冬虫夏草是冬虫夏草菌Ophiocordyceps sinensis寄生于蝙蝠蛾Hepialus armoricanus幼虫体后发育成的真菌子座和充满菌丝的僵死幼虫的复合体（Zhou et al. 2014;Liu et al. 2015;Lu et al. 2016）,是我国传统的名贵中草药。冬虫夏草菌是学术界普遍认同的冬虫夏草无性型（刘锡琎等 1989;李增智等 2000;Chen et al. 2001;莫明和等 2001;刘作易等 2003;谢放等 2011）。随着组学技术的快速发展,挖掘冬虫夏草有性启动、宿主侵染、代谢物合成等的关键基因,成为了目前该领域的研究热点。
实时荧光定量PCR（qRT-PCR）现已成为不同样品之间进行基因表达水平定量差异比较的权威性方法（Nolan et al. 2006）。在实时荧光定量PCR试验中,为了消除由于材料、反应效率等因素导致基因表达数据的误差,通常将持家基因作为研究的内参基因对数据进行标准化处理,以此来减小研究误差（Foldager et al. 2009）,这就要求所选择的内参基因在所有的研究材料中都必须稳定表达。然而,越来越多的研究表明,在某种试验稳定表达的内参基因,在另一种试验中有可能是变化的（Jain et al. 2006;Løvdal & Lillo 2009;Tong et al. 2009）。而在任何试验条件下都能稳定表达的内参基因几乎不存在（Li et al. 2016;Rui et al. 2016）。因此要针对于不同的试验条件选择最适合的内参基因,以此来提高试验数据的准确性。目前,内参基因的筛选在灵芝Ganoderma lingzhi（Xu et al. 2014）、毛木耳Auricularia cornea（Jia et al. 2019）、黑木耳Auricularia heimuer（张越等 2020）、香菇Lentinula edodes（Xiang et al. 2018）、糙皮侧耳Pleurotus ostreatus（Fernández-Fueyo et al. 2014）、刺芹侧耳Pleurotus eryngii（秦晓艺和王杰 2015）等重要的食药用菌中已有报道,而冬虫夏草研究领域未见相关报道。
在以往研究中,绝大多数都是用组织分离方法从野生冬虫夏草中获取冬虫夏草菌丝体作为研究材料。在冬虫夏草菌培养过程中,会出现3种有明显差异的菌丝形态（图1）,但其发生的原因和机理未见报道。为排除可能是混入的杂菌干扰,我们通过单子囊孢子纯化菌株对这一现象开展研究,排除了杂菌因素,发现在形态、弯曲程度、致密程度、显微表面结构及产孢能力等方面均存在显著差异。因此,以冬虫夏草菌3种菌丝形态为研究材料来筛选冬虫夏草菌菌丝体时期表达最为稳定的内参基因,能为冬虫夏草组学研究提供重要的参考依据。
图1
图1
三种菌丝形态图
A:气生菌丝;B:菌丝团;C:基生菌丝
Fig. 1
Morphology of hyphae.
A: Aerial mycelium; B: Hyphal knot; C: Substrate mycelium.
本研究以冬虫夏草菌单孢菌株的3种菌丝形态为材料,选择了11个持家基因,利用geNorm、NormFinder、BestKeeper 3种分析程序进行了分析评价,并用RefFinder程序进行了综合排比,筛选出了冬虫夏草菌菌丝体时期表达最为稳定的内参基因。
1 材料与方法
1.1 供试菌株的准备
使用本课题组利用单个子囊孢子培养得到的单孢菌株为供试菌株,编号为TZ8-1,现保存于兰州交通大学生物种苗工程研究所。分别取气生菌丝（A）、菌丝团（B）和基生菌丝（C）3种菌丝形态（图1）为试验材料,每组取3个生物学重复样本,-80℃冰箱保存,用于内参基因的筛选研究。
1.2 候选内参基因的选择与引物设计
选择11个常见的持家基因为内参候选基因,分别是18S核糖体RNA（18S rRNA）、腺嘌呤磷酸核糖转移酶（APRTase）、β-微管蛋白（β-TUB）、核糖体蛋白L2（RPL2）、翻译延长因子1-a（EF1-α）、磷酸葡萄糖异构酶（PGI）、磷酸葡萄糖变异酶（PGM）、质膜质子ATP酶（H+-ATPase）、肌动蛋白1（ACT1）、多聚泛素酶（UBQ）和3-磷酸甘油脱氢酶（GAPDH）。引物序列根据NCBI中Ophiocordyceps sinensis CO18（ASM44836v1）的基因组序列信息,经由上海欧易生物医学科技有限公司设计并由北京擎科新业生物技术有限公司合成,引物序列见表1。
表1 候选内参基因的引物序列
Table 1
| 基因名称 Gene name | 正向引物 Forward primer (5’-3’) | 反向引物 Reverse primer (5’-3’) | 扩增产物 Amplicon size (bp) | Tm (°C) |
|---|---|---|---|---|
| 18S rRNA | GCAGTGGCATCTCTCAGTC | TCATCGATGCCAGAACC | 128 | 60 |
| APRTase | ATGCTGAGCTGTTTAGCG | TGCCCTGTTCGTCGTAGA | 90 | 60 |
| β-TUB | TACGCCTCTTCGACGATAG | GCCGTTGTAGACACCATT | 148 | 60 |
| RPL2 | ACCTACCGTCTCCATCAT | GTGAACCTGCTGGACAAT | 109 | 60 |
| EF1-α | CAAGGGCTCTTTCAAGTATGC | GTGACATAGTACCTGGGAGT | 114 | 60 |
| PGI | TTCGACCAGTATCTTCATCGC | GTGTACTTGACCGACGATCC | 83 | 60 |
| PGM | AAGCCCTTTCAGGACCAA | GAACGACTCGGTGTAGTG | 87 | 60 |
| H+-ATPase | CGCTTCGCGGAAATCTATAC | AGACGTTCTTGTTGACGG | 90 | 60 |
| ACT1 | CAATCGGCACAACTGGACA | GACGACCTGAGCGGAATA | 95 | 60 |
| UBQ | CGACATCGAGTTGGACTAC | ATACCTGCAATCTGTCCG | 82 | 60 |
| GAPDH | GAGGCCGAGAGCCAACTA | TTCATCACGACAGCACCA | 99 | 60 |
1.3 样品总RNA的提取及cDNA的合成
采用试剂盒（mirVana™ miRNA ISOlation Kit,Ambion-1561）提取总RNA,之后利用NanoDrop 2000分光光度计（Thermo Scientific,USA）测定浓度及OD260/OD280,琼脂糖凝胶电泳检测RNA完整性。检测合格后利用TransScript All-in-One First-Strand cDNA Synthesis SuperMIX for qPCR试剂盒将待测RNA逆转录成cDNA。反转录体系为:总RNA 0.5μg;5×TransScript All-in-one SuperMix for qPCR 5μL;gDNA Remover 0.5μL;Nuclease- free H2O加至10μL。反应程序:42℃ 15min,85℃ 5s。逆转录完毕后加入90μL Nuclease- free H2O储存在-20℃冰箱备用。
1.4 荧光定量PCR
利用PerfectStartTM Green qPCR SuperMix试剂盒在LightCycler® 480 Ⅱ型荧光定量PCR仪（Roche,Swiss）上进行反应。反应体系:2×PerfectStartTM Green qPCR SuperMix 5μL;10μmol/L Forward primer 0.2μL;10μmol/L Reverse primer 0.2μL;cDNA 1μL;Nuclease- free H2O 3.6μL。PCR程序:94℃ 30s;94℃ 5s;60℃ 30s;45个循环。循环结束后利用熔解曲线检测产物特异性:从60℃缓慢升温至97℃,每℃采集5次荧光信号。
1.5 表达稳定性分析
qRT-PCR扩增完毕后,利用geNorm（Vandesompele et al. 2002）、NormFinder（Andersen et al. 2004）和BestKeeper（Pfaffl et al. 2004）3种软件分析11个候选内参基因的表达差异。利用RefFinder（Zsori et al. 2013）软件对11个候选内参基因的表达稳定性进行综合排名。
2 结果与分析
2.1 RNA的分离与纯化
RIN（RNA integrity number）,代表RNA完整性数值,范围在1-10之间,是Agilent Bioanalyzer对total RNA完整性给出的数字化评估,数值越小说明降解越严重。RIN值在1-6之间说明RNA发生明显降解,RIN值在7-10之间说明RNA完整性较好。18S与28S是真核生物rRNA的两个主要亚基,如果28S/18S为1.8-2.0表明所提取RNA完整性较好,基本无降解发生,当28S/18S小于0.7时,表明已经发生较明显的降解,该样品不可用于后续分析（易乐飞等 2016;Padhi et al. 2018）。本研究中RNA样品的质检结果见表2,RIN值均在7以上,28S/18S值均在0.7以上,说明所有样品符合后续分析要求。
表2 RNA质检结果
Table 2
| 样本 Sample | 浓度 Concentration (μg/μL) | A260/280 | A260/230 | 体积 Volume (μL) | 总量 Total (μg) | 28S/18S | RIN |
|---|---|---|---|---|---|---|---|
| A1 | 0.3864 | 2.18 | 1.84 | 20 | 7.73 | 1.7 | 9.5 |
| A2 | 0.1979 | 2.19 | 2.28 | 20 | 3.96 | 0.9 | 7.7 |
| A3 | 0.1701 | 2.14 | 1.78 | 20 | 3.40 | 1.0 | 7.2 |
| B1 | 0.3490 | 2.18 | 1.81 | 20 | 6.98 | 1.7 | 10.0 |
| B2 | 0.2323 | 2.17 | 1.77 | 20 | 4.65 | 2.1 | 9.2 |
| B3 | 0.1352 | 2.16 | 1.75 | 15 | 2.03 | 1.2 | 7.1 |
| C1 | 0.3873 | 2.16 | 2.24 | 20 | 7.75 | 1.5 | 8.8 |
| C2 | 0.5354 | 2.23 | 2.00 | 20 | 10.71 | 1.1 | 7.9 |
| C3 | 0.2250 | 2.16 | 2.10 | 20 | 4.50 | 1.3 | 7.9 |
2.2 候选内参基因的引物分析
12个候选内参基因引物进行qRT-PCR扩增得到的熔解曲线均为单一熔解峰（图2）,这说明所设计的引物具有较强的特异性,定量分析结果可靠性高。
图2
图2
由qRT-PCR产生的熔解曲线
横坐标:温度;纵坐标:-(d/dt) Fluorescence (465-510)
Fig. 2
Melting curve generated by qRT-PCR.
Abscissa: Temperature; Ordinate: -(d/dt) fluorescence (465-510).
2.3 候选内参基因的Ct值分析
11个候选内参基因在不同形态菌丝样本中Ct值的分布箱形图见图3,Ct值的变化范围可以体现其转录水平在不同样品中的离散程度。11个候选内参基因的Ct值均在9-31之间,其中RPL2的Ct值变化范围最大,相差3.07个循环,APRTase的Ct值变化范围最小,相差1.13个循环。可以看出,11个不同的候选内参基因在不同菌丝形态的样本中转录水平存在不同程度的差异。因此,在不同样本中筛选出表达最为稳定的内参基因极为重要。
图3
2.4 候选内参基因的表达稳定性分析
2.4.1 geNorm分析结果:geNorm是专门用于Real-time PCR中筛选内参基因及确定最适内参基因数目的程序,可用于筛选任何实验的任意数目的内参基因,并最终挑选出两个或两个以上的内参基因组合来校正数据,可使相对定量的结果更为精确（吴建阳等 2017）。该程序通过计算出每个候选内参基因稳定性的M值来筛选出稳定性较好的内参基因,判定标准为M值小于1.5即可作为内参基因,M值越小内参基因的稳定性越好（Vandesompele et al. 2002）。
11个候选内参基因通过geNorm程序分析发现,M值均小于1.5,因此,11个候选内参基因均可作为冬虫夏草菌菌丝体时期不同形态的内参基因。其中,候选内参基因UBQ与PGM的M值最小。结果显示11个候选内参基因的稳定性依次为PGM、UBQ>EF-1α> RPL2>β-TUB>PGI>18S rRNA>ACT1>H+-ATPase> APRTase>GAPDH（图4）。
图4
图4
十一个候选内参基因的稳定性折线图
Fig. 4
Broken line diagram of the stability of 11 candidate reference genes.
2.4.2 NormFinder分析结果:NormFinder程序计算原理与geNorm程序相似,也是先获得内参基因表达稳定值,再根据稳定值大小来筛选出最合适的内参基因,判定标准为表达稳定值最小的内参基因为最合适的内参基因（Andersen et al. 2004;吴建阳等 2017）。
NormFinder程序对冬虫夏草菌的11个候选内参基因表达稳定性的分析结果见表3,稳定值越低,基因表达越稳定,因此所得到最为稳定内参基因为UBQ。
表3 NormFinder分析候选内参基因的表达稳定值
Table 3
| 基因名称 Gene name | 稳定值 Stability value | 最优基因 Best gene |
|---|---|---|
| UBQ | 0.096 | UBQ |
| PGM | 0.102 | |
| ACT1 | 0.122 | |
| H+-ATPase | 0.140 | |
| EF-1α | 0.155 | |
| 18S rRNA | 0.223 | |
| APRTase | 0.269 | |
| PGI | 0.292 | |
| β-TUB | 0.350 | |
| RPL2 | 0.363 | |
| GAPDH | 0.646 |
2.4.3 BestKeeper分析结果:BestKeeper程序是针对内参基因和目标基因表达量分析的程序,最多只能比较100个样品中10个内参基因和10个目标基因的表达水平。通过该程序可计算获得每个基因之间产生配对的相关系数（r）、标准偏差（SD）和变异系数（CV）,在通过比较各个值的大小,最终确定稳定性较好的内参基因,判定原则为相关系数越大,标准偏差和变异系数越小,内参基因的稳定性越好,反之稳定性越差。当SD>1时,则该内参基因表达不稳定（Pfaffl et al. 2004;吴建阳等 2017）。BestKeeper程序分析11个候选内参基因的稳定性结果见表4,11个候选内参基因的SD均小于1,这进一步说明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。根据每个内参基因Ct值的标准差（SD）和变异系数（CV）综合排名前三的内参基因分别是APRTase、ACT1和H+-ATPase。
表4 BestKeeper程序分析候选内参基因的稳定性表达
Table 4
| 基因名称 Gene name | 变异系数 CV | 标准差 SD |
|---|---|---|
| APRTase | 1.23 | 0.33 |
| ACT1 | 1.68 | 0.43 |
| H+-ATPase | 1.8 | 0.53 |
| UBQ | 2.17 | 0.65 |
| PGM | 2.97 | 0.69 |
| 18S rRNA | 4.31 | 0.7 |
| GAPDH | 2.37 | 0.7 |
| EF-1A | 3.9 | 0.73 |
| PGI | 3.65 | 0.86 |
| β-TUB | 3.9 | 0.88 |
| RPL2 | 3.86 | 0.9 |
2.5 内参基因组合数分析
2.5.1 RefFinder综合分析结果:RefFinder是一个很好的网络综合分析工具,可用于实验数据评估和内参基因的筛选。集成了目前内参基因筛选可用的主要计算程序（geNorm、Normfinder、BestKeeper等）,对候选内参基因进行比较和排序。会根据每个程序的排名,给每个候选内参基因赋予一个适当的权重,并计算出其权重的几何平均值,从而得出最终的总排名（Xie et al. 2012;Zsori et al. 2013）。
通过RefFinder对几种分析程序分析结果进行综合排名,11个候选内参基因综合排比结果前三的分别是UBQ、PGE和ACT1,后三名分别是GAPDH、RPL2和β-TUB（表5）。
表5 RefFinder综合排名结果
Table 5
| 基因名称 Gene name | Delta CT排名 Delta CT ranking | geNorm排名 geNorm ranking | NormFinder排名 NormFinder ranking | BestKeeper排名 BestKeeper ranking | 几何均值 Geomean | 综合排名 Comprehensive ranking |
|---|---|---|---|---|---|---|
| UBQ | 2 | 2 | 1 | 4 | 1.78 | 1 |
| PGM | 1 | 1 | 2 | 5 | 1.86 | 2 |
| ACT1 | 4 | 8 | 3 | 2 | 4.12 | 3 |
| EF-1α | 3 | 3 | 5 | 8 | 4.49 | 4 |
| H+-ATPase | 5 | 9 | 4 | 3 | 5.18 | 5 |
| APRTase | 8 | 10 | 7 | 1 | 5.79 | 6 |
| 18S rRNA | 6 | 7 | 6 | 6 | 6.48 | 7 |
| PGI | 7 | 6 | 8 | 9 | 7.16 | 8 |
| β-TUB | 9 | 5 | 9 | 10 | 8.17 | 9 |
| RPL2 | 10 | 4 | 10 | 11 | 8.32 | 10 |
| GAPDH | 11 | 11 | 11 | 7 | 10.84 | 11 |
2.5.2 两两变异分析:geNorm软件通过两两比较（Vn/n+1）可以确定最佳内参基因的数量。在此过程中默认的V值为0.15,当Vn/n+1值小于0.15时,无需引入额外的内参基因（吴建阳等 2017）。如果内参基因的平均M值小于0.2,则认为该基因是稳定的（Jia et al. 2019）。在本研究中最低M值小于0.2,并且V值均在0.15以下（图5）,这说明有一个内参基因就可以对基因表达数据进行归一化处理,而为了结果更加可靠,引入两个内参基因的效果会更好。因此,根据M值的大小,判断出UBQ和PGM这两者是最好的组合。
图5
图5
十二个候选内参基因两两变异（Vn/n+1）分析
Fig. 5
Pairwise variation analysis of 12 candidate reference genes (Vn/n+1).
3 讨论
大量研究表明,不同试验条件下内参基因的选择有所不同,不存在不同物种或不同试验条件下通用的内参基因（Xu et al. 2014;赵小龙 2016;Xiang et al. 2018;张倩倩等 2018;Jia et al. 2019）。本研究采用最适生长条件下生长120d后的冬虫夏草菌单孢菌株的3种菌丝形态为试验材料,筛选了冬虫夏草菌菌丝体时期最适的内参基因,所得到的结果仅限于为类似试验体系提供参考,并不能保证所有试验体系适用,尤其以子实体为研究材料的相关实验体系可能还需要进一步验证。
在候选内参基因上,本研究选择了11个典型的持家基因作为候选内参基因,在选取数量上多于其他食药用真菌的相关研究（Xu et al. 2014;安丹丹等 2016;赵小龙 2016;Xiang et al. 2018;Jia et al. 2019）,因此本研究所得结果可靠性更好。但由于机体中持家基因数目庞大,因此本研究选取的也只不过是冰山一角。本研究所获得的结果良好,所选取的11个候选内参基因通过geNorm分析所得的M值范围在0.15-0.58之间,且Vn/n+1值均小于0.15,这说明本研究所选取的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,完全能为该领域研究提供参考,而无需再做过多验证。
本研究在候选基因稳定性分析过程中发现,选择不同的分析程序所得到的结果有所差异,如APRTase在BestKeeper分析结果中稳定性最好,但在geNorm和NormFinder分析结果中却处于末端。这种现象在其他物种内参基因筛选中也同样出现（Xu et al. 2014;Tao et al. 2016;Qian et al. 2018;Xiang et al. 2018）,究其原因是BestKeeper程序分析统计的算法和侧重点有别于geNorm和NormFinder分析程序。而本研究通过引入RefFinder对各程序所得结果进行综合排名,很好地解决这了一问题,因此,参考RefFinder程序的综合排名结果,可靠性会更好。
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DOI:S1087-1845(14)00019-X
PMID:24560615
Pleurotus ostreatus is an important edible mushroom and a model lignin degrading organism, whose genome contains nine genes of ligninolytic peroxidases, characteristic of white-rot fungi. These genes encode six manganese peroxidase (MnP) and three versatile peroxidase (VP) isoenzymes. Using liquid chromatography coupled to tandem mass spectrometry, secretion of four of these peroxidase isoenzymes (VP1, VP2, MnP2 and MnP6) was confirmed when P. ostreatus grows in a lignocellulose medium at 25°C (three more isoenzymes were identified by only one unique peptide). Then, the effect of environmental parameters on the expression of the above nine genes was studied by reverse transcription-quantitative PCR by changing the incubation temperature and medium pH of P. ostreatus cultures pre-grown under the above conditions (using specific primers and two reference genes for result normalization). The cultures maintained at 25°C (without pH adjustment) provided the highest levels of peroxidase transcripts and the highest total activity on Mn(2+) (a substrate of both MnP and VP) and Reactive Black 5 (a VP specific substrate). The global analysis of the expression patterns divides peroxidase genes into three main groups according to the level of expression at optimal conditions (vp1/mnp3>vp2/vp3/mnp1/mnp2/mnp6>mnp4/mnp5). Decreasing or increasing the incubation temperature (to 10°C or 37°C) and adjusting the culture pH to acidic or alkaline conditions (pH 3 and 8) generally led to downregulation of most of the peroxidase genes (and decrease of the enzymatic activity), as shown when the transcription levels were referred to those found in the cultures maintained at the initial conditions. Temperature modification produced less dramatic effects than pH modification, with most genes being downregulated during the whole 10°C treatment, while many of them were alternatively upregulated (often 6h after the thermal shock) and downregulated (12h) at 37°C. Interestingly, mnp4 and mnp5 were the only peroxidase genes upregulated under alkaline pH conditions. The differences in the transcription levels of the peroxidase genes when the culture temperature and pH parameters were changed suggest an adaptive expression according to environmental conditions. Finally, the intracellular proteome was analyzed, under the same conditions used in the secretomic analysis, and the protein product of the highly-transcribed gene mnp3 was detected. Therefore, it was concluded that the absence of MnP3 from the secretome of the P. ostreatus lignocellulose cultures was related to impaired secretion. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Validation of suitable house keeping genes for hypoxia-cultured human chondrocytes
DOI:10.1186/1471-2199-10-94
PMID:19818117
[本文引用: 1]
Hypoxic culturing of chondrocytes is gaining increasing interest in cartilage research. Culturing of chondrocytes under low oxygen tension has shown several advantages, among them increased synthesis of extracellular matrix and increased redifferentiation of dedifferentiated chondrocytes. Quantitative gene expression analyses such as quantitative real-time PCR (qRT-PCR) are powerful tools in the investigation of underlying mechanisms of cell behavior and are used routinely for differentiation and phenotype assays. However, the genes used for normalization in normoxic cell-cultures might not be suitable in the hypoxic environment. The objective of this study was to determine hypoxia-stable housekeeping genes (HKG) for quantitative real-time PCR (qRT-PCR) in human chondrocytes cultured in 21%, 5% and 1% oxygen by geNorm and NormFinder analyses.The chondrocytic response to the hypoxic challange was validated by a significant increase in expression of the hypoxia-inducible gene ankyrin repeat 37 as well as SOX9 in hypoxia. When cultured on the 3-dimentional (3D) scaffold TATA-binding protein (TBP) exhibited the highest expression stability with NormFinder while Ribosomal protein L13a (RPL13A) and beta2-microglobulin (B2M) were the most stable using geNorm analysis. In monolayer RPL13A were the most stable gene using NormFinder, while geNorm assessed RPL13A and human RNA polymerase II (RPII) as most stable. When examining the combination of (3D) culturing and monolayer RPL13A and B2M showed the highest expression stability from geNorm analysis while RPL13A also showed the highest expression stability using NormFinder. Often used HKG such as beta actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were the most unstable genes investigated in all comparisons. The pairwise variations for the two most stable HKG in each group were all below the cut-off value of 0.15, suggesting that the two most stable HKG from geNorm analysis would be sufficient for qRT-PCR.All data combined we recommend RPL13A, B2M and RPII as the best choice for qRT-PCR analyses when comparing normoxic and hypoxic cultured human chondrocytes although other genes might also be suitable. However, the matching of HKG to target genes by means of a thorough investigation of the stability in each study would always be preferable.
Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR
DOI:10.1016/j.bbrc.2006.04.140 URL [本文引用: 1]
Validation of reference genes for quantitative gene expression analysis in Auricularia cornea
DOI:10.1016/j.mimet.2019.105658 URL [本文引用: 4]
Validation and comparison of reference genes for qPCR normalization of celery (apium graveolens) at different development stages
Molecular evidence for anamorph determination of Cordyceps sinensis (Berk.) Sacc
Isolation and identification of Ophiocordyceps sinensis asexual stage
The chemical constituents and pharmacological actions of Cordyceps sinensis
Investigation on microcycle conidiation of ascospores and conidiogenous structures of anamorph of Cordyceps sinensis
Reference gene selection for quantitative real-time PCR normalization in tomato subjected to nitrogen, cold, and light stress
DOI:10.1016/j.ab.2009.01.024
PMID:19454243
[本文引用: 1]
We examined eight putative consistently expressed genes-actin (ACT), beta-tubulin, elongation factor 1alpha (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), ribosomal protein L2 (RPL2), ubiquitin (UBI), and a catalytic subunit of protein phosphatase 2A (PP2Acs)-for their potential as references for the normalization of gene expression in tomato leaves. Expression stability of candidate reference genes was tested during growth conditions of nitrogen (N) starvation, low temperature, and suboptimal light. The geNorm algorithm, using reciprocal cross-validation among a larger group of candidate references, was applied for this purpose. The widely used reference genes GAPDH and PGK were top ranked during light stress but poorly ranked during N and cold stress. In contrast, EF1 was top ranked during N and cold stress but poorly ranked during light stress. The novel references RPL2 and PP2Acs, as well as the traditional references ACT and UBI, appeared to be stably expressed when looking at the data set as a whole. No gene was identified that exhibited such a constant level of expression as to outperform the other candidates under all experimental conditions. Thus, the results highlight the need for normalizing gene expression in tomato using the geometric average of multiple carefully selected reference genes.
A jacalin-related lectin regulated the formation of aerial mycelium and fruiting body in Flammulina velutipes
DOI:10.3390/ijms17121884 URL [本文引用: 2]
Microcycle conidiation of Cordyceps sinensis and anamorph isolation
Quantification of mRNA using real-time RT-PCR
DOI:10.1038/nprot.2006.236 URL [本文引用: 1]
A PCR-based quantitative assay for the evaluation of mRNA integrity in rat samples
Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeperExcel-based tool using pair-wise correlations
DOI:10.1023/B:BILE.0000019559.84305.47 URL [本文引用: 2]
Selection and evaluation of appropriate reference genes for RT-qPCR normalization of Volvariella volvacea gene expression under different conditions
Selection of reference gene for quantitative real-time PCR analysis of lignification related genes in postharvest Pleurotus eryngii
Selection and validation of appropriate reference genes for quantitative real-time PCR analysis of gene expression in Lycoris aurea
DOI:10.3389/fpls.2016.00536
PMID:27200013
[本文引用: 1]
Lycoris aurea (L' Hér.) Herb, a perennial grass species, produces a unique variety of pharmacologically active Amaryllidaceae alkaloids. However, the key enzymes and their expression pattern involved in the biosynthesis of Amaryllidaceae alkaloids (especially for galanthamine) are far from being fully understood. Quantitative real-time polymerase chain reaction (qRT-PCR), a commonly used method for quantifying gene expression, requires stable reference genes to normalize its data. In this study, to choose the appropriate reference genes under different experimental conditions, 14 genes including YLS8 (mitosis protein YLS8), CYP2 (Cyclophilin 2), CYP 1 (Cyclophilin 1), TIP41 (TIP41-like protein), EXP2 (Expressed protein 2), PTBP1 (Polypyrimidine tract-binding protein 1), EXP1 (Expressed protein 1), PP2A (Serine/threonine-protein phosphatase 2A), β-TUB (β-tubulin), α-TUB (α-tubulin), EF1-α (Elongation factor 1-α), UBC (Ubiquitin-conjugating enzyme), ACT (Actin) and GAPDH (Glyceraldehyde 3-phosphate dehydrogenase) were selected from the transcriptome datasets of L. aurea. And then, expressions of these genes were assessed by qRT-PCR in various tissues and the roots under different treatments. The expression stability of the 14 candidates was analyzed by three commonly used software programs (geNorm, NormFinder, and BestKeeper), and their results were further integrated into a comprehensive ranking based on the geometric mean. The results show the relatively stable genes for each subset as follows: (1) EXP1 and TIP41 for all samples; (2) UBC and EXP1 for NaCl stress; (3) PTBP1 and EXP1 for heat stress, polyethylene glycol (PEG) stress and ABA treatment; (4) UBC and CYP2 for cold stress; (5) PTBP1 and PP2A for sodium nitroprusside (SNP) treatment; (6) CYP1 and TIP41 for methyl jasmonate (MeJA) treatment; and (7) EXP1 and TIP41 for various tissues. The reliability of these results was further enhanced through comparison between part qRT-PCR result and RNA sequencing (RNA-seq) data. In summary, our results identified appropriate reference genes for qRT-PCR in L. aurea, and will facilitate gene expression studies under these conditions.
Identification of novel and robust internal control genes from Volvariella volvacea that are suitable for RT-qPCR in filamentous fungi
DOI:10.1038/srep29236 URL [本文引用: 1]
Selection of reliable reference genes for gene expression studies in peach using real-time PCR
DOI:10.1186/1471-2199-10-1 URL [本文引用: 1]
Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes
Analysis method of systematically evaluating stability of reference genes using geNorm, NormFinder and BestKeeper
Identification and evaluation of reference genes for qRT-PCR studies in Lentinula edodes
DOI:10.1371/journal.pone.0190226 URL [本文引用: 4]
miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs
DOI:10.1007/s11103-012-9885-2 URL [本文引用: 1]
RAPD and analysis of ITS sequences of Ophiocordyceps sinensis in Gansu
Identification and evaluation of reference genes for qRT-PCR normalization in Ganoderma lucidum
DOI:10.1007/s00284-013-0442-2 URL [本文引用: 4]
Correct assessment of total RNA integrity in Litopenaeus vannamei
Selection of reference genes for qRT-PCR in Morchella esculenta
Screening of reference genes for qRT-PCR amplification in Auricularia heimuer
Selection of reference genes for qRT-PCR in Wolfiporia cocos
Advances in research of the artificial cultivation of Ophiocordyceps sinensis in China
DOI:10.3109/07388551.2013.791245 URL [本文引用: 1]
Validation of reference genes for the determination of platelet transcript level in healthy individuals and in patients with the history of myocardial infarction
DOI:10.3390/ijms14023456 URL [本文引用: 2]
利用geNorm、NormFinder和BestKeeper软件进行内参基因稳定性分析的方法
