Characterising the molecular mechanisms underlying disease risk variants identified in genome-wide association studies (GWAS) is of major interest. Expression Quantitative Trait Loci (eQTL) mapping studies provide a genome-wide characterisation of the impact of common genetic variation on gene expression and splicing and therefore have the potential to achieve this. In this thesis, I investigated the effect of common genetic variants in human brain through eQTL analysis. As part of the UK Brain Expression Consortium project, the analyses in this PhD thesis were performed on whole transcriptome RNA sequencing data from neuropathologically normal human post-mortem brain. I conducted eQTL analyses on putamen and substantia nigra using different types of quantification in order to interrogate regulation at different stages of RNA processing. This analysis pointed to splicing as an important process for the pathogenesis of Parkison"s Disease. Thus, I identify not only disease-relevant regulatory loci but also the types of analyses yielding the most disease-specific information. Due to the limitations of current gene annotation and the complex transcriptomic landscape in human brain, I investigated transcription and splicing in the hippocampus using annotation-agnostic methods. This not only revealed the existence of widespread gene misannotation in the human brain, but also revealed the limitation of current quantification methods to capture transcriptome complexity in brain. Therefore, a reference-free eQTL analysis was performed and by testing for eQTL-GWAS co-localisation I found that incomplete annotation of the brain transcriptome limits the interpretation of risk loci for neurological disorders. I anticipate that analyses of this kind will have an increasing impact on our understanding of a range of disorders, but are likely to have most impact on neurological and neuropsychiatric disorders because of the high transcriptome complexity of human brain tissue.

This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and statistical tools for translational bioinformatics in the areas of gene transcription and regulation, including the tools for next generation sequencing analyses, alternative spicing, the modeling of signaling pathways, network analyses in predicting disease genes, as well as protein and gene expression data integration in complex human diseases etc. The book is particularly useful for researchers and students in the field of molecular biology, clinical biology and bioinformatics, as well as physicians etc. Dr. Jiaqian Wu is assistant professor in the Vivian L. Smith Department of Neurosurgery and Center for Stem Cell and Regenerative Medicine, University of Texas Health Science Centre, Houston, TX, USA.​

How does the genome, interacting with the multi-faceted environment, translate into the development by which the human brain achieves its astonishing, adaptive array of cognitive and behavioral capacities? Why and how does this process sometimes lead to neurodevelopmental disorders with a major, lifelong personal and social impact? This volume of Progress in Brain Research links findings on the structural development of the human brain, the expression of genes in behavioral and cognitive phenotypes, environmental effects on brain development, and developmental processes in perception, action, attention, cognitive control, social cognition, and language, in an attempt to answer these questions. Leading authors review the state-of-the-art in their field of investigation and provide their views and perspectives for future research Chapters are extensively referenced to provide readers with a comprehensive list of resources on the topics covered All chapters include comprehensive background information and are written in a clear form that is also accessible to the non-specialist

Published since 1959, International Review of Neurobiology is a well-known series appealing to neuroscientists, clinicians, psychologists, physiologists, and pharmacologists. Led by an internationally renowned editorial board, this important serial publishes both eclectic volumes made up of timely reviews and thematic volumes that focus on recent progress in a specific area of neurobiology research. This volume, concentrates on the brain transcriptome. Brings together cutting-edge research on the brain transcriptome

Gene expression converts the information coded by our genes into proteins. These determine the structure and function of an organ such as the brain. Itis therefore an essential process, linking molecular genetics with neurochemistry and behavioral neuroscience. This volume presents a didactic approach to the understanding of the basic processes of gene expression and their involvement in certain brain diseases, such asAlzheimer's disease and schizophrenia. Generously illustrated, the contributions provide a valuable outline of this key aspect of molecular neurobiology and clinical neuroscience.

Neurodevelopmental and neuropsychiatric diseases, such as autism spectrum disorder (ASD) and schizophrenia (SCZ), are highly heritable, with hundreds of risk loci contributing to disease risk identified through large-scale genomic studies. The ability to interpret these susceptibility variants and their contributions to disease has been difficult due to the fact that many of these variants fall in non-coding regions of the genome, or in regions of high linkage disequilibrium. Given the non-coding nature of the majority of these variants, as well as their enrichment in known enhancers, many of these variants are predicted to regulate gene expression, which is known to be dependent on tissue, cell type and developmental stage. Here, I have characterized functional genetic variation controlling transcriptional regulation in developing human brain to dissect common variation contributing to neurodevelopmental and early onset neuropsychiatric diseases, characterized by phenotypes originating in utero or early postnatal life. I have comprehensively profiled expression and splicing levels by RNA sequencing and high-density genotyping in 201 mid-gestational human brains and have performed expression and splicing quantitative trait loci analysis, which is currently the largest eQTL study in the developing brain. I identified 7962 expression QTL (eQTL) and 4635 splice QTL (sQTL), including several thousand fetal-specific regulatory regions when compared to published QTL studies of the adult brain. I leveraged these eQTL and sQTL to identify splicing and transcriptional drivers affected by human genetic variation, by significant enrichment in experimentally determined transcription factor, DNA binding proteins, and RNA bringing proteins binding sides. Further integration with experimental transcription factor knockdown data provide evidence that the regulatory regions identified through the eQTL and sQTL analysis are functional and validate that the changes seen in gene expression levels and/or splicing are likely due to the transcription factor's role in regulating that gene. By integration with GWAS, I characterized the genes and isoforms contributing to specific neuropsychiatric disorders, including SCZ and ASD, as well as other cognitive or behavioral-related phenotypes. Specifically showing prenatal brain regulatory regions are significantly enriched for SCZ GWAS risk in a complimentary and additive manner to adult brain regulatory regions. I then perform gene co-expression network analysis and identify co-expressed modules of genes representing distinct biological processes in the developing brain. By integrating the QTL identified gene regulatory regions with co-expression modules and GWAS risk loci, I find SCZ and ASD impact distinct developmental gene co-expression modules. Yet, in both disorders, common and rare genetic variation converge. In ASD this convergence also implicates a specific cell type as well, superficial cortical neurons. Additionally, integration of eQTL and sQTL with GWAS via transcriptome wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in SCZ. These analyses demonstrate the highly distinctive effects of transcriptional control, as well as divergent age-related contributions to disease. More broadly, these findings demonstrate the genetic mechanisms by which early developmental events have a striking and widespread influence on adult anatomical and behavioral phenotypes.

Neuropsychiatric disorders are behavioral conditions marked by intellectual, social, or emotional deficits that can be linked to diseases of the nervous system. Autism spectrum disorder (ASD), schizophrenia (SCZ), bipolar disorder (BP), major depressive disorder (MDD), and attention deficit and hyperactivity disorder (ADHD) are common, heritable diseases each with a prevalence exceeding 1% of the population, none of which can be characterized by discernable anatomical or neurological pathologies. Genetic association studies have identified mutations in hundreds of genes that contribute to risk for at least one of these disorders, and have shown that a substantial fraction of the genetic liability is shared between many of these neuropsychiatric diseases. It has long been hoped that with enough genetic evidence we will identify the biological pathways, developmental time points, and brain regions that, when disrupted, give rise to neuropsychiatric disorders. However, the cellular and functional complexity of the human brain, as well as the genetic complexity of neuropsychiatric disease, make it difficult to search for such convergence. In this thesis, I investigate global and local transcriptional regulation within and across 12 regions of the human brain in order to investigate the regional specificity of neuropsychiatric disorders. I develop novel bioinformatics methods - ranging from data processing to network construction - to identify whether the transcriptional regulation of a set of genes is shared or specific. I hypothesize that local, region-specific transcriptional regulation corresponds directly to cell types and processes that are specific to, or far more prevalent in, a given region; that cross-regional transcriptional regulation corresponds to cell types that show little heterogeneity across brain regions; and that genetic disruption of region-specific transcriptional programs results in regional susceptibility. I use a systems-biology approach to summarize transcriptional regulation into reproducibly co-expressed gene sets ("co-expression modules"), which can be analyzed statistically to identify common functions, pathways, and cell types. I then integrate data from genetic association studies to ascertain gene sets conferring outsized risk for neuropsychiatric disorders, thereby implicating the corresponding pathways for further investigation in disease etiology. Finally, I use the network structure itself to investigate the genetic architecture of ASD and SCZ in terms of omnigenics and network polygenics. Chapter 1 presents the biological background for the studies and summarizes some of the major studies of neuropsychiatric disorders along with their principal methods and conclusions. In chapter 2, utilizing my multi-regional co-expression approach, I identify 12 brain-wide, 114 region-specific, and 50 cross-regional co-expression modules. Nearly 40% of expressed genes fall into brain-wide modules and correspond to major cell classes and conserved biological processes, while region-specific modules comprise 25% of expressed genes and correspond to region-specific cell types. The detailed study in chapter 3 demonstrates that neuropsychiatric risk concentrates in both brain wide and multi-regional modules, implicating major core cell types in disease etiology but not region-specific susceptibility. Chapter 4 presents a new and more general framework for defining genetic networks. Using this framework, I show that the network pattern of ASD-associated rare loss-of-function mutations, as well as the large number of significant targets for trans master regulators in BP and SCZ, support a classical polygenic architecture with thousands of directly causal genes. These results suggest that a nontrivial component of risk for neuropsychiatric disease comes from the global polygenic disruption of neuronal function and neuronal maturation.