Selection and evaluation of reference genes for qRT-PCR analysis in Euscaphis konishii Hayata based on transcriptome data

Tiger nut (Cyperus esculentus), a perennial C4 plant of the Cyperaceae family, is an unconventional crop that is distinguished by its oil-rich tubers, which also possesses the advantages of strong resistance, wide adaptability, short life periods, and large biomass. To facilitate studies on gene expression in this species, we identified and validated a series of reference genes (RGs) based on transcriptome data, which can be employed as internal controls for qRT-PCR analysis in tiger nut. Fourteen putative candidate RGs were identified and evaluated across nine different tissues of two cultivars, and the RGs were analyzed using three different algorithms (geNorm, NormFinder, and BestKeeper). The stability rankings of the candidate RGs were merged into consensus lists with RankAggreg. For the below-ground storage organ of tiger nut, the optimal RGs were TUB4 and UCE2 in different developmental stages of tubers. UCE2 and UBL5 were the most stably expressed RGs among all tissues, while Rubisco and PGK exhibited the lowest expression stability. UCE2, UBL5 and Rubisco were compared to normalize the expression levels of the caleosin (CLO) and diacylglycerol acyltransferase 2-2 (DGAT2-2) genes across the same tissues. Our results showed that the RGs identified in this study, which exhibit more uniform expression patterns, may be utilized for the normalization of qRT-PCR results, promoting further research on gene expression in various tissues of tiger nut.

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Choice of a Stable Set of Reference Genes for qRT-PCR Analysis in Amblyomma maculatum (Acari: Ixodidae)

Journal of Medical Entomology ◽

10.1603/me12123 ◽

2012 ◽

Vol 49 (6) ◽

pp. 1339-1346 ◽

Cited By ~ 15

Author(s):

Rebecca Browning ◽

Steven Adamson ◽

Shahid Karim

Keyword(s):

Reference Genes ◽

Stable Set ◽

Pcr Analysis ◽

Amblyomma Maculatum ◽

Qrt Pcr

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Validation of reference genes for qRT-PCR analysis in peel and flesh of six apple cultivars (Malus domestica) at diverse stages of fruit development

Scientia Horticulturae ◽

10.1016/j.scienta.2018.09.033 ◽

2019 ◽

Vol 244 ◽

pp. 165-171 ◽

Cited By ~ 5

Author(s):

Lifang Zhu ◽

Chengquan Yang ◽

Yaohua You ◽

Wei Liang ◽

Nannan Wang ◽

...

Keyword(s):

Malus Domestica ◽

Fruit Development ◽

Reference Genes ◽

Pcr Analysis ◽

Qrt Pcr ◽

Apple Cultivars

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Comparison of Reliable Reference Genes Following Different Hormone Treatments by Various Algorithms for qRT-PCR Analysis of Metasequoia

International Journal of Molecular Sciences ◽

10.3390/ijms20010034 ◽

2018 ◽

Vol 20 (1) ◽

pp. 34 ◽

Cited By ~ 3

Author(s):

Jing-Jing Wang ◽

Shuo Han ◽

Weilun Yin ◽

Xinli Xia ◽

Chao Liu

Keyword(s):

Gene Expression ◽

Reference Genes ◽

Elongation Factor ◽

Pcr Analysis ◽

Qrt Pcr ◽

Gene Normalization ◽

Accurate Normalization ◽

Suitable Reference ◽

Different Tissues ◽

Gene Expression Levels

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is the most sensitive technique for evaluating gene expression levels. Choosing appropriate reference genes for normalizing target gene expression is important for verifying expression changes. Metasequoia is a high-quality and economically important wood species. However, few systematic studies have examined reference genes in Metasequoia. Here, the expression stability of 14 candidate reference genes in different tissues and following different hormone treatments were analyzed using six algorithms. Candidate reference genes were used to normalize the expression pattern of FLOWERING LOCUS T and pyrabactin resistance-like 8. Analysis using the GrayNorm algorithm showed that ACT2 (Actin 2), HIS (histone superfamily protein H3) and TATA (TATA binding protein) were stably expressed in different tissues. ACT2, EF1α (elongation factor-1 alpha) and HIS were optimal for leaves treated with the flowering induction hormone solution, while Cpn60β (60-kDa chaperonin β-subunit), GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and HIS were the best reference genes for treated buds. EF1α, HIS and TATA were useful reference genes for accurate normalization in abscisic acid-response signaling. Our results emphasize the importance of validating reference genes for qRT-PCR analysis in Metasequoia. To avoid errors, suitable reference genes should be used for different tissues and hormone treatments to increase normalization accuracy. Our study provides a foundation for reference gene normalization when analyzing gene expression in Metasequoia.

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Selection of Reference Genes for qRT-PCR Analysis of Gene Expression in Stipa grandis during Environmental Stresses

PLoS ONE ◽

10.1371/journal.pone.0169465 ◽

2017 ◽

Vol 12 (1) ◽

pp. e0169465 ◽

Cited By ~ 6

Author(s):

Dongli Wan ◽

Yongqing Wan ◽

Qi Yang ◽

Bo Zou ◽

Weibo Ren ◽

...

Keyword(s):

Gene Expression ◽

Reference Genes ◽

Environmental Stresses ◽

Pcr Analysis ◽

Qrt Pcr ◽

Selection Of

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Selection of reference genes for qRT-PCR analysis of gene expression in sea cucumber Apostichopus japonicus during aestivation

Chinese Journal of Oceanology and Limnology ◽

10.1007/s00343-015-4004-2 ◽

2014 ◽

Vol 32 (6) ◽

pp. 1248-1256 ◽

Cited By ~ 9

Author(s):

Ye Zhao ◽

Muyan Chen ◽

Tianming Wang ◽

Lina Sun ◽

Dongxue Xu ◽

...

Keyword(s):

Gene Expression ◽

Reference Genes ◽

Sea Cucumber ◽

Apostichopus Japonicus ◽

Pcr Analysis ◽

Qrt Pcr ◽

Selection Of

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Reference gene selection and evaluation for expression analysis using qRT-PCR in Galeruca daurica (Joannis)

Bulletin of Entomological Research ◽

10.1017/s0007485316000948 ◽

2016 ◽

Vol 107 (3) ◽

pp. 359-368 ◽

Cited By ~ 12

Author(s):

Y. Tan ◽

X.-R. Zhou ◽

B.-P. Pang

Keyword(s):

Reference Gene ◽

Reference Genes ◽

Target Genes ◽

Gene Selection ◽

Developmental Stages ◽

Pcr Analysis ◽

Experimental Conditions ◽

Reference Gene Selection ◽

Functional Studies ◽

Qrt Pcr

AbstractQuantitative real-time PCR (qRT-PCR) has been used extensively to analyze gene expression and decipher gene function. To obtain the optimal and stable normalization factors for qRT-PCR, selection and validation of reference genes should be conducted in diverse conditions. In insects, more and more studies confirmed the necessity and importance of reference gene selection. In this study, eight traditionally used reference genes in Galeruca daurica (Joannis) were assessed, using qRT-PCR, for suitability as normalization genes under different experimental conditions using four statistical programs: geNorm, Normfinder, BestKeeper and the comparative ΔCt method. The genes were ranked from the most stable to the least stable using RefFinder. The optimal suite of recommended reference genes was as follows: succinate dehydrogenase (SDHA) and tubulin-alpha (TUB-α) for temperature-treated larvae; ribosomal protein L32, SDHA and glutathione S-transferase were best for all developmental stages; ACT and TUB-α for male and female adults; SDHA and TUB-α were relatively stable and expressed in different tissues, both diapause and non-diapause adults. Reference gene evaluation was validated using expression of two target genes: the P450 CYP6 gene and the heat shock protein gene Hsp70. These results confirm the importance of custom reference gene selection when studies are conducted under diverse experimental conditions. A standardized qRT-PCR analysis procedure for gene functional studies is provided that could be useful in studies on other insect species.

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Identification of Reference Genes for qRT-PCR Analysis in Yesso Scallop Patinopecten yessoensis

PLoS ONE ◽

10.1371/journal.pone.0075609 ◽

2013 ◽

Vol 8 (9) ◽

pp. e75609 ◽

Cited By ~ 32

Author(s):

Liying Feng ◽

Qian Yu ◽

Xue Li ◽

Xianhui Ning ◽

Jing Wang ◽

...

Keyword(s):

Reference Genes ◽

Pcr Analysis ◽

Patinopecten Yessoensis ◽

Qrt Pcr ◽

Yesso Scallop

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Evaluation of potential reference genes for quantitative RT-PCR analysis in spotted sea bass (Lateolabrax maculatus) under normal and salinity stress conditions

PeerJ ◽

10.7717/peerj.5631 ◽

2018 ◽

Vol 6 ◽

pp. e5631 ◽

Cited By ~ 14

Author(s):

Haolong Wang ◽

Haishen Wen ◽

Yun Li ◽

Kaiqiang Zhang ◽

Yang Liu

Keyword(s):

Salinity Stress ◽

Reference Genes ◽

18S Rrna ◽

Sea Bass ◽

Stress Conditions ◽

Pcr Analysis ◽

Stable Gene ◽

Qrt Pcr ◽

Lateolabrax Maculatus ◽

Suitable Reference

The aim of this study was to select the most suitable reference genes for quantitative real-time polymerase chain reaction (qRT-PCR) of spotted sea bass (Lateolabrax maculatus), an important commercial marine fish in Pacific Asia, under normal physiological and salinity stress conditions. A total of 9 candidate reference genes (HPRT, GAPDH, EF1A, TUBA, RPL7, RNAPol II, B2M, ACTB and 18S rRNA) were analyzed by qRT-PCR in 10 tissues (intestine, muscle, stomach, brain, heart, liver, gill, kidney, pectoral fins and spleen) of L. maculatus. Four algorithms, geNorm, NormFinder, BestKeeper, and comparative ΔCt method, were used to evaluate the expression stability of the candidate reference genes. The results showed the 18S rRNA was most stable in different tissues under normal conditions. During salinity stress, RPL7 was the most stable gene according to overall ranking and the best combination of reference genes was RPL7 and RNAPol II. In contrast, GAPDH was the least stable gene which was not suitable as reference genes. The study showed that different algorithms might generate inconsistent results. Therefore, the combination of several reference genes should be selected to accurately calibrate system errors. The present study was the first to select reference genes of L. maculatus by qRT-PCR and provides a useful basis for selecting the appropriate reference gene in L. maculatus. The present study also has important implications for gene expression and functional genomics research in this species or other teleost species.

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Selection of Reference Genes for qRT-PCR in Bletilla striata under Heat Stress

International Journal of Agriculture and Biology ◽

10.17957/ijab/15.1700 ◽

2021 ◽

Vol 25 (03) ◽

pp. 547-554

Author(s):

Fang Liang

Keyword(s):

Internal Control ◽

Reference Genes ◽

Elongation Factor ◽

Pcr Analysis ◽

Bletilla Striata ◽

Traditional Chinese Herbal Medicine ◽

Qrt Pcr ◽

Wide Range ◽

Root Tuber ◽

Different Tissues

Bletilla striata (Thunb.) Reihb.f., a traditional Chinese herbal medicine, has attracted increasing attention because of its wide range of applicability to the medical field and chemical industry. B. striata has been identified to be particularly sensitive to high temperatures. Thus, the study of temperature stress on gene transcription is of interest in the field. Use of reliable reference genes is essential for qRT-PCR analysis of genes. However, little information regarding suitable reference genes for the genus Bletilla has been published. In this study, the sequences of seven potential reference genes in B. striata were obtained via a homology cloning strategy. These genes were as follows: glyceraldehydes-3-phosphate dehydrogenase (GAPDH), 18S ribosomal RNA (18S), elongation factor 1 alpha (EF1α), α-tubulin (TUA), β-tubulin (TUB), ubiquitin (UBI), and NAC domain protein (NAC). We then evaluated the stability levels of these transcripts in different tissues (root, tuber, and leaf) exposed to high temperature using three conventional software and comprehensive RefFinder algorithms. The results indicated that 18S and TUB were the best internal control genes among different periods of heat treatment and that a combination of 18S and UBI was the best in different tissues. Altogether, 18S and UBI were identified to be the best reference genes for all the samples, while NAC and TUA were the least stable reference genes. The results will be useful for studies on target gene expression in plants of the Bletilla genus. © 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers © 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers© 2021 Friends Science Publishers©

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