Improved background correction for spotted DNA microarrays.

Most microarray scanning software for glass spotted arrays provides estimates for the intensity for the "foreground" and "background" of two channels for every spot. The common approach in further analyzing such data is to first subtract the background from the foreground for each channel and to use the ratio of these two results as the estimate of the expression level. The resulting ratios are, after possible averaging over replicates, the usual inputs for further data analysis, such as clustering. If, with this background correction procedure, the foreground intensity was smaller than the background intensity for a channel, that spot (on that array) yields no usable data. In this paper it is argued that this preprocessing leads to estimates of the expression that have a much larger variance than needed when the expression levels are low.     

Determinants of sensitivity and specificity in spotted DNA microarrays with unmodified oligonucleotides

DNA microarrays with unmodified oligonucleotides are a cost-effective alternative to cDNA microarrays. This study examined how purity, length, homology and GC content of the oligonucleotide probes influence the sensitivity and specificity of the method using cyanobacterial genes. Oligonucleotide purification by high pressure liquid chromatography was omitted without significant reduction in hybridization sensitivity. For two of three genes tested, a reduction in oligonucleotide length did not reduce hybridization sensitivity, and maximum sensitivity was achieved with probes that were 45 nt long. Oligonucleotide probes with 相似文献   

Evaluation of hybridization conditions for spotted oligonucleotide-based DNA microarrays

We compared different hybridization conditions of oligonucleotide-based DNA microarray to acquire optimized and reliable microarray data. Several parameters were evaluated at different hybridization conditions, including signal-to-background (S:B) ratios, signal dynamic range, usable spots, and reproducibility. Statistical analysis showed that better results were obtained when spotted, presynthesized long oligonucleotide arrays were blocked with succinic anhydride and hybridized at 42°C in the presence of 50% formamide.     

Methods for estimating and mitigating errors in spotted, dual-color DNA microarrays

The conceptual simplicity of DNA microarray technology often belies the complex nature of the measurement errors inherent in the methodology. As the technology has developed, the importance of understanding the sources of uncertainty in the measurements and developing ways to control their influence on the conclusions drawn has become apparent. In this review, strategies for modeling measurement errors and minimizing their effect on the outcome of experiments using a variety of techniques are discussed in the context of spotted, dual-color microarrays. First, methods designed to reduce the influence of random variability through data filtering, replication, and experimental design are introduced. This is followed by a review of data analysis methods that partition the variance into random effects and one or more systematic effects, specifically two-sample significance testing and analysis of variance (ANOVA) methods. Finally, the current state of measurement error models for spotted microarrays and their role in variance stabilizing transformations are discussed.     

Analysis of repeatability in spotted cDNA microarrays

We report a strategy for analysis of data quality in cDNA microarrays based on the repeatability of repeatedly spotted clones. We describe how repeatability can be used to control data quality by developing adaptive filtering criteria for microarray data containing clones spotted in multiple spots. We have applied the method on five publicly available cDNA microarray data sets and one previously unpublished data set from our own laboratory. The results demonstrate the feasibility of the approach as a foundation for data filtering, and indicate a high degree of variation in data quality, both across the data sets and between arrays within data sets.     

Reliability of gene expression ratios for cDNA microarrays in multiconditional experiments with a reference design

In a typical gene expression profiling experiment with multiple conditions, a common reference sample is used for co-hybridization with the samples to yield expression ratios. Differential expression for any other sample pair can then be calculated by assembling the ratios from their hybridizations with the reference. In this study we test the validity of this approach. Differential expression of a sample pair (i, j) was obtained in two ways: directly, by hybridizations of sample i versus j, and indirectly, by multiplying the expression ratios for hybridizations of sample i versus pool and pool versus sample j. We performed gene expression profiling using amphibian embryos (Xenopus laevis). Every sample combination of four different stages and a pool was profiled. Direct and indirect values were compared and used as the quality criterion for the data. Based on this criterion, 82% of all ratios were found to be sufficiently accurate. To increase the reliability of the signals, several widely used filtering techniques were tested. Filtering by differences of repeated hybridizations was found to be the optimal filter. Finally, we compared microarray-based gene expression profiles with the corresponding expression patterns obtained by whole-mount in situ hybridizations, resulting in a 90% correspondence.     

Construction and use of spotted large-insert clone DNA microarrays for the detection of genomic copy number changes

Microarray-based comparative genomic hybridization has become a widespread method for the analysis of DNA copy number changes across the human genome. Initial methods for microarray construction using large-insert clones required the preparation of DNA from large-scale cultures. This rapidly became an expensive and time-consuming process when expanded to the number of clones needed for higher resolution arrays. To overcome this problem, several PCR-based strategies have been developed to enable array construction from small amounts of cloned DNA. Here, we describe the construction of microarrays composed of human-specific large-insert clones (40-200 kb) using a specific degenerate oligonucleotide PCR strategy. In addition, we also describe array hybridization using manual and automated procedures and methods for array analysis. The technology and protocols described in this article can easily be adapted for other species dependent on the availability of clone libraries. According to our protocols, the procedure will take approximately 3 days from labeling the DNA to scanning the hybridized slides.     

Multifactorial experimental design for optimizing transformation: Electroporation of Streptococcus thermophilus

A multifactorial process was used to optimize transformation of Streptococcus thermophilus by electroporation. Simple experimental designs were applied to study three, four, or five factors in eight experiments. Four qualitative factors, growth and recovering media, and plasmid and bacterial strains, were studied empirically. Eight quantitative factors, including electrical, physiological, and chemical parameters, were studied by fractional factorial designs. Effects of individual parameters as well as interactions between them were investigated and optimized. Optimization was performed for one S. thermophilus strain, ST11, and proved to work for all other tested strains of the same species. Transformation efficiencies of 9 x 10(2) to 6 x 10(5) transformants per microgram DNA were achieved, depending on the strains and vectors used. (c) 1994 John Wiley & Sons, Inc.     

Detecting unknown sequences with DNA microarrays: explorative probe design strategies

Designing environmental DNA microarrays that can be used to survey the extreme diversity of microorganisms existing in nature, represents a stimulating challenge in the field of molecular ecology. Indeed, recent efforts in metagenomics have produced a substantial amount of sequence information from various ecosystems, and will continue to accumulate large amounts of sequence data given the qualitative and quantitative improvements in the next-generation sequencing methods. It is now possible to take advantage of these data to develop comprehensive microarrays by using explorative probe design strategies. Such strategies anticipate genetic variations and thus are able to detect known and unknown sequences in environmental samples. In this review, we provide a detailed overview of the probe design strategies currently available to construct both phylogenetic and functional DNA microarrays, with emphasis on those permitting the selection of such explorative probes. Furthermore, exploration of complex environments requires particular attention on probe sensitivity and specificity criteria. Finally, these innovative probe design approaches require exploiting newly available high-density microarray formats.     

Normalization of two-channel microarrays accounting for experimental design and intensity-dependent relationships

In normalizing two-channel expression arrays, the ANOVA approach explicitly incorporates the experimental design in its model, and the MA plot-based approach accounts for intensity-dependent biases. However, both approaches can lead to inaccurate normalization in fairly common scenarios. We propose a method called efficient Common Array Dye Swap (eCADS) for normalizing two-channel microarrays that accounts for both experimental design and intensity-dependent biases. Under reasonable experimental designs, eCADS preserves differential expression relationships and requires only a single array per sample pair.     

Genome-scale design of PCR primers and long oligomers for DNA microarrays

During the last years, the demand for custom-made cDNA chips/arrays as well as whole genome chips is increasing rapidly. The efficient selection of gene-specific primers/oligomers is of the utmost importance for the successful production of such chips. We developed GenomePRIDE, a highly flexible and scalable software for designing primers/oligomers for large-scale projects. The program is able to generate either long oligomers (40–70 bases), or PCR primers for the amplification of gene-specific DNA fragments of user-defined length. Additionally, primers can be designed in-frame in order to facilitate large-scale cloning into expression vectors. Furthermore, GenomePRIDE can be adapted to specific applications such as the generation of genomic amplicon arrays or the design of fragments specific for alternative splice isoforms. We tested the performance of GenomePRIDE on the entire genomes of Listeria monocytogenes (1584 gene-specific PCRs, 48 long oligomers) as well as of eukaryotes such as Schizosaccharomyces pombe (5006 gene-specific PCRs), and Drosophila melanogaster (21 306 gene-specific PCRs). With its computing speed of 1000 primer pairs per hour and a PCR amplification success of 99%, GenomePRIDE represents an extremely cost- and time-effective program.     

DNA microarrays with stem-loop DNA probes: preparation and applications

We have developed DNA microarrays containing stem-loop DNA probes with short single-stranded overhangs immobilized on a Packard HydroGel chip, a 3-dimensional porous gel substrate. Microarrays were fabricated by immobilizing self-complementary single-stranded oligonucleotides, which adopt a partially duplex structure upon denaturing and re-annealing. Hybridization of single-stranded DNA targets to such arrays is enhanced by contiguous stacking interactions with stem-loop probes and is highly sequence specific. Subsequent enzymatic ligation of the targets to the probes followed by stringent washing further enhances the mismatched base discrimination. We demonstrate here that these microarrays provide excellent specificity with signal-to-background ratios of from 10- to 300-fold. In a comparative study, we demonstrated that HydroGel arrays display 10-30 times higher hybridization signals than some solid surface DNA microarrays. Using Sanger sequencing reactions, we have also developed a method for preparing nested 3'-deletion sets from a target and evaluated the use of stem-loop DNA arrays for detecting p53 mutations in the deletion set. The stem-loop DNA array format is simple, robust and flexible in design, thus it is potentially useful in various DNA diagnostic tests.     

Systematic profiling of cellular phenotypes with spotted cell microarrays reveals mating-pheromone response genes

We have developed spotted cell microarrays for measuring cellular phenotypes on a large scale. Collections of cells are printed, stained for subcellular features, then imaged via automated, high-throughput microscopy, allowing systematic phenotypic characterization. We used this technology to identify genes involved in the response of yeast to mating pheromone. Besides morphology assays, cell microarrays should be valuable for high-throughput in situ hybridization and immunoassays, enabling new classes of genetic assays based on cell imaging.     

Exploring the post-transcriptional RNA world with DNA microarrays

Genomic approaches are valuable for understanding the complex layer of gene regulation that involves the control of RNA processing, localization and stability. Recent work provides a prime example of the power of unbiased microarray-based methods to discover unexpected functions for proteins in the RNA world. The challenges ahead relate to extending such approaches to larger genomes and to integrating this type of information with that generated by standard expression profiling.     

Quantification of global transcription patterns in prokaryotes using spotted microarrays

We describe an analysis, applicable to any spotted microarray dataset produced using genomic DNA as a reference, that quantifies prokaryotic levels of mRNA on a genome-wide scale. Applying this to Mycobacterium tuberculosis, we validate the technique, show a correlation between level of expression and biological importance, define the complement of invariant genes and analyze absolute levels of expression by functional class to develop ways of understanding an organism's biology without comparison to another growth condition.