Project description:The development of the human brain is a complex and precisely regulated process that unfolds over a protracted period of time. Human-specific features of this process, especially the ways in which highly complex neural circuits of the cerebral cortex form, are likely to be important factors in the evolution of human specializations. However, in addition to giving us remarkable cognitive and motor abilities, the formation of intricate neural circuits may have also increased our susceptibility to psychiatric and neurodegenerative disorders. Furthermore, substantial evidence suggests that the symptoms and progression of many brain disorders are dramatically influenced by genetic and developmental processes that define regional cell phenotypes and connectivity. Sex differences also play an important role in brain development and function and are a risk factor for several brain disorders, such as autism spectrum disorders (ASD) and depression. Thus understanding the spatiotemporal dynamics and functional organization of the brain transcriptome is essential to teasing out the keys to human neurodevelopment, sexual dimorphism, and evolution as well as our increased susceptibility to certain brain disorders. Most transcriptome studies of the developing brain have been restricted to rodents, and those performed in humans and nonhuman primates have included relatively small sample sizes and predominantly focused on few regions or developmental time points. Because many prominent features of human brain development significantly diverge from those of well-characterized model organisms, the translation of knowledge across species is difficult, and it is likely that many underlying genetic processes have gone undetected. In this study, we have taken a genome-wide approach to analyze the human transcriptome at single-exon resolution with ~1.4 million exon-level probe sets in 16 brain regions from donors representing both sexes and multiple ethnicities, across pre and postnatal development, including adolescence, and adulthood. We also generated genome-wide genotype data for 2.5 million single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for each specimen. Our analyses of the data revealed several features of the human brain transcriptome: spatiotemporal expression dynamics of individual and functionally related groups of genes, differential exon usage, sex-specific expression patterns and exon usage, and organization of the transcriptome into functional modules. We also profiled developmental trajectories of genes important for neurobiological themes and genes associated with ASD and schizophrenia. Finally, we present associations between specific SNPs and gene expression levels in different brain regions across development. The dataset presented here provides research opportunities and a wealth of information not previously available to the scientific community. Here we report the generation and analysis of genome-wide exon-level transcriptome data from 16 brain regions comprising the cerebellar cortex, mediodorsal nucleus of the thalamus, striatum, amygdala, hippocampus, and 11 areas of the neocortex. The dataset was generated from 1,340 samples collected from both hemispheres of 57 postmortem human brains, spanning from embryonic development to late adulthood and representing males and females of multiple ethnicities. We also performed genome-wide genotyping of 2.5 million single nucleotide polymorphisms (SNPs) and assessed copy number variations for all donors. We found that approximately 86% of protein-coding genes are expressed above background, and over 90% of these are differentially regulated at the whole transcript or exon level across regions and/or time. The majority of these spatiotemporal differences occur before birth, followed by a progressive increase in the similarity among regional transcriptome during the postnatal lifespan. Distinctive transcriptional patterns were also identified among neocortical areas, including an alternative isoform of ANKRD32 that is transiently upregulated in the late midfetal frontal cortex of human but not mouse. Developmentally and regionally regulated differences in gene expression and exon usage were also identified between males and females, including IGF2, an imprinted gene implicated in brain growth and cognitive function, and NLGN4X, a candidate gene for autism spectrum disorders. We found that the developing transcriptome is organized into functionally distinct large-scale networks of co-regulated transcripts. We also observed marked differences in expression trajectories of genes associated with specific neurodevelopmental processes, neural cell types, neurotransmitter systems, autism spectrum disorders, and schizophrenia. Association analysis of the SNP genotypes and transcriptome revealed potential polymorphic regulators of gene expression in different regions across development. This study provides a comprehensive, publicly available dataset on the spatiotemporal human brain transcriptome and new insights into the transcriptional foundations of brain development and evolution. This submission represents the transcriptome component of the study. Submitter did not submit SNP and CNV data due to privacy issue of patients.

Project description:The development of the human brain is a complex and precisely regulated process that unfolds over a protracted period of time. Human-specific features of this process, especially the ways in which highly complex neural circuits of the cerebral cortex form, are likely to be important factors in the evolution of human specializations. However, in addition to giving us remarkable cognitive and motor abilities, the formation of intricate neural circuits may have also increased our susceptibility to psychiatric and neurodegenerative disorders. Furthermore, substantial evidence suggests that the symptoms and progression of many brain disorders are dramatically influenced by genetic and developmental processes that define regional cell phenotypes and connectivity. Sex differences also play an important role in brain development and function and are a risk factor for several brain disorders, such as autism spectrum disorders (ASD) and depression. Thus understanding the spatiotemporal dynamics and functional organization of the brain transcriptome is essential to teasing out the keys to human neurodevelopment, sexual dimorphism, and evolution as well as our increased susceptibility to certain brain disorders. Most transcriptome studies of the developing brain have been restricted to rodents, and those performed in humans and nonhuman primates have included relatively small sample sizes and predominantly focused on few regions or developmental time points. Because many prominent features of human brain development significantly diverge from those of well-characterized model organisms, the translation of knowledge across species is difficult, and it is likely that many underlying genetic processes have gone undetected. In this study, we have taken a genome-wide approach to analyze the human transcriptome at single-exon resolution with ~1.4 million exon-level probe sets in 16 brain regions from donors representing both sexes and multiple ethnicities, across pre and postnatal development, including adolescence, and adulthood. We also generated genome-wide genotype data for 2.5 million single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for each specimen. Our analyses of the data revealed several features of the human brain transcriptome: spatiotemporal expression dynamics of individual and functionally related groups of genes, differential exon usage, sex-specific expression patterns and exon usage, and organization of the transcriptome into functional modules. We also profiled developmental trajectories of genes important for neurobiological themes and genes associated with ASD and schizophrenia. Finally, we present associations between specific SNPs and gene expression levels in different brain regions across development. The dataset presented here provides research opportunities and a wealth of information not previously available to the scientific community.

Project description:Accurate and comprehensive de novo transcriptome profiling in heart is a central issue to better understand cardiac physiology and diseases. Although significant progress has been made in genome-wide profiling for quantitative changes in cardiac gene expression, current knowledge offers limited insights to the total complexity in cardiac transcriptome at individual exon level. To develop more robust bioinformatic approaches to analyze high-throughput RNA sequencing (RNA-Seq) data, with the focus on the investigation of transcriptome complexity at individual exon and transcript levels. In addition to overall gene expression analysis, the methods developed in this study were used to analyze RNA-Seq data with respect to individual transcript isoforms, novel spliced exons, novel alternative terminal exons, novel transcript clusters (i.e., novel genes) and long non-coding RNA genes. We applied these approaches to RNA-Seq data obtained from mouse hearts following pressure-overload induced by trans-aortic constriction. Based on experimental validations, analyses of the features of the identified exons/transcripts, and expression analyses including previously published RNA-Seq data, we demonstrate that the methods are highly effective in detecting and quantifying individual exons and transcripts. Novel insights inferred from the examined aspects of the cardiac transcriptome open ways to further experimental investigations. Our work provided a comprehensive set of methods to analyze mouse cardiac transcriptome complexity at individual exon and transcript levels. Applications of the methods may infer important new insights to gene regulation in normal and disease hearts in terms of exon utilization and potential involvement of novel components of cardiac transcriptome. Left ventricular tissues were collected from C57BL/6 mice after 1 week (hypertrophy stage, HY) and 8 weeks post trans-aortic constriction (TAC) procedure (heart failure stage, HF), respectively, and their corresponding Sham controls (Sham-HY, Sham-HF). To conduct RNA-Seq analysis, total RNAs from six TAC and Sham-operated mice at the HY stage and four TAC and corresponding Sham mice at the HF stage were obtained.

Project description:Numerous genome-wide screens for polymorphisms that influence gene expression have provided key insights into the genetic control of transcription. Despite this work, the relevance of specific polymorphisms to in vivo expression and splicing remains unclear. We carried out the first genome-wide screen, to our knowledge, for SNPs that associate with alternative splicing and gene expression in human primary cells, evaluating 93 autopsy-collected cortical brain tissue samples with no defined neuropsychiatric condition and 80 peripheral blood mononucleated cell samples collected from living healthy donors. We identified 23 high confidence associations with total expression and 80 with alternative splicing as reflected by expression levels of specific exons. Fewer than 50% of the implicated SNPs however show effects in both tissue types, reflecting strong evidence for distinct genetic control of splicing and expression in the two tissue types. The data generated here also suggest the possibility that splicing effects may be responsible for up to 13 out of 84 reported genome-wide significant associations with human traits. These results emphasize the importance of establishing a database of polymorphisms affecting splicing and expression in primary tissue types and suggest that splicing effects may be of more phenotypic significance than overall gene expression changes. We evaluated 93 autopsy-collected cortical brain tissue samples with no defined neuropsychiatric condition and 80 peripheral blood mononucleated cell samples collected from living healthy donors. Affymetrix Human ST 1.0 exon arrays were used to assess exon and transcript expression levels for all samples used in the study. Replicate analyses were not performed. Exon array sample preparation from total RNA was conducted based on standard Affymetrix protocols. Data were normalized separately within PBMC and brain sets Affymetrix PLIER protocol with a sketch-quantile normalization procedure (Affymetrix Expression Console). Normalized files include brain core transcripts (NABRAINSETCOMBplier-gene-core.summary), brain all transcripts (NABRAINSETCOMBplier-gene-full.summary), brain core exons (NABRAINSETCOMBplier-exon-core.summary), brain all exons (NABRAINSETCOMBplier-exon-all.summary), PBMC core transcripts (NAPBMCfullsetplier-gene-core.summary), PBMC all transcripts (NAPBMCfullsetplier-gene-full.summary), PBMC core exons (NAPBMCfullsetplier-exon-core.summary), PBMC all exons (NAPBMCfullsetplier-exon-all.summary). all, full and core definitions are provided by Affymetrix.

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	manifest_phs000755.BrainSpanAtlas_Project.v1.p1.c1.GRU.pdf	Pdf
	datadict_v2.xsl	Other

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BrainSpan Atlas of the Human Brain

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