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accession-icon GSE2164
Gender-specific gene expression in post-mortem human brain
  • organism-icon Homo sapiens
  • sample-icon 87 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a)

Description

Gender differences in brain development and in the prevalence of neuropsychiatric disorders such as depression have been reported. Gender differences in human brain might be related to patterns of gene expression. Microarray technology is one useful method for investigation of gene expression in brain. We investigated gene expression, cell types, and regional expression patterns of differentially expressed sex chromosome genes in brain. We profiled gene expression in male and female dorsolateral prefrontal cortex, anterior cingulate cortex, and cerebellum using the Affymetrix oligonucleotide microarray platform. Differentially expressed genes between males and females on the Y chromosome (DBY, SMCY, UTY, RPS4Y, and USP9Y) and X chromosome (XIST) were confirmed using real-time PCR measurements. In situ hybridization confirmed the differential expression of gender-specific genes and neuronal expression of XIST, RPS4Y, SMCY, and UTY in three brain regions examined. The XIST gene, which silences gene expression on regions of the X chromosome, is expressed in a subset of neurons. Since a subset of neurons express gender-specific genes, neural subpopulations may exhibit a subtle sexual dimorphism at the level of differences in gene regulation and function. The distinctive pattern of neuronal expression of XIST, RPS4Y, SMCY, and UTY and other sex chromosome genes in neuronal subpopulations may possibly contribute to gender differences in prevalence noted for some neuropsychiatric disorders. Studies of the protein expression of these sex-chromosome-linked genes in brain tissue are required to address the functional consequences of the observed gene expression differences.

Publication Title

Gender-specific gene expression in post-mortem human brain: localization to sex chromosomes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE6306
Sample Matching by Inferred Agonal Stress in Gene Expression Analyses of the Brain
  • organism-icon Homo sapiens
  • sample-icon 1210 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Gene expression patterns in the brain are strongly influenced by the severity of physiological stress at death. This agonal effect, if not well controlled, can lead to spurious findings in case-control comparisons. While many recent studies match samples by tissue pH and clinically recorded agonal conditions, we found that these commonly used indicators were sometimes at odds with observed stress-related patterns of gene expression, and that matching by these criteria still sometimes results in identifying differences between cases and controls that are primarily driven by residual agonal effects. This problem is analogous to the one in genetic studies, where race and ethnicity are often imprecise proxies for complex environmental and genetic factors.

Publication Title

Sample matching by inferred agonal stress in gene expression analyses of the brain.

Sample Metadata Fields

Subject

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accession-icon GSE45642
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder [control set]
  • organism-icon Homo sapiens
  • sample-icon 667 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

A cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders.

Publication Title

Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.

Sample Metadata Fields

Subject

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accession-icon SRP073813
RNA-sequencing of human post-mortem brain tissues
  • organism-icon Homo sapiens
  • sample-icon 335 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

RNA-seq profiling was conducted on clinically-annotated human post-mortem brain tissues Overall design: We measured the transcriptome in 281 clinically-annotated human post-mortem brain tissues

Publication Title

Post-mortem molecular profiling of three psychiatric disorders.

Sample Metadata Fields

Sex, Specimen part, Race, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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