scholarly journals Arousal-dependent auditory response in the brain of Bengalese finches as measured by gene expression

2021 ◽  
Author(s):  
Takafumi Iizuka ◽  
Chihiro Mori ◽  
Kazuo Okanoya
Keyword(s):  
Gene Expression ◽  
Auditory Feedback ◽  
Neural Circuit ◽  
Electrophysiological Study ◽  
Early Gene ◽  
Whole Brain ◽  
Auditory Responses ◽  
Outstanding Question ◽  
Auditory Suppression ◽  
The Brain

Songbirds use auditory feedback to maintain their own songs. Juveniles also memorize a tutor song and use memory as a template to make up their own songs through auditory feedback. A recent electrophysiological study revealed that HVC neurons respond to BOS playback only in low arousal, sleeping, or anesthetized conditions. One outstanding question is how does auditory suppression occur in the brain? Here, we determined how arousal affects auditory responses simultaneously in the whole brain and over the song neural circuit in Bengalese finches, using the immediate early gene egr-1 as a marker of neural activity. Our results showed that auditory responses in the low-arousal state were less susceptible to gating, which was also confirmed by gene expression, and that the suppression may be weaker than observed in previous zebra finch studies. This may be because the Bengalese finch is a domesticated species. In addition, our results suggest that information may flow from the MLd.I of the midbrain to higher auditory regions. Altogether, this study presents a new attempt to explore the auditory suppression network by simultaneously investigating the whole brain using molecular biology methods.

scholarly journals Vascular Genomics of the Human Brain

2002 ◽  
Vol 22 (3) ◽  
pp. 245-252 ◽  
Author(s):  
Eric V. Shusta ◽  
Ruben J. Boado ◽  
Gary W. Mathern ◽  
William M. Pardridge
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Differential Gene Expression ◽  
Molecular Transport ◽  
Brain Diseases ◽  
Microvascular Endothelium ◽  
Whole Brain ◽  
Differential Gene ◽  
Brain Microvasculature ◽  
The Brain

The microvasculature of the human brain plays an important role in the development and maintenance of the central nervous system and in the pathogenesis of brain diseases, and is the site of differential gene expression within the brain. However, human brain microvascular-specific genes may not be detected in whole-brain gene microarray because the volume of the brain microvascular endothelium is relatively small (0.1%) compared with the whole brain. Therefore, the differential gene expression within the human brain microvasculature was evaluated using suppression subtractive hybridization with RNA isolated from human brain microvessels. Gene identification was restricted to the first 71 clones that were differentially expressed at the brain microvasculature. Twenty of these were genes encoding proteins with known function that were involved in angiogenesis, neurogenesis, molecular transport, and maintenance of endothelial tight junctions or the cytoskeleton. Eighteen genes coding for proteins of an unknown function were identified, including five genes containing satellite DNA sequences. The results provide the initial outline of the genomics of the human brain microvasculature, and have implications for the identification of both targets for brain-specific drug transport and changes in microvascular gene expression in brain diseases.

scholarly journals Estradiol and the Developing Brain

2008 ◽  
Vol 88 (1) ◽  
pp. 91-134 ◽  
Author(s):  
MARGARET M. McCARTHY
Keyword(s):  
Gene Expression ◽  
Endocrine Disrupting Compounds ◽  
Developing Brain ◽  
Early Gene ◽  
Calcium Handling ◽  
Neuroprotective Effects ◽  
Regulate Gene Expression ◽  
Endocrine Disrupting ◽  
The Brain ◽  
Considerable Concern

Estradiol is the most potent and ubiquitous member of a class of steroid hormones called estrogens. Fetuses and newborns are exposed to estradiol derived from their mother, their own gonads, and synthesized locally in their brains. Receptors for estradiol are nuclear transcription factors that regulate gene expression but also have actions at the membrane, including activation of signal transduction pathways. The developing brain expresses high levels of receptors for estradiol. The actions of estradiol on developing brain are generally permanent and range from establishment of sex differences to pervasive trophic and neuroprotective effects. Cellular end points mediated by estradiol include the following: 1) apoptosis, with estradiol preventing it in some regions but promoting it in others; 2) synaptogenesis, again estradiol promotes in some regions and inhibits in others; and 3) morphometry of neurons and astrocytes. Estradiol also impacts cellular physiology by modulating calcium handling, immediate-early-gene expression, and kinase activity. The specific mechanisms of estradiol action permanently impacting the brain are regionally specific and often involve neuronal/glial cross-talk. The introduction of endocrine disrupting compounds into the environment that mimic or alter the actions of estradiol has generated considerable concern, and the developing brain is a particularly sensitive target. Prostaglandins, glutamate, GABA, granulin, and focal adhesion kinase are among the signaling molecules co-opted by estradiol to differentiate male from female brains, but much remains to be learned. Only by understanding completely the mechanisms and impact of estradiol action on the developing brain can we also understand when these processes go awry.

scholarly journals Identification and analysis of vocal communication pathways in birds through inducible gene expression

2004 ◽  
Vol 76 (2) ◽  
pp. 243-246 ◽  
Author(s):  
Claudio V. Mello
Keyword(s):  
Gene Expression ◽  
Auditory Processing ◽  
Vocal Communication ◽  
Vocal Learning ◽  
Early Gene ◽  
Brain Areas ◽  
Control Brain ◽  
Activity Dependent ◽  
The Brain ◽  
Inducible Gene

The immediate-early gene zenk is an activity-dependent gene highly induced in auditory processing or vocal motor control brain areas when birds engage in hearing or producing song, respectively. Studies of the expression of zenk in songbirds and other avian groups will be reviewed here briefly, with a focus on how this analysis has generated new insights on the brain pathways and mechanisms involved in perceptual and motor aspects of vocal communication and vocal learning.

scholarly journals Assessing the replicability of spatial gene expression using atlas data from the adult mouse brain

PLoS Biology ◽  
2021 ◽  
Vol 19 (7) ◽  
pp. e3001341
Author(s):  
Shaina Lu ◽  
Cantin Ortiz ◽  
Daniel Fürth ◽  
Stephan Fischer ◽  
Konstantinos Meletis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Linear Regression ◽  
Mouse Brain ◽  
Cell Biology ◽  
Adult Mouse ◽  
Brain Area ◽  
Adult Mouse Brain ◽  
Whole Brain ◽  
Spatial Expression ◽  
The Brain

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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