Dataset Information

Defining the Human Brain Proteome Using Transcriptomics and Antibody-Based Profiling with a Focus on the Cerebral Cortex.

ABSTRACT: The mammalian brain is a complex organ composed of many specialized cells, harboring sets of both common, widely distributed, as well as specialized and discretely localized proteins. Here we focus on the human brain, utilizing transcriptomics and public available Human Protein Atlas (HPA) data to analyze brain-enriched (frontal cortex) polyadenylated messenger RNA and long non-coding RNA and generate a genome-wide draft of global and cellular expression patterns of the brain. Based on transcriptomics analysis of altogether 27 tissues, we have estimated that approximately 3% (n=571) of all protein coding genes and 13% (n=87) of the long non-coding genes expressed in the human brain are enriched, having at least five times higher expression levels in brain as compared to any of the other analyzed peripheral tissues. Based on gene ontology analysis and detailed annotation using antibody-based tissue micro array analysis of the corresponding proteins, we found the majority of brain-enriched protein coding genes to be expressed in astrocytes, oligodendrocytes or in neurons with molecular properties linked to synaptic transmission and brain development. Detailed analysis of the transcripts and the genetic landscape of brain-enriched coding and non-coding genes revealed brain-enriched splice variants. Several clusters of neighboring brain-enriched genes were also identified, suggesting regulation of gene expression on the chromatin level. This multi-angle approach uncovered the brain-enriched transcriptome and linked genes to cell types and functions, providing novel insights into the molecular foundation of this highly specialized organ.

SUBMITTER: Sjostedt E

PROVIDER: S-EPMC4468152 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Defining the Human Brain Proteome Using Transcriptomics and Antibody-Based Profiling with a Focus on the Cerebral Cortex.

Sjöstedt Evelina E Fagerberg Linn L Hallström Björn M BM Häggmark Anna A Mitsios Nicholas N Nilsson Peter P Pontén Fredrik F Hökfelt Tomas T Uhlén Mathias M Mulder Jan J

PloS one 20150615 6

The mammalian brain is a complex organ composed of many specialized cells, harboring sets of both common, widely distributed, as well as specialized and discretely localized proteins. Here we focus on the human brain, utilizing transcriptomics and public available Human Protein Atlas (HPA) data to analyze brain-enriched (frontal cortex) polyadenylated messenger RNA and long non-coding RNA and generate a genome-wide draft of global and cellular expression patterns of the brain. Based on transcrip ...[more]

PMID: 26076492

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Project description:Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.

Dataset Information

Defining the Human Brain Proteome Using Transcriptomics and Antibody-Based Profiling with a Focus on the Cerebral Cortex.

Publications

Defining the Human Brain Proteome Using Transcriptomics and Antibody-Based Profiling with a Focus on the Cerebral Cortex.

Similar Datasets

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