Background:Chromatin-associated RNA(caRNA)acts as a ubiquitous epigenetic layer in eukaryotes,and has been reported to be essential in various biological processes,including gene transcription,chromatin remodeling and...Background:Chromatin-associated RNA(caRNA)acts as a ubiquitous epigenetic layer in eukaryotes,and has been reported to be essential in various biological processes,including gene transcription,chromatin remodeling and cellular differentiation.Recently,numerous experimental techniques have been developed to characterize genome-wide RNA-chromatin interactions to understand their underlying biological functions.However,these experimental methods are generally expensive,time-consuming,and limited in identifying all potential sites,while most of the existing computational methods are restricted to detecting only specific types of RNAs interacting with chromatin.Methods:Here,we propose a highly interpretable computational framework,named DeepRCI,to identify the interactions between various types of RNAs and chromatin.In this framework,we introduce a novel deep learning component called variformer and integrate multi-omics data to capture intrinsic genomic features at both RNA and DNA levels.Results:Extensive experiments demonstrate that DeepRCI can detect RNA-chromatin interactions more accurately when compared to the state-of-the-art baseline prediction methods.Furthermore,the sequence features extracted by DeepRCI can be well matched to known critical gene regulatory components,indicating that our model can provide useful biological insights into understanding the underlying mechanisms of RNA-chromatin interactions.In addition,based on the prediction results,we further delineate the relationships between RNA-chromatin interactions and cellular functions,including gene expression and the modulation of cell states.Conclusions:In summary,DeepRCI can serve as a useful tool for characterizing RNA-chromatin interactions and studying the underlying gene regulatory code.展开更多
目的:探究解旋酶样转录因子(helicase like transcription factor,HLTF)基因在肝细胞癌(hepatocellular carcinoma,HCC)中潜在的调控机制。方法:构建HLTF基因稳定敲除的HCC细胞株。应用RNA测序法(RNA sequencing,RNA-seq)检测并分析肝...目的:探究解旋酶样转录因子(helicase like transcription factor,HLTF)基因在肝细胞癌(hepatocellular carcinoma,HCC)中潜在的调控机制。方法:构建HLTF基因稳定敲除的HCC细胞株。应用RNA测序法(RNA sequencing,RNA-seq)检测并分析肝癌细胞HLTF基因敲除前后的差异表达基因。应用转座酶可及性染色质测序法(assay for transposase-accessible chromatin using sequencing,ATAC-seq)检测HLTF基因敲除前后肝癌细胞染色质可及性的改变。采用RNA-seq和ATAC-seq多组学数据进行联合分析,寻找HLTF基因潜在的下游调控通路和关键基因。结果:癌症基因组图谱(the cancer genome atlas,TCGA)数据库分析表明HLTF基因在HCC组织中的表达水平升高,且其高表达与HCC预后不良有关联;RNA-seq分析结果显示,与野生型肝癌细胞相比,HLTF基因敲除细胞中有563个基因的表达水平上调,656个基因的表达水平下调;ATAC-seq分析结果显示,共27818个区域在HLTF基因缺失时染色质可及性发生显著改变,其中14225个区域染色质可及性增强,13593个区域染色质可及性减弱;对染色质可及性改变的区域进行motif富集分析,数据显示在染色质可及性增强的区域,Atf3、Fra1和BATF等被富集,在染色质可及性减弱的区域,Fra1、Fra2和JunB等被富集;RNA-seq和ATAC-seq多组学数据联合分析表明,重叠基因主要富集在花生四烯酸代谢通路、Wnt信号通路、钙离子信号通路和转化生长因子β(transforming growth factorβ,TGF-β)信号通路等。HLTF基因的缺失使核RNA输出因子3(nuclear RNA export factor 3,NXF3)基因表达水平升高。NXF3基因高表达的HCC患者的预后较NXF3基因低表达的HCC患者好。结论:在HCC中,HLTF基因可能参与调控花生四烯酸代谢通路、Wnt信号通路和TGF-β信号通路等,NXF3基因可能是HLTF基因的潜在下游基因。展开更多
基金supported in part by the National Natural Science Foundation of China(61872216,T2125007 to JZ,31900862 to DZ)the National Key Research and Development Program of China(2018YFC0910404,2021YFF1201300)the Turing AI Institute of Nanjing,the Tsinghua-Toyota Joint Research Fund and the US National Institute of Health grant(1R01NS125018).
文摘Background:Chromatin-associated RNA(caRNA)acts as a ubiquitous epigenetic layer in eukaryotes,and has been reported to be essential in various biological processes,including gene transcription,chromatin remodeling and cellular differentiation.Recently,numerous experimental techniques have been developed to characterize genome-wide RNA-chromatin interactions to understand their underlying biological functions.However,these experimental methods are generally expensive,time-consuming,and limited in identifying all potential sites,while most of the existing computational methods are restricted to detecting only specific types of RNAs interacting with chromatin.Methods:Here,we propose a highly interpretable computational framework,named DeepRCI,to identify the interactions between various types of RNAs and chromatin.In this framework,we introduce a novel deep learning component called variformer and integrate multi-omics data to capture intrinsic genomic features at both RNA and DNA levels.Results:Extensive experiments demonstrate that DeepRCI can detect RNA-chromatin interactions more accurately when compared to the state-of-the-art baseline prediction methods.Furthermore,the sequence features extracted by DeepRCI can be well matched to known critical gene regulatory components,indicating that our model can provide useful biological insights into understanding the underlying mechanisms of RNA-chromatin interactions.In addition,based on the prediction results,we further delineate the relationships between RNA-chromatin interactions and cellular functions,including gene expression and the modulation of cell states.Conclusions:In summary,DeepRCI can serve as a useful tool for characterizing RNA-chromatin interactions and studying the underlying gene regulatory code.
文摘目的:探究解旋酶样转录因子(helicase like transcription factor,HLTF)基因在肝细胞癌(hepatocellular carcinoma,HCC)中潜在的调控机制。方法:构建HLTF基因稳定敲除的HCC细胞株。应用RNA测序法(RNA sequencing,RNA-seq)检测并分析肝癌细胞HLTF基因敲除前后的差异表达基因。应用转座酶可及性染色质测序法(assay for transposase-accessible chromatin using sequencing,ATAC-seq)检测HLTF基因敲除前后肝癌细胞染色质可及性的改变。采用RNA-seq和ATAC-seq多组学数据进行联合分析,寻找HLTF基因潜在的下游调控通路和关键基因。结果:癌症基因组图谱(the cancer genome atlas,TCGA)数据库分析表明HLTF基因在HCC组织中的表达水平升高,且其高表达与HCC预后不良有关联;RNA-seq分析结果显示,与野生型肝癌细胞相比,HLTF基因敲除细胞中有563个基因的表达水平上调,656个基因的表达水平下调;ATAC-seq分析结果显示,共27818个区域在HLTF基因缺失时染色质可及性发生显著改变,其中14225个区域染色质可及性增强,13593个区域染色质可及性减弱;对染色质可及性改变的区域进行motif富集分析,数据显示在染色质可及性增强的区域,Atf3、Fra1和BATF等被富集,在染色质可及性减弱的区域,Fra1、Fra2和JunB等被富集;RNA-seq和ATAC-seq多组学数据联合分析表明,重叠基因主要富集在花生四烯酸代谢通路、Wnt信号通路、钙离子信号通路和转化生长因子β(transforming growth factorβ,TGF-β)信号通路等。HLTF基因的缺失使核RNA输出因子3(nuclear RNA export factor 3,NXF3)基因表达水平升高。NXF3基因高表达的HCC患者的预后较NXF3基因低表达的HCC患者好。结论:在HCC中,HLTF基因可能参与调控花生四烯酸代谢通路、Wnt信号通路和TGF-β信号通路等,NXF3基因可能是HLTF基因的潜在下游基因。
