Planta

, Volume 237, Issue 3, pp 873–889 | Cite as

Identification and testing of reference genes for Sesame gene expression analysis by quantitative real-time PCR

  • Libin Wei
  • Hongmei Miao
  • Ruihong Zhao
  • Xiuhua Han
  • Tide Zhang
  • Haiyang Zhang
Open Access
Original Article

Abstract

Sesame (Sesamum indicum L.) is an ancient and important oilseed crop. However, few sesame reference genes have been selected for quantitative real-time PCR until now. Screening and validating reference genes is a requisite for gene expression normalization in sesame functional genomics research. In this study, ten candidate reference genes, i.e., SiACT, SiUBQ6, SiTUB, Si18S rRNA, SiEF1α, SiCYP, SiHistone, SiDNAJ, SiAPT and SiGAPDH, were chosen and examined systematically in 32 sesame samples. Three qRT-PCR analysis methods, i.e., geNorm, NormFinder and BestKeeper, were evaluated systematically. Results indicated that all ten candidate reference genes could be used as reference genes in sesame. SiUBQ6 and SiAPT were the optimal reference genes for sesame plant development; SiTUB was suitable for sesame vegetative tissue development, SiDNAJ for pathogen treatment, SiHistone for abiotic stress, SiUBQ6 for bud development and SiACT for seed germination. As for hormone treatment and seed development, SiHistone, SiCYP, SiDNAJ or SiUBQ6, as well as SiACT, SiDNAJ, SiTUB or SiAPT, could be used as reference gene, respectively. To illustrate the suitability of these reference genes, we analyzed the expression variation of three functional sesame genes of SiSS, SiLEA and SiGH in different organs using the optimal qRT-PCR system for the first time. The stability levels of optimal and worst reference genes screened for seed development, anther sterility and plant development were validated in the qRT-PCR normalization. Our results provided a reference gene application guideline for sesame gene expression characterization using qRT-PCR system.

Keywords

BestKeeper GeNorm NormFinder Quantitative real-time PCR Reference gene Sesame (Sesamum indicum L.) 

Abbreviations

ABA

Abscicic acid

ACT

Actin

APT

Adenine phosphoribosyl transferase

Ct

Cycle threshold

CYP

Cyclophilin

DNAJ

DNAJ-like protein

EF1α

Elongation factor 1-alpha

GAPDH

Glyceraldehyde-3-phosphate dehydrogenase

GH

Glycosyl hydrolase family protein

LEA

Late embryogenesis abundant protein

qRT-PCR

Quantitative real-time polymerase chain reaction

R

Coefficient of correlation

SS

Starch synthase

TUB

Beta-tubulin

UBQ6

Ubiquitin 6

Introduction

Gene expression analysis is an important and basic step for the systematic understanding of plant biological processes, such as growth and development and biotic and abiotic stress defense pathways. In recent years, quantitative real-time reverse transcriptase PCR (qRT-PCR) has been used as the main analysis technique for quantification and regulating characterization of gene expression. Compared with the traditional method of Northern blot hybridization (Yukawa et al. 1996; Jin et al. 2001; Tai et al. 2002; Chun et al. 2003; Choi et al. 2008; Park et al. 2010), qRT-PCR is an efficient, reliable and sensitive technique for a limited number of target genes (Bustin 2000; Gachon et al. 2004; Hong et al. 2008; Maroufi et al. 2010). To quantify the expression level of a target gene in qRT-PCR, at least one control gene, termed a reference gene, is needed for normalization. Traditional reference genes, such as actin (ACT), ubiquitin 6 (UBQ6), beta-tubulin (TUB), 18S rRNA, elongation factor 1-alpha (EF1α), cyclophilin (CYP), histone, DNAJ-like protein (DNAJ), adenine phosphoribosyl transferase (APT) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), mostly involving in basic cellular processes, have been widely used as internal controls for gene expression analyses in many crops (Brunner et al. 2004; Nicot et al. 2005; Jain et al. 2006; Jian et al. 2008; Artico et al. 2010; Lee et al. 2010; Qi et al. 2010). While an ideal reference gene would be absolutely valid with a stable expression level in all given tissues and treated conditions (Brunner et al. 2004; Jain et al. 2006), no such universal reference gene has yet been reported. Some studies showed that reference genes did not always keep their stability in any tissues or experimental conditions (Thellin et al. 1999, 2009 Guénin et al. 2009). Selecting several suitable reference genes is necessary for target gene quantification, as the possibility of mismeasures with unvalidated references can be minimized.

Sesame (Sesamum indicum L.), which belongs to the Pedaliaceae family, is an ancient and important oilseed crop with high oil quality (Chung et al. 2003). Sesame seed is consumed as a traditional health food for its specific antihypertensive effect, hypocholesterolemic activity and antioxidative activity (Coulman et al. 2005; Jan et al. 2009, 2010, 2011; Liao et al. 2009; Mochizuki et al. 2010). However, few reference genes have been selected and validated in sesame until now. During a recent expression survey of a few target genes, the sesame elongation factor gene (EF) was used as the sole reference gene in RT-PCR, even though its preliminary validation had never been performed (Kim et al. 2007, 2010). UBQ5, eIF4A and α-tubulin reported as the optimal reference genes for sesame charcoal rot disease resistance research in March, 2012 have not yet validated with specific sesame genes (Liu et al. 2012). Systematic exploration and validation of more stable sesame reference genes is still requisite.

Therefore, the aims of this study were: (1) to acquire the sequences of ten candidate reference genes based on the new sesame dataset (JP631635–JP668414) or relevant sequence information in other crops, (2) to screen and rank optimal sesame reference genes by their expression variation in 32 different sesame tissues under biotic or abiotic stress conditions and (3) to illustrate the application of the chosen reference genes with three test genes in sesame.

Materials and methods

Plant materials

Yuzhi 11 (Sesamum indicum L.), a cultivated sesame, was used in the study. Thirty-two different tissues were collected and investigated (Table 1). Vegetative tissue samples including root, stem and leaf were collected at the seedling and flowering stages. Developing buds and seeds were collected through their whole development stages. Callus tissues induced from seed cotyledon and germinating seeds were cultured under proper conditions before being collected. All materials were grown in a greenhouse at 25 °C with 14 h light per day or in the field at the Yuanyang experiment station of Henan Academy of Agricultural Sciences (HAAS).
Table 1

Description of 32 samples for qRT-PCR in Sesamum indicum L.

Sample no.

Sample type

Growth condition and treatment

S1

Root

Seedling with two pairs of leaves, grown in greenhouse, 25 °C, 14 h light per day

S2

Stem

S3

Leaf

S4

Root

Flowering stage, grown in greenhouse, 25 °C, 14 h light per day

S5

Stem

S6

Leaf

S7

Root

Seedlings with two pairs of leaves inoculated with 1 × 106 L−1 Fusarium oxysporum conidiophore suspension for 5 h, grown in greenhouse, 25 °C, 14 h light per day

S8

Stem

S9

Leaf

S10

Root

Seedlings with two pairs of leaves, treated with 200 mM NaCl for 5 h, grown in greenhouse, 25 °C, 14 h light per day

S11

Stem

S12

Leaf

S13

Root

Seedlings with two pairs of leaves, treated with 20 % PEG 6000 for 5 h, grown in greenhouse, 25 °C, 14 h light per day

S14

Stem

S15

Leaf

S16

Root

Seedlings with two pairs of leaves, treated with 4 °C, for 5 h, grown in greenhouse, 25 °C, 14 h light per day

S17

Stem

S18

Leaf

S19

Root

Seedlings with two pairs of leaves, treated with 200 μM ABA for 5 h, grown in greenhouse, 25 °C, 14 h light per day

S20

Stem

S21

Leaf

S22

Bud, 2 mm

Developing buds with 2–8 mm sizes, grown in experimental field

S23

Bud, 5 mm

S24

Bud, 8 mm

S25

5DAF seed

Developing seeds 5–35 days after flowering (DAF), grown in experimental field

S26

15DAF seed

S27

25DAF seed

S28

35DAF seed

S29

Seed germinating 1 day

Seeds were surface-sterilized and cultured on filter paper with distilled water in 1–3 days, 25 °C, 14 h light per day

S30

Seed germinating 2 days

S31

Seed germinating 3 days

S32

Callus tissue

Induced from cotyledon and cultured on MS medium with 0.1 mg L−1 NAA and 2.0 mg L−1 6-BA and 30 g L−1 sucrose

For biotic stress treatment, seedlings with two pairs of leaves were inoculated with 1 ml of ×106 conidiophore suspension of Fusarium wilt pathogen (No. HSFO 09030) for 5 h at 25 °C.

For salt and drought stress treatments, seedlings with two pairs of leaves were treated with 200 mM NaCl and 20 % PEG 6000 for 5 h. For cold treatment, the seedlings were cultured at 4 °C for 5 h.

For hormone treatment, seedlings were sprayed with 200 μM abscisic acid (ABA) and were cultured for 5 h.

To verify the expression pattern of the chosen reference genes, ms86-1, a genic male sterile (GMS) line, was cultured in the field and the fertile (plump, white) and sterile (thin, green) anthers were collected under two stages (bud size <4 and >4 mm).

All the collected samples were immersed in liquid nitrogen and stored individually at −70 °C for RNA extraction.

RNA isolation and cDNA preparation

Total RNA was isolated using the TRIzol reagent (Invitrogen) according to the manufacturer’s instructions. RNA samples were assessed with OD 260/280 > 2.0 and OD 260/230 > 1.8. Equal amounts of total RNA (2 μg) in all samples were treated with gDNA Eraser to eliminate genomic DNA contamination, and then used for cDNA synthesis using a PrimeScript RT Reagent Kit (Perfect Real Time; TaKaRa). Purified cDNA samples were diluted properly with RNase-free water before used as templates in the qRT-PCR process. RNA extraction and cDNA synthesis from all samples were performed with two biological replicates.

Selection of sesame candidate reference genes and functional genes

Ten housekeeping sesame genes, including SiACT, SiUBQ6, SiTUB, Si18S rRNA, SiEF1α, SiCYP, SiHistone, SiDNAJ, SiAPT and SiGAPDH, were selected as candidate reference genes. Three functional genes of late embryogenesis abundant protein (SiLEA), starch synthase (SiSS) and glycosyl hydrolase family protein (SiGH) were selected for reference gene validation. Si18S rRNA sequence was obtained from NCBI data (Accession number: AJ236041). The sequences of other nine reference genes and three validation genes were obtained from our sesame RNA-seq transcriptome dataset (http://www.ncbi.nlm.nih.gov/genbank/TSA.html accession numbers JP631635-JP668414) and compared with the AGI (Arabidopsis Genome Initiative) protein database using BLASTX (http://www.arabidopsis.org/cgi-bin/Blast/TAIRblast.pl; Table 2) with E-value cut-off of 1E−20 as ‘significant matches’.
Table 2

Description of ten sesame candidate reference genes for qRT-PCR

Gene name

Gene description

Accession number

Arabidopsis homolog locus

E values

Primer and probe sequence (5′–3′)

T m (°C)

Amplicon size (bp)

PCR efficiency (%)

Correlation coefficient (R 2)

Si18S rRNA

18S rRNA gene

AJ236041.1

AT3G41768

0

Forward: AGAAACGGCTACCACATCCA

57.9

251

96

0.992

Reverse: CCAACCCAAGGTCCAACTAC

56.8

Probe: FAM-AGCAGGCGCGCAAATTACCCAATC-BHQ1

69.0

SiEF1α

Elongation factor 1-alpha

JP631636

AT5G60390.3

0

Forward: AAGCCCCTCCGTCTCCCACT

63.0

135

98

0.997

Reverse: TTCAGTGGTCAAGCCAGATGG

60.0

Probe: FAM-ATTGGTACTGTCCCCGTTGGTCGTGTG-BHQ1

70.0

SiACT

Actin 7

JP631637

AT5G09810.1

E−109

Forward: CTCCCTTTATGCCAGTGGTCGT

61.5

197

102

0.997

Reverse: GCTCAGCTGTTGTAGTGAAGGA

58.2

Probe: FAM-CTTGATCTTGCTGGCCGTGATCTCACA-BHQ1

69.9

SiDNAJ

DnaJ protein-like

JP631642

AT1G28210.2

2E−70

Forward: CAAAATGGTCCGTTCACACTT

59.9

118

109

0.997

Reverse: CTGTTTTTGTCCCTTTCACCA

60.0

Probe: FAM-TACTTGTCCAAATTGCGGAGGAGCTG-BHQ1

69.9

SiGAPDH

Glyceraldehyde 3-phosphate dehydrogenase

JP631641

AT3G04120.1

E−155

Forward: GATAAGGCTGCTGCCCACTT

58.0

110

98

0.998

Reverse: GGCTTGTATTCCTTCTCATTGACA

58.0

Probe: FAM-CTAAGAAGGTCGTCATCTCTGCCCCGA-BHQ1

69.0

SiCYP

Cyclophilin

JP631639

AT3G56070.2

8E−70

Forward: ACAGACCAGGCTCAGTATGCTTT

58.0

103

113

0.997

Reverse: GGTGGAGACTTCACTAAGGGTAATG

58.0

Probe: FAM-TTGCTCCATAAATTGATTCTCCCCCAGTC-BHQ1

68.0

SiTUB

β-tubulin

JP631640

AT5G23860.2

0

Forward: TGGTGACCTCAACCACCTCAT

59.0

101

105

0.996

Reverse: TGACAGCGAGTTTCCTGAGATC

58.0

Probe: FAM-TGTCACATGTTGTCTCCGGTTCCCTG-BHQ1

69.0

SiAPT

Adenine phosphoribosyl transferase 1

JP631635

AT1G27450.2

E−76

Forward: TTGCCAATGGACAAAGGGTT

61.5

228

101

0.997

Reverse: GAGGGTCGGGTCAAGTTAGG

60.9

Probe: FAM-AGCTGAGCTCACAAGAACAAACAGCG-BHQ1

69.0

SiUBQ6

Ubiquitin 6

JP631638

AT2G47110.2

6E−67

Forward: CACCAAGCCGAAGAAGATCAAG

60.0

100

98

0.996

Reverse: CCTCAGCCTCTGCACCTTTC

59.0

Probe: FAM-TGAAGCTCGCTGTTCTCCAGTTCTACAAGG-BHQ1

69.0

SiHistone

Histone H3

JP631643

AT5G10980.1

3E−41

Forward: CTTGATCAGGAAGTTGCCTTTTC

58.0

101

100

1.000

Reverse: CCTGAAGCGCCAACACAGCAT

59.0

Probe: FAM-TTCGCGAAATTGCCCAGGACTTCA-BHQ1

69.0

SiSS

Starch synthase

JP631789

AT3G01180.1

E−157

Forward: GGTTGAAGCACAGATGGGTA

58.6

159

105

0.996

Reverse: CCTGAGAAAGCAAGAGGAGTT

57.8

Probe: FAM-TGGATGAGACCACACGGTTCGAATC-BHQ1

69.9

SiLEA

Late embryogenesis abundant protein

JP656886

AT3G15670.1

3E−31

Forward: ATGGCTGATGTGGATGAAGA

59.3

106

102

0.997

Reverse: AAACAAAGAGCAATACGACCC

58.6

Probe: FAM-TGGCCACTAAGAAGATACAGAGGAGATGC-BHQ1

68.4

SiGH

Glycosyl hydrolase family protein

JP647810

AT5G20950.2

0

Forward: TTGAGGAAATGGGTGACGAGA

59.1

185

101

0.990

Reverse: GGAGGCACAGCAAAAGGGA

59.8

Probe: FAM-TGCATGCATCTTCTGTCCGTTCCAA-BHQ1

68.3

The efficiency and coefficient of determination (R 2) of qRT-PCR system were determined using LinRegPCR software (R 2 varied from 0.992 to 1.000 with high efficiency, though the amplicon size of two genes in the qRT-PCR system was larger than 200 bp

qRT-PCR primer and probe design

qRT-PCR primers for the above thirteen genes were designed using Primer Express 3.0 (ABI) with the melting temperature between 60 and 62 °C and a primer length of 20–26 bp. The length of amplicons ranged from 100 to 251 bp with high polymerization efficiency, which minimized the RNA integrity impact (Fleige and Pfaffl 2006). Meanwhile, specific probes of ten candidate genes with 5′FAM and 3′BHQ1 fluorescence radicals were designed with the melting temperature between 68 and 71 °C, a length of 24–30 bp and about 50 % GC content (Table 2).

qRT-PCR conditions

To assay the gene expression variability in sesame, qRT-PCR was conducted with an Eppendorf Mastercycler ep Realplex 2.2 Detection System. The PCR reaction volume was 30 μL containing 2.0 μL of diluted cDNA, 0.2 μM of each primer, 0.1 μM probe, 1× PCR buffer, 50 μM of each dNTP and 1.0 U Platinum Taq DNA polymerase (Invitrogen). Reaction mixtures were incubated for 2 min at 37 °C, 5 min at 95 °C, followed by 40 amplification cycles of 15 s at 95 °C and 60 s at 60 °C. All samples were amplified in triplicate times. A negative control without cDNA template was also done at the same time. A standard curve for each gene was generated using tenfold serial dilutions of pooled cDNAs (data not shown). The efficiency of the thirteen pairs of primers in qRT-PCR was calculated using LinRegPCR (Ramakers et al. 2003). To determine their amplicon specificity, electrophoresis analysis of the PCR products was also carried out. Expression levels of the 13 genes in all samples were determined by their cycle threshold values (C ts).

Reference gene expression stability determination

Three publicly available software tools, i.e., geNorm (Vandesompele et al. 2002), Normfinder (Andersen et al. 2004) and Bestkeeper (Pfaffl et al. 2004), were used for expression stability determination of the ten genes in sesame.

GeNorm approach

GeNorm software is a Visual Basic Application (VBA) for ranking the interested genes by the expression stability index, M. The least stable gene with the highest M value was ranked on the left, and the most stable on the right. The M value of a reference gene was not more than 1.5, which is the default limit point (Vandesompele et al. 2002). The pairwise variation (Vn/Vn + 1) between the sequential normalization factors (NF; NFn and NFn + 1) was calculated for determining the optimal number of reference genes (Vandesompele et al. 2002).

NormFinder approach

Normfinder software, another VBA applet, was used as a model-based approach for identifying the optimal normalization gene(s) among a set of candidates (Andersen et al. 2004). Genes were ranked according to their stability value.

Bestkeeper approach

BestKeeper, an Excel-based tool, could perform numerous pairwise correlation analyses using raw C t values of each gene and estimate inter-gene relations of possible reference gene pairs. The lowest average expression stability value indicated the most stable level (Pfaffl et al. 2004).

Results

Identification and characterization of sesame candidate reference genes and functional genes

Compared with the sequences of common reference genes usually used in many plants (Brunner et al. 2004; Nicot et al. 2005; Jain et al. 2006; Jian et al. 2008; Lee et al. 2010; Artico et al. 2010; Qi et al. 2010) and the gene information in GenBank (AJ236041) and our sesame RNA-seq transcriptome data (Zhang et al. 2012), 10 sesame housekeeping genes, including SiACT, SiUBQ6, SiTUB, Si18S rRNA, SiEF1α, SiCYP, SiHistone, SiDNAJ, SiAPT and SiGAPDH, were selected as reference gene candidates. The homology levels of ten genes in sesame and Arabidopsis were all high with the E values of <1E−20. SiLEA, SiSS and SiGH, which were denominated by Arabidopsis homologs, were selected as the validation genes for their specificity in sesame plant development process (Table S1). SiLEA and SiSS were predominantly expressed in sesame seed and seedling organs, respectively. SiGH was mainly expressed in sterile anther rather than fertile anther. Sequences for all of thirteen genes were obtained from GenBank and our sesame RNA-seq dataset (http://www.ncbi.nlm.nih.gov/genbank/TSA.html, accession numbers JP631635- JP668414; Table 2). To ensure their specificity, partial fragments of thirteen genes obtained by RT-PCR were resequenced with the Sanger chain termination method. The results indicated that all amplicons had the same nucleotide sequences as the sequence dataset except for SiHistone gene with one nucleotide change (T to G) (data not shown). The qRT-PCR primers and probes of twelve genes were designed by their sequences in the GenBank. As for SiHistone, the mutation site was excluded from the primer and probe sequences for qRT- PCR system design (Table 2).

qRT-PCR specificity and efficiency

To evaluate the amplification specificity and efficiency, electrophoresis was performed for amplicons of the candidate reference genes derived from cDNA and genomic DNA templates in RT-PCR (Fig. S1). All genes generated only single amplicon band from cDNA samples. SiDNAJ, SiACT, SiGAPDH and SiHistone of 10 genes showed the amplification differences in amplicon size or number between with genomic DNA templates and cDNA templates, as their primers might span an intron or different gene copies exist in the genome. These four genes could be used for RNA extraction quality assay.

Before carrying out the qRT-PCR, all of the RNA samples with high quality were verified by the PCR results of SiACT and SiGAPDH genes. There was no genomic DNA contamination in cDNA templates and no amplicons were detected in the negative controls. Neither primer dimers nor unexpected products were found (data not shown). Amplification efficiency ranged from 96 in Si18S rRNA to 113 in SiCYP, and coefficient of determination (R 2) varied from 0.992 to 1.000 (Table 2). The qRT-PCR system was demonstrated to be efficient and specific for sesame target gene amplification.

Expression profiles of ten candidate reference genes

Ten house-keeping genes showed relatively wide ranges of C t values, from 11.48 to 27.21 in 32 tested sample pools (Fig. 1), and most C t values were between 21.44 and 26.21 (Fig. 1b). The least abundant transcripts were SiDNAJ and SiTUB with C t values of 27.21 and 26.21, respectively. The average C t value of the protein encoding genes was approximately 22.64 cycles. Being one of the most abundant RNA species in cell (Guillermo et al. 2011), Si18S rRNA expressed highly with its threshold fluorescence point in 11.48 cycles. Also, its transcript level was over 2000-fold higher than the other nine genes. In addition, each candidate gene showed a specific C t value variation tendency under the applied conditions. SiAPT and SiUBQ6 showed stable gene expression (below 3 cycles), while SiGAPDH, SiATP and Si18S rRNA had obvious expression variation (above 5 cycles) as shown in Fig. 1b.
Fig. 1

Expression levels of ten candidate reference genes tested in 32 sesame samples. a C t values of ten candidate reference genes with three replicates. b The mean C t values of ten candidate reference genes in all sesame samples. The boxes represent mean C t values. The bars indicate the maximum and minimum values

GeNorm analysis

Before investigating gene expression stability, 32 samples were divided into eight groups by plant development stage and treatment type. We used geNorm software to analyze the expression stability of the tested genes in all samples, and ranked them accordingly to gene stability measure (M), which means the genes with the lowest M values have the most stable expression (Fig. 2a–h). The result showed that all of the tested genes expressed relatively stably with the M value less than 1.0 (Fig. 2a). For all 32 samples, SiAPT and SiUBQ6 showed the lowest M value of 0.555, and Si18S rRNA was the highest with an M value of 0.948. For vegetative tissue development (Fig. 2b), SiACT and SiTUB genes showed the stability with an M value of 0.109; SiAPT and SiTUB genes ranked the most stable under the sesame Fusarium wilt pathogen inoculation with an M value of 0.180, while SiGAPDH was the least stable with an M of 0.634 (Fig. 2c). SiHistone and SiCYP were the most stable across both abiotic stress (salt, drought and cold) and ABA treatment (Fig. 2d, e). SiUBQ6 and Si18S rRNA were the most stable reference genes with an M of 0.065 during bud development (Fig. 2f). As for seed development including seed developing and germinating stages, one of the most stable genes was SiACT consistently (Fig. 2g, h).
Fig. 2

Expression stability values (M) of 10 genes in eight sample groups (ah) by geNorm software. a All sesame samples (S1–S32), b vegetative tissues in different developing stages (S1–S6), c biotic stress treatment (S7–S9) and normal control (S1–S3), d abiotic stress treatment (S10–S18) and normal control (S1–S3), e ABA treatment (S19–S21) and normal control (S1–S3), f developing buds (S22–S24), g developing seeds (S25–S28), h germinating seeds (S29–S31)

The pairwise variation, Vn/n + 1, of geNorm software was also used to indicate effects of more new additional reference genes on the PCR normalization. Results showed that only two groups of samples, i.e., the all 32 mixed sample and the abiotic stress treatment sample, showed higher pairwise variation V2/3 value more than 0.15 (Fig. 3). Therefore, three reference genes were necessary and could give more help to gene expression normalization in both group samples.
Fig. 3

Pairwise variation (V) analysis of 10 sesame candidate reference genes in eight sample groups. Asterisk indicates the optimal number of reference genes for ah sample groups. ah Sample groups are the same as in Fig. 2

NormFinder analysis

To further validate the stability of the reference genes obtained by the geNorm software, we applied the NormFinder software, another VBA approach, for optimal normalization gene(s) identification among the candidates (Andersen et al. 2004). Results indicated that SiUBQ6 ranked as the most stable gene (stability value = 0.461) and Si18S rRNA as the most unstable gene in 32 samples (stability value = 1.097; Table 3), which was consistent with the geNorm analysis. SiAPT was optimal with a stability value of 0.115 for the sesame development assay. However, it was noteworthy that SiDNAJ showed the same remarkable stability (stability value <0.12) in biotic and abiotic stress treatments, which differed from the results by geNorm. During the seed formation and germination processes, SiACT ranked in the top third in NormFinder analysis. In bud development, SiUBQ6 was considered as the most stable gene. It also meant that different reference genes should be chosen for specific tissues or treatment types.
Table 3

Expression stability analysis of ten reference genes in eight sample groups by NormFinder

Rank

a

b

c

d

e

f

g

h

Gene name

Stability value

Gene name

Stability value

Gene name

Stability value

Gene name

Stability value

Gene name

Stability value

Gene name

Stability value

Gene name

Stability value

Gene name

Stability value

1

SiUBQ6

0.461

SiAPT

0.115

SiDNAJ

0.119

SiDNAJ

0.111

SiDNAJ

0.054

SiUBQ6

0.057

SiTUB

0.126

EF1α

0.073

2

SiEF1α

0.502

SiACT

0.134

SiEF1α

0.162

SiEF1α

0.159

SiACT

0.092

SiACT

0.057

SiDNAJ

0.145

SiHistone

0.097

3

SiDNAJ

0.539

SiUBQ6

0.169

SiGAPDH

0.178

SiUBQ6

0.417

SiEF1α

0.186

SiHistone

0.203

SiACT

0.206

SiACT

0.111

4

SiHistone

0.547

SiTUB

0.207

SiHistone

0.205

SiCYP

0.533

SiAPT

0.348

SiGAPDH

0.272

SiEF1α

0.467

SiCYP

0.210

5

SiCYP

0.561

SiDNAJ

0.255

Si18S rRNA

0.226

SiHistone

0.612

SiCYP

0.488

SiEF1α

0.521

SiAPT

0.473

SiUBQ6

0.217

6

SiTUB

0.607

SiCYP

0.410

SiACT

0.377

SiAPT

0.652

SiHistone

0.528

SiDNAJ

0.737

SiGAPDH

0.581

SiTUB

0.255

7

SiACT

0.619

SiHistone

0.427

SiUBQ6

0.574

SiTUB

0.653

SiTUB

0.609

Si18S rRNA

0.951

SiHistone

0.806

SiAPT

0.384

8

SiAPT

0.628

Si18S rRNA

0.522

SiCYP

0.620

SiACT

0.889

Si18S rRNA

0.611

SiAPT

1.031

SiCYP

0.839

SiGAPDH

0.784

9

SiGAPDH

1.054

SiGAPDH

0.828

SiTUB

0.802

SiGAPDH

1.074

SiUBQ6

0.624

SiCYP

1.295

SiUBQ6

0.919

SiDNAJ

0.789

10

Si18S rRNA

1.097

SiEF1α

1.114

SiAPT

1.170

Si18S rRNA

1.109

SiGAPDH

1.329

SiTUB

1.811

Si18S rRNA

1.645

Si18S rRNA

1.010

a–h sample groups were the same as in Fig. 2

BestKeeper analysis

Being another popular analysis method, BestKeeper was also applied for reference gene expression analysis in this study. Results showed that SiATP (SD = 0.645) and SiUBQ6 (SD = 0.649) were most stable in 32 samples (a), which was almost consistent with the results by geNorm and NormFinder (Fig. 4). For the rest seven group samples (b–h), most stable reference genes were not same as results of above both analysis approaches.
Fig. 4

Expression stability analysis of ten reference genes in eight sample groups by BestKeeper. ah Sample groups were the same as in Fig. 2. SD standard deviation. A lower average expression stability value indicates more stable expression

Testing of sesame reference genes

To illustrate the validation of the above reference genes, as well as investigate the expression levels of sesame functional genes, SiSS (JP631789), SiLEA (JP656886) and SiGH (JP647810) genes with specific temporal or spacial expression characters were chosen from our sesame transcriptome dataset.

To validate the reliability of the recommended and relative worst reference genes in sesame vegetable growth and development process, we investigated the expression levels of SiGBSS and SiLEA with SiAPT, SiUBQ6, SiCYP and Si18S rRNA for normalizing the qRT-PCR system, respectively (Table 4a). SiSS expressed mainly in leaves, rather than in root, stem, bud and seed, with the normalization of either group of the reference genes (Fig. 5). The expression of SiLEA normalized with SiAPT, SiUBQ6 and SiCYP as reference genes, was predominant in seed; however, the high expression level was also observed in stem except for in seed organ, as Si18S rRNA, the worst reference gene, was used for expression normalization (Fig. 6). To further explore the stability of these reference genes, we investigated the expression levels of SiLEA during sesame seed development. Four recommended reference genes of SiTUB, SiACT, SiAP and SiDNAJ, as well as the worst reference gene of Si18S rRNA (Table 4g), were performed in qRT-PCR. The expression patterns of SiLEA in four seed- developing stages (5, 15, 25 and 35 DAF) with five different internal controls were consistent, and presented the enhanced tendency in the seed development process (Fig. 7). The results indicated that these recommended references were suitable for sesame-specific gene expression analysis. In some cases, the gene expression pattern could not be normalized with unsuitable reference genes. Furthermore, we analyzed another functional gene, SiGH, to validate the reference genes suitable for sesame reproductive growth. SiGH was higher in sterile anther compared with fertile anther by the transcriptome dataset (Table S1). Using the recommended reference gene, SiUBQ6, SiHistone and Si18S RNA, as well as the worst reference gene, SiGAPDH and SiTUB for bud development assay (Table 4f), we compared the expression level of SiGH in early and late anther development stages with a sesame nucleic male sterile line, ms86-1 (Fig. 8). The expression variation of SiGH gene was just as expected as almost position-specific in sterile anthers rather than fertile anthers. The results further showed that the five reference genes were suitable for sesame gene expression analysis.
Table 4

Optimal and worst sesame reference genes in eight sample groups by three methods

Sample groups

Optimal reference gene

Worst reference gene

geNorm

Normfinder

BestKeeper

Common gene

geNorm

Normfinder

BestKeeper

Common gene

a

SiAPT, SiUBQ6, SiCYP

SiUBQ6

SiAPT

SiAPT, SiUBQ6

Si18S rRNA

Si18S rRNA

SiGAPDH

Si18S rRNA

b

SiACT, SiTUB

SiAPT

SiTUB

SiTUB

SiEF1α

SiEF1α

SiGAPDH

SiEF1α

c

SiAPT, SiTUB

SiDNAJ

SiDNAJ

SiDNAJ

SiGAPDH

SiAPT

SiGAPDH

SiGAPDH

d

SiHistone, SiCYP, SiAPT

SiDNAJ

SiHistone

SiHistone

Si18S rRNA

Si18S rRNA

SiGAPDH

Si18S rRNA

e

SiHistone, SiCYP

SiDNAJ

SiUBQ6

None

SiGAPDH

SiGAPDH

SiGAPDH

SiGAPDH

f

SiUBQ6, Si18S rRNA

SiUBQ6

SiHistone

SiUBQ6

SiGAPDH

SiTUB

SiGAPDH

SiGAPDH

g

SiACT, SiDNAJ

SiTUB

SiAPT

None

Si18S rRNA

Si18S rRNA

Si18S rRNA

Si18S rRNA

h

SiACT, SiCYP

SiEF1α

SiACT

SiACT

Si18S rRNA

Si18S rRNA

SiGAPDH

Si18S rRNA

a–h sample groups were the same as in Fig. 2

Fig. 5

The expression level of the SiSS in different plant organs. SiUBQ6 (i), SiAPT (ii) and SiCYP (iii) were used as recommended internal controls defined by NormFinder, geNorm and BestKeeper. SiGAPDH (iv) and Si18S RNA (v) were used as the worst internal controls accordingly

Fig. 6

The expression level of the SiLEA in different plant organs. SiUBQ6 (i), SiAPT (ii) and SiCYP (iii) were used as recommended internal controls defined by NormFinder, geNorm and BestKeeper. SiGAPDH (iv) and Si18S RNA (v) were used as the worst internal controls accordingly

Fig. 7

The expression level of the SiLEA in developing seed (5–35 DAF) organs. SiTUB (i), SiACT (ii), SiAPT (iii) and SiDNAJ (iv) were used as recommended internal controls defined by NormFinder, geNorm and BestKeeper. Si18S RNA (v) was used as the worst internal controls accordingly

Fig. 8

The expression level of the SiGH in fertile anthers (FA) and sterile anthers (SA) of different sizes (early anther with 2.1–4.0 mm length; late anther with 4.1–7.0 mm length). SiUBQ6 (i), SiHistone (ii) and Si18S RNA (iii) were used as recommended internal controls defined by NormFinder, geNorm and BestKeeper. SiGAPDH (iv) and SiTUB (v) were used as the worst internal controls accordingly

In conclusion, the optimal sesame reference genes for sesame vegetable and reproductive growth and biotic or abiotic stress conditions were obtained and verified from ten candidate genes. The normalized qRT-PCR system was successfully applicated for the expression pattern analysis of sesame-specific functional genes for the first time.

Discussion

To investigate sesame reference genes, we selected ten sesame house-keeping genes and observed their relatively wide expression variations from below 3 cycles to more than 5 cycles in this study. Results validated that no single gene among these ten reference genes was ideal for gene transcript normalization in each tissue type and under biotic or abiotic stress conditions. Therefore, more reliable reference gene(s) for various specific conditions are necessary for sesame transcriptome research.

Some reports suggested that applying different analysis software would result in different validation results in the same tissue or treatment, due to their distinct statistical algorithms and analytical procedures (Hong et al. 2008; Hu et al. 2009; Wan et al. 2010). Our results also showed that there was no completely consistent reference gene among the eight (a–h) sample groups using three (geNorm, Normfinder and BestKeeper) analysis approaches in this paper. To analyze gene expression pattern, six common stable genes were chosen and listed as the reference gene(s) for the specific tissues or conditions. SiUBQ6 and SiAPT were the optimal reference genes with the most stable expression level during sesame development. SiTUB was suitable for sesame vegetative tissue development analysis, SiDNAJ for pathogen treatment, SiHistone for abiotic stress, SiUBQ6 for bud development and SiACT for seed germination. As for hormone treatment and seed development, SiHistone, SiCYP, SiDNAJ or SiUBQ6, as well as SiACT, SiDNAJ, SiTUB or SiAPT, could be used as reference gene, respectively, as no common reliable reference genes were obtained using the three analysis methods.

During testing the suitability of reference genes, SiSS, SiLEA and SiGH genes with specific temporal or spacial expression characters had been used in this study. SiSS was annotated by Arabidopsis homolog with the E value of E−157. Phylogenetic analysis results showed that SiSS was closest with IbGBSS (Fig. S2). GBSS contributes to the elongation of glucan chains during starch biosynthesis and has been well characterized in starch crops (Dry et al. 1992; Hylton et al. 1996; Nakamura et al. 1998; Vrinten and Nakamura 2000; Sattler et al. 2009). In cereals, GBSS consists of two isoforms (GBSSI or waxy protein and GBSSII) for their different tissue specificity. GBSSI or waxy gene expresses exclusively in storage tissues such as seed endosperm and embryo, while the GBSSII gene is transcripted mainly in non-storage tissues such as leaf, stem, root, and pericarp (Dry et al. 1992; Vrinten and Nakamura 2000; Dian et al. 2003). In addition, other different isoforms of GBSS have also been reported in eudicot species (pea, orange, apple and peach), and have various expression profiles differing in cereals (Denyer et al. 1997; Edwards et al. 2002; Szydlowski et al. 2011; Cheng et al. 2012). While validating the normalized qRT-PCR system, we explored and confirmed the tissue specificity of SiSS gene in sesame. The SiSS gene should belong to GBSS isoform as for its tissue specificity, BLASTX and phylogenetic analysis results.

SiLEA gene, which was annotated as the late embryogenesis abundant protein, showed the seed specificity in RNA-seq expression profiles (Table S1) (Zhang et al. 2012). Phylogenetic analysis indicated that SiLEA had the high homology with GmLEA (Fig. S3). The first LEA gene was characterized in cotton as a set of proteins and highly accumulated in embryos at the maturation phase of seed development (Galau and Dure 1981). To date, many LEA proteins or their genes have been isolated from cotton, barley, wheat, rice and maize (Baker et al. 1988; Curry et al. 1991; Curry and Walker-Simmons 1993; Takahashi et al. 1994; White and Rivin 1995). The gene transcripts are accumulated during late stage seed development and correlated with the seed desiccation stage in other crops (Galau et al. 1987; Hong et al. 1988; Raynal et al. 1989; Hundertmark and Hincha 2008). The seed specificity and expression tendency of SiLEA were observed in sesame qRT-PCR (Fig. 7). It also verified the reliability of the recommended reference genes and qRT-PCR system.

Furthermore, we also used SiGH gene to validate the qRT-PCR system. Belonging to the glycosyl hydrolases family (Fig. S4), GH genes play an important role in many important processes, e.g. fruit ripening, wound and defense responses, pollen maturation and pollen tube growth in plants (Hird et al. 1993; Kang et al. 1994; Duroux et al. 1998; Clément et al. 1999; Moctezuma et al. 2003). Jakobsen et al. (2005) carried out full genome microarray analysis of the wild-type and mia mutant anthers transcriptome using Affymetrix chips in Arabidopsis and found 17 genes in the glycosyl hydrolase family had strongly increased expression levels in mia insertion mutants (Jakobsen et al. 2005). Before this study, we had found that SiGH gene expression level probably correlated with sesame male nucleic sterility. In this study, the male sterility expression profile of SiGH gene was also revealed in male sterile flower buds in the normalized sesame qRT-PCR system, which was consistent with the expression patterns in cabbage and flax genic male sterile lines (Jungen et al. 2006; Bateer et al. 2009). As a result, the expression profile of SiSS, SiLEA and SiGH functional genes was consistent with results of both our previous RNA-seq and other plants.

In a word, the sesame reference genes obtained in this research were extremely reliable in given tissues and conditions. The gene expression analysis system would provide a guideline for sesame gene function research in the future.

Notes

Acknowledgments

This program was financially supported by the China National ‘973’ Project [Grant No. 2011CB109304], the earmarked fund for China Agriculture Research System [Grant No. CARS-15] and the grant of China National Key Technology R&D Program [Grant No. 2009BADA8B04-03].

Supplementary material

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Supplementary material 1 (DOC 1078 kb)
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Supplementary material 2 (DOC 64 kb)
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Supplementary material 3 (DOC 68 kb)
425_2012_1805_MOESM4_ESM.doc (70 kb)
Supplementary material 4 (DOC 70 kb)
425_2012_1805_MOESM5_ESM.doc (28 kb)
Supplementary material 5 (DOC 28 kb)

References

  1. Andersen CL, Jensen JL, Ørntoft TF (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 64:5245–5250PubMedCrossRefGoogle Scholar
  2. Artico S, Nardeli SM, Brilhante O, Grossi-de-Sa MF, Alves-Ferreira M (2010) Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data. BMC Plant Biol 10:49PubMedCrossRefGoogle Scholar
  3. Baker J, dennSteele C, Dure L (1988) Sequence and characterization of 6 Lea proteins and their genes from cotton. Plant Mol Biol 11:277–291CrossRefGoogle Scholar
  4. Bateer S, Qiang L, Hui Z, Agula H, Xiaoyun J, Fengyun G (2009) Study on mRNA differential expression in male sterile and fertile flower buds of dominant genomic male sterile flax and sequence analysis of differential fragments. Biotechnol Bull 8:67–70Google Scholar
  5. Brunner AM, Yakovlev IA, Strauss SH (2004) Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol 4:14PubMedCrossRefGoogle Scholar
  6. Bustin SA (2000) Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 25:169–193PubMedCrossRefGoogle Scholar
  7. Cheng J, Khan MA, Qiu WM, Li J, Zhou H, Zhang Q (2012) Diversification of genes encoding granule-bound starch synthase in monocots and dicots is marked by multiple genome-wide duplication events. PLoS ONE 7:e30088PubMedCrossRefGoogle Scholar
  8. Choi AM, Lee SB, Cho SH, Hwang I, Hur CG, Suh MC (2008) Isolation and characterization of multiple abundant lipid transfer protein isoforms in developing sesame (Sesamum indicum L.) seeds. Plant Physiol Biochem 46:127–139PubMedCrossRefGoogle Scholar
  9. Chun JA, Jin UH, Lee JW, Yi YB, Hyung NI, Kang MH (2003) Isolation and characterization of a myo-inositol 1-phosphate synthase cDNA from developing sesame (Sesamum indicum L.) seeds: functional and differential expression, and salt-induced transcription during germination. Planta 216:874–880PubMedGoogle Scholar
  10. Chung SM, Jung KM, Hur CG, Myung BJ, Park I, Chung CH (2003) Comparative analysis of expressed sequence tags from Sesamum indicum and Arabidopsis thaliana developing seeds. Plant Mol Biol 52:1107–1123PubMedCrossRefGoogle Scholar
  11. Clément C, Pacini E, Audran JC (1999) Anther and pollen: from biology to biotechnology. Springer, Berlin Heidelberg, pp 183–189CrossRefGoogle Scholar
  12. Coulman KD, Liu Z, Hum WQ, Michaelides J, Thompson LU (2005) Whole sesame seed is as rich a source of mammalian lignan precursors as whole flaxseed. Nutr Cancer 52:156–165PubMedCrossRefGoogle Scholar
  13. Curry J, Walker-Simmons M (1993) Unusual sequence of group 3 LEA (II) mRNA inducible by dehydration stress in wheat. Plant Mol Biol 21:907–912PubMedCrossRefGoogle Scholar
  14. Curry J, Morris CF, Walker-Simmons M (1991) Sequence analysis of a cDNA encoding a group 3 LEA mRNA inducible by ABA or dehydration stress in wheat. Plant Mol Biol 16:1073–1076PubMedCrossRefGoogle Scholar
  15. Denyer K, Barber L, Edwards E, Smith A, Wang T (1997) Two isoforms of the GBSSI class of granule-bound starch synthase are differentially expressed in the pea plant (Pisum sativum L.). Plant Cell Environ 20:1566–1572CrossRefGoogle Scholar
  16. Dian W, Jiang H, Chen Q, Liu F, Wu P (2003) Cloning and characterization of the granule-bound starch synthase II gene in rice: gene expression is regulated by the nitrogen level, sugar and circadian rhythm. Planta 218:261–268PubMedCrossRefGoogle Scholar
  17. Dry I, Smith A, Edwards A, Bhattacharyya M, Dunn P, Martin C (1992) Characterization of cDNAs encoding two isoforms of granule-bound starch synthase which show differential expression in developing storage organs of pea and potato. Plant J 2:193–202PubMedGoogle Scholar
  18. Duroux L, Delmotte F, Lancelin J, Keravis G, Jay-Allemand C (1998) Insight into naphthoquinone metabolism: β-glucosidase-catalysed hydrolysis of hydrojuglone β-D-glucopyranoside. Biochemical Journal 333:275–283PubMedGoogle Scholar
  19. Edwards A, Vincken JP, Suurs LCJM, Visser RGF, Zeeman S, Smith A (2002) Discrete forms of amylose are synthesized by isoforms of GBSSI in pea. Plant Cell Online 14:1767–1785CrossRefGoogle Scholar
  20. Fleige S, Pfaffl MW (2006) RNA integrity and the effect on the real-time qRT-PCR performance. Mol Asp Med 27:126–139CrossRefGoogle Scholar
  21. Gachon C, Mingam A, Charrier B (2004) Real-time PCR: what relevance to plant studies? J Exp Bot 55:1445–1454PubMedCrossRefGoogle Scholar
  22. Galau GA, Dure L III (1981) Developmental biochemistry of cottonseed embryogenesis and germination: changing messenger ribonucleic acid populations as shown by reciprocal heterologous complementary deoxyribonucleic acid-messenger ribonucleic acid hybridization. Biochemistry 20:4169–4178PubMedCrossRefGoogle Scholar
  23. Galau GA, Bijaisoradat N, Hughes DW (1987) Accumulation kinetics of cotton late embryogenesis-abundant mRNAs and storage protein mRNAs: coordinate regulation during embryogenesis and the role of abscisic acid. Dev Biol 123:198–212PubMedCrossRefGoogle Scholar
  24. Guénin S, Mauriat M, Pelloux J, Van Wuytswinkel O, Bellini C, Gutierrez L (2009) Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references. J Exp Bot 60:487–493PubMedCrossRefGoogle Scholar
  25. Guillermo M, Mónica S, Vanesa M, Graciela T (2011) Reference gene selection for gene expression studies using RT-qPCR in virus-infected plant hoppers. Virol J 8:308CrossRefGoogle Scholar
  26. Hird DL, Worrall D, Hodge R, Smartt S, Paul W, Scott R (1993) The anther-specific protein encoded by the Brassica napus and Arabidopsis thaliana A6 gene displays similarity to β-1,3-glucanases. Plant J 4:1023–1033PubMedCrossRefGoogle Scholar
  27. Hong B, Uknes SJ, Ho TD (1988) Cloning and characterization of a cDNA encoding a mRNA rapidly-induced by ABA in barley aleurone layers. Plant Mol Biol 11:495–506CrossRefGoogle Scholar
  28. Hong SY, Seo PJ, Yang MS, Xiang F, Park CM (2008) Exploring valid reference genes for gene expression studies in Brachypodium distachyon by real-time PCR. BMC Plant Biol 8:112PubMedCrossRefGoogle Scholar
  29. Hu R, Fan C, Li H, Zhang Q, Fu YF (2009) Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. BMC Mol Biol 10:93PubMedCrossRefGoogle Scholar
  30. Hundertmark M, Hincha D (2008) LEA (Late Embryogenesis Abundant) proteins and their encoding genes in Arabidopsis thaliana. BMC genomics 9:118PubMedCrossRefGoogle Scholar
  31. Hylton CM, Denyer K, Keeling PL, Chang MT, Smith AM (1996) The effect of waxy mutations on the granule-bound starch synthases of barley and maize endosperms. Planta 198:230–237CrossRefGoogle Scholar
  32. Jain M, Nijhawan A, Tyagi AK, Khurana JP (2006) Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem Biophys Res Commun 345:646–651PubMedCrossRefGoogle Scholar
  33. Jakobsen MK, Poulsen LR, Schulz A, Fleurat-Lessard P, Møller A, Husted S (2005) Pollen development and fertilization in Arabidopsis is dependent on the MALE GAMETOGENESIS IMPAIRED ANTHERS gene encoding a type V P-type ATPase. Genes Dev 19:2757–2769PubMedCrossRefGoogle Scholar
  34. Jan KC, Hwang LS, Ho CT (2009) Biotransformation of sesaminol triglucoside to mammalian lignans by intestinal microbiota. J Agric Food Chem 57:6101–6106PubMedCrossRefGoogle Scholar
  35. Jan KC, Ku KL, Chu YH, Hwang LS, Ho CT (2010) Tissue distribution and elimination of estrogenic and anti-Inflammatory catechol metabolites from sesaminol triglucoside in rats. J Agric Food Chem 58:7693–7700PubMedCrossRefGoogle Scholar
  36. Jan KC, Ku KL, Chu YH, Hwang LS, Ho CT (2011) Intestinal distribution and excretion of sesaminol and its tetrahydrofuranoid metabolites in rats. J Agric Food Chem 59:3078–3086PubMedCrossRefGoogle Scholar
  37. Jian B, Liu B, Bi Y, Hou W, Wu C, Han T (2008) Validation of internal control for gene expression study in soybean by quantitative real-time PCR. BMC Mol Biol 9:59PubMedCrossRefGoogle Scholar
  38. Jin UH, Lee JW, Chung YS, Lee JH, Yi YB, Kim YK (2001) Characterization and temporal expression of a ω-6 fatty acid desaturase cDNA from sesame (Sesamum indicum L.) seeds. Plant Sci 161:935–941CrossRefGoogle Scholar
  39. Jungen K, Xiaowu W, Guoyu Z, Yanguo Z, Ping L, Zhiyuan F (2006) Sequential expression of fertility-related genes detected by cDNA-AFLP in different types of cabbage male sterile lines. Acta Horticulturae Sinica 33:544–548Google Scholar
  40. Kang IK, Suh SG, Gross KC, Byun JK (1994) N-terminal amino acid sequence of persimmon fruit β-galactosidase. Plant Physiol 105:975–979PubMedCrossRefGoogle Scholar
  41. Kim MJ, Kim JK, Shin JS, Suh MC (2007) The SebHLH transcription factor mediates trans-activation of the SeFAD2 gene promoter through binding to E-and G-box elements. Plant Mol Biol 64:453–466PubMedCrossRefGoogle Scholar
  42. Kim MJ, Go YS, Lee SB, Kim YS, Shin JS, Min MK (2010) Seed-expressed casein kinase I acts as a positive regulator of the SeFAD2 promoter via phosphorylation of the SebHLH transcription factor. Plant Mol Biol 73:425–437PubMedCrossRefGoogle Scholar
  43. Lee JM, Roche JR, Donaghy DJ, Thrush A, Sathish P (2010) Validation of reference genes for quantitative RT-PCR studies of gene expression in perennial ryegrass (Lolium perenne L.). BMC Mol Biol 11:8PubMedCrossRefGoogle Scholar
  44. Liao CD, Hung WL, Lu WC, Jan KC, Shih DYC, Yeh AI (2009) Differential tissue distribution of sesaminol triglucoside and its metabolites in rats fed with lignan glycosides from sesame meal with or without Nano/Submicrosizing. Journal of agricultural and food chemistry 58:563–569CrossRefGoogle Scholar
  45. Liu LM, Liu HY, Tian BM (2012) Selection of reference genes from sesame infected by Macrophomina phaseolina. Acta Agron Sin 38:471–478Google Scholar
  46. Maroufi A, Van Bockstaele E, De Loose M (2010) Validation of reference genes for gene expression analysis in chicory (Cichorium intybus) using quantitative real-time PCR. BMC Mol Biol 11:15PubMedCrossRefGoogle Scholar
  47. Mochizuki M, Tsuchie Y, Yamada N, Miyake Y, Osawa T (2010) Effect of sesame lignans on TNF-α-induced expression of adhesion molecules in endothelial cells. Biosci Biotechnol Biochem 74:1539–1544PubMedCrossRefGoogle Scholar
  48. Moctezuma E, Smith DL, Gross KC (2003) Antisense suppression of a β-galactosidase gene (TB G6) in tomato increases fruit cracking. J Exp Bot 54:2025–2033PubMedCrossRefGoogle Scholar
  49. Nakamura T, Vrinten P, Hayakawa K, Ikeda J (1998) Characterization of a granule-bound starch synthase isoform found in the pericarp of wheat. Plant Physiol 118:451–459PubMedCrossRefGoogle Scholar
  50. Nicot N, Hausman JF, Hoffmann L, Evers D (2005) Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. J Exp Bot 56:2907–2914PubMedCrossRefGoogle Scholar
  51. Park MR, Cho E, Rehman S, Yun SJ (2010) Expression of a sesame geranylgeranyl reductase cDNA is induced by light but repressed by abscisic acid and ethylene. Pak J Bot 42:1815–1825Google Scholar
  52. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper–Excel-based tool using pair-wise correlations. Biotechnol Lett 26:509–515PubMedCrossRefGoogle Scholar
  53. Qi J, Yu S, Zhang F, Shen X, Zhao X, Yu Y, Zhang D (2010) Reference gene selection for real-time quantitative polymerase chain reaction of mRNA transcript levels in Chinese cabbage (Brassica rapa L. ssp. pekinensis). Plant Molecular Biology Reporter 28:597–604CrossRefGoogle Scholar
  54. Ramakers C, Ruijter JM, Deprez RHL, Moorman AFM (2003) Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett 339:62–66PubMedCrossRefGoogle Scholar
  55. Raynal M, Depigny D, Cooke R, Delseny M (1989) Characterization of a radish nuclear gene expressed during late seed maturation. Plant Physiol 91:829–836PubMedCrossRefGoogle Scholar
  56. Sattler SE, Singh J, Haas EJ, Guo L, Sarath G, Pedersen JF (2009) Two distinct waxy alleles impact the granule-bound starch synthase in sorghum. Mol Breeding 24:349–359CrossRefGoogle Scholar
  57. Szydlowski N, Ragel P, Hennen-Bierwagen TA, Planchot V, Myers AM, Mérida A (2011) Integrated functions among multiple starch synthases determine both amylopectin chain length and branch linkage location in Arabidopsis leaf starch. J Exp Bot 62:4547–4559PubMedCrossRefGoogle Scholar
  58. Tai SSK, Chen MCM, Peng CC, Tzen JTC (2002) Gene family of oleosin isoforms and their structural stabilization in sesame seed oil bodies. Biosci Biotechnol Biochem 66:2146–2153PubMedCrossRefGoogle Scholar
  59. Takahashi R, Joshee N, Kitagawa Y (1994) Induction of chilling resistance by water stress, and cDNA sequence analysis and expression of water stress-regulated genes in rice. Plant Mol Biol 26:339–352PubMedCrossRefGoogle Scholar
  60. Thellin O, Zorzi W, Lakaye B, De Borman B, Coumans B, Hennen G, Grisar T, Igout A, Heinen E (1999) Housekeeping genes as internal standards: use and limits. J Biotechnol 75:291–295PubMedCrossRefGoogle Scholar
  61. Thellin O, ElMoualij B, Heinen E, Zorzi W (2009) A decade of improvements in quantification of gene expression and internal standard selection. Biotechnol Adv 27:323–333PubMedCrossRefGoogle Scholar
  62. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3: research0034Google Scholar
  63. Vrinten PL, Nakamura T (2000) Wheat granule-bound starch synthase I and II are encoded by separate genes that are expressed in different tissues. Plant Physiol 122:255–264PubMedCrossRefGoogle Scholar
  64. Wan H, Zhao Z, Qian C, Sui Y, Malik AA, Chen J (2010) Selection of appropriate reference genes for gene expression studies by quantitative real-time polymerase chain reaction in cucumber. Anal Biochem 399:257–261PubMedCrossRefGoogle Scholar
  65. White CN, Rivin CJ (1995) Sequence and regulation of a late embryogenesis abundant group 3 protein of maize. Plant Physiol 108:1337–1338PubMedCrossRefGoogle Scholar
  66. Yukawa Y, Takaiwa F, Shoji K, Masuda K, Yamada K (1996) Structure and expression of two seed-specific cDNA clones encoding stearoyl-acyl carrier protein desaturase from sesame, Sesamum indicum L. Plant Cell Physiol 37:201–205PubMedCrossRefGoogle Scholar
  67. Zhang HY, Wei LB, Miao HM, Zhang TD, Wang CY (2012) Development and validation of genic-SSR markers in sesame by RNA-seq. BMC Genomics 13:316PubMedCrossRefGoogle Scholar

Copyright information

© The Author(s) 2012

Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Authors and Affiliations

  • Libin Wei
    • 1
  • Hongmei Miao
    • 1
  • Ruihong Zhao
    • 1
  • Xiuhua Han
    • 1
  • Tide Zhang
    • 1
  • Haiyang Zhang
    • 1
  1. 1.Henan Sesame Research CenterHenan Academy of Agricultural SciencesZhengzhouPeople’s Republic of China

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