茶树实时荧光定量PCR分析中内参基因的选择

选择合适的内参基因是提高实时荧光定量PCR分析(qRT-PCR)准确性的先决条件。该文以茶树(Camellia sinensis) 芽、叶、幼根、嫩茎、花瓣、种子和愈伤组织为材料, 应用实时荧光定量PCR技术, 分析了18S rRNA、GAPDH、β-actin和α-tubulin 4个常用内参基因在茶树不同器官组织中的表达情况。经GeNorm和NormFinder软件分析发现, 当利用荧光定量PCR分析比较茶树不同器官组织中的基因表达差异时, 可选择β-actin作为校正内参基因; 而比较不同成熟度的叶片和愈伤组织时, 可以选择GAPDH作为校正内参基因。     

鳜鱼基因表达转录分析中的内参选择比较

目前基因表达的转录分析多采用单一或多个看家基因作为内参来校正目的基因的表达量。该实验以鳜鱼6个不同组织和5个不同胚胎发育阶段为研究对象,应用实时荧光定量PCR技术,观察了GAPDH、β-actin和18S rRNA三个看家基因mRNA水平的表达情况。geNorm统计分析表明,胚胎发育阶段β-actin表达最为稳定;不同的组织样品间,GAPDH表达最为稳定;而18S rRNA 的表达在不同的发育阶段不稳定。当利用多基因作为内参时,使用两个最稳定表达的看家基因即可对目的基因的表达进行准确校正。该结果证实了基因表达转录分析中内参基因选择的必要性,同时为鳜鱼等鱼类基因表达分析时内参基因的选择提供有价值的参考     

岩白菜实时荧光定量PCR分析的内参基因的筛选

本研究为筛选在岩白菜中稳定表达的内参基因,以用于岩白菜实时荧光定量PCR研究,以岩白菜的幼叶、成熟叶、叶柄、根、一年生根状茎和二年生根状茎为材料,采用实时荧光定量PCR技术比较了GAPDH、18S rRNA、β-actin、TUA、UBQ5和TUB等6个候选内参基因的表达情况,并经Ge Norm、Norm Finder和Best Keeper等3种软件分析,分析表明6个候选内参基因在岩白菜不同器官中的表达情况存在差异,其中GAPDH和18S rRNA的表达都较为稳定,可作为岩白菜实时荧光定量PCR分析的内参基因。     

草鱼MYH mRNA表达量分析中采用的内参基因稳定性比较

本研究分别以β-actin、18S rRNA和GAPDH为内参基因,采用实时荧光定量PCR对草鱼早期发育时期肌球蛋白重链(myosin heavy light,MYH)基因的mRNA表达量进行分析,并比较不同内参基因对MYH基因mRNA表达水平检测结果的准确性.研究结果表明,以β-actin和GAPDH作为内参,MYH基因mRNA表达水平完全一致,其表达量从原肠到仔鱼阶段逐次递增,仔鱼与原肠期阶段相比表达量差异显著;当采用18S rRNA作为内参时,MYH基因mRNA在发育阶段的表达量呈不稳定状态.因此,β-actin和GAPDH均可作为内参基因,用于草鱼早期发育中MYH基因mRNA的相对定量研究:而18S rRNA作为内参时,可能会对检测结果造成偏差.本研究不仅准确的揭示了草鱼MYH基因mRNA的表达特征,并且为荧光定量PCR技术在鱼类基因表达研究方面提供了有价值的参考.     

RNA质量对内参基因选择和qRT-PCR结果评价的影响

目的:研究RNA质量对内参基因选择和实时定量PCR(qRT-PCR)分析肿瘤坏死因子α(TNFα)诱导基因表达结果评价的影响。方法:用TNFα刺激体外培养的小鼠血管内皮细胞,采用qRT-PCR技术,以2种常用的管家基因β-actin和GAPDH为内参,检测细胞间黏附分子1(ICAM-1)基因的表达,探讨RNA纯度对TNFα下游基因表达检测结果的影响。结果:当提取的总RNA纯度很高(D260nm/D230nm2.0)时,以β-actin和GAPDH为内参基因检测ICAM-1基因表达的结果相近;当总RNA可能被盐及小分子污染(D260nm/D230nm2.0)时,以β-actin为内参基因检测的ICAM-1基因相对表达量显著高于以GAPDH为内参所得结果。结论:RNA质量显著影响荧光定量PCR对基因表达的检测结果,因此在RNA质量较低时应选择2个或以上内参基因进行校正,以减少实验结果误差,得到准确结果。     

光处理下粘虫头部组织定量PCR分析中内参基因的筛选

[目的]筛选不同光处理下粘虫Mythimna separata稳定表达的内参基因,为基因定量研究提供基础.[方法]以粘虫头部组织为材料,选取18s rRNA、EF-1α、β-actin、GAPDH和AK5种候选内参基因进行实时荧光定量PCR(qRT-PCR)分析,然后通过△Ct法,BestKeeper、GeNorrn、Normfinder和RefFinder软件对候选内参基因的稳定性进行分析;利用GeNorm软件进行基因配对差异分析,以判断内参基因的最适组合.[结果]5种候选内参基因的Ct值都处于15-28之间.4种软件对5个候选基因稳定性的分析结果存在一定差异.综合分析各种软件的分析结果,推荐粘虫成虫不同光处理条件下采用AK和GAPDH作为内参基因.[结论]根据特定试验体系选择合适的内参基因对于qRT-PCR定量结果的准确定和可靠性具有重要意义.本研究对后续粘虫在不同光处理条件下目标基因的准确定量具有重要意义.     

翘嘴鳜per1 mRNA表达量分析中采用的内参基因稳定性比较

为筛选生物钟核心基因per1表达定量中的相对稳定性最好的内参基因,本研究取翘嘴鳜成鱼心脏、肝脏、肾脏、脑、红肌、白肌、肠、眼和脾等九个组织为研究对象,选取GAPDH、18S rRNA、β-actin、rps29、RPL13a、B2M和EF1a为内参基因,采用实时荧光定量PCR(qRT-PCR)对per1基因mRNA表达水平进行检测分析。研究结果表明18S rRNA和GAPDH的平均稳定值M最低,相对表达量最稳定。以18S rRNA和GAPDH为内参基因时分析发现per1基因表达量在肝脏中最高。本研究为在鱼类per1 mRNA表达检测过程中选用稳定的内参基因提供了实验和理论参考。     

糙皮侧耳热胁迫背景下RT-qPCR内参基因的筛选

通过文献报道和对糙皮侧耳基因组进行搜索,得到14个候选基因。以40℃热胁迫不同时间（0, 1,2, 4, 8, 12 h）的菌丝作为材料,通过反转录得到的候选基因片段,进行实时荧光定量PCR筛选,使用geNorm、NormFinder、BestKeeper 3种软件对结果进行分析,筛选得到稳定的内参基因β肌动蛋白（β-actin）、假定蛋白（sar1）。此外,选取2种热应激反应基因Hsp9、Hsp90作为靶基因,分别以筛选得到的稳定、不稳定基因以及多个内参基因作为内参进行分析,结果显示选用多个内参基因时能够缩小不同基因作为内参导致的结果差异。     

柑橘大实蝇内参基因的评估

【目的】柑橘大实蝇Bactrocera minax (Enderlein)是一种危害严重的柑橘害虫。本研究旨在筛选柑橘大实蝇在特定条件下体内稳定表达的内参基因, 以确保使用实时荧光定量PCR分析目标基因表达的可靠性。【方法】选择10种候选内参基因用于进行实时荧光定量PCR（qRT-PCR）, 利用5种软件对柑橘大实蝇在不同虫态下（低龄幼虫、3龄幼虫、1日龄蛹、80日龄蛹、160日龄蛹、雄成虫、雌成虫）以及成虫不同部位（成虫头、胸、腹、整体）中候选内参基因的Ct值进行分析, 明确其表达的稳定性。【结果】在柑橘大实蝇不同虫态和成虫不同部位, 10种候选内参基因的Ct值都处于15~30之间, 各基因Ct值的不同表明各基因的表达量存在差异。 综合分析各种软件对内参基因稳定性的排名, 结合geNorm软件对最佳内参基因数量的分析结果, 推荐在不同虫态下采用UBQ, GAPDH和GST作为内参基因, 在不同成虫部位中采用TUB, GAPDH和GST作为内参基因。【结论】为了获取可信的目标基因表达分析结果, 建议根据不同条件选择使用不同的内参基因组合。本研究结果有利于进一步研究柑橘大实蝇在特定条件下的目标基因表达。     

皱环球盖菇实时荧光定量PCR内参基因的筛选

本研究以皱环球盖菇Stropharia rugosoannulata不同发育时期(菌丝期、原基期、幼菇期、小菇期、成熟期)、不同组织部位(菌盖、菌柄、菌褶)和不同颜色菌盖(红色、黄色、白色)为试验材料,选择10个内参基因(ACT、GAPDH、TEF、RPL4、PGI、PGM、RPB2、β-TUB、α-TUB、UBQ)并设计跨内含子的引物,采用实时荧光定量PCR(RT-qPCR)技术进行扩增,利用geNorm、NormFinder、BestKeeper和ΔCt算法进行表达稳定性分析以及综合评价算法ReFinder进行加权评比,最终筛选适宜各类样本的内参基因。根据内参基因稳定性的最终排名,最适宜作为不同颜色菌盖内参基因的组合是UBQ和GAPDH,最不适宜的是ACT、PGI和TEF;最适宜作为子实体不同组织部位内参基因的组合是UBQ和RPB2,最不适宜的是ACT、RPL4和TEF;最适宜作为不同发育时期内参基因的组合是ACT和RPB2,最不适宜的是GAPDH、α-TUB和β-TUB。     

五龄飞蝗不同发育时间实时定量PCR内参基因的筛选

【目的】筛选5龄飞蝗不同发育时间的最适内参基因,为相关研究提供基础数据。【方法】本文选取β-肌动蛋白(β-actin)、延长因子(EF-1α)、3-磷酸甘油醛脱氢酶(GAPDH)、核糖体蛋白49(RP49)、α-微管蛋白(α-Tubulin)和18S核糖体RNA(18S rRNA)基因作为候选内参基因,运用实时定量PCR(qPCR)方法研究各基因在5龄飞蝗不同发育时间的相对表达量,用geNorm与Normfmder软件分析这6个基因表达稳定性。【结果】geNorm分析结果显示6个内参基因表达稳定度M值顺序为:β-actin(0.3720)>RP49(0.3750)>α-Tubulin(0.4030)>18S rRNA(0.4270)>EF-1α(0.4970)>GAPDH(0.6040)。M值越小表示基因表达稳定度越高,同时geNorm软件以标准化因子配对差异值(Pairwise variations)0.15默认为取舍值,由于V2/3=0.098<0.15,所以最适内参基因数目为2个。运用NormFinder软件也得出相似的结果。【结论】β-actin与RP49为5龄飞蝗不同发育时间的最适内参基因。     

A Panel of Stably Expressed Reference Genes for Real-Time qPCR Gene Expression Studies of Mallards (Anas platyrhynchos)

Determining which reference genes have the highest stability, and are therefore appropriate for normalising data, is a crucial step in the design of real-time quantitative PCR (qPCR) gene expression studies. This is particularly warranted in non-model and ecologically important species for which appropriate reference genes are lacking, such as the mallard—a key reservoir of many diseases with relevance for human and livestock health. Previous studies assessing gene expression changes as a consequence of infection in mallards have nearly universally used β-actin and/or GAPDH as reference genes without confirming their suitability as normalisers. The use of reference genes at random, without regard for stability of expression across treatment groups, can result in erroneous interpretation of data. Here, eleven putative reference genes for use in gene expression studies of the mallard were evaluated, across six different tissues, using a low pathogenic avian influenza A virus infection model. Tissue type influenced the selection of reference genes, whereby different genes were stable in blood, spleen, lung, gastrointestinal tract and colon. β-actin and GAPDH generally displayed low stability and are therefore inappropriate reference genes in many cases. The use of different algorithms (GeNorm and NormFinder) affected stability rankings, but for both algorithms it was possible to find a combination of two stable reference genes with which to normalise qPCR data in mallards. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies in ducks. The fact that nearly all previous studies of the influence of pathogen infection on mallard gene expression have used a single, non-validated reference gene is problematic. The toolkit of putative reference genes provided here offers a solid foundation for future studies of gene expression in mallards and other waterfowl.     

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.     

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.