Asymmetric gene expression in the brain during acute compensation to unilateral vestibular labyrinthectomy in the Mongolian gerbil

2007 ◽  
Vol 16 (4-5) ◽  
pp. 147-169
Author(s):  
Michael E. Shinder ◽  
Murugappan Ramanathan ◽  
Galen D. Kaufman
Keyword(s):  
Gene Expression ◽  
Brain Regions ◽  
Vestibular Compensation ◽  
Compensatory Response ◽  
Gene Target ◽  
Signaling Systems ◽  
Gene Sets ◽  
Vestibular Complex ◽  
Transcriptome Expression ◽  
Cortical Regions

Commercial microarrays were used to identify transcriptome expression within vestibular related brain regions (vestibular brainstem and cerebellum, and caudotemporal cortical regions) during the acute period of recovery following unilateral surgical vestibular labyrinth ablation in the gerbil. As a representative model of vestibular compensation, vestibular lesions in the gerbil produced activation in a common set of genes related to vestibular compensation. The total RNA was prepared and amplified using Affymetrix Gene Chip™ probes from the Rat U34 Neurobiology and R230, and Mouse M430 gene sets, resulting in GCRMA summarized data from S+AA software. Matched rat and mouse genes from gerbil hybridization produced good interspecies synteny. Multiple gene target trends supported global increases in neuron excitability throughout the vestibular brainstem and cerebellum. We focused further on gene expression with anatomically asymmetric activation relative to the lesion, indicative of involvement in rebalancing central vestibular tone during the vestibular compensation process. Cluster analysis revealed distinct spatial (regional and ipsi-contra) and temporal patterns. The asymmetric genes were part of well-defined neuron-related networks and included multiple members of the glutamate and GABA neurotransmitter systems. Transcripts for D3 dopamine, glycine, and some GABA receptor signals increased quickly in the ipsilesional vestibular complex and then increased gradually in the contralateral region, restoring the expression symmetry. Alternatively, the NMDA binding subunit decreased gradually over the acute compensation period in the contralateral vestibular complex. There was evidence for numerous associations between signaling systems with PKC as one possible mediator between early changes in GABA and progressive changes in NMDA signaling. These data begin to define the compensatory response at the level of molecular cascades.

scholarly journals Physical positioning markedly enhances brain transduction after intrathecal AAV9 infusion

2018 ◽  
Vol 4 (11) ◽  
pp. eaau9859 ◽  
Author(s):  
Michael J. Castle ◽  
Yuhsiang Cheng ◽  
Aravind Asokan ◽  
Mark H. Tuszynski
Keyword(s):  
Gene Expression ◽  
Gene Delivery ◽  
Neurological Disorders ◽  
Fold Increase ◽  
Brain Regions ◽  
Intrathecal Administration ◽  
Simple Method ◽  
Virus Serotype ◽  
Cortical Regions ◽  
The Brain

Several neurological disorders may benefit from gene therapy. However, even when using the lead vector candidate for intrathecal administration, adeno-associated virus serotype 9 (AAV9), the strength and distribution of gene transfer to the brain are inconsistent. On the basis of preliminary observations that standard intrathecal AAV9 infusions predominantly drive reporter gene expression in brain regions where gravity might cause cerebrospinal fluid to settle, we tested the hypothesis that counteracting vector “settling” through animal positioning would enhance vector delivery to the brain. When rats are either inverted in the Trendelenburg position or continuously rotated after intrathecal AAV9 infusion, we find (i) a significant 15-fold increase in the number of transduced neurons, (ii) a marked increase in gene delivery to cortical regions, and (iii) superior animal-to-animal consistency of gene expression. Entorhinal, prefrontal, frontal, parietal, hippocampal, limbic, and basal forebrain neurons are extensively transduced: 95% of transduced cells are neurons, and greater than 70% are excitatory. These findings provide a novel and simple method for broad gene delivery to the cortex and are of substantial relevance to translational programs for neurological disorders, including Alzheimer’s disease and related dementias, stroke, and traumatic brain injury.

scholarly journals Investigating the influence of perinatal nicotine and alcohol exposure on the genetic profiles of dopaminergic neurons in the VTA using miRNA–mRNA analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tina Kazemi ◽  
Shuyan Huang ◽  
Naze G. Avci ◽  
Charlotte Mae K. Waits ◽  
Yasemin M. Akay ◽  
...  
Keyword(s):  
Gene Expression ◽  
Axon Guidance ◽  
Mirna Gene ◽  
Alcohol Exposure ◽  
Brain Regions ◽  
Saline Control ◽  
Perinatal Exposure ◽  
Drug Reinforcement ◽  
Gene Target ◽  
Rat Pups

Abstract Nicotine and alcohol are two of the most commonly used and abused recreational drugs, are often used simultaneously, and have been linked to significant health hazards. Furthermore, patients diagnosed with dependence on one drug are highly likely to be dependent on the other. Several studies have shown the effects of each drug independently on gene expression within many brain regions, including the ventral tegmental area (VTA). Dopaminergic (DA) neurons of the dopamine reward pathway originate from the VTA, which is believed to be central to the mechanism of addiction and drug reinforcement. Using a well-established rat model for both nicotine and alcohol perinatal exposure, we investigated miRNA and mRNA expression of dopaminergic (DA) neurons of the VTA in rat pups following perinatal alcohol and joint nicotine–alcohol exposure. Microarray analysis was then used to profile the differential expression of both miRNAs and mRNAs from DA neurons of each treatment group to further explore the altered genes and related biological pathways modulated. Predicted and validated miRNA-gene target pairs were analyzed to further understand the roles of miRNAs within these networks following each treatment, along with their post transcription regulation points affecting gene expression throughout development. This study suggested that glutamatergic synapse and axon guidance pathways were specifically enriched and many miRNAs and genes were significantly altered following alcohol or nicotine–alcohol perinatal exposure when compared to saline control. These results provide more detailed insight into the cell proliferation, neuronal migration, neuronal axon guidance during the infancy in rats in response to perinatal alcohol/ or nicotine–alcohol exposure.

scholarly journals An atlas of cortical arealization identifies dynamic molecular signatures

Nature ◽  
2021 ◽  
Vol 598 (7879) ◽  
pp. 200-204
Author(s):  
Aparna Bhaduri ◽  
Carmen Sandoval-Espinosa ◽  
Marcos Otero-Garcia ◽  
Irene Oh ◽  
Raymund Yin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Radial Glia ◽  
Expression Patterns ◽  
Brain Structures ◽  
Cell Types ◽  
Brain Regions ◽  
Cortical Areas ◽  
Spatial Differences ◽  
Cortical Regions

AbstractThe human brain is subdivided into distinct anatomical structures, including the neocortex, which in turn encompasses dozens of distinct specialized cortical areas. Early morphogenetic gradients are known to establish early brain regions and cortical areas, but how early patterns result in finer and more discrete spatial differences remains poorly understood1. Here we use single-cell RNA sequencing to profile ten major brain structures and six neocortical areas during peak neurogenesis and early gliogenesis. Within the neocortex, we find that early in the second trimester, a large number of genes are differentially expressed across distinct cortical areas in all cell types, including radial glia, the neural progenitors of the cortex. However, the abundance of areal transcriptomic signatures increases as radial glia differentiate into intermediate progenitor cells and ultimately give rise to excitatory neurons. Using an automated, multiplexed single-molecule fluorescent in situ hybridization approach, we find that laminar gene-expression patterns are highly dynamic across cortical regions. Together, our data suggest that early cortical areal patterning is defined by strong, mutually exclusive frontal and occipital gene-expression signatures, with resulting gradients giving rise to the specification of areas between these two poles throughout successive developmental timepoints.

scholarly journals Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure

2021 ◽  
Author(s):  
Viola Hollestein ◽  
Geert Poelmans ◽  
Natalie Forde ◽  
Christian F Beckmann ◽  
Christine Ecker ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sensory Processing ◽  
Brain Structure ◽  
Symptom Severity ◽  
Expression Profiles ◽  
Brain Regions ◽  
Gene Set Analysis ◽  
Gene Set ◽  
Gene Sets ◽  
Autism Symptomatology

Background: The excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism spectrum disorder (autism). However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. Methods: We used innovative analysis methods - combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT)- to investigate the relationship between genetic variance, brain structure and autism symptomatology of participants from the EU-AIMS LEAP cohort (autism=360, male/female=259/101; neurotypical control participants=279, male/female=178/101) aged 6 to 30 years. Competitive gene-set analysis investigated associations between glutamatergic and GABAergic signaling pathway gene-sets and clinical measures, and CT. Additionally, we investigated expression profiles of the genes within those sets throughout the brain and how those profiles relate to differences in CT between autistic and neurotypical control participants in the same regions. Results: The glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group, while the GABA set was associated with sensory processing measures (using the SSP subscales) across all participants. Brain regions with greater gene expression of both glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants. Conclusions: Our results suggest crucial roles for glutamate and GABA genes in autism symptomatology as well as CT, where GABA is more strongly associated with sensory processing and glutamate more with autism symptom severity. 

scholarly journals An Atlas of Cortical Arealization Identifies Dynamic Molecular Signatures

2021 ◽  
Author(s):  
Aparna Bhaduri ◽  
Carmen Sandoval-Espinosa ◽  
Marcos Otero-Garcia ◽  
Irena Oh ◽  
Raymund Yin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Single Molecule ◽  
Radial Glia ◽  
Expression Patterns ◽  
Brain Structures ◽  
Cell Types ◽  
Brain Regions ◽  
Cortical Areas ◽  
Cortical Regions

The human brain is subdivided into distinct anatomical structures. The neocortex, one of these structures, enables higher-order sensory, associative, and cognitive functions, and in turn encompasses dozens of distinct specialized cortical areas. Early morphogenetic gradients are known to establish an early blueprint for the specification of brain regions and cortical areas. Furthermore, recent studies have uncovered distinct transcriptomic signatures between opposing poles of the developing neocortex1. However, how early, broad developmental patterns result in finer and more discrete spatial differences across the adult human brain remains poorly understood2. Here, we use single-cell RNA-sequencing to profile ten major brain structures and six neocortical areas during peak neurogenesis and early gliogenesis. Our data reveal that distinct cell subtypes are predominantly brain-structure specific. Within the neocortex, we find that even early in the second trimester, a large number of genes are differentially expressed across distinct cortical areas in all cell types, including radial glia, the neural progenitors of the cortex. However, the abundance of areal transcriptomic signatures increases as radial glia differentiate into intermediate progenitor cells and ultimately give rise to excitatory neurons. Using an automated, multiplexed single-molecule fluorescent in situ hybridization (smFISH) approach, we validated the expression pattern of area-specific neuronal genes and also discover that laminar gene expression patterns are highly dynamic across cortical regions. Together, our data suggest that early cortical areal patterning is defined by strong, mutually exclusive frontal and occipital gene expression signatures, with resulting gradients giving rise to the specification of areas between these two poles throughout successive developmental timepoints.

scholarly journals Sequence Alterations of Cortical Genes Linked to Individual Connectivity of the Human Brain

2018 ◽  
Vol 29 (9) ◽  
pp. 3828-3835 ◽  
Author(s):  
Qilong Xin ◽  
Laura Ortiz-Terán ◽  
Ibai Diez ◽  
David L Perez ◽  
Julia Ginsburg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Functional Connectivity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Brain Regions ◽  
Genetic Sequence ◽  
Cortical Areas ◽  
Cortical Regions ◽  
High Degree ◽  
The Brain

Abstract Individual differences in humans are driven by unique brain structural and functional profiles, presumably mediated in part through differential cortical gene expression. However, the relationships between cortical gene expression profiles and individual differences in large-scale neural network organization remain poorly understood. In this study, we aimed to investigate whether the magnitude of sequence alterations in regional cortical genes mapped onto brain areas with high degree of functional connectivity variability across individuals. First, human genetic expression data from the Allen Brain Atlas was used to identify protein-coding genes associated with cortical areas, which delineated the regional genetic signature of specific cortical areas based on sequence alteration profiles. Thereafter, we identified brain regions that manifested high degrees of individual variability by using test-retest functional connectivity magnetic resonance imaging and graph-theory analyses in healthy subjects. We found that rates of genetic sequence alterations shared a distinct spatial topography with cortical regions exhibiting individualized (highly-variable) connectivity profiles. Interestingly, gene expression profiles of brain regions with highly individualized connectivity patterns and elevated number of sequence alterations are devoted to neuropeptide-signaling-pathways and chemical-synaptic-transmission. Our findings support that genetic sequence alterations may underlie important aspects of brain connectome individualities in humans. Significance Statement: The neurobiological underpinnings of our individuality as humans are still an unsolved question. Although the notion that genetic variation drives an individual’s brain organization has been previously postulated, specific links between neural connectivity and gene expression profiles have remained elusive. In this study, we identified the magnitude of population-based sequence alterations in discrete cortical regions and compared them to the brain topological distribution of functional connectivity variability across an independent human sample. We discovered that brain regions with high degree of connectional individuality are defined by increased rates of genetic sequence alterations; these findings specifically implicated genes involved in neuropeptide-signaling pathways and chemical-synaptic transmission. These observations support that genetic sequence alterations may underlie important aspects of the emergence of the brain individuality across humans.

Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer

2018 ◽  
Vol 21 (2) ◽  
pp. 74-83
Author(s):  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Yu-Heng Chen ◽  
Yu-Ching Hsu ◽  
Hung-I Harry Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Therapy ◽  
Cancer Treatment ◽  
Cancer Survival ◽  
Expression Profiles ◽  
Functional Gene ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
Gene Sets

Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.

Gene Set Correlation Analysis and Visualization Using Gene Expression Data

2020 ◽  
Vol 15 ◽  
Author(s):  
Chen-An Tsai ◽  
James J. Chen
Keyword(s):  
Gene Expression ◽  
Correlation Analysis ◽  
Gene Expression Data ◽  
Differentially Expressed Gene ◽  
Differentially Expressed ◽  
Superior Performance ◽  
Expression Data ◽  
Gene Set ◽  
Gene Sets ◽  
Set Correlation

Background: Gene set enrichment analyses (GSEA) provide a useful and powerful approach to identify differentially expressed gene sets with prior biological knowledge. Several GSEA algorithms have been proposed to perform enrichment analyses on groups of genes. However, many of these algorithms have focused on identification of differentially expressed gene sets in a given phenotype. Objective: In this paper, we propose a gene set analytic framework, Gene Set Correlation Analysis (GSCoA), that simultaneously measures within and between gene sets variation to identify sets of genes enriched for differential expression and highly co-related pathways. Methods: We apply co-inertia analysis to the comparisons of cross-gene sets in gene expression data to measure the costructure of expression profiles in pairs of gene sets. Co-inertia analysis (CIA) is one multivariate method to identify trends or co-relationships in multiple datasets, which contain the same samples. The objective of CIA is to seek ordinations (dimension reduction diagrams) of two gene sets such that the square covariance between the projections of the gene sets on successive axes is maximized. Simulation studies illustrate that CIA offers superior performance in identifying corelationships between gene sets in all simulation settings when compared to correlation-based gene set methods. Result and Conclusion: We also combine between-gene set CIA and GSEA to discover the relationships between gene sets significantly associated with phenotypes. In addition, we provide a graphical technique for visualizing and simultaneously exploring the associations of between and within gene sets and their interaction and network. We then demonstrate integration of within and between gene sets variation using CIA and GSEA, applied to the p53 gene expression data using the c2 curated gene sets. Ultimately, the GSCoA approach provides an attractive tool for identification and visualization of novel associations between pairs of gene sets by integrating co-relationships between gene sets into gene set analysis.

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