总RNA和mRNA来源的探针与cDNA芯片杂交的差异研究

提取BEP2D细胞的总RNA并按两种方式进行cDNA芯片探针的标记,一种是将100μg BEP2D细胞的总RNA利用逆转录法直接标记成荧光探针,另一种是先从100μg BEP2D细胞的总RNA中分离出mRNA,然后再标记成荧光探针。将两份标记好的探针同时与含有230个基因的cDNA芯片杂交。杂交后的芯片经Axon4100B扫描仪扫描,发现两种方式标记探针的一致性为93．04％,并且mRNA来源探针杂交后的荧光信号值较总RNA的弱。探讨了这两种方法标记探针在基因芯片表达谱研究中的差异性,目的是为利用这两种方法标记探针进行基因表达谱研究提供一些依据。     

一种标记cDNA芯片探针的新方法

探讨mRNA长片段反转录PCR技术(RT-LDPCR)在cDNA芯片微量探针标记和信号放大中的应用.首先提取BEP2D细胞的总RNA,然后用两种不同的方法进行标记,一种为RT-LDPCR,用荧光素Cy3-dCTP进行标记;另一种为传统的RNA反转录,用荧光素Cy5-dCTP进行标记.将两种方法标记好的探针等量混合后与含有440个点(44个基因)的cDNA芯片同时杂交,发现二者具有很高的一致性(0.5＜Cy3/Cy5＞2.0).由于RNA反转录法为cDNA芯片探针标记的传统方法,从而验证了RT-LDPCR用于cDNA芯片探针标记的可行性.RT-LDPCR具有对样品总RNA的需要量少和可对样品中信号进行放大的优点,特别适合于对材料来源受到限制的RNA进行标记.     

GFP质控芯片的初步研究

目的：建立一种质量控制芯片来监测样品标记、杂交和检测过程中的失误。方法：针对GFP基因设计的4条60mer寡核苷酸探针和1条阳性对照探针polv（U）与流感寡核苷酸探针一起打印在DAKO玻片上,并构建了GFP基因的克隆载体和体外表达载体,将从这两种重组载体上获得的绿色荧光蛋白（Green Fluorescent Protein,GFP）基因的ILNA、DNA片段和人的全血样品中的DNA用限制性显示技术（Restriction Display technology,RD）扩增标记,将标记的样品和荧光标记的通用引物U分别与芯片杂交、检测,并对扫描的结果进行统计分析。结果：GFP探针与相应的样品杂交时出现阳性信号,阳性对照探针在所有的杂交中均出现阳性信号,而空白对照则未检测荧光信号。结论：建立的质控芯片具有较好的敏感性和特异性,可以用于基因芯片中的质量监控。     

DNA芯片技术中利用内标对数据归一化后检测基因的表达变化

在DNA芯片技术中 ,通过反转录反应 ,由mRNA合成带有荧光标记物的cDNA的过程中 ,往往要参入已知质量的poly(A) + RNA ,以对DNA芯片的检测灵敏度进行归一化处理 .通过体外转录的方法 ,以真核生物的cDNA克隆中的DNA片段为模板合成poly(A) +RNA ,对之定量后 ,以不同的质量比参入到样品的反转录体系中 ,代表不同的RNA拷贝丰度 ,从而对DNA芯片检测的灵敏度进行了定量 ,并得到DNA芯片上杂交点的荧光信号强度与基因表达的RNA拷贝数成正相关的关系 .利用含有内标的DNA芯片检测了热击反应后酵母细胞的基因表达变化 ,结果与Northern印迹方法检测结果是相符的     

用SARS冠状病毒全基因组芯片杂交方法分析SARS-CoV

为从临床样品中检测和分析SARSCoV病毒打基础,并为分析SARSCoV病毒的复制和转录等机理提供一种有效方法。以SARS冠状病毒TOR2株序列作为标准设计和制备一种覆盖SARS冠状病毒全基因组的寡聚核苷酸芯片,探针长度为70nt,每相邻的探针序列重复25nt,共660条。用该芯片分析了细胞培养的SARSCoV病毒总RNA、7个SARSCoV病毒的基因克隆片段。对RNA样品用随机引物进行反转录PCR获得cDNA。对DNA用随机引物扩增和dUTPcy3标记。结果用这种芯片杂交检测SARSCoV病毒RNA可见阳性信号呈全基因组分布,并且有多处连续的阳性信号点;用正常人的白细胞RNA为对照,杂交未出现明显阳性信号。检测7个SARSCoV病毒基因克隆片段,在该片段相应的探针区段出现连续阳性信号点。这种方法可有效地检测和分析样品中SARS冠状病毒全基因组的信息。     

DNA芯片制作原理及其杂交信号检测方法

文章讨论了DNA芯片的制作原理和杂交信号的检测方法。依其结构,DNA芯片可分为两种形式,DNA阵列和寡核苷酸微芯片。DNA芯片的制作方法主要有光导原位合成法和自动化点样法。DNA芯片与标记的探针或DNA样品杂交,并通过探测杂交信号谱型来实现DNA序列或基因表达的分析。适应于DNA芯片的发展,同时出现了许多新型的杂交信号检测方法。主要有激光荧光扫描显微镜、激光扫描共焦显微镜、结合使用CCD相机的荧光显微镜、光纤生物传感器、化学发生法、光激发磷光物质存储屏法、光散射法等。     

DNA芯片与应用

DNA芯片就是利用光导原位化学合成或液相合成自动化点样,将数以万计的寡核苷酸固定于固相支持物硅片、尼龙膜上,与荧光素或同位素标记的特检样本DNA/cDNA杂交,通过对杂交信号分析反映样本中的DNA序列信息。它广泛应用基因表达、DNA测序、基因分型、基因突变与多态性检测和遗传作图等生物医学研究领域。     

一种基于寡核苷酸微阵列芯片的多重可扩增探针杂交技术

多重可扩增探针杂交技术(multiplex amplifiable probe hybridization,MAPH)是近年来发展起来的一种用于基因组中DNA拷贝数检测的新技术。并发展了一种基于寡核苷酸微阵列芯片的MAPH技术。该方法根据所检测的DNA序列,制备若干具有通用引物的FCR产物作为可扩增探针组,与固定在尼龙膜上待测的基因组DNA杂交。用磁珠回收特异性杂交的探针,经生物素标记的通用引物扩增后,与相应的寡核苷酸微阵列芯片杂交。该特异性的寡核苷酸微阵列芯片包括10个抗肌营养不良基因的外显子探针和阴性、阳性探针。杂交清冼后,链霉亲和素-Cy3染色用芯片扫描仪得到杂交的荧光图像。分析荧光信号的强度差异给出特定基因片段拷贝数的变化。该方法用微阵列技术代替MAPH中的电泳检测技术,可大幅度增加检测的通量。选择了一个正常男性、一个正常女性和一个肌营养不良症患者的基因组DNA来进行验证。结果表明,该方法能够同时给出抗肌营养不良基因多个外显子中的基因片段拷贝数差异信息。     

肿瘤相关基因表达检测寡核苷酸芯片的制备及其初步应用

为研制肿瘤相关寡核苷酸芯片,并实现其在抗肿瘤反义核酸“癌泰得”作用机理研究方面的初步应用,制备了包含近450种肿瘤相关基因特异寡核苷酸探针的寡核苷酸芯片,建立了相应的质控标准.“癌泰得”用脂质体转染HepG2肿瘤细胞,提取细胞总RNA反转录并荧光标记cDNA,用制备的寡核苷酸芯片检测肝癌细胞HepG2的肿瘤相关基因表达水平,用软件分析获得其差异基因表达谱.0.4 μmol/L的反义核酸“癌泰得”作用于HepG2细胞15 h后,MDNCF、DHS等基因mRNA表达下调,MUC2、MPP11、LAT、HRIF-B、JNK3A1等mRNA基因表达上调,初步检测到了“癌泰得”的抗肿瘤作用可能的相关基因,为进一步的分子作用机理的探讨奠定基础.结果表明,制备的肿瘤相关芯片敏感度高、特异性高、重复性均较好,可用于检测肿瘤相关基因的表达谱,为临床诊断和基础研究提供了技术平台.     

新城疫液相芯片快速检测方法的建立

目的：建立可检测新城疫病毒（Newcastle disease virus,NDV）的液相芯片快速检测技术。方法：用DNAStar软件对GEN-BANK中NDV的NP基因进行序列分析设计NDV特异性探针并标记生物素,利用该探针与荧光编码微球偶联后与抽提的NDV病毒RNA的RT-PCR产物杂交反应,用液相芯片检测仪（Liquichip 200）检测荧光信号建立了NDV快速液相芯片检测方法。结果：检测结果显示,该法具有较好的特异性,不与H5AIV和H9AIV反应;检测灵敏度达到150个EID50;该法与鸡胚病毒分离法检出NDV的符合率达到97.1%。结论：初步建立了检测NDV的液相芯片技术,为进一步搭建NDV全新快速高通量检测平台奠定了基础,也为其他同类病毒的快速高通量检测提供了借鉴和经验。     

Normalization of cDNA microarray data

Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.     

Analysis of cDNA microarray images.

Microarrays are part of a new class of biotechnologies that allow the monitoring of expression levels for thousands of genes simultaneously. Image analysis is an important aspect of microarray experiments, one that can have a potentially large impact on subsequent analyses, such as clustering or the identification of differentially expressed genes. This paper reviews a number of existing image analysis methods used on cDNA microarray data. In particular, it describes and discusses the different segmentation and background adjustment methods. It was found that in some cases background adjustment can substantially reduce the precision--that is, increase the variability of low-intensity spot values. In contrast, the choice of segmentation procedure seems to have a smaller impact.     

The sharing of cDNA microarray data

During the initial development of microarrays, much discussion revolved around the technology itself. The discussion has now shifted to data analysis and data sharing. There is great interest in the sharing of cDNA microarray data, but several issues related to format, quality and validation will need to be resolved before microarray data can be meaningfully integrated into other molecular databases.     

Fundamentals of cDNA microarray data analysis

Microarray technology is a powerful approach for genomics research. The multi-step, data-intensive nature of this technology has created an unprecedented informatics and analytical challenge. It is important to understand the crucial steps that can affect the outcome of the analysis. In this review, we provide an overview of the contemporary trend on various main analysis steps in the microarray data analysis process, which includes experimental design, data standardization, image acquisition and analysis, normalization, statistical significance inference, exploratory data analysis, class prediction and pathway analysis, as well as various considerations relevant to their implementation.     

肺癌相关基因芯片的制作

探讨肺癌相关基因芯片的制作过程及其在基因表达谱方面的应用,同时对一些传统的技术环节进行了改进。首先有目的搜集了60个肺癌相关基因,用修饰后的引物将其分别克隆,经纯化、变性后,用Cartesian PinSys5500 cDNA Microarray点样仪以微阵列的形式将其点布于醛基化的玻璃片上;然后将人支气管上皮恶性转化细胞模型BEP2D细胞的原代、20代、35代的总RNA逆转录后再经LD PCR标记成荧光探讨与基因芯片进行杂交。ScanArray 3000荧光扫描仪扫描后显示,图象背景均匀、信号清晰,证实该芯片制作成功,并能取得良好的杂交效果。     

cDNA microarray technology and its applications

The cDNA microarray is the most powerful tool for studying gene expression in many different organisms. It has been successfully applied to the simultaneous expression of many thousands of genes and to large-scale gene discovery, as well as polymorphism screening and mapping of genomic DNA clones. It is a high throughput, highly parallel RNA expression assay technique that permits quantitative analysis of RNAs transcribed from both known and unknown genes. This technique provides diagnostic fingerprints by comparing gene expression patterns in normal and pathological cells, and because it can simultaneously track expression levels of many genes, it provides a source of operational context for inference and predication about complex cell control systems. This review describes this recently developed cDNA microarray technology and its application to gene discovery and expression, and to diagnostics for certain diseases.     

Standardization of protocols in cDNA microarray analysis

Systematic variations can occur at various steps of a cDNA microarray experiment and affect the measurement of gene expression levels. Accepted standards integrated into every cDNA microarray analysis can assess these variabilities and aid the interpretation of cDNA microarray experiments from different sources. A universally applicable approach to evaluate parameters such as input and output ratios, signal linearity, hybridization specificity and consistency across an array, as well as normalization strategies, is the utilization of exogenous control genes as spike-in and negative controls. We suggest that the use of such control sets, together with a sufficient number of experimental repeats, in-depth statistical analysis and thorough data validation should be made mandatory for the publication of cDNA microarray data.