A meta-analysis of kidney microarray datasets: investigation of cytokine gene detection and correlation with rt-PCR and detection thresholds

Abstract

Background: Microarrays provide a means to simultaneously examine the gene expression of the entire transcriptome in a single sample. Many studies have highlighted the need for novel software and statistical approaches to assess the measured gene expression. Less attention has been directed toward whether genes considered undetectable by microarray can be detected by other strategies or whether these genes can provide accurate gene expression determinations. In the kidney this is a concern for genes such as cytokines which dramatically influence the immune response but are often considered low abundance genes produced by a small number of cells.

Toll-like receptors-related genes in kidney transplant patients with chronic allograft nephropathy and acute rejection

“…Some studies reported that is necessary after microarray analysis to confirm with real time PCR, however recent studies compared these two techniques concluded that for genes expressed by microarray analysis the changes in gene expression observed by microarray and real time PCR had excellent correlation. However in samples undetectable or detectable below 50% by microarray in some cases is detectable by real time PCR because is the more sensitive platform [26,28].…”

Differential Ly6C Expression after Renal Ischemia-Reperfusion Identifies Unique Macrophage Populations

“…One key piece of evidence supporting a role in fibrosis is the common gene signature identified between the Ly6C low population and numerous genomic studies linked to fibrotic diseases including kidney transplant patients that have interstitial fibrosis. 47, 48 Additionally, several genes are directly linked to fibrosis. SPARC regulates the expression of secreted extracellular matrix proteins to mediate fibrosis 49,50 while Timp2 inhibits extracellular matrix turnover by matrix metalloproteinases (MMPs) leading to matrix accumulation.…”

Identification of a common molecular pathway in hypertensive renal damage

“…Gene-expression data from renal allografts with subclinical fibrosis (n ¼ 8) and without (n ¼ 7) were obtained from the Gene Expression Omnibus database (accession number E-GEOD-7392) [9]. The allograft data were analysed using the same pipeline as the rat data; however, the dataset on the human kidney in ageing was used and compared from the published data it had been previously adjusted to correlate with increasing age [10].…”