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。     

牛转FAD3B基因胎儿成纤维细胞中内参基因的稳定性评估

采用RT-PCR扩增亚麻种子(Linum usitatissimum Linn)FAD3B基因,构建不同启动子的两种重组真核表达载体pIRES-AcGFP-CMV-FAD3B和pIRES-AcGFP-CAG-FAD3B,通过qRT-PCR检测转基因细胞中FAD3B基因的表达水平.以不同过表达水平的转基因细胞为试验对象,评价9种候选内参基因ACTB、GAPDH、18S rRNA、UXT、PPP1R11、RPS15A、SF3A1、EEF1A2和HMBS的稳定性.根据GeNorm、NornFinder和BestKeeper 3种统计学算法得到的稳定性值对基因进行排序.结果显示,内参基因稳定性的综合排序为PPP1R11＞EEF1A2＞1 8S rRNA＞RPS15A＞GAPDH＞HMBS＞UXT＞ACTB＞SF3A1,其中PPP1R11和EEF1A2是最稳定的内参基因.稳定内参的选择可以更加准确地校正基因的表达水平,从而为阐述基因的功能奠定了坚实的基础.     

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。     

近零磁场下粘虫雌蛾内参基因转录表达稳定性评价

【目的】筛选近零磁场下粘虫Mythimnaseparata雌蛾内稳定表达的内参基因,为在近零磁场下的粘虫靶标基因表达的定量分析准确性提供依据。【方法】利用亥姆霍兹线圈产生近零磁场,分别在近零磁场(<500nT)和地磁场(约50μT)2种磁场强度下饲养粘虫。采用qRT-PCR技术测定2种磁场强度下饲养的粘虫初羽化雌蛾10种内参基因:β-肌动蛋白(β-Actin)、β-微管蛋白(β-TUB)、TATA盒结合蛋白(TBP)、延伸因子(EF-1α)、甘油醛-3-磷酸脱氢酶(GAPDH)、18S核糖体RNA(18S rRNA)、28S核糖体RNA(28SrRNA)、cGMP依赖性蛋白激酶(PKG)、核糖体蛋白L12(RPL12)和腺苷三磷酸酶(ATPase)的定量表达,利用geNorm、NormFinder、BestKeeper以及在线综合分析系统RefFinder内参筛选分析软件分别对2种磁场强度下粘虫的内参基因稳定性进行评估筛选。【结果】β-Actin和18S rRNA的稳定性在NormFinder结果中居于前两位,geNorm和BestKeeper结果中β-Actin和PKG基因稳定性最好,RefFinder综合分析表明,β-Actin稳定性最好,其次为18S rRNA和PKG基因,β-TUB和TBP的表达稳定性在三个软件分析结果中都较差。geNorm软件进一步对内参基因的分析表明引入β-Actin和18S rRNA两个内参基因最佳。【结论】明确了近零磁场强度下适用于粘虫初羽化雌成虫稳定表达的内参基因,确保了近零磁场下粘虫靶标基因转录表达水平的准确测定,为粘虫磁感受分子机制研究提供了重要工具。     

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。     

冬虫夏草菌实时荧光定量PCR内参基因的筛选

以冬虫夏草单子囊孢子分离得到的菌株TZ8-1的3种菌丝形态为实验材料,提取RNA,经反转录获取cDNA,选择了11个持家基因为候选内参基因（18S rRNA、APRTase、β-TUB、RPL2、EF1-α、PGI、PGM、H⁺-ATPase、ACT1、UBQ和GAPDH）,根据该菌基因组注释结果来设计引物,采用实时荧光定量PCR（qRT-PCR）技术进行定量扩增,利用geNorm、NormFinder和BestKeeper算法程序进行表达稳定性评估,并用RefFinder对评估结果进行综合排比,最终筛选得到了最适内参基因。结果表明,所选取的11个候选内参基因均可作为冬虫夏草菌菌丝体时期的内参基因,稳定性最好的3个内参基因分别是UBQ、PGE和ACT1,稳定性较差的3个内参基因分别是GAPDH、RPL2和β-TUB。     

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...     

夜香树花期荧光定量PCR内参基因的筛选

为筛选夜香树（Cestrum nocturnum L.）香气释放、生物钟等相关基因表达研究适用的内参基因,本研究采用夜香树盛花期叶片和花为实验材料,利用同源克隆和RACE技术,获得了夜香树6种经典的内参基因序列,分别为：Actb7、EF-1A、GAPDH、TUA、TUB2、UBQ;采用荧光定量PCR方法对18s rRNA和这6个内参基因的表达模式进行了分析,并通过Bestkeeper、geNorm、NormFinder 3种程序分析了内参基因的稳定性。结果表明,在花中,Actb7表达最稳定;在叶片中,EF-1A和UBQ的表达比较稳定;在2种组织中,EF-1A的表达相对稳定。3组稳定性分析中,geNorm程序确定的最佳内参基因数目均为2,最佳内参基因组合均为Actb7/EF-1A。本研究通过对稳定内参基因的筛选,以期为准确检测夜香树盛花期花瓣节律运动、香气释放、生物钟变化等相关基因的表达研究奠定基础。     

朱红毛斑蛾实时荧光定量PCR内参基因的筛选

筛选朱红毛斑蛾Phauda flammans(Walker)在不同成虫组织、性别及发育阶段处理条件下稳定表达的内参基因,为进一步开展朱红毛斑蛾相关基因的定量研究提供参考.本研究以不同成虫组织(头、胸、腹、足、翅和触角)、不同成虫性别和不同发育阶段(卵、幼虫、蛹和成虫)为实验材料,对10个候选内参基因进行实时荧光定量PCR(qRT-PCR),并使用GeNorm、NormFinder和BestKeeper软件及RefFinder网站对候选内参基因的表达稳定性进行评价和综合分析.结果表明:在朱红毛斑蛾不同成虫组织基因定量研究中,TUB2＞GAPDH＞TUBJ＞AK＞EFlα＞ACTIN3＞TBP＞TUB3＞ACTIN2＞RPL32,建议以TUB2和GAPDH作为内参基因;在不同成虫性别基因定量研究中,TUB1＞EFlα＞ACTIN3＞RPL32＞ACTIN2＞TUB2＞AK＞GAPDH＞TUB3＞TBP,建议以 TUB1 和EFlα作为内参基因;在不同发育阶段基因定量研究中,ACTIN3＞TBP＞TUB1＞EFlα＞TUB3＞ACTIN2＞GAPDH＞RPL32＞TUB2＞AK,建议以ACTIN3和TBP作为内参基因.基于GeNorm分析,最佳内参基因使用数目为2个.     

光裸星虫(Sipunculus nudus)不同发育时期卵细胞内参基因的筛选

内参基因的选择对功能基因表达量的归一化处理尤为重要。为了筛选出光裸星虫不同发育时期卵子的最适内参基因,利用qRT-PCR测定了甘油醛-3-磷酸脱氢酶(GAPDH)、肽基脯氨酰顺反异构酶A(PPIA)、60S核糖体蛋白L10(60S-L10)、铁蛋白(Ferritin)、β-肌动蛋白(β-actin)、泛素C(UBC)、真核生物翻译起始因子(eIF)、NADH脱氢酶(NDH)、28S核糖体RNA(28S)、TATA盒结合蛋白(TBP)、18S核糖体RNA(18S)和琥珀酸脱氢酶A亚基(SDHA)共12个候选内参基因的表达水平,并通过4个程序(geNorm,NormFinder,BestKeeper以及RefFinder)综合分析了各基因的表达稳定性。结果显示:(1)12个候选内参基因均能获得特异性扩增产物,但表达情况各异;(2)对候选内参基因进行综合打分,得到候选内参基因稳定性排名为18S>GAPDH>28S>β-actin>UBC>e IF>NDH|TBP>PPIA|Ferritin>60S-L10>SDHA。18S和GAPDH稳定性较好,可作为不同发育时期卵细胞基因表达研究的单内参基因,或最优组合内参基因。     

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.     

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.     

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.     

Identifying suitable reference genes for developing and injured mouse CNS tissues

Accurate quantification of gene expression is fundamental for understanding the molecular, genetic and functional bases of tissue development and diseases. Quantitative real‐time PCR (qPCR) is now the most widely used method of quantifying gene expression due to its simplicity, specificity, sensitivity, and wide quantification range. The use of appropriate reference genes to ensure accurate normalization is crucial for the correct quantification of gene expression from the early development, maturation, aging to injury processes in the central nervous system (CNS). In this study, we have determined the expression profiles of 12 candidate housekeeping genes (ACTB, CYC1, HMBS, GAPDH, HPRT1, RPL13A, YWHAZ, PPIA, RPLP0, TFRC, GUS, and 18S rRNA) in developing mouse brain and spinal cord. Throughout development, there was a significant degree of fluctuations in their expression levels, indicating the importance and complexity of finding appropriate reference genes. Three software including BestKeeper, geNorm and NormFinder were used to evaluate the stability of potential reference genes. GUS was the most stable gene and GUS/YWHAZ were the most stable reference gene pair across different developmental stages in different CNS regions, whereas HPRT1 and GAPDH were the most variable genes and thus inappropriate to use as reference genes. Therefore, our results identified GUS and YWHAZ as the best combination of two reference genes for expression data normalization in CNS developmental studies. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 39–50, 2018     

Selection of optimal reference genes for quantitative RT-PCR studies of boar spermatozoa cryopreservation

Reference genes can be used to normalize mRNA levels across different samples for the exact comparison of the mRNA expression level. It is important to select reference genes with high quality for the accurate interpretation of qRT-PCR data. Although several studies have attempted to validate reference genes in pigs, no validation studies have been performed on spermatozoa samples frozen with different cryoprotectants. In this study, 11 commonly used reference genes (ACTB, B2M, GAPDH, HPRT1, RPL4, SDHA, YWHAZ, PPIA, PGK1, S18, and BLM) were investigated in boar spermatozoa frozen with six different cryoprotectants using qRT-PCR. The expression stability of these reference genes in different samples was evaluated using geNorm (qbase^plus software), NormFinder, and BestKeeper. The geNorm results revealed that PGK1, ACTB, and RPL4 exhibit high expression stability in all of the samples, and the NormFinder results indicated that GAPDH is the most stable gene. Furthermore, the BestKeeper results indicated that the three most stable genes are PPIA, GAPDH, and RPL4 and that S18, B2M and BLM are the three least stable genes. There are a number of differences in the ranking order of the reference genes obtained using the different algorithms. In conclusion, GAPDH, RPL4, and PPIA were the three most stable genes in frozen boar spermatozoa, as determined based on the cycle threshold coefficient of variation (Ct CV%) and the comprehensive ranking order, and this finding is consistent with the BestKeeper results     

Validation of reference genes of grass carp Ctenopharyngodon idellus for the normalization of quantitative real-time PCR

Expression of four reference genes of grass carp, including β-actin (ACTB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18S rRNA (18S) and elongation factor-1 alpha (EF1α), was studied in tissues of normal individuals and bacteria-infected individuals. EF1α had the most stable expressions followed by 18S rRNA then GAPDH; ACTB had the least stability. After being infected with bacteria, the grass carp showed minimal changes in expression levels of EF1α in the liver and head kidney, while ACTB had the most stable expressions in spleen but the least stable in liver. EF1α is thus the optimal reference gene in quantitative real-time PCR analysis to quantitate the expression levels of target genes in tissues of grass carp.     

Identification of suitable reference genes for gene expression studies of human serous ovarian cancer by real-time polymerase chain reaction

Quantitative real-time RT-PCR (RT-qPCR) has proven to be a valuable molecular technique in gene expression quantification. Target gene expression levels are usually normalized to a stably expressed reference gene simultaneously determined in the same sample. It is critical to select optimal reference genes to interpret data generated by RT-qPCR. However, no suitable reference genes have been identified in human ovarian cancer to date. In this study, 10 housekeeping genes, ACTB, ALAS1, GAPDH, GUSB, HPRT1, PBGD, PPIA, PUM1, RPL29, and TBP as well as 18S rRNA that were already used in various studies were analyzed to determine their applicability. Totally 20 serous ovarian cancer specimens and 20 normal ovarian epithelial tissue specimens were examined. All candidate reference genes showed significant differences in expression between malignant and nonmalignant groups except GUSB, PPIA, and TBP. The expression stability and suitability of the 11 genes were validated employing geNorm and NormFinder. GUSB, PPIA, and TBP were demonstrated as the most stable reference genes and thus could be used as reference genes for normalization in gene profiling studies of serous ovarian cancer, while the combination of two genes (GUSB and PPIA) or the all three genes should be recommended as a much more reliable normalization strategy.