Microarray analysis of gene regulation under iron restriction have been studied in A. pleuropneumoniae, Pasteurella multocida, Haemophilus influenza, Mannheimia haemolytica, and Haemophilus parasuis, respectively [ 26- 29, 36].
Aside from the 3Amut LCLs that we have included in our analysis, only two previous microarrays studying EBNA3 gene regulation have been published.
We have used microarrays to study gene regulation by the three yeast zinc finger proteins Mig1, Mig2 and Mig3.
Compared to microarray which provides limited gene regulation information, RNA-seq offers a comprehensive picture of the transcriptome.
Analysis of gene regulation by microarray analysis revealed a large number of genes that were both up- and down-regulated (>3-fold) after HIF-1α-PPN expression for either 1 day or 3 days (GEO reference GPL7119).
We then performed microarray analysis to visualize differential gene regulation before vs. after induction.
In order to gain further insight into gene regulation, a microarray analysis was performed in H358 cells that had been treated with TCDD and or -B[ a]P-7,8-dihydrodiol.
Accordingly, this system can be adopted to analyze co-regulation in microarray gene expression databases, such as AtGenExpress [ 48] and Genevestigator [ 49].
For 65% of the genes, including Cryαa Cryγf, Cryβa1, Cryβb2, Mmp12, Tgfbi, Mfng, Col1a1, Bcl2a1, Plat, Vcam, α-Sma, and Cdh2, fold differences were higher according to qRT-PCR, indicating that microarray can underestimate the extent of gene regulation compared to qRT-PCR, while for the rest of the genes fold differences were of comparable magnitude.
Future versions of GPMiner will include detailed information about gene regulation such as microarray gene-expression profiles.
