Complex patterns of dopamine‐related gene expression in the ventral tegmental area of male zebra finches relate to dyadic interactions with long‐term female partners

Dopaminergic projections from the ventral tegmental area (VTA) to multiple efferent targets are implicated in pair bonding, yet the role of the VTA in the maintenance of long‐term pair bonds is not well characterized. Complex interactions between numerous neuromodulators modify activity in the VTA, suggesting that individual differences in patterns of gene expression in this region may explain individual differences in long‐term social interactions in bonded pairs. To test this hypothesis we used RNA‐seq to measure expression of over 8000 annotated genes in male zebra finches in established male‐female pairs. Weighted gene co‐expression network analysis identified a gene module that contained numerous dopamine‐related genes with TH found to be the most connected gene of the module. Genes in this module related to male agonistic behaviors as well as bonding‐related behaviors produced by female partners. Unsupervised learning approaches identified two groups of males that differed with respect to expression of numerous genes. Enrichment analyses showed that many dopamine‐related genes and modulators differed between these groups, including dopamine receptors, synthetic and degradative enzymes, the avian dopamine transporter and several GABA‐ and glutamate‐related genes. Many of the bonding‐related behaviors closely associated with VTA gene expression in the two male groups were produced by the male's partner, rather than the male himself. Collectively, results highlight numerous candidate genes in the VTA that can be explored in future studies and raise the possibility that the molecular/genetic organization of the VTA may be strongly shaped by a social partner and/or the strength of the pair bond.     

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co‐expression network analysis

The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan‐cancer validation and time‐dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed. Eight genes were eventually screened out as progression‐related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E‐MTAB‐4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time‐dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan‐cancer patients. Our outcome model was the first prognosis model for human bladder cancer progression prediction via integrative bioinformatics analysis, which may aid in clinical decision‐making.     

Identification of key genes and novel immune infiltration-associated biomarkers of sepsis

Sepsis is the major cause of mortality in the intensive care unit. The aim of this study was to identify the key prognostic biomarkers of abnormal expression and immune infiltration in sepsis. In this study, a total of 36 differentially expressed genes were identified to be mainly involved in a number of immune-related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The hub genes (MMP9 and C3AR1) were significantly related to the prognosis of sepsis patients. The immune infiltration analysis indicated a significant difference in the relative cell content of naive B cells, follicular Th cells, activated NK cells, eosinophils, neutrophils and monocytes between sepsis and normal controls. Weighted gene co-expression network analysis and a de-convolution algorithm that quantifies the cellular composition of immune cells were used to analyse the sepsis expression data from the Gene Expression Omnibus database and to identify modules related to differential immune cells. CEBPB is the key immune-related gene that may be involved in sepsis. Gene set enrichment analysis revealed that CEBPB is involved in the processes of T cell selection, B cell–mediated immunity, NK cell activation and pathways of T cells, B cells and NK cells. Therefore, CEBPB may play a key role in the biological and immunological processes of sepsis.     

Identification of EPHX2 and RMI2 as two novel key genes in cervical squamous cell carcinoma by an integrated bioinformatic analysis

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein–protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC-related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC-associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC-associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC-associated genes for their potentiality in diagnosis, prognosis, and targeted therapy.     

埃及伊蚊不同组织的基因共表达模式分析

【目的】利用权重基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)探索埃及伊蚊Aedes aegypti不同组织基因共表达模式。【方法】从NCBI SRA数据库中选择埃及伊蚊不同组织的转录组数据中具代表性的9种组织(雌雄成蚊的触角和脑,雌蚊的喙、下颚须和卵巢,雄成蚊的前足、中足、后足和腹部末端)的双端测序数据;经过缺失值移除以及方差计算后,筛选出方差最大的5 000个基因,利用R软件中WGCNA包建立埃及伊蚊成蚊不同组织的基因共表达网络并划分模块;然后利用clusterProfiler包对组织特异性模块内的基因进行GO(Gene Ontology)和KEGG(Kyoto Encyclopediaof Genes and Genomes)富集分析,并用Cytoscape软件中的CytoHubba插件筛选共表达模块内的hub基因。【结果】从埃及伊蚊成蚊不同组织中共鉴定出11个基因共表达模块,在雌蚊触角、喙、卵巢、下颚须以及雄蚊脑、腹部末端组织中各鉴定出1个特异性表达模块,雄蚊前足、中足和后足组织中无特异性表达模块。6个组织特异性表达模块内基因功能注释到组织生物学功能;其中,雌蚊触角特异性green模块内基因具有气味结合和嗅觉受体活性等功能;雌蚊喙特异性purple模块内基因具有丝氨酸型肽链内切酶活性和丝氨酸水解酶活性等功能;雄蚊脑特异性blue模块内基因在生物学过程调节、信号转导和神经系统过程等生物学过程中发挥主要作用。利用CytoHubba进一步鉴定出所选组织特异性共表达模块中具有高连通性的hub基因,包括AAEL010426, AAEL002896, AAEL002600, AAEL000961, AAEL007784和AAEL006429。【结论】本研究依据埃及伊蚊不同组织转录组数据,利用WGCNA方法发现了许多重要的基因共表达模块。本研究的结果为蚊虫基因共表达模式分析提供新思路和方法基础,对探究蚊虫不同组织特有的基因资源信息以及功能基因生物信息学研究有参考价值。