Evaluation of suitable reference genes for gene expression studies in porcine alveolar macrophages in response to LPS and LTA

Abstract

BackgroundTo obtain reliable quantitative real-time PCR data, normalization relative to stable housekeeping genes (HKGs) is required. However, in practice, expression levels of 'typical' housekeeping genes have been found to vary between tissues and under different experimental conditions. To date, validation studies of reference genes in pigs are relatively rare and have never been performed in porcine alveolar macrophages (AMs). In this study, expression stability of putative housekeeping genes were identified in the porcine AMs in response to the stimulation with two pathogen-associated molecular patterns (PAMPs) lipopolysaccharide (LPS) and lipoteichoic acid (LTA). Three different algorithms (geNorm, Normfinder and BestKeeper) were applied to assess the stability of HKGs.ResultsThe mRNA expression stability of nine commonly used reference genes (B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP and YWHAZ) was determined by qRT-PCR in AMs that were stimulated by LPS and LTA in vitro. mRNA expression levels of all genes were found to be affected by the type of stimulation and duration of the stimulation (P < 0.0001). geNorm software revealed that SDHA, B2M and RPL4 showed a high expression stability in the irrespective to the stimulation group, while SDHA, YWHAZ and RPL4 showed high stability in non-stimulated control group. In all cases, GAPDH showed the least stability in geNorm. NormFinder revealed that SDHA was the most stable gene in all the groups. Moreover, geNorm software suggested that the geometric mean of the three most stable genes would be the suitable combination for accurate normalization of gene expression study.ConclusionsThere was discrepancy in the ranking order of reference genes obtained by different analysing algorithms. In conclusion, the geometric mean of the SDHA, YWHAZ and RPL4 seemed to be the most appropriate combination of HKGs for accurate normalization of gene expression data in porcine AMs without knowing the type of bacterial pathogenic status of the animals.

Identification and validation of reference genes to study the gene expression in Gluconacetobacter diazotrophicus grown in different carbon sources using RT-qPCR

“…The use of reference genes which have a stable expression between the compared groups is crucial for gene expression investigation (Nieto et al, 2009;Cinar et al, 2012). Previous studies have shown that different reference genes can modify the outcome and conclusions of a specific study (Glare et al, 2002;Dheda et al, 2004;Kriegova et al, 2008).…”

Selection of Suitable Reference Genes for Normalization of Quantitative Real-Time PCR in Cartilage Tissue Injury and Repair in Rabbits

“…The NF is calculated from two or more genes with the variable V as the pairwise variation (V n /V n +1) between two sequential normalization factors (NF n and NF n +1). We applied the default threshold (0.15) as a cut-off [7]. If the calculated NF is less than 0.15, additional reference genes are not necessary.…”

“…However, more and more evidence suggests that expression of some commonly accepted reference genes, such as glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) and beta actin ( ACTB ), are affected by experimental and clinical conditions; therefore, they may not always be suitable controls for normalization [7–10]. Leading qPCR investigators have suggested that reference genes must be validated for each experimental situation to acquire meaningful data [11,12].…”

ADSL, AMPD1, and ATIC Expression Levels in Muscle and Their Correlations with Muscle Inosine Monophosphate Content in Dapulian and Hybridized Pig Species

“…Eleven genes (ACTB, GAPDH, B2M, TBP, RPL4, TOP2B, HMBS, HPRT1, SDHA, YWHAZ, and PPIA) were selected (Table 1) for stability analysis [24] [25] [26] [27]. The specific primers of ADSL, AMPD1, and ATIC were designed using Primer Premier 5.0 software ( Table 2) …”