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.     

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-tubulin4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。     

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。     

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.     

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。     

褐飞虱热胁迫下内参基因的筛选及热激蛋白基因表达分析（英文）

【目的】褐飞虱Nilaparvata lugens(Stl)是为害水稻的重要害虫之一,温度是影响其暴发、迁飞的主要环境因子之一。本研究旨在探讨研究褐飞虱对高温胁迫适应性的热激蛋白基因表达调控模式。【方法】分别以不同的高温(30℃~40℃)处理褐飞虱雌、雄虫1 h和2 h,利用荧光定量PCR技术检测其体内的β-actin 1,β-actin2,β-actin3,28S rRNA,18S rRNA和α-2-tubulin 6个内参基因的表达量,用geN orm和BestK eeper软件分析确定最稳定表达的内参基因,并检测热胁迫后hsp70和hsp90基因在处理褐飞虱成虫体内的表达模式。【结果】geN orm软件分析结果表明,热胁迫后褐飞虱内参基因稳定性在雌虫体内为:β-actin1=β-actin328S rRNAα-2-tubulin18S rRNAβ-actin2;在雄虫体内为:β-actin1=β-actin3α-2-tubulin28S rRNA18S rRNAβ-actin2。BestK eeper软件分析结果显示,在热胁迫的雌、雄虫体内β-actin1均最稳定,18S rRNA次之,β-actin2最不稳定。两种软件分析结果基本一致。以β-actin1为校正内参基因,荧光定量PCR分析hsp70和hsp90在不同热胁迫条件下的表达模式,结果表明,各高温处理下hsp70表达量与对照26℃下的表达量没有显著性差异;而hsp90基因表达模式表现为被高温诱导上调表达,在雌、雄虫体内表达量达到最高的处理条件分别为40℃和38℃处理2 h。【结论】β-actin1基因可以作为热胁迫下褐飞虱雌雄虫体内基因表达模式分析的校正内参基因使用。褐飞虱hsp90基因能被高温诱导表达,该基因可能在褐飞虱适应热胁迫过程中起着重要的作用。     

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。     

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。     

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。     

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。     

Validation of Reference Housekeeping Genes for Gene Expression Studies in Western Corn Rootworm (Diabrotica virgifera virgifera)

Quantitative Real-time PCR (qRT-PCR) is a powerful technique to investigate comparative gene expression. In general, normalization of results using a highly stable housekeeping gene (HKG) as an internal control is recommended and necessary. However, there are several reports suggesting that regulation of some HKGs is affected by different conditions. The western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), is a serious pest of corn in the United States and Europe. The expression profile of target genes related to insecticide exposure, resistance, and RNA interference has become an important experimental technique for study of western corn rootworms; however, lack of information on reliable HKGs under different conditions makes the interpretation of qRT-PCR results difficult. In this study, four distinct algorithms (Genorm, NormFinder, BestKeeper and delta-CT) and five candidate HKGs to genes of reference (β-actin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; β-tubulin; RPS9, ribosomal protein S9; EF1a, elongation factor-1α) were evaluated to determine the most reliable HKG under different experimental conditions including exposure to dsRNA and Bt toxins and among different tissues and developmental stages. Although all the HKGs tested exhibited relatively stable expression among the different treatments, some differences were noted. Among the five candidate reference genes evaluated, β-actin exhibited highly stable expression among different life stages. RPS9 exhibited the most similar pattern of expression among dsRNA treatments, and both experiments indicated that EF1a was the second most stable gene. EF1a was also the most stable for Bt exposure and among different tissues. These results will enable researchers to use more accurate and reliable normalization of qRT-PCR data in WCR experiments.     

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.     

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