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Adult mouse brain gene expression patterns bear an embryologic imprint.

ABSTRACT: The current model to explain the organization of the mammalian nervous system is based on studies of anatomy, embryology, and evolution. To further investigate the molecular organization of the adult mammalian brain, we have built a gene expression-based brain map. We measured gene expression patterns for 24 neural tissues covering the mouse central nervous system and found, surprisingly, that the adult brain bears a transcriptional "imprint" consistent with both embryological origins and classic evolutionary relationships. Embryonic cellular position along the anterior-posterior axis of the neural tube was shown to be closely associated with, and possibly a determinant of, the gene expression patterns in adult structures. We also observed a significant number of embryonic patterning and homeobox genes with region-specific expression in the adult nervous system. The relationships between global expression patterns for different anatomical regions and the nature of the observed region-specific genes suggest that the adult brain retains a degree of overall gene expression established during embryogenesis that is important for regional specificity and the functional relationships between regions in the adult. The complete collection of extensively annotated gene expression data along with data mining and visualization tools have been made available on a publicly accessible web site (www.barlow-lockhart-brainmapnimhgrant.org).

SUBMITTER: Zapala MA

PROVIDER: S-EPMC1173363 | biostudies-literature | 2005 Jul

REPOSITORIES: biostudies-literature

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Adult mouse brain gene expression patterns bear an embryologic imprint.

Zapala Matthew A MA Hovatta Iiris I Ellison Julie A JA Wodicka Lisa L Del Rio Jo A JA Tennant Richard R Tynan Wendy W Broide Ron S RS Helton Rob R Stoveken Barbara S BS Winrow Christopher C Lockhart Daniel J DJ Reilly John F JF Young Warren G WG Bloom Floyd E FE Lockhart David J DJ Barlow Carrolee C

Proceedings of the National Academy of Sciences of the United States of America 20050707 29

The current model to explain the organization of the mammalian nervous system is based on studies of anatomy, embryology, and evolution. To further investigate the molecular organization of the adult mammalian brain, we have built a gene expression-based brain map. We measured gene expression patterns for 24 neural tissues covering the mouse central nervous system and found, surprisingly, that the adult brain bears a transcriptional "imprint" consistent with both embryological origins and classi ...[more]

PMID: 16002470

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Project description:Genomic imprinting, a phenomenon by which genes are expressed in a monoallelic, parent-of-origin-dependent fashion, is critical for normal brain development. Expression of imprinted genes is regulated via epigenetic mechanisms, including DNA methylation (5-methylcytosine, 5mC), and disruptions in imprinting can lead to disease. Early-life exposure to the endocrine disrupting chemical bisphenol A (BPA) is associated with abnormalities in brain development and behavior, as well as with disruptions in epigenetic patterning, including 5mC and DNA hydroxymethylation (5-hydroxymethylcytosine, 5hmC). Using an established mouse model of perinatal environmental exposure, the objective of this study was to examine the effects of perinatal BPA exposure on epigenetic regulation of imprinted gene expression in adult mice. Two weeks prior to mating, dams were assigned to control chow or chow containing an environmentally relevant dose (50 µg/kg) of BPA. Exposure continued until offspring were weaned at post-natal day 21, and animals were followed until 10 months of age. Expression of three imprinted genes-Pde10a, Ppp1r9a, and Kcnq1, as well as three genes encoding proteins critical for regulation of 5mC and 5hmC-Dnmt1, Tet1, and Tet2, were evaluated in the right cortex and midbrain using qRT-PCR. Perinatal BPA exposure was associated with a significant increase in adult Kcnq1 (p = 0.04) and Dnmt1 (p = 0.02) expression in the right cortex, as well as increased expression of Tet2 in the midbrain (p = 0.03). Expression of Tet2 and Kcnq1 were positively correlated in the midbrain. Analysis of 5mC and 5hmC at the Kcnq1 locus was conducted in parallel samples using standard and oxidative bisulfite conversion followed by pyrosequencing. This analysis revealed enrichment of both 5mC and 5hmC at this locus in both brain regions. No significant changes in 5mC and 5hmC at Kcnq1 were observed with perinatal BPA exposure. Together, these data suggest that perinatal BPA exposure results in altered expression of Kcnq1, Dnmt1, and Tet2 in the adult mouse brain. Further studies with larger sample sizes are necessary to understand the mechanistic basis for these changes, as well as to determine the implications they have for brain development and function.

Project description:High-throughput, spatially resolved gene expression techniques are poised to be transformative across biology by overcoming a central limitation in single-cell biology: the lack of information on relationships that organize the cells into the functional groupings characteristic of tissues in complex multicellular organisms. Spatial expression is particularly interesting in the mammalian brain, which has a highly defined structure, strong spatial constraint in its organization, and detailed multimodal phenotypes for cells and ensembles of cells that can be linked to mesoscale properties such as projection patterns, and from there, to circuits generating behavior. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain subdivisions, between the Allen Institute's in situ hybridization data from the adult mouse brain (Allen Brain Atlas (ABA)) and a similar dataset collected using spatial transcriptomics (ST). With the advent of tractable spatial techniques, for the first time, we are able to benchmark the Allen Institute's whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. We use regularized linear regression (LASSO), linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen Reference Atlas labels are classifiable using transcription in both data sets, but that performance is higher in the ABA than in ST. Furthermore, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bidirectionally. While an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. In general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability ultimately providing a valuable reference set for understanding the cell biology of the brain.

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Adult mouse brain gene expression patterns bear an embryologic imprint.

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Adult mouse brain gene expression patterns bear an embryologic imprint.

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