FOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders.

Autism spectrum disorder (ASD) is a disorder of brain development. Most cases lack a clear etiology or genetic basis, and the difficulty of re-enacting human brain development has precluded understanding of ASD pathophysiology. Here we use three-dimensional neural cultures (organoids) derived from induced pluripotent stem cells (iPSCs) to investigate neurodevelopmental alterations in individuals with severe idiopathic ASD. While no known underlying genomic mutation could be identified, transcriptome and gene network analyses revealed upregulation of genes involved in cell proliferation, neuronal differentiation, and synaptic assembly. ASD-derived organoids exhibit an accelerated cell cycle and overproduction of GABAergic inhibitory neurons. Using RNA interference, we show that overexpression of the transcription factor FOXG1 is responsible for the overproduction of GABAergic neurons. Altered expression of gene network modules and FOXG1 are positively correlated with symptom severity. Our data suggest that a shift toward GABAergic neuron fate caused by FOXG1 is a developmental precursor of ASD.

Somatic copy number mosaicism in human skin revealed by induced pluripotent stem cells.

Reprogramming somatic cells into induced pluripotent stem cells (iPSCs) has been suspected of causing de novo copy number variation. To explore this issue, here we perform a whole-genome and transcriptome analysis of 20 human iPSC lines derived from the primary skin fibroblasts of seven individuals using next-generation sequencing. We find that, on average, an iPSC line manifests two copy number variants (CNVs) not apparent in the fibroblasts from which the iPSC was derived. Using PCR and digital droplet PCR, we show that at least 50% of those CNVs are present as low-frequency somatic genomic variants in parental fibroblasts (that is, the fibroblasts from which each corresponding human iPSC line is derived), and are manifested in iPSC lines owing to their clonal origin. Hence, reprogramming does not necessarily lead to de novo CNVs in iPSCs, because most of the line-manifested CNVs reflect somatic mosaicism in the human skin. Moreover, our findings demonstrate that clonal expansion, and iPSC lines in particular, can be used as a discovery tool to reliably detect low-frequency CNVs in the tissue of origin. Overall, we estimate that approximately 30% of the fibroblast cells have somatic CNVs in their genomes, suggesting widespread somatic mosaicism in the human body. Our study paves the way to understanding the fundamental question of the extent to which cells of the human body normally acquire structural alterations in their DNA post-zygotically.

P-value calibration for multiple testing problems in genomics.

Conservative statistical tests are often used in complex multiple testing settings in which computing the type I error may be difficult. In such tests, the reported p-value for a hypothesis can understate the evidence against the null hypothesis and consequently statistical power may be lost. False Discovery Rate adjustments, used in multiple comparison settings, can worsen the unfavorable effect. We present a computationally efficient and test-agnostic calibration technique that can substantially reduce the conservativeness of such tests. As a consequence, a lower sample size might be sufficient to reject the null hypothesis for true alternatives, and experimental costs can be lowered. We apply the calibration technique to the results of DESeq, a popular method for detecting differentially expressed genes from RNA sequencing data. The increase in power may be particularly high in small sample size experiments, often used in preliminary experiments and funding applications.

Modeling human cortical development in vitro using induced pluripotent stem cells.

Human induced pluripotent stem cells (hiPSCs) are emerging as a tool for understanding human brain development at cellular, molecular, and genomic levels. Here we show that hiPSCs grown in suspension in the presence of rostral neuralizing factors can generate 3D structures containing polarized radial glia, intermediate progenitors, and a spectrum of layer-specific cortical neurons reminiscent of their organization in vivo. The hiPSC-derived multilayered structures express a gene expression profile typical of the embryonic telencephalon but not that of other CNS regions. Their transcriptome is highly enriched in transcription factors controlling the specification, growth, and patterning of the dorsal telencephalon and displays highest correlation with that of the early human cerebral cortical wall at 8-10 wk after conception. Thus, hiPSC are capable of enacting a transcriptional program specifying human telencephalic (pallial) development. This model will allow the study of human brain development as well as disorders of the human cerebral cortex.

Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach.

INTRODUCTION: The Amyloid/Tau/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer's disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data. METHODS: 927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories. We used machine learning (ML) methods to identify a set of significant features separating each neurodegeneration-related group from controls (A-T-(N)-). Random Forest and linear-kernel SVM with stratified 5-fold cross validations were used to optimize model whose performance was then tested in the ADNI database. RESULTS: Our optimal results outperformed ATN cross-validated logistic regression models by between 2.2% and 8.3%. The optimal feature sets were not consistent across the 4 models with the AD pathologic change vs controls set differing the most from the rest. Because of that we have identified a subset of 10 features that yield results very close or identical to the optimal. DISCUSSION: Our study demonstrates the gains offered by ML in generating ATN risk prediction over logistic regression models among pre-dementia individuals.

Age-related changes of gene expression in the neocortex: preliminary data on RNA-Seq of the transcriptome in three functionally distinct cortical areas.

The study of gene expression (i.e., the study of the transcriptome) in different cells and tissues allows us to understand the molecular mechanisms of their differentiation, development and functioning. In this article, we describe some studies of gene-expression profiling for the purposes of understanding developmental (age-related) changes in the brain using different technologies (e.g., DNA-Microarray) and the new and increasingly popular RNA-Seq. We focus on advancements in studies of gene expression in the human brain, which have provided data on the structure and age-related variability of the transcriptome in the brain. We present data on RNA-Seq of the transcriptome in three distinct areas of the neocortex from different ages: mature and elderly individuals. We report that most age-related transcriptional changes affect cellular signaling systems, and, as a result, the transmission of nerve impulses. In general, the results demonstrate the high potential of RNA-Seq for the study of distinctive features of gene expression among cortical areas and the changes in expression through normal and atypical development of the central nervous system.

EBNA1 regulates cellular gene expression by binding cellular promoters.

Epstein-Barr virus (EBV) is associated with several types of lymphomas and epithelial tumors including Burkitt's lymphoma (BL), HIV-associated lymphoma, posttransplant lymphoproliferative disorder, and nasopharyngeal carcinoma. EBV nuclear antigen 1 (EBNA1) is expressed in all EBV associated tumors and is required for latency and transformation. EBNA1 initiates latent viral replication in B cells, maintains the viral genome copy number, and regulates transcription of other EBV-encoded latent genes. These activities are mediated through the ability of EBNA1 to bind viral-DNA. To further elucidate the role of EBNA1 in the host cell, we have examined the effect of EBNA1 on cellular gene expression by microarray analysis using the B cell BJAB and the epithelial 293 cell lines transfected with EBNA1. Analysis of the data revealed distinct profiles of cellular gene changes in BJAB and 293 cell lines. Subsequently, chromatin immune-precipitation revealed a direct binding of EBNA1 to cellular promoters. We have correlated EBNA1 bound promoters with changes in gene expression. Sequence analysis of the 100 promoters most enriched revealed a DNA motif that differs from the EBNA1 binding site in the EBV genome.

A Framework for Comparison and Assessment of Synthetic RNA-Seq Data.

The ever-growing number of methods for the generation of synthetic bulk and single cell RNA-seq data have multiple and diverse applications. They are often aimed at benchmarking bioinformatics algorithms for purposes such as sample classification, differential expression analysis, correlation and network studies and the optimization of data integration and normalization techniques. Here, we propose a general framework to compare synthetically generated RNA-seq data and select a data-generating tool that is suitable for a set of specific study goals. As there are multiple methods for synthetic RNA-seq data generation, researchers can use the proposed framework to make an informed choice of an RNA-seq data simulation algorithm and software that are best suited for their specific scientific questions of interest.

An application of the elastic net for an endophenotype analysis.

We provide an illustration of an application of the elastic net to a large number of common genetic variants in the context of the search for the genetic bases of an endophenotype conceivably related to individual differences in learning. GABA concentration in the occipital cortex, a critical area for reading, was obtained in a group (n = 76) of children aged 6-10 years. Two extreme groups, high and low, were selected for genotyping with the 650Y Illumina array chip (Ilmn650Y). An elastic net approach was applied to the resulting SNP dataset; 100 SNPs were identified for each chromosome as "interesting" based on having the highest absolute value coefficients. The analyses highlighted chromosomes 15 and 20, which contained 55 candidate genes. The STRING partner analyses of the associated proteins pointed to a number of related genes, most notably, GABA and NTRK receptors.

A procedure for highly specific, sensitive, and unbiased whole-genome amplification.

Highly specific amplification of complex DNA pools without bias or template-independent products (TIPs) remains a challenge. We have developed a method using phi29 DNA polymerase and trehalose and optimized control of amplification to create micrograms of specific amplicons without TIPs from down to subfemtograms of DNA. With an input of as little as 0.5-2.5 ng of human gDNA or a few cells, the product could be close to native DNA in locus representation. The amplicons from 5 and 0.5 ng of DNA faithfully demonstrated all previously known heterozygous segmental duplications and deletions (3 Mb to 18 kb) located on chromosome 22 and even a homozygous deletion smaller than 1 kb with high-resolution chromosome-wide comparative genomic hybridization. With 550k Infinium BeadChip SNP typing, the >99.7% accuracy was compared favorably with results on unamplified DNA. Importantly, underrepresentation of chromosome termini that occurred with GenomiPhi v2 was greatly rescued with the present procedure, and the call rate and accuracy of SNP typing were also improved for the amplicons with a 0.5-ng, partially degraded DNA input. In addition, the amplification proceeded logarithmically in terms of total yield before saturation; the intact cells was amplified >50 times more efficiently than an equivalent amount of extracted DNA; and the locus imbalance for amplicons with 0.1 ng or lower input of DNA was variable, whereas for higher input it was largely reproducible. This procedure facilitates genomic analysis with single cells or other traces of DNA, and generates products suitable for analysis by massively parallel sequencing as well as microarray hybridization.

Transcriptome Analysis of the Human Striatum in Tourette Syndrome.

BACKGROUND: Genome-wide association studies have not revealed any risk-conferring common genetic variants in Tourette syndrome (TS), requiring the adoption of alternative approaches to investigate the pathophysiology of this disorder. METHODS: We obtained the basal ganglia transcriptome by RNA sequencing in the caudate and putamen of nine TS and nine matched normal control subjects. RESULTS: We found 309 downregulated and 822 upregulated genes in the caudate and putamen (striatum) of TS individuals. Using data-driven gene network analysis, we identified 17 gene coexpression modules associated with TS. The top-scoring downregulated module in TS was enriched in striatal interneuron transcripts, which was confirmed by decreased numbers of cholinergic and gamma-aminobutyric acidergic interneurons by immunohistochemistry in the same regions. The top-scoring upregulated module was enriched in immune-related genes, consistent with activation of microglia in patients' striatum. Genes implicated by copy number variants in TS were enriched in the interneuron module, as well as in a protocadherin module. Module clustering revealed that the interneuron module was correlated with a neuronal metabolism module. CONCLUSIONS: Convergence of differential expression, network analyses, and module clustering, together with copy number variants implicated in TS, strongly implicates disrupted interneuron signaling in the pathophysiology of severe TS and suggests that metabolic alterations may be linked to their death or dysfunction.

Induced pluripotent stem cells: a new tool to confront the challenge of neuropsychiatric disorders.

Studies in the area of human brain development are critical as research on neurological and psychiatric disorders has advanced, revealing the origins of pathophysiology to be in the earliest developmental stages. Only with a more precise understanding of the genes and environments that influence the brain in these early stages can we address questions about the pathology, diagnosis, prevention and treatment of neuropsychiatric disorders of developmental origin, like autism, schizophrenia, and Tourette syndrome. A new approach for studying early developmental events is the use of induced pluripotent stem cells (iPSCs). These are cells with wide potential, similar to that of embryonic stem cells, derived from mature somatic cells. We review the protocols used to create iPSCs, including the most efficient and reliable reprogramming strategies available to date for generating iPSCs. In addition, we discuss how this new tool can be applied to neuropsychiatric research. The use of iPSCs can advance our understanding of how genes and gene products are dynamically involved in the formation of unique features of the human brain, and how aberrant genetic variation may interfere with its typical formation. The iPSC technology, if properly applied, can also address basic questions about neural differentiation such as how stem cells can be guided into general and specific neurodevelopmental pathways. Current work in neuropsychiatry with iPSCs derived from patients has focused on disorders with specific genetics deficits and those with less-defined origins; it has revealed previously unknown aspects of pathology and potential pharmacological interventions. These exciting advances based on the use of iPSCs hold promise for improving early diagnosis and, possibly, treatment of psychiatric disorders. This article is part of a Special Issue entitled 'Trends in neuropharmacology: in memory of Erminio Costa'.

Paired-end mapping reveals extensive structural variation in the human genome.

Structural variation of the genome involves kilobase- to megabase-sized deletions, duplications, insertions, inversions, and complex combinations of rearrangements. We introduce high-throughput and massive paired-end mapping (PEM), a large-scale genome-sequencing method to identify structural variants (SVs) approximately 3 kilobases (kb) or larger that combines the rescue and capture of paired ends of 3-kb fragments, massive 454 sequencing, and a computational approach to map DNA reads onto a reference genome. PEM was used to map SVs in an African and in a putatively European individual and identified shared and divergent SVs relative to the reference genome. Overall, we fine-mapped more than 1000 SVs and documented that the number of SVs among humans is much larger than initially hypothesized; many of the SVs potentially affect gene function. The breakpoint junction sequences of more than 200 SVs were determined with a novel pooling strategy and computational analysis. Our analysis provided insights into the mechanisms of SV formation in humans.