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Human-specific transcriptional networks in the brain.

ABSTRACT: Understanding human-specific patterns of brain gene expression and regulation can provide key insights into human brain evolution and speciation. Here, we use next-generation sequencing, and Illumina and Affymetrix microarray platforms, to compare the transcriptome of human, chimpanzee, and macaque telencephalon. Our analysis reveals a predominance of genes differentially expressed within human frontal lobe and a striking increase in transcriptional complexity specific to the human lineage in the frontal lobe. In contrast, caudate nucleus gene expression is highly conserved. We also identify gene coexpression signatures related to either neuronal processes or neuropsychiatric diseases, including a human-specific module with CLOCK as its hub gene and another module enriched for neuronal morphological processes and genes coexpressed with FOXP2, a gene important for language evolution. These data demonstrate that transcriptional networks have undergone evolutionary remodeling even within a given brain region, providing a window through which to view the foundation of uniquely human cognitive capacities.

SUBMITTER: Konopka G

PROVIDER: S-EPMC3645834 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Human-specific transcriptional networks in the brain.

Konopka Genevieve G Friedrich Tara T Davis-Turak Jeremy J Winden Kellen K Oldham Michael C MC Gao Fuying F Chen Leslie L Wang Guang-Zhong GZ Luo Rui R Preuss Todd M TM Geschwind Daniel H DH

Neuron 20120801 4

Understanding human-specific patterns of brain gene expression and regulation can provide key insights into human brain evolution and speciation. Here, we use next-generation sequencing, and Illumina and Affymetrix microarray platforms, to compare the transcriptome of human, chimpanzee, and macaque telencephalon. Our analysis reveals a predominance of genes differentially expressed within human frontal lobe and a striking increase in transcriptional complexity specific to the human lineage in th ...[more]

PMID: 22920253

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Project description:BackgroundThe epithelial lining of the human epididymis is critical for sperm maturation. This process requires distinct specialized functions in the head, body, and tail of the duct. These region-specific properties are maintained by distinct gene expression profiles which are governed by transcription factor networks, non-coding RNAs, and other factors.Materials and methodsWe used genome-wide protocols including DNase-seq, RNA-seq and ChIP-seq to characterize open (active) chromatin, the transcriptome and occupancy of specific transcription factors (TFs) respectively, in caput, corpus, and cauda segments of adult human epididymis tissue and primary human epididymis epithelial (HEE) cell cultures derived from them. RNA-seq following TF depletion or activation, combined with gene ontology analysis also determined TF targets.ResultsAmong regional differentially expressed transcripts were epithelial-selective transcription factors (TFs), microRNAs, and antiviral response genes. Caput-enriched TFs included hepatocyte nuclear factor 1 (HNF1) and the androgen receptor (AR), both of which were also predicted to occupy cis-regulatory elements identified as open chromatin in HEE cells. HNF1 targets were identified genome-wide using ChIP-seq, in HEE cells. Next, siRNA-mediated depletion of HNF1 revealed a pivotal role for this TF in coordinating epithelial water and solute transport in caput epithelium. The importance of AR in HEE cells was shown by AR ChIP-seq, and by RNA-seq after synthetic androgen (R1881) treatment. AR has a distinct transcriptional program in the HEE cells and likely recruits different co-factors (RUNX1 and CEBPβ) in comparison to those used in prostate epithelium.Discussion and conclusionOur data identify many transcription factors that regulate the development and differentiation of HEE cells. Moreover, a comparison between immature and adult HEE cells showed key TFs in the transition to fully differentiated function of this epithelium. These data may help identify new targets to treat male infertility and have the potential to open new avenues for male contraception.

Project description:BackgroundPilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours.MethodsRNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization.ResultsIn this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions.ConclusionsThese results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer.

Dataset Information

Human-specific transcriptional networks in the brain.

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Human-specific transcriptional networks in the brain.

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