Microarray assay was performed using a service provider (LC Sciences). Total RNA sample (2 µg) were 3’-extended with a poly(A) tail using poly(A) polymerase. An oligonucleotide tag was then ligated to the poly(A) tail for later fluorescent dye staining.
Hybridization protocol
Hybridization was performed overnight (16 hours) on a µParaflo microfluidic chip using a micro-circulation pump (Atactic Technologies) ((a)Gao, X., Gulari, E., and Zhou, X. (2004) In situ synthesis of oligonucleotide microarrays. Biopolymers 73, 579-596; (b) Zhu, Q., Hong, A., Sheng, N., Zhang, X., Jun, K.-Y., Srivannavit, O., Gulari, E., Gao, X., and Zhou, X. (2007) Microfluidic biochip for nucleic acid and protein analysis. in Methods Mol. Biol. Ed. Rampal, J. B. 382:287-312.). On the microfluidic chip, each detection probe consisted of a chemically modified nucleotide coding segment complementary to target microRNA (from miRBase, http://mirbase.org) or other RNA (control or customer defined sequences) and a spacer segment of polyethylene glycol to extend the coding segment away from the substrate. The detection probes were made by in situ synthesis using PGR (photogenerated reagent) chemistry. The hybridization melting temperatures were balanced by chemical modifications of the detection probes. Hybridization used 100 mL 6xSSPE buffer (0.90 M NaCl, 60 mM Na2HPO4, 6 mM EDTA, pH 6.8) containing 25% formamide at 34 °C. After RNA hybridization, tag-conjugating Alexa Fluor®546 dye was circulated through the microfluidic chip for dye staining.
Scan protocol
Fluorescence images were collected using a laser scanner (GenePix 4000B, Molecular Device) and digitized using Array-Pro image analysis software (Media Cybernetics).
Description
Hco ISE (MHco3)
Data processing
Data were analyzed by first subtracting the background and then normalizing the signals using a LOWESS filter (Locally-weighted Regression) (Bolstad et al, 2003). Background is determined using a regression-based background mapping method. The regression is performed on 5% to 25% of the lowest intensity data points excluding blank spots. Raw data matrix is then subtracted by the background matrix. Normalization is carried out using a LOWESS (Locally-weighted Regression) method on the background-subtracted data. The normalization is to remove system related variations, such as sample amount variations, different labeling dyes, and signal gain differences of scanners so that biological variations can be faithfully revealed [B. M. Bolstad, R. A. Irizarry, M. Astrandand T. P. Speed, (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias, Bioinformatics, 19 (2), 185-193]. A transcript to be listed as detectable must meets at least two conditions: signal intensity higher than 3×(background standard deviation) and spot CV < 0.5. CV is calculated by (standard deviation)/(signal intensity). When repeating probes are present on an array, a transcript is listed as detectable only if the signals from at least 50% of the repeating probes are above detection level. t-Test is performed between “control” and “test” sample groups. T-values are calculated for each miRNA, and p-values are computed from the theoretical t-distribution. miRNAs with p-values below a critical p-value (typically 0.01) are selected for cluster analysis. The clustering is done using hierarchical method and is performed with average linkage and Euclidean distance metric. All data processes, except clustering plot, are carried out using in-house developed computer programs. The clustering plot is generated using TIGR MeV (Multiple Experimental Viewer) software from The Institute for Genomic Research.
