2. Materials and Methods 60
2.7 Microarray 66
2.7.1 Three-prime expression microarrays (Drosophila Genome
2.0 Array)
Targets were prepared using the One-Cycle Eukaryotic Target labelling Assay protocol and kit (PN 900431) from Affymetrix were used in this experiment. 2ug RNA was used in line with the manufacture’s protocol. Four replicate samples were used when preparing targets from tubules of Drosophila Simulans,
Drosophila Pseudoodbscura and Drosophila melanogaster. The outline of the
assay is shown in Figure 2-2. The RNA quality, quantities and integrity were checked by Nanodrop and Agilent bioanalyzer (chapter 2.5.2). 2ug total RNA,
PolyA control and T7 oligo (dT) primer mixture were denatured at 700C for 10
mins to open the RNA second structure. First strand synthesis was performed using superscript II. Second strand synthesis was performed DNA ligase and DNA polymerase and T4 DNA polymerase was used to polish the end of dsDNA. The dsDNA was then cleaned up by the DNA clean up kit. The Biotin-labelled
ribonucleotides and T7 RNA polymerase were used in ‘In Vitro Transcription’ to make the biotin-labelled complementary RNA (cRNA). The quality of cRNA was then determined by Agilent 2100 Bioanalyzer.
Target Hybridization was performed by first fragmenting 10ug corrected cRNA. 200µl array target was made with control oligo B2 and 20x hybridization control. 130ul of the target was hybridized in Drosophila Genome 2.0 Array at 60rpm,
450C oven for 16-18 hours.
Fluidic Station Setup: Fluidic station 450 was set up by prime wash using the GeneChip Operating software (GCOS) in line with Affymetrix’s instruction to operate the whole process. The samples and project information was entered and saved as an experiment file.
Figure 2-2 Overview of the GeneChip 3' IVT Express Labelling Assay
The process of 3’end expression microarrays includes one cycle (2µg RNA) and two cycles (100ng RNA) reverse transcription, in vitro transcription and labelling procedure. Picture is taken from
www.affymetrix.com.
Probe Array Wash and Staining: SAPE, Antibody and SAPE stain were performed using fluidic station in line with Affymetrix’s instruction using the Midi_euk2v3 protocol in this process.
Probe Array Scan: The array was scanned by Affymetrix Scanner 3000 7G. The cell files were created as in raw data format for further analysis by other software such as Partek.
2.7.2 Drosophila tiling microarrays
GeneChip Whole Transcript (WT) Double-Strand Target Assays protocol and kit (PN 900652) were used in this experiment. The outline of this procedure is shown in FIgure2-3. Four replicates of Drosophila whole flies, testes, heads and tubules were processed. The quality of total RNA of all the samples was checked on Nanodrop ND-1000 (Chapter 2.2.5.2) and Agilent 2100 Bioanalyzer (Chapter 2.2.5.2). The experiment was started with 7µg good quality total RNA. First strand cDNA synthesis used random primer and superscript II, second strand synthesis used DNA polymerase I, dUTP was incorporated in both strands for later recognition by the fragment enzyme. The double-stranded DNA was
cleaned up by GeneChip Sample Clean up Module (PN 900371). The 7.5µg dsDNA was then fragmented by using enzyme UDG and APE to recognize the dUTP in the dsDNA. The fragmented dsDNA was labelled by TdT for the end labelling
procedure (terminal labelling). The quality of the terminal labelling fragmented dsDNA can be checked by ‘gel shift assay’. The hybridization target was made by the labelled dsDNA, control oligoB2, herring sperm DNA and BSA. The Fluidic Setup, Wash and Stain, Scan was performed as in Section 2.7.1. The Tiling chips in this experiment were GeneChip Drosophila Tiling 2.0R Array.
Figure 2-3 GeneChip Whole Transcript Double-Stranded Target Assay Schematic
The process of tiling microarrays includes reverse transcription, fragmentation and end labelling producture. Picture is taken from www.affymetrix.com.
2.7.3 Genomic DNA Array
Invitrogen BioPrime® DNA Labelling System (Cat. No. 18094-011) was used to generate DNA target in this experiment. 500ng DNA was used; Random primers were annealed to the denatured DNA template and extended by Klenow
fragment in the presence of biotin-14-dCTP to produce sensitive biotinylated- DNA probes. The entire labelled genomic DNA with Control oligo B2, 20x
Hybridization control, BSA, Herring sperm to produce the hybridization cocktail. The hybridization, Fluidic Setup, Wash and Stain, Scan protocols were performed as in Section 2.7.1. The labelled DNA was hybridized to Drosophila Genome 2.0 Array.
2.7.4 Microarray data analysis
2.7.4.1 Normalization method
Three popular normalization methods applied to microarray are MAS5.0, RMA and GC-RMA. This can be referred to as low-level microarray analysis.
MAS 5.0 method. Li and Wong (2001) were the first to propose model-based expression measures. They observed a very strong probe effect in that PM-MM values, the need for non-linear normalization, and the advantages of using multi-array summaries for detection and removal of outliers (Li and Hung Wong, 2001; Li and Wong, 2001)(Li and Hung Wong, 2001; Li and Wong, 2001)(Li and Hung Wong, 2001; Li and Wong, 2001).
RMA (Robust Multiarray Average) normalization method. It is linear and performs the background correction, normalization across arrays, probe level intensity calculation and probe set summarization. The RMA method is notable for employing quantile normalization that forces the distributions of probe-level measurements to be equal across multiple arrays before median-polish probe-set summaries are calculated.
GC-RMA normalization method. A modification to RMA, GC-RMA performs the background correction by considering the GC contents. G/C in sequence leads to stronger hybridization because each G-C pair forms three hydrogen bonds
whereas each A-T pair forms two. GC-RMA uses the mismatch data that RMA ignores to model the effects of GC-content on nonspecific binding.
The differential gene expression using statistical hypothesis testing methods including analysis of variance (ANOVA) can be referred to as high-level
microarray analysis. The fundamental idea behind analysis of variance (ANOVA) is that, given an appropriate experimental design, variability in the quantity being measured (gene expression) can be partitioned into various identifiable sources. The assumed sources of variability will include the experimental factors, as well as random noise (Pavlidis, 2003).