Biology subjects

Pearl, J. R.

Publications and source records attributed to Pearl, J. R..

3 recordsLinked to original sources

bioRxiv2020

Altered Huntingtin-Chromatin Interactions Predict Transcriptional and Epigenetic Changes in Huntingtons Disease

Progressive striatal gene expression changes and epigenetic alterations are a prominent feature of Huntingtons disease (HD), but the mechanistic basis remains poorly understood. Using chromatin immunoprecipitation and sequencing (ChIP-seq), we show that the huntingtin protein (HTT) reproducibly occupies specific locations in the mouse genome. Moreover, many genomic loci were differentially occupied by HTT in striatal tissue from a homozygous knock-in mouse model of HD (B6.HttQ111/Q111) when compared to wildtype controls. Huntingtin ChIP-seq peaks were enriched in the coding regions of cell identity genes important for striatal function, with many of these genes found to have reduced expression in the striata of HD patients and mouse models, as well as reduced HTT occupancy in HttQ111/Q111mice compared to controls. Conversely, HTT ChIP-seq peaks were depleted near genes that are up-regulated in HD. ChIP-seq of bulk striatal histone modifications, generated in parallel, revealed genotype-specific colocalization of HTT with active chromatin marks (H3K4me3 and H3K27ac), and with enhancer of zeste homolog 2 (EZH2), a key enzymatic component of the PRC2 complex. Near genes that are differentially regulated in HD, greater HTT occupancy in HttQ111/Q111 vs. wildtype mice was associated with increased EZH2 binding, increased histone H3 lysine 4 (H3K4me3), and decreased histone H3 lysine 27 (H3K27me3). Our study suggests that huntingtin-chromatin interactions may play a direct role in organizing chromatin and promoting cell type-specific gene expression, with loss of HTT occupancy predicting decreased gene expression in HD.

neuroscience↗

bioRxiv2017

Genome-scale transcriptional regulatory network models of psychiatric and neurodegenerative disorders

Genetic and genomic studies suggest an important role for transcriptional regulatory changes in brain diseases, but roles for specific transcription factors (TFs) remain poorly understood. We integrated human brain-specific DNase I footprinting and TF-gene co-expression to reconstruct a transcriptional regulatory network (TRN) model for the human brain, predicting the brain-specific binding sites and target genes for 741 TFs. We used this model to predict core TFs involved in psychiatric and neurodegenerative diseases. Our results suggest that disease-related transcriptomic and genetic changes converge on small sets of disease-specific regulators, with distinct networks underlying neurodegenerative vs. psychiatric diseases. Core TFs were frequently implicated in a disease through multiple mechanisms, including differential expression of their target genes, disruption of their binding sites by disease-associated SNPs, and associations of the genetic loci encoding these TFs with disease risk. We validated our models predictions through systematic comparison to publicly available ChIP-seq and TF perturbation studies and through experimental studies in primary human neural stem cells. Combined genetic and transcriptional evidence supports roles for neuronal and microglia-enriched, MEF2C-regulated networks in Alzheimers disease; an oligodendrocyte-enriched, SREBF1-regulated network in schizophrenia; and a neural stem cell and astrocyte-enriched, POU3F2-regulated network in bipolar disorder. We provide our models of brain-specific TF binding sites and target genes as a resource for network analysis of brain diseases.

genetics↗

bioRxiv2016

Genome-scale transcriptional regulatory network models for the mouse and human striatum predict roles for SMAD3 and other transcription factors in Huntington’s disease

Transcriptional changes occur presymptomatically and throughout Huntingtons Disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD. We reconstructed a genome-scale model for the target genes of 718 TFs in the mouse striatum by integrating a model of the genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF-target gene modules associated with age- and Htt allele-dependent gene expression changes in the mouse striatum, and replicated many of these associations in independent transcriptomic and proteomic datasets. Strikingly, many of these predicted target genes were also differentially expressed in striatal tissue from human disease. We experimentally validated a key model prediction that SMAD3 regulates HD-related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP-seq) of mouse striatum. We found Htt allele-dependent changes in the genomic occupancy of SMAD3 and confirmed our models prediction that many SMAD3 target genes are down-regulated early in HD. Importantly, our study provides a mouse and human striatal-specific TRN and prioritizes a hierarchy of transcription factor drivers in HD.

systems biology↗