scholarly journals Oxytocin variation and brain region‐specific gene expression in a domesticated avian species

2021 ◽  
Author(s):  
Yasuko Tobari ◽  
Constantina Theofanopoulou ◽  
Chihiro Mori ◽  
Yoshimi Sato ◽  
Momoka Marutani ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Region ◽  
Avian Species ◽  
Specific Gene ◽  
Specific Gene Expression

scholarly journals Brain region-specific gene expression profiles in freshly isolated rat microglia

2015 ◽  
Vol 9 ◽  
Author(s):  
Karlijn J. Doorn ◽  
John J. P. Brevé ◽  
Benjamin Drukarch ◽  
Hendrikus W. Boddeke ◽  
Inge Huitinga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Region ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Isolated Rat

scholarly journals Brain Region-Specific Gene Expression Activation Required for Reconsolidation and Extinction of Contextual Fear Memory

2009 ◽  
Vol 29 (2) ◽  
pp. 402-413 ◽  
Author(s):  
N. Mamiya ◽  
H. Fukushima ◽  
A. Suzuki ◽  
Z. Matsuyama ◽  
S. Homma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Region ◽  
Fear Memory ◽  
Specific Gene ◽  
Contextual Fear ◽  
Contextual Fear Memory ◽  
Specific Gene Expression

scholarly journals The Neurogenesis Actuator and NR2B/NMDA Receptor Antagonist Ro25-6981 Consistently Improves Spatial Memory Retraining Via Brain Region-Specific Gene Expression

2018 ◽  
Vol 65 (2) ◽  
pp. 167-178 ◽  
Author(s):  
Marina A. Gruden ◽  
Alexander M. Ratmirov ◽  
Zinaida I. Storozheva ◽  
Olga A. Solovieva ◽  
Vladimir V. Sherstnev ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nmda Receptor ◽  
Spatial Memory ◽  
Receptor Antagonist ◽  
Brain Region ◽  
Nmda Receptor Antagonist ◽  
Specific Gene ◽  
Specific Gene Expression

scholarly journals BrainGENIE: The Brain Gene Expression and Network Imputation Engine

2020 ◽  
Author(s):  
Jonathan L. Hess ◽  
Samuel Chen ◽  
Thomas P. Quinn ◽  
Sek Won Kong ◽  
Murray Cairns ◽  
...  
Keyword(s):  
Gene Expression ◽  
Peripheral Blood ◽  
Brain Region ◽  
Ex Vivo ◽  
Specific Gene ◽  
Expression Levels ◽  
Specific Gene Expression ◽  
Brain Gene Expression ◽  
The Brain ◽  
Gene Expression Levels

AbstractEx vivo molecular analysis of the human brain is virtually impossible given major risks and ethical concerns. Transcriptome imputation offers a promising and non-invasive alternative for developing models (albeit imperfect) of brain gene expression in lieu of biopsying brain tissue. Popular tools such as FUSION (Gusev et al., 2016) and PrediXcan (Gamazon et al., 2015) use genotypes at common cis-expression quantitative trait loci (eQTLs) to predict tissue-specific gene expression levels. However, those tools cannot reliably predict expression levels for a majority of genes in the brain. This raises the question of whether an alternative modeling approach should be evaluated to capture greater variance in more genes in the brain that are not yet imputable with existing cis-eQTL imputation tools. To address this problem, we developed a novel transcriptome-imputation method called the Brain Gene Expression and Network Imputation Engine (BrainGENIE) that imputes brain-region-specific gene expression levels from peripheral blood gene expression. BrainGENIE predicted brain-region-specific expression levels for 1,733 – 11,569 genes (cross-validation R2≥0.01, false-discovery rate-adjusted p<0.05), few of which are imputable by PrediXcan. Disease-related transcriptome signals detected by BrainGENIE showed stronger agreement with known transcriptome signatures from postmortem brain when compared with findings from analyses of peripheral blood or S-PrediXcan. BrainGENIE complements and outperforms existing transcriptome-imputation tools, provides biologically meaningful predictions, and opens avenues for studying brain transcriptomes longitudinally. BrainGENIE was developed using R (v.3.6.3, tested in 4.0.2) and is freely available at: https://github.com/hessJ/BrainGENIE.

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