IFN-I and interferon signature genes were reported to be elevated both at the mRNA level based on data from microarray analyses and even at the protein level in the serum of SLE patients [ 4, 37- 39].
The enormous amount of data generated by microarray analyses is a challenge even in small studies, easily summing up to several gigabyte of raw expression data.
Even though microarray analyses did not suggest transcriptional modulation as an early implicated mechanism, we first explored the impact of CGs on Mcl-1 mRNA expression levels by RT-PCR to further ascertain our results.
Even among the various microarray analyses performed from human cell lines, the differences between experiments are much greater than the similarities.
Although both RNAseq and microarray analyses measure the transcriptome, studies report different genes as DE using one method or the other, even when using the exact same samples [ 43– 43].
Work flow for microarray analyses.
Microarray analyses using the OsNAC6 overexpressors clarified the downstream genes, which included many stress-inducible genes.
Open image in new window Fig. 3 Microarray analyses of seawater samples.
Microarray analyses of rice tissues challenged with the Asian rice gall midge biotype 1 (GMB1).
We compared OsDREB1A, AP59, OsbZIP23, SNAC1, OsNAC5 and OsNAC6 downstream genes identified by microarray analyses.
