Molecular atlas of the adult mouse brain.
Ontology highlight
ABSTRACT:
SUBMITTER: Ortiz C
PROVIDER: S-EPMC7319762 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain organization based on unbiased extraction of spatially-defining features. Applying whole-brain spatial transcriptomics, we captured the gene expression signatures to define the spatial organization of molecularly discrete subregions. We found that the molecular code contained sufficiently detailed information to directly deduce the complex spatial organization of the brain. This unsupervised molecular classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and a new division of striatum. The whole-brain molecular atlas further supports the identification of the spatial origin of single neurons using their gene expression profile, and forms the foundation to define a minimal gene set - a brain palette – that is sufficient to spatially annotate the adult brain. In summary, we have established a new molecular atlas to formally define the identity of brain regions, and a molecular code for mapping and targeting of discrete neuroanatomical domains.
2020-05-03 | GSE147747 | GEO
Project description:Molecular Atlas of the Adult Mouse Brain
| PRJNA623858 | ENA
Project description: Not available
| S-EPMC10719113 | biostudies-literature
Project description:Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brain's 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brain's cellular-spatial and regulatory genome diversity.
| S-EPMC10153407 | biostudies-literature
Project description:The pathology of many neurodegenerative diseases is characterized by the accumulation of misfolded and aggregated proteins in various cell types and regional substructures throughout the central and peripheral nervous systems. The accumulation of these aggregated proteins signals dysfunction of cellular protein homeostatic mechanisms such as the ubiquitin/proteasome system, autophagy, and the chaperone network. Although there are several published studies in which transcriptional profiling has been used to examine gene expression in various tissues, including tissues of neurodegenerative disease models, there has not been a report that focuses exclusively on expression of the chaperone network. In the present study, we used the Allen Brain Atlas online database to analyze chaperone expression levels. This database utilizes a quantitative in situ hybridization approach and provides data on 270 chaperone genes within many substructures of the adult mouse brain. We determined that 256 of these chaperone genes are expressed at some level. Surprisingly, relatively few genes, only 30, showed significant variations in levels of mRNA across different substructures of the brain. The greatest degree of variability was exhibited by genes of the DnaJ co-chaperone, Tetratricopeptide repeat, and the HSPH families. Our analysis provides a valuable resource towards determining how variations in chaperone gene expression may modulate the vulnerability of specific neuronal populations of mammalian brain.
| S-EPMC2965669 | biostudies-literature
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.
| S-EPMC8321401 | biostudies-literature
Project description:Mice are routinely used to study the development of the external genitalia and, in particular, the process of male urethral closure. This is because misplacement of the male penile urethra, or hypospadias, is amongst the most common birth defects reported in humans. While mice present a tractable model to study penile development, several structures differ between mice and humans, and there is a lack of consensus in the literature on their annotation and developmental origins. Defining the ontology of the mouse prepuce is especially important for the relevance and interpretation of mouse models of hypospadias to human conditions. We have developed a detailed annotation of the adult mouse penis that addresses these differences and enables an accurate comparison of murine and human hypospadias phenotypes. Through MRI data, gross morphology and section histology, we define the origin of the mouse external and internal prepuces, their relationship to the single human foreskin as well as provide a comprehensive view of the various structures of the mouse penis and their associated muscle attachments within the body. These data are combined to annotate structures in a novel 3D adult penis atlas that can be downloaded, viewed at any angle, and manipulated to examine the relationship of various structures.
| S-EPMC5012965 | biostudies-literature
Project description:Despite vast numbers of studies of stained cells in the mouse brain, no current brain atlas provides region-by-region neuron counts. In fact, neuron numbers are only available for about 4% of brain of regions and estimates often vary by as much as 3-fold. Here we provide a first 3D cell atlas for the whole mouse brain, showing cell positions constructed algorithmically from whole brain Nissl and gene expression stains, and compared against values from the literature. The atlas provides the densities and positions of all excitatory and inhibitory neurons, astrocytes, oligodendrocytes, and microglia in each of the 737 brain regions defined in the AMBA. The atlas is dynamic, allowing comparison with previously reported numbers, addition of cell types, and improvement of estimates as new data is integrated. The atlas also provides insights into cellular organization only possible at this whole brain scale, and is publicly available.
| S-EPMC6280067 | biostudies-literature
Project description:Background The molecular mechanisms mediating postnatal loss of cardiac regeneration in mammals are not fully understood. We aimed to provide an integrated resource of mRNA , protein, and metabolite changes in the neonatal heart for identification of metabolism-related mechanisms associated with cardiac regeneration. Methods and Results Mouse ventricular tissue samples taken on postnatal day 1 (P01), P04, P09, and P23 were analyzed with RNA sequencing and global proteomics and metabolomics. Gene ontology analysis, KEGG pathway analysis, and fuzzy c-means clustering were used to identify up- or downregulated biological processes and metabolic pathways on all 3 levels, and Ingenuity pathway analysis (Qiagen) was used to identify upstream regulators. Differential expression was observed for 8547 mRNA s and for 1199 of 2285 quantified proteins. Furthermore, 151 metabolites with significant changes were identified. Differentially regulated metabolic pathways include branched chain amino acid degradation (upregulated at P23), fatty acid metabolism (upregulated at P04 and P09; downregulated at P23) as well as the HMGCS ( HMG -CoA [hydroxymethylglutaryl-coenzyme A] synthase)-mediated mevalonate pathway and ketogenesis (transiently activated). Pharmacological inhibition of HMGCS in primary neonatal cardiomyocytes reduced the percentage of BrdU-positive cardiomyocytes, providing evidence that the mevalonate and ketogenesis routes may participate in regulating the cardiomyocyte cell cycle. Conclusions This study is the first systems-level resource combining data from genomewide transcriptomics with global quantitative proteomics and untargeted metabolomics analyses in the mouse heart throughout the early postnatal period. These integrated data of molecular changes associated with the loss of cardiac regeneration may open up new possibilities for the development of regenerative therapies.
| S-EPMC6474944 | biostudies-literature
Project description:The mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remain poorly understood. Here, we generate a metabolome atlas of the aging wildtype mouse brain from 10 anatomical regions spanning from adolescence to old age. We combine data from three assays and structurally annotate 1,547 metabolites. Almost all metabolites significantly differ between brain regions or age groups, but not by sex. A shift in sphingolipid patterns during aging related to myelin remodeling is accompanied by large changes in other metabolic pathways. Functionally related brain regions (brain stem, cerebrum and cerebellum) are also metabolically similar. In cerebrum, metabolic correlations markedly weaken between adolescence and adulthood, whereas at old age, cross-region correlation patterns reflect decreased brain segregation. We show that metabolic changes can be mapped to existing gene and protein brain atlases. The brain metabolome atlas is publicly available ( https://mouse.atlas.metabolomics.us/ ) and serves as a foundation dataset for future metabolomic studies.
| S-EPMC8519999 | biostudies-literature