Stable reference genes for expression studies in breast muscle of normal and white striping-affected chickens

The normalization with proper reference genes is a crucial step to obtain accurate mRNA expression levels in quantitative PCR (qPCR) studies. Therefore, in this study, 10 reference candidate genes were evaluated to determine their stability in normal pectoralis major muscle of broilers and those counterparts affected with White Striping (WS) myopathy at 42 days age. Four different tools were used for ranking the most stable genes: GeNorm, NormFinder, BestKeeper and Comparative Ct (ΔCt), and a general ranking was performed using the RankAggreg tool to select the best reference genes among all tools. From the 10 genes evaluated in the breast muscle of broilers, 8 were amplified. Most of the algorithms/tools indicated the same two genes, RPL30 and RPL5, as the most stable in the broilers breast muscle. In addition, there was agreement among the tools for the least stable genes: MRPS27, GAPDH and RPLP1 in the broilers breast muscle. Therefore, it is interesting to note that even with different tools for evaluating gene expression, there was consensus on the most and least stable genes. These results indicate that the Ribosomal protein L30 (RPL30) and Ribosomal protein L5 (RPL5) can be recommended for accurate normalization in qPCR studies with chicken pectoralis major muscle affected with White Striping and other myopathies.

     

Selection and validation of reference genes for quantitative gene expression analyses in various tissues and seeds at different developmental stages in <Emphasis Type="Italic">Bixa orellana</Emphasis> L.

Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana, coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, ΔCt method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA, for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.     

Evaluation of housekeeping genes as references for quantitative real-time PCR analysis of European eel,Anguilla anguilla

Eels are important aquaculture species for which an increasing number of reference genes are being identified and applied. In this study, five housekeeping genes [RPL7 (ribosomal protein L7), 18 S (18 S ribosomal RNA), EF1A (elongation factor 1α), ACTB (β-actin) and GAPDH (glyceraldehyde-3-phosphate dehydrogenase)] were chosen to evaluate their reliability as reference genes for quantitative real-time PCR (qPCR) for the study of Anguilla anguilla. The expression of the selected genes in different eel tissues was determined using qPCR at different growth stages or upon challenge by Anguillid herpesvirus (AngHV), and the expression levels of these genes were then compared and evaluated using the geNorm and NormFinder algorithms. Then, RefFinder was used to comprehensively rank the examined housekeeping genes. Interestingly, the expression of the evaluated housekeeping genes exhibited tissue-dependent and treatment-dependent variations. In different growth periods A. anguilla tissues, the most stable genes were the following: ACTB in mucus; 18 S in skin and kidney; RPL7 in muscle, gill, intestine and brain; EF1A in heart and liver; and GAPDH in spleen. In contrast, in AngHV-challenged A. anguilla tissues, the most stable genes were the following: 18 S in mucus; RPL7 in skin, gill, heart, spleen, kidney and intestine; EF1A in muscle and liver; and ACTB in brain. Further comparison analysis indicated that the expression of RPL7 and EF1A was stable in multiple A. anguilla tissues in different growth periods and in eels challenged by AngHV. Nonetheless, the expression level of GAPDH in eel tissues was lower, and it was unstable in several tissues. These results indicated that the selection of reference genes for qPCR analysis in A. anguilla should be made in accordance with experimental parameters, and both RPL7 and EF1A could be used as reference genes for qPCR study of A. anguilla at different growth stages or upon challenge by AngHV. The reference genes identified in this study could improve the accuracy of qPCR data and facilitate further studies aimed at understanding the biology of eels.     

Normalizing genes for real-time polymerase chain reaction in epithelial and nonepithelial cells of mouse small intestine

Gene expression studies in intestinal epithelial and stromal cells are a common tool for investigating the mechanisms by which the homeostasis of the small intestine is regulated under normal and pathological conditions. Quantitative real-time PCR (qPCR) is a sensitive and highly reproducible method of gene expression analysis, with expression levels quantified by normalization against reference genes in most cases. However, the lack of suitable reference genes for epithelial cells with different differentiation states and nonepithelial tissue cells has limited the application of qPCR in gene expression studies of small intestinal samples. In this study, 13 housekeeping genes, ACTB, B2M, GAPDH, GUSB, HPRT1, HMBS, HSP90AB1, RPL13A, RPS29, RPLP0,PPIA, TBP, and TUBA1, were analyzed to determine their applicability for isolated crypt cells, villus cells, deepithelialized mucosa, and whole mucosa of the mouse small intestine. Using geNorm and NormFinder software, GUSB and TBP were identified as the most stably expressed genes, whereas the expressions of the commonly used reference genes GAPDH, B2M, and ACTB, and ribosomal protein genes RPL13A, RPS29, and RPLP0 were relatively unstable. Thus, this study demonstrates that GUSB and TBP are the optimal reference genes for the normalization of gene expression in the mouse small intestine.     

RNA-Seq is not required to determine stable reference genes for qPCR normalization

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, however, we demonstrate that the statistical approach to determine the best reference genes from commonly used conventional candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using conventional reference genes render the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.     

Evaluation of reference genes for quantitative real-time PCR in the brain,pituitary, and gonads of songbirds

Quantitative real-time PCR (qPCR) is becoming a popular tool for the quantification of gene expression in the brain and endocrine tissues of songbirds. Accurate analysis of qPCR data relies on the selection of appropriate reference genes for normalization, yet few papers on songbirds contain evidence of reference gene validation. Here, we evaluated the expression of ten potential reference genes (18S, ACTB, GAPDH, HMBS, HPRT, PPIA, RPL4, RPL32, TFRC, and UBC) in brain, pituitary, ovary, and testis in two species of songbirds: zebra finch and white-throated sparrow. We used two algorithms, geNorm and NormFinder, to assess the stability of these reference genes in our samples. We found that the suitability of some of the most popular reference genes for target gene normalization in mammals, such as 18S, depended highly on tissue type. Thus, they are not the best choices for brain and gonad in these songbirds. In contrast, we identified alternative genes, such as HPRT, RPL4 and PPIA, that were highly stable in brain, pituitary, and gonad in these species. Our results suggest that the validation of reference genes in mammals does not necessarily extrapolate to other taxonomic groups. For researchers wishing to identify and evaluate suitable reference genes for qPCR in songbirds, our results should serve as a starting point and should help increase the power and utility of songbird models in behavioral neuroendocrinology.     

Bt毒素诱导下小菜蛾实时定量PCR 内参基因的筛选

【目的】筛选出Bt毒素诱导后的小菜蛾Plutella xylostella (L.)的实时定量PCR最适内参基因。【方法】选取核糖体18S rRNA (18S rRNA)、 肌动蛋白（ACTB）、 延伸因子（EF1）、3-磷酸甘油醛脱氢酶（GAPDH）、 核糖体蛋白L32 (RPL32)、 核糖体蛋白S13 （RPS13）、 核糖体蛋白S20 （RPS20）和β-微管蛋白(TUB)基因作为候选内参基因, 以geNorm、 Normfinder和BestKeeper软件分析这8个基因在Bt毒素诱导后的小菜蛾不同品系中肠组织中的表达稳定性。并应用筛选出来的内参基因分析小菜蛾氨肽酶2（aminopeptidase N2, APN2）基因的表达水平。【结果】geNorm软件以RPS13和EF1为最稳定内参基因, NormFinder和BestKeeper软件均以RPS13和RPL32为最稳定基因。使用3种不同内参基因分析Bt毒素诱导后的小菜蛾Bt抗性和敏感品系中ANP2表达水平时, 新的内参基因EF1和传统内参基因RPL32表现了良好的稳定性, 二者作为标准化因子, ANP2表达量结果基本一致, 而使用18S rRNA作为内参基因, 却导致部分表达量分析结果有所误差。【结论】筛选出PRS13,RPL32和EF1可以作为小菜蛾某些试验条件下的内参基因, 对小菜蛾基因表达研究奠定了一定基础, 也对其他昆虫内参基因的筛选具有参考价值。     

Validation of housekeeping genes for gene expression studies in an ice alga <Emphasis Type="Italic">Chlamydomonas</Emphasis> during freezing acclimation

Antarctic ice alga Chlamydomonas sp. ICE-L can endure extreme low temperature and high salinity stress under freezing conditions. To elucidate the molecular acclimation mechanisms using gene expression analysis, the expression stabilities of ten housekeeping genes of Chlamydomonas sp. ICE-L during freezing stress were analyzed. Some discrepancies were detected in the ranking of the candidate reference genes between geNorm and NormFinder programs, but there was substantial agreement between the groups of genes with the most and the least stable expression. RPL19 was ranked as the best candidate reference genes. Pairwise variation (V) analysis indicated the combination of two reference genes was sufficient for qRT-PCR data normalization under the experimental conditions. Considering the co-regulation between RPL19 and RPL32 (the most stable gene pairs given by geNorm program), we propose that the mean data rendered by RPL19 and GAPDH (the most stable gene pairs given by NormFinder program) be used to normalize gene expression values in Chlamydomonas sp. ICE-L more accurately. The example of FAD3 gene expression calculation demonstrated the importance of selecting an appropriate category and number of reference genes to achieve an accurate and reliable normalization of gene expression during freeze acclimation in Chlamydomonas sp. ICE-L.     

The Use of Laser Microdissection in the Identification of Suitable Reference Genes for Normalization of Quantitative Real-Time PCR in Human FFPE Epithelial Ovarian Tissue Samples

Quantitative real-time PCR (qPCR) is a powerful and reproducible method of gene expression analysis in which expression levels are quantified by normalization against reference genes. Therefore, to investigate the potential biomarkers and therapeutic targets for epithelial ovarian cancer by qPCR, it is critical to identify stable reference genes. In this study, twelve housekeeping genes (ACTB, GAPDH, 18S rRNA, GUSB, PPIA, PBGD, PUM1, TBP, HRPT1, RPLP0, RPL13A, and B2M) were analyzed in 50 ovarian samples from normal, benign, borderline, and malignant tissues. For reliable results, laser microdissection (LMD), an effective technique used to prepare homogeneous starting material, was utilized to precisely excise target tissues or cells. One-way analysis of variance (ANOVA) and nonparametric (Kruskal-Wallis) tests were used to compare the expression differences. NormFinder and geNorm software were employed to further validate the suitability and stability of the candidate genes. Results showed that epithelial cells occupied a small percentage of the normal ovary indeed. The expression of ACTB, PPIA, RPL13A, RPLP0, and TBP were stable independent of the disease progression. In addition, NormFinder and geNorm identified the most stable combination (ACTB, PPIA, RPLP0, and TBP) and the relatively unstable reference gene GAPDH from the twelve commonly used housekeeping genes. Our results highlight the use of homogeneous ovarian tissues and multiple-reference normalization strategy, e.g. the combination of ACTB, PPIA, RPLP0, and TBP, for qPCR in epithelial ovarian tissues, whereas GAPDH, the most commonly used reference gene, is not recommended, especially as a single reference gene.     

Stably Expressed Housekeeping Genes across Developmental Stages in the Two-Spotted Spider Mite,Tetranychus urticae

Quantitative real-time PCR (qRT-PCR) is a reliable and reproducible technique for measuring mRNA expression. To facilitate gene expression studies and obtain more accurate qRT-PCR analysis, normalization relative to stable housekeeping genes is mandatory. In this study, ten housekeeping genes, including beta-actin (Actin) , elongation factor 1 α (EF1A) , glyceralde hyde-3-phosphate dehydrogenase (GAPDH) , ribosomal protein L13 (RPL13) , ribosomal protein 49 (RP49) , α-tubulin (Tubulin) , vacuolar-type H+-ATPase (v-ATPase) , succinate dehydrogenase subunit A (SDHA) , 28S ribosomal RNA (28S) , and 18S ribosomal RNA (18S) from the two-spotted spider mite, Tetranychus urticae, were selected as the candidate reference genes. Four algorithms, geNorm, Normfinder, BestKeeper, and the ΔC_t method, were used to evaluate the performance of these candidates as endogenous controls across different developmental stages. In addition, RefFinder, which integrates the above-mentioned software tools, provided the overall ranking of the stability/suitability of these candidate reference genes. Among them, PRL13 and v-ATPase were the two most stable housekeeping genes across different developmental stages. This work is the first step toward establishing a standardized qRT-PCR analysis in T. urticae following the MIQE guideline. With the recent release of the T. urticae genome, results from this study provide a critical piece for the subsequent genomics and functional genomics research in this emerging model system.