovery rate. Availability: GAT’s source code, documentation and tutorials are available at http://code.google.com/p/genomic-association-tester. Contact: andreas.heger@dpag.ox.ac.uk

Systematic Phenomics Analysis Deconvolutes Genes Mutated in Intellectual Disability into Biologically Coherent Modules.

Intellectual disability (ID) disorders are genetically and phenotypically extremely heterogeneous. Can this complexity be depicted in a comprehensive way as a means of facilitating the understanding of ID disorders and their underlying biology? We provide a curated database of 746 currently known genes, mutations in which cause ID (ID-associated genes [ID-AGs]), classified according to ID manifestation and associated clinical features. Using this integrated resource, we show that ID-AGs are substantially enriched with co-expression, protein-protein interactions, and specific biological functions. Systematic identification of highly enriched functional themes and phenotypes revealed typical phenotype combinations characterizing process-defined groups of ID disorders, such as chromatin-related disorders and deficiencies in DNA repair. Strikingly, phenotype classification efficiently breaks down ID-AGs into subsets with significantly elevated biological coherence and predictive power. Custom-made functional Drosophila datasets revealed further characteristic phenotypes among ID-AGs and specific clinical classes. Our study and resource provide systematic insights into the molecular and clinical landscape of ID disorders, represent a significant step toward overcoming current limitations in ID research, and prove the utility of systematic human and cross-species phenomics analyses in highly heterogeneous genetic disorders.

Phenotype Ontologies and Cross-Species Analysis for Translational Research

The use of model organisms as tools for the investigation of human genetic variation has significantly and rapidly advanced our understanding of the aetiologies underlying hereditary traits. However, while equivalences in the DNA sequence of two species may be readily inferred through evolutionary models, the identification of equivalence in the phenotypic consequences resulting from comparable genetic variation is far from straightforward, limiting the value of the modelling paradigm. In this review, we provide an overview of the emerging statistical and computational approaches to objectively identify phenotypic equivalence between human and model organisms with examples from the vertebrate models, mouse and zebrafish. Firstly, we discuss enrichment approaches, which deem the most frequent phenotype among the orthologues of a set of genes associated with a common human phenotype as the orthologous phenotype, or phenolog, in the model species. Secondly, we introduce and discuss computational reasoning approaches to identify phenotypic equivalences made possible through the development of intra- and interspecies ontologies. Finally, we consider the particular challenges involved in modelling neuropsychiatric disorders, which illustrate many of the remaining difficulties in developing comprehensive and unequivocal interspecies phenotype mappings.

Accurate distinction of pathogenic from benign CNVs in mental retardation.

Copy number variants (CNVs) have recently been recognized as a common form of genomic variation in humans. Hundreds of CNVs can be detected in any individual genome using genomic microarrays or whole genome sequencing technology, but their phenotypic consequences are still poorly understood. Rare CNVs have been reported as a frequent cause of neurological disorders such as mental retardation (MR), schizophrenia and autism, prompting widespread implementation of CNV screening in diagnostics. In previous studies we have shown that, in contrast to benign CNVs, MR-associated CNVs are significantly enriched in genes whose mouse orthologues, when disrupted, result in a nervous system phenotype. In this study we developed and validated a novel computational method for differentiating between benign and MR-associated CNVs using structural and functional genomic features to annotate each CNV. In total 13 genomic features were included in the final version of a Naïve Bayesian Tree classifier, with LINE density and mouse knock-out phenotypes contributing most to the classifiers accuracy. After demonstrating that our method (called GECCO) perfectly classifies CNVs causing known MR-associated syndromes, we show that it achieves high accuracy (94%) and negative predictive value (99%) on a blinded test set of more than 1,200 CNVs from a large cohort of individuals with MR. These results indicate that this classification method will be of value for objectively prioritizing CNVs in clinical research and diagnostics.

Network topologies and convergent aetiologies arising from deletions and duplications observed in individuals with autism.

Autism Spectrum Disorders (ASD) are highly heritable and characterised by impairments in social interaction and communication, and restricted and repetitive behaviours. Considering four sets of de novo copy number variants (CNVs) identified in 181 individuals with autism and exploiting mouse functional genomics and known protein-protein interactions, we identified a large and significantly interconnected interaction network. This network contains 187 genes affected by CNVs drawn from 45% of the patients we considered and 22 genes previously implicated in ASD, of which 192 form a single interconnected cluster. On average, those patients with copy number changed genes from this network possess changes in 3 network genes, suggesting that epistasis mediated through the network is extensive. Correspondingly, genes that are highly connected within the network, and thus whose copy number change is predicted by the network to be more phenotypically consequential, are significantly enriched among patients that possess only a single ASD-associated network copy number changed gene (p = 0.002). Strikingly, deleted or disrupted genes from the network are significantly enriched in GO-annotated positive regulators (2.3-fold enrichment, corrected p = 2×10−5), whereas duplicated genes are significantly enriched in GO-annotated negative regulators (2.2-fold enrichment, corrected p = 0.005). The direction of copy change is highly informative in the context of the network, providing the means through which perturbations arising from distinct deletions or duplications can yield a common outcome. These findings reveal an extensive ASD-associated molecular network, whose topology indicates ASD-relevant mutational deleteriousness and that mechanistically details how convergent aetiologies can result extensively from CNVs affecting pathways causally implicated in ASD.