Screening Human Embryos for Polygenic Traits Has Limited Utility.

The increasing proportion of variance in human complex traits explained by polygenic scores, along with progress in preimplantation genetic diagnosis, suggests the possibility of screening embryos for traits such as height or cognitive ability. However, the expected outcomes of embryo screening are unclear, which undermines discussion of associated ethical concerns. Here, we use theory, simulations, and real data to evaluate the potential gain of embryo screening, defined as the difference in trait value between the top-scoring embryo and the average embryo. The gain increases very slowly with the number of embryos but more rapidly with the variance explained by the score. Given current technology, the average gain due to screening would be ≈2.5 cm for height and ≈2.5 IQ points for cognitive ability. These mean values are accompanied by wide prediction intervals, and indeed, in large nuclear families, the majority of children top-scoring for height are not the tallest.

DPYSL2/CRMP2 isoform B knockout in human iPSC-derived glutamatergic neurons confirms its role in mTOR signaling and neurodevelopmental disorders.

The DPYSL2/CRMP2 gene encodes a microtubule-stabilizing protein crucial for neurogenesis and is associated with numerous psychiatric and neurodegenerative disorders including schizophrenia, bipolar disorder, and Alzheimer's disease. DPYSL2 generates multiple RNA and protein isoforms, but few studies have differentiated between them. We previously reported an association of a functional variant in the DPYSL2-B isoform with schizophrenia (SCZ) and demonstrated in HEK293 cells that this variant reduced the length of cellular projections and created transcriptomic changes that captured schizophrenia etiology by disrupting mTOR signaling-mediated regulation. In the present study, we follow up on these results by creating, to our knowledge, the first models of endogenous DPYSL2-B knockout in human induced pluripotent stem cells (iPSCs) and neurons. CRISPR/Cas9-faciliated knockout of DPYSL2-B in iPSCs followed by Ngn2-induced differentiation to glutamatergic neurons showed a reduction in DPYSL2-B/CRMP2-B RNA and protein with no observable impact on DPYSL2-A/CRMP2-A. The average length of dendrites in knockout neurons was reduced up to 58% compared to controls. Transcriptome analysis revealed disruptions in pathways highly relevant to psychiatric disease including mTOR signaling, cytoskeletal dynamics, immune function, calcium signaling, and cholesterol biosynthesis. We also observed a significant enrichment of the differentially expressed genes in SCZ-associated loci from genome-wide association studies (GWAS). Our findings expand our previous results to neuronal cells, clarify the functions of the human DPYSL2-B isoform and confirm its involvement in molecular pathologies shared between many psychiatric diseases.

Evaluating the mouse neural precursor line, SN4741, as a suitable proxy for midbrain dopaminergic neurons.

To overcome the ethical and technical limitations of in vivo human disease models, the broader scientific community frequently employs model organism-derived cell lines to investigate disease mechanisms, pathways, and therapeutic strategies. Despite the widespread use of certain in vitro models, many still lack contemporary genomic analysis supporting their use as a proxy for the affected human cells and tissues. Consequently, it is imperative to determine how accurately and effectively any proposed biological surrogate may reflect the biological processes it is assumed to model. One such cellular surrogate of human disease is the established mouse neural precursor cell line, SN4741, which has been used to elucidate mechanisms of neurotoxicity in Parkinson disease for over 25 years. Here, we are using a combination of classic and contemporary genomic techniques - karyotyping, RT-qPCR, single cell RNA-seq, bulk RNA-seq, and ATAC-seq - to characterize the transcriptional landscape, chromatin landscape, and genomic architecture of this cell line, and evaluate its suitability as a proxy for midbrain dopaminergic neurons in the study of Parkinson disease. We find that SN4741 cells possess an unstable triploidy and consistently exhibits low expression of dopaminergic neuron markers across assays, even when the cell line is shifted to the non-permissive temperature that drives differentiation. The transcriptional signatures of SN4741 cells suggest that they are maintained in an undifferentiated state at the permissive temperature and differentiate into immature neurons at the non-permissive temperature; however, they may not be dopaminergic neuron precursors, as previously suggested. Additionally, the chromatin landscapes of SN4741 cells, in both the differentiated and undifferentiated states, are not concordant with the open chromatin profiles of ex vivo, mouse E15.5 forebrain- or midbrain-derived dopaminergic neurons. Overall, our data suggest that SN4741 cells may reflect early aspects of neuronal differentiation but are likely not a suitable proxy for dopaminergic neurons as previously thought. The implications of this study extend broadly, illuminating the need for robust biological and genomic rationale underpinning the use of in vitro models of molecular processes.

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways.

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Polygenic risk scores differentiate schizophrenia patients with toxoplasma gondii compared to toxoplasma seronegative patients.

Schizophrenia (SCZ) is an etiologically heterogeneous disease with genetic and environmental risk factors (e.g., Toxoplasma gondii infection) differing among affected individuals. Distinguishing such risk factors may point to differences in pathophysiological pathways and facilitate the discovery of individualized treatments. Toxoplasma gondii (TOXO) has been implicated in increasing the risk of schizophrenia. To determine whether TOXO-positive individuals with SCZ have a different polygenic risk burden than uninfected people, we applied the SCZ polygenic risk score (SCZ-PRS) derived from the Psychiatric GWAS Consortium separately to the TOXO-positive and TOXO-negative subjects with the diagnosis of SCZ as the outcome variable. The SCZ-PRS does not include variants in the major histocompatibility complex. Of 790 subjects assessed for TOXO, the 662 TOXO-negative subjects (50.8% with SCZ) reached a Bonferroni corrected significant association (p = 0.00017, R2 = 0.023). In contrast, the 128 TOXO-positive individuals (53.1% with SCZ) showed no significant association (p = 0.354) for SCZ-PRS and had a much lower R2 (R2 = 0.007). To account for Type-2 error in the TOXO-positive dataset, we performed a random sampling of the TOXO-negative subpopulation (n = 130, repeated 100 times) to simulate equivalent power between groups: the p-value was <0.05 for SCZ-PRS 55% of the time but was rarely (6% of the time) comparable to the high p-value of the seropositive group at p > 0.354. We found intriguing evidence that the SCZ-PRS predicts SCZ in TOXO-negative subjects, as expected, but not in the TOXO-positive individuals. This result highlights the importance of considering environmental risk factors to distinguish a subgroup with independent or different genetic components involved in the development of SCZ.

Developing Treatments for Alzheimer's and Related Disorders with Precision Medicine: A Vision.

Precision medicine, also known as personalized medicine, is concerned with finding the right treatment for the right patient at the right time. It is a way of thinking focused on parsing heterogeneity ultimately down to the level of the individual. Its main mission is to identify characteristics of heterogeneous clinical conditions so as to target tailored therapies to individuals. Precision Medicine however is not an agnostic collection of all manner of clinical, genetic and other biologic data in select cohorts. This is an important point. Simply collecting as much information as possible on individuals without applying this way of thinking should not be considered Precision Medicine.

Schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk: A mediation analysis.

Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many data sets, analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points, and homogeneous cell types, the extent of this one-to-many relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a bystander and puts into question the direction of expression effect of on the risk, since the many variants-regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression data sets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both data sets 33 showed consistent mediation direction (Chi2 test p = 6 × 10-6 ). One might expect that the expression would correlate with the risk allele in the same direction it correlates with the disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different from expected directions.

Modeling Psychiatric Disorder Biology with Stem Cells.

PURPOSE OF REVIEW: We review the ways in which stem cells are used in psychiatric disease research, including the related advances in gene editing and directed cell differentiation. RECENT FINDINGS: The recent development of induced pluripotent stem cell (iPSC) technologies has created new possibilities for the study of psychiatric disease. iPSCs can be derived from patients or controls and differentiated to an array of neuronal and non-neuronal cell types. Their genomes can be edited as desired, and they can be assessed for a variety of phenotypes. This makes them especially interesting for studying genetic variation, which is particularly useful today now that our knowledge on the genetics of psychiatric disease is quickly expanding. The recent advances in cell engineering have led to powerful new methods for studying psychiatric illness including schizophrenia, bipolar disorder, and autism. There is a wide array of possible applications as illustrated by the many examples from the literature, most of which are cited here.

A screen of 1,049 schizophrenia and 30 Alzheimer's-associated variants for regulatory potential.

Recent genome-wide association studies (GWAS) identified numerous schizophrenia (SZ) and Alzheimer's disease (AD) associated loci, most outside protein-coding regions and hypothesized to affect gene transcription. We used a massively parallel reporter assay to screen, 1,049 SZ and 30 AD variants in 64 and nine loci, respectively for allele differences in driving reporter gene expression. A library of synthetic oligonucleotides assaying each allele five times was transfected into K562 chronic myelogenous leukemia lymphoblasts and SK-SY5Y human neuroblastoma cells. One hundred forty eight variants showed allelic differences in K562 and 53 in SK-SY5Y cells, on average 2.6 variants per locus. Nine showed significant differences in both lines, a modest overlap reflecting different regulatory landscapes of these lines that also differ significantly in chromatin marks. Eight of nine were in the same direction. We observe no preference for risk alleles to increase or decrease expression. We find a positive correlation between the number of SNPs in linkage disequilibrium and the proportion of functional SNPs supporting combinatorial effects that may lead to haplotype selection. Our results prioritize future functional follow up of disease associated SNPs to determine the driver GWAS variant(s), at each locus and enhance our understanding of gene regulation dynamics.

Linear models enable powerful differential activity analysis in massively parallel reporter assays.

BACKGROUND: Massively parallel reporter assays (MPRAs) have emerged as a popular means for understanding noncoding variation in a variety of conditions. While a large number of experiments have been described in the literature, analysis typically uses ad-hoc methods. There has been little attention to comparing performance of methods across datasets. RESULTS: We present the mpralm method which we show is calibrated and powerful, by analyzing its performance on multiple MPRA datasets. We show that it outperforms existing statistical methods for analysis of this data type, in the first comprehensive evaluation of statistical methods on several datasets. We investigate theoretical and real-data properties of barcode summarization methods and show an unappreciated impact of summarization method for some datasets. Finally, we use our model to conduct a power analysis for this assay and show substantial improvements in power by performing up to 6 replicates per condition, whereas sequencing depth has smaller impact; we recommend to always use at least 4 replicates. An R package is available from the Bioconductor project. CONCLUSIONS: Together, these results inform recommendations for differential analysis, general group comparisons, and power analysis and will help improve design and analysis of MPRA experiments.

HLA typing using genome wide data reveals susceptibility types for infections in a psychiatric disease enriched sample.

BACKGROUND: The infections Toxoplasma gondii (T. gondii), cytomegalovirus, and Herpes Simplex Virus Type 1 (HSV1) are common persistent infections that have been associated with schizophrenia and bipolar disorder. The major histocompatibility complex (MHC, termed HLA in humans) region has been implicated in these infections and these mental illnesses. The interplay of MHC genetics, mental illness, and infection has not been systematically examined in previous research. METHODS: In a cohort of 1636 individuals, we used genome-wide association data to impute 7 HLA types (A, B, C, DRB1, DQA1, DQB1, DPB1), and combined this data with serology data for these infections. We used regression analysis to assess the association between HLA alleles, infections (individually and collectively), and mental disorder status (schizophrenia, bipolar disorder, controls). RESULTS: After Bonferroni correction for multiple comparisons, HLA C∗07:01 was associated with increased HSV1 infection among mentally healthy controls (OR 3.4, p = 0.0007) but not in the schizophrenia or bipolar groups (P > 0.05). For the multiple infection outcome, HLA B∗ 38:01 and HLA C∗12:03 were protective in the healthy controls (OR ≈ 0.4) but did not have a statistically-significant effect in the schizophrenia or bipolar groups. T. gondii had several nominally-significant positive associations, including the haplotypes HLA DRB∗03:01 ∼ HLA DQA∗05:01 ∼ HLA DQB∗02:01 and HLA B∗08:01 ∼ HLA C∗07:01. CONCLUSIONS: We identified HLA types that showed strong and significant associations with neurotropic infections. Since some of these associations depended on mental illness status, the engagement of HLA-related pathways may be altered in schizophrenia due to immunogenetic differences or exposure history.

Multi-Trait Analysis of GWAS and Biological Insights Into Cognition: A Response to Hill (2018).

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.

Neuregulin 3 and its roles in schizophrenia risk and presentation.

Neuregulins, a four-member family of epidermal growth factor-like signaling molecules, have been studied for over two decades. They were first implicated in schizophrenia in 2002 with the detection of linkage and association at the NRG1 locus followed after a few years by NRG3. However, the associations with disease have not been very consistently observed. In contrast, association of NGR3 variants with disease presentation, specifically the presence of delusions, has been more consistent. This appears to be mediated by quantitative changes in the alternative splicing of the gene, which has also been consistently observed. Additional diseases and phenotypes, psychiatric or not, have also been connected with NRG3. These results demonstrate two important aspects of behavioral genetics research. The first is that if we only consider simple risk and fail to examine the details of each patient's individual phenotype, we will miss important insights on the disease biology. This is an important aspect of the goals of precision medicine. The second is that the functional consequences of variants are often more complex than simple alterations in levels of transcription of a particular gene, including, among others, regulation of alternative splicing. To accurately model and understand the biological consequences of phenotype-associated genetic variants, we need to study the biological consequences of each specific variant. Simply studying the consequences of a null allele of the orthologous gene in a model system, runs the risk of missing the many nuances of hypomorphic and/or gain of function variants in the genome of interest.

New targets for monitoring and therapy in Barth syndrome.

PURPOSE: Barth syndrome (BTHS), an X-linked disorder caused by defects in TAZ, is the only known single-gene disorder of cardiolipin remodeling. We hypothesized that through analysis of affected individuals, we would gain a better understanding of the range of clinical features and identify targets for monitoring and therapy. METHODS: We conducted a multidisciplinary investigation involving 42 patients with BTHS, including echocardiograms, muscle strength testing, functional exercise capacity testing, physical activity assessments, cardiolipin analysis, 3-methylglutaconic acid analysis, and review of genotype data. We analyzed data points to provide a quantitative spectrum of disease characteristics and to identify relationships among phenotype, genotype, and relevant metabolites. RESULTS: Echocardiography revealed considerable variability in cardiac features. By contrast, almost all patients had significantly reduced functional exercise capacity. Multivariate analysis revealed significant relationships between cardiolipin ratio and left ventricular mass and between cardiolipin ratio and functional exercise capacity. We additionally identified genotypes associated with a less severe metabolic and clinical profile. CONCLUSION: We defined previously unrecognized metabolite/phenotype/genotype relationships, established targets for therapeutic monitoring, and validated avenues for clinical assessment. In addition to providing insight into BTHS, these studies also provide insight into the myriad of multifactorial disorders that converge on the cardiolipin pathway.Genet Med 18 10, 1001-1010.

A population pharmacokinetic model for R- and S-citalopram and desmethylcitalopram in Alzheimer's disease patients with agitation.

The citalopram for Alzheimer's disease trial evaluated citalopram for the management for agitation in Alzheimer's disease patients. Sparse data was available from this elderly patient population. A nonlinear mixed effects population pharmacokinetic modeling approach was used to describe the pharmacokinetics of R- and S-citalopram and their primary metabolite (desmethylcitalopram). A structural model with 4 compartments (one compartment/compound) with linear oral absorption and elimination described the data adequately. Overall, the model showed that clearance of the R-enantiomer was slower than the clearance of the S-enantiomer. Without accounting for any patient-specific covariates, the population estimate of the metabolic clearance of citalopram was 8.6 (R-citalopram) and 14 L/h (S-citalopram). The population estimate of the clearance of desmethylcitalopram was 23.8 (R-Dcit) and 38.5 L/h (S-Dcit). Several patient-specific covariates were found to have a significant effect on the pharmacokinetics of R,S-citalopram and desmethylcitalopram. A significant difference in the metabolic clearance of R-citalopram between males and females (13 vs 9.05 L/h) was identified in this analysis. Both R- and S-citalopram metabolic clearance decreased with age. Additionally, consistent with literature reports S-citalopram metabolic clearance increased with increasing body weight and was significantly influenced by CYPC19 genotype, with a difference of 5.8 L/h between extensive/rapid and intermediate/poor metabolizers. R,S-desmethylcitalopram clearance increased with increasing body weight. This model may allow for the opportunity to delineate the effect of R- and S-citalopram on pharmacodynamics outcomes related to the management of agitation in Alzheimer's disease.

Genome-wide association study of schizophrenia in Ashkenazi Jews.

Schizophrenia is a common, clinically heterogeneous disorder associated with lifelong morbidity and early mortality. Several genetic variants associated with schizophrenia have been identified, but the majority of the heritability remains unknown. In this study, we report on a case-control sample of Ashkenazi Jews (AJ), a founder population that may provide additional insights into genetic etiology of schizophrenia. We performed a genome-wide association analysis (GWAS) of 592 cases and 505 controls of AJ ancestry ascertained in the US. Subsequently, we performed a meta-analysis with an Israeli AJ sample of 913 cases and 1640 controls, followed by a meta-analysis and polygenic risk scoring using summary results from Psychiatric GWAS Consortium 2 schizophrenia study. The U.S. AJ sample showed strong evidence of polygenic inheritance (pseudo-R(2) ∼9.7%) and a SNP-heritability estimate of 0.39 (P = 0.00046). We found no genome-wide significant associations in the U.S. sample or in the combined US/Israeli AJ meta-analysis of 1505 cases and 2145 controls. The strongest AJ specific associations (P-values in 10(-6) -10(-7) range) were in the 22q 11.2 deletion region and included the genes TBX1, GLN1, and COMT. Supportive evidence (meta P < 1 × 10(-4) ) was also found for several previously identified genome-wide significant findings, including the HLA region, CNTN4, IMMP2L, and GRIN2A. The meta-analysis of the U.S. sample with the PGC2 results provided initial genome-wide significant evidence for six new loci. Among the novel potential susceptibility genes is PEPD, a gene involved in proline metabolism, which is associated with a Mendelian disorder characterized by developmental delay and cognitive deficits.

Common genetic variation and schizophrenia polygenic risk influence neurocognitive performance in young adulthood.

Neurocognitive abilities constitute complex traits with considerable heritability. Impaired neurocognition is typically observed in schizophrenia (SZ), whereas convergent evidence has shown shared genetic determinants between neurocognition and SZ. Here, we report a genome-wide association study (GWAS) on neuropsychological and oculomotor traits, linked to SZ, in a general population sample of healthy young males (n = 1079). Follow-up genotyping was performed in an identically phenotyped internal sample (n = 738) and an independent cohort of young males with comparable neuropsychological measures (n = 825). Heritability estimates were determined based on genome-wide single-nucleotide polymorphisms (SNPs) and potential regulatory effects on gene expression were assessed in human brain. Correlations with general cognitive ability and SZ risk polygenic scores were tested utilizing meta-analysis GWAS results by the Cognitive Genomics Consortium (COGENT) and the Psychiatric Genomics Consortium (PGC-SZ). The GWAS results implicated biologically relevant genetic loci encoding protein targets involved in synaptic neurotransmission, although no robust individual replication was detected and thus additional validation is required. Secondary permutation-based analysis revealed an excess of strongly associated loci among GWAS top-ranked signals for verbal working memory (WM) and antisaccade intra-subject reaction time variability (empirical P < 0.001), suggesting multiple true-positive single-SNP associations. Substantial heritability was observed for WM performance. Further, sustained attention/vigilance and WM were suggestively correlated with both COGENT and PGC-SZ derived polygenic scores. Overall, these results imply that common genetic variation explains some of the variability in neurocognitive functioning among young adults, particularly WM, and provide supportive evidence that increased SZ genetic risk predicts neurocognitive fluctuations in the general population.

A functional schizophrenia-associated genetic variant near the TSNARE1 and ADGRB1 genes.

Recent collaborative genome-wide association studies (GWAS) have identified >200 independent loci contributing to risk for schizophrenia (SCZ). The genes closest to these loci have diverse functions, supporting the potential involvement of multiple relevant biological processes, yet there is no direct evidence that individual variants are functional or directly linked to specific genes. Nevertheless, overlap with certain epigenetic marks suggest that most GWAS-implicated variants are regulatory. Based on the strength of association with SCZ and the presence of regulatory epigenetic marks, we chose one such variant near TSNARE1 and ADGRB1, rs4129585, to test for functional potential and assay differences that may drive the pathogenicity of the risk allele. We observed that the variant-containing sequence drives reporter expression in relevant neuronal populations in zebrafish. Next, we introduced each allele into human induced pluripotent cells and differentiated four isogenic clones homozygous for the risk allele and five clones homozygous for the non-risk allele into neural progenitor cells. Employing RNA sequencing, we found that the two alleles yield significant transcriptional differences in the expression of 109 genes at a false discovery rate (FDR) of <0.05 and 259 genes at a FDR of <0.1. We demonstrate that these genes are highly interconnected in pathways enriched for synaptic proteins, axon guidance, and regulation of synapse assembly. Exploration of genes near rs4129585 suggests that this variant does not regulate TSNARE1 transcripts, as previously thought, but may regulate the neighboring ADGRB1, a regulator of synaptogenesis. Our results suggest that rs4129585 is a functional common variant that functions in specific pathways likely involved in SCZ risk.

SynaptomeDB: an ontology-based knowledgebase for synaptic genes.

MOTIVATION: The synapse is integral to the function of the brain and may be an important source of dysfunction underlying many neuropsychiatric disorders. Consequently, it is an excellent candidate for large-scale genomic and proteomic study. However, while the tools and databases available for the annotation of high-throughput DNA and protein are generally robust, a comprehensive resource dedicated to the integration of information about the synapse is lacking. RESULTS: We present an integrated database, called SynaptomeDB, to retrieve and annotate genes comprising the synaptome. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion/cytoskeletal proteins, scaffold proteins, membrane transporters. SynaptomeDB integrates various and complex data sources for synaptic genes and proteins.

Whole-genome sequencing of a single proband together with linkage analysis identifies a Mendelian disease gene.

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders.