Gene expression ratios derived from spotted-glass microarray experiments have become invaluable to researchers by providing sensitive and comprehensive indicators of the molecular underpinnings of cell behaviors and states. However, several drawbacks to this form of data have been noted, including the inability to relate ratios to absolute expression levels or to compare experimental conditions not measured with the same control. In this study we demonstrate a method for overcoming these obstacles. First, instead of cohybridizing labeled experimental and control samples, we hybridize each sample against labeled oligos complementary to every microarray feature. Ratios between sample intensities and intensities of the oligo reference measure sample RNA levels on a scale that relates to their absolute abundance, instead of to the variable and unknown abundances of a cDNA reference. We demonstrate that results from this type of hybridization are accurate and retain absolute abundance information far better than conventional microarray ratios. Next, to ensure the accurate measurement of sample and oligo reference intensities, which may differ by several orders of magnitude, we use a linear regression algorithm, implemented in a freely available PERL script, to combine the linear ranges of multiple scans taken at different scanner sensitivity settings onto an extended linear scale. We discuss future applications of our method to measure RNA expression on the absolute scale of number of transcripts per cell from any organism for which oligo-based spotted-glass microarrays are available. O ne of the most successful genomics technologies developed to date is the DNA microarray (1-4), which permits simultaneous detection of expression levels for every gene in an organism. Currently, spotted-glass microarray experiments are performed by using probes synthesized from two RNA samples (a reference and an experimental sample) that are labeled with different color fluors and cohybridized to an array. Differences in gene expression levels are reported as the ratio between the experimental and reference intensities (conventional microarray ratios). However, this technology, which has produced large databases of whole-genome expression data on subjects ranging from bacterial metabolism to human cancer, is not yet fully mature. The use of ratios in two-color hybridization experiments controls for several sources of experimental variation inherent in the spotted-glass microarray technology, including variation across ORFs in labeled nucleotide frequency, amount and quality of DNA spotted onto the array, uneven hybridization, and spot size and morphology (2, 5). However, conventional microarray ratios have several properties that limit subsequent computational analysis, and thus the amount of information that can be extracted from these large data sets. First, reporting expression data as ratios between cDNA reference and experimental samples results in loss of the absolute transcript abundance information carried by the individual spot fluorescence intensities, thus obscuring important differences in levels of gene expression between ORFs. The use of cDNA reference samples, which are largely uncharacterized and not easily reproduced, also hampers comparisons between data sets that use different cDNA references. One example is the inability to cluster similar conditions between time-course experiments that use initial time points as reference samples (supplemental materials to ref. 6). In this study, we develop a combination of experimental and computational methods that improves the accuracy and comparability of DNA microarray data by (i) measuring spot intensity relative to a calibrated reference sample and (ii) extrapolating data from multiple scans to increase the range of intensities reported. In this system, labeled cDNA from a sample of interest is hybridized in conjunction with a set of differentially labeled oligonucleotides of known abundance (calibrated oligo reference) containing sequences complementary to every spot on the array. After hybridization, spot intensities are measured by scanning at several detection sensitivity settings, and the results are combined onto a common linear scale by using a linear regression algorithm implemented in a PERL script called masliner (MicroArray Spot LINEar Regression). Finally, RNA abundance is expressed as a ratio to the calibrated oligo reference, a sample that is easily reproduced and provides significant signal for every feature on the array. Strains and Media. The Saccharomyces cerevisiae strain used in this study is FY4, a MATa prototroph isogenic to a GAL2 ϩ derivative of S288C (7). Media were prepared as described (8). Glucose cultures (Glu) were grown in yeast extract͞peptone͞ dextrose (YPD; 2% glucose), raffinose cultures (Raff) were grown in SDRaf (2% raffinose), and ethanol cultures (EtOH) were grown in SDEtOH (2% ethanol). Galactose cultures (Gal) were grown in YPRaf (2% raffinose) and induced for 20 min by the addition of galactose to 2%. All cultures were grown at 30°C and harvested at densities of 1-2 ϫ 10 7 cells per ml.
Another method that combines multiple scans is the masliner (Microarray Spot LINEar Regression) algorithm REF .
Measuring absolute expression with microarrays with a calibrated reference sample and an extended signal intensity range.
Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences of the United States of America
Medicine Biology