共查询到20条相似文献,搜索用时 31 毫秒
1.
2.
Xiaoran Ma Cun Liu Chundi Gao Jie Li Jing Zhuang Lijuan Liu Huayao Li Xue Wang Xiaoming Zhang Shixia Dong Chao Zhou Changgang Sun 《Journal of cellular physiology》2020,235(4):3973-3983
Recently, increasing evidences show that circular RNAs (circRNAs) are important regulators of various diseases, especially cancer. However, the regulatory role and the potential mechanism of action of circRNAs in breast cancer remain largely unknown. In this study, weighted gene co-expression network analysis was conducted with the differentially expressed miRNAs and mRNAs in breast cancer from The Cancer Genome Atlas database to identify the key modules associated with the carcinogenesis of breast cancer. In the significant turquoise and brown modules, 22 miRNAs and 1877 mRNAs were identified, respectively. Then, We compared and predicted the target genes and performed survival analysis to identify the miRNAs and mRNAs related to the prognosis of breast cancer. A circRNA-related competitive endogenous RNA network was identified by database co-screening, and deleted in liver cancer 1 (DLC1) was identified as a key gene. Finally, to assess how genes in key modules and key genes contribute to the development of breast cancer, relevant pathway information was obtained through DAVID and Gene Set Enrichment Analysis. These data demonstrated that three circRNAs (hsa-circ-0083373, hsa-circ-0083374, and hsa-circ-0083375) that regulate DLC1 expression via hsa-mir-511 and are involved in the pathogenesis and development of breast cancer. 相似文献
3.
Breast cancer is the most common form of cancer afflicting women worldwide. Patients with breast cancer of different molecular classifications need varied treatments. Since it is known that the development of breast cancer involves multiple genes and functions, identification of functional gene modules (clusters of the functionally related genes) is indispensable as opposed to isolated genes, in order to investigate their relationship derived from the gene co-expression analysis. In total, 6315 differentially expressed genes (DEGs) were recognized and subjected to the co-expression analysis. Seven modules were screened out. The blue and turquoise modules have been selected from the module trait association analysis since the genes in these two modules are significantly correlated with the breast cancer subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment show that the blue module genes engaged in cell cycle, DNA replication, p53 signaling pathway, and pathway in cancer. According to the connectivity analysis and survival analysis, 8 out of 96 hub genes were filtered and have shown the highest expression in basal-like breast cancer. Furthermore, the hub genes were validated by the external datasets and quantitative real-time PCR (qRT-PCR). In summary, hub genes of Cyclin E1 (CCNE1), Centromere Protein N (CENPN), Checkpoint kinase 1 (CHEK1), Polo-like kinase 1 (PLK1), DNA replication and sister chromatid cohesion 1 (DSCC1), Family with sequence similarity 64, member A (FAM64A), Ubiquitin Conjugating Enzyme E2 C (UBE2C) and Ubiquitin Conjugating Enzyme E2 T (UBE2T) may serve as the prognostic markers for different subtypes of breast cancer. 相似文献
4.
In the modern chicken industry, fast-growing broilers have undergone strong artificial selection for muscle growth, which has led to remarkable phenotypic variations compared with slow-growing chickens. However, the molecular mechanism underlying these phenotypes differences remains unknown. In this study, a systematic identification of candidate genes and new pathways related to myofiber development and composition in chicken Soleus muscle (SOL) has been made using gene expression profiles of two distinct breeds: Qingyuan partridge (QY), a slow-growing Chinese breed possessing high meat quality and Cobb 500 (CB), a commercial fast-growing broiler line. Agilent cDNA microarray analyses were conducted to determine gene expression profiles of soleus muscle sampled at sexual maturity age of QY (112 d) and CB (42 d). The 1318 genes with at least 2-fold differences were identified (P?0.05, FDR <0.05, FC?≥?2) in SOL muscles of QY and CB chickens. Differentially expressed genes (DEGs) related to muscle development, energy metabolism or lipid metabolism processes were examined further in each breed based on Gene Ontology (GO) analysis, and 11 genes involved in these processes were selected for further validation studies by qRT-PCR. In addition, based on KEGG pathway analysis of DEGs in both QY and CB chickens, it was found that in addition to pathways affecting myogenic fibre-type development and differentiation (pathways for Hedgehog &; Calcium signaling), energy metabolism (Phosphatidylinositol signaling system, VEGF signaling pathway, Purine metabolism, Pyrimidine metabolism) were also enriched and might form a network with pathways related to muscle metabolism to influence the development of myofibers. This study is the first stage in the understanding of molecular mechanisms underlying variations in poultry meat quality. Large scale analyses are now required to validate the role of the genes identified and ultimately to find molecular markers that can be used for selection or to optimize rearing practices. 相似文献
5.
Co-Expression Analysis of Fetal Weight-Related Genes in Ovine Skeletal Muscle during Mid and Late Fetal Development Stages 总被引:1,自引:0,他引:1
Lingyang Xu Fuping Zhao Hangxing Ren Li Li Jian Lu Jiasen Liu Shifang Zhang George E. Liu Jiuzhou Song Li Zhang Caihong Wei Lixin Du 《International journal of biological sciences》2014,10(9):1039-1050
6.
7.
8.
9.
Tieshan Xu Lihong Gu Kyle Michael Schachtschneider Xiaolin Liu Wei Huang Ming Xie Shuisheng Hou 《PloS one》2014,9(9)
Lean-type Pekin duck is a commercial breed that has been obtained through long-term selection. Investigation of the differentially expressed genes in breast muscle and skin fat at different developmental stages will contribute to a comprehensive understanding of the potential mechanisms underlying the lean-type Pekin duck phenotype. In the present study, RNA-seq was performed on breast muscle and skin fat at 2-, 4- and 6-weeks of age. More than 89% of the annotated duck genes were covered by our RNA-seq dataset. Thousands of differentially expressed genes, including many important genes involved in the regulation of muscle development and fat deposition, were detected through comparison of the expression levels in the muscle and skin fat of the same time point, or the same tissue at different time points. KEGG pathway analysis showed that the differentially expressed genes clustered significantly in many muscle development and fat deposition related pathways such as MAPK signaling pathway, PPAR signaling pathway, Calcium signaling pathway, Fat digestion and absorption, and TGF-beta signaling pathway. The results presented here could provide a basis for further investigation of the mechanisms involved in muscle development and fat deposition in Pekin duck. 相似文献
10.
Bikash Jaiswal Kumar Utkarsh D.K. Bhattacharyya 《Journal of Genetic Engineering and Biotechnology》2018,16(2):447-457
In the domain of gene-gene network analysis, construction of co-expression networks and extraction of network modules have opened up enormous possibilities for exploring the role of genes in biological processes. Through such analysis, one can extract interesting behaviour of genes and would help in the discovery of genes participating in a common biological process. However, such network analysis methods in sequential processing mode often have been found time-consuming even for a moderately sized dataset.It is observed that most existing network construction techniques are capable of handling only positive correlations in gene-expression data whereas biologically-significant genes exhibit both positive and negative correlations. To address these problems, we propose a faster method for construction and analysis of gene-gene network and extraction of modules using a similarity measure which can identify both negatively and positively correlated co-expressed patterns. Our method utilizes General-purpose computing on graphics processing units (GPGPU) to provide fast, efficient and parallel extraction of biologically relevant network modules to support biomarker identification for breast cancer. The modules extracted are validated using p-value and q-value for both metastasis and non-metastasis stages of breast cancer. PNME has been found capable of identifying interesting biomarkers for this critical disease. We identified six genes with the interesting behaviours which have been found to cause breast cancer in homo-sapiens. 相似文献
11.
A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. 相似文献
12.
Xu Y Duanmu H Chang Z Zhang S Li Z Li Z Liu Y Li K Qiu F Li X 《Molecular biology reports》2012,39(2):1627-1637
Copy number variations (CNVs) are one type of the human genetic variations and are pervasive in the human genome. It has been
confirmed that they can play a causal role in complex diseases. Previous studies of CNVs focused more on identifying the disease-specific
CNV regions or candidate genes on these CNV regions, but less on the synergistic actions between genes on CNV regions and
other genes. Our research combined the CNVs with related gene co-expression to reconstruct gene co-expression network by using
single nucleotide polymorphism microarray datasets and gene microarray datasets of breast cancer, and then extracted the modules
which connected densely inside and analyzed the functions of modules. Interestingly, all of these modules’ functions were
related to breast cancer according to our enrichment analysis, and most of the genes in these modules have been reported to
be involved in breast cancer. Our findings suggested that integrating CNVs and gene co-expressed relations was an available
way to analyze the roles of CNV genes and their synergistic genes in breast cancer, and provided a novel insight into the
pathological mechanism of breast cancer. 相似文献
13.
14.
15.
Mohammed Mamdani Vernell Williamson Gowon O. McMichael Tana Blevins Fazil Aliev Amy Adkins Laura Hack Tim Bigdeli Andrew D. van der Vaart Bradley Todd Web Silviu-Alin Bacanu Gursharan Kalsi COGA Consortium Kenneth S. Kendler Michael F. Miles Danielle Dick Brien P. Riley Catherine Dumur Vladimir I. Vladimirov 《PloS one》2015,10(9)
16.
17.
Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis 下载免费PDF全文
Sheng‐Min Guo Jian‐Xiong Wang Jin Li Fang‐Yuan Xu Quan Wei Hai‐Ming Wang Hou‐Qiang Huang Si‐Lin Zheng Yu‐Jie Xie Chi Zhang 《Journal of cellular biochemistry》2018,119(9):7687-7695
Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA‐associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease‐related networks based on 21756 gene expression correlation coefficients, hub‐genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits‐related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA‐associated genes. Moreover, 310 OA‐associated genes were found, and 34 of them were among hub‐genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)‐receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'‐kinase (PI3K)‐Akt signaling pathway (PI3K‐AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA. 相似文献
18.
19.
为鉴定鸡下丘脑发育相关特异性表达miRNA,基于固始鸡1日龄和36周龄下丘脑小RNA的Solexa测序数据,共鉴定到266种2个发育阶段共表达的miRNA,其中157种miRNA的表达水平被显著下调,22种被显著上调.聚类分析显示,鸡下丘脑高丰度差异性miRNA主要集中于let-7、mir-181、mir-30、mir-99、mir-1和mir-17等基因家族.另外,预测了10种高丰度差异性miRNA的靶基因,并进行了相应的GO分析和KEGG通路分析.结果显示,预测靶基因在发育过程、代谢过程、细胞过程和生物学过程调节等4个生物学过程以及细胞周期、粘着斑、TGF-beta信号通路和MAPK信号通路等通路中显著富集.研究结果为进一步揭示miRNA调控鸡下丘脑发育的分子机制提供了有益线索. 相似文献
20.
Kristina Buac Mai Xu Julie Cronin Ashani T. Weeraratna Stephen M. Hewitt William J. Pavan 《Pigment cell & melanoma research》2009,22(6):773-784
Neuregulin (NRG) signaling through the receptor tyrosine kinase, ERBB3, is required for embryonic development, and dysregulated signaling has been associated with cancer progression. Here, we show that NRG1/ERBB3 signaling inhibits melanocyte (MC) maturation and promotes undifferentiated, migratory and proliferative cellular characteristics. Embryonic analyses demonstrated that initial MC specification and distribution were not dependent on ERBB3 signaling. However NRG1/ERBB3 signaling was both necessary and sufficient to inhibit differentiation of later stages of MC development in culture. Analysis of tissue arrays of human melanoma samples suggests that ERBB3 signaling may also contribute to metastatic progression of melanoma as ERBB3 was phosphorylated in primary tumors compared with nevi or metastatic lesions. Neuregulin 1‐treated MCs demonstrated increased proliferation and invasion and altered morphology concomitant with decreased levels of differentiation genes, increased levels of proliferation genes and altered levels of melanoma progression and metastases genes. ERBB3 activation in primary melanomas suggests that NRG1/ERBB3 signaling may contribute to the progression of melanoma from benign nevi to malignancies. We propose that targeting ERBB3 activation and downstream genes identified in this study may provide novel therapeutic interventions for malignant melanoma. 相似文献