快速老化小鼠海马差异表达cDNA芯片的制作

老年性痴呆(Alzheimer’s disease,AD)是老年人群中最普遍的痴呆类型,是一种神经退行性紊乱疾病,目前临床上还没有有效的治疗方法。快速老化小鼠亚系P8(senescence-accelerated mouse prone8,SAMP8)是研究增龄相关性认知缺陷机制以及研究脑老化机制的良好动物,同时也是研究AD较为理想的实验动物模型之一。cDNA芯片技术可以同时规模研究成千上万个基因的表达,尤其适于AD这种多机制、多靶标、多途径的复杂疾病的研究,为了揭示AD的发病机制,发现用于治疗AD的药物靶标,以SAMP8和SAMR1海马抑制消减cDNA文库中的cDNA片段为材料,以β-actin和G3PDH为内参,设计了16×(1×14)点阵方案,并点制了含有3136个点的SAM海马差异表达cDNA芯片。芯片背景均匀一致,点的大小均一,排列规则整齐。在靶分子与探针杂交过程中,进行了杂交条件和洗涤芯片的优化。将杂交结果进行统计分析,选择差异表达的cDNA进行测序并进行生物信息学分析,用实时定量RT-PCR对部分基因的表达进行了验证,检测了芯片筛选结果的可靠性。该芯片的成功制备为进一步进行差异表达基因的筛选和研究提供了良好的手段,并将成为揭示SAMP8脑老化和AD发病机制的有力手段。     

Single-Stranded DNA Catalyzes Hybridization of PCR-Products to Microarray Capture Probes

Since its development, microarray technology has evolved to a standard method in the biotechnological and medical field with a broad range of applications. Nevertheless, the underlying mechanism of the hybridization process of PCR-products to microarray capture probes is still not completely understood, and several observed phenomena cannot be explained with current models. We investigated the influence of several parameters on the hybridization reaction and identified ssDNA to play a major role in the process. An increase of the ssDNA content in a hybridization reaction strongly enhanced resulting signal intensities. A strong influence could also be observed when unlabeled ssDNA was added to the hybridization reaction. A reduction of the ssDNA content resulted in a massive decrease of the hybridization efficiency. According to these data, we developed a novel model for the hybridization mechanism. This model is based on the assumption that single stranded DNA is necessary as catalyst to induce the hybridization of dsDNA. The developed hybridization model is capable of giving explanations for several yet unresolved questions regarding the functionality of microarrays. Our findings not only deepen the understanding of the hybridization process, but also have immediate practical use in data interpretation and the development of new microarrays.     

Identification and removal of contaminating fluorescence from commercial and in-house printed DNA microarrays

Microarray analysis is a critically important technology for genome-enabled biology, therefore it is essential that the data obtained be reliable. Current software and normalization techniques for microarray analysis rely on the assumption that fluorescent background within spots is essentially the same throughout the glass slide and can be measured by fluorescence surrounding the spots. This assumption is not valid if background fluorescence is spot-localized. Inaccurate estimates of background fluorescence under the spot create a source of error, especially for low expressed genes. We have identified spot-localized, contaminating fluorescence in the Cy3 channel on several commercial and in-house printed microarray slides. We determined through mock hybridizations (without labeled target) that pre-hybridization scans could not be used to predict the contribution of this contaminating fluorescence after hybridization because the change in spot-to-spot fluorescence after hybridization was too variable. Two solutions to this problem were identified. First, allowing 4 h of exposure to air prior to printing on to Corning UltraGAPS slides significantly reduced contaminating fluorescence intensities to approximately the value of the surrounding glass. Alternatively, application of a novel, hyperspectral imaging scanner and multivariate curve resolution algorithms, allowed the spectral contributions of Cy3 signal, glass, and contaminating fluorescence to be distinguished and quantified after hybridization.     

On-chip hybridization kinetics for optimization of gene expression experiments

DNA microarray technology is a powerful tool for getting an overview of gene expression in biological samples. Although the successful use of microarray-based expression analysis was demonstrated in a number of applications, the main problem with this approach is the fact that expression levels deduced from hybridization experiments do not necessarily correlate with RNA concentrations. Moreover oligonucleotide probes corresponding to the same gene can give different hybridization signals. Apart from cross-hybridizations and differential splicing, this could be due to secondary structures of probes or targets. In addition, for low-copy genes, hybridization equilibrium may be reached after hybridization times much longer than the one commonly used (overnight, i.e., 15 h). Thus, hybridization signals could depend on kinetic properties of the probe, which may vary between different oligonucleotide probes immobilized on the same microarray. To validate this hypothesis, on-chip hybridization kinetics and duplex thermostability analysis were performed using oligonucleotide microarrays containing 50-mer probes corresponding to 10 mouse genes. We demonstrate that differences in hybridization kinetics between the probes exist and can influence the interpretation of expression data. In addition, we show that using on-chip hybridization kinetics, quantification of targets is feasible using calibration curves.     

GenXHC: a probabilistic generative model for cross-hybridization compensation in high-density genome-wide microarray data

MOTIVATION: Microarray designs containing millions to hundreds of millions of probes that tile entire genomes are currently being released. Within the next 2 months, our group will release a microarray data set containing over 12,000,000 microarray measurements taken from 37 mouse tissues. A problem that will become increasingly significant in the upcoming era of genome-wide exon-tiling microarray experiments is the removal of cross-hybridization noise. We present a probabilistic generative model for cross-hybridization in microarray data and a corresponding variational learning method for cross-hybridization compensation, GenXHC, that reduces cross-hybridization noise by taking into account multiple sources for each mRNA expression level measurement, as well as prior knowledge of hybridization similarities between the nucleotide sequences of microarray probes and their target cDNAs. RESULTS: The algorithm is applied to a subset of an exon-resolution genome-wide Agilent microarray data set for chromosome 16 of Mus musculus and is found to produce statistically significant reductions in cross-hybridization noise. The denoised data is found to produce enrichment in multiple gene ontology-biological process (GO-BP) functional groups. The algorithm is found to outperform robust multi-array analysis, another method for cross-hybridization compensation.     

Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion

Background

The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained.

Methodology/Principal Findings

This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias.

Conclusions

Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.     

Relationship between genome similarity and DNA-DNA hybridization among closely related bacteria

DNA-DNA hybridization has been established as an important technology in bacterial species taxonomy and phylogenetic analysis. In this study, we analyzed how the efficiency with which the genomic DNA from one species hybridizes to the genomic DNA of another species (DNA-DNA hybridization) in microarray analysis relates to the similarity between two genomes. We found that the predicted DNA-DNA hybridization based on genome sequence similarity correlated well with the experimentally determined microarray hybridization. Between closely related strains, significant numbers of highly divergent genes (<55% identity) and/or the accumulation of mismatches between conserved genes lowered the DNA-DNA hybridization signal, and this reduced the hybridization signals to below 70% for even bacterial strains with over 97% 16S rRNA gene identity. In addition, our results also suggest that a DNA-DNA hybridization signal intensity of over 40% indicates that two genomes at least shared 30% conserved genes (>60% gene identity). This study may expand our knowledge of DNA-DNA hybridization based on genomic sequence similarity comparison and further provide insights for bacterial phylogeny analyses.     

The microarray manual curation tool (MMCT): A Web server for microarray probe evaluations

Quality control of probe sequences is a major concern in microarray technology. The presence of poor quality probes has a negative impact on the microarray data analysis process. The Microarray Manual Curation Tool (MMCT) is a web server application that provides computational and visual means to investigate the quality of individual probes for oligo microarrays. The MMCT quality metrics assess the free energy of hybridization and the secondary structure of duplexes formed by selected targets and probes, which are specific to various microarray platforms. AVAILABILITY: http://www.nrcbioinformatics.ca/mmct.     

Analysis of large-scale gene expression data.

DNA microarray technology has resulted in the generation of large complex data sets, such that the bottleneck in biological investigation has shifted from data generation, to data analysis. This review discusses some of the algorithms and tools for the analysis and organisation of microarray expression data, including clustering methods, partitioning methods, and methods for correlating expression data to other biological data.     

Conditions to ensure competitive hybridization in two-color microarray: a theoretical and experimental analysis

We derived a theoretical model that explains certain biases observed in the two-color microarray hybridization experiments reported in the literature. We show that true competition is achieved only when the hybridization kinetics of the two differentially labeled probes are the same. If the hybridization kinetics of the two differentially labeled probes is different, which can occur when the labeling and hybridization conditions for the two probes are dissimilar, then differential expression observed becomes a function of the amount of the target (i.e., DNA spotted on the slide). We use this model to validate the microarray methodology by determining the differential expression of four select Arabidopsis genes and two human genes (beta-actin and GAPDH) as a function of the amount of target arrayed. We show through both modeling and experiments that the rate constants for Cy5- and Cy3-labeled probes are the same under our exrimental conditions. Therefore, the target concentrations need not greatly exceed the probe concentration. It is obvious from the data presented that a simple treatment of an individual hybridization rate calculation does notfully describe what is occuring in today's complex, multispecies experiments. The method of validation is easily implemented to ensure data reliability by two-color microarray.     

A dual-probe hybridization method for reducing variability in single nucleotide polymorphism analysis with oligonucleotide microarrays

DNA microarray technology has become powerful and popular in mutation/single nucleotide polymorphism (SNP) discovery and genotyping. However, this method is often associated with considerable signal noise of nonbiological origin that may compromise the data quality and interpretation. To achieve a high degree of reliability, accuracy, and sensitivity in data analysis, an effective normalization method to minimize the technical variability is highly desired. In the current study, a simple and robust normalization method is described. The method is based on introduction of a reference probe coimmobilized with SNP probes on the microarray for a dual-probe hybridization (DPH) reaction. The reference probe is used as an intraspot control for the customized microarrays. Using this method, the interassay coefficient of variation (CV) was reduced significantly by approximately 10%. After DPH normalization, the CVs and ranges of the ratios were reduced by two to five times. The relative magnitudes of variation of different sources were also analyzed by analysis of variance. Glass slides were shown to contribute the most to the variance, whereas sampling and residual errors had relatively modest contribution. The results showed that this DPH-based spot-dependent normalization method is an effective solution for reducing experimental variation associated with microarray genotyping data.     

Innovative instrumentation for microarray scanning and analysis: application for characterization of oligonucleotide duplexes behavior.

Accuracy in microarray technology requires new approaches to microarray reader development. A microarray reader system (optical scanning array or OSA reader) based on automated microscopy with large field of view, high speed 3 axis scanning at multiple narrow-band spectra of excitation light has been developed. It allows fast capture of high-resolution, multi-fluorescence images and is characterized by a linear dynamic range and sensitivity comparable to commonly used photo-multiplier tube (PMT)-based laser scanner. Controlled by high performance software, the instrument can be used for scanning and quantitative analysis of any type of dry microarray. Studies implying temperature-controlled hybridization chamber containing a microarray can also be performed. This enables the registration of kinetics and melting curves. This feature is required in a wide range of on-chip chemical and enzymatic reactions including on-chip PCR amplification. We used the OSA reader for the characterization of hybridization and melting behaviour of oligonucleotide:oligonucleotide duplexes on three-dimensional Code Link slides.