scholarly journals Quantitative gene expression profiling of mouse brain regions reveals differential transcripts conserved in human and affected in disease models

2008 ◽  
Vol 33 (2) ◽  
pp. 170-179 ◽  
Author(s):  
Camille Brochier ◽  
Marie-Claude Gaillard ◽  
Elsa Diguet ◽  
Nicolas Caudy ◽  
Carole Dossat ◽  
...  
Keyword(s):  
Gene Expression ◽  
Substantia Nigra ◽  
Mouse Model ◽  
Human Brain ◽  
Mouse Brain ◽  
Wild Type Mouse ◽  
Brain Regions ◽  
Expression Data ◽  
Brain Functions

Using serial analysis of gene expression, we collected quantitative transcriptome data in 11 regions of the adult wild-type mouse brain: the orbital, prelimbic, cingulate, motor, somatosensory, and entorhinal cortices, the caudate-putamen, the nucleus accumbens, the thalamus, the substantia nigra, and the ventral tegmental area. With >1.2 million cDNA tags sequenced, this database is a powerful resource to explore brain functions and disorders. As an illustration, we performed interregional comparisons and found 315 differential transcripts. Most of them are poorly characterized and 20% lack functional annotation. For 78 differential transcripts, we provide independent expression level measurements in mouse brain regions by real-time quantitative RT-PCR. We also show examples where we used in situ hybridization to achieve infrastructural resolution. For 30 transcripts, we next demonstrated that regional enrichment is conserved in the human brain. We then quantified the expression levels of region-enriched transcripts in the R6/2 mouse model of Huntington disease and the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of Parkinson disease and observed significant alterations in the striatum, cerebral cortex, thalamus and substantia nigra of R6/2 mice and in the striatum of MPTP-treated mice. These results show that the gene expression data provided here for the mouse brain can be used to explore pathophysiological models and disclose transcripts differentially expressed in human brain regions.

scholarly journals A pH-eQTL interaction at the RIT2-SYT4 Parkinson's disease risk locus in the substantia nigra

2020 ◽  
Author(s):  
Sejal Patel ◽  
Derek Howard ◽  
Leon French
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Human Brain ◽  
Disease Risk ◽  
Brain Regions ◽  
Dopamine Neurons ◽  
Postmortem Human Brain ◽  
Increased Risk

BACKGROUND: Parkinson's disease (PD) causes severe motor and cognitive disabilities that result from the progressive loss of dopamine neurons in the substantia nigra. The rs12456492 variant in the RIT2 gene has been repeatedly associated with increased risk for Parkinson's disease. From a transcriptomic perspective, a meta-analysis found that RIT2 gene expression is correlated with pH in the human brain. OBJECTIVE: To assess pH associations at the RIT2-SYT4 locus. METHODS: Linear models to examine two datasets that assayed rs12456492, gene expression, and pH in the postmortem human brain. RESULTS: Using the BrainEAC dataset, we replicate the positive correlation between RIT2 gene expression and pH in the human brain. Furthermore, we found that the relationship between expression and pH is influenced by rs12456492. When tested across ten brain regions, this interaction is specifically found in the substantia nigra. A similar association was found for the co-localized SYT4 gene. In addition, SYT4 associations are stronger in a combined model with both genes, and the SYT4 interaction appears to be specific to males. In the GTEx dataset, the pH associations involving rs12456492 and expression of either SYT4 and RIT2 was not seen. This null finding may be due to the short postmortem intervals (PMI) of the GTEx tissue samples. In the BrainEAC data, we tested the effect of PMI and only observed the interactions in the longer PMI samples. CONCLUSIONS: These previously unknown associations suggest novel mechanistic roles for rs12456492, RIT2, and SYT4 in the regulation of pH in the substantia nigra.

scholarly journals Comparing the Expression of Genes Related to Serotonin (5-HT) in C57BL/6J Mice and Humans Based on Data Available at the Allen Mouse Brain Atlas and Allen Human Brain Atlas

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
C. A. Acevedo-Triana ◽  
L. A. León ◽  
F. P. Cardenas
Keyword(s):  
Human Brain ◽  
Mouse Brain ◽  
Expression Patterns ◽  
Brain Atlas ◽  
Expression Data ◽  
Expression Of Genes ◽  
High Degree ◽  
The Relationship ◽  
Allen Mouse Brain Atlas

Brain atlases are tools based on comprehensive studies used to locate biological characteristics (structures, connections, proteins, and gene expression) in different regions of the brain. These atlases have been disseminated to the point where tools have been created to store, manage, and share the information they contain. This study used the data published by the Allen Mouse Brain Atlas (2004) for mice (C57BL/6J) and Allen Human Brain Atlas (2010) for humans (6 donors) to compare the expression of serotonin-related genes. Genes of interest were searched for manually in each case (in situ hybridization for mice and microarrays for humans), normalized expression data (z-scores) were extracted, and the results were graphed. Despite the differences in methodology, quantification, and subjects used in the process, a high degree of similarity was found between expression data. Here we compare expression in a way that allows the use of translational research methods to infer and validate knowledge. This type of study allows part of the relationship between structures and functions to be identified, by examining expression patterns and comparing levels of expression in different states, anatomical correlations, and phenotypes between different species. The study concludes by discussing the importance of knowing, managing, and disseminating comprehensive, open-access studies in neuroscience.

scholarly journals Gene expression heterogeneity during brain development and aging: temporal changes and functional consequences

2019 ◽  
Author(s):  
Ulaş Işıldak ◽  
Mehmet Somel ◽  
Janet M. Thornton ◽  
Handan Melike Dönertaş
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Meta Analysis ◽  
Brain Regions ◽  
Genetic Alterations ◽  
Individual Heterogeneity ◽  
Brain Functions ◽  
Aging Period ◽  
Gene Expression Heterogeneity ◽  
Development And Aging

AbstractCells in largely non-mitotic tissues such as the brain are prone to stochastic (epi-)genetic alterations that may cause increased variability between cells and individuals over time. Although increased inter-individual heterogeneity in gene expression was previously reported, whether this process starts during development or if it is restricted to the aging period has not yet been studied. The regulatory dynamics and functional significance of putative aging-related heterogeneity are also unknown. Here we address these by a meta-analysis of 19 transcriptome datasets from diverse human brain regions. We observed a significant increase in inter-individual heterogeneity during aging (20+ years) compared to postnatal development (0 to 20 years). Increased heterogeneity during aging was consistent among different brain regions at the gene level and associated with lifespan regulation and neuronal functions. Overall, our results show that increased expression heterogeneity is a characteristic of aging human brain, and may influence aging-related changes in brain functions.

scholarly journals Assessing the requirements of prenatal UBE3A expression for rescue of behavioral phenotypes in a mouse model for Angelman syndrome

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Monica Sonzogni ◽  
Peipei Zhai ◽  
Edwin J. Mientjes ◽  
Geeske M. van Woerden ◽  
Ype Elgersma
Keyword(s):  
Gene Expression ◽  
Mouse Model ◽  
Brain Development ◽  
Mouse Brain ◽  
Angelman Syndrome ◽  
Neurodevelopmental Disorder ◽  
Brain Regions ◽  
Critical Function ◽  
Behavioral Phenotypes ◽  
Mouse Brain Development

Abstract Background Angelman syndrome (AS) is a rare neurodevelopmental disorder caused by the loss of functional ubiquitin protein ligase E3A (UBE3A). In neurons, UBE3A expression is tightly regulated by a mechanism of imprinting which suppresses the expression of the paternal UBE3A allele. Promising treatment strategies for AS are directed at activating paternal UBE3A gene expression. However, for such strategies to be successful, it is important to know when such a treatment should start, and how much UBE3A expression is needed for normal embryonic brain development. Methods Using a conditional mouse model of AS, we further delineated the critical period for UBE3A expression during early brain development. Ube3a gene expression was induced around the second week of gestation and mouse phenotypes were assessed using a behavioral test battery. To investigate the requirements of embryonic UBE3A expression, we made use of mice in which the paternal Ube3a allele was deleted. Results We observed a full behavioral rescue of the AS mouse model phenotypes when Ube3a gene reactivation was induced around the start of the last week of mouse embryonic development. We found that full silencing of the paternal Ube3a allele was not completed till the first week after birth but that deletion of the paternal Ube3a allele had no significant effect on the assessed phenotypes. Limitations Direct translation to human is limited, as we do not precisely know how human and mouse brain development aligns over gestational time. Moreover, many of the assessed phenotypes have limited translational value, as the underlying brain regions involved in these tasks are largely unknown. Conclusions Our findings provide further important insights in the requirement of UBE3A expression during brain development. We found that loss of up to 50% of UBE3A protein during prenatal mouse brain development does not significantly impact the assessed mouse behavioral phenotypes. Together with previous findings, our results indicate that the most critical function for mouse UBE3A lies in the early postnatal period between birth and P21.

scholarly journals A pH-eQTL Interaction at the RIT2–SYT4 Parkinson’s Disease Risk Locus in the Substantia Nigra

2021 ◽  
Vol 13 ◽  
Author(s):  
Sejal Patel ◽  
Derek Howard ◽  
Leon French
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Human Brain ◽  
Disease Risk ◽  
Brain Regions ◽  
Dopamine Neurons ◽  
Postmortem Human Brain ◽  
Increased Risk

Parkinson’s disease causes severe motor and cognitive disabilities that result from the progressive loss of dopamine neurons in the substantia nigra. The rs12456492 variant in the RIT2 gene has been repeatedly associated with increased risk for Parkinson’s disease. From a transcriptomic perspective, a meta-analysis found that RIT2 gene expression is correlated with pH in the human brain. To assess these pH associations in relation to Parkinson’s disease risk, we examined the two datasets that assayed rs12456492, gene expression, and pH in the postmortem human brain. Using the BrainEAC dataset, we replicate the positive correlation between RIT2 gene expression and pH in the human brain (n = 100). Furthermore, we found that the relationship between expression and pH is influenced by rs12456492. When tested across ten brain regions, this interaction is specifically found in the substantia nigra. A similar association was found for the co-localized SYT4 gene. In addition, SYT4 associations are stronger in a combined model with both genes, and the SYT4 interaction appears to be specific to males. In the Genotype-Tissue Expression (GTEx) dataset, the pH associations involving rs12456492 and expression of either SYT4 and RIT2 were not seen. This null finding may be due to the short postmortem intervals of the GTEx tissue samples. In the BrainEAC data, we tested the effect of postmortem interval and only observed the interactions in samples with the longer intervals. These previously unknown associations suggest novel roles for rs12456492, RIT2, and SYT4 in the regulation and response to pH in the substantia nigra.

scholarly journals Identification of spatial compartments in tissue from in situ sequencing data

2019 ◽  
Author(s):  
Gabriele Partel ◽  
Markus M. Hilscher ◽  
Giorgia Milli ◽  
Leslie Solorzano ◽  
Anna H. Klemm ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Mouse Brain ◽  
Gene Expression Analysis ◽  
Spatial Organization ◽  
Biological Function ◽  
Brain Regions ◽  
Sequencing Data ◽  
Spatially Resolved

ABSTRACTSpatial organization of tissue characterizes biological function, and spatially resolved gene expression has the power to reveal variations of features with high resolution. Here, we propose a novel graph-based in situ sequencing decoding approach that improves recall, enabling precise spatial gene expression analysis. We apply our method on in situ sequencing data from mouse brain sections, identify spatial compartments that correspond with known brain regions, and relate them with tissue morphology.

scholarly journals Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression

2019 ◽  
Vol 36 (3) ◽  
pp. 782-788 ◽  
Author(s):  
Jiebiao Wang ◽  
Bernie Devlin ◽  
Kathryn Roeder
Keyword(s):  
Gene Expression ◽  
Empirical Bayes ◽  
Brain Regions ◽  
Tissue Level ◽  
Supplementary Information ◽  
Specific Gene ◽  
Expression Data ◽  
Cell Type ◽  
Multiple Measurements ◽  
Cell Type Specific

Abstract Motivation Patterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects. Results Complementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g. multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL). Availability and implementation We implement this method as an R package MIND, hosted on https://github.com/randel/MIND. Supplementary information Supplementary data are available at Bioinformatics online.

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