Normalization Of Real-time RT-PCR Data Research Articles

Identification of genes for normalization of real-time RT-PCR data in placental tissues from intrahepatic cholestasis of pregnancy

The selection of suitable reference genes is crucial for proper interpretation of RT-qPCR data. To date, a systematic screening for reference genes in placental tissues from intrahepatic cholestasis of pregnancy (ICP) is missing. Eighteen candidate reference genes were investigated to determine their applicability by descriptive statistics and published algorithms. HPRT1, YWHAZ and PUM1 were found to be the most stable genes and could be used for normalization in gene expression study of placentas from ICP. The combination of HPRT1 and YWHAZ is sufficient and the use of all three genes should be recommended for an improved reliability of normalization.

Per-unit-living tissue normalization of real-time RT-PCR data in ischemic rat hearts

In studies of gene expression in acute ischemic heart tissue, internal reference genes need to show stable expression per-unit-living tissue to hinder dead cells from biasing real-time RT-PCR data. Until now, this important issue has not been appropriately investigated. We hypothesized that the expression of seven internal reference genes would show stable per-unit-living tissue expression in Langendorff-perfused rat hearts subjected to ischemia-reperfusion. This was found for cyclophilin A, GAPDH, RPL-32, and PolR2A mRNA, with GAPDH showing the highest degree of stability (R = 0.11), suggesting unchanged rates of mRNA transcription in live cells and complete degradation of mRNA from dead cells. The infarct size-dependent degradation of GAPDH was further supported by a close correlation between changes in GAPDH mRNA and changes in RNA quality measured as RNA integrity number (R = 0.90, P < 0.05). In contrast, β-actin and 18S rRNA showed stable expression per-unit-weight tissue and a positive correlation with infarct size (R = 0.61 and R = 0.77, P < 0.05 for both analyses). The amount of total RNA extracted per-unit-weight tissue did not differ between groups despite wide variation in infarct size (7.1-50.1%). When β-actin expression was assessed using four different normalization strategies, GAPDH and geNorm provided appropriate per-unit-living expression, while 18S and total RNA resulted in marked underestimations. In studies of ischemic tissues, we recommend using geometric averaging of carefully selected reference genes for normalization of real-time RT-PCR data. A marked shift in the mRNA/rRNA ratio renders rRNA as useless for normalization purposes.

Validation of reference genes for normalization of real‐time quantitative RT‐PCR data in traumatic brain injury

Careful validation of reference genes used for the normalization of real-time RT-PCR data is required to obtain accurate results regarding gene expression. We evaluated the stability of seven commonly used reference genes in the cerebral cortex and hippocampus of rats 3 days following traumatic brain injury (TBI). HPRT, SDHA, and GUSB were found to be the most stable reference genes in the cerebral cortex, whereas B2MG, TBP, and GAPDH were the most stable in the hippocampus. The use of three reference genes was determined to be the optimal number for accurate normalization of data. To illustrate this point, when our gene of interest, substance P (SP), was normalized against the three most stable reference genes in both brain areas, we found no significant difference between injured and uninjured rats at the 3-day time point. However, when our SP data were normalized to each reference gene individually, SP mRNA level was highly variable depending on the reference gene chosen. The results of the present study highlight the importance of validating reference genes to be used for real-time RT-PCR analysis. The use of the most stable reference genes presented here will allow more accurate normalization of gene expression data in TBI.

Identification of genes for normalization of real-time RT-PCR data in breast carcinomas

BackgroundQuantitative real-time RT-PCR (RT-qPCR) has become a valuable molecular technique in basic and translational biomedical research, and is emerging as an equally valuable clinical tool. Correlation of inter-sample values requires data normalization, which can be accomplished by various means, the most common of which is normalization to internal, stably expressed, reference genes. Recently, such traditionally utilized reference genes as GAPDH and B2M have been found to be regulated in various circumstances in different tissues, emphasizing the need to identify genes independent of factors influencing the tissue, and that are stably expressed within the experimental milieu. In this study, we identified genes for normalization of RT-qPCR data for invasive breast cancer (IBC), with special emphasis on estrogen receptor positive (ER+) IBC, but also examined their applicability to ER- IBC, normal breast tissue and breast cancer cell lines.MethodsThe reference genes investigated by qRT-PCR were RPLP0, TBP, PUM1, ACTB, GUS-B, ABL1, GAPDH and B2M. Biopsies of 18 surgically-excised tissue specimens (11 ER+ IBCs, 4 ER- IBCs, 3 normal breast tissues) and 3 ER+ cell lines were examined and the data analyzed by descriptive statistics, geNorm and NormFinder. In addition, the expression of selected reference genes in laser capture microdissected ER+ IBC cells were compared with that of whole-tissue.ResultsA group of 3 genes, TBP, RPLP0 and PUM1, were identified for both the combined group of human tissue samples (ER+ and ER- IBC and normal breast tissue) and for the invasive cancer samples (ER+ and ER- IBC) by GeNorm, where NormFinder consistently identified PUM1 at the single best gene for all sample combinations.ConclusionThe reference genes of choice when performing RT-qPCR on normal and malignant breast specimens should be either the collected group of 3 genes (TBP, RPLP0 and PUM1) employed as an average, or PUM1 as a single gene.

Development of a new set of reference genes for normalization of real-time RT-PCR data of porcine backfat and longissimus dorsi muscle, and evaluation with PPARGC1A

BackgroundAn essential part of using real-time RT-PCR is that expression results have to be normalized before any conclusions can be drawn. This can be done by using one or multiple, validated reference genes, depending on the desired accuracy of the results. In the pig however, very little information is available on the expression stability of reference genes. The aim of this study was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in porcine backfat and longissimus dorsi muscle, both representing an economically important part of a pig's carcass. Because of its multiple functions in fat metabolism and muscle fibre type composition, peroxisome proliferative activated receptor γ coactivator 1α (PPARGC1A) is a very interesting candidate gene for meat quality, and was an ideal gene to evaluate our developed set of reference genes for normalization of mRNA expression data of both tissue types.ResultsThe mRNA expression stability of 10 reference genes was determined. The expression of RPL13A and SDHA appeared to be highly unstable. After normalization to the geometric mean of the three most stably expressed reference genes (ACTB, TBP and TOP2B), the results not only showed that the mRNA expression of PPARGC1A was significantly higher in each of the longissimus dorsi muscle samples than in backfat (P < 0.05), but also that the expression was significantly higher in the most cranial of the three muscle samples (P < 0.05).ConclusionThis study provides a new set of reference genes (ACTB, TBP and TOP2B) suitable for normalization of real-time RT-PCR data of backfat and longissimus dorsi muscle in the pig. The obtained PPARGC1A expression results, after application of this set of reference genes, are a first step in unravelling the PPARGC1A expression pattern in the pig and provide a basis for possible selection towards improved meat quality while maintaining a lean carcass.