Cell culture and RNA sample preparation
LβT2 cells obtained from Pamela Mellon (University of California, San Diego, CA) were maintained at 37°C in 5% CO2
in humidified air in DMEM (Mediatech, Herndon, VA) containing 10% fetal bovine serum (Gemini, Calabasas, CA). Cells (40–50 × 106
) were seeded in 15 cm dishes and medium was replaced 24 h later with DMEM containing 25 mM HEPES (Mediatech) and glutamine. The next day, the cells were treated with 100 nM GnRH or vehicle and were returned to the CO2
incubator for 1 h, at which point the medium was replaced with 10 ml lysis buffer (4 M guanidinium thiocyanate, 25 mM sodium citrate pH 7.0, 0.5% N
-lauroyl-sarcosine and 0.1 M 2-mercaptoethanol). Total RNA was isolated according to the method of Chomczynski and Sacchi (12
). Samples from three vehicle- and three GnRH-exposed cultures were assayed using each of the two microarray platforms studied. As one treated and control sample pair was hybridized with both arrays, a total of 10 RNA samples were used in this study (Fig. ).
Oligonucleotide microarray probe labeling and hybridization
First strand cDNA was synthesized by incubating 40 µg of total RNA with 400 U SuperScript II reverse transcriptase (Invitrogen, Carlsbad, CA), 100 pmol T7-(dT)24 primer [5′-GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGCGG-(dT)24-3′], 1× first strand buffer (50 mM Tris–HCl pH 8.3, 75 mM KCl, 3 mM MgCl2, 10 mM DTT) and 0.5 mM dNTPs at 42°C for 1 h. Second strand synthesis was performed by incubating the first strand cDNA with 10 U Escherichia coli ligase (Invitrogen), 40 U DNA polymerase I (Invitrogen), 2 U RNase H (Invitrogen), 1× reaction buffer [18.8 mM Tris–HCl pH 8.3, 90.6 mM KCl, 4.6 mM MgCl2, 3.8 mM DTT, 0.15 mM NAD, 10 mM (NH4)2SO4] and 0.2 mM dNTPs at 16°C for 2 h. Ten units of T4 DNA polymerase (Invitrogen) were then added, and the reaction was allowed to continue for another 5 min at 16°C. After phenol–chloroform extraction and ethanol precipitation, the double-stranded cDNA was resuspended in 10 µl DEPC-treated dH2O. Labeling of the dsDNA was done by in vitro transcription using a BioArray HighYield RNA transcript labeling kit (Enzo Diagnostics, Farmingdale, NY). Briefly, the dsDNA was mixed with 1× HY reaction buffer, 1× biotin labeled ribonucleotides (NTPs with Bio-UTP and Bio-CTP), 1× DTT, 1× RNase inhibitor mix and 1× T7 RNA polymerase. The mixture was incubated at 37°C for 5 h, with gentle mixing every 30 min. The labeled cRNA was then purified using a RNeasy mini kit (Qiagen, Valencia, CA) according to the manufacturer’s protocol and ethanol precipitated. The purified cRNA was fragmented in 1× fragmentation buffer (40 mM Tris–acetate, 100 mM KOAc, 30 mM MgOAc) at 94°C for 35 min. For hybridization with GeneChip cartridge (Affymetrix), 15 µg fragmented cRNA probe was incubated with 50 pM control oligonucleotide B2, 1× eukaryotic hybridization control (1.5 pM BioB, 5 pM BioC, 25 pM BioD and 100 pM cre), 0.1 mg/ml herring sperm DNA, 0.5 mg/ml acetylated BSA and 1× manufacturer recommended hybridization buffer in a 45°C rotisserie oven for 16 h. Washing and staining was performed with a GeneChip fluidic station (Affymetrix) using the appropriate antibody amplification washing and staining protocol. The phycoerythrin-stained array was scanned as a digital image file.
Oligonucleotide array quality control and data analysis
To assess the quality of the cRNA labeling, the probe was first hybridized to a Test2 Array (Affymetrix). The scanned image, after visually inspected to be free of specks or scratches, was analyzed using Microarray Suite 5.0 (Affymetrix). We required probe labeling to exceed the following benchmarks in the test array: low noise (RawQ <15), low background (<600), low 3′ to 5′ ratio of actin and GAPDH (ratio <2) and presence of control genes cre, BioD and BioC. Probes that exceeded these quality control values in the test hybridization were used with the GeneChip U74A mouse genome array. A total of six arrays were used (three with vehicle-treated samples and three with GnRH-treated samples). Quality control was identical to that for the Test2 Array but, because of the smaller feature size on the high density U74A array (20 versus 50 µm on the Test2 Array), a slightly higher noise was acceptable (RawQ <30). Pairwise comparison was done between all possible vehicle-treated versus GnRH-treated sample pairs to generate the relative levels of expression of each transcript, Fa(oligo), used in the analysis. A repeat analysis of all data was also performed using Microarray Suite 4.0 (Affymetrix), which is based on an empirical algorithm rather than a statistical algorithm. In this case the ratios of the mean-difference of all perfect-match mismatch oligonucleotide pairs for each gene between each experimental and control samples are the Fa(oligo) values used for analysis. The occasional negative fold-change values obtained using Microarray Suite 4.0 were converted to the reciprocal of the absolute value and all tildes were removed. All oligonucleotide data shown in the Figures are from the Microarray Suite 5.0-based analysis. As there are three experimental and three control samples, there were nine Fa(oligo) values for cluster on the array studied. The nine genes assayed by more than one cluster on the array were analyzed independently.
cDNA microarray development, probe labeling and hybridization
The design, quality control, validation and detailed protocols for use and analysis of this microarray have been described elsewhere (5
). Briefly, this array contains 956 clones selected mostly from an NIA 15K library (13
) or purchased from Research Genetics. Plasmid inserts were amplified by PCR, products were confirmed by agarose gel electrophoresis and purified. The dried product was spotted in 50% DMSO (three hits/feature, three features/gene) with a GMS 417 Arrayer (Affymetrix) on CMT–GAPS coated glass slides (Corning, Corning, NY). DNA was fixed at 85°C for 2 h.
Aliquots of 20 µg of total RNA from each sample were labeled with either Cy3 or Cy5 using the Atlas indirect labeling kit (Clontech, Palo Alto, CA) as indicated by the manufacturer. After array prehybridization (6× SSC, 0.5% SDS, 1% BSA at 42°C for 45 min), the probe was denatured and hybridized in 24 µl 50% formamide, 6× SSC, 0.5% SDS, 5× Denhardt’s with 2.4 µg salmon sperm DNA, 10 µg poly(dA) at 42°C for 16 h. Following 10 min washes in 0.1× SSC, 0.1% SDS, and twice in 0.1× SSC, the slide was scanned using the GMS 418 Scanner (Affymetrix).
cDNA microarray data analysis
Scanned microarray data were exported as TIFF files to Genepix (Axon Instruments, Union City, CA) and spot registration was optimized manually as suggested by the developer. The median background-subtracted feature intensity was utilized for further analysis. Overall differences in the signal intensity of the two wavelengths measured on each slide (λ = 532 nm and λ = 635 nm) were corrected using the loess function in S Plus Professional (Insightful Corporation, Seattle, WA). Predictors were generated using a symmetric distribution, span = 0.75 (14
). The ratios of the resulting corrected data for each feature were used for subsequent analysis. Coefficient of variations (cv) of the triplicate measurements on each array were determined as previously described (5
As a basis for comparison of the two array platforms, we chose to analyze a selection of 47 genes that are present on both arrays. These 47 selected genes have previously been shown to consist of roughly equal numbers of regulated and non-regulated genes in this experimental paradigm (5
). Some target clusters were incorrectly designed on the U74A oligonucleotide array and the genes selected for study excluded target clusters from this group. All 47 genes selected were sequence confirmed on the cDNA array. Out of these 47 genes, 7 were represented by two or more separate clusters on the oligonucleotide arrays and 5 were represented by two different inserts on the cDNA array.
Quantitative real-time PCR
We used a previously described protocol (15
). Briefly, 5 µg total RNA was converted into cDNA and 1/400 (~250 pg) was utilized for 40 cycle three-step PCR in either an ABI Prism 7700 or ABI 7900HT (Applied Biosystems, Foster City, CA) in 20 mM Tris pH 8.4, 50 mM KCl, 3 mM MgCl2
, 200 µM dNTPs, 0.5× SYBR Green I (Molecular Probes, Eugene, OR), 200 nM each primer and 0.5 U Platinum Taq (Invitrogen). Amplicon size and reaction specificity were confirmed by agarose gel electrophoresis. The number of target copies in each sample was interpolated from its detection threshold (CT
) value using a plasmid or purified PCR product standard curve included on each plate. The sequence of the primer sets utilized are reported elsewhere (5
). Each transcript in each sample was assayed five times and the median CT
values were used to calculate the Fp
values (fold-change ratios between experimental and control samples for each gene) used in the analysis.
QRTPCR measurement precision was assessed by determining the reproducibility of Fp values. For this purpose, four or five independent Fp determinations were made in separate QRTPCR runs for five genes using the same experimental and treatment RNA samples. The resulting Fp values were then used to calculate the cv for each of the five genes and the overall average cv.
Determination of relative expression of the genes assayed in the different samples by QRTPCR should be corrected for any differences in reaction efficiency between the sample cDNAs and the standard curve samples. In order to determine reaction efficiency, we parametrized the QRTPCR fluorescence data for every run according to
F(C) = P(C)+T × (1+E)C
where F(C) is the fluorescence detected at each cycle number C, P(C) is the instrument background fluorescence, T is the fluorescence arising from the target sequence, and E is the PCR efficiency.
First, the background fluorescence was fit as a second order polynomial by unweighted regression using a commercial statistical analysis software package (S-Plus 6 Release 2, Insightful Corp.) over a range of cycles in which the target-induced fluorescence remained insignificant. This approach was selected to accommodate any systematic instrument drift occurring over time. This polynomial was subtracted from the fluorescence data over its entire range, and a range of cycles was selected over which the resulting fluorescence data f(C) was well fit by an exponential function
f(C) = T × exp(N × C)
with pre-factor T and slope N, using the same software. This occurred in a cycle range over which ln(f) was approximately linear: beyond the initial background-dominated region and before the saturation region. The efficiency was then straightforwardly determined as
E = exp(N) – 1
Variation in QRTPCR arising from reverse transcription
We evaluated the variation in the determination of the levels of specific mRNAs that resulted from the reverse transcription of the RNA samples by determining the variation in CT values obtained for several transcripts when repeated independent cDNA syntheses from the same RNA sample were assayed. Six repeated cDNA syntheses were performed with a total of four RNA samples and five transcripts were assayed in cDNAs from two of the RNA samples and five other transcripts were assayed in cDNAs from the other two RNA samples. To reduce the contribution of the variation occurring from the PCR to the overall determination of variance in this experiment, we obtained three to six replicate measurements for each transcript assayed from each sample and utilized the median value of these repeated measurements for our calculations. We then determined a cv using each group of six resulting median CT values corresponding to the same transcript assayed in six cDNA samples generated from the same starting RNA sample. A total of 18 determinations of cv from repeated cDNA syntheses were obtained.
The experiments utilized to generate the samples for this study results in only up-regulated genes (5
). An oligonucleotide array gene was considered regulated if it was identified as increased in at least six of the nine pairwise comparisons from all experiments using the difference call algorithm included in the statistics-based Microarray Suite 5.0 (see Fig. and Supplementary Material Table S1). Outlier detection of the same dataset was also performed with the empirical algorithm-based Microarray Suite 4.0 (Supplementary Material Table S2).
cDNA array genes were identified as regulated based on an algorithm described in detail elsewhere (5
). Briefly, t
values for the log transform ratios (logFa
) were determined for triplicate data from each slide. Genes were considered to be regulated if they showed Fa
> 1.3, t
> 3 and signal intensity for at least one fluorophore >1% of the median signal intensity value, with all criteria met in at least two of the three experiments (see Fig. ).
QRTPCR. In order to compare microarray sensitivity and specificity, subgroups of definitely regulated and definitely unregulated transcripts were determined by QRTPCR measurements. There are a total of 11 experimental/control ratios used in either oligonucleotide or cDNA microarray analysis (see Fig. ; nine comparisons are made with the oligonucleotide arrays, three with the cDNA arrays, and one of these comparisons, E3 + C3, overlaps in both platforms). Definitely regulated genes were defined as those transcripts showing >1.3-fold changes by QRTPCR in all 11 experimental/control ratios corresponding to the sample comparisons studied with either microarray platform. Definitely unregulated genes were defined as those showing <1.5-fold changes by QRTPCR in all 11 experimental/control ratios corresponding to the sample comparisons studied with either microarray platform. These criteria identify two distinct groups of genes in our experimental QRTPCR data (see Supplementary Material, Tables S1 and S2).
The degree of bias (δ) in the microarray datasets was estimated using
and N is the total number of ratios utilized. This assessment was calculated for all ratios with 1.3 < Fp < 50. The interval was chosen because the bias is most pronounced for regulated genes and because the few genes included in this analysis that are regulated >50-fold show a maximal array regulation effect that would distort the estimate of overall array bias were they included. δ is negative when the Fa value tends to underestimate the Fp value, and positive when the Fa value tends to overestimate the Fp value.
cDNA array calibration
The cDNA array data were calibrated by applying the following power-law transformation:
where Fc is the corrected fold change for each microarray fold change Fa between experimental and control samples. The power q was determined by fitting the microarray and PCR data using a linear regression of their logarithms, namely
over a range of QRTPCR fold changes Fp between 1.3 and 32, treating every microarray measurement independently. The power q can be visualized as that power necessary to level the slope of a straight-line fit to the data in Figure A. Each cDNA microarray contains three measurements of each gene. Each of those measurements was treated independently and compared with the same Fp value. Duplicate genes included on the microarray are likewise treated as independent measurements in calculating q. The correction obtained from this subgroup of genes was then applied to all Fa(cDNA) values.
Figure 7 cDNA array bias and calibration. (A) The ratios obtained by cDNA arrays and by QRTPCR [log (Fa(cDNA)/Fp)] are plotted against the ratio determined by QRTPCR (log Fp) as a moving average with a window of 10 values. Note the predictable (more ...)