A Novel Algorithm for Transcriptome Analysis 1 2

1 A growing body of evidence implicates the oocyte as a key regulator of ovarian 2 folliculogenesis and early embryonic development. We have screened bovine cDNA microarrays 3 (containing ESTs representing > 15,000 unique genes) with Cy3 and Cy5 labeled cDNA derived 4 from bovine oocyte samples collected at two different stages of meiotic maturation (germinal 5 vesicle versus metaphase II; n = 3 samples per group). Here, we present a novel data analysis 6 approach that uses all available information from above experiments to obtain and index the 7 transcriptome of bovine oocytes and changes in transcriptome composition in response to 8 meiotic maturation. Signal intensities (Fg) for all house-keeping genes were omitted prior to 9 analysis. A local threshold for gene expression was computed as background intensity (Bg) plus 10 2 times the standard deviation of background and foreground signals. Within each array, data 11 were normalized using the LOWESS procedure. Subsequently, a two-stage mixed model was 12 fitted to remove systematic variations. In the first stage, the response was the LOWESS 13 normalized Fg with treatment as a fixed effect. In stage two, the residuals from stage one were 14 analyzed in a gene-specific model that included treatment group and spots nested within patch 15 and array. A test for the difference between Least Squares Means (LSM) for the treatment effect 16 was performed. A False Discovery Rate (FDR) adjustment on the p-values for the difference was 17 carried out. This novel algorithm was compared with approaches that ignore the FDR and the 18 threshold described herein and stark differences obtained. 19 20