Mouse Phenome Database

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is an open source, web-based repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice and their derivatives. MPD is also a facility for query, analysis and in silico hypothesis testing. Currently MPD contains about 1400 phenotypic measurements contributed by research teams worldwide, including phenotypes relevant to human health such as cancer susceptibility, aging, obesity, susceptibility to infectious diseases, atherosclerosis, blood disorders and neurosensory disorders. Electronic access to centralized strain data enables investigators to select optimal strains for many systems-based research applications, including physiological studies, drug and toxicology testing, modeling disease processes and complex trait analysis. The ability to select strains for specific research applications by accessing existing phenotype data can bypass the need to (re)characterize strains, precluding major investments of time and resources. This functionality, in turn, accelerates research and leverages existing community resources. Since our last NAR reporting in 2007, MPD has added more community-contributed data covering more phenotypic domains and implemented several new tools and features, including a new interactive Tool Demo available through the MPD homepage (quick link: http://phenome.jax.org/phenome/trytools)

Allele-specific copy-number discovery from whole-genome and whole-exome sequencing

Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/

Common-variant associations with fragile X syndrome

Fragile X syndrome is rare but a prominent cause of intellectual disability. It is usually caused by a de novo mutation that occurs on multiple haplotypes and thus would not be expected to be detectible using genome-wide association (GWA). We conducted GWA in 89 male FXS cases and 266 male controls, and detected multiple genome-wide significant signals near FMR1 (odds ratio = 8.10, P = 2.5 × 10 −10 ). These findings withstood robust attempts at falsification. Fine-mapping yielded a minimum P = 1.13 × 10 −14 , but did not narrow the interval. Comprehensive functional genomic integration did not provide a mechanistic hypothesis. Controls carrying a risk haplotype had significantly longer FMR1 CGG repeats than controls with the protective haplotype (P = 4.75 × 10 −5 ), which may predispose toward increases in CGG number to the premutation range over many generations. This is a salutary reminder of the complexity of even “simple” monogenetic disorders

A customized and versatile high-density genotyping array for the mouse

We designed a high-density mouse genotyping array containing 623,124 SNPs that capture the known genetic variation present in the laboratory mouse. The array also contains 916,269 invariant genomic probes that are targeted to functional elements and regions known to harbor segmental duplications. The array opens the door to the characterization of genetic diversity, copy number variation, allele specific gene expression and DNA methylation and will extend the successes of human genome-wide association studies to the mouse

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia

The antipsychotic clozapine is uniquely effective in the management of schizophrenia; however, its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown, although genetic factors have an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed human leukocyte antigen (HLA) alleles, exome array and copy-number variation (CNV) analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (odds ratio (OR)=4.32, P=1.79 × 10−8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effec

Psychiatric gene discoveries shape evidence on ADHD's biology

The Wellcome Trust, MRC and Action Medical Research have provided ADHD research support for AT, PH, JM, NW, MJO, MCO; we also acknowledge support from NIH grants R1 3MH059126, R0 1MH62873 and R0 1MH081803 to Dr SV Faraone. Dr E Mick received funding through the UMass Center for Clinical and Translational Science (P30HD004147) supported by the NIH.A strong motivation for undertaking psychiatric gene discovery studies is to provide novel insights into unknown biology. Although attention-deficit hyperactivity disorder (ADHD) is highly heritable, and large, rare copy number variants (CNVs) contribute to risk, little is known about its pathogenesis and it remains commonly misunderstood. We assembled and pooled five ADHD and control CNV data sets from the United Kingdom, Ireland, United States of America, Northern Europe and Canada. Our aim was to test for enrichment of neurodevelopmental gene sets, implicated by recent exome-sequencing studies of (a) schizophrenia and (b) autism as a means of testing the hypothesis that common pathogenic mechanisms underlie ADHD and these other neurodevelopmental disorders. We also undertook hypothesis-free testing of all biological pathways. We observed significant enrichment of individual genes previously found to harbour schizophrenia de novo non-synonymous single-nucleotide variants (SNVs; P=5.4 × 10-4) and targets of the Fragile X mental retardation protein (P=0.0018). No enrichment was observed for activity-regulated cytoskeleton-associated protein (P=0.23) or N-methyl-D-aspartate receptor (P=0.74) post-synaptic signalling gene sets previously implicated in schizophrenia. Enrichment of ADHD CNV hits for genes impacted by autism de novo SNVs (P=0.019 for non-synonymous SNV genes) did not survive Bonferroni correction. Hypothesis-free testing yielded several highly significantly enriched biological pathways, including ion channel pathways. Enrichment findings were robust to multiple testing corrections and to sensitivity analyses that excluded the most significant sample. The findings reveal that CNVs in ADHD converge on biologically meaningful gene clusters, including ones now established as conferring risk of other neurodevelopmental disorders.Publisher PDFPeer reviewe

Evidence that duplications of 22q11.2 protect against schizophrenia.

A number of large, rare copy number variants (CNVs) are deleterious for neurodevelopmental disorders, but large, rare, protective CNVs have not been reported for such phenotypes. Here we show in a CNV analysis of 47 005 individuals, the largest CNV analysis of schizophrenia to date, that large duplications (1.5-3.0 Mb) at 22q11.2--the reciprocal of the well-known, risk-inducing deletion of this locus--are substantially less common in schizophrenia cases than in the general population (0.014% vs 0.085%, OR=0.17, P=0.00086). 22q11.2 duplications represent the first putative protective mutation for schizophrenia

Characterization of single gene copy number variants in schizophrenia

Background Genetic studies of schizophrenia have implicated numerous risk loci including several copy number variants (CNVs) of large effect and hundreds of loci of small effect. In only a few cases has a specific gene been clearly identified. Rare CNVs affecting a single gene offer a potential avenue to discovering schizophrenia risk genes. Methods CNVs were generated from exome-sequencing of 4,913 schizophrenia cases and 6,188 controls from Sweden. We integrated multiple CNV calling methods (XHMM and ExomeDepth) to expand our set of single-gene CNVs and leveraged two different approaches for validating these variants (qPCR and Nanostring). Results We found a significant excess of all rare CNVs (deletions p=0.0004, duplications p=0.0006) and single-gene CNVs (deletions p=0.04, duplications p=0.03) in schizophrenia cases compared to controls. An expanded set of CNVs generated from integrating multiple approaches showed a significant burden of deletions in 11/21 gene-sets previously implicated in schizophrenia and across all genes in those sets (p=0.008), although no tests survived correction. We performed an extensive validation of all deletions in the significant set of voltage-gated calcium channels among CNVs called from both exome-sequencing and genotyping arrays. In total, 4 exonic, single-gene deletions validated in cases and none in controls (p=0.039), of which all were identified by exome-sequencing. Conclusions These results point to the potential contribution of single-gene CNVs to schizophrenia, that the utility of exome-sequencing for CNV calling has yet to be maximized and single-gene CNVs should be included in gene focused studies using other classes of variation

Cardiovascular Response to Beta-Adrenergic Blockade or Activation in 23 Inbred Mouse Strains

We report the characterisation of 27 cardiovascular-related traits in 23 inbred mouse strains. Mice were phenotyped either in response to chronic administration of a single dose of the β-adrenergic receptor blocker atenolol or under a low and a high dose of the β-agonist isoproterenol and compared to baseline condition. The robustness of our data is supported by high trait heritabilities (typically H2>0.7) and significant correlations of trait values measured in baseline condition with independent multistrain datasets of the Mouse Phenome Database. We then focused on the drug-, dose-, and strain-specific responses to β-stimulation and β-blockade of a selection of traits including heart rate, systolic blood pressure, cardiac weight indices, ECG parameters and body weight. Because of the wealth of data accumulated, we applied integrative analyses such as comprehensive bi-clustering to investigate the structure of the response across the different phenotypes, strains and experimental conditions. Information extracted from these analyses is discussed in terms of novelty and biological implications. For example, we observe that traits related to ventricular weight in most strains respond only to the high dose of isoproterenol, while heart rate and atrial weight are already affected by the low dose. Finally, we observe little concordance between strain similarity based on the phenotypes and genotypic relatedness computed from genomic SNP profiles. This indicates that cardiovascular phenotypes are unlikely to segregate according to global phylogeny, but rather be governed by smaller, local differences in the genetic architecture of the various strains

Copy number variation in schizophrenia in Sweden

Schizophrenia is a highly heritable neuropsychiatric disorder of complex genetic etiology. Previous genome-wide surveys have revealed a greater burden of large, rare CNVs in schizophrenia cases and identified multiple rare recurrent CNVs that increase risk of schizophrenia although with incomplete penetrance and pleiotropic effects. Identification of additional recurrent CNVs and biological pathways enriched for schizophrenia CNVs requires greater sample sizes. We conducted a genome-wide survey for CNVs associated with schizophrenia using a Swedish national sample (4,719 cases and 5,917 controls). High-confidence CNV calls were generated using genotyping array intensity data and their effect on risk of schizophrenia was measured. Our data confirm increased burden of large, rare CNVs in schizophrenia cases as well as significant associations for recurrent 16p11.2 duplications, 22q11.2 deletions and 3q29 deletions. We report a novel association for 17q12 duplications (odds ratio=4.16, P=0.018), previously associated with autism and mental retardation but not schizophrenia. Intriguingly, gene set association analyses implicate biological pathways previously associated with schizophrenia through common variation and exome sequencing (calcium channel signaling and binding partners of the fragile X mental retardation protein). We found significantly increased burden of the largest CNVs (>500Kb) in genes present in the post-synaptic density, in genomic regions implicated via schizophrenia genome-wide association studies, and in gene products localized to mitochondria and cytoplasm. Our findings suggest that multiple lines of genomic inquiry – genome-wide screens for CNVs, common variation, and exonic variation – are converging on similar sets of pathways and/or genes