实时荧光定量PCR分析中毛果杨内参基因的筛选和验证

实时荧光定量PCR(qRT-PCR)技术具有高灵敏性、高保真性和高特异性, 被广泛应用于基因表达的分析。在数据处理过程中, 选用稳定表达的基因作为内参基因对准确分析实验结果非常关键。以毛果杨(Populus trichocarpa)的不同组织以及锌胁迫下的组培苗为材料, 使用荧光定量PCR方法分析了TUA8、TUB6、ubiquitin、GAPDH、actin、18S rRNA和EF1α 7个看家基因的表达情况。通过geNorm、NormFinder和BestKeeper 3个程序的综合分析, 发现actin、ubiquitin、EF1α和18S rRNA的稳定性较好, 可用作毛果杨基因表达研究的内参基因; 而TUB6在不同组织中稳定性最差; GAPDH在锌胁迫下的组织中稳定性最差, 因此不适宜作为内参基因。毛果杨NAC基因的表达分析, 进一步验证了上述结果。该研究对采用qRT-PCR方法分析毛果杨基因表达过程中内参基因的选择具有指导作用, 同时对揭示NAC基因的功能也有一定的意义。     

Determination and Validation of Reference Gene Stability for qPCR Analysis in Polysaccharide Hydrogel-Based 3D Chondrocytes and Mesenchymal Stem Cell Cultural Models

Gene expression study is widely used to obtain information of the cell activities and phenotypes. To quantify gene expression, measurement of the mRNA copy number is commonly done by quantitative RT-PCR (RT-qPCR). However, proper reference gene is needed for different tissues to normalize the expression level of different genes accurately. In this study, reference gene determination was done for three-dimensional (3D) artificial tissue constructs in hydrogel. Porcine synovium-derived mesenchymal stem cells (SMSCs) and rabbit chondrocytes were cultured in both alginate and agarose hydrogels to set up four different 3D culture systems to form the artificial tissue constructs. The gene expression levels of candidate genes were determined by RT-qPCR and then analyzed by geNorm, Bestkeeper, and Normfinder. For porcine SMSCs, PPIA, and TBP were selected for tissue in alginate scaffold whereas HPRT and TBP were selected for the agarose scaffold system. On the other hand, HPRT, PPIA, and RPL18 were the stable reference genes for rabbit chondrocytes in alginate scaffold while TBP, RPL5, and RPL18 were selected for rabbit chondrocytes in agarose scaffold. This study has further indicated that suitable reference genes are different for each tissue and study purpose. The reference genes are expressed in different stability when a scaffold of different material is used.     

黄梁木实时荧光定量PCR分析中内参基因的选择

为筛选黄梁木(Neolamarckia cadamba)实时定量PCR最佳内参基因, 该研究以黄梁木的根、芽、叶、花、果、皮及形成层为材料, 利用RT-qPCR技术对ACT、CAC、CYP和EF1α等21个管家基因家族43个候选内参基因进行表达量分析, 并利用geNorm、NormFinder和BestKeeper软件进行内参基因稳定性分析。geNorm的分析结果显示, UPL基因的稳定性最高(M=0.443), UBQ基因的稳定性最低(M=2.859); NormFinder的分析结果显示, UPL基因的稳定性最高(E=0.223), UBQ基因的稳定性最低(M=4.759); BestKeeper分析显示, UPL基因的标准偏差(SD=0.513)最低。研究结果表明, UPL基因作为内参基因稳定性最高, UBQ基因的稳定性最低。因此可以选择UPL基因作为黄梁木不同组织中RT-qPCR定量分析的内参基因。     

Selection of Reference Genes for Normalizing Gene Expression During Seed Priming and Germination Using qPCR in Zea mays and Spinacia oleracea

Quantitative real-time RT-PCR (qPCR) has been widely used to investigate gene expression during seed germination, a process involving seed transition from dry/physiologically inactive to hydrated/active state. This transition may result in altered expression of many housekeeping genes (HKGs), conventionally used as internal controls, thereby posing a challenge about selection of HKGs in such scenarios. The objectives of this study included identifying valid reference genes for seed priming and germination studies, both of which involve the transition of seed hydration status, and assessing whether or not findings derived from the “seed model” used in this study would also be applicable to other plant species. Eight commonly used HKGs were evaluated in maize seeds during hydropriming and germination. Using Bestkeeper, geNorm, and NormFinder, we provided a rank of stability for these HKGs. Actdf, UBQ, βtub, 18S, Act, and GAPDH were adjudged as valid internal controls by geNorm and NormFinder. Under the second objective, we conducted a case study with spinach seeds collected during osmopriming and germination. Our results indicate that the conclusions derived from maize were applicable to spinach as well, in that 18S exhibited greater expression stability than GAPDH in osmoprimed and germinated seeds; this held true even under stress conditions. While both of these genes were rejected by BestKeeper, we found that 18S exhibited stable expression when “dry” and “hydrated” seeds were analyzed as separate data sets. Although this approach precludes the comparison between “hydrated” and “dry” seeds, it still provides effective comparison among samples of same hydration status.     

Identification and Validation of Reference Genes for qPCR Detection of Serum microRNAs in Colorectal Adenocarcinoma Patients

Serum microRNAs (miRNAs) have become a highlighted research hotspot, especially for their great potential as a novel promising non-invasive biomarker in cancer diagnosis. The most frequently used approach for serum miRNAs detection is quantitative real time polymerase chain reaction (qPCR). In order to obtain reliable qPCR data of miRNAs expression, the use of reference genes as endogenous control is undoubtly necessary. However, no systematic evaluation and validation of reference genes for normalizing qPCR analysis of serum miRNAs has been reported in colorectal adenocarcinoma. We firstly profiled pooled serum of colorectal adenocarcinoma, colorectal adenoma and healthy controls and selected a list of 13 miRNAs as candidate reference genes. U6 snRNA (U6) and above-mentioned 13 miRNAs were included in further confirmation by qPCR. As a result, 5 miRNAs (miR-151a-3p, miR-4446-3p, miR-221-3p, miR-93-5p and miR-3184-3p) were not detected in all samples and 2 miRNAs (miR-197-3p and miR-26a-5p) were relatively low with median Cq more than 35, and were excluded from further stability analysis. Then variable stability of other 6 miRNAs (miR-103b, miR-484, miR-16-5p, miR-3615, miR-18a-3p and miR-191-5p) and U6 were evaluated using two algorithms: geNorm and NormFinder which both identified miR-191-5p as the most stably expressed reference gene and selected miR-191-5p and U6 as the most stable pair of reference genes. After validating in an independent large cohorts and selecting miR-92a-3p as target miRNA to evaluate the effect of reference gene, we propose that combination of miR-191-5p and U6 could be used as reference genes for serum microRNAs qPCR data in colorectal adenocarcinoma, colorectal adenoma and healthy controls.     

Comparative Validation of Conventional and RNA-Seq Data-Derived Reference Genes for qPCR Expression Studies of Colletotrichum kahawae

Colletotrichum kahawae is an emergent fungal pathogen causing severe epidemics of Coffee Berry Disease on Arabica coffee crops in Africa. Currently, the molecular mechanisms underlying the Coffea arabica—C. kahawae interaction are still poorly understood, as well as the differences in pathogen aggressiveness, which makes the development of functional studies for this pathosystem a crucial step. Quantitative real time PCR (qPCR) has been one of the most promising approaches to perform gene expression analyses. However, proper data normalization with suitable reference genes is an absolute requirement. In this study, a set of 8 candidate reference genes were selected based on two different approaches (literature and Illumina RNA-seq datasets) to assess the best normalization factor for qPCR expression analysis of C. kahawae samples. The gene expression stability of candidate reference genes was evaluated for four isolates of C. kahawae bearing different aggressiveness patterns (Ang29, Ang67, Zim12 and Que2), at different stages of fungal development and key time points of the plant-fungus interaction process. Gene expression stability was assessed using the pairwise method incorporated in geNorm and the model-based method used by NormFinder software. For C. arabica—C. kahawae interaction samples, the best normalization factor included the combination of PP1, Act and ck34620 genes, while for C. kahawae samples the combination of PP1, Act and ck20430 revealed to be the most appropriate choice. These results suggest that RNA-seq analyses can provide alternative sources of reference genes in addition to classical reference genes. The analysis of expression profiles of bifunctional catalase-peroxidase (cat2) and trihydroxynaphthalene reductase (thr1) genes further enabled the validation of the selected reference genes. This study provides, for the first time, the tools required to conduct accurate qPCR studies in C. kahawae considering its aggressiveness pattern, developmental stage and host interaction.     

实时荧光定量PCR相对定量法检测循环miRNA的内参选择

microRNA(miRNA)是一类内源性非编码微小RNA,在调控细胞增殖、分化、凋亡等方面发挥重要作用。研究发现,miRNA能够稳定存在于细胞外液,被称为循环miRNA。在多种疾病状态下循环miRNA表达谱改变,具有成为非创伤性新型生物标志物的潜能。实时荧光定量PCR(RT-qPCR)是检测miRNA表达变化的确证实验,其中内参的选择关系到相对定量结果是否真实可靠。我们简要综述国内外实验室常用的RT-qPCR内参及其特点。     

基因表达研究中内参基因的选择与应用

管家基因是一类无组织特异性的,在物种的所有组织细胞中都表达的基因,被广泛用作内参基因来检测目标基因在不同的组织器官、一定的发育阶段或胁迫的环境条件下的表达规律变化。这些管家基因并不是在所有生理条件下都能作为理想内参基因稳定表达。在基因表达转录分析中,大多数普遍使用的内参基因已不能满足准确定量的要求。基于统计学分析软件,如geNorm、BestKeeper和NormFinder三种分析软件,可以筛选出稳定性较好的内参基因。本文综述了内参基因的选择条件、方法及应用。     

Validation of kinetics similarity in qPCR

Quantitative real-time PCR (qPCR) is the method of choice for specific and sensitive quantification of nucleic acids. However, data validation is still a major issue, partially due to the complex effect of PCR inhibition on the results. If undetected PCR inhibition may severely impair the accuracy and sensitivity of results. PCR inhibition is addressed by prevention, detection and correction of PCR results. Recently, a new family of computational methods for the detection of PCR inhibition called kinetics outlier detection (KOD) emerged. KOD methods are based on comparison of one or a few kinetic parameters describing a test reaction to those describing a set of reference reactions. Modern KOD can detect PCR inhibition reflected by shift of the amplification curve by merely half a cycle with specificity and sensitivity >90%. Based solely on data analysis, these tools complement measures to improve and control pre-analytics. KOD methods do not require labor and materials, do not affect the reaction accuracy and sensitivity and they can be automated for fast and reliable quantification. This review describes the background of KOD methods, their principles, assumptions, strengths and limitations. Finally, the review provides recommendations how to use KOD and how to evaluate its performance.     

Toward Enhanced MIQE Compliance: Reference Residual Normalization of qPCR Gene Expression Data

Normalization of fluorescence-based quantitative real-time PCR (qPCR) data varies across quantitative gene expression studies, despite its integral role in accurate data quantification and interpretation. Identification of suitable reference genes plays an essential role in accurate qPCR normalization, as it ensures that uncorrected gene expression data reflect normalized data. The reference residual normalization (RRN) method presented here is a modified approach to conventional 2^−ΔΔCtqPCR normalization that increases mathematical transparency and incorporates statistical assessment of reference gene stability. RRN improves mathematical transparency through the use of sample-specific reference residuals (RR_i) that are generated from the mean C_t of one or more reference gene(s) that are unaffected by treatment. To determine stability of putative reference genes, RRN uses ANOVA to assess the effect of treatment on expression and subsequent equivalence-threshold testing to establish the minimum permitted resolution. Step-by-step instructions and comprehensive examples that demonstrate the influence of reference gene stability on target gene normalization and interpretation are provided. Through mathematical transparency and statistical rigor, RRN promotes compliance with Minimum Information for Quantitative Experiments and, in so doing, provides increased confidence in qPCR data analysis and interpretation.     

Identification of Novel Reference Genes Using Multiplatform Expression Data and Their Validation for Quantitative Gene Expression Analysis

Normalization of mRNA levels using endogenous reference genes (ERGs) is critical for an accurate comparison of gene expression between different samples. Despite the popularity of traditional ERGs (tERGs) such as GAPDH and ACTB, their expression variability in different tissues or disease status has been reported. Here, we first selected candidate housekeeping genes (HKGs) using human gene expression data from different platforms including EST, SAGE, and microarray, and 13 novel ERGs (nERGs) (ARL8B, CTBP1, CUL1, DIMT1L, FBXW2, GPBP1, LUC7L2, OAZ1, PAPOLA, SPG21, TRIM27, UBQLN1, ZNF207) were further identified from these HKGs. The mean coefficient variation (CV) values of nERGs were significantly lower than those of tERGs and the expression level of most nERGs was relatively lower than high expressing tERGs in all dataset. The higher expression stability and lower expression levels of most nERGs were validated in 108 human samples including formalin-fixed paraffin-embedded (FFPE) tissues, frozen tissues and cell lines, through quantitative real-time RT-PCR (qRT-PCR). Furthermore, the optimal number of nERGs required for accurate normalization was as few as two, while four genes were required when using tERGs in FFPE tissues. Most nERGs identified in this study should be better reference genes than tERGs, based on their higher expression stability and fewer numbers needed for normalization when multiple ERGs are required.     

Reference Gene Selection for Real-Time Quantitative PCR Analysis of the Mouse Uterus in the Peri-Implantation Period

The study of uterine gene expression patterns is valuable for understanding the biological and molecular mechanisms that occur during embryo implantation. Real-time quantitative RT-PCR (qRT-PCR) is an extremely sensitive technique that allows for the precise quantification of mRNA abundance; however, selecting stable reference genes suitable for the normalization of qRT-PCR data is required to avoid the misinterpretation of experimental results and erroneous analyses. This study employs several mouse models, including an early pregnancy, a pseudopregnancy, a delayed implantation and activation, an artificial decidualization and a hormonal treatment model; ten candidate reference genes (PPIA, RPLP0, HPRT1, GAPDH, ACTB, TBP, B2M, 18S, UBC and TUBA) that are found in uterine tissues were assessed for their suitability as internal controls for relative qRT-PCR quantification. GeNorm^PLUS, NormFinder, and BestKeeper were used to evaluate these candidate reference genes, and all of these methods identified RPLP0 and GAPDH as the most stable candidates and B2M and 18S as the least stable candidates. However, when the different models were analyzed separately, the reference genes exhibited some variation in their expression levels.     

Reference Gene Selection for Gene Expression Studies Using Quantitative Real-Time PCR Normalization in Atropa belladonna

Quantitative PCR (qPCR) is a powerful tool for measuring gene expression levels. Accurate and reproducible results are dependent on the correct choice of reference genes for data normalization. Atropa belladonna is a commercial plant species from which pharmaceutical tropane alkaloids are extracted. In this study, eight candidate reference genes, namely 18S ribosomal RNA (18S), actin (ACT), cyclophilin (CYC), elongation factor 1α (EF-1α), β-fructosidase (FRU), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), and beta-tubulin (TUB), were selected and their expression stabilities studied to determine their suitability for normalizing gene expression in A. belladonna. The expression stabilities of these genes were analyzed in the root, stem, and leaf under cold, heat, NaCl, UV-B, methyl jasmonate, salicylic acid, and abscisic acid treatments using geNorm, NormFinder, and BestKeeper. The statistical algorithms indicated that PGK was a reliable gene for normalizing gene expression under most of the experimental conditions. The pairwise value analysis showed that two genes were sufficient for proper expression normalization, except when analyzing gene expression in heat-treated roots. However, the choice of the second reference gene depended on specific conditions. Finally, the relative expression level of the PMT gene of A. belladonna was detected to validate the selection of PGK a reliable reference gene. In summary, our results should guide the selection of appropriate reference genes for gene expression studies in A. belladonna under different organs and abiotic stress conditions.