BMC Genomics,
Jianbo Yao, Lei Wang, Hairong Wei, Mark A Hostuttler, Gregory M Weber, Hao Ma
英文
BMC Genomics,2020年
Kai Xu, Xiaosong Ma, Hongyan Liu, Hui Xia, Liang Chen, Lijun Luo, Lei Wang
LicenseType:CC BY |
BMC Genomics,2017年
Lei Wang, Yin Zhang, Linlin Xing, Chunyu Wang, Xiaoyan Liu, Maozu Guo
LicenseType:Unknown |
BMC Genomics,2021年
Lei Wang, Xiaoyan Cai, Cuili Pan, Yun Ma, Zhaoxiong Lei, Shuzhe Wang, Zhuoma Luoreng, Xingping Wang, Dawei Wei
LicenseType:Unknown |
BMC Genomics,2016年
Weixing Feng, Jin Li, Wang Cong, Yulin Deng, Lei Wang, Chengzhen Xu, Hong Liang, Yunlong Liu, Ying Wang, Yue Wang, Todd C. Skaar, Xuefeng Dai
LicenseType:CC BY |
BackgroundIn combination with gene expression profiles, the protein interaction network (PIN) constructs a dynamic network that includes multiple functional modules. Previous studies have demonstrated that rifampin can influence drug metabolism by regulating drug-metabolizing enzymes, transporters, and microRNAs (miRNAs). Rifampin induces gene expression, at least in part, by activating the pregnane X receptor (PXR), which induces gene expression; however, the impact of rifampin on global gene regulation has not been examined under the molecular network frameworks.MethodsIn this study, we extracted rifampin-induced significant differentially expressed genes (SDG) based on the gene expression profile. By integrating the SDG and human protein interaction network (HPIN), we constructed the rifampin-regulated protein interaction network (RrPIN). Based on gene expression measurements, we extracted a subnetwork that showed enriched changes in molecular activity. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG), we identified the crucial rifampin-regulated biological pathways and associated genes. In addition, genes targeted by miRNAs that were significantly differentially expressed in the miRNA expression profile were extracted based on the miRNA-gene prediction tools. The miRNA-regulated PIN was further constructed using associated genes and miRNAs. For each miRNA, we further evaluated the potential impact by the gene interaction network using pathway analysis.Results and DisccussionWe extracted the functional modules, which included 84 genes and 89 interactions, from the RrPIN, and identified 19 key rifampin-response genes that are associated with seven function pathways that include drug response and metabolism, and cancer pathways; many of the pathways were supported by previous studies. In addition, we identified that a set of 6 genes (CAV1, CREBBP, SMAD3, TRAF2, KBKG, and THBS1) functioning as gene hubs in the subnetworks that are regulated by rifampin. It is also suggested that 12 differentially expressed miRNAs were associated with 6 biological pathways.ConclusionsOur results suggest that rifampin contributes to changes in the expression of genes by regulating key molecules in the protein interaction networks. This study offers valuable insights into rifampin-induced biological mechanisms at the level of miRNAs, genes and proteins.
BMC Genomics,2016年
Lei Wang, Yuan Fang, Xiu-e Wang, Yufeng Wu, Ximeng Wang, Xiucai Pan, Jin Xiao, Wenli Zhang, Qi You, Zhen Su
LicenseType:CC BY |
BackgroundBidirectional gene pairs are highly abundant and mostly co-regulated in eukaryotic genomes. The structural features of bidirectional promoters (BDPs) have been well studied in yeast, humans and plants. However, the underlying mechanisms responsible for the coexpression of BDPs remain understudied, especially in plants.ResultsHere, we characterized chromatin features associated with rice BDPs. Several unique chromatin features were present in rice BDPs but were missing from unidirectional promoters (UDPs), including overrepresented active histone marks, canonical nucleosomes and underrepresented H3K27me3. In particular, overrepresented active marks (H3K4ac, H4K12ac, H4K16ac, H3K4me2 and H3K36me3) were truly overrepresented in type I BDPs but not in the other two BDPs, based on a Kolmogorov-Smirnov test.ConclusionsOur analyses indicate that active marks (H3K4ac, H4K12ac, H4K16ac, H3K4me3, H3K9ac and H3K27ac) may coordinate with repressive marks (H3K27me3 and H3K9me1/3) to build a unique chromatin structure that favors the coregulation of bidirectional gene pairs. Thus, our findings help to enhance the understanding of unique epigenetic mechanisms that regulate bidirectional gene pairs and may improve the manipulation of gene pairs for crop bioengineering.