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Contains fulltext : 154153.pdf (publisher's version ) (Open Access), Clusters of functionally related genes can be disrupted by a single copy number variant (CNV). We demonstrate that the simultaneous disruption of multiple functionally related genes is a frequent and significant characteristic of de novo CNVs in patients with developmental disorders (P = 1 x 10(-3)). Using three different functional networks, we identified unexpectedly large numbers of functionally related genes within de novo CNVs from two large independent cohorts of individuals with developmental disorders. The presence of multiple functionally related genes was a significant predictor of a CNV's pathogenicity when compared to CNVs from apparently healthy individuals and a better predictor than the presence of known disease or haploinsufficient genes for larger CNVs. The functionally related genes found in the de novo CNVs belonged to 70% of all clusters of functionally related genes found across the genome. De novo CNVs were more likely to affect functional clusters and affect them to a greater extent than benign CNVs (P = 6 x 10(-4)). Furthermore, such clusters of functionally related genes are phenotypically informative: Different patients possessing CNVs that affect the same cluster of functionally related genes exhibit more similar phenotypes than expected (P < 0.05). The spanning of multiple functionally similar genes by single CNVs contributes substantially to how these variants exert their pathogenic effects.

Contains fulltext : 155339.PDF (publisher's version ) (Open Access), Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Item does not contain fulltext, 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.

Contains fulltext : 122877.pdf (publisher's version ) (Open Access)

01 april 2010, Contains fulltext : 87854.pdf (publisher's version ) (Open Access), 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 Naive Bayesian Tree classifier, with LINE density and mouse knock-out phenotypes contributing most to the classifier's 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.

Contains fulltext : 80641.pdf (publisher's version ) (Open Access), Rare copy number variants (CNVs) are frequently associated with common neurological disorders such as mental retardation (MR; learning disability), autism, and schizophrenia. CNV screening in clinical practice is limited because pathological CNVs cannot be distinguished routinely from benign CNVs, and because genes underlying patients' phenotypes remain largely unknown. Here, we present a novel, statistically robust approach that forges links between 148 MR-associated CNVs and phenotypes from approximately 5,000 mouse gene knockout experiments. These CNVs were found to be significantly enriched in two classes of genes, those whose mouse orthologues, when disrupted, result in either abnormal axon or dopaminergic neuron morphologies. Additional enrichments highlighted correspondences between relevant mouse phenotypes and secondary presentations such as brain abnormality, cleft palate, and seizures. The strength of these phenotype enrichments (>100% increases) greatly exceeded molecular annotations (<30% increases) and allowed the identification of 78 genes that may contribute to MR and associated phenotypes. This study is the first to demonstrate how the power of mouse knockout data can be systematically exploited to better understand genetically heterogeneous neurological disorders.

Contains fulltext : 71198.pdf (publisher's version ) (Open Access), Copy number variation is a dominant contributor to genomic variation and may frequently underlie an individual's 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.