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Selection of Reference Genes for Transcriptional Analysis of Edible Tubers of Potato (Solanum tuberosum L.)

  • Roberta Fogliatto Mariot ,

    Contributed equally to this work with: Roberta Fogliatto Mariot, Luisa Abruzzi de Oliveira

    Affiliation Food Science Department, Food Science and Technology Institute, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

  • Luisa Abruzzi de Oliveira ,

    Contributed equally to this work with: Roberta Fogliatto Mariot, Luisa Abruzzi de Oliveira

    Affiliation Genetics Department, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

  • Marleen M. Voorhuijzen,

    Affiliation RIKILT, Wageningen UniversityR, Wageningen, The Netherlands

  • Martijn Staats,

    Affiliation RIKILT, Wageningen UniversityR, Wageningen, The Netherlands

  • Ronald C. B. Hutten,

    Affiliation Plant Breeding, Wageningen UR, Wageningen, The Netherlands

  • Jeroen P. Van Dijk,

    Affiliation RIKILT, Wageningen UniversityR, Wageningen, The Netherlands

  • Esther Kok,

    Affiliation RIKILT, Wageningen UniversityR, Wageningen, The Netherlands

  • Jeverson Frazzon

    jeverson.frazzon@ufrgs.br

    Affiliation Food Science Department, Food Science and Technology Institute, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

Selection of Reference Genes for Transcriptional Analysis of Edible Tubers of Potato (Solanum tuberosum L.)

  • Roberta Fogliatto Mariot, 
  • Luisa Abruzzi de Oliveira, 
  • Marleen M. Voorhuijzen, 
  • Martijn Staats, 
  • Ronald C. B. Hutten, 
  • Jeroen P. Van Dijk, 
  • Esther Kok, 
  • Jeverson Frazzon
PLOS
x

Abstract

Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

Introduction

A wide range of biological processes leads to changes in mRNA transcription levels, and these variations are important to ensure timely cellular responses. Based on this, mRNA transcriptional profiling has become a popular research field in functional genomics studies, as it can be used to evaluate complex regulatory gene networks [13]. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) has been commonly used to analyze gene expression in different organisms and under numerous conditions, since it permits specific and reproducible quantification of nucleic acids [1, 4]. However, the stability of the expressed housekeeping gene is a fundamental factor in the appropriate standard normalization of the data, which is usually normalized to more than one reference gene to avoid differences in complementary DNA (cDNA) quantity, purity, RNA stability, and enzymatic efficiency of cDNA synthesis and subsequent PCR amplifications [56]. The assortment of an appropriate reference gene is an absolute requirement to minimize non-biological variation between samples and achieve precise results [7]; hence, the selection of suitable reference genes is crucial to RT-qPCR analysis. The ideal reference gene would be stably expressed through all examined samples [89].

Many reference genes have already been identified for several crops under different treatments and conditions, particularly for model plants [10]. However, the expression of putative reference genes differs across individual sets of organs and experimental conditions [7, 11]. In this context, several free software packages such as geNorm [12], NormFinder [9] or BestKeeper [13], may be used in order to the best internal controls from a group of candidate normalization genes for a specific set of biological samples.

The goal of this study was to examine by RT-qPCR the stability of ten putative reference genes selected from RNAseq experiments. We have focused the investigation of control genes by evaluating the expression variability of 10 genes with relatively high stability levels in potato tubers.

Materials and Methods

Ethics statements

The field experiments in both years (in this case normal yield trials) were performed on a trial field in the proximity of Wageningen (GPS coordinates: 51.95230, 5.63490) owned by Wageningen UR. No specific permission was required to carry out these potato trials.

Field experimental design

Eight potato edible tubers from four distinct genotypes, experimental lines, obtained in duplicates, one grown in 2011 and the other in 2012, with a post-harvest storage time of 13 and 28 days, and cultivated at Plant Breeding Sciences—Wageningen University and Research Center (WUR)—Wageningen, The Netherlands.

The varieties HZ 94 DTA 11 and RH00-386-2 are diploid, and the varieties RH4X-029-2 and RH4X-036-11 are tetraploid potato breeding clones. Although, all 4 clones have a wild potato species clone as a grandparent, they are all considered and treated as “normal” potatoes (Solanum tuberosum).

All potato samples are listed and detailed on Table 1.

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Table 1. Field information of the eight potato samples used in this study for experimental validation of candidate reference genes.

https://doi.org/10.1371/journal.pone.0120854.t001

Samples preparation

Four average sized tubers were selected; of these, opposite eights were pooled to minimize variation effects in the tuber. Potato tubers were washed in water at room temperature dried with paper and chopped using a food processor into 1 cm3 cubes. Potato cubes were immediately frozen in liquid N2 to avoid tuber oxidation, packed in plastic bags and stored in an ultra-freezer at -80°C. Samples were sent to ZIRBUS Technology, Tiel, The Netherlands, for lyophilisation, milling and vacuum packaging. Potato powder was stored at room temperature until use.

RNA isolation and quality assessment

RNA was isolated from 0.5 g of each freeze-dried sample, according to the hexadecyltrimethylammonium bromide (CTAB) buffer lysis method, followed by chloroform/isoamyl alcohol extraction and overnight precipitation with lithium chloride (LiCl) proposed by van Dijk et al. (2009) [14], with some modifications, as follows. Lysis was performed with the extraction buffer pre-warmed to 60°C before use; the chloroform/isoamyl alcohol extraction was repeated three times before the LiCl precipitation; and the final precipitation with 96% ethanol was performed with the tubes kept on ice and then centrifuged at 4°C for 15 min at 14,000 g. Total RNA isolated was dissolved in 100 μL of 10 mM Tris (pH 7,0) and warmed to 65°C for 10 min. Total RNA was stored at -80°C until use.

RNA purity and concentration were assessed by absorbance measurements using a Nanodrop 1000 instrument (Thermo Fisher Scientific, NanoDrop Technologies Wilmington, DE, USA). For integrity evaluation, 1 μg of RNA was migrated by electrophoresis (10 min at 80 V and 50 min at 100 V) in denaturing agarose gel (1% agarose, 5% formamide, 1X TBE) stained with ethidium bromide. Gels were visualized in Gel Doc XR+ Systems (Bio-Rad Laboratories, Life Technologies Corporation, Carlsbad, CA, USA) and analyzed using Quantity One 1-D (Bio-Rad Laboratories).

Candidate gene selection and primer design

Candidate potato reference genes with stable expression levels in tubers were selected from a large collection of RNAseq profiles generated for 90 potato tubers grown under diverse range of growth conditions, locations, and growth year. Ten potato genes with more than 50 counts per million reads and with lowest interquartile range (IQR) were selected using R version 3.01 [15] for further evaluation with RT-qPCR (Table 2). Information about candidate genes was determined using Ensembl Plant Database (http://plants.ensembl.org/index.html).

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Table 2. Candidate potato reference genes with more than 50 counts per million reads (highest expression), lowest inter quartile ranges (IQRs) and known functions, used for experimental validation.

https://doi.org/10.1371/journal.pone.0120854.t002

Solanum tuberosum genes, cDNA sequences, and exon-intron-exon junctions were also obtained from Ensembl Plant Database. All primers were designed using the Primer Quest tool from IDT DNA (http://www.idtdna.com/primerquest/Home/Index) with melting temperatures between 58°C and 62°C, GC contents from 45 to 65% and amplicon lengths ranging from 75 to 150 bp (Table 2). The Oligo Analyzer software from IDT DNA was also used to infer primer secondary structures (http://www.idtdna.com/analyzer/applications/oligoanalyzer/).

Since 4 out of the 10 candidate genes display alternative splicing (see Table 2), BLAST searches were performed, in order to design oligonucleotides complementary to a region of homology between the different transcripts of a given gene.

To determine PCR efficiencies, standard curves were constructed with four points in five-fold dilutions starting from a 1/5 cDNA concentration (1:5, 1:25, 1:125 and 1:625), according to Perini, et al. (2014) [16] and strongly suggested by Bustin, et al. (2009) [17]. Reaction efficiencies (E) and correlation coefficients (r2) were estimated using StepOne Software v.2.3 (Life Technologies), based on the slopes of the plots and the Cps (crossing points) versus log input of cDNA. E and r2 values for each reaction performed are also presented in Table 2.

Complementary DNA synthesis

Each RNA sample was converted into cDNA in triplicates, as recommended by Bustin, et al. (2009) [17]. One microgram of total RNA was used for synthesis according to the manufacturer´s protocol, using the iScript cDNA Synthesis Kit (BIORAD). Specificity of the primers was checked for the 24 resulting cDNAs by end-point PCR followed by electrophoresis in agarose gel and melting curve analysis. The cDNA samples were stored at -20°C until use.

Quantitative PCR (qPCR)

qPCR chain reactions were carried out in a StepOne Plus Real Time PCR System (Life Technologies) using SYBR Green (BIORAD; 1:10,000 dilution) for monitoring double strand DNA synthesis during qPCR. Reactions were performed in a 20 μL final volume with 10 μL of diluted cDNA (1:50), 0.2 μM of each primer, 0.1 mM of dNTPs, 0.25 units of Platinum Taq DNA Polymerase (Life Technologies) 1X Buffer Solution, and 1.5 mM of MgCl2. Each cDNA was analyzed in four technical replicates, and negative controls were included. PCR cycling conditions were as follows: 94°C for 5 min, 40 cycles at 94°C for 15 seconds, 60°C for 10 seconds, 72°C for 15 seconds and 60°C for 35 seconds, and a final melting curve between 50 and 99°C (Δ0.3°C/s).

Gene expression stability analyses

All results from RT-qPCR were compared using NormFinder [9], geNorm—v. 3.5 [12] software and BestKeeper an Excel-based program [13].

The NormFinder algorithm ranks candidate genes based on their stability of expression and determines the best pair of genes for using as endogenous controls for the samples. geNorm calculates the average expression stability (M-value), defining the mean variation of a certain gene in relation to the other candidate genes. Following, geNorm determines the best number of reference genes through the pairwise variation estimation (V). Vandesompele et al. (2002) [12] suggested a V cut-off value of 0.15, below which the inclusion of an additional reference gene would not be required. Finally, BestKeeper estimates the reference genes with the greatest expression stability by assessing a BestKeeper Index specific for each sample, which is calculated as the geometric mean of the Cp values of its candidate housekeeping genes [13].

Results

RT-qPCR analysis of candidate reference genes

In order to select a reliable set of reference genes for gene expression studies in potato edible tubers, RT-qPCR assays were performed for 10 candidate housekeeping genes. The correlation coefficients (r2) for all resulting amplification curves were higher than 0.99, and all 10 primer pairs allowed amplification efficiencies (E) between 86 and 104.5% (Table 2). Considering the optimal PCR efficiency as 100%, which allows duplication of the whole target cDNA at each PCR cycle during the exponential phase, the observed efficiency values were considered acceptable; hence, the amplification products of each reaction were comparable to each other.

Primers for elongation factor 1 alpha, 18S rRNA [18, 19], and actin [20] genes were initially included in the data set; however, they were discarded from the analysis due to unexpected amplification products.

Next, Cp values [21] were used to analyze the steady state mRNA levels of each candidate gene in eight different potato samples, showing a relative wide range of Cp values (Fig 1). In all tested samples, the lowest mean Cp value was observed for the gene eukaryotic translation initiation factor 3 subunit, followed by exocyst complex component sec3 (SEC3).

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Fig 1. Expression profiles of the tested reference genes in raw Cp values for all 8 samples.

Expression data are displayed as raw Cp values for each reference gene across all samples. The line denotes the median and boxes indicate the 25/75 percentiles.

https://doi.org/10.1371/journal.pone.0120854.g001

Analyses of reference genes stability via geNorm, NormFinder and BestKeeper algorithms

Three different algorithms, NormFinder, geNorm and BestKeeper, were applied in computational assessment of gene expression stability in order to minimize potential biases intrinsic to each software.

NormFinder uses a mathematical modelling that allows an estimation of gene expression based in a variation of reference genes and in a subgroup of sample sets, considering the best genes those with the lowest stability value, with minimal intra and inter group variation, and indicate the best combination of gene pairs groups and subgroups [9]. Table 3 presents the ranking of the candidate reference genes according to their stability value for the samples, as determined by NormFinder. This algorithm identified C2, followed by SEC3, as the most stably expressed genes in all 8 different samples.

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Table 3. Ranking of candidate reference genes according to the estimated values of stability of expression, as calculated by the NormFinder algorithm and M value calculated using geNorm estimated M–values, for the candidate reference genes.

https://doi.org/10.1371/journal.pone.0120854.t003

Table 3 describes the ranking of candidate genes as assessed by geNorm. Also, pairwise variations (V) were calculated for obtaining the optimal number of normalization factors and the use of 2 primer pairs were definitively enough for this dataset. Fig 2 shows the M-values and pairwise variation (V) calculated by geNorm for all candidates and their best partners for the potato samples. The most stable candidate gene was C2, followed by ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A), with M-values above 0.7 for both. In agreement, the best gene pair consisted also of the C2 and CUL3A (see Fig 2). Additionally, the V-values were below the established 0.15 threshold suggested by Vandesompele et al. (2002) [12], corroborating that the inclusion of an additional gene is not required for data normalization.

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Fig 2. Average values of stability of gene expression for the selected reference genes assessed by geNorm.

The plots indicate expression profiles and the determination of the optimal number of control genes for the eight samples.

https://doi.org/10.1371/journal.pone.0120854.g002

According to the BestKeeper algorithm, the importin subunit alpha and ubiquitin-associated/ts-n domain-containing protein genes were the most stably expressed ones in S. tuberosum edible tubers across all eight samples, with a standard deviation (SD) of 0.66 for both candidates (Table 4). Only 3-oxoacyl-(acyl-carrier protein) reductase and dck/dgk-like deoxyribonucleoside kinase (less stable) were considered to be inconsistent for BestKeeper quality parameters ([±Cp] > 1.00), with SDs 1.01 and 3.05, respectively.

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Table 4. Descriptive statistics of candidate reference gene expression patterns, as measured by BestKeeper.

https://doi.org/10.1371/journal.pone.0120854.t004

Discussion

Recently, the quantification of RNA transcripts has become increasingly rapid and precise due to advances in gene quantification strategies. Associated with that, newly identified reference genes showing more stable expression patterns than traditional normalization genes have been reported by analyzing microarray and transcriptome sequencing data [2223], and these high throughput techniques might be excellent potential sources of good candidate reference genes, as showed in the present work.

The accuracy of RT-qPCR results is highly dependent on a reliable normalization strategy that employs an invariant (i.e. stably expressed) reference gene [2425]. For example, Nicot et al. (2005) and Lopez-Pardo, Ruiz de Galarreta and Ritter (2013) [18, 19] already performed this analysis testing several reference genes, including the elongation factor 1 alpha, with successfully results. Different of our data, the analysis was based on candidates chosen from the literature, not on gene expression experiments, such as microarray or RNAseq. In addition, Nicot et al. (2005) [18] did not use samples derived from edible tubers, but samples from a pool of all parts of the potato plant, both under biotic and abiotic stresses, without any distinction between different plant organs. Still, Lopez-Pardo, Ruiz de Galarreta and Ritter (2013) [19] used potato edible tubers as samples, but specifically under cold stress.

It has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions. For instance, the expression of the so-called ‘housekeeping’ genes, although constant under some experimental conditions, can vary considerably in other cases, implying that the stability of the proposed control gene has to be tested before each new experiment [7, 10, 11, 16, 2628]. Normalization with multiple reference genes is becoming a common practice and the gold standard for the technique, but reports that identify such genes in plant investigations are still limited [7, 16, 18, 2841].

In the present work we evaluated by RT-qPCR 10 reference genes displaying relatively stable expression in edible tubers. Results obtained by geNorm and NormFinder were very similar to each other and more different than those obtained by BestKeeper. While the geNorm and NormFinder algorithms correct for inter-sample variations, BestKeeper does not regard differences in RNA quality or cDNA conversion efficiency across samples, which might influence the distinct findings observed here. Differently from the pairwise approach used by geNorm, NormFinder selects the top rank candidates with minimal variation rather than correlated expression, which is less influenced by co-regulated genes. Moreover, NormFinder takes into consideration systematic differences between sample subgroups [9, 1213]. Hence, it is expected that the comparison of these three algorithms, as performed here, might provide a more reliable set of reference genes under specific experimental conditions. In this sense, our study provides evidence for the use of certain genes as normalizers in gene expression experiments for potato edible tubers, which is essential for obtaining accurate and reliable gene expression data profiles.

From our analysis three genes called SEC3, CUL3A and C2 were selected as the best normalizers in gene expression of potato edible tubers. However, for each set of samples a validation are needed, and the best reference gene may be different, this could be observed in this present work that the rank for ten candidates to be reference genes for our 8 samples were not exactly the same order of the rank as RNAseq database.

The gene SEC3 as well as SEC5, SEC6, SEC8, SEC10, SEC15, EXO70, and EXO84 genes are part of an evolutionarily conserved octameric protein complex of secretory vesicles [4243]. The Arabidopsis genome encodes single or multiple isoforms of all exocyst subunits [44], and homologous structural models of plant exocyst subunits indicate well conserved rod-like structural features, including putative phosphatidylinositol phosphate binding sites on SEC3 and EXO70 subunits. Through interaction with RAB and RHO GTPases, these proteins are known to be crucial for the proper targeting of the exocyst to membranes [45].

The CUL3 gene is a constituent of ubiquitin ligase complexes [40]. In Arabidopsis, both CUL3A and CUL3B proteins interact with the RING-H2 finger protein RBX1 and with several members of plant BTB domain proteins [4647], suggesting that they form similar CUL3-based E3 complexes. However, cul3a loss-of-function mutants are viable and fertile, exhibiting only slightly delayed flowering and reduced sensitivity to far red light [46]. This viability might be attributed to functional redundancy between the two CUL3 genes in Arabidopsis, since disruption of both genes causes embryo lethality, indicating that CUL3 plays important roles during early steps of plant development [4849]. Indeed, CUL3 seems to regulate the ethylene-independent distal root patterning and primary root growth by a novel ethylene-dependent pathway, thus implicating CUL3 in the division and organization of the root stem cell niche and columella root cap cells [50].

Finally, the gene that is referred to in the EnsemblPlants database and hence in this paper as C2 is actually coding for a yet uncharacterized protein, designated M1C6S3_SOLTU in the UniProt database (http://www.uniprot.org/uniprot/M1C6S3). In this entry it is mentioned that the protein contains three C2 domains. The C2 domain polypeptide is one of the most prevalent eukaryotic lipid-binding domains used in diverse functional contexts. This structural domain helps target proteins to cell membranes, and its typical version (PKC-C2) has a beta-sandwich conformation composed of 8 β-strands that co-ordinate two or three calcium ions, which bind in a cavity formed by the first and final loops of the domain on the membrane binding face [5051].

Conclusions

Transcriptome data such as those obtained from microarray and RNAseq experiments provide an excellent resource of selecting candidate RT-qPCR reference genes. Here, through bioinformatics and experimental data, we show the selection and validation of ten putative reference genes for RT-qPCR studies in potato samples. The C2, SEC3, and CUL3A genes were found to be the most stable and suitable normalizers for potato edible tubers expression studies. In summary, these findings provide useful tools for the normalization of RT-qPCR experiments and will enable more accurate and reliable gene expression studies related to functional genomics in potato.

Acknowledgments

We would like to thanks M.Sc. Eduardo Preusser de Mattos for critical english review of the manuscript.

Author Contributions

Conceived and designed the experiments: EK JF. Performed the experiments: RFM LAO MS RH. Analyzed the data: RFM LAO MS JPVD. Contributed reagents/materials/analysis tools: RFM MMV. Wrote the paper: RFM LAO.

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