Identification and evaluation of internal control genes for gene expression studies by real-time quantitative PCR normalization in different tissues of Tuberose (Polianthes tuberosa)

Scientia Horticulturae 194 (2015) 63–70

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Identification and evaluation of internal control genes for gene expression studies by real-time quantitative PCR normalization in different tissues of Tuberose (Polianthes tuberosa) Madhavan Jayanthi 1 , Nagavara Prasad Gantasala 1 , Pradeep Kumar Papolu, Prakash Banakar, Chanchal Kumari, Uma Rao ∗ Division of Nematology, Indian Agricultural Research Institute, New Delhi, India

a r t i c l e

i n f o

Article history: Received 23 March 2015 Received in revised form 28 July 2015 Accepted 29 July 2015 Keywords: RT-qPCR Reference genes Tuberose (Polianthes tuberosa) Gene expression Normalization

a b s t r a c t Quantitative real time PCR has become the most popular method to study the gene expression due to its accuracy. However the expression level of the target gene may be misunderstood due to the unstable expression of the reference genes under different experimental conditions. Therefore, it is a prerequisite to identify and validate the reference genes in each species for gene expression analysis. Polianthes tuberosa, a very popular commercial flowering crop globally, lacks information on any such reference genes. In this study, we describe the first systematic evaluation of four conventional candidate reference genes; 18S ribosomal RNA (18S rRNA), Ribulose bisphosphate (RuBP), Glyceraldehyde 3 phosphate dehydrogenase (GAPDH), Actin and four novel genes; Coatomer subunit delta (CSD), Peptidyl-prolyl isomerase (PPI), Serine/threonine-protein phosphatase, (STPP) and ATP synthase E-subunit (ATP SE) in tuberose. The transcript abundance of these genes was analyzed in eleven different tissues like young leaf, leaf sheath, root, immature flower bud, mature flower bud, open flower, stamen, ovary, stigma, petals and flower tube. Three RT-qPCR statistical analysis methods, BestKeeper, NormFinder and geNorm were used to evaluate the stability of gene expression that indicated expression of PPI and CSD to be most stable across all the tested tissues. The stability of these two genes was also confirmed across four popular commercial varieties and under biotic and abiotic stresses. Utility of PPI in tuberose as a reference gene is a pioneer report in plants whereas, usefulness of CSD as a stable reference gene has been demonstrated for the first time in a crop besides the model plant, Arabidiopsis. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Tuberose (Polianthes tuberosa) is an ornamental bulbous plant native of Mexico. Its flower has a beautiful fragrance which is active at night when it blooms. Due to this, it is known as “Night Queen” or “Mistress of the Night”. The genus Polianthes has 13 species out of which the most commercially popular is Polianthes tuberosa. The tuberose occupies a very selective and special position among the ornamental bulbous plants for its attractive beauty, elegance and sweet pleasant fragrance and the long spikes of the flower are excellent for cut flowers. The loose flowers are the source of tuberose oil and thus it has a great economic potential for both cut-flower trade and essential oil industry. Tuberose oil is one of the most

∗ Corresponding author: Fax: +91 11 25846400. E-mail address: [email protected] (U. Rao). 1 First authors. http://dx.doi.org/10.1016/j.scienta.2015.07.042 0304-4238/© 2015 Elsevier B.V. All rights reserved.

sought after and expensive perfumery raw materials. It belongs to the family of Amaryllidaceae to which the prominent members like Narcissus (daffodils) and Galanthus (snow drops) belong to. In spite of its considerable industrial importance, genomic information on tuberose is very scarce. Though there has been several reports of reference genes from other flowering crops like, chrysanthemum (Fu et al., 2013), cineraria (Gopaulchan et al., 2013), phelanopsis (Yuan et al., 2014) and anthurium (Fu et al., 2013), there is none on tuberose or any other species in the family of Amaryllidaceae. To initiate gene expression studies in this crop we need to make use of quantitative real-time PCR (RT-qPCR) which has been widely used to analyze expression of candidate genes. Northern Blotting, microarray and RT-qPCR are some of the techniques commonly used to study gene expression under different experimental conditions. Among these, RT-qPCR is one of the most widely used methods for gene expression analysis due to its sensitivity, accuracy and reliability (Bin et al., 2012; Dheda et al., 2005; Gachon et al., 2004; Gantasala et al., 2013; Ginzinger,

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Fig. 1. Different tuberose plant tissues used for RT-qPCR. (A) Immature flower bud, (B) open flower, (C) mature flower bud, (D) flower tube, (E) petals, (F) stamen, (G) stigma and ovary, (H) young leaf, (I) leaf sheath, (J) root, (K) tuberose plant.

2002; Weis et al., 1992). Some low copy number genes express at such minute level that no such method except RT-qPCR can detect expression accurately (Kumar et al., 2011). Several variables must be considered while using RT-qPCR to analyse gene expression like RNA quality, cDNA quality, quantity and quality of source material, amplification efficiency and use of endogenous control genes. Among these factors, the use of appropriate and stable reference genes for the normalization of gene expression is the most important prerequisite for reliable results in any RT-qPCR analysis. Most of these genes are housekeeping genes which are essential for the maintenance of cellular function and vitality and hence ideally they should be stably expressed in all tissues and cells but in practice we find that their levels are influenced by tissue types, developmental stages and experimental conditions (Gadkar and Filion, 2015). Initially, various traditional reference such as tubulin (alpha or beta), ribosomal units (18 or 28 s rRNA) and ubiquitin (UBQ), GAPDH etc., were widely used as reference or internal control genes to normalize RT-qPCR data (Kumar et al., 2011). However, several studies have indicated that some of these well known reference genes are inappropriate for normalization due to expression variability (Czechowski et al., 2005; Remans et al., 2008; Schmittgen and Zakrajsek, 2000). Kumar et al., (2011) have reported that in recent times, several novel reference genes are being used to overcome the limitations posed by traditional reference genes. Techniques like microarray analysis have facilitated this process. It has been reported that microarray analysis for different experimental conditions across different tissues in Arabidopsis (Czechowski et al., 2005) and barley (Faccioli et al., 2007) have provided a number of novel reference genes which may replace the traditional reference genes in future.

Gene expression maps have been developed for model plants like Arabidopsis thaliana (Schmid et al., 2005), Medicago sativa (Benedito et al., 2008), rice (Wang et al., 2010), soyabean (Libault et al., 2010) and maize (Sekhon et al., 2011) and these are publicly accessible. This has made it easy to access candidate reference gene sequences for these plants and also for genomes to which these plants share sequence homology. But for non model crops like tuberose belonging to Amaryllidaceae, an empirical analysis of potential candidate genes has to be undertaken prior to commencing any expression analysis studies. Several statistical alogirthms have been used to validate the expression stability of candidate reference genes like geNorm (Vandesompele et al., 2002), Best keeper (Pfaffl et al., 2004) and NormFinder (Andersen et al., 2004). These have been evaluated for the selection of suitable reference genes for normalizations of RT-qPCR data. This approach based on different statistical algorithms using multiple reference genes is the best strategy for normalization of RT-qPCR (Li et al., 2014a; Lopez-Pardo et al., 2013; Pollier et al., 2014; Wu et al., 2012). Such validated information on suitable reference genes for gene expression analysis in tuberose is lacking. In this study, we report for the first time the identification of the reference genes in tuberose, followed by isolation, cloning, characterization and stability analysis which will form the basis for any kind of gene expression studies in this crop. The genes which have been selected for the study are 18S ribosomal RNA (18S rRNA), ribulose bisphosphate (RuBP), glyceraldehyde 3 phosphate dehydrogenase (GAPDH), actin, coatomer subunit delta (CSD), peptidyl prolyl isomerase subunit (PPI), serine/threonine-protein phosphatase, (STPP) and ATP subunit (ATP SE). The stability of selected genes were also analysed from tissues collected from dif-

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ferent sources including four different varieties and from plants exposed to abiotic and biotic stresses. 2. Material and methods 2.1. Plant materials, varieties and growth conditions Three biological replicates of different tissues like young leaf, leaf sheath, root, immature flower bud, mature flower bud, open flower, Stamen, ovary, stigma, petals and flower tube (Fig. 1) were collected from fully grown flowering plants of tuberose from the fields at the Indian Agricultural Research Institute and were immediately frozen in liquid nitrogen and stored at −80 ◦ C and RNA was extracted within 24 h. For validation experiments in tuberose varieties, leaves of four popular Indian varieties, Vaibhav, Shrinagar, Phule Rajini and Subhasini grown under green house conditions of Indian Agricultural Research Institute, New Delhi were collected and and were immediately frozen in liquid nitrogen and stored at −80 ◦ C and RNA was extracted within 24 h. For validation of the shortlisted reference genes in root knot nematode (Meloidogyne incognita) challenged tuberose plants of variety Vaibhav, the roots of 15 days old plants were inoculated with approximately 300 freshly hatched infective second stage juveniles of M. incognita. The nematode inoculated plants were grown in a growth chamber for 30 days where the temperature, relative humidity and photoperiod was maintained at 27 ◦ C, 70% and 16 h light and 8 h dark conditions respectively. This facilitated the nematodes to complete the lifecycle. Subsequently, the leaves were removed and were immediately frozen in liquid nitrogen and stored at −80 ◦ C and RNA was extracted within 24 h and used for further real time PCR to study the expression of the selected genes. Similarly the shortlisted reference genes were also validated for abiotic stress by exposing the tuberose seedlings to salt. Salt stress was induced by exposing the seedlings for 6 h to MS nutrient solution containing 10, 50, 100, 200 and 500 mM NaCl. After this period, the leaves were collected and were immediately frozen in liquid nitrogen and stored at −80 ◦ C and RNA was extracted within 24 h for studying the expression of the selected genes. 2.2. RNA extraction and cDNA synthesis Total RNA was extracted from all the tissues collected by using NucleoSpin total RNA Kit (Macherey–Nagel, Germany) and treated with rDNAse enzyme to avoid genomic DNA contamination. The RNA quality and quantity was assessed using Nanodrop ND-2000 spectrophotometer (Thermo Scientific) and Agilent 2100 Bioanalyzer with RNA 6000 nanokit (Agilent Technologies). RNA with an RNA integrity number (RIN) of 8.0 was used for cDNA synthesis. One ␮g of total RNA sample was reverse transcribed to cDNA by using cDNA synthesis Kit (Superscript VILO, Invitrogen) according to the manufacturer’s instructions. 2.3. Selection of genes and primer designing Primers for 18S rRNA, GAPDH, Actin and RuBP encoding genes were selected based on previous studies (Gantasala et al., 2013) and primers for ATP SE, CSD, PPI and STPP genes also known for various housekeeping functions in plants were selected from Genbank database. The accession numbers of these genes along with their functions is given in Table 1. Primers for both PCR and RT-qPCR were designed using the primer quest tool in Integrated DNA technology website (http://eu.idtdna.com/primerquest) for reported and non reported housekeeping genes of other species available in the Genbank database (Tables 1 and 2).

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2.4. Cloning and sequencing of housekeeping genes The selected housekeeping genes were PCR amplified from the cDNA using the primers designed based on the known nucleotide sequence of other plant species. The primer sequences and the other details are provided in Table 1. PCR amplification reactions were performed in 25 ␮l reaction volumes containing 2.5 ␮l 10 × assay buffer, 200 ␮M each of dATP, dCTP, dGTP and dTTP (Fermentas), 0.5 ␮M primer, 1 unit of Taq polymerase (MBI Fermentas, Genetix, India) and 1 ␮l (50–100 ng) cDNA. The PCR cycles consisted of initial denaturation at 94 ◦ C for 4 min, followed by 35 cycles of amplification, denaturation at 94 ◦ C for 60 s, annealing at 62 ◦ C for 30 s and extension at 72 ◦ C for 1 min with a final extension at 72 ◦ C for 10 min. The amplified products were later resolved on 1.2% agarose gel. The fresh PCR product was cloned into pGEM-T cloning vector (Promega) using the manufacturer’s protocol. Freshly prepared competent cells of Escherichia coli DH5␣ were transformed with the recombinant plasmids. Positive clones were selected by using blue white colonies screening and colony PCR. The inserts were confirmed by restriction digestion with EcoR I and custom sequenced using SOLiD sequencing system. These sequences were analyzed using the BLAST program of NCBI (http://blast.ncbi.nlm.nih.gov/ Blast.cgi). Database searches were performed with the BLAST Network Service (NCBI, national center for biotechnology information), using the BLASTX and BLASTN algorithm using default settings. 2.5. Real time PCR and analysis of gene expression stability Quantitative real time PCR was performed using SYBR green in Realplex2 thermal cycler (Eppendorf). A master mix for each sample was prepared with SYBR Green mix (Eurogentec). Reaction mix of 10 ␮l was prepared by adding 5 ng of cDNA and 750 nM each of the specific primers. The PCR cycles consisted of initial denaturation at 95 ◦ C for 5 min, followed by 40 cycles of amplification, denaturation at 95 ◦ C for 15 s followed by 60 ◦ C for 1 min. Specificity of amplification was assessed by disassociation or melt curve analysis at 60–95 ◦ C after 40 cycles. Real time PCR analysis was carried out for three biological replicates for each sample and three technical replicates were analysed for each biological replicate (Gantasala et al., 2013). Controls without template were included in our experiments. Three statistical software’s BestKeeper (Pfaffl MW et al., 2004), NormFinder (Andersen CL et al., 2004) and geNorm (Vandesompele et al., 2002) were used for measurement of stability of expression of the candidate genes. 3. Results 3.1. Cloning of housekeeping genes Due to lack of prior sequence information regarding any housekeeping genes in tuberose, 15 orthologous housekeeping genes from various other species were selected for PCR amplification. However, only eight genes could be successfully amplified from the cDNA viz., 18S rRNA, GAPDH, Actin, RuBP, ATP SE, CSD, PPI, STPP that resulted in 416 bp, 586 bp, 269 bp, 501 bp, 636 bp, 369 bp, 465 bp, and 456 bp amplicons respectively, which were cloned and sequenced (Fig. 2). Out of these 8 genes, 18S rRNA, GAPDH, RuBP, and Actin were conventional genes whereas, ATP SE, CSD, PPI and STPP were novel genes. The sequences were confirmed by BLAST analysis and they were deposited in the GenBank database and the accession numbers assigned were KJ200629, KJ200631, KJ200630, KJ472484, KM077022, KM077023, KM077024 and KM658171. The primer efficiencies for the selected genes were calculated that

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Table 1 Details of function of the candidate genes and primers used for the cDNA amplication. Name

Accession number

Function

Forward Primer 5 -3 Reverse Primer

Length (bp)

Tm ◦ ( C)

18S rRNA

JX448341

40S ribosome subunit

GAPDH

JX448342

Glucose metabolic process

RuBP

JX448343

Photosynthesis

Actin

AB111527

Cytoskeleton contraction

ATP SE

XM 008800441

Electron transport complex and respiration

CSD (coatomer subunit delta)

XM 009600390

Protein transport

PPI (peptidyl-prolyl isomerase)

XM 008459854

Protein folding

STPP (serine/threonine-protein phosphatase)

XM 009390773

DNA and RNA metabolism

CGCGCAAATTACCCAATCCTGACA 416 60 TCCCGAAGGCCAACGTAAATAGGA AACCGGTGTCTTCACTGACAAGGA 586 60 GCTTGACCTGCTGTCACCAACAAA GCAGGTGTGGCCACCAATTAACAA 269 60 TGCACTCTCCGACCTCATTCAACA GACTCAAATTATGTTCGAGACATTCAAC 501 63 TCGCATTTCATGATGGAGTTGTAG GATGTCTCGAAGCAGATCCAG 636 62 CTTCTTCCGAAAGACGACATCTA TTCACCTCTGTTCTTCTCAATCT 369 62 CGCTATGTGTACCAGCCAATA GAGGCCCTTGCATATTTACC 465 60 CACAGAGATTGGTGATGACA GCTCTGGCTATCAGTTTAAGGT 456 62 CCGTGGATACTACTCAGTTGAAA

Table 2 Details of primers used for the real time-PCR expression study of candidate reference genes. Name

Forward Primer 5 -3

Reverse Primer 5 -3

Primer efficiency (%)

Length (bp)

Tm (◦ C)

18S rRNA GAPDH RuBP Actin ATP SE CSD PPI STPP

CGCGCAAATTACCCAATCC GTGGAGCCAAGAAGGTTATCA TCGAGACTGAGCACGGATTTGTGT GATCTTGCTGGACGTGATCTT GTCAGTGCTTCATTCTGCAAAG GCAGACACCCTCTTCATCTAAA TCTTCTCTGCCGTATTCATGTC TCCACCAGTGCTGTCAATG

CCTCCAATGGATCCTCGTTAAG GTGGTGCAGCTAGCATTAGA TGCACTCTCCGACCTCATTCAACA GCTTCTCCTTCATGTCTCTCAC TGAGCATGCTGATGGTTAGG CGCTATGTGTACCAGCCAATA CCTAGCTGTAGTTCCTCCAAAC CCACGAAAGCCGTCAGATTA

101.2 100.5 97.8 95.6 103.8 96.2 99.5 98.1

121 121 141 112 117 147 101 129

62 62 60 62 62 62 62 62

ther used for the calculation of expression stability (Fig. S1 and Table 3). The expression levels of these genes were determined and the transcripts of these genes showed different levels of abundance. 18S rRNA showed the lowest Cq value ranging from 3.06 to 3.82 indicating its high level of expression. RuBP was eliminated for further analysis due to very low expression. Further, we have used the most commonly used statistical algorithms BestKeeper, Normfinder and geNorm for normalization of RT-qPCR data of seven genes. Supplementry material related to this article found, in the online version, at http://dx.doi.org/10.1016/j.scienta.2015.07.042 Fig. 2. cDNA amplification of housekeeping genes. Lane M: 100 bp DNA ladder/marker, lane 1. 18S rRNA (416 bp), lane2: GAPDH (586 bp), lane3: RuBP (269 bp), lane 4: Actin (501 bp), lane 5: CSD (369 bp), lane 6: STPP (456 bp), lane 7: ATP SE (636 bp), lane 8: PPI (465 bp).

ranged from 95.6 to 103.8 (Table 2). These primers were used for all RT-qPCR studies. 3.2. Evaluation of expression stability of the reference genes 18S rRNA, GAPDH, Actin, RuBP encoding genes were selected based on previous studies. ATP synthase E-sub unit (ATP SE), coatomer subunit delta (CSD), peptidyl-prolyl isomerase (PPI), serine/threonine-protein phosphatase (STPP) genes were selected from Genbank database. These eight candidate reference genes were assessed by using RT-qPCR to quantify their mRNA levels. To analyze the expression stability of the selected candidate genes, mRNA levels were measured in eleven different tissues of the tuberose plant (young leaf, leaf sheath, root, immature flower bud, mature flower bud, open flower, stamen, ovary, stigma, petals and flower tube). Cq mean values of three biological replicates were obtained from Realplex2 software. These Cq mean values were fur-

3.3. Bestkeeper analysis BestKeeper computed the gene expression variation for the seven target genes in all the samples based on crossing points (CP) (Gantasala et al., 2013; Pfaffl, 2001). Primary analysis of the RTqPCR data based on the assessment of raw CP values calculated the standard deviation, SD (±CP) and coefficient of variance, CV (%CP) for the target genes in all the samples. This data was further used to determine the stability of gene expression. Based on the variability, control genes were ranked as the most stably expressing showing lowest variation to the least stable one with the highest variation. All the reference genes showing stable expression were combined into BestKeeper index for the individual sample using the geometric mean of the CP values for each of the candidate gene. Samples with efficiency corrected intrinsic variation within three fold over or under expression were considered acceptable. Bestkeeper analysis was done using raw Cq values. Firstly, standard deviation (SD) was analyzed. All candidate reference genes that exhibited SD value less than 1, were qualified for their utility as reference genes. Subsequently, data processing using pair wise correlation and regression analysis assessed the inter gene relations and eliminated GAPDH, as the gene with the least correlation (r = 0.587) (Table 4). The anal-

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Table 3 Expression pattern of the housekeeping genes and average values of quantification cycle (Cq) ± standard deviation (SD) in biological replicates. Plant Tissue

18SrRNA Cq ± SD

GAPDH

CSD

PPI

STTP

Actin

ATP SE

Young Leaf Leaf Sheath Root Immature Flower Bud Mature Flower Bud Open Flower Stamen Ovary Stigma Petals Flower Tube

3.82 ± 0.21 3.44 ± 0.15 3.51 ± 0.26 3.06 ± 0.18 3.53 ± 0.12 3.32 ± 0.25 3.69 ± 0.31 3.65 ± 0.11 3.35 ± 0.22 3.24 ± 0.33 3.51 ± 0.16

15.81 ± 0.08 15.39 ± 0.10 15.62 ± 0.15 14.26 ± 0.24 14.75 ± 0.33 14.41 ± 0.31 14.09 ± 0.22 15.38 ± 0.19 18.53 ± 0.13 14.29 ± 0.20 14.84 ± 0.16

20.28 ± 0.31 18.97 ± 0.17 17.77 ± 0.09 17.28 ± 0.14 18.28 ± 0.32 18.50 ± 0.11 20.00 ± 0.05 18.84 ± 0.16 18.12 ± 0.20 18.58 ± 0.41 19.20 ± 0.13

20.24 ± 0.33 19.28 ± 0.25 18.42 ± 0.07 18.39 ± 0.50 19.01 ± 0.41 18.72 ± 0.07 19.66 ± 0.14 18.96 ± 0.21 19.98 ± 0.34 19.15 ± 0.28 19.22 ± 0.18

21.80 ± 0.04 20.43 ± 0.15 19.94 ± 0.36 19.52 ± 0.29 20.53 ± 0.13 20.13 ± 0.15 21.86 ± 0.20 20.70 ± 0.11 19.98 ± 0.09 20.48 ± 0.14 20.76 ± 0.22

18.35 ± 0.48 18.20 ± 0.13 17.24 ± 0.23 16.74 ± 0.03 17.18 ± 0.29 18.12 ± 0.30 18.41 ± 0.19 17.84 ± 0.17 19.17 ± 0.33 18.61 ± 0.43 18.72 ± 0.09

21.63 ± 0.07 21.03 ± 0.19 19.73 ± 0.31 20.18 ± 0.18 20.51 ± 0.41 19.75 ± 0.35 20.52 ± 0.30 21.12 ± 0.12 21.02 ± 0.26 19.37 ± 0.11 19.81 ± 0.14

Fig. 3. Expression stability and ranking of housekeeping genes by three statistical softwares, (A) Best keeper (B) Norm Finder (C) geNorm.

Table 4 Statistical analysis of housekeeping genes.

BestKeeper index, PPI and CSD were selected as possible reference genes.

Gene name

BestKeeper coefficient of correlation (r)

NormFinder stability value ()

geNorm expression stability (M)

18S rRNA GAPDH CSD PPI STPP Actin ATP SE

0.791 (3) 0.587 (7) 0.796 (2) 0.916 (1) 0.755 (4) 0.659 (6) 0.731 (5)

0.403 (2) 1.108 (7) 0.639 (6) 0.249 (1) 0.534 (4) 0.539 (5) 0.526 (3)

0.538 (3) 0.797 (6) 0.284 (1) 0.475 (2) 0.284 (1) 0.603 (4) 0.655 (5)

Note: numbers in parenthesis indicate the ranking of the genes.

ysis of the remaining two genes (PPI, CSD) showed a strong and significant correlation with a value of (r) 0.916 for PPI and 0.796 for CSD indicating their stable expression levels. Accordingly, the BestKeeper index (p) was found to be 0.001 and 0.003, respectively, for PPI and CSD (Fig. 3A). In view of high correlation value and low

3.4. Norm Finder analysis Normfinder utilizes a model based approach to establish expression stability of candidate genes (Andersen et al., 2004). It estimates the overall expression variation of the candidate reference genes and the variation between sample subgroups. Analysis of Normfinder results revealed that the gene expression of four candidate reference genes, PPI, 18S rRNA, ATP SE and STPP had lower stability values across the samples (Table 4). However, the remaining reference genes showed that CSD had higher intra-group variation than Actin, ranked at the fifth position. Further, GAPDH had highest intra-group variation and highest stability values. Thus, based on Normfinder analysis PPI and 18S rRNA were considered as the best candidate reference genes (Fig. 3B).

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Table 5 Validation of the reference gene expression in tuberose varieties, under nematode infection and tuberose plants grown in different salt (NaCl) concentrations. Conditions

PPI

CSD

Tuberose varieties Shrinagar Phule Rajini Subhasini Vaibhav

Cq ± SD 18.36 ± 0.28 18.68 ± 0.08 18.40 ± 0.07 18.65 ± 0.02

19.49 ± 0.17 19.21 ± 0.12 19.27 ± 0.01 19.01 ± 0.07

Nematode infection Control Nematode infected

17.67 ± 0.15 18.05 ± 0.26

19.63 ± 0.30 19.94 ± 0.37

NaCl concentrations 0 mM 10 mM 100 mM 200 mM 250 mM 500 mM

18.63 ± 0.27 18.43 ± 0.50 18.76 ± 0.36 18.59 ± 0.27 18.26 ± 0.19 18.45 ± 0.11

18.83 ± 0.25 18.68 ± 0.39 18.94 ± 0.41 18.21 ± 0.19 18.40 ± 0.31 18.53 ± 0.26

Note: Cq is quantification cycle, SD is standard deviation. Cq ± SD is Cq values standard deviation between biological replicates.

3.5. geNorm analysis The geNorm was used to calculate candidate reference gene stability values (M) based on the expression data. Expression stability measure is calculated as the mean of pairwise variation of a gene compared to that of all other genes (Vandesompele et al., 2002). Analysis of raw non-normalized data of eleven different tissue samples (n = 11) allowed sorting of genes ranked on the basis of their expression stability (M) from most stable to least stable (STPP, CSD,PPI, 18S rRNA, Actin, ATP SE and GAPDH) (Fig. 3C). CSD and STPP were given the same ranking followed by PPI (Table 4). Successive elimination of the least stable genes based on the highest M values led to the identification of CSD, ST PP and PPI as potential reference genes. 3.6. Validation of reference genes The conclusions from the analyses described above were applied to quantify the transcript level of the two genes, PPI and CSD, in different varieties, biotic and abiotic stress conditions to determine their stability in expression. The expression stability of PPI and CSD genes was tested in these four different tuberose varieties using real-time PCR. A uniform expression pattern was observed in all the four genotypes for the selected genes indicating their utility as reference genes for real-time PCR analysis (Table 5). The expression of the selected reference genes were also validated in the tuberose plants that were infected with root knot nematode, M. incognita (Table 5). It was observed that the expression of the two reference genes in the leaf tissue of the nematode challenged plants was similar to that in the uninfected plants. Similarly, the expression of two selected genes under different salt concentrations (10, 50, 100, 200 and 500 mM) remained stable (Table 5). This indicated that selected genes can be used as reference genes. Hence, the above experiments established the identification and utility of the two novel housekeeping genes as reference genes for gene expression studies in tuberose using real-time PCR. 4. Discussion The ideal reference gene should have constant expression regardless of the experimental conditions. Previously, it was understood that common reference genes like Actin, Tubulin, Cyclphilin, GAPDH, 18S/28S rRNA etc., would be stable under all environmental conditions. But, subsequently it was established that the expression of these common reference genes varied with environ-

mental conditions (Bustin, 2002; Huggett et al., 2005; Zhu et al., 2013). It was also reported that there is no universal housekeeping gene which is stable under all experimental conditions to be used as an internal reference gene. This is explained by the fact that housekeeping genes are not only implicated in the basal cell metabolism but also participate in other cellular functions (Ishitani et al., 1996). The study under report included evaluation of eight candidate reference genes in 11 tissue samples of P. tuberose out of which four were conventional and four were novel genes. ATP SE, CSD, PPI and STPP were selected since they are involved in critical housekeeping functions like Electron transport complex and respiration, Protein transport, protein folding, and DNA and RNA metabolism respectively. Tuberose being a non model system, selection and validation process was very challenging since no functional genes have ever been reported from this plant species. In the absence of prior sequence information in the public domain like GenBank (NCBI), the present study addressed this lacuna. Among the eight genes selected, RuBP was deleted due to its low level of expression. We found that expression of the remaining seven genes varied in different tissues. The expression of the five genes, 18S rRNA, CSD, PPI, STPP and Actin was highest in immature flower bud and the lowest in young leaf. However, expression of ATP SE was highest in petals while that of GADPH was in stamens. On the other hand, expression was least in stigma for both GADPH and Actin. Similar findings of varied expressions in different tissues and conditions have been reported in other crops also (Han et al., 2012; Lin et al., 2013; Mafra et al., 2012; Zhu et al., 2013; Zhu et al., 2012). The RT-qPCR data was analyzed using three different softwares viz. geNorm, Normfinder and BestKeeper (Andersen et al., 2004; Pfaffl et al., 2004; Vandesompele et al., 2002) to determine stability in the expression statistically so as to identify the most stable housekeeping genes. The three softwares use different calculation algorithms and provide different results. geNorm is based on the expression stability value M, which is described as the average pairwise variation of a single candidate reference gene to all other tested genes. According to this tool, the value of M ranged from 0.284 to 0.797 confirming the stable expression of STPP, PPI and CSD (Table 4). Normfinder tool ranks all the reference gene candidates based on inter and intra group variations and combines both results into a stability value for each candidate reference gene (Zhong et al., 2011). According to this, the most stable expression was shown by PPI. The third software Bestkeeper is designed to determine the most stable expressed genes according to the coefficient of correlation of the Bestkeeper index which is the geometric mean value of the candidate reference gene Ct values. The value of Bestkeeper index ranged from 0.587 to 0.916 and the high stability was shown by PPI and CSD. Hence based on these three analyses, we have selected PPI and CSD for further confirmation for expression stability in different varieties and also under salt stress and nematode infection that indicated the expression stability. It is reported that it is not necessary that all the statistical packages should rank the candidate reference genes in the same way (Li et al., 2014b; Pollier et al., 2014). GAPDH is a traditional reference gene and is involved in basic cellular functions and often assumed to have uniform expression and found to be most stable in barley leaf and grapevine (Jarosova and Kundu, 2010; Reid et al., 2006). However, expression of GAPDH in Nicotiana tabacum and Buglossoides arvensis has been found to be unstable (Gadkar and Filion, 2015; Schmidt and Delaney, 2010). Likewise, the present findings also revealed GAPDH to be least stable. Similarly, another widely used housekeeping gene, Actin which is involved in basic cytoskeletal functioning was found to be unsuitable by all the three statistical methods. Comparable results with Actin have been obtained by Gadkar and Filion (2015) and they also reported that the members of the Actin gene family are influenced by various external factors. Though 18S rRNA was ranked second by Normfinder, we did not

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consider it for further validation due to its controversy as a normalizer (Sturzenbaum and Kille, 2001). The primary reason for the unsuitability of the 18S rRNA or any other ribosomal unit as a reference gene is that they have high expression levels in cells versus functional mRNA’s. This hyper expression results in stochiometric imbalance between the rRNA and mRNA fractions resulting in skewed normalized data (Gadkar and Filion, 2015). However, 18S rRNA as a reference gene in certain plants has also been reported (Gantasala et al., 2013; Jain et al., 2006; Nicot et al., 2005). Among the four novel genes that we have used, ATP SE and PPI have so far not been reported as housekeeping genes in plants. Recently, ATP SE has been found to be the most stable housekeeping gene in two spotted spider mite Tetranychus urticae (Yang et al., 2015). PPI has been reported to be the most stable housekeeping gene in atopic human bronchial epithelial cells (He et al., 2008). CSD and STPP were found to be stable housekeeping genes in Arabidopsis (Czechowski et al., 2005) and olives (Ray and Johnson, 2014) respectively. Of late, many new house keeping genes showing highly stable expression have been reported from Arabidopsis, rose, and buffalo grass (Klie and Debener, 2011; Li et al., 2014b; Libault et al., 2008). Further, Kumar et al. (2011) has provided a comprehensive list of novel genes used as reference genes and it has been mentioned that novel genes outperform traditional reference genes indicating that traditional reference genes have some limitations of variable expression over threshold level while novel genes cover a wide range of absolute expression levels. In the present study also, the two novel genes were useful for RT-qPCR data normalization as against the four conventional genes. This work constitutes the first effort for the identification of reference genes in this commercially important plant and also the selection of optimal endogenous controls for quantitative real time PCR studies. The present results will be useful for metabolic engineering in this crop and for functional genomics in P. tuberosa. Utility of PPI in tuberose as a reference gene is a pioneer report in plants whereas, usefulness of CSD as a stable reference gene has been demonstrated for the first time in a crop besides the model plant, Arabidiopsis. Establishment of these two novel reference genes for RT-qPCR enriched the options for selecting the housekeeping genes in plants over the known traditional genes. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgments We would like to acknowledge and extend our gratitude to IARI and ICAR, New Delhi, India for infrastructure facilities and financial support. References Andersen, C.L., Jensen, J.L., Ørntoft, T.F., 2004. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 64, 5245–5250. Benedito, V.A., Torres-Jerez, I., Murray, J.D., Andriankaja, A., Allen, S., Kakar, K., Wandrey, M., Verdier, J., Zuber, H., Ott, T., Moreau, S., Niebel, A., Frickey, T., Weiller, G., He, J., Dai, X., Zhao, P.X., Tang, Y., Udvardi, M.K., 2008. A gene expression atlas of the model legume Medicago truncatula. Plant J. Cell Mol. Biol. 55, 504–513. Bin, W., Wei, L., Ping, D., Li, Z., Wei, G., Bing, L., Gui, P., Jian, W., Feng, C., 2012. Evaluation of appropriate reference genes for gene expression studies in pepper by quantitative real-time PCR. Mol. Breed. 30, 1393–1400. Bustin, S.A., 2002. Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. J. Mol. Endocrinol. 29, 23–39. Czechowski, T., Stitt, M., Altmann, T., Udvardi, M.K., Scheible, W.R., 2005. Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiol. 139, 5–17.

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