Although Cyp11a1 and Hsd3b1 expressions were found to be reduced in siRNA1-transfected MLTCs by real-time RT-PCR and microarray analyses respectively, such reduced activities were not reproduced in siRNA2-transfected MLTCs.
One of the limitations of applying microarray analyses to such context is the amount of tissue material needed [ 10].
Future microarray analyses utilizing additional controls such as cells grown at a lower concentration of Penicillin G, and cells that are enzymatically stripped of their cell wall might be useful to better pinpoint L-form specific responses.
In microarray analyses, we found two such candidate genes in common with human and murine CRR cells.
Like RNA-seq, microarray analyses suffer from limitations, such as measurement noise, biases due to systematic variations between experimental conditions or sample handling, labelling biases and preferential amplification due to the variable hybridization strength of the probe target pairs (56 58).
Thus, for microarray analyses involving complex tissues such as brain, low fold changes in gene expression may indicate large fold changes in a subset of cells or cells in a particular region of the tissue and should not be overlooked.
Current approaches for genome-wise functional analyses, such as microarray and RNA interference studies, rely on the specificity of oligonucleotide sequences to selectively target cellular transcripts.
However, this approach is much more cost- and time-effective, as performing large scale analyses, such as microarray or sequencing studies, could allow all the genes and the entire genome of an organism to be examined in a single experiment.
The occurrence of missing values in microarray data disadvantageously influences downstream analyses, such as discovery of differentially expressed genes [ 11, 12], construction of gene regulatory networks [ 13, 14], supervised classification of clinical samples [ 15], gene cluster analysis [ 10, 16], and biomarker detection.
This reference database for genes co-expressed with IL-8 can be cross-referenced with other large scale expression analyses, such as microarray experiments, to help decipher the regulation network and the functions of IL-8 and IL-8 co-expressed genes.
