Selection and Validation of Appropriate Reference Genes for Quantitative RT-PCR Analysis in Rubia yunnanensis Diels Based on Transcriptome Data

Abstract

Real-time quantitative polymerase chain reaction (RT-qPCR) has been widely applied in gene expression and transcription abundance analysis because of its high sensitivity, good repeatability, and strong specificity. Selection of relatively stable reference genes is a precondition in order to obtain the reliable analysis results. However, little is known about evaluation of a set of reference genes through scientific experiments in Rubia plants. Here, 15 candidate reference genes were selected from R. yunnanensis transcriptome database and analyzed under abiotic stresses, hormone treatments, and different tissues. Among these 15 candidate reference genes, heterogeneous nuclear ribonucleoprotein (hnRNP), TATA binding protein (TBP), ribosomal protein L5 (RPL5), malate dehydrogenase (MDH), and elongation factor 1-alpha (EF-1α) were indicated as the five most stable reference genes by four statistical programs (geNorm, NormFinder, BestKeeper, and RefFinder). Ultimately, the validity of reference genes was confirmed by normalizing the expression of o-succinylbenzoate-CoA ligase (OSBL) and isochorismate synthase (ICS) involved in the anthraquinone biosynthesis pathway in different tissues and hormone treatments. Meanwhile, four other putative genes involved in the anthraquinone biosynthesis pathway were also normalized with the selected reference genes, which showed similar expression levels with those given by transcriptome data. This work is the first research that aims at a systematic validation on the stability of reference genes selected from R. yunnanensis transcriptome data and will be conducive to analyze gene expression in R. yunnanensis or other Rubia species.

Identification of Reference Genes for RT-qPCR Analysis in Gleditsia microphylla under Abiotic Stress and Hormone Treatment

“…However, no universal reference genes for normalization using RT-qPCR have been discovered, making it particularly important to find proper reference genes when working with tissues of different histological origin or under different conditions. Owning to the absence of reports on reference genes in G. microphylla , twelve housekeeping genes ( TBP1 , CBP20 , TIP41 , EF-1α , EIF4A1 , PTB1 , ACT1 , ACT7 , GAPA , GAPB , TUB1 , and eIF2 ) were selected from our transcriptome datasets for evaluation according to the literature [ 20 , 34 , 35 , 36 , 37 , 38 , 39 ]. Among the designed primer pairs for all the candidate reference genes, ten presented high specificity and PCR efficiency, indicating that they could be used in RT-qPCR analysis ( Table S1 ); and two, TIP41 (86.90%) and ACT1 (87.90%), were not further analyzed until higher-efficiency primer pairs were redesigned.…”

“…Several statistical algorithms such as geNorm [ 15 , 16 ], NormFinder [ 17 ], BestKeeper [ 18 ], and RefFinder [ 19 ] have emerged for screening stable internal reference genes for RT-qPCR normalization. Many novel reference genes have been identified and validated by employing these programs in different plants, such as Rubia yunnanensis [ 20 ], Schima superba [ 21 ], and Piper species [ 22 ].…”

De Novo Transcriptome Analysis Reveals Putative Genes Involved in Anthraquinone Biosynthesis in Rubia yunnanensis

“…Each PCR reaction was repeated in three biological and technical replicates. The relative quantification of gene expression was computed using the 2 −ΔΔCt method [ 39 ] and normalized to the expression of hnRNP and TBP , the two most stable genes in R. yunnanensis at the different treatments [ 40 ].…”

“…The following supporting information can be downloaded at: , Figure S1: Chemical structures of six anthraquinones and two naphthoquinones isolated from R. yunnanensis , Figure S2: Length distribution of the assembled R. yunnanensis transcripts, Figure S3: GO classification of R. yunnanensis assembled transcripts, Figure S4: KEGG classification of assembled transcripts from R. yunnanensis , Figure S5: Number of differentially expressed genes (DEGs) in the samples between roots (R) and a mixture of stems and leaves (SL) of R. yunnanensis , Figure S6: RT-qPCR validation of the expression levels of six putative key genes involved in anthraquinone biosynthesis pathways [ 40 ], Figure S7: Contents of anthraquinones and naphthoquinones in the hairy roots of R. yunnanensis after 1, 6, 12, and 24 h’s MeJA treatment, Table S1: RNA in roots (R), a mixture of stems and leaves (SL) of R. yunnanensis , Table S2. The sequences of the primers for 15 genes involved in anthraquinone biosynthesis, Table S3: A summary of raw data, Table S4: Statistics of transcript assembly, Table S5: Transcripts associated with ubiquinone and terpenoid-quinone biosynthesis according to the KEGG pathway mapping, Table S6: Correlation values between 15 genes involved in the anthraquinone biosynthesis and the contents of six anthraquinones and two naphthoquinones.…”

Sequencing of the complete chloroplast genome of Rubia yunnanensis Diels and its phylogenetic analysis

“…Its dried roots and rhizomes named ‘Xiaohongshen,’ is a traditional Chinese medicine for treating vertigo, insomnia, rheumatism, tuberculosis, menstrual disorders, and contusions (Yi et al. 2020 ). This species is used as a local alternative for R. cordifolia listed in Chinese Pharmacopeia.…”