Dissecting the genetic basis of comorbid epilepsy phenotypes in neurodevelopmental disorders.

BACKGROUND:Neurodevelopmental disorders (NDDs) such as autism spectrum disorder, intellectual disability, developmental disability, and epilepsy are characterized by abnormal brain development that may affect cognition, learning, behavior, and motor skills. High co-occurrence (comorbidity) of NDDs indicates a shared, underlying biological mechanism. The genetic heterogeneity and overlap observed in NDDs make it difficult to identify the genetic causes of specific clinical symptoms, such as seizures. METHODS:We present a computational method, MAGI-S, to discover modules or groups of highly connected genes that together potentially perform a similar biological function. MAGI-S integrates protein-protein interaction and co-expression networks to form modules centered around the selection of a single "seed" gene, yielding modules consisting of genes that are highly co-expressed with the seed gene. We aim to dissect the epilepsy phenotype from a general NDD phenotype by providing MAGI-S with high confidence NDD seed genes with varying degrees of association with epilepsy, and we assess the enrichment of de novo mutation, NDD-associated genes, and relevant biological function of constructed modules. RESULTS:The newly identified modules account for the increased rate of de novo non-synonymous mutations in autism, intellectual disability, developmental disability, and epilepsy, and enrichment of copy number variations (CNVs) in developmental disability. We also observed that modules seeded with genes strongly associated with epilepsy tend to have a higher association with epilepsy phenotypes than modules seeded at other neurodevelopmental disorder genes. Modules seeded with genes strongly associated with epilepsy (e.g., SCN1A, GABRA1, and KCNB1) are significantly associated with synaptic transmission, long-term potentiation, and calcium signaling pathways. On the other hand, modules found with seed genes that are not associated or weakly associated with epilepsy are mostly involved with RNA regulation and chromatin remodeling. CONCLUSIONS:In summary, our method identifies modules enriched with de novo non-synonymous mutations and can capture specific networks that underlie the epilepsy phenotype and display distinct enrichment in relevant biological processes. MAGI-S is available at https://github.com/jchow32/magi-s

A High-Resolution Single Nucleotide Polymorphism Genetic Map of the Mouse Genome

High-resolution genetic maps are required for mapping complex traits and for the study of recombination. We report the highest density genetic map yet created for any organism, except humans. Using more than 10,000 single nucleotide polymorphisms evenly spaced across the mouse genome, we have constructed genetic maps for both outbred and inbred mice, and separately for males and females. Recombination rates are highly correlated in outbred and inbred mice, but show relatively low correlation between males and females. Differences between male and female recombination maps and the sequence features associated with recombination are strikingly similar to those observed in humans. Genetic maps are available from http://gscan.well.ox.ac.uk/#genetic_map and as supporting information to this publication

Human embryonic stem cells from aneuploid blastocysts identified by pre-implantation genetic screening

Human embryonic stem cells are derived from the inner cell mass of pre-implantation embryos. The cells have unlimited proliferation potential and capacity to differentiate into the cells of the three germ layers. Human embryonic stem cells are used to study human embryogenesis and disease modeling and may in the future serve as cells for cell therapy and drug screening. Human embryonic stem cells are usually isolated from surplus normal frozen embryos and were suggested to be isolated from diseased embryos detected by pre-implantation genetic diagnosis. Here we report the isolation of 12 human embryonic stem cell lines and their thorough characterization. The lines were derived from embryos detected to have aneuploidy by pre-implantation genetic screening. Karyotype analysis of these cell lines showed that they are euploid, having 46 chromosomes. Our interpretation is that the euploid cells originated from mosaic embryos, and in vitro selection favored the euploid cells. The undifferentiated cells exhibited long-term proliferation and expressed markers typical for embryonic stem cells such as OCT4, NANOG, and TRA-1-60. The cells manifested pluripotent differentiation both in vivo and in vitro. To further characterize the different lines, we have analyzed their ethnic origin and the family relatedness among them. The above results led us to conclude that the aneuploid mosaic embryos that are destined to be discarded can serve as source for normal euploid human embryonic stem cell lines. These lines represent various ethnic groups; more lines are needed to represent all populations

Neurogenomic Evidence for a Shared Mechanism of the Antidepressant Effects of Exercise and Chronic Fluoxetine in Mice

Several different interventions improve depressed mood, including medication and environmental factors such as regular physical exercise. The molecular pathways underlying these effects are still not fully understood. In this study, we sought to identify shared mechanisms underlying antidepressant interventions. We studied three groups of mice: mice treated with a widely used antidepressant drug – fluoxetine, mice engaged in voluntary exercise, and mice living in an enriched environment. The hippocampi of treated mice were investigated at the molecular and cellular levels. Mice treated with fluoxetine and mice who exercised daily showed, not only similar antidepressant behavior, but also similar changes in gene expression and hippocampal neurons. These changes were not observed in mice with environmental enrichment. An increase in neurogenesis and dendritic spine density was observed following four weeks of fluoxetine treatment and voluntary exercise. A weighted gene co-expression network analysis revealed four different modules of co-expressed genes that were correlated with the antidepressant effect. This network analysis enabled us to identify genes involved in the molecular pathways underlying the effects of fluoxetine and exercise. The existence of both neuronal and gene expression changes common to antidepressant drug and exercise suggests a shared mechanism underlying their effect. Further studies of these findings may be used to uncover the molecular mechanisms of depression, and to identify new avenues of therapy

Networks of Neuronal Genes Affected by Common and Rare Variants in Autism Spectrum Disorders

Autism spectrum disorders (ASD) are neurodevelopmental disorders with phenotypic and genetic heterogeneity. Recent studies have reported rare and de novo mutations in ASD, but the allelic architecture of ASD remains unclear. To assess the role of common and rare variations in ASD, we constructed a gene co-expression network based on a widespread survey of gene expression in the human brain. We identified modules associated with specific cell types and processes. By integrating known rare mutations and the results of an ASD genome-wide association study (GWAS), we identified two neuronal modules that are perturbed by both rare and common variations. These modules contain highly connected genes that are involved in synaptic and neuronal plasticity and that are expressed in areas associated with learning and memory and sensory perception. The enrichment of common risk variants was replicated in two additional samples which include both simplex and multiplex families. An analysis of the combined contribution of common variants in the neuronal modules revealed a polygenic component to the risk of ASD. The results of this study point toward contribution of minor and major perturbations in the two sub-networks of neuronal genes to ASD risk

The genetic variation of RELN expression in schizophrenia and bipolar disorder.

Reelin plays an important role in the development and function of the brain and has been linked to different neuropsychiatric diseases. To further clarify the connection between reelin and psychiatric disorders, we studied the factors that influence the expression of reelin gene (RELN) and its different isoforms. We examined the total expression of RELN, allelic expression, and two alternative RELN isoforms in postmortem brain samples from patients with schizophrenia and bipolar disorder, as well as unaffected controls. We did not find a significant reduction in the total expression of RELN in schizophrenia or bipolar disorder. However, we did find a significant reduction of the proportion of the short RELN isoform, missing the C-terminal region in bipolar disorder, and imbalance in the allelic expression of RELN in schizophrenia. In addition, we tested the association between variation in RELN expression and rs7341475, an intronic SNP that was found to be associated with schizophrenia in women. We did not find an association between rs7341474 and the total expression of RELN either in women or in the entire sample. However, we observed a nominally significant effect of genotype-by-sex interaction on the variation in microexon skipping. Women with the risk genotype of rs7341475 (GG) had a higher proportion of microexon skipping, which is the isoform predominant in tissues outside the brain, while men had the opposite trend. Finally, we tested 83 SNPs in the gene region for association with expression variation of RELN, but none were significant. Our study further supports the connection between RELN dysfunction and psychiatric disorders, and provides a possible functional role for a schizophrenia associated SNP. Nevertheless, the positive associations observed in this study needs further replication as it may have implications for understanding the biological causes of schizophrenia and bipolar disorder

Mouse Inbred Strain Sequence Information and Yin-Yang Crosses for Quantitative Trait Locus Fine Mapping

The shared ancestry of mouse inbred strains, together with the availability of sequence and phenotype information, is a resource that can be used to map quantitative trait loci (QTL). The difficulty in using only sequence information lies in the fact that in most instances the allelic state of the QTL cannot be unambiguously determined in a given strain. To overcome this difficulty, the performance of multiple crosses between various inbred strains has been proposed. Here we suggest and evaluate a general approach, which consists of crossing the two strains used initially to map the QTL and any new strain. We have termed these crosses “yin-yang,” because they are complementary in nature as shown by the fact that the QTL will necessarily segregate in only one of the crosses. We used the publicly available SNP database of chromosome 16 to evaluate the mapping resolution achievable through this approach. Although on average the improvement of mapping resolution using only four inbred strains was relatively small (i.e., reduction of the QTL-containing interval by half at most), we found a great degree of variability among different regions of chromosome 16 with regard to mapping resolution. This suggests that with a large number of strains in hand, selecting a small number of strains may provide a significant contribution to the fine mapping of QTL