Genomics Proteomics & BioinformaticsBioinformaticsPeer-reviewed journal article
Morphine Re-arranges Chromatin Spatial Architecture of Primate Cortical Neurons
Liang WangiD, Xiaojie WangiD, Chunqi LiuiD, Wei XuiD, Weihong KuangiD, Qian BuiD, Hongchun LiiD, Ying ZhaoiD, Linhong JiangiD, Yaxing CheniD, Feng QiniD, Shu LiiD, Qinfan WeiiD, Xiaocong LiuiD, Bin LiuiD, Yuanyuan CheniD, Yanping DaiiD, Hongbo WangiD, Jingwei TianiD, Gang CaoiD, Yinglan ZhaoiD, Xiaobo CeniD
Abstract
The expression of linear DNA sequences is precisely regulated by the three-dimensional (3D) architecture of chromatin. Morphine-induced aberrant gene networks of neurons have been extensively investigated; however, how morphine impacts the 3D genomic architecture of neuorns is still unknown. Here, we applied digestion-ligation-only high-throughput chromosome conformation capture (DLO Hi-C) technology to investigate the affection of morphine on 3D chromatin architecture of primate cortical neurons. After receiving continuous morphine administration for 90 days on rhesus monkeys, we discovered that morphine re-arranged chromosome territories, with a total of 391 segmented compartments being switched. Morphine altered over half of the detected topologically associated domains (TADs), most of which exhibited a variety of shifts, followed by separating and fusing types. Analysis of the looping events at kilobase-scale resolution revealed that morphine increased not only the number but also the length of differential loops. Moreover, all identified differentially expressed genes (DEGs) from the RNA sequencing (RNA-seq) were mapped to the specific TAD boundaries or differential loops, and were further validated to be significantly changed. Collectively, an altered 3D genomic architecture of cortical neurons may regulate the gene networks associated-morphine effects. Our finding provides critical hubs connecting chromosome spatial organization and gene networks associated with the morphine effects in humans.
- organism: rat
- organism: non-human primate
- assay: Hi-C
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 2
- FWCI
- 0.18
- Field percentile
- 37th percentile
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