致心律失常型右室心肌病引起的心力衰竭分子标志物的筛选

目的：筛选致心律失常型右室心肌病引起心力衰竭的分子标志物。方法：从本院的心脏病组织库中挑选5例病理诊断明确和各方面资料比较齐全的致心律失常型右室心肌病引起心力衰竭的心脏病标本(来源于心脏移植的受体),与年龄、性别和种族等因素相匹配的正常对照心脏组织(来源于心脏移植的供体)进行全基因组表达芯片的比较研究。提取致心律失常型右室心肌病的左心室组织RNA,同时提取正常对照心脏相应部位的RNA。应用晶芯人类全基因组寡核苷酸微阵列基因表达谱芯片(含有人类基因35,000个),筛选致心律失常型右室心肌病引起的心力衰竭基因表达谱的改变。应用实时定量荧光反转录聚合酶链式反应(real-time RT-PCR)验证致心律失常型右室心肌病引起的心力衰竭基因表达改变的真实性和准确性。 结果：应用基因表达芯片研究方法共筛选出78个差异表达基因,其中有35个基因在致心律失常型右室心肌病引起的心力衰竭中表达升高,而另有43个基因表达降低。其中变化较多的基因属于与代谢相关的基因。对其中36个差异表达基因应用real-time RT-PCR的方法进行了验证,差异表达基因的准确性在75%,并首次报告了心钠素在致心律失常型右室心肌病引起的心力衰竭中表达明显升高。结论：本研究在世界上首次应用基因表达芯片的方法,观察了致心律失常型右室心肌病引起的心力衰竭基因表达谱的改变,为致心律失常型右室心肌病引起的心力衰竭分子机制的阐明和寻找疾病特异的分子标志物,以用于鉴别诊断、判断病情和预后及指导个性化治疗奠定了基础。     

生信分析筛选心衰氧化应激相关关键[]基因并预测候选药物

为探究氧化应激相关基因在心力衰竭发生发展中的作用,并发现核心基因进行靶基因药物预测。从GEO数据库下载GSE120895基因表达图谱,通过GEO2R筛选差异表达基因,将差异表达基因与GeneCard数据库中筛选的氧化应激相关基因取交集,得到心力衰竭氧化应激相关差异表达基因,利用R软件对差异表达基因进行GO及KEGG分析,利用Cytoscape进行PPI网络的模块以及关键基因的筛选。之后在GSE17800基因表达图谱中验证关键基因的表达,并针对关键基因进行相互作用药物预测。差异表达基因与氧化应激相关基因取交集后,共筛选出52个上调的氧化应激相关差异表达基因,在此基础上,筛选出ACTB,STAT3,FN1,EDN1,CAT共5个关键基因,在GSE17800基因表达图谱中验证后,针对4个关键基因预测了19个靶基因潜在药物。总之,本研究通过生物信息学方法鉴定关键基因,并预测潜在治疗药物,从而为了解心力衰竭的分子机制及其诊治方法提供新的见解。     

Affymetrix基因表达谱芯片在新疆维吾尔族与汉族胰腺癌组织样本间差异表达基因筛选中的运用

目的:运用基因表达谱芯片筛选并分析新疆维吾尔族与汉族胰腺癌组织样本间的差异表达基因。方法:收集我院2014年1月至2016年6月间行手术切除的维吾尔族与汉族胰腺导管细胞癌组织并提取总RNA,选取经Nanodrop 2000与Agilent 2100仪器质检合格的样本总RNA采用Affymetrix基因表达谱芯片筛选出差异表达基因并绘制统计图,运用基因本体(GO)分析及信号通路(Pathway)分析对这些差异表达基因的生物信息进行汇总分析。结果:通过基因表达谱芯片分析,新疆维吾尔族与汉族胰腺癌组织样本间共检测到1063个基因存在差异表达,在维吾尔族胰腺癌标本中显著上调表达的基因共281个,差异表达倍数最高的为IGLV1-44基因(差异倍数:9.99)下调表达的基因共782个,差异表达倍数最高的为CPB1基因(差异倍数:33.76);在Gene Ontology数据库中共检索到815个上述差异表达基因具有明确的GO分类,差异表达倍数最高的为CPB1基因(差异倍数:33.76);Pathway分析中共检测到30条信号通路包含有上述差异表达基因,共涉及196个基因,其中以FAK信号通路差异表达基因富集程度最高,差异表达倍数最高的基因为COL11A1基因(差异倍数:5.02)。结论:基因表达谱芯片分析结果显示,在新疆维吾尔族与汉族胰腺癌组织样本间存在大量的差异表达基因,这些基因与胰腺癌的增殖分化、侵袭转移及多药耐药等特性密切相关,且参与了多条生物体内重要信号转导通路的调控。     

生物信息学分析筛选结直肠癌靶基因及评估预后价值

为寻找与结直肠癌发展和预后相关的潜在关键基因及信号通路.从美国国立信息中心NCBI的GEO数据库获得结直肠癌基因表达数据集GSE106582,通过PCA对样本进行分组,利用GEO2R进行综合分析,筛选结直肠癌与癌旁对照组的差异表达基因;通过DAVID在线工具对差异表达基因进行GO本体分析和KEGG通路富集分析,初步分析...     

Molecular signatures of cardiac defects in down syndrome lymphoblastoid cell lines suggest altered ciliome and hedgehog pathways

Forty percent of people with Down syndrome exhibit heart defects, most often an atrioventricular septal defect (AVSD) and less frequently a ventricular septal defect (VSD) or atrial septal defect (ASD). Lymphoblastoid cell lines (LCLs) were established from lymphocytes of individuals with trisomy 21, the chromosomal abnormality causing Down syndrome. Gene expression profiles generated from DNA microarrays of LCLs from individuals without heart defects (CHD(-); n?=?22) were compared with those of LCLs from patients with cardiac malformations (CHD(+); n?=?21). After quantile normalization, principal component analysis revealed that AVSD carriers could be distinguished from a combined group of ASD or VSD (ASD+VSD) carriers. From 9,758 expressed genes, we identified 889 and 1,016 genes differentially expressed between CHD(-) and AVSD and CHD(-) and ASD+VSD, respectively, with only 119 genes in common. A specific chromosomal enrichment was found in each group of affected genes. Among the differentially expressed genes, more than 65% are expressed in human or mouse fetal heart tissues (GEO dataset). Additional LCLs from new groups of AVSD and ASD+VSD patients were analyzed by quantitative PCR; observed expression ratios were similar to microarray results. Analysis of GO categories revealed enrichment of genes from pathways regulating clathrin-mediated endocytosis in patients with AVSD and of genes involved in semaphorin-plexin-driven cardiogenesis and the formation of cytoplasmic microtubules in patients with ASD-VSD. A pathway-oriented search revealed enrichment in the ciliome for both groups and a specific enrichment in Hedgehog and Jak-stat pathways among ASD+VSD patients. These genes or related pathways are therefore potentially involved in normal cardiogenesis as well as in cardiac malformations observed in individuals with trisomy 21.     

The mechanical effects of CRT promoting autophagy via mitochondrial calcium uniporter down‐regulation and mitochondrial dynamics alteration

The mechanism of cardiac resynchronization therapy (CRT) remains unclear. In this study, mitochondria calcium uniporter (MCU), dynamin‐related protein‐1 (DNM1L/Drp1) and their relationship with autophagy in heart failure (HF) and CRT are investigated. Thirteen male beagle's dogs were divided into three groups (sham, HF, CRT). Animals received left bundle branch (LBB) ablation followed by either 8‐week rapid atrial pacing or 4‐week rapid atrial pacing and 4‐week biventricular pacing. Cardiac function was evaluated by echocardiography. Differentially expressed genes (DEGs) were detected by microarray analysis. General morphological changes, mitochondrial ultrastructure, autophagosomes and mitophagosomes were investigated. The cardiomyocyte stretching was adopted to imitate the mechanical effect of CRT. Cells were divided into three groups (control, angiotensin‐II and angiotensin‐II + stretching). MCU, DNM1L/Drp1 and autophagy markers were detected by western blots or immunofluorescence. In the present study, CRT could correct cardiac dysfunction, decrease cardiomyocyte's size, alleviate cardiac fibrosis, promote the formation of autophagosome and mitigate mitochondrial injury. CRT significantly influenced gene expression profile, especially down‐regulating MCU and up‐regulating DNM1L/Drp1. Cell stretching reversed the angiotensin‐II induced changes of MCU and DNM1L/Drp1 and partly restored autophagy. CRT's mechanical effects down‐regulated MCU, up‐regulated DNM1L/Drp1 and subsequently enhanced autophagy. Besides, the mechanical stretching prevented the angiotensin‐II‐induced cellular enlargement.     

Isolation and analysis of genes mainly expressed in adult mouse heart using subtractive hybridization cDNA library

Subtractive hybridization cDNA library (SHL) is one of the powerful approaches for isolating differentially expressed genes. Using this technique between mouse heart and skeletal muscle (skm) tissues, we aimed to construct a cDNA-library that was specific to heart tissue and to identify the potential candidate genes that might be responsible for the development of cardiac diseases or related pathophysiological conditions. In the first step of the study, we created a cDNA-library between mouse heart and skm tissues. The homologies of the randomly selected 215 clones were analyzed and then classified by function. A total of 146 genes were analyzed for their expression profiles in the heart and skm tissues in published mouse microarray dataset. In the second step, we analyzed the expression patterns of the selected genes by Northern blot and RNA in situ hybridization (RISH). In Northern blot analyses, the expression levels of Myl3, Myl2, Mfn2, Dcn, Pdlim4, mt-Co3, mt-Co1, Atpase6 and Tsc22d1 genes were higher in heart than skm. For first time with this study, expression patterns of Pdlim4 and Tsc22d1 genes in mouse heart and skm were shown by RISH. In the last step, 43 genes in this library were identified to have relationships mostly with cardiac diseases and/or related phenotypes. This is the first study reporting differentially expressed genes in healthy mouse heart using SHL technique. This study confirms our hypothesis that tissue-specific genes are most likely to have a disease association, if they possess mutations.     

Identification of hypertrophy- and heart failure-associated genes by combining in vitro and in vivo models

Heart failure (HF) is a complex disease involving multiple changes including cardiomyocyte hypertrophy (growth). Here we performed a set of screens in different HF and hypertrophy models to identify differentially expressed genes associated with HF and/or hypertrophy. Hypertensive Ren2 rats and animals with postmyocardial infarction (post-MI) HF were used as in vivo HF models, and neonatal rat cardiomyocytes treated with hypertrophy inducing hormones phenylephrine, endothelin-1, and isoproterenol were used as in vitro models. This combined approach revealed a robust set of genes that were differentially expressed both in vitro and in vivo. This included known genes like NPPA (ANP) and FHL1, but also novel genes not previously associated with hypertrophy/HF. Among these are PTGIS, AKIP1, and Dhrs7c, which could constitute interesting targets for further investigations. We also identified a number of in vivo specific genes and these appeared to be enriched for fibrosis, wounding, and stress responses. Therefore a number of novel genes within this in vivo specific list could be related to fibroblasts or other noncardiomyocytes present in the heart. We also observed strong differences between the two HF rat models. For example KCNE1 was strongly upregulated in Ren2, but not in post-MI HF rats, suggesting possible etiology-specific differences. Moreover, Gene Ontology analysis revealed that genes involved in fatty acid oxidation were specifically down regulated in the post-MI group only. Together these results show that combining multiple models, both in vivo and in vitro, can provide a robust set of hypertrophy/HF-associated genes. Moreover it provides insight in the differences between the different etiology models and neurohormonal effects.     

乳腺癌基因芯片实验数据分析与挖掘

目的 对公共数据库上下载得到的乳腺癌基因芯片试验结果进行数据分析,找出在正常组织与癌组织中呈现差异表达的基因,并寻找差异表达基因的相关基因.方法 综合运用显著性分析（SAM）、顶级评分基因对（TSP）、关联规则挖掘等方法,对数据进行处理.结果 筛选出若干呈现差异表达的基因,并且寻找了其中一部分基因的可能高度相关的基因.结论 筛选出的基因及其相关基因可用于为进一步的研究提供候选基因.     

Cardiomyocyte apoptosis in the right auricle of patients with ostium secundum atrial septal defect diseases

Ostium secundum atrial septal defect (osASD) is one of the most commonly occurring cardiac malformations. Although some embryological pathways have been elucidated, the molecular etiologies of ASD are not fully understood. Previous microarray analysis in our laboratory identified differentially expressed genes between osASD and normal right auricular myocardium. Of the 1056 differentially expressed genes, 14 genes were related to apoptosis: eight pro-apoptotic genes were up-regulated and six anti-apoptotic genes were down-regulated in ASD patients. In the current study, we utilized semi-quantitative RT-PCR, electron microscopy, TUNEL and flow cytometry to further understand the role of apoptosis in the atrium of osASD patients. RT-PCR results confirmed differential expression data from previous microarray studies. Additionally, while apoptosis was detected in the right auricular myocardium of all osASD patients, it was absent in controls. These data suggested apoptosis may play an important role in the pathogenesis of osASD or possibly occurs as a consequence of volume overload and hemodynamic changes in right atrium of osASD patients.     

A Regression-Based Differential Expression Detection Algorithm for Microarray Studies with Ultra-Low Sample Size

Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED). Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.     

6天龄与10天龄大鼠的睾丸组织的基因差异表达

通过基因芯片技术,利用Roche-NimbleGen公司制作的大鼠12×135K全基因组表达谱芯片,对日龄为6d和10d的大鼠睾丸组织进行全基因组表达差异分析。结果显示:具有2倍以上的差异表达基因有4298个,其中表达上调的基因共1878个,表达下调的基因共2420个。这些差异表达的基因中有3154个基因具有基因本体注释,参与了154个生物学通路。进一步分析表明具有8倍以上差异表达的基因有13个,这些基因参与了生物学过程、细胞组分和分子功能等基因本体分类,进一步选择3个差异表达的基因,LOC686076、Cxcl6和Trib3,做了实时定量RT-PCR检测。其结果趋势与芯片数据一致。因此,我们初步认为精原干细胞的发生与增殖在大鼠早期的发育过程中已经有大量的基因参与,是一个多基因协调表达的过程。     

The Whole Genome Expression Analysis using Two Microarray Technologies to Identify Gene Networks That Mediate the Myocardial Phenotype of CD36 Deficiency

We have previously shown that CD36 is a membrane protein that facilitates long chain fatty acid (FA) transport by muscle tissues. We also documented the significant impact of muscle CD36 expression on heart function, skeletal muscle insulin sensitivity as well as on overall metabolism. To identify a comprehensive set of genes that are differentially regulated by CD36 expression in the heart, we used two microarray technologies (Affymetrix and Agilent) to compare gene expression in heart tissues from CD36 KnocK-Out (KO-CD36) versus wild type (WT-CD36) mice. The obtained results using the two technologies were similar with around 35 genes differentially expressed using both technologies. Absence of CD36 led to down-regulation of the expression of three groups of genes involved in pathways of FA metabolism, angiogenesis/apoptosis and structure. These data are consistent with the fact that the CD36 protein binds FA and thrombospondin 1 invoved respectively in lipid metabolism and anti-angiogenic activities. In conclusion, our findings led to validate our data analysis workflow and identify specific pathways, possibly underlying the phenotypic abnormalities in CD36 Knock -Out hearts.