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     

qRT-PCR分析鳜鱼内参基因的筛选

选择合适的内参基因是提高实时荧光定量PCR分析(quantitative real-time polymerase chain reaction,qRT-PCR)准确性的首要条件。本实验采取鳜鱼8个不同胚胎发育阶段、5个胚后发育时期和8个成鱼组织为研究对象,应用qRT-PCR技术,分析了RPL13、RPL19、EF1a、RPL13a、B2M、hprt1和rps29七个内参基因的表达稳定情况。经GeNorm软件分析发现,B2M和RPL13a在鳜鱼成鱼不同组织中表达最稳定;在胚后不同时期中表达最稳定的是EF1a和RPL13a;EF1a和B2M是在不同胚胎发育阶段中表达最稳定的两个基因。根据内参基因标准化因子的配对差异分析V_(n/n+1),在鳜鱼不同组织和不同发育阶段中,均使用两个最稳定表达的内参基因即可达到准确校正的目的。因此,该实验结果为鳜鱼基因表达分析时内参基因的选择提供了参考。     

小鼠基因转录表达分析中内参基因的优选

目的 建立小鼠基因转录表达分析中内参基因的选择方法.方法 以C57BL/6J和C3H/HeJ两个品系3个不同组织及2个不同发育阶段为研究对象,应用反转录实时定量PCR技术,评价GAPDH(glyceraldehyde-3-phosphate dehydrogenase)、HPRTl(hypoxanthine phosphoribosyl transferase)、B2M(β2-microglobulin)、PPIA(peptidylprolyl isomerase A)、ACTB(Actin-beta)和18S rRNA(18S ribosomal RNA)等6个看家基因在下丘脑、垂体与卵巢中mRNA水平的表达稳定性.结果 GeNorm统计分析表明,GAPDH和HPRT1表达最为稳定,PPIA等次之,B2M在不同组织和发育阶段中都几乎无表达.结论 成功筛选到GAPDH和HPRT1两个稳定表达的看家基因,证实了小鼠基因表达转录分析中内参基因选择的必要性和可行性.     

内参基因在昆虫实时荧光定量PCR中的研究进展

作为一种高效的定量PCR技术,实时荧光定量PCR(qRT-PCR)因其灵敏度高、特异性强、定量准确等优点,已被广泛运用于昆虫基因表达和转录分析。然而,为了控制样本RNA在质量和逆转录效率上存在差异,必须筛选表达稳定的"看家基因"作为内参基因,对目的基因表达量进行校正和标准化。许多学者研究表明,昆虫种类和实验条件的不同,导致选择的内参基因也不尽相同。因此,本文综述了前人有关昆虫内参基因的研究及其稳定性评价,为其它昆虫内参基因的研究提供理论参考依据。     

松墨天牛化学感受组织荧光定量PCR内参基因的鉴定与筛选

【目的】本研究拟选择适合用于分析松墨天牛Monochamus alternatus化学感受组织中基因表达的内参基因。【方法】依据转录组测序结果进行内参基因鉴定,利用RT-q PCR技术分析内参基因在松墨天牛不同发育阶段和不同性别化学感受组织间的表达差异,并利用软件ge Norm,Norm Finder和Best Keeper比较其表达的稳定性。【结果】松墨天牛转录组中鉴定出9个候选内参基因(Actin,TUB,18S rRNA,RPS27A,RPS3,RPL10,AK,GAPDH和EF1A),其中后7个候选内参基因在松墨天牛中被首次鉴定,松墨天牛候选内参基因和其他昆虫相应基因的同源性很高。9个候选内参基因引物均具有良好的扩增效率,18S rRNA的表达水平最高,EF1A的表达水平最低;18S rRNA和Actin在不同样品间的表达水平差异最大,GAPDH和TUB表达水平在不同样品间差异最小。ge Norm和Norm Finder软件分析认为,GAPDH是最稳定的内参基因,TUB是较为稳定的内参基因,18S rRNA和Actin是最不稳定的内参基因;Best Keeper软件分析认为,GAPDH和TUB是合适的内参基因,18S rRNA和Actin是不适合的内参基因。最适合校正松墨天牛化学感受组织中基因表达数据的内参基因数量为2个,即GAPDH和TUB,并且这样的内参基因组合可以用于不同发育阶段和不同性别的不同化学感受组织。【结论】本研究结果为利用RT-q PCR技术准确分析松墨天牛和其他天牛基因包括化学感受组织基因相对表达量的内参基因选择提供了重要参考。     

梭梭qRT-PCR内参基因的筛选及稳定性分析

本研究旨在探明梭梭（Haloxylon ammodendron）在不同非生物胁迫下稳定表达的内参基因,为后续梭梭抗逆性相关基因功能研究奠定基础。研究采用实时定量聚合酶链式反应（qRT-PCR）技术从梭梭转录组数据库中检测了GAPDH、ef1-α、UBC、RPL32、ALB、50S-1721、50S-1063、RPⅡ、H3、PP2A、SOD、HSC70、TUA和TUB等14个候选内参基因在高温、干旱、盐、ABA和昼夜节律条件下的表达变化。利用geNorm、NormFinder、BestKeeper和RefFinder软件对梭梭候选内参基因的稳定性进行评价,最终筛选出合适的内参基因,并通过对梭梭磷酸烯醇丙酮酸羧化酶（phosphoenolpyruvate carboxylase, PEPC）基因表达分析,验证了不同内参基因对实验结果的影响。4种软件分析得到的最优内参基因存在差异,在RefFinder网站上综合排序分析表明,在ABA处理和昼夜节律下,ALB是最优内参基因,RPⅡ基因在干旱胁迫下表达最稳定,TUB和RPⅡ基因在盐胁迫下最适用,H3基因在高温胁迫下表达最为稳定。各种胁迫下最适宜的内参基因为ALB和RPL32。通过计算几何平均值,得到14个候选内参基因的综合稳定性排名,其中排名前两位的基因分别为SOD和RPL32。综上,RPL32和SOD可作为梭梭qRT-PCR标准化的内参基因。     

大灰象甲实时定量PCR内参基因的筛选

【目的】筛选出适合分析大灰象甲Sympiezomias velatus成虫不同组织中基因表达水平的内参基因。【方法】利用转录组测序技术获得大灰象甲管家基因序列作为候选内参基因,采用实时荧光定量PCR(qRT-PCR)技术分析候选基因在大灰象甲雌雄成虫触角、头、胸、腹和足中的表达量;并利用geNorm, NormFinder和BestKeeper软件及在线工具RefFinder评价候选基因的表达稳定性。以大灰象甲气味结合蛋白1(odorant bindng protein 1, OBP1)基因为目标基因验证候选基因在大灰象甲成虫不同组织中的表达稳定性。【结果】基于大灰象甲转录组数据首次鉴定得到β-肌动蛋白基因(ACT)、3-磷酸甘油醛脱氢酶基因(GAPDH)、18S核糖体RNA基因(18S rRNA)、60S核糖体蛋白L12基因(RPL12)、60S核糖体蛋白L32基因(RPL32)、40S核糖体蛋白S20基因(RPS20)、延伸因子2基因(EF2)、α-微管蛋白基因(TUA)和β-微管蛋白基因(TUB)共9个管家基因序列。geNorm分析结果显示,RPL12和RPS20是最稳定表达的内参基因,而BestKeeper和NormFinder分析结果显示最稳定表达的内参基因分别是TUA和TUB。综合各分析方法得出9个候选基因中TUB,TUA,RPS20和RPL12是最稳定表达的内参基因,而18S rRNA,ACT和GAPDH这3个广泛应用的内参基因则表现出最低的表达稳定性。最后以OBP1为目标基因对稳定性不同的4个候选基因进行稳定性验证,发现以TUB和RPL12为内参基因,OBP1在成虫不同组织之间的表达模式基本一致;而以RPL32为内参基因,表达模式与应用TUB作为内参基因时稍有不同,使用18S rRNA作为内参基因得到的OBP1表达模式则与应用TUB作为内参基因时的完全不一致。【结论】TUB,TUA,RPS20和RPL12可以作为分析大灰象甲成虫不同组织中基因表达水平的内参基因,为后续基因表达研究奠定了基础。     

葱鳞葡萄孢菌诱导下韭菜RT-qPCR内参基因的筛选和验证

葱鳞葡萄胞菌引起的韭菜灰霉病是影响韭菜产量和品质的主要因素之一。为了筛选出感染灰霉病后韭菜叶片中稳定表达的内参基因用于基因定量表达分析,以模拟接种和接种葱鳞葡萄孢菌24、48、72 h的韭菜叶片为材料,基于前期的转录组测序结果选取UBC1、UBC2、UBQ1、UBQ2、GAPDH3、GAPDH4、TUB、EF-1α、40S RP、DDX、eIF-1A、PABP和DnaJ共13个基因为候选内参基因,利用实时荧光定量PCR(RT-qPCR)技术检测13个基因的表达情况,采用geNorm、NormFinder、BestKeeper软件和Reffinder在线程序对候选内参基因的表达稳定性进行评估。结果表明,13个候选内参基因中UBQ1的Ct值变化范围最小,表达水平最稳定。GeNorm、NormFinder和BestKeeper软件筛选出的最佳内参基因不同,RefFinder综合评估显示,UBC2和UBQ1是韭菜叶片接种葱鳞葡萄孢菌后表达稳定性较好的基因,DDX是稳定性较差的基因。为了验证所筛选内参基因的可靠性,选择6个稳定性不同的候选内参基因分别作为定量分析的内部参照,对接种葱鳞葡萄孢菌后不...     

梨小食心虫实时荧光定量PCR内参基因的筛选

【目的】本研究旨在探明梨小食心虫Grapholita molesta在不同发育阶段、成虫不同组织以及不同浓度的3种杀虫剂处理后成虫中稳定表达的内参基因,为后续对梨小食心虫目的基因表达的研究奠定基础。【方法】基于梨小食心虫转录组数据筛选10个候选内参基因(β-actin, 18S rRNA,β-tubulin,EF-1α,RPL13,RPL32,RSPL40,UBC7,α-tubulin和RPS20);通过实时荧光定量PCR(qRT-PCR)测定候选内参基因在梨小食心虫不同发育阶段(卵、1-5龄幼虫、蛹和成虫)、成虫不同组织(头、前肠、中肠、后肠、脂肪体、马氏管、精巢和卵巢)以及不同浓度的3种杀虫剂(阿维菌素：19.819, 72.897和179.663μg/mL;吡虫啉：17.638, 163.323和762.986μg/mL以及高效氯氟氰菊酯：33.791, 96.123和198.282μg/mL)通过玻璃管药膜法处理后成虫中的表达量;利用geNorm, NormFinder,ΔCt, BestKeeper和RefFinder对10个候选内参基因的表达稳定性进行评价。选择梨小食心虫细...     

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。     

Evaluation of reference genes for real-time quantitative PCR studies in

ABSTRACT: BACKGROUND: The selection of stable and suitable reference genes for real-time quantitative PCR (RT-qPCR) is a crucial prerequisite for reliable gene expression analysis under different experimental conditions. The present study aimed to identify reference genes as internal controls for gene expression studies by RT-qPCR in azole-stimulated Candida glabrata. RESULTS: The expression stability of 16 reference genes under fluconazole stress was evaluated using fold change and standard deviation computations with the hkgFinder tool. Our data revealed that the mRNA expression levels of three ribosomal RNAs (RDN5.8, RDN18, and RDN25) remained stable in response to fluconazole, while PGK1, UBC7, and UBC13 mRNAs showed only approximately 2.9-, 3.0-, and 2.5-fold induction by azole, respectively. By contrast, mRNA levels of the other 10 reference genes (ACT1, EF1a, GAPDH, PPIA, RPL2A, RPL10, RPL13A, SDHA, TUB1, and UBC4) were dramatically increased in C. glabrata following antifungal treatment, exhibiting changes ranging from 4.5- to 32.7-fold. We also assessed the expression stability of these reference genes using the 2-[increment][increment]CT method and three other software packages. The stability rankings of the reference genes by geNorm and the 2-[increment][increment]CT method were identical to those by hkgFinder, whereas the stability rankings by BestKeeper and NormFinder were notably different. We then validated the suitability of six candidate reference genes (ACT1, PGK1, RDN5.8, RDN18, UBC7, and UBC13) as internal controls for ten target genes in this system using the comparative CT method. Our validation experiments passed for all six reference genes analyzed except RDN18, where the amplification efficiency of RDN18 was different from that of the ten target genes. Finally, we demonstrated that the relative quantification of target gene expression varied according to the endogenous control used, highlighting the importance of the choice of internal controls in such experiments. CONCLUSIONS: We recommend the use of RDN5.8, UBC13, and PGK1 alone or the combination of RDN5.8 plus UBC13 or PGK1 as reference genes for RT-qPCR analysis of gene expression in C. glabrata following azole treatment. In contrast, we show that ACT1 and other commonly used reference genes (GAPDH, PPIA, RPL13A, TUB1, etc.) were not validated as good internal controls in the current model.     

Evidence based selection of housekeeping genes

For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes (reference or internal control genes) is required. It is known that commonly used housekeeping genes (e.g. ACTB, GAPDH, HPRT1, and B2M) vary considerably under different experimental conditions and therefore their use for normalization is limited. We performed a meta-analysis of 13,629 human gene array samples in order to identify the most stable expressed genes. Here we show novel candidate housekeeping genes (e.g. RPS13, RPL27, RPS20 and OAZ1) with enhanced stability among a multitude of different cell types and varying experimental conditions. None of the commonly used housekeeping genes were present in the top 50 of the most stable expressed genes. In addition, using 2,543 diverse mouse gene array samples we were able to confirm the enhanced stability of the candidate novel housekeeping genes in another mammalian species. Therefore, the identified novel candidate housekeeping genes seem to be the most appropriate choice for normalizing gene expression data.     

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.     

Reference gene selection for transcriptional profiling by RT-qPCR in the 28-spotted larger potato ladybird

Henosepilachna vigintioctomaculata is one of the most serious defoliates attacking potatoes. However, studies on functional genes have greatly been limited due to the insufficiency of effective and stable endogenous references to normalize RT-qPCR data. In this report, nine housekeeping genes (RPL4, RPL6, RPL13, RPL32, RPS18, ACT, EF1α, GAPDH and α-TUB) involved in different biological processes were selected. Their expression levels under diverse experimental conditions including developmental stages, tissues, temperatures and host plants were determined using RT-qPCR technology. The tested candidate genes were comprehensively ranked based on five alternative stability analysis methods (Ct value, geNorm, NormFinder, BestKeeper and ReFinder). The results revealed that the optimal internal reference genes varied under different experimental conditions. Any gene pair among the five candidates (RPL4, RPL13, RPL32, RPS18 and EF1α) was a suitable reference gene set under different temperatures and on different host plants. A combination of RPL6 and RPL13 was recommended as the best reference gene set across different developmental stages. A pair of RPS18 and EF1α was ranked as the optimal reference gene combination within different tissues. The most suitable reference genes were RPS18 and RPL13 under four different experimental conditions. Our findings not only establish an accurate and reliable normalization of RT-qPCR data, but also lay a solid foundation for further functional gene researches in H. vigintioctomaculata.     

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.     

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.