Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies

Identification and validation of reference genes for RT-qPCR analysis in fetal rat pancreas

The choice of reference gene is crucial for quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) assay. To screen and determine the suitable reference genes in fetal rat pancreas, we selected eight candidate reference genes (Gapdh, Actb, Rn18 s, B2m, Rpl13a, Tbp, Ywhaz and Ubc), and evaluated the constancy of gene expression from fetal rat pancreases in non-pathological situation and prenatal dexamethasone exposure (PDE) model, using four algorithms: GeNorm, NormFinder, Bestkeeper and Comparative ΔCt method. In addition, the alteration of mRNA levels of pancreatic insulin was compared between control and PDE groups to validate the reliability of selected reference genes for data normalization of RT-qPCR. The comprehensive ranking of reference genes under physiological condition was as follow: Gapdh > Actb > Ywhaz > Ubc > Rn18s > Rpl13a > B2m > Tbp (female); Actb > Ywhaz > Gapdh > Ubc > B2m > Rpl13a > Rn18 s | Tbp (male). The top ranking reference genes were also stably expressed in PDE fetal pancreas. The best reference gene combinations are: Ywhaz+Actb for female and Ywhaz+Gapdh for male fetal rat pancreas, respectively. Compared with low ranking or single reference gene, the change trend of insulin mRNA normalized by the best reference gene combination between control and PDE groups was more significant and consistent with that of serum insulin level. In conclusion, our results provided the optimal combination of stable reference genes for RT-qPCR assay in pancreatic developmental toxicity study.

A functional genomic approach to identify reference genes for human pancreatic beta cell real-time quantitative RT-PCR analysis

Exposure of human pancreatic beta cells to pro-inflammatory cytokines or metabolic stressors is used to model events related to type 1 and type 2 diabetes, respectively. Quantitative real-time PCR is commonly used to quantify changes in gene expression. The selection of the most adequate reference gene(s) for gene expression normalization is an important pre-requisite to obtain accurate and reliable results. There are no universally applicable reference genes, and the human beta cell expression of commonly used reference genes can be altered by different stressors. Here we aimed to identify the most stably expressed genes in human beta cells to normalize quantitative real-time PCR gene expression.We used comprehensive RNA-sequencing data from the human pancreatic beta cell line EndoC-βH1, human islets exposed to cytokines or the free fatty acid palmitate in order to identify the most stably expressed genes. Genes were filtered based on their level of significance (adjusted P-value >0.05), fold-change (|fold-change| <1.5) and a coefficient of variation <10%. Candidate reference genes were validated by quantitative real-time PCR in independent samples.We identified a total of 264 genes stably expressed in EndoC-βH1 cells and human islets following cytokines - or palmitate-induced stress, displaying a low coefficient of variation. Validation by quantitative real-time PCR of the top five genes ARF1, CWC15, RAB7A, SIAH1 and VAPA corroborated their expression stability under most of the tested conditions. Further validation in independent samples indicated that the geometric mean of ACTB and VAPA expression can be used as a reliable normalizing factor in human beta cells.

HRT Atlas v1.0 database: redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets

Housekeeping (HK) genes are constitutively expressed genes that are required for the maintenance of basic cellular functions. Despite their importance in the calibration of gene expression, as well as the understanding of many genomic and evolutionary features, important discrepancies have been observed in studies that previously identified these genes. Here, we present Housekeeping and Reference Transcript Atlas (HRT Atlas v1.0, www.housekeeping.unicamp.br) a web-based database which addresses some of the previously observed limitations in the identification of these genes, and offers a more accurate database of human and mouse HK genes and transcripts. The database was generated by mining massive human and mouse RNA-seq data sets, including 11 281 and 507 high-quality RNA-seq samples from 52 human non-disease tissues/cells and 14 healthy tissues/cells of C57BL/6 wild type mouse, respectively. User can visualize the expression and download lists of 2158 human HK transcripts from 2176 HK genes and 3024 mouse HK transcripts from 3277 mouse HK genes. HRT Atlas also offers the most stable and suitable tissue selective candidate reference transcripts for normalization of qPCR experiments. Specific primers and predicted modifiers of gene expression for some of these HK transcripts are also proposed. HRT Atlas has also been integrated with a regulatory elements resource from Epiregio server.