LbCML38 and LbRH52, two reference genes derived from RNA-Seq data suitable for assessing gene expression in Lycium barbarum L.

Gong, Lei; Yang, Yajun; Chen, Yuchao; Shi, Jing; Yao, Song; Zhang, Hongxia

doi:10.1038/srep37031

Cited by 14 publications

(6 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both ACT and UBQ are stably expressed in wheat, but not in tomato 24,25 . Gong et al 26 analyzed the expression stability of 18 candidate reference genes of Goji at www.nature.com/scientificreports/ different developmental stages and under drought stress condition. They observed that two novel reference genes LbCML38 and LbRH52 were more stably expressed than the commonly used reference genes.…”

Section: Discussionmentioning

confidence: 99%

Reference gene selection for qRT-PCR analyses of luffa (Luffa cylindrica) plants under abiotic stress conditions

Chen

Wang

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Selecting suitable internal reference genes is an important prerequisite for the application of quantitative real-time PCR (qRT-PCR). However, no systematic studies have been conducted on reference genes in luffa. In this study, seven reference genes were selected, and their expression levels in luffa plants exposed to various simulated abiotic stresses [i.e., cold, drought, heat, salt, H2O2, and abscisic acid (ABA) treatments] were analyzed by qRT-PCR. The stability of the reference gene expression levels was validated using the geNorm, NormFinder, BestKeeper, and RefFinder algorithms. The results indicated that EF-1α was the most stably expressed and suitable reference gene overall and for the heat, cold, and ABA treatments. Additionally, UBQ expression was stable following the salt treatment, whereas TUB was identified as a suitable reference gene for H2O2 and drought treatments. The reliability of the selected reference genes was verified by analyzing the expression of copper/zinc superoxide dismutase (Cu/Zn-SOD) gene in luffa. When the most unstable reference genes were used for data normalizations, the resulting expression patterns had obvious biases when compared with the expression patterns for the most ideal reference genes used alone or combined. These results will be conducive to more accurate quantification of gene expression levels in luffa.

show abstract

Section: Discussionmentioning

confidence: 99%

Reference gene selection for qRT-PCR analyses of luffa (Luffa cylindrica) plants under abiotic stress conditions

Chen

Wang

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…In addition to DEGs, constitutively expressed genes can be used to screen stable expression genes suitable for RT-qPCR. In recent years, RNA-Seq data has been used for the selection and validation of more new stable reference genes in many studies, for example in pregnant woman (Chim et al, 2017), human cancer tissue (MacRae et al, 2013), different Streptomyces coelicolor strains (Li et al, 2015), and different developmental stages and drought stress conditions in Goji (Gong et al, 2016). These studies successfully identified new reference genes which are more stable than the traditionally used ones, indicating that selection of stably expressed reference gene from RNA-Seq data is a powerful and reliable method.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Identification and Evaluation of New Reference Genes for Gene Expression Analysis Under Temperature and Salinity Stresses in Ciona savignyi

Huang

Zhan

2019

Front. Genet.

View full text Add to dashboard Cite

Rapid adaptation/accommodation to changing environments largely contributes to maximal survival of invaders during biological invasions, usually leading to success in crossing multiple barriers and finally in varied environments in recipient habitats. Gene expression is one of the most important and rapid ways during responses to environmental stresses. Selection of proper reference genes is the crucial prerequisite for gene expression analysis using the common approach, real-time quantitative PCR (RT-qPCR). Here we identified eight candidate novel reference genes from the RNA-Seq data in an invasive model ascidian Ciona savignyi under temperature and salinity stresses. Subsequently, the expression stability of these eight novel reference genes, as well as other six traditionally used reference genes, was evaluated using RT-qPCR and comprehensive tool RefFinder. Under the temperature stress, two traditional reference genes, ribosomal proteins S15 and L17 ( RPS15, RPL17 ), and one novel gene Ras homolog A ( RhoA ), were recommended as the top three stable genes, which can be used to normalize target genes with a high and moderate expression level, respectively. Under the salinity stress, transmembrane 9 superfamily member ( TMN ), MOB kinase activator 1A-like gene ( MOB ) and ubiquitin-conjugating enzyme ( UBQ2 ) were suggested as the top three stable genes. On the other hand, several commonly used reference genes such as α-tubulin ( TubA ), β-tubulin ( TubB ) and glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) showed unstable expressions, thus these genes should not be used as internal controls for gene expression analysis. We also tested the expression level of an important stress response gene, large proline-rich protein bag6-like gene ( BAG ) using different reference genes. As expected, we observed different results and conclusions when using different normalization methods, thus suggesting the importance of selection of proper reference genes and associated normalization methods. Our results provide a valuable reference gene resource for the normalization of gene expression in the study of environmental adaptation/accommodation during biological invasions using C. savignyi as a model.

show abstract

“…However, several studies have found that the expression levels of HKGs vary to different degrees based on tissues, developmental stages, or experimental conditions ( Thellin et al, 1999 ; Nicot et al, 2005 ; Wu et al, 2016 ). Therefore, it is necessary to select stably expressed HKGs as RGs before they are used to normalize target gene expression by qRT-PCR ( Guenin et al, 2009 ; Gong et al, 2016 ). Up to date, many HKGs, such as 18S ribosomal RNA ( 18S rRNA ), 28S ribosomal RNA ( 28S rRNA ), β-actin ( ACT ), elongation factor 1-alpha ( EF1A ), glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ), α tubulin ( TUA ), β tubulin ( TUB ), polyubiquitin ( UBQ ), cyclophilin ( CYP ), SAND protein family ( SAND ), malate dehydrogenase ( MDH ), glyceraledehyde-3-phosphate dehydrogenase of plastid 1 ( GAPCP1 ), and so on, have been used to conducted studies for evaluating their stability under different experimental conditions ( Demidenko, Logacheva & Penin, 2011 ; Chen et al, 2015 ; Cao, Wang & Lan, 2016 ; Ferraz Dos Santos et al, 2016 ; Wang et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Reference gene selection for qRT-PCR assays inStellera chamaejasmesubjected to abiotic stresses and hormone treatments based on transcriptome datasets

Liu

Guan

Song

et al. 2018

PeerJ

View full text Add to dashboard Cite

BackgroundStellera chamaejasme Linn, an important poisonous plant of the China grassland, is toxic to humans and livestock. The rapid expansion of S. chamaejasme has greatly damaged the grassland ecology and, consequently, seriously endangered the development of animal husbandry. To draft efficient prevention and control measures, it has become more urgent to carry out research on its adaptive and expansion mechanisms in different unfavorable habitats at the genetic level. Quantitative real-time polymerase chain reaction (qRT-PCR) is a widely used technique for studying gene expression at the transcript level; however, qRT-PCR requires reference genes (RGs) as endogenous controls for data normalization and only through appropriate RG selection and qRT-PCR can we guarantee the reliability and robustness of expression studies and RNA-seq data analysis. Unfortunately, little research on the selection of RGs for gene expression data normalization in S. chamaejasme has been reported.MethodIn this study, 10 candidate RGs namely, 18S, 60S, CYP, GAPCP1, GAPDH2, EF1B, MDH, SAND, TUA1, and TUA6, were singled out from the transcriptome database of S. chamaejasme, and their expression stability under three abiotic stresses (drought, cold, and salt) and three hormone treatments (abscisic acid, ABA; gibberellin, GA; ethephon, ETH) were estimated with the programs geNorm, NormFinder, and BestKeeper.ResultOur results showed that GAPCP1 and EF1B were the best combination for the three abiotic stresses, whereas TUA6 and SAND, TUA1 and CYP, GAPDH2 and 60S were the best choices for ABA, GA, and ETH treatment, respectively. Moreover, GAPCP1 and 60S were assessed to be the best combination for all samples, and 18S was the least stable RG for use as an internal control in all of the experimental subsets. The expression patterns of two target genes (P5CS2 and GI) further verified that the RGs that we selected were suitable for gene expression normalization.DiscussionThis work is the first attempt to comprehensively estimate the stability of RGs in S. chamaejasme. Our results provide suitable RGs for high-precision normalization in qRT-PCR analysis, thereby making it more convenient to analyze gene expression under these experimental conditions.

show abstract

LbCML38 and LbRH52, two reference genes derived from RNA-Seq data suitable for assessing gene expression in Lycium barbarum L.

Cited by 14 publications

References 39 publications

Reference gene selection for qRT-PCR analyses of luffa (Luffa cylindrica) plants under abiotic stress conditions

Reference gene selection for qRT-PCR analyses of luffa (Luffa cylindrica) plants under abiotic stress conditions

Genome-Wide Identification and Evaluation of New Reference Genes for Gene Expression Analysis Under Temperature and Salinity Stresses in Ciona savignyi

Reference gene selection for qRT-PCR assays inStellera chamaejasmesubjected to abiotic stresses and hormone treatments based on transcriptome datasets

Contact Info

Product

Resources

About