scholarly journals The Mouse Brain Transcriptome by SAGE: Differences in Gene Expression between P30 Brains of the Partial Trisomy 16 Mouse Model of Down Syndrome (Ts65Dn) and Normals

2000 ◽  
Vol 10 (12) ◽  
pp. 2006-2021 ◽  
Author(s):  
Roman Chrast ◽  
Hamish S. Scott ◽  
Marie Pierre Papasavvas ◽  
Colette Rossier ◽  
Emmanuel S. Antonarakis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Down Syndrome ◽  
Mouse Brain ◽  
Expression Profiles ◽  
System Structure ◽  
Abnormal Development ◽  
Mammalian Brain ◽  
Normal Male ◽  
Normal Female ◽  
Brain Transcriptome

Trisomy 21, or Down syndrome (DS), is the most common genetic cause of mental retardation. Changes in the neuropathology, neurochemistry, neurophysiology, and neuropharmacology of DS patients' brains indicate that there is probably abnormal development and maintenance of central nervous system structure and function. The segmental trisomy mouse (Ts65Dn) is a model of DS that shows analogous neurobehavioral defects. We have studied the global gene expression profiles of normal and Ts65Dn male and normal female mice brains (P30) using the serial analysis of gene expression (SAGE) technique. From the combined sample we collected a total of 152,791 RNA tags and observed 45,856 unique tags in the mouse brain transcriptome. There are 14 ribosomal protein genes (nine underexpressed) among the 330 statistically significant differences between normal male and Ts65Dn male brains, which possibly implies abnormal ribosomal biogenesis in the development and maintenance of DS phenotypes. This study contributes to the establishment of a mouse brain transcriptome and provides the first overall analysis of the differences in gene expression in aneuploid versus normal mammalian brain cells.

Neural system-enriched gene expression: relationship to biological pathways and neurological diseases

2004 ◽  
Vol 18 (2) ◽  
pp. 167-183 ◽  
Author(s):  
Jianhua Zhang ◽  
Amy Moseley ◽  
Anil G. Jegga ◽  
Ashima Gupta ◽  
David P. Witte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nervous System ◽  
Intracellular Signaling ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene List ◽  
Structure And Function ◽  
System Structure ◽  
Psychiatric Disease ◽  
And Function

To understand the commitment of the genome to nervous system differentiation and function, we sought to compare nervous system gene expression to that of a wide variety of other tissues by gene expression database construction and mining. Gene expression profiles of 10 different adult nervous tissues were compared with that of 72 other tissues. Using ANOVA, we identified 1,361 genes whose expression was higher in the nervous system than other organs and, separately, 600 genes whose expression was at least threefold higher in one or more regions of the nervous system compared with their median expression across all organs. Of the 600 genes, 381 overlapped with the 1,361-gene list. Limited in situ gene expression analysis confirmed that identified genes did represent nervous system-enriched gene expression, and we therefore sought to evaluate the validity and significance of these top-ranked nervous system genes using known gene literature and gene ontology categorization criteria. Diverse functional categories were present in the 381 genes, including genes involved in intracellular signaling, cytoskeleton structure and function, enzymes, RNA metabolism and transcription, membrane proteins, as well as cell differentiation, death, proliferation, and division. We searched existing public sites and identified 110 known genes related to mental retardation, neurological disease, and neurodegeneration. Twenty-one of the 381 genes were within the 110-gene list, compared with a random expectation of 5. This suggests that the 381 genes provide a candidate set for further analyses in neurological and psychiatric disease studies and that as a field, we are as yet, far from a large-scale understanding of the genes that are critical for nervous system structure and function. Together, our data indicate the power of profiling an individual biologic system in a multisystem context to gain insight into the genomic basis of its structure and function.

scholarly journals Integrated analysis of the aging brain transcriptome and proteome in tauopathy

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Carl Grant Mangleburg ◽  
Timothy Wu ◽  
Hari K. Yalamanchili ◽  
Caiwei Guo ◽  
Yi-Chen Hsieh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Mutant Form ◽  
Brain Gene Expression ◽  
Brain Transcriptome ◽  
Age Dependent

Abstract Background Tau neurofibrillary tangle pathology characterizes Alzheimer’s disease and other neurodegenerative tauopathies. Brain gene expression profiles can reveal mechanisms; however, few studies have systematically examined both the transcriptome and proteome or differentiated Tau- versus age-dependent changes. Methods Paired, longitudinal RNA-sequencing and mass-spectrometry were performed in a Drosophila model of tauopathy, based on pan-neuronal expression of human wildtype Tau (TauWT) or a mutant form causing frontotemporal dementia (TauR406W). Tau-induced, differentially expressed transcripts and proteins were examined cross-sectionally or using linear regression and adjusting for age. Hierarchical clustering was performed to highlight network perturbations, and we examined overlaps with human brain gene expression profiles in tauopathy. Results TauWT induced 1514 and 213 differentially expressed transcripts and proteins, respectively. TauR406W had a substantially greater impact, causing changes in 5494 transcripts and 697 proteins. There was a ~ 70% overlap between age- and Tau-induced changes and our analyses reveal pervasive bi-directional interactions. Strikingly, 42% of Tau-induced transcripts were discordant in the proteome, showing opposite direction of change. Tau-responsive gene expression networks strongly implicate innate immune activation. Cross-species analyses pinpoint human brain gene perturbations specifically triggered by Tau pathology and/or aging, and further differentiate between disease amplifying and protective changes. Conclusions Our results comprise a powerful, cross-species functional genomics resource for tauopathy, revealing Tau-mediated disruption of gene expression, including dynamic, age-dependent interactions between the brain transcriptome and proteome.

scholarly journals Hippocampal transcriptomic responses to cellular dissociation

2017 ◽  
Author(s):  
Rayna M. Harris ◽  
Hsin-Yi Kao ◽  
Juan Marcos Alarcón ◽  
Hans A. Hofmann ◽  
André A. Fenton
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Research Effort ◽  
Expression Profiles ◽  
Research Question ◽  
Gene Expression Profiles ◽  
Long Term Potentiation ◽  
System Structure ◽  
Neural Function ◽  
The Impact

AbstractSingle-neuron gene expression studies may be especially important for understanding nervous system structure and function because of the neuron-specific functionality and plasticity that defines functional neural circuits. Cellular dissociation is a prerequisite technical manipulation for single-cell and single cell-population studies, but the extent to which the cellular dissociation process affects neural gene expression has not been determined. This information is necessary for interpreting the results of experimental manipulations that affect neural function such as learning and memory. The goal of this research was to determine the impact of chemical cell dissociation on brain transcriptomes. We compared gene expression of microdissected samples from the dentate gyrus (DG), CA3, and CA1 subfields of the mouse hippocampus either prepared by a standard tissue homogenization protocol or subjected to a chemical cellular dissociation procedure. We report that compared to homogenization, chemical cellular dissociation alters about 350 genes or 2% of the hippocampal transcriptome. While only a few genes canonically implicated in long-term potentiation (LTP) and fear memory change expression levels in response to the dissociation procedure, these data indicate that sample preparation can affect gene expression profiles, which might confound interpretation of results depending on the research question. This study is important for the investigation of any complex tissues as research effort moves from subfield level analysis to single cell analysis of gene expression.

scholarly journals Precocious clonal hematopoiesis in Down syndrome is accompanied by immune dysregulation

2021 ◽  
Vol 5 (7) ◽  
pp. 1791-1796
Author(s):  
L. Alexander Liggett ◽  
Matthew D. Galbraith ◽  
Keith P. Smith ◽  
Kelly D. Sullivan ◽  
Ross E. Granrath ◽  
...  
Keyword(s):  
Gene Expression ◽  
Down Syndrome ◽  
Trisomy 21 ◽  
Expression Profiles ◽  
Clonal Evolution ◽  
Gene Expression Profiles ◽  
Immune Dysregulation ◽  
Children With Down Syndrome ◽  
Clonal Hematopoiesis ◽  
Key Points

Key Points Children with Down syndrome develop early signs of clonal evolution that resemble traditional clonal hematopoiesis. Children with trisomy 21 who exhibit clonal hematopoiesis display cytokine and gene expression profiles indicative of disrupted immunity.

scholarly journals Replicability of spatial gene expression atlas data from the adult mouse brain

2020 ◽  
Author(s):  
Shaina Lu ◽  
Cantin Ortiz ◽  
Daniel Fürth ◽  
Stephan Fischer ◽  
Konstantinos Meletis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mouse Brain ◽  
Spatial Data ◽  
Adult Mouse ◽  
Brain Area ◽  
Physical Distance ◽  
Mammalian Brain ◽  
Data Types ◽  
Adult Mouse Brain ◽  
Whole Brain

AbstractBackgroundSpatial gene expression is particularly interesting in the mammalian brain, with the potential to serve as a link between many data types. 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 sub-divisions, between the Allen Institute’s in situ hybridization data from the adult mouse brain (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.ResultsWe use 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, but that performance is higher in the ABA than ST. Further, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bi-directionally. Finally, while an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset.ConclusionsIn 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.

scholarly journals Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain

2014 ◽  
pp. 154-161 ◽  
Author(s):  
Julio Cesar Montoya ◽  
Dianora Fajardo ◽  
Ángela Peña ◽  
Adalberto Sánchez ◽  
Martha C Domínguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Down Syndrome ◽  
Human Brain ◽  
Critical Region ◽  
Expression Profiles ◽  
Brain Atlas ◽  
Normal Human Brain ◽  
Normal Human ◽  
The Brain ◽  
Brain Homeostasis

Background: The information of gene expression obtained from databases, have made possible the extraction and analysis of data related with several molecular processes involving not only in brain homeostasis but its disruption in some neuropathologies; principally in Down syndrome and the Alzheimer disease. Objective: To correlate the levels of transcription of 19 genes located in the Down Syndrome Critical Region (DSCR) with their expression in several substructures of normal human brain. Methods: There were obtained expression profiles of 19 DSCR genes in 42 brain substructures, from gene expression values available at the database of the human brain of the Brain Atlas of the Allen Institute for Brain Sciences", (http://human.brain-map.org/). The co-expression patterns of DSCR genes in brain were calculated by using multivariate statistical methods. Results: Highest levels of gene expression were registered at caudate nucleus, nucleus accumbens and putamen among central areas of cerebral cortex. Increased expression levels of RCAN1 that encode by a protein involved in signal transduction process of the CNS were recorded for PCP4 that participates in the binding to calmodulin and TTC3; a protein that is associated with differentiation of neurons. That previously idenjpgied brain structures play a crucial role in the learning process, in different class of memory and in motor skills. Conclusion: The precise regulation of DSCR gene expression is crucial to maintain the brain homeostasis, especially in those areas with high levels of gene expression associated with a remarkable process of learning and cognition.

scholarly journals Integrated analysis of the aging brain transcriptome and proteome in tauopathy

2020 ◽  
Author(s):  
Carl Grant Mangleburg ◽  
Timothy Wu ◽  
Hari K. Yalamanchili ◽  
Caiwei Guo ◽  
Yi-Chen Hsieh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Aging Brain ◽  
Brain Gene Expression ◽  
Brain Transcriptome ◽  
Age Dependent

AbstractBackgroundTau neurofibrillary tangle pathology characterizes Alzheimer’s disease and other neurodegenerative tauopathies. Brain gene expression profiles can reveal mechanisms; however, few studies have systematically examined both the transcriptome and proteome or differentiated Tau- versus age-dependent changes.MethodsPaired, longitudinal RNA-sequencing and mass-spectrometry were performed in a Drosophila model of tauopathy, based on pan-neuronal expression of human wildtype Tau (TauWT) or a mutation causing frontotemporal dementia (TauR406W). Tau-induced, differentially expressed transcripts and proteins were examined cross-sectionally or using linear regression and adjusting for age. Hierarchical clustering was performed to highlight network perturbations, and we examined overlaps with human brain gene expression profiles in tauopathy.ResultsTauWT induced 1,514 and 213 differentially expressed transcripts and proteins, respectively. TauR406W had a substantially greater impact, causing changes in 5,494 transcripts and 697 proteins. There was a ~70% overlap between age- and Tau-induced changes and our analyses reveal pervasive bi-directional interactions. Strikingly, 42% of Tau-induced transcripts were discordant in the proteome, showing opposite direction of change. Tau-responsive gene expression networks strongly implicate innate immune activation, despite the absence of microglia in flies. Cross-species analyses pinpoint human brain gene perturbations specifically triggered by Tau pathology and/or aging, and further differentiate between disease amplifying and protective changes.ConclusionsOur results comprise a powerful, cross-species functional genomics resource for tauopathy, revealing Tau-mediated disruption of gene expression, including dynamic, age-dependent interactions between the brain transcriptome and proteome.

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