scholarly journals Selection of reference genes for quantitative real-time PCR evaluation of chronic erythropoietin treatment effect on the SH-SY5Y and PC12 cells

2013 ◽  
Vol 11 (3) ◽  
pp. 348-357
Author(s):  
Klemen Španinger ◽  
Arthur Sytkowski ◽  
Nataša Debeljak
Keyword(s):  
Real Time ◽  
Pc12 Cells ◽  
Reference Gene ◽  
Reference Genes ◽  
Housekeeping Genes ◽  
Expression Stability ◽  
Normalization Gene ◽  
Erythropoietin Treatment ◽  
Control Plate ◽  
Selection Of

AbstractAbstract The quantitative real-time polymerase chain reaction (qPCR) is a sensitive technique for examining the influence of erythropoietin (Epo) on gene expression. A critical and fundamental step for data analysis is the selection of and normalization to the optimal reference gene(s). We identified appropriate reference gene(s) among 32 genes during chronic recombinant human Epo (rHuEpo) treatment of SH-SY5Y cells using TaqMan human Express Endogenous Control Plate. Expression stability of the selected reference gene (RPLP) was retested with qPCR, together with two commonly used reference genes (GAPDH, ACTB) and six genes of interest (EPOR, EPO, STAT5B, STAT5A, JUN, AKT). In PC12 cells, three commonly used reference genes (Gapdh, CycA and Ywhaz) and seven genes of interest (EpoR, Epo, Stat5b, Stat5a, Jun, Akt, Fos) were evaluated. For the evaluation of expression stability, geNorm, NormFinder and BestKeeper software were used. All three gave similar results. We demonstrated that among the housekeeping genes, RPLP in SH-SY5Y and CycA and Ywhaz in PC12 are the most stable genes. Additionally, we showed that normalization with GAPDH gave misleading results compared to normalization with geNorm. In conclusion, selection of the appropriate normalization gene(s) is crucial for correct interpretation of rHuEpo treatment results. Graphical abstract

scholarly journals Reference Gene Validation for Quantitative Real-time PCR Studies in Amphibian Kidney-derived A6 Epithelial Cells

2019 ◽  
Vol 47 (2) ◽  
pp. 63-70 ◽  
Author(s):  
Elin Verbrugghe ◽  
An Martel ◽  
Frank Pasmans
Keyword(s):  
Cell Line ◽  
Real Time ◽  
Reference Gene ◽  
Reference Genes ◽  
Tissue Sample ◽  
Housekeeping Genes ◽  
Optimal Number ◽  
Pairwise Variation ◽  
Expression Stability ◽  
Specific Tissue

Quantitative real-time polymerase chain reaction is a widely used technique that relies on reference genes for the normalisation of gene expression. These reference genes are constitutively expressed and must remain stable across all samples and treatments. Stability of housekeeping genes may vary and must be optimised for a specific tissue, sample or cell line. Here we present a study screening for possible reference gene candidates, eef1a1, rpl8, sub1.L, clta, H4 and odc1, in the Xenopus laevis (A6) kidney cell line. Quantification cycle results were analysed using geNorm to calculate the average expression stability and the coefficient of variation (CV) for each candidate reference gene. All of the tested genes met the guidelines for stable reference genes, namely an average expression stability of < 0.5 and a CV value of < 0.2, with eef1a1 > sub1.L > rpl8 > clta > odc1 > H4. By using pairwise variation analysis, the optimal number of reference targets was determined to be 2. As such, we report that the reference genes eef1a1 and sub1.L should be used to achieve optimal normalisation in A6 cells.

scholarly journals Reference Gene Selection for Quantitative Real-Time PCR of Mycelia fromLentinula edodesunder High-Temperature Stress

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xu Zhao ◽  
Huanling Yang ◽  
Mingjie Chen ◽  
Xiaoxia Song ◽  
Changxia Yu ◽  
...  
Keyword(s):  
High Temperature ◽  
Real Time ◽  
Temperature Stress ◽  
Reference Gene ◽  
Reference Genes ◽  
Candidate Reference Gene ◽  
Housekeeping Genes ◽  
High Temperature Stress ◽  
Stable Gene ◽  
Mrna Levels

Housekeeping genes are important for measuring the transcription expression of functional genes; 10 traditional reference genes,TUB, TUA, GADPH, EF1, 18S, GTP, ACT, UBI, UBC,andH2A, were tested for their adequacy inLentinula edodes(L. edodes). Using specific primers, mRNA levels of these candidate housekeeping genes were evaluated in mycelia ofL. edodes, which were treated with high-temperature stress at 37°C for 0, 4, 8, 12, 18, and 24 hours. After treatment, expression stability of candidate genes was evaluated using three statistical software programs: geNorm, NormFinder, and BestKeeper. According to geNorm,TUBhad the lowest M values inL. edodesstrains 18 and 18N44. Using NormFinder, the best candidate reference gene in strain 18 wasTUB(0.030), and the best candidate reference gene in strain 18N44 wasUBI(0.047). In BestKeeper analysis, the standard deviation (SD) values ofUBC,TUA,H2A,EF1,ACT,18S, andGTPin strain 18 and those ofGADPHandGTPin strain 18N44 were greater than 1; thus, these genes were disqualified as reference genes. Taken together, onlyUBIandTUBwere found to be desirable reference genes by BestKeeper software. Based on the results of three software analyses,TUBwas the most stable gene under all conditions and was verified as an appropriate reference gene for quantitative real-time polymerase chain reaction inL. edodesmycelia under high-temperature stress.

Selection of reference genes for quantitative real-time RT-PCR on gene expression in Golden Pompano (Trachinotus ovatus)

2017 ◽  
Vol 20 (3) ◽  
pp. 583-594 ◽  
Author(s):  
X.J. Chen ◽  
X.Q. Zhang ◽  
S. Huang ◽  
Z.J. Cao ◽  
Q.W. Qin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Real Time ◽  
Reference Genes ◽  
Housekeeping Genes ◽  
Poly I:C ◽  
Stable Gene ◽  
Trachinotus Ovatus ◽  
Golden Pompano ◽  
Normal Physiological Condition ◽  
Selection Of

Abstract Golden pompano (Trachinotus ovatus) is an important economically fish species. In this study, with an aim to identify reliable reference genes for quantitative real-time PCR (qRT-PCR) in golden pompano, we evaluated the expression stability of eight housekeeping genes in the presence and absence of poly I:C stimulation in eight tissues. The PCR data was analyzed by geNorm and NormFinder algorithms. The results showed that the expression of all the examined genes exhibited tissue-dependent variations. When under normal physiological condition, geNorm and NormFinder identified B2M and 18S as suitable genes. When studying gene expression under conditions of poly I:C stimulation, the selection of the internal controls should be selected on a tissue basis. At 12 h stimulation, geNorm ranked Actin/UBCE, Actin/B2M, UBCE/B2M, Actin/UBCE, RPL13/B2M, UBCE/GAPDH, B2M/RPL13, and UBCE/B2M, respectively, as the most stably expressed genes in liver, spleen, kidney, gill, intestine, heart, muscle, and brain. Comparable ranking orders were produced by NormFinder. Similar results were obtained at 48 h stimulation. Taken together, these results indicate that B2M and 18S are the most stable gene across tissue types under normal physiological conditions. However, during poly I:C stimulation, no single gene or single pair of genes in the examined set of housekeeping genes can serve as a universal reference across all tissue types. If one gene is preferred, B2M, B2M, UBCE, Actin, B2M/RPL13, B2M, B2M, and RPL13 may be used in spleen, kidney, liver, gill, intestine, brain, muscle, and heart of golden pompano, respectively.

scholarly journals Selection of Reference Genes for Quantitative Real-Time PCR in Chrysoperla nipponensis (Neuroptera: Chrysopidae) Under Tissues in Reproduction and Diapause

2020 ◽  
Vol 20 (4) ◽  
Author(s):  
Xiao Wang ◽  
Xue Kong ◽  
Shaoye Liu ◽  
Haiyi Huang ◽  
Zhenzhen Chen ◽  
...  
Keyword(s):  
Real Time ◽  
Reference Gene ◽  
Reference Genes ◽  
Fat Body ◽  
Model Organism ◽  
Reproductive Diapause ◽  
Genomics Research ◽  
Polymerase Chain ◽  
Selection Of ◽  
Polymerase Chain Reaction Data

Abstract Chrysoperla nipponensis (Okamoto), which has the unique diapause phenotype distinguishable from nondiapause adult, is an ideal model organism for studying the mechanism of reproductive diapause. However, there is no reliable and effective reference genes used for the reproductive diapause study of C. nipponensis. Therefore, in this study, we evaluated the expression stability of 10 candidate reference genes (Tub1, Arpc5, EF1a, 128up, RpS5, RpS26e, GAPDH, Arp3, Actin, α-Tub) in adults under diapause and nondiapause induction conditions using four statistical algorithms including GeNorm, NormFinder, Bestkeeper, and ∆CT method. Results showed that Arp3 and Tub1 were the most stable reference genes in all samples and in the adult tissues group. Arp3 and RpS5 were the most stable reference genes in the development degree group. α-Tub and EF1a were unstable reference genes under the conditions of this study. Meanwhile, to verify the reliability of the reference genes, we evaluated the relative expression levels of Vg and VgR in different treatments. Significant upregulation and downregulation in expression level of two genes in response to diapause termination and diapause fat body tissue was, respectively, observed when using Arp3 as the reference gene but not when using an unstable reference gene. The reference genes identified in this work provided not only the basis for future functional genomics research in diapause of C. nipponensis and will also identify reliable normalization factors for real-time quantitative real-time polymerase chain reaction data for other related insects.

scholarly journals The Selection of Reference Genes for Quantitative Real-Time PCR in the Ashidan Yak Mammary Gland During Lactation and Dry Period

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 943 ◽  
Author(s):  
Xiaoyun Wu ◽  
Xuelan Zhou ◽  
Xuezhi Ding ◽  
Min Chu ◽  
Chunnian Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mammary Gland ◽  
Real Time ◽  
Milk Yield ◽  
Reference Genes ◽  
Quantitative Polymerase Chain Reaction ◽  
Expression Stability ◽  
Dry Period ◽  
Relative Expression ◽  
Selection Of

Investigating the critical genes related to milk synthesis is essential for the improvement of the milk yield of the yak. Real-time quantitative polymerase chain reaction (RT-qPCR) is a reliable and widely used method to measure and evaluate gene expression levels. Selection of suitable reference genes is mandatory to acquire accurate normalization of gene expression results from RT-qPCR. To select the most stable reference genes for reliable normalization of mRNA expression by RT-qPCR in the mammary gland of the Ashidan yak, we selected 16 candidate reference genes and analyzed their expression stability at different physiological stages (lactation and dry period). The expression stability of the candidate reference genes was assessed using geNorm, NormFinder, BestKeeper, Delta Ct, and RefFinder methods. The results showed that the hydroxymethylbilane synthase gene (HMBS) and the tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide gene (YWHAZ) were the most stable genes across all treatment samples. The reliability of selected reference genes was validated by normalizing relative expression of the lactation-related 60S ribosomal protein L35 gene (RPL35). The relative expression of RPL35 varied considerably according to the different reference genes. This work provides valuable information to further promote research in the molecular mechanisms involved in lactation and mammary gland development and provides a foundation for the improvement of the milk yield and quality of the Ashidan yak.

scholarly journals The role and robustness of the Gini coefficient as an unbiased tool for the selection of Gini genes for normalising expression profiling data

2019 ◽  
Author(s):  
Marina Wright Muelas ◽  
Farah Mughal ◽  
Steve O’Hagan ◽  
Philip J. Day ◽  
Douglas B. Kell
Keyword(s):  
Cell Lines ◽  
Gini Coefficient ◽  
Expression Profiling ◽  
Reference Genes ◽  
Housekeeping Genes ◽  
Data Sets ◽  
Expression Stability ◽  
Expression Levels ◽  
Median Expression ◽  
Selection Of

AbstractWe recently introduced the Gini coefficient (GC) for assessing the expression variation of a particular gene in a dataset, as a means of selecting improved reference genes over the cohort (‘housekeeping genes’) typically used for normalisation in expression profiling studies. Those genes (transcripts) that we determined to be useable as reference genes differed greatly from previous suggestions based on hypothesis-driven approaches. A limitation of this initial study is that a single (albeit large) dataset was employed for both tissues and cell lines.We here extend this analysis to encompass seven other large datasets. Although their absolute values differ a little, the Gini values and median expression levels of the various genes are well correlated with each other between the various cell line datasets, implying that our original choice of the more ubiquitously expressed low-Gini-coefficient genes was indeed sound. In tissues, the Gini values and median expression levels of genes showed a greater variation, with the GC of genes changing with the number and types of tissues in the data sets. In all data sets, regardless of whether this was derived from tissues or cell lines, we also show that the GC is a robust measure of gene expression stability. Using the GC as a measure of expression stability we illustrate its utility to find tissue- and cell line-optimised housekeeping genes without any prior bias, that again include only a small number of previously reported housekeeping genes. We also independently confirmed this experimentally using RT-qPCR with 40 candidate GC genes in a panel of 10 cell lines. These were termed the Gini Genes.In many cases, the variation in the expression levels of classical reference genes is really quite huge (e.g. 44 fold for GAPDH in one data set), suggesting that the cure (of using them as normalising genes) may in some cases be worse than the disease (of not doing so). We recommend the present data-driven approach for the selection of reference genes by using the easy-to-calculate and robust GC.

scholarly journals The role and robustness of the Gini coefficient as an unbiased tool for the selection of Gini genes for normalising expression profiling data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Marina Wright Muelas ◽  
Farah Mughal ◽  
Steve O’Hagan ◽  
Philip J. Day ◽  
Douglas B. Kell
Keyword(s):  
Cell Lines ◽  
Gini Coefficient ◽  
Expression Profiling ◽  
Reference Genes ◽  
Housekeeping Genes ◽  
Data Sets ◽  
Expression Stability ◽  
Expression Levels ◽  
Median Expression ◽  
Selection Of

AbstractWe recently introduced the Gini coefficient (GC) for assessing the expression variation of a particular gene in a dataset, as a means of selecting improved reference genes over the cohort (‘housekeeping genes’) typically used for normalisation in expression profiling studies. Those genes (transcripts) that we determined to be useable as reference genes differed greatly from previous suggestions based on hypothesis-driven approaches. A limitation of this initial study is that a single (albeit large) dataset was employed for both tissues and cell lines. We here extend this analysis to encompass seven other large datasets. Although their absolute values differ a little, the Gini values and median expression levels of the various genes are well correlated with each other between the various cell line datasets, implying that our original choice of the more ubiquitously expressed low-Gini-coefficient genes was indeed sound. In tissues, the Gini values and median expression levels of genes showed a greater variation, with the GC of genes changing with the number and types of tissues in the data sets. In all data sets, regardless of whether this was derived from tissues or cell lines, we also show that the GC is a robust measure of gene expression stability. Using the GC as a measure of expression stability we illustrate its utility to find tissue- and cell line-optimised housekeeping genes without any prior bias, that again include only a small number of previously reported housekeeping genes. We also independently confirmed this experimentally using RT-qPCR with 40 candidate GC genes in a panel of 10 cell lines. These were termed the Gini Genes. In many cases, the variation in the expression levels of classical reference genes is really quite huge (e.g. 44 fold for GAPDH in one data set), suggesting that the cure (of using them as normalising genes) may in some cases be worse than the disease (of not doing so). We recommend the present data-driven approach for the selection of reference genes by using the easy-to-calculate and robust GC.

scholarly journals Selection of reference genes for quantitative real-time PCR analysis in halophytic plantRhizophora apiculata

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5226 ◽  
Author(s):  
Ankush Ashok Saddhe ◽  
Manali Ramakant Malvankar ◽  
Kundan Kumar
Keyword(s):  
Gene Expression ◽  
Salt Stress ◽  
Real Time ◽  
Reference Gene ◽  
Reference Genes ◽  
Candidate Reference Gene ◽  
Expression Level ◽  
Bisphosphate Carboxylase ◽  
Qrt Pcr ◽  
Selection Of

Rhizophora apiculatais a halophytic, small mangrove tree distributed along the coastal regions of the tropical and subtropical areas of the world. They are natural genetic reservoirs of salt adaptation genes and offer a unique system to explore adaptive mechanisms under salinity stress. However, there are no reliable studies available on selection and validation of reference genes for quantitative real-time polymerase chain reaction (qRT-PCR) inR. apiculataphysiological tissues and in salt stress conditions. The selection of appropriate candidate reference gene for normalization of qRT-PCR data is a crucial step towards relative analysis of gene expression. In the current study, seven genes such as elongation factor 1α (EF1α), Ubiquitin (UBQ), β-tubulin (β-TUB), Actin (ACT), Ribulose1,5-bisphosphate carboxylase/oxygenase (rbcL), Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and 18S rRNA (18S) were selected and analyzed for their expression stability. Physiological tissues such as leaf, root, stem, and flower along with salt stress leaf samples were used for selection of candidate reference genes. The high-quality expression data was obtained from biological replicates and further analyzed using five different programs such as geNorm, NormFinder, BestKeeper, Delta Ct and RefFinder. All algorithms comprehensively rankedEF1α followed byACTas the most stable candidate reference genes inR. apiculataphysiological tissues. Moreover, β-TUBand 18S were ranked as moderately stable candidate reference genes, while GAPDH andrbcLwere least stable reference genes. Under salt stress,EF1α was comprehensively recommended top-ranked candidate reference gene followed byACTand 18S. In order to validate the identified most stable candidate reference genes,EF1α,ACT, 18S andUBQwere used for relative gene expression level of sodium/proton antiporter (NHX) gene under salt stress. The expression level ofNHXvaried according to the internal control which showed the importance of selection of appropriate reference gene. Taken together, this is the first ever systematic attempt of selection and validation of reference gene for qRT-PCR inR. apiculataphysiological tissues and in salt stress. This study would promote gene expression profiling of salt stress tolerance related genes inR. apiculata.

scholarly journals Optimizations for identifying reference genes in bone and cartilage bioengineering

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fei Xiong ◽  
Xiangyun Cheng ◽  
Chao Zhang ◽  
Roland Manfred Klar ◽  
Tao He
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Adipose Tissue ◽  
Real Time ◽  
Reference Gene ◽  
Muscle Tissue ◽  
Reference Genes ◽  
Target Genes ◽  
The Stability ◽  
And Cartilage

Abstract Background Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) remains one of the best-established techniques to assess gene expression patterns. However, appropriate reference gene(s) selection remains a critical and challenging subject in which inappropriate reference gene selction can distort results leading to false interpretations. To date, mixed opinions still exist in how to choose the most optimal reference gene sets in accodrance to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guideline. Therefore, the purpose of this study was to investigate which schemes were the most feasible for the identification of reference genes in a bone and cartilage bioengineering experimental setting. In this study, rat bone mesenchymal stem cells (rBMSCs), skeletal muscle tissue and adipose tissue were utilized, undergoing either chondrogenic or osteogenic induction, to investigate the optimal reference gene set identification scheme that would subsequently ensure stable and accurate interpretation of gene expression in bone and cartilage bioengineering. Results The stability and pairwise variance of eight candidate reference genes were analyzed using geNorm. The V0.15- vs. Vmin-based normalization scheme in rBMSCs had no significant effect on the eventual normalization of target genes. In terms of the muscle tissue, the results of the correlation of NF values between the V0.15 and Vmin schemes and the variance of target genes expression levels generated by these two schemes showed that different schemes do indeed have a significant effect on the eventual normalization of target genes. Three selection schemes were adopted in terms of the adipose tissue, including the three optimal reference genes (Opt3), V0.20 and Vmin schemes, and the analysis of NF values with eventual normalization of target genes showed that the different selection schemes also have a significant effect on the eventual normalization of target genes. Conclusions Based on these results, the proposed cut-off value of Vn/n + 1 under 0.15, according to the geNorm algorithm, should be considered with caution. For cell only experiments, at least rBMSCs, a Vn/n + 1 under 0.15 is sufficient in RT-qPCR studies. However, when using certain tissue types such as skeletal muscle and adipose tissue the minimum Vn/n + 1 should be used instead as this provides a far superior mode of generating accurate gene expression results. We thus recommended that when the stability and variation of a candidate reference genes in a specific study is unclear the minimum Vn/n + 1 should always be used as this ensures the best and most accurate gene expression value is achieved during RT-qPCR assays.

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