Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill
© de Almeida et al; licensee BioMed Central Ltd. 2010
Received: 5 April 2010
Accepted: 20 September 2010
Published: 20 September 2010
Eucalyptus globulus and its hybrids are very important for the cellulose and paper industry mainly due to their low lignin content and frost resistance. However, rooting of cuttings of this species is recalcitrant and exogenous auxin application is often necessary for good root development. To date one of the most accurate methods available for gene expression analysis is quantitative reverse transcription-polymerase chain reaction (qPCR); however, reliable use of this technique requires reference genes for normalization. There is no single reference gene that can be regarded as universal for all experiments and biological materials. Thus, the identification of reliable reference genes must be done for every species and experimental approach. The present study aimed at identifying suitable control genes for normalization of gene expression associated with adventitious rooting in E. globulus microcuttings.
By the use of two distinct algorithms, geNorm and NormFinder, we have assessed gene expression stability of eleven candidate reference genes in E. globulus: 18S, ACT2, EF2, EUC12, H2B, IDH, SAND, TIP41, TUA, UBI and 33380. The candidate reference genes were evaluated in microccuttings rooted in vitro, in presence or absence of auxin, along six time-points spanning the process of adventitious rooting. Overall, the stability profiles of these genes determined with each one of the algorithms were very similar. Slight differences were observed in the most stable pair of genes indicated by each program: IDH and SAND for geNorm, and H2B and TUA for NormFinder. Both programs indentified UBI and 18S as the most variable genes. To validate these results and select the most suitable reference genes, the expression profile of the ARGONAUTE1 gene was evaluated in relation to the most stable candidate genes indicated by each algorithm.
Our study showed that expression stability varied between putative reference genes tested in E. globulus. Based on the AGO1 relative expression profile obtained using the genes suggested by the algorithms, H2B and TUA were considered as the most suitable reference genes for expression studies in E. globulus adventitious rooting. UBI and 18S were unsuitable for use as controls in qPCR related to this process. These findings will enable more accurate and reliable normalization of qPCR results for gene expression studies in this economically important woody plant, particularly related to rooting and clonal propagation.
Eucalyptus sp. is one of the most planted hardwood genus in the world , mainly because of its applications for generating wood and paper products. Brazil is the largest world producer of eucalypts for short fiber pulp , thanks to clonal forests developed from elite material with high productivity . In southern Brazil and temperate areas, especially Mediterranean Europe, Portugal and Chile, Eucalyptus globulus and its hybrids are of interest for the cellulose industry due to their relatively high frost resistance and low lignin content, which facilitates cellulose extraction . On the other hand, E. globulus is generally considered recalcitrant to rooting [5, 6]. The commercial eucalypt forests are generally formed through vegetative propagation which has adventitious rooting as a key step . This developmental process can be divided in two main steps, each with its own requirements and characteristics: (1) induction step, which involves biochemical and molecular events, without visible morphological changes; and (2) formation step, which consists of cellular divisions involved in both root meristem organization and primordium establishment, followed by root elongation and emergence out of the cutting .
Multiple factors can interfere with adventitious rooting, such as phytohormones, phenolic compounds, nutritional conditions and genetic characteristics . Among phytohormones, auxins play a central role in rooting capacity , particularly its endogenous content and transport rate . However, concentrations that are beneficial to root induction can block its elongation . The shoot apex is the main source of endogenous auxin. Stems have a specific basipetal active transport through vascular parenchyma carried out by both influx (AUX1) and efflux (PIN) carriers [12, 13].
Eucalyptus globulus needs exogenous auxin application for an adequate root development in vitro, but it is unknown if this occurs because of defficiencies in auxin content, transport or perception mechanisms, or due to some other non-auxin related reason that can block spontaneous rooting responses. At gene expression level, little is known about the formation of root meristems in woody plants and even less concerning the effect of auxins on this process .
To evaluate changes in gene expression, reverse-transcription followed by quantitative, real-time polymerase chain reaction (qPCR) is one of the most widely used methods. Some of the advantages of qPCR are high sensitivity and specificity, speed, ease of use and capacity to carry out simultaneous measurements of gene expression in several different samples for a limited number of genes [15–17]. To accurately and reproducibly quantify gene expression, some factors should be taken into account, such as quality and amount of starting material, presence of inhibitors in different samples, primer design, RNA extraction and reverse-transcription efficiencies . Therefore, selection of an appropriate normalization strategy is essential for obtaining an accurate and reliable quantification of gene expression levels [15, 16, 18]. The most commonly applied approach for normalization of qPCR is the use of one or more endogenous reference genes [18–20], which will undergo the same type of variation and preparation steps throughout the assay as the target genes.
An ideal reference gene, also known as housekeeping or internal control gene, is assumed to be constitutive, i.e., it should be expressed at a constant level in the majority of the study organism cells, through different developmental stages and in different organs. Besides, its expression is assumed to be unaffected by experimental parameters . Genes involved in basic cellular processes, such as cell structure maintenance or primary metabolism, are often chosen as normalizers . However, the transcript levels of these putative reference genes are not always stable and their systematic use without previous validation may lead to the misinterpretation of results. Indeed, the previous assurance of at least one stable gene expression in all variable situations tested is recommended to accurately validate the expression of genes under analysis [22–27]. In recent years, a large number of reference gene validation attempts have been reported for plants, but most of them have covered model and crop species: rice [28, 29], sugarcane , Arabidopsis thaliana[22, 31], potato , grape , barley , Brachypodium sp. , soybean [35, 36], tomato , Brachiaria sp. , coffee , peach , wheat , chicory , cotton , cucumber , longan tree , Petunia sp. , ryegrass , rapeseed  and tobacco . Just a few studies have focused on forest genera, such as poplar [25, 27] and Eucalyptus sp. ; however, there is a lack of investigations covering in vitro growth or adventitious rooting.
Description of reference genes used for qPCR in Eucalyptus globulus.
Arabidopsis thaliana's best hit locus
Arabidopsis thaliana locus description
Putative E. globulus orthologs GeneBank accession number
RNA ribosomal 18S
RNA ribosomal 18S
Cytosolic small ribosomal subunit, translation
Structural constituent of cytoskeleton
Translation elongation factor 2
Translation elongation factor 2, putative
Translation factor activity, nucleic acid binding
Putative RNA bindig protein
Histone H2B, putative
Strutural constituent of the eukaryotic nucleosome core
Polyubiquitin gene, belongs to a subtype group with UBQ10 and UBQ14
Signalling complexes for protein degradation, translation control, DNA repair, endocytosis regulation, protein traffic
SAND family protein
Intracellular vesicular transport, biogenesis and vacuole signalling
TIP41-like family protein
Structural constituent of cytoskeleton, microtubule-based processes
Primer sequences and amplicon characteristics for each of the 11 reference genes and for the Argonaute 1 gene of interest.
Primer sequence (5' → 3')
Expression levels of reference gene candidates
Expression stability of reference gene candidates
Two programs were used to evaluate the stability of the 11 candidate reference genes: geNorm and NormFinder. Cq data were collected for all samples and transformed to relative quantities using the delta-Cq method developed by Livak and Schmittgen  (see Material and Methods section for details).
Ranking of candidate reference genes in decreasing order of expression stability calculated by geNorm and NormFinder.
NormFinder(Stability value ± EB*)
H2B (0.031 ± 0.006)
TUA (0.084 ± 0.067)
IDH (0.116 ± 0.082)
EUC12 (0.121 ± 0.087)
TIP41 (0.123 ± 0.091)
SAND (0.143 ± 0.124)
33380 (0.161 ± 0.156)
EF2 (0.174 ± 0.183)
ACT2 (0.186 ± 0.215)
UBI (0.306 ± 0.566)
18S (0.547 ± 1.833)
In addition to the analysis by the geNorm software, the expression stability of the candidate reference genes on the experimental samples was also evaluated by NormFinder. This program takes into account the intra- and inter-group variations for normalization factor calculation and the results are not affected by occasional co-regulated genes. The best candidate will be the one with the inter-group variation as close to zero as possible, and, at the same time, having the smallest errors bars possible . A change in the indication of most stable genes was observed after NormFinder analysis when compared to geNorm, with H2B showing the most stable expression (near zero variation value and small error bars), followed by TUA. These two genes were also among the most stably expressed genes based on geNorm analysis, displaying M values below 0.5 (Figure 3). UBI and 18S were the least stable genes (both with variation values farther from zero and larger error bars) (Table 3). When defining the best combination of two genes using NormFinder, once again both H2B and TUA were the genes of choice, with a stability value of 0.045 when used together (data not show).
Relative expression profile of AGO1
To further validate the control genes and for determining the best choice of genes to use, the relative expression of a putative ortholog of A. thaliana ARGONAUTE1 (AGO1) gene in E. globulus was investigated during rooting. AGO1 encodes a micro RNA binding protein  involved in regulating the expression of ARF17 (Auxin Response Factor 17), an auxin response transcription factor with inhibitory action, possibly controling genes related to auxin homeostasis and adventitious root development in A. thalina. The two gene pairs indicated by geNorm and Normfinder were used as references to evaluate AGO1 relative expression in eight samples, covering time points of adventitious root induction and formation, both under presence and absence of auxin during the induction step.
In gene expression studies, qPCR is often the method of choice for a target gene expression profile investigation because it is currently one of the most sensitive techniques available [15–17, 20]. In this context, a correct normalization is a pre-requisite for the reliability of the final results [59, 60], especially considering possible biological relevance of small differences in gene expression or in the study of different tissues and organ samples .
In the present work, candidate reference genes for expression studies on adventitious rooting in E. globulus microcuttings were selected based on previous reports of normalization in plants, mainly with A. thaliana, Populus sp. and Eucalyptus sp., taking into account the model plant status of the first species and the woody habit of the last two genera. Additional genes frequently used for normalization in qPCR studies in other plant species were also evaluated.
The use of a single reference gene has been avoided to minimize the chances of erroneous expression estimates [24, 57]. In fact, the use of multiple reference genes is becoming the golden standard in expression studies . In order to select the most suitable reference genes for use in adventitious rooting, we investigated the relative expression profile of a gene of interest (AGO1) during this process, using the pairs of reference genes indicated as most stable by each one of the programs (geNorm and NormFinder).
An increase in AGO1 expression would be expected during microcutting root development considering its function in regulating auxin metabolism-related genes during adventitious rooting in Arabidopsis. The higher AGO1 expression in the absence of auxin may be due to a lower requirement for the regulation of auxin-metabolism related genes in presence of exogenous auxin.
Therefore, NormFinder seemed to be better suited for the selection of the most stable reference genes for monitoring gene expression during adventitious rooting, detecting subtle differences that can be regarded as important for the adventitious rooting process. Recent studies have reported some discrepancies between different approaches for selection of reference genes and have chosen NormFinder[43, 45, 61, 62] as data analysis tool. This is mainly due to the wide applicability of this tool in any kind of experimental design, especially when involving different cell types and experimental stages associated with high variation of gene expression [45, 51]. Hence, we suggest H2B and TUA as the most adequate reference genes for expression studies during the rooting of E. globulus microcuttings.
H2B (Histone H2B) is one of the four core histones that form the mononucleosome, the fundamental repeating unit of chromatin in eukaryotic cells , being a key component for genetic material structure . Two works have motivated us to include H2B in our analysis. Hays et al.  employed it as reference in Northern blot analysis to assess differential gene expression between alfalfa (Medicago sativa L.) varieties exhibiting long- or short-stalked glandular hairs. Later, Sterky et al. , through a transcriptomics approach, showed that transcripts for histones (and ribosomal proteins) were among the most ubiquitous gene products present in different tissues and species of Populus. More recently, a histone H3 gene was included when defining reference genes for the analysis of gene expression in longan tree somatic embryogenesis by qPCR . Nevertheless, histone genes have been employed as references mostly for expression studies in animal systems [66, 67].
The high expression stability showed in our experiments for TUA corroborates data of Brunner et al. in a study with poplar. On the other hand, Tong and collaborators found TUA as one of the most variable genes for studies with peach, except when comparing genotypes or different storage time of fruit .
Data to date point to IDH as the most used control gene for normalization in Eucalyptus sp. [53–55], but without indication of a previous reference-gene detailed analysis. Although elected as the most stably expressed gene in Eucalyptus clones under biotic and abiotic stress , results from the present study did not support ranking IDH as one of the best reference genes because, together with SAND, it appears less sensitive to detect slight differences in the expression profile of an adventitious rooting-related gene of interest. This fact reinforces the need of detailed reference gene analysis for specific experimental conditions and processes.
Adventitious rooting is a very complex process, regulated by both environmental and endogenous factors, but the molecular mechanisms by which adventitious root formation is regulated are still poorly understood. Important advances are upcoming with genetic and microarray studies in Populus, especially after the availability of the poplar genome . Studying gene expression during rooting in Pinus contorta, Brinker et al. reported an increased expression of genes involved in protein synthesis and a decreased expression of genes related to protein degradation for the first 3 days after auxin treatment, whereas an opposite trend was observed during root formation and elongation. Sorin et al. also identified proteins with altered expression during adventitious rooting in Arabidopsis mutants, and, among these, there were some related to protein degradation . These observations may help explain the low expression stability of the gene for polyubiquitin (UBI) found in our experiments (Figure 3 and Table 3), since the product of this gene is known to function in protein degradation .
The least stably expressed gene was 18S, both by geNorm and NormFinder analysis (Figure 3 and Table 3). The use of rRNA as reference gene was previously considered a good strategy in gene expression studies  but recent works suggest that this is often not the case [24, 72, 29, 40, 44, 45]. This is possibly due to the high abundance of 18S rRNA compared with target mRNA transcripts, making it difficult to accurately subtract the baseline value in qPCR data analysis . Besides, 18S rRNA can not be used for this purpose when reverse transcription is carried out using oligo-dT primers or only mRNA is used as template .
The most stably expressed genes identified in this study, H2B and TUA, were effective references in both phases of the rooting process, induction and formation, and also in presence or absence of auxin, i.e. with conditions leading to profuse and scarce root development, respectively (Figure 2B and Figure 5B). This is a rather important feature because it allows the use of these genes as internal controls in evaluating the expression of putative key genes in the rooting process that are likely to vary between phases and in conditions leading or not to root development . These key genes may include those encoding auxin transporters, auxin metabolism enzymes, auxin receptors and selective proteolysis-related proteins .
This work constitutes the first in-depth study to validate optimal control genes for the quantification of transcript levels in E. globulus during in vitro adventitious rooting.
Considering that both programs used are based on distinct statistical algorithms, potential discrepancies could be expected. The comparative AGO1 expression profile, using the combinations of reference genes indicated by each program, allowed us to suggest the most adequate combination of control genes, based on the functions described in the literature for this gene of interest. Hence, the NormFinder program was considered more appropriate for our experiments, indicating H2B and TUA as suitable reference genes for normalization in E. globulus microcuttings rooted in vitro. Besides, UBI and 18S are not indicated for use as internal controls in this species under the conditions tested.
In summary, these findings represent useful tools for normalization of qPCR results and will enable more accurate and reliable gene expression studies related to the vital process of clonal propagation by rooting in this important woody species.
Seeds of Eucalyptus globulus Labill (batches from Chile and kindly supplied by Celulose Riograndense S.A., Guaíba, RS, Brazil) were surface-sterilized in 70% (v/v) ethanol (1 min) and 1.5% (v/v) NaClO (20 min) followed by 4 washes in sterile distilled water. Fifteen seeds were planted in 300 ml glass flasks (capped with a double layer of aluminum foil) containing 60 ml of medium as follows: half-strength modified MS salts  with the concentration of calcium chloride reduced to 1/6, 2% (w/v) sucrose, pH adjusted to 5.8 ± 1 and 0.6% (w/v) agar (extra pure microbiological grade, Merck) . The medium was sterilized in autoclave for 20 min at 121°C. The growth room conditions were 16 h photoperiod, 30 μmol m-2s-1 of photosynthetically active radiation (provided by white light fluorescent tubes) and temperature of 23 ± 2°C. After 14 weeks, tip microcuttings (about 3 cm in length) were excised from the seedlings and used for in vitro rooting experiments.
In vitro adventitious rooting experiments
The culture system consisted of a two-step protocol: an initial step of induction, which lasted 96 h (induction medium composition: 0.3x MS salt concentration, 0.4 mg l-1 thiamine HCl, 100 mg l-1 inositol, zero (control) or 10 mg l-1 indolyl-butyric acid (leading to rooting), equivalent to 49.3 μM, 30 g l-1 sucrose and 6 g l-1 agar, adjusted to pH 5.8 ± 1 before autoclaving), followed by a formation step (same composition of induction medium except without added auxin and supplemented with 1 g l-1 activated charcoal) .
Experiments were carried out in 20 ml glass vials containing 6 ml of medium, which were capped with a double layer of aluminum foil, at a density of two explants per vial. Both treatments (presence and absence of auxin during the induction step) were carried out in a growth room with the same conditions described above for seed germination.
The expression analysis of the selected genes was monitored along the rooting process and the harvest of microcuttings for RNA extraction was at 12, 24, 48 and 96 h of exposure to induction medium and 24 and 48 h after transfer to formation medium (formation step), for both treatments (with and without auxin in the first step). For the formation step harvest, the microcuttings remained for 96 h in the induction medium before transfer to formation medium (see Figure 1 for details). The microcuttings were immediately frozen in liquid nitrogen and stored at -80°C until RNA extraction. Each point of harvest combined six microcuttings (approximately 200 mg of homogenized tissue fresh weight). The experimental design was completely randomized and the experiments were independently repeated three times with similar results.
Total RNA extraction and first strand cDNA synthesis
Total RNA was isolated using NucleoSpin RNA Plant Kit (Macherey-Nagel) including DNAse I treatment, following the manufacturer recommendations, with modifications as follows: 200 mg of homogenized tissue fresh weight from each sample was divided in two fractions of 100 mg. Each fraction of 100 mg had its RNA extracted separately. After the extraction procedure, the corresponding fractions were joined again for RNA quantification. Total RNA concentration was determined using Quant-iT™ RNA Assay Kit and the Qubit fluorometer (Invitrogen) and quality was monitored by electrophoresis in 1% agarose gel (data not show). One independent cDNA synthesis was performed for all of the samples starting from 100 ng total RNA. First strand cDNA synthesis was performed using oligo-dT primers and reverse transcriptase M-MLV (Invitrogen) in a final volume of 20 μl. The final cDNA products were diluted 10-fold in RNAse-free distilled water prior to use in qPCR.
PCR primer design
The sequences used to design the primer pairs, except IDH, whose primers were obtained from Carvalho et al., represent putative orthologs in eucalypt of genes chosen for this study and are described in Table 1. For that, sequences placed in the Arabidopsis thaliana Database (http://www.arabidopsis.org) were subjected to a tBlastx against the Genolyptus Project Database (http://www.lge.ibi.unicamp.br/eucalyptus/) and the sequence with highest homology was selected. For all genes, primer pairs were designed using Oligo Perfect™ Designer software (Invitrogen) and are described in Table 2. The specifications were: melting temperatures (Tm) of 58 - 62°C, primer lengths of 20 nucleotides, guanine-cytosine contents of 45-55% and PCR amplicon lengths of 100-150 base pairs.
The qPCR analyses were performed in fast optical 48-well reaction plates 0.1 ml (MicroAmp™- Applied Biosystems) using a StepOne™ Real-Time PCR System (Applied Biosystems) according to the manufacturer instructions. All of the reactions were carried out in quadruplicates for each cDNA sample and contained 10 μl 10-fold diluted cDNA template, 4.25 μl sterile water, 2 μl 10× PCR Buffer (Invitrogen), 1.2 μl of 25 mM MgCl2 (Invitrogen), 0.1 μl of 10 mM dNTP (Invitrogen), 2 μl SYBR Green (1:10,000, Molecular Probes, Applied Biosystems), 0.2 μl of each of the 10 μM forward and reverse gene-specific primers and 0.05 μl Platinum® Taq DNA polymerase (5 U/μl, Invitrogen) in a final volume of 20 μl. This experiment was repeated three times in independent runs for all selected genes per time sample.
Reactions were incubated at 95°C for 5 min to activate the Platinum® Taq DNA polymerase (Invitrogen), followed by 40 cycles of 95°C for 15 sec, 60°C for 10 sec, and 72°C for 15 sec. The specificity of the PCR was confirmed with a heat dissociation curve (or melting curve) from 60°C to 90°C, following the final PCR cycle. This procedure allowed us to verify that the resulting fluorescence originated from a single PCR product and did not represent primer dimerization formed during PCR or a non-specific product.
Determination of reference gene expression stability
Two publicly available software tools, geNorm v. 3.5  and NormFinder were used to evaluate gene expression stability. Both tools require the transformation of Cq (quantification cycle) values to linear scale expression quantities. The Cq values were converted into relative quantities by the delta-Cq method  using the sample with the lowest Cq as calibrator and taking into account the amplification efficiencies for each primer pair obtained with LinReg PCR software. The measures were then exported to Microsoft Excel.
The geNorm software is a Visual Basic Application (VBA) tool for Microsoft Excel and relies on the principle that the expression ratio of two ideal reference genes should be constant throughout the different experimental conditions or cell types . This program estimates an expression stability value (M) for each gene, defined as the average pairwise variation of a certain gene with all other control genes in a given panel of cDNA samples. Genes with the lowest M values have the most stable expression and an ideal M-value must be preferably <0.5 [57, 27]. Reference genes are ranked by geNorm through the elimination of the worst-scoring candidate control gene (the one with the highest M value) and recalculating of new M values for the remaining genes. At the end of this procedure, two candidate genes are always top-ranked because expression ratios are required for gene-stability measurements . The geNorm program also allows the establishment of minimal number of control genes required for calculating an accurate normalization factor, as the geometric mean of their relative quantities. A pairwise variation of 0.15 is accepted as cut-off below which the inclusion of an additional control gene is not required for reliable normalization.
The NormFinder software , another VBA applet, uses a model-based approach for identifying the optimal normalization gene(s) among a set of candidates. This strategy is based on a mathematical model of gene expression that enables estimation of the intra- and inter-group variations, which are combined into a stability value. Candidate control genes with the minimal intra-group variation will have the lowest stability value and will be top ranked . For adequate application of the NormFinder program, the sample sets were subdivided in two groups (presence and absence of auxin in the induction step of adventitious rooting) with each of them containing 6 samples.
Determination of AGO1 expression profile
The putative A. thaliana AGO1 ortholog in E. globulus had its expression profile investigated in eight samples among the twelve analyzed in this study (12 and 24 h after inoculation in induction medium, and 24 and 48 h after transfer to formation medium, both in presence and absence of auxin in induction medium). The experiment was carried out with three biological replicates and the qPCR method and primer design strategy followed the same parameters used for the analysis of reference genes. The relative expression profile analysis was obtained through the delta-Cq method . Analysis of Variance (ANOVA), followed by Duncan's test when appropriate (P ≤ 0.05), were applied for samples of the same treatment (presence or absence of auxin). To compare the same time point of different treatments, a t-test was used (P ≤ 0.05).
List of abbreviations
Auxin Resistant 1
Arabidopsis thaliana PIN-Formed proteins
reverse-transcription followed by quantitative real-time Polymerase Chain Reaction
Polymerase Chain Reaction
Visual Basic Application
complementary Deoxyribonucleic Acid.
This research was funded by the Brazilian agencies National Council for Scientific and Technological Development (CNPq) and National Commission for Graduate Program Funding and Evaluation (CAPES). Seeds of E. globulus were a gift from Celulose Riograndense (Guaíba, RS, Brazil).
- Del Lungo A, Ball J, Carle J: Global planted forests thematic study: results and analysis. Planted Forests and Trees Working Paper 38. 2006, FAO (Food and Agriculture Organization of the United Nations - Forestry Department)Google Scholar
- Statistical yearbook from ABRAF. 2009, Brazilian Association of Foresters (Associação Brasileira de Produtores de Florestas Plantadas)
- Mora AL, Garcia CH: The Eucalyptus Culture in Brazil (A Cultura do Eucalipto no Brasil). 2000, 112-SBS, São Paulo, Google Scholar
- Chiang V: From rags to riches. Nat Biotechnol. 2002, 20: 557-558. 10.1038/nbt0602-557View ArticlePubMedGoogle Scholar
- Le Roux JJ, Van Staden J: Micropropagation and tissue culture of Eucalyptus - a review. Tree Physiol. 1991, 9: 435-477.View ArticlePubMedGoogle Scholar
- Serrano L, Rochange F, Semblant JP, Marque C, Teulières C, Boudet AM: Genetic transformation of Eucalyptus globulus through biolistics: complementary development of procedures for organogenesis from zygotic embryos and stable transformation of corresponding proliferating tissue. J Exp Bot. 1996, 45: 285-290. 10.1093/jxb/47.2.285.View ArticleGoogle Scholar
- De Klerk GJ, Van Der Krieken W, De Jong JC: The formation of adventitious roots: New concepts, new possibilities. In Vitro Cell Dev-Pl. 1999, 35 (3): 189-199. 10.1007/s11627-999-0076-z.View ArticleGoogle Scholar
- Fett-Neto AG, Fett JP, Goulart LWV, Pasquali G, Termignoni RR, Ferreira AG: Distinct effects of auxin and light on adventitious root development in Eucalyptus saligna and Eucalyptus globulus. Tree Physiol. 2001, 21: 457-464.View ArticlePubMedGoogle Scholar
- Ruedell CM, Schwambach J, Corrêa LR, Fett-Neto AG: Strategies for adventitious rooting in clonal propagation of Eucalyptus. Adventitious root formation of forest trees and horticultural plants - From genes to applications. Edited by: Niemi K, Scagel C. 2009, 337-358. Kerala: Research Signpost, Google Scholar
- Sorin C, Bussell JD, Camus I, Ljung K, Kowalczyk M, Geiss G, Mckhann H, Garcion C, Vaucheret H, Sandberg G, Bellini C: Auxin and light control of adventitious rooting in Arabidopsis require ARGONAUTE 1. Plant Cell. 2005, 17: 1343-1359. 10.1105/tpc.105.031625View ArticlePubMedPubMed CentralGoogle Scholar
- Fogaça CM, Fett-Neto AG: Role of auxin and its modulators in the adventitious rooting of Eucalyptus species differing in recalcitrance. Plant Growth Regul. 2005, 45: 1-10. 10.1007/s10725-004-6547-7.View ArticleGoogle Scholar
- Muday GK, Delong A: Polar auxin transport: controlling where and how much. Trends Plant Sci. 2001, 6: 535-542. 10.1016/S1360-1385(01)02101-XView ArticlePubMedGoogle Scholar
- Benjamins R, Scheres B: Auxin: the looping star in plant development. Annu Rev Plant Biol. 2008, 59: 443-465. 10.1146/annurev.arplant.58.032806.103805View ArticlePubMedGoogle Scholar
- Li S-W, Xue L, Xu S, Feng H, An L: Mediators, genes and signaling in adventitious rooting. Bot Rev. 2009, 75: 230-247. 10.1007/s12229-009-9029-9.View ArticleGoogle Scholar
- Bustin SA: Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. J Mol Endocrinol. 2002, 29: 23-39. 10.1677/jme.0.0290023View ArticlePubMedGoogle Scholar
- Ginzinger DG: Gene quantification using real-time quantitative PCR: An emerging technology hits the mainstream. Exp Hematol. 2002, 30 (6): 503-512. 10.1016/S0301-472X(02)00806-8View ArticlePubMedGoogle Scholar
- Gachon C, Mingam A, Charrier B: Real time PCR: what relevance to plant studies?. J Exp Bot. 2004, 55 (402): 1445-1454. 10.1093/jxb/erh181View ArticlePubMedGoogle Scholar
- Huggett J, Dheda K, Bustin S, Zumla A: Real-time RT-PCR normalisation; strategies and considerations. Genes Immun. 2005, 1-6.Google Scholar
- Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT: The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments. Clin Chem. 2009, 55 (4): 611-622. 10.1373/clinchem.2008.112797View ArticlePubMedGoogle Scholar
- Van Guilder HD, Vrana KE, Freeman WM: Twenty-five years of quantitative PCR for gene expression analysis. BioTechniques. 2008, 44: 619-626. 10.2144/000112776View ArticleGoogle Scholar
- Thellin O, Zorzi W, Lakaye B, De Borman B, Coumans B, Hennen G, Grisar T, Igout A, Heinen E: Housekeeping genes as internal standards: use and limits. J Biotechnol. 1999, 75: 291-295. 10.1016/S0168-1656(99)00163-7View ArticlePubMedGoogle Scholar
- Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible W: Genome-wide identification and testing of superior reference-genes for transcript normalization in Arabidopsis. Plant Physiol. 2005, 139: 5-17. 10.1104/pp.105.063743View ArticlePubMedPubMed CentralGoogle Scholar
- Schmittgen TD, Zakrajsek BA: Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J Biochem Bioph Meth. 2000, 46: 69-81. 10.1016/S0165-022X(00)00129-9.View ArticleGoogle Scholar
- Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalisation of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002, 3: 1-11. 10.1186/gb-2002-3-7-research0034.View ArticleGoogle Scholar
- Brunner AM, Yakovlev IA, Strauss SH: Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol. 2004, 4: 14- 10.1186/1471-2229-4-14View ArticlePubMedPubMed CentralGoogle Scholar
- Nicot N, Hausman J, Hoffman L, Evers D: Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. J Exp Bot. 2005, 56 (421): 2907-2914. 10.1093/jxb/eri285View ArticlePubMedGoogle Scholar
- Gutierrez L, Mauriat M, Guénin S, Pelloux J, Lefebvre J, Louvet R, Rusterucci C, Moritz T, Guerineau F, Bellini C, Van Wuytswinkel O: The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RT-PCR) analysis in plants. Plant Biotechnol J. 2008, 6: 609-618. 10.1111/j.1467-7652.2008.00346.xView ArticlePubMedGoogle Scholar
- Kim BR, Nam HY, Kim SU, Kim SI, Chang YJ: Normalization of reverse transcription quantitative-PCR with housekeeping genes in rice. Biotechnol Lett. 2003, 25 (21): 1869-72. 10.1023/A:1026298032009View ArticlePubMedGoogle Scholar
- Jain M, Nijhawan A, Tyagi AK, Khurana JP: Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem Bioph Res Co. 2006, 345: 646-651. 10.1016/j.bbrc.2006.04.140.View ArticleGoogle Scholar
- Iskandar HM, Simpson RS, Casu RE, Bonnett GD, Maclean DJ, Manner JM: Comparison of reference genes for quantitative real-time polymerase chain reaction analysis of gene expression in sugarcane. Plant Mol Biol Rep. 2004, 22: 325-337. 10.1007/BF02772676.View ArticleGoogle Scholar
- Remans T, Smeets K, Opdenakker K, Mathijsen D, Vangronsveld J, Cuypers A: Normalization of real-time RT-PCR gene expression measurements in Arabidopsis thaliana exposed to increased metal concentrations. Planta. 2008, 227: 1343-1349. 10.1007/s00425-008-0706-4View ArticlePubMedGoogle Scholar
- Reid KE, Olsson N, Schlosser J, Peng F, Lund ST: An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development. BMC Plant Biol. 2006, 6: 27- 10.1186/1471-2229-6-27View ArticlePubMedPubMed CentralGoogle Scholar
- Faccioli P, Ciceri GP, Provero P, Stanca AM, Morcia C, Terzi V: A combined strategy of ''in silico'' transcriptome analysis and web search engine optimization allows an agile identification of reference genes suitable for normalization in gene expression studies. Plant Mol Biol. 2007, 63: 679-688. 10.1007/s11103-006-9116-9View ArticlePubMedGoogle Scholar
- Hong S, Seo PJ, Yang MS, Xiang F, Park CM: Exploring valid reference genes for gene expression studies in Brachypodium distachyon by real-time PCR. BMC Plant Biol. 2008, 8: 112- 10.1186/1471-2229-8-112View ArticlePubMedPubMed CentralGoogle Scholar
- Jian B, Liu B, Bi Y, Hou W, Wu C, Han T: Validation of internal control for gene expression study in soybean by quantitative real-time PCR. BMC Mol Biol. 2008, 9: 59- 10.1186/1471-2199-9-59View ArticlePubMedPubMed CentralGoogle Scholar
- Libault M, Thibivilliers S, Bilgin DD, Radwan O, Benitez M, Clough SJ, Stacey G: Identification of four soybean reference genes for gene expression normalization. Plant Genome. 2008, 1: 44-54. 10.3835/plantgenome2008.02.0091.View ArticleGoogle Scholar
- Expósito-Rodríguez M, Borges AA, Borges-Pérez A, Pérez JA: Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process. BMC Plant Biol. 2008, 8: 131- 10.1186/1471-2229-8-131View ArticlePubMedPubMed CentralGoogle Scholar
- Silveira ED, Alves-Ferreira M, Guimarães LA, Silva FR, Carneiro VTC: Selection of reference genes for quantitative real-time PCR expression studies in the apomictic and sexual grass Brachiaria brizantha. BMC Plant Biol. 2009, 9: 84- 10.1186/1471-2229-9-84View ArticlePubMedPubMed CentralGoogle Scholar
- Barsalobres-Cavallari CF, Severino FE, Maluf MP, Maia IG: Identification of suitable internal control genes for expression studies in Coffea arabica under different experimental conditions. BMC Molecular Biol. 2009, 10: 1-10.1186/1471-2199-10-1.View ArticleGoogle Scholar
- Tong Z, Gao Z, Wang F, Zhou J, Zhang Z: Selection of reliable reference genes for gene expression studies in peach using real-time PCR. BMC Mol Biol. 2009, 10: 71- 10.1186/1471-2199-10-71View ArticlePubMedPubMed CentralGoogle Scholar
- Paolacci AR, Tanzarella OA, Porceddu E, Ciaffi M: Identification and validation of reference genes for quantitative RT-PCR normalization in wheat. BMC Mol Biol. 2009, 10: 11- 10.1186/1471-2199-10-11View ArticlePubMedPubMed CentralGoogle Scholar
- Maroufi A, Van Bockstaele E, De Loose M: Validation of reference genes for gene expression analysis in chicory (Cichorium intybus) using quantitative real-time PCR. BMC Mol Biol. 2010, 11: 15- 10.1186/1471-2199-11-15View ArticlePubMedPubMed CentralGoogle Scholar
- Artico S, Nardeli SM, Brilhante O, Maria Grossi-de-Sá F, Alves-Ferreira M: Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data. BMC Plant Biol. 2010, 10: 49- 10.1186/1471-2229-10-49View ArticlePubMedPubMed CentralGoogle Scholar
- Wan H, Zhao Z, Qian C, Sui Y, Malik AA, Chen J: Selection of appropriate reference genes for gene expression studies by quantitative real-time polymerase chain reaction in cucumber. Anal Biochem. 2010, 399: 257-261. 10.1016/j.ab.2009.12.008View ArticlePubMedGoogle Scholar
- Lin YL, Lai ZX: Reference gene selection for qPCR analysis during somatic embryogenesis in longan tree. Plant Science. 2010, 178: 359-365. 10.1016/j.plantsci.2010.02.005.View ArticleGoogle Scholar
- Mallona I, Lischewski S, Weiss J, Hause B, Egea-Cortines M: Validation of reference genes for quantitative real-time PCR during leaf and flower development in Petunia hybrida. BMC Plant Biol. 2010, 10: 4- 10.1186/1471-2229-10-4View ArticlePubMedPubMed CentralGoogle Scholar
- Lee JM, Roche JR, Donaghy DJ, Thrush A, Sathish P: Validation of reference genes for quantitative RT-PCR studies on gene expression in perennial ryegrass (Lolium perenne L.). BMC Mol Biol. 2010, 11: 8- 10.1186/1471-2199-11-8View ArticlePubMedPubMed CentralGoogle Scholar
- Wu G, Zhang L, Wu Y, Cao Y, Lu C: Comparison of five endogenous reference genes for specific PCR detection and quantification of Brassica napus. J Agric Food Chem. 2010, 58: 2812-2817. 10.1021/jf904255bView ArticlePubMedGoogle Scholar
- Schmidt GW, Delaney SK: Stable internal reference genes for normalization of real-time RT-PCR in tobacco (Nicotiana tabacum) during development and abiotic stress. Mol Genet Genomics. 2010, 283: 233-241. 10.1007/s00438-010-0511-1View ArticlePubMedGoogle Scholar
- Boava LP, Laia ML, Jacob TR, Dabbas KM, Gonçalves JF, Ferro JA, Ferro MIT, Furtado EL: Selection of endogenous genes for gene expression studies in Eucalyptus under biotic (Puccinia psidii) and abiotic (acibenzolar-S-methyl) stresses using RTqPCR. BMC Res Notes. 2010, 3: 43- 10.1186/1756-0500-3-43View ArticlePubMedPubMed CentralGoogle Scholar
- Andersen CL, Jensen JL, Orntoft TF: 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. 2004, 64: 5245-5250. 10.1158/0008-5472.CAN-04-0496View ArticlePubMedGoogle Scholar
- Campos EI, Reinberg D: Histones: annotating chromatin. Annu Rev Genet. 2009, 43: 559-99. 10.1146/annurev.genet.032608.103928View ArticlePubMedGoogle Scholar
- Goicoechea M, Lacombe E, Legay S, Mihaljevic S, Rech P, Jauneau A, Lapierre C, Pollet B, Verhaegen D, Chaubet-Gigot N, Grima-Pettenati J: EgMYB2, a new transcriptional activator from Eucalyptus xylem, regulates secondary cell wall formation and lignin biosynthesis. Plant Journal. 2005, 43: 553-567. 10.1111/j.1365-313X.2005.02480.xView ArticlePubMedGoogle Scholar
- Legay S, Lacombe E, Goicoechea M, Brièrea C, Séguind A, Mackayc J, Grima-Pettenati J: Molecular characterization of EgMYB1, a putative transcriptional repressor of the lignin biosynthetic pathway. Plant Sci. 2007, 173 (5): 542-549. 10.1016/j.plantsci.2007.08.007.View ArticleGoogle Scholar
- Carvalho MCCG, Caldas DGG, Carneiro RT, Moon DH, Salvatierra GR, Franceschini LM, Andrade A, Celedon PAF, Oda S, Labate CA: SAGE transcript profiling of the juvenile cambial region of Eucalyptus grandis. Tree Physiol. 2008, 28: 905-919.View ArticleGoogle Scholar
- Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods. 2001, 25: 402-408. 10.1006/meth.2001.1262View ArticlePubMedGoogle Scholar
- Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J: qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol. 2007, 8: 19-10.1186/gb-2007-8-2-r19.View ArticleGoogle Scholar
- Chen X: Small RNAs and their roles in plant development. Annu Rev Cell Dev Biol. 2009, 25: 21-44. 10.1146/annurev.cellbio.042308.113417View ArticlePubMedGoogle Scholar
- Dheda K, Huggett JF, Chang JS, Kima LU, Bustin SA, Johnson MA, Rook GAW, Zumla A: The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization. Anal Biochem. 2005, 344: 141-143. 10.1016/j.ab.2005.05.022View ArticlePubMedGoogle Scholar
- Guénin S, Mauriat M, Pelloux J, Van Wuytswinkel O, Bellini C, Gutierrez L: Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references. J Exp Bot. 2009, 60 (2): 487-493. 10.1093/jxb/ern305View ArticlePubMedGoogle Scholar
- Pernot F, Dorandeu F, Beaup C, Peinnequin A: Selection of reference genes for real-time quantitative reverse transcription-polymerase chain reaction in hippocampal structure in a murine model of temporal lobe epilepsy with focal seizures. Journal of Neuroscience Research. 2010, 88: 1000-1008.PubMedGoogle Scholar
- Steiger MG, Mach RL, Mach-Aigner AS: An accurate normalization strategy for RT-qPCR in Hipocrea jecorina (Trichoderma reesei). Journal of Biotechnology. 2010, 145: 30-37. 10.1016/j.jbiotec.2009.10.012View ArticlePubMedGoogle Scholar
- Chatterjee C, Muir TW: Chemical approaches for studying histone modifications. J Biol Chem. 2010, 285: 11045-11050. 10.1074/jbc.R109.080291View ArticlePubMedPubMed CentralGoogle Scholar
- Hays DB, Skinner DZ: Development of an expressed sequence tag (EST) library for Medicago sativa. Plant Sci. 2001, 161: 517-526. 10.1016/S0168-9452(01)00440-X.View ArticleGoogle Scholar
- Sterky F, Bhalerao RR, Unneberg P, Segerman B, Nilsson P, Brunner AM, Charbonnel-Campaa L, Lindvall JJ, Tandre K, Strauss SH, Sundberg B, Gustafsson P, Uhlén M, Bhalerao RP, Nilsson O, Sandberg G, Karlsson J, Lundeberg J, Jansson S: A Populus EST resource for plant functional genomics. P Natl Acad Sci USA. 2004, 101: 13951-13956. 10.1073/pnas.0401641101.View ArticleGoogle Scholar
- Goossens K, Van Poucke M, Van Soom A, Vandesompele J, Van Zeveren A, Peelman LJ: Selection of reference genes for quantitative real-time PCR in bovine preimplantation embryos. BMC Dev Biol. 2005, 5: 27- 10.1186/1471-213X-5-27View ArticlePubMedPubMed CentralGoogle Scholar
- Sindelka R, Ferjentsik Z, Jonák J: Developmental expression profiles of Xenopus laevis reference genes. Dev Dynam. 2006, 235: 754-758. 10.1002/dvdy.20665.View ArticleGoogle Scholar
- Busov V, Yordanov YS, Meilan R: Discovery of genes involved in adventitious root formation using Populus as a model. Adventitious root formation of forest trees and horticultural plants - From genes to applications. Edited by: Niemi K, Scagel C. 2009, 85-103. Kerala: Research Signpost, Google Scholar
- Brinker M, Van Zyl L, Liu W, Craig D, Sederoff RR, Clapham DH, Von Arnold S: Microarray analyses of gene expression during adventitious root development in Pinus contorta. Plant Physiol. 2004, 135: 1526-1539. 10.1104/pp.103.032235View ArticlePubMedPubMed CentralGoogle Scholar
- Sorin C, Negroni L, Balliau T, Corti H, Jacquemot M, Davanture M, Sandberg G, Zivy M, Bellini C: Proteomic analysis of different mutant genotypes of Arabidopsis led to the identification of 11 proteins correlating with adventitious root development. Plant Physiol. 2006, 140: 349-364. 10.1104/pp.105.067868View ArticlePubMedPubMed CentralGoogle Scholar
- Schrader EK, Harstad KG, Matouschek A: Targeting proteins for degradation. Nat Chem Biol. 2009, 5: 815-822. 10.1038/nchembio.250View ArticlePubMedPubMed CentralGoogle Scholar
- Gonçalves S, Cairney J, Maroco J, Oliveira MM, Miguel C: Evaluation of control transcripts in real-time RT-PCR expression analysis during maritime pine embryogenesis. Planta. 2005, 222: 556-563. 10.1007/s00425-005-1562-0View ArticlePubMedGoogle Scholar
- Ludwig-Müller J: Molecular basis for the role of auxins in adventitious rooting. Adventitious root formation of forest trees and horticultural plants - From genes to applications. Edited by: Niemi K, Scagel C. 2009, 1-29. Kerala: Research SignpostGoogle Scholar
- Woodward AW, Bartel B: A receptor for auxin. Plant Cell. 2005, 17: 2425-2429. 10.1105/tpc.105.036236View ArticlePubMedPubMed CentralGoogle Scholar
- Murashigue T, Skoog F: A revised medium for rapid growth and bioassay with tobacco tissue cultures. Physiol Plant. 1962, 15: 473-498. 10.1111/j.1399-3054.1962.tb08052.x.View ArticleGoogle Scholar
- Ramakers C, Ruijtera JM, Deprez RHL, Moorman AFM: Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett. 2003, 339: 62-66. 10.1016/S0304-3940(02)01423-4View ArticlePubMedGoogle Scholar