Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

Ament, Seth A.; Pearl, Jocelynn; Cantle, Jeffrey P.; Bragg, Robert M.; Skene, Peter J.; Coffey, Sydney R.; Bergey, Dani E; Wheeler, Vanessa C.; MacDonald, Marcy E.; Baliga, Nitin S.; Rosinski, Jim; Hood, Leroy; Carroll, Jeffrey B.; Price, Nathan D.

doi:10.15252/msb.20167435

Cited by 62 publications

(56 citation statements)

References 80 publications

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“…Next, we generated an integrative model for TF-target gene interactions in the brain by combining our model of brain TFBSs with evidence of co-expression between TF-gene pairs, using an approach similar to our previous work on TRNs in the mouse brain (Ament et al, 2018a). Briefly, we considered TFgene pairs where the predicted binding sites for that TF were enriched +/À10 kb from a gene's transcription start site (a window shown to maximize overlap of target gene predictions from DNase footprinting with target gene predictions from chromatin immunoprecipitation sequencing [ChIP-seq]; Plaisier et al, 2016).…”

Section: Reconstruction Of a Transcriptional Regulatory Network Modelmentioning

confidence: 99%

Genome-Scale Transcriptional Regulatory Network Models of Psychiatric and Neurodegenerative Disorders

et al. 2019

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Graphical AbstractHighlights d Network model predicts binding sites and target genes of 741 TFs in the human brain d Target genes of key regulator TFs were dysregulated in brain diseases d POU3F2 regulates a schizophrenia-and bipolar-disorderassociated gene network SUMMARY Transcriptional regulatory changes in the developing and adult brain are prominent features of brain diseases, but the involvement of specific transcription factors (TFs) remains poorly understood. We integrated brain-specific DNase footprinting and TFgene co-expression to reconstruct a transcriptional regulatory network (TRN) model for the human brain. We identified key regulator TFs whose predicted target genes were enriched for differentially expressed genes in the prefrontal cortex of individuals with psychiatric and neurodegenerative diseases. Many of these TFs were further implicated in the same diseases through disruption of their binding sites by disease-associated SNPs and associations of TF loci with disease risk. Using primary human neural stem cells, we validated network predictions that link the TF POU3F2 to schizophrenia and bipolar disorder via both cisand trans-acting mechanisms. Our models of brain-specific TF binding sites and target genes provide a resource for network analysis of brain diseases.

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Section: Reconstruction Of a Transcriptional Regulatory Network Modelmentioning

confidence: 99%

Genome-Scale Transcriptional Regulatory Network Models of Psychiatric and Neurodegenerative Disorders

et al. 2019

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“…Whereas bulk transcriptome-wide studies have provided important insights into molecular changes in HD [1,14,15,23,29,38], bulk samples comprise a mixture of cell types, so astrocyte-specific signatures in HD may be obscured. Single cell RNA sequencing (scRNAseq) is a powerful technique to interrogate cellular heterogeneity [6,42].…”

Section: Introductionmentioning

confidence: 99%

Single-nucleus RNA-seq identifies Huntington disease astrocyte states

Al‐Dalahmah

Sosunov

Shaik

et al. 2020

acta neuropathol commun

189

139

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Huntington Disease (HD) is an inherited movement disorder caused by expanded CAG repeats in the Huntingtin gene. We have used single nucleus RNASeq (snRNASeq) to uncover cellular phenotypes that change in the disease, investigating single cell gene expression in cingulate cortex of patients with HD and comparing the gene expression to that of patients with no neurological disease. In this study, we focused on astrocytes, although we found significant gene expression differences in neurons, oligodendrocytes, and microglia as well. In particular, the gene expression profiles of astrocytes in HD showed multiple signatures, varying in phenotype from cells that had markedly upregulated metallothionein and heat shock genes, but had not completely lost the expression of genes associated with normal protoplasmic astrocytes, to astrocytes that had substantially upregulated glial fibrillary acidic protein (GFAP) and had lost expression of many normal protoplasmic astrocyte genes as well as metallothionein genes. When compared to astrocytes in control samples, astrocyte signatures in HD also showed downregulated expression of a number of genes, including several associated with protoplasmic astrocyte function and lipid synthesis. Thus, HD astrocytes appeared in variable transcriptional phenotypes, and could be divided into several different "states", defined by patterns of gene expression. Ultimately, this study begins to fill the knowledge gap of single cell gene expression in HD and provide a more detailed understanding of the variation in changes in gene expression during astrocyte "reactions" to the disease.

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“…Further, since the signals derived from GWAS are typically in non-coding regions, prioritized regions still need to be refined through the incorporation of functional genomic information into analyses. 16 This is pertinent, since it is well documented that changes in gene expression are a hallmark of HD disease pathology, 17, 18 and HTT is expressed ubiquitously across tissues. 19…”

Section: Introductionmentioning

confidence: 99%

Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease

Wright

Caron

et al. 2019

Preprint

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Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in the HTT gene. In an attempt to identify genomic modifiers that contribute towards the age of onset of HD, we performed a transcriptome wide association study assessing heritable differences in genetically determined expression in diverse tissues, employing genome wide data from over 4,000 patients. This identified genes that showed evidence for colocalization and replication, with downstream functional validation being performed in isogenic HD stem cells and patient brains. Enrichment analyses detected associations with various biologically-relevant gene sets and striatal coexpression modules that are mediated by CAG length. Further, cortical coexpression modules that are relevant for HD onset were also associated with cognitive decline and HD-related traits in a longitudinal cohort. In summary, the combination of population-scale gene expression information with HD patient genomic data identified novel modifier genes for the disorder.

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Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

Cited by 62 publications

References 80 publications

Genome-Scale Transcriptional Regulatory Network Models of Psychiatric and Neurodegenerative Disorders

Genome-Scale Transcriptional Regulatory Network Models of Psychiatric and Neurodegenerative Disorders

Single-nucleus RNA-seq identifies Huntington disease astrocyte states

Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease

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