Enhanced construction of gene regulatory networks using hub gene information

Yu, Donghyeon,Lim, Johan,Wang, Xinlei,Liang, Faming,Xiao, Guanghua BioMed Central 2017 BMC bioinformatics Vol.18 No.1

<P><B>Background</B></P><P>Gene regulatory networks reveal how genes work together to carry out their biological functions. Reconstructions of gene networks from gene expression data greatly facilitate our understanding of underlying biological mechanisms and provide new opportunities for biomarker and drug discoveries. In gene networks, a gene that has many interactions with other genes is called a hub gene, which usually plays an essential role in gene regulation and biological processes. In this study, we developed a method for reconstructing gene networks using a partial correlation-based approach that incorporates prior information about hub genes. Through simulation studies and two real-data examples, we compare the performance in estimating the network structures between the existing methods and the proposed method.</P><P><B>Results</B></P><P>In simulation studies, we show that the proposed strategy reduces errors in estimating network structures compared to the existing methods. When applied to <I>Escherichia coli</I>, the regulation network constructed by our proposed ESPACE method is more consistent with current biological knowledge than the SPACE method. Furthermore, application of the proposed method in lung cancer has identified hub genes whose mRNA expression predicts cancer progress and patient response to treatment.</P><P><B>Conclusions</B></P><P>We have demonstrated that incorporating hub gene information in estimating network structures can improve the performance of the existing methods.</P>

Using weighted gene co-expression network analysis (WGCNA) to identify the hub genes related to hypoxic adaptation in yak (Bos grunniens)

Bao Qi,Zhang Xiaolan,Bao Pengjia,Liang Chunnian,Guo Xian,Chu Min,Yan Ping 한국유전학회 2021 Genes & Genomics Vol.43 No.10

Background As a mammal living at the highest altitude in the world, the yak has strong adaptability to the harsh natural environment (such as low temperature, scarce food, especially low oxygen) of Qinghai-Tibet Plateau (QTP) after a long process of natural selection. Objective Here, we used Weighted Correlation Network Analysis (WGCNA), a systematic biology method, to identify hypoxic adaptation-related modules and hub genes. The research of the adaptability of yak against hypoxia is of great signifcance to identify the genetic characteristics and yak breeding. Methods Based on the transcriptome sequencing data (PRJNA362606), the R package DESeq2 and WGCNA were conducted to analyze diferentially expressed genes (DEGs) and construct the gene co-expression network. The module hub genes were identifed and characterized by the correlation of gene and trait, module membership (kME). In addition, GO and KEGG enrichment analyses were used to explore the functions of hub genes. Results Our results revealed that 1098, 1429, and 1645 DEGs were identifed in muscle, spleen, and lung, respectively. Besides, a total of 13 gene co-expression modules were detected, of which two hypoxic adaptation-related modules (saddlebrown and turquoise) were found. We identifed 39 and 150 hub genes in these two modules. Functional enrichment analyses showed that 12 GO terms and 18 KEGG pathways were enriched in the saddlebrown module while 85 GO terms and 22 KEGG pathways were enriched in the turquoise module. The signifcant pathways related to hypoxia adaptation include FoxO signaling pathway, Thermogenesis pathway, and Retrograde endocannabinoid signaling pathway, etc. Conclusions In this study, we obtained two hypoxia-related specifc modules and identifed hub genes based on the connectivity by constructing a weighted gene co-expression network. Function enrichment analysis of two modules revealed mitochondrion is the most important organelle for hypoxia adaptation. Moreover, the insulin-related pathways and thermogenic-related pathways played a major role. The results of this study provide theoretical guidance for further understanding the molecular mechanism of yak adaptation to hypoxia.

Identification of key genes and functional enrichment analysis of liver fibrosis in nonalcoholic fatty liver disease through weighted gene co-expression network analysis

Yue Hu,Jun Zhou Korea Genome Organization 2023 Genomics & informatics Vol.21 No.4

Nonalcoholic fatty liver disease (NAFLD) is a common type of chronic liver disease, with severity levels ranging from nonalcoholic fatty liver to nonalcoholic steatohepatitis (NASH). The extent of liver fibrosis indicates the severity of NASH and the risk of liver cancer. However, the mechanism underlying NASH development, which is important for early screening and intervention, remains unclear. Weighted gene co-expression network analysis (WGCNA) is a useful method for identifying hub genes and screening specific targets for diseases. In this study, we utilized an mRNA dataset of the liver tissues of patients with NASH and conducted WGCNA for various stages of liver fibrosis. Subsequently, we employed two additional mRNA datasets for validation purposes. Gene set enrichment analysis (GSEA) was conducted to analyze gene function enrichment. Through WGCNA and subsequent analyses, complemented by validation using two additional datasets, we identified five genes (BICC1, C7, EFEMP1, LUM, and STMN2) as hub genes. GSEA analysis indicated that gene sets associated with liver metabolism and cholesterol homeostasis were uniformly downregulated. BICC1, C7, EFEMP1, LUM, and STMN2 were identified as hub genes of NASH, and were all related to liver metabolism, NAFLD, NASH, and related diseases. These hub genes might serve as potential targets for the early screening and treatment of NASH.

Exploring molecular mechanisms underlying the pathophysiological association between knee osteoarthritis and sarcopenia

Jiyong Yang,Tao Jiang,Guangming Xu,Shuai Wang,Wengang Liu 대한골다공증학회 2023 Osteoporosis and Sarcopenia Vol.9 No.3

Objectives: Accumulating evidence indicates a strong link between knee osteoarthritis (KOA) and sarcopenia. However, the mechanisms involved have not yet been elucidated. This study primarily aims to explore the molecular mechanisms that explain the connection between these 2 disorders. Methods: The gene expression profiles for KOA and sarcopenia were obtained from the Gene Expression Omnibus database, specifically from GSE55235, GSE169077, and GSE1408. Various bioinformatics techniques were employed to identify and analyze common differentially expressed genes (DEGs) across the 3 datasets. The techniques involved the analysis of Gene Ontology and pathways to enhance understanding, examining proteinprotein interaction (PPI) networks, and identifying hub genes. In addition, we constructed the network of interactions between transcription factors (TFs) and genes, the co-regulatory network of TFs and miRNAs for hub genes, and predicted potential drugs. Results: In total, 14 common DEGs were found between KOA and sarcopenia. Detailed information on biological processes and signaling pathways of common DEGs was obtained through enrichment analysis. After performing PPI network analysis, we discovered 4 hub genes (FOXO3, BCL6, CDKN1A, and CEBPB). Subsequently, we developed coregulatory networks for these hub genes involving TF-gene and TF-miRNA interactions. Finally, we identified 10 potential chemical compounds. Conclusions: By conducting bioinformatics analysis, our study has successfully identified common gene interaction networks between KOA and sarcopenia. The potential of these findings to offer revolutionary understanding into the common development of these 2 conditions could lead to the identification of valuable targets for therapy. 1. Introduction Knee osteoarthritis (KOA) is a prevalent degenerative condition of the musculoskeletal system that predominantly impacts individuals in the middle-aged and older age groups. This progressive ailment gradually impairs the patient’s mobility and overall well-being [1,2]. The primary pathological feature of knee osteoarthritis (KOA) involves the breakdown and loss of articular cartilage. Different joint tissues are impacted to different extents, including remodeling of the subchondral bone, degeneration of the meniscus, weakening and looseness of ligaments, inflammation of the infrapatellar fat pad, and inflammation of the synovial membrane [2–5]. Furthermore, the presence of periarticular muscle atrophy plays a significant role in the progression of KOA. Decreased muscle strength can alter mechanical stress, reduce joint stability, and accelerate cartilage degeneration and abnormal subchondral bone changes [6–9]. Sarcopenia, which frequently coexists with KOA [10–12], is primarily characterized by the decline in both muscle mass and strengt

Photobiomodulation Facilitates Rat Cutaneous Wound Healing by Promoting Epidermal Stem Cells and Hair Follicle Stem Cells Proliferation

Wang Tong,Song Yajuan,Yang Liu,Liu Wei,He Zhen’an,Shi Yi,Song Baoqiang,Yu Zhou 한국조직공학과 재생의학회 2024 조직공학과 재생의학 Vol.21 No.1

Background: Cutaneous wound healing represents a common fundamental phenomenon requiring the participation of cells of distinct types and a major concern for the public. Evidence has confirmed that photobiomodulation (PBM) using near-infrared (NIR) can promote wound healing, but the cells involved and the precise molecular mechanisms remain elusive. Methods: Full-thickness skin defects with a diameter of 1.0 cm were made on the back of rats and randomly divided into the control group, 10 J, 15 J, and 30 J groups. The wound healing rate at days 4, 8, and 12 postoperatively was measured. HE and Masson staining was conducted to reveal the histological characteristics. Immunofluorescence staining was performed to label the epidermal stem cells (ESCs) and hair follicle stem cells (HFSCs). Western blot was performed to detect the expressions of proteins associated with ESCs and HFSCs. Cutaneous wound tissues were collected for RNA sequencing. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes analysis was performed, and the hub genes were identified using CytoHubba and validated by qRT-PCR. Results: PBM can promote reepithelialization, extracellular matrix deposition, and wound healing, increase the number of KRT14+/PCNA+ ESCs and KRT15+/PCNA+ HFSCs, and upregulate the protein expression of P63, Krt14, and PCNA. Three hundred and sixty-six differentially expressed genes (DEGs) and 7 hub genes including Sox9, Krt5, Epcam, Cdh1, Cdh3, Dsp, and Pkp3 were identified. These DEGs are enriched in skin development, cell junction, and cadherin binding involved in cell–cell adhesion etc., while these hub genes are related to skin derived stem cells and cell adhesion. Conclusion: PBM accelerates wound healing by enhancing reepithelialization through promoting ESCs and HFSCs proliferation and elevating the expression of genes associated with stem cells and cell adhesion. This may provide a valuable alternative strategy to promote wound healing and reepithelialization by modulating the proliferation of skin derived stem cells and regulating genes related to cell adhesion. Background: Cutaneous wound healing represents a common fundamental phenomenon requiring the participation of cells of distinct types and a major concern for the public. Evidence has confirmed that photobiomodulation (PBM) using near-infrared (NIR) can promote wound healing, but the cells involved and the precise molecular mechanisms remain elusive. Methods: Full-thickness skin defects with a diameter of 1.0 cm were made on the back of rats and randomly divided into the control group, 10 J, 15 J, and 30 J groups. The wound healing rate at days 4, 8, and 12 postoperatively was measured. HE and Masson staining was conducted to reveal the histological characteristics. Immunofluorescence staining was performed to label the epidermal stem cells (ESCs) and hair follicle stem cells (HFSCs). Western blot was performed to detect the expressions of proteins associated with ESCs and HFSCs. Cutaneous wound tissues were collected for RNA sequencing. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes analysis was performed, and the hub genes were identified using CytoHubba and validated by qRT-PCR. Results: PBM can promote reepithelialization, extracellular matrix deposition, and wound healing, increase the number of KRT14+/PCNA+ ESCs and KRT15+/PCNA+ HFSCs, and upregulate the protein expression of P63, Krt14, and PCNA. Three hundred and sixty-six differentially expressed genes (DEGs) and 7 hub genes including Sox9, Krt5, Epcam, Cdh1, Cdh3, Dsp, and Pkp3 were identified. These DEGs are enriched in skin development, cell junction, and cadherin binding involved in cell–cell adhesion etc., while these hub genes are related to skin derived stem cells and cell adhesion. Conclusion: PBM accelerates wound healing by enhancing reepithelialization through promoting ESCs and HFSCs proliferation and elevating the expression of genes associated with stem cells and cell adhesion. This may provide a valuable alternative strategy to promote wound healing and reepithelialization by modulating the proliferation of skin derived stem cells and regulating genes related to cell adhesion.

A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma

Mahfuz, A.M.U.B.,Zubair-Bin-Mahfuj, A.M.,Podder, Dibya Joti Korea Genome Organization 2021 Genomics & informatics Vol.19 No.2

Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.

Identification of Specific Gene Modules in Mouse Lung Tissue Exposed to Cigarette Smoke

Xing, Yong-Hua,Zhang, Jun-Ling,Lu, Lu,Li, De-Guan,Wang, Yue-Ying,Huang, Song,Li, Cheng-Cheng,Zhang, Zhu-Bo,Li, Jian-Guo,Xu, Guo-Shun,Meng, Ai-Min Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.10

Background: Exposure to cigarette may affect human health and increase risk of a wide range of diseases including pulmonary diseases, such as chronic obstructive pulmonary disease (COPD), asthma, lung fibrosis and lung cancer. However, the molecular mechanisms of pathogenesis induced by cigarettes still remain obscure even with extensive studies. With systemic view, we attempted to identify the specific gene modules that might relate to injury caused by cigarette smoke and identify hub genes for potential therapeutic targets or biomarkers from specific gene modules. Materials and Methods: The dataset GSE18344 was downloaded from the Gene Expression Omnibus (GEO) and divided into mouse cigarette smoke exposure and control groups. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to construct a gene co-expression network for each group and detected specific gene modules of cigarette smoke exposure by comparison. Results: A total of ten specific gene modules were identified only in the cigarette smoke exposure group but not in the control group. Seven hub genes were identified as well, including Fip1l1, Anp32a, Acsl4, Evl, Sdc1, Arap3 and Cd52. Conclusions: Specific gene modules may provide better understanding of molecular mechanisms, and hub genes are potential candidates of therapeutic targets that may possible improve development of novel treatment approaches.

Identification of hub genes and their SNP analysis in West Nile virus infection for designing therapeutic methodologies using RNA-Seq data

Iftikhar Aslam Tayubi,Ahmad Firoz,Omar M. Barukab,Adeel Malik 한국유전학회 2015 Genes & Genomics Vol.37 No.8

The West Nile virus (WNV) infections are generally asymptomatic and are considered as immediate concerns of biodefense due to the lack of any therapeutic remedies. In this work, we created an interaction network of 1159 differentially expressed genes to detect potential hub genes from WNV infected primary human macrophages. We go on to explore the genetic variations that can alter the expression and function of identified hub genes (HCLS1, SLC15A3, HCK, and LY96) using the PROVEAN Protein Batch tool and PolyPhen-2. Community analysis of the network revealed that these clusters were enriched in GO terms such as inflammatory response and regulation of proliferation. Analysis of hub genes can aid in determining their degree of conservation and may help us in understanding their functional roles in biological systems. The nsSNPs proposed in this work may be further targeted through experimental methods for improving treatment towards the infection of WNV.

Prediction of hub genes of Alzheimer's disease using a protein interaction network and functional enrichment analysis

Wee, Jia Jin,Kumar, Suresh Korea Genome Organization 2020 Genomics & informatics Vol.18 No.4

Alzheimer's disease (AD) is a chronic, progressive brain disorder that slowly destroys affected individuals' memory and reasoning faculties, and consequently, their ability to perform the simplest tasks. This study investigated the hub genes of AD. Proteins interact with other proteins and non-protein molecules, and these interactions play an important role in understanding protein function. Computational methods are useful for understanding biological problems, in particular, network analyses of protein-protein interactions. Through a protein network analysis, we identified the following top 10 hub genes associated with AD: PTGER3, C3AR1, NPY, ADCY2, CXCL12, CCR5, MTNR1A, CNR2, GRM2, and CXCL8. Through gene enrichment, it was identified that most gene functions could be classified as integral to the plasma membrane, G-protein coupled receptor activity, and cell communication under gene ontology, as well as involvement in signal transduction pathways. Based on the convergent functional genomics ranking, the prioritized genes were NPY, CXCL12, CCR5, and CNR2.

한우 태아기 6, 9개월령 등심 조직의 전사체 분석을 통한 근생성 및 지방생성 관여 유전자 발굴

정태준(Taejoon Jeong),정기용(Ki-Yong Chung),박원철(Woncheol Park),손주환(Ju-Hwan Son),박종은(Jong-Eun Park),채한화(Han-Ha Chai),권응기(Eung-Gi Kwon),안준상(Jun-Sang Ahn),이지웅(Jiwoong Lee),임다정(Dajeong Lim),Mi-Rim Park 한국생명과학회 2020 생명과학회지 Vol.30 No.1

동물의 근섬유는 배아기와 태아기를 거치며 형성하게 되며 출생 후에는 상처 치유를 위한 것 외에 근섬유 수를 늘리는 순수한 근섬유 형성은 없으며, 이미 존재하고 있는 근섬유의 비대로 근육의 성장이 이뤄진다. 따라서 태아기의 근육의 성장과 발달이 성체의 근육량 및 조성에 미치는 영향이 매우 크며 이 시기에 발현되는 유전자 및 기능을 구명하는 것은 최종적으로 육질, 육량에 개선시키기 위한기초 자료로 활용될 수 있을 것이다. 하지만 한우에서의 연구는 전무한 실정이다. 본 연구는한우 태아기 성장 단계별 근육의 성장과 발달에 관여하는 유전자를 찾기 위한 전사체 분석을 수행하였다. 한우 태아기 6, 9개월령 등심 조직 시료에서 생산한 전사체 자료를 대상으로 DESeq2와 edgeR을 활용하여 성장단계별 유전자의 발현량을 분석하여 차등발현유전자군을 추출했으며, 2개 소프트웨어서 공통적으로 추출된 유전자군(6개월령 특이 발현 유전자 913개, 9개월령 특이 발현 유전자 233개)을 차등발현유전자로 구명 하였다. 차등발현유전자군으로 분류하였다. 차등발현유전자군을 활용하여공발현 유전자 네트워크 분석을 구성하였으며, 유사한 발현 양상을 보이는 유전자들을 그룹화하여 6개월령 특이 발현 유전자군 5개, 9개월령 특이 발현 유전자군 2개의 모듈로 분류했다. 각 모듈은 Gene Ontology (GO) 및 KEGG pathway 분석으로 유의한 기능을 확인하였다. 그 결과, 한우 태아기 6, 9개월령 특이 발현 유전자 네트워크 중, 근육과 지방생성 대사회로와 관련된 2개의 모듈에 대해 네트워크 내에 허브 유전자를 선정할 수 있었다. STRING을 활용하여 단백질 상호작용 네트워크를 구성하고, MCC (maximal clique centrality) 점수를 활용하여 상위 10%의 유전자들을 공발현 분석의 모듈내 허브 유전자로 선정하였다. 그 결과 6개월령 특이 발현 유전자군의 모듈에서는 axin1(AXIN1) 유전자, 9개월령 특이 발현 유전자군 모듈에서는 succinate-CoA ligase ADP-forming beta subunit (SUCLA2) 유전자가 허브 유전자로 확인되었다. AXIN1 유전자는 선행 연구를 통해 6개월령에서 9개월령으로 넘어가면서 근섬유 수의 증식이 억제되고 지방생성이 활발히 이뤄지는 것에 핵심적인 역할을 하는 것으로 추정할 수 있었다. 또한, 시트르산 회로의 중요 요소인 SUCLA2 유전자는 소의 태아기 지방 조직 성장단계에 따라 유전자의 발현이 증가된다는 보고에 따라, 지방 대사와 관련된 유전자임을 알 수 있었다. 추후 한우 태아기 6, 9개월령에 특이적으로 발현된 유전자들을 대상으로 근육 및 지방 형성 관련 기능을 검증하는 후속 연구가 필요할 것이다. The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules’ functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules’(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.