BACKGROUND
the general aims of transcriptomic analysis are identification of genes differentially expressed and measurement of the relative levels of their transcripts.
transcriptomic analysis like that relying on microarray techniques reveals an underlying expression dynamic that changes between tissues and over time  <cit> .
results must then be validated by other means in order to obtain robust data that will support working hypotheses directed at a better understanding of development or environmental responsiveness.
since the advent of quantitative pcr, it has become the method of choice to validate gene expression data.
however, data obtained by qpcr can be strongly affected by the properties of the starting material, rna extraction procedures, and cdna synthesis.
therefore, relative quantification procedures require comparison of the gene of interest to an internal control, based on a normalization factor derived from one or more genes that can be argued to be equally active in the relevant cell types.
this requires the previous identification of such genes, which can then be reliably used to normalise relative expression of genes of interest.
identification of candidate genes useful for normalization has become a major task, as it has been shown that normalization errors are probably the most common mistake, resulting in significant artefacts that can lead to erroneous conclusions  <cit> .
several software tools have been developed to compute relative levels of specific transcripts  based on group-wise comparisons between a gene of interest and another endogenous gene  <cit> .
however identification of genes with stable patterns of gene expression requires pairwise testing of several genes with each other.
among the software programs developed toward this end are genorm  <cit> , bestkeeper  <cit> , normfinder  <cit>  or qbaseplus  <cit> .
the programs genorm and qbaseplus use pairwise comparisons and geometric averaging across a matrix of reference genes.
qbaseplus also calculates a coefficient of variation  for each gene as a stability measurement.
bestkeeper uses pairwise correlation analysis of each internal gene to an optimal normalization factor that merges data from all of them.
finally, normfinder fits data to a mathematical model, which allows comparison of intra- and intergroup variation and calculation of expression stability.
using the programs described above researchers have identified genes suitable for use as normalization controls in arabidopsis  <cit> , rice  <cit> , potato leaves  <cit> , the parasitic plant orobanche ramosa  <cit> , brachypodium distachyon  <cit>  and grape  <cit> .
in the solanaceae, candidate genes for normalization have been determined based on est abundance  <cit> , and qpcr followed by statistical analysis using the tools described above have been reported  <cit> .
a feature shared amongst these studies, and a large number of additional publications describing human, animal and plant systems, is the identification of genes specific for a certain tissue, developmental stage or environmental condition.
this is a logical experimental design, as individual research programs tend to be focused, and the number of appropriate genes can be expected to be inversely related to the number of cell types or conditions under investigation.
recent studies that included different cultivars of soybean  <cit> , underscore how the characteristics of the plant and the types of organs studied must drive the experimental approach to transcriptomic analysis.
the garden petunia  has been extensively used as a model for developmental biology  <cit> .
amongst the inbred petunia lines used in research, the white-flowered mitchell  <cit> , also known as w <dig>  is routinely exploited for transformation and scent studies  <cit> .
the genetics of flower pigmentation has been intensively studied in lines such as v <dig>  <cit> .
mitchell and v <dig> are genetically dissimilar, as demonstrated in mapping studies, and vary in a number of other ways, including growth habit and amenability to propagation in culture.
here we have used multiple developmental stages of flowers and leaves of these two petunia lines to identify genes that show reliable robustness as candidates for use in normalization of relative transcript abundance.
the experiments were carried out in two different laboratories, with different pcr machines and different purification and amplification conditions.
we found that the final shortlist of valuable genes was different between lines suggesting the necessity of performing reference gene stability measurements as part of the experimental design where differences in gene expression in petunia is tested.
RESULTS
petunia lines, developmental stages and selection of genes for normalization
two very different petunia lines were used for the analyses.
mitchell, also known as w <dig>  is a doubled haploid line obtained from anther culture of an interspecific petunia hybrid  <cit> ; it is characterized by vigorous growth, exceptional fertility, strong fragrance and white flowers.
v <dig> is an inbred line of modest growth habit and fertility featuring deep purple petals and pollen.
from each line we harvested flowers representing four developmental stages, from young flower buds to open flowers shortly before anthesis, and two leaf developmental stages, young and full-sized .
potentially useful rg were selected based on review of the relevant literature, from which we identified genes previously used for normalization or routinely used as controls for northern blots or rt-pcr.
from the original list we developed a short list of nine, including genes encoding actin- <dig> , cyclophilin- <dig>  <cit> , elongation factor 1α , ubiquitin  glyceraldehyde-3-phosphate dehydrogenase , gtp-binding protein ran <dig> , sand protein   <cit> , ribosomal protein s <dig>   <cit>  and b-tubulin  <dig>   <cit>  .
the products of these genes are associated with a wide variety of biological functions.
moreover, these genes are described as not co-regulated, a prerequisite for using one of the algorithms to identify stably expressed genes  reliably  <cit> .
selected candidate reference genes accessions are shown as identifiers of solanaceae genomics network  and arabidopsis tair databases .
homologous arabidopsis genes were determined on the basis of tblastx e-values
strategy for data mining and statistical analysis
the genes described above were selected to test for stability of transcript levels through leaf and flower development in two petunia lines, mitchell and v <dig>  as the aim of the present work is to find if we could obtain a similar rank of genes irrespective of the petunia line, growth conditions or sample processing, we developed all the data mining procedures separately for each line.
cycle threshold  values were determined and expression stability, i.e., the constancy of transcript levels, ranked.
as a strategy for calculating relative expression quantities  we applied the qbaseplus software, taking into account for each reaction its specific pcr efficiency.
rescaling of normalized quantities employed the sample with the lowest ct value .
with qbaseplus we measured expression stability  and coefficients of variation .
relative quantities were transferred to genorm for computing m stability values.
it is worth noting that the procedure for computing m values differs between genorm and qbaseplus.
finally, we used the combined stability measurements produced by genorm, normfinder, bestkeeper and qbaseplus to establish a consensus rank of genes by applying rankaggreg  <cit> .
the input to this statistical package was a matrix of rank-ordered genes according to the different stability measurements previously computed.
rankaggreg calculated spearman footrule distances and the software reformatted this distance matrix into an ordered list that matched each inital order as closely as possible this consensus rank list was obtained by means of the cross-entropy monte carlo algorithm present in the software.
ct values and variability between organs and developmental stages in mitchell and v30
real-time pcr reactions were performed on the six cdna samples obtained from each petunia line with the nine primer pairs representing the candidate rg.
in order to assess run reliability non-template controls were added and three technical repetitions were included for each biological replicate.
ct values were defined as the number of cycles required for normalized fluorescence to reach a manually set threshold of 20% total fluorescence.
product melting analysis and/or gel electrophoresis allowed for the discarding of non-specific products.
moreover, we considered only ct technical repetitions differing by less than one cycle.
the ct values obtained for all the genes under study differed between the two petunia lines .
the range of values was consistently narrower in mitchell than in v <dig>  this could indicate that gene expression in general is less variable in mitchell than in v <dig>  however these data correspond to averages derived from all the samples and further analysis showed that in fact v <dig> exhibited more constant levels of tested transcripts at the single organ level or developmental stage .
for mitchell samples ubq was the most highly expressed gene overall, with a ct of  <dig> , and sand the lowest, with a ct of  <dig> .
in contrast, the highest and lowest expressed genes in v <dig> were ef1α and act, with cts of  <dig>  and  <dig> , respectively.
analysis of variance of ct values between organs was performed separately for mitchell and v <dig> samples.
since ct values were not normally distributed, we calculated kruskall-wallis and a post-hoc pairwise rank sum wilcoxon test, both non-parametrical, using a bonferroni correction and a significance cut-off of  <dig> .
in mitchell the genes ran <dig>  rps <dig> and ubq showed significant differences in transcript levels between developmental stages .
ran <dig> transcript levels differed significantly between leaf a and flowers c and d, rps <dig> differed in flower d from the rest of floral stages analysed, and ubq transcript levels differed significantly between leaf a and flower d. for v <dig>  the overall ct variability was higher than that seen in mitchell; in fact, expression of all the genes analysed showed significant differences between one or more sets of organs and/or developmental stages.
expression of the genes gapdh and tub differed between leaves a and c, while levels of other measured transcripts were essentially the same in the two leaf stages.
in contrast, during flower development, we could distinguish genes that showed two levels of significantly different ct values , those that showed three  and others that differed at each developmental stage analysed .
stability of gene expression in mitchell and v30
data from each of the two chosen petunia lines were analyzed separately.
as a first approach, we applied data as a unique population and transferred it to normfinder, bestkeeper, genorm and qbaseplus according to the flowchart plotted in figure  <dig>  in a second approach, we subdivided data into several subpopulations, corresponding to unique developmental stages , then, piped this data into the qbaseplus and genorm tools.
the results of both sets of analyses are presented in tables  <dig> and  <dig> and additional files  <dig>   <dig> and  <dig>
m values computed by genorm and qbaseplus allow to rank optimal reference genes.
for each organ and mix of organs the two top-ranked genes are shown.
the number of genes required for a reliable quantification is established using a pairwise variation  cut-off of  <dig> ; n is the the minimum number of control genes required na means that no one pairwise variation was under the proposed cut-off.
gene expression data were analyzed using five statistical parameters in both petunia lines.
each column refers to a gene suitability ranking computed by one statistical tool, taking into account all data of a petunia line.
ct values were log-transformed and used as input for the normfinder tool, which fitted this data into a mathematical model based on six independent groups corresponding to single developmental stages.
estimates for stability of gene expression are based on the comparison between inter- and intra-group variability.
in the mitchell line, the gene exhibiting the most stable level of expression was ef1α  and cyp and ef1α represented the best combination .
in v <dig>  normfinder estimated ubq  as the most stably expressed gene, and ran <dig> and ubq  as the best combination of two genes.
ct values and one efficiency value for each primer pair served as input for the bestkeeper package.
this program was intended to establish the best-suited standards out of the nine rg candidates, and to merge them in a normalization factor called the bestkeeper index.
because bestkeeper software is designed to determine a reliable normalization factor but not to compute the goodness of each rg independently, we took as the stability-of-expression value the coefficient of determination of each gene to the bestkeeper index.
bestkeeper calculated the highest reliability for cyp in line mitchell and v <dig> finding gapdh as the least suitable gene in mitchell and tub in v <dig>
qbaseplus and genorm calculate m stability values by a slightly different procedure.
this parameter is defined as the average pair-wise variation in the level of transcripts from one gene with that of all other reference genes in a given group of samples; it is inversely related to expression stability.
however, because the inclusion of a gene with highly variable expression can alter the estimation of the rest, genorm  performs a stepwise exclusion of the least stably expressed genes.
taking into account the entire dataset from mitchell with genorm, ran <dig> and sand were calculated to be the most stably expressed genes , gapdh the least .
in v <dig>  rps <dig> and ubq were calculated to be the genes of least variable expression , whereas gapdh was the most variable .
in terms of qbaseplus m values, ef1α was valued as the best gene for mitchell  and gapdh the worst ; for v <dig>  act was ranked as the most valuable gene  and gapdh was the worst .
considering each developmental stage separately, we found that m values were consistently higher in mitchell than in v <dig>  suggesting more variable levels of rg expression in mitchell.
flower stage d exhibited the most stable expression pattern in both lines .
it is noteworthy that stability of transcript levels between reproductive and vegetative modules differed in the two lines.
in general, m values calculated with qbaseplus, were higher in flowers stage c and d than in leaves from mitchell, whereas v <dig> showed an opposite trend.
a remarkable case was gapdh, with an m value four times higher in mitchell than in v <dig> at leaf stage c, whereas it was three times lower in mitchell compared to v <dig> at flower stage a .
mean cv value, a measurement of the variation of relative quantities of rna for a normalized reference gene, showed little difference between lines, with a value of  <dig>  in mitchell and  <dig>  in v <dig>  for data analysed as a whole.
determination of the number of genes for normalization
quantification of gene expression relative to multiple reference genes implies the calculation of a normalization factor  that merges data from several internal genes.
determination of the minimal number of its components is estimated by computing the pairwise variation  of two sequential nfs  as the standard deviation of the logarithmically transformed nfn/nfn+ <dig> ratios, reflecting the effect of including an additional gene  <cit> .
if the pairwise variation value for n genes is below a cut-off of  <dig> , additional genes are considered not to improve normalization.
the number of genes required for normalization was determined to be two for both mitchell and v <dig>  except when either different floral developmental stages or vegetative and reproductive stages were mixed .
the pv values showed the same trend as that seen for stability measurements, i.e., the developmental stage with the lowest average pv was flower stage d, both in mitchell and v <dig>  in contrast, gene expression in leaves of mitchell showed more variability, with higher pv values, than those of v <dig> .
consensus list of similarities between lines
the different software programs used to determine gene suitability for normalization of gene expression give slightly different results and statistical stability values for each gene.
we arranged the internal genes in five lists according to the rank positions generated by each of the five statistical approaches, m values by genorm and qbaseplus, normfinder stability value, coefficient of determination to bestkeeper and cv of qbaseplus.
these lists were used to create an aggregate order, with the aim of obtaining an optimal list of genes for each petunia line.
the results of the merged data revealed that the most adequate of the genes tested for normalization in mitchell are ef1α, sand and rps13; the three showing the lowest reliability are tub, act and gapdh .
for v <dig>  the best candidate genes are cyp, ran <dig> and act, while the three lowest ranking are ef1α, sand and gapdh.
thus none of the genes found as highly reliable coincide between the lines.
despite of that, gapdh was highly unstable in both lines.
discussion
identification of robust normalization genes for petunia
we have attempted to identify a set of genes suitable for normalization of transcript levels in p. hybrida.
since several petunia lines are used for research, we based this work on two that are extensively used for different purposes.
in an effort to reflect different growth environments typical of distinct lab setups, plants of each line were grown in a set of conditions, differing in photoperiod, thermoperiod and growth substrate between lines .
rna was isolated using different rna extraction kits, and amplifications were carried out using different reagents and pcr machines.
the experimental design aimed to maximize potential variability in transcript abundance for the putative rg under study.
highly contrasting results would suggest that every laboratory do a pilot experiment to identify genes suitable for use in normalization; similar results between the two systems would point to a set of genes reliable for broad application, minimally for the lines and developmental stages described.
our findings in terms of line-associated variability were not in accordance with the results from a soybean study comparing different cultivars.
results of that study suggested no highly relevant cultivar influence on rg suitability  <cit> .
a similar study has been reported in coffee, for which average m stability values for leaves from different cultivars were lower than that for different organs of a single cultivar.
our result suggests that there are differences in gene expression between same tissues from different lines as well as different tissues from the same line.
noise in gene expression patterns
development of petals, like that of many tissues and organs in petunia, is characterized by a spatial and temporal gradient of cell division that is eventually replaced by cell expansion  <cit> .
however the experiments described here used whole flower tissues including full petals along with sepals, stamens and carpels.
this imposes a general requirement that any gene emerging as robust be differentially regulated to a huge extent neither in the various tissues analyzed together nor in these tissues at different stages of maturation.
one interesting aspect of our findings was the identification of flower stage c as a particularly noisy developmental stage compared to early or fully developed flowers.
the transition between cell division and expansion in petals, or other flower tissues during this developmental stage, might explain the increased noise.
an alternative non-exclusive explanation is that the intermediate stages of flower development are generally less tightly defined than the open flower stage.
leaf development similarly consists of cell growth followed with cell expansion  <cit> .
however, an important difference between floral and leaf development is that leaves perform their essential function, e.g., photosynthesis, from a very early stage such that developing leaf tissue is always a mixture of at least three processes: growth, cell morphogenesis and differentiated cell function.
this combination of processes might account for the increased gene expression noise observed.
number of genes required for normalization of gene expression in petunia
gathering data from several rg into a normalization factor is currently an accepted method of accurate relative quantification of gene expression  <cit> .
moreover, this method has been statistically and empirically validated  <cit> .
ideally the number of genes required should be low enough to make experimental procedures affordable, and high enough to merit confidence in the conclusions.
the pv value obtained for both mitchell and v <dig> was very low.
although the value tended to be higher in mitchell, the number of genes deemed necessary for normalization was the same for both lines: using the proposed cut-off of  <dig>  and comparing single developmental stages, the required number was two for mitchell and v <dig>  the requirement for only two genes is low compared to the results reported for other phylogenetically related species  <cit>  and will require significantly less work than the previously suggested minimum of three genes  <cit> .
data mining strategies and consensus list of genes for normalization
the present research aims to identify the control genes best suited for use in gene expression studies in several organs of two petunia lines.
the candidate rg combined classical and recently identified genes.
since each software package can introduce bias, we employed several tools in our analysis.
as discussed by other authors, genorm bases its stability measurement on pairwise comparisons of relative expression quantities of all the panel of genes in the material of interest requiring a suite of non-coregulated rg  <cit> .
bestkeeper and normfinder examine primarily ct values, whereas qbaseplus and genorm evaluate rq, a consequence of which is that pcr efficiency dissimilarities can affect stability measurements  <cit> .
nevertheless, some of these algorithms are intrinsically biased because they assume that data are normally distributed.
for instance bestkeeper is based on pearson correlation analysis, which requires normally distributed and variance homogeneous data.
the author described this problem and suggested further versions of the software in which spearman and kendall tau correlation should be used  <cit> .
however, those versions are currently not available.
our plant material diverged in the variability of statistical outputs amongst lines.
v <dig> showed a high variability in terms of raw expression data  and low in terms of expression stability measurements, whereas mitchell showed the opposite responses.
our global analysis merged different statistics, some of which are ct-based and others rq-based, with the aim of counteracting this biasing influence.
summarizing the results of our entire dataset analysis, genorm recommended use of ran <dig> and sand genes for mitchell and rps <dig> and ubq for v <dig> and discouraged use of gapdh for both lines.
non-suitability of gapdh has been described by several authors  <cit> .
regarding to solanaceae, its unsuitability has been confirmed in tomato  <cit>  but it was selected as a stable rg in coffee  <cit> .
due to its sequential exclusion of the least stable gene in the m value calculus algorithm, genorm m values can differ from those of qbaseplus.
qbaseplus corresponded with genorm, evaluating ef1α as the most reliable gene in line mitchell but differed in line v <dig>  recommending act as the best candidate.
ef1α suitability has been confirmed in potato during biotic and abiotic stress  <cit> , atlantic salmon  <cit>  and several developmental stages of xenopus laevis  <cit> .
expression of act genes differs depending on the family member.
act2/ <dig> has been reported as a stably expressed gene whereas act <dig> was reported as unstable  <cit> .
it is worth noting that the act gene used in this study corresponds to an act <dig>
CONCLUSIONS
altogether, there were strong similarities between the different programs but the coincidence in assigning best and worst genes was not absolute.
the fact that each program identified slightly different genes as best suited for normalization prompted us to merge the data in an unsupervised way and giving identical weight to the output of the different programs.
we used the rankaggreg program for this purpose.
our results show that gapdh was the worst gene to use in normalization in both lines.
in contrast, the suggested genes did not coincide and were ef1α and sand in mitchell, whilst cyp and ran <dig> were the genes of choice in v <dig>  in conclusion, we provide a list of genes in discrete developmental stages that show m values below  <dig>    <cit> .
a normalization factor including two genes should be enough for reliable quantification.
nevertheless we propose a reference gene stability test when performing gene expression studies in petunia.

 the general aims of transcriptomic analysis are identification of genes differentially expressed and measurement of the relative levels of their transcripts. transcriptomic analysis like that relying on microarray techniques reveals an underlying expression dynamic that changes between tissues and over time. results must then be validated by other means in order to obtain robust data that will support working hypotheses directed at a better understanding of development or environmental responsiveness. since the advent of quantitative pcr, it has become the method of choice to validate gene expression data. however, data obtained by qpcr can be strongly affected by the properties of the starting material, rna extraction procedures, and cdna synthesis. therefore, relative quantification procedures require comparison of the gene of interest to an internal control, based on a normalization factor derived from one or more genes that can be argued to be equally active in the relevant cell types. this requires the previous identification of such genes, which can then be reliably used to normalise relative expression of genes of interest. identification of candidate genes useful for normalization has become a major task, as it has been shown that normalization errors are probably the most common mistake, resulting in significant artefacts that can lead to erroneous conclusions. several software tools have been developed to compute relative levels of specific transcripts based on group-wise comparisons between a gene of interest and another endogenous gene. however identification of genes with stable patterns of gene expression requires pairwise testing of several genes with each other. among the software programs developed toward this end are genorm, bestkeeper, normfinder or qbaseplus. the programs genorm and qbaseplus use pairwise comparisons and geometric averaging across a matrix of reference genes. qbaseplus also calculates a coefficient of variation for each gene as a stability measurement. bestkeeper uses pairwise correlation analysis of each internal gene to an optimal normalization factor that merges data from all of them. finally, normfinder fits data to a mathematical model, which allows comparison of intra- and intergroup variation and calculation of expression stability. using the programs described above researchers have identified genes suitable for use as normalization controls in arabidopsis, rice, potato leaves, the parasitic plant orobanche ramosa, brachypodium distachyon and grape. in the solanaceae, candidate genes for normalization have been determined based on est abundance, and qpcr followed by statistical analysis using the tools described above have been reported. a feature shared amongst these studies, and a large number of additional publications describing human, animal and plant systems, is the identification of genes specific for a certain tissue, developmental stage or environmental condition. this is a logical experimental design, as individual research programs tend to be focused, and the number of appropriate genes can be expected to be inversely related to the number of cell types or conditions under investigation. recent studies that included different cultivars of soybean, underscore how the characteristics of the plant and the types of organs studied must drive the experimental approach to transcriptomic analysis. the garden petunia has been extensively used as a model for developmental biology. amongst the inbred petunia lines used in research, the white-flowered mitchell, also known as w is routinely exploited for transformation and scent studies. the genetics of flower pigmentation has been intensively studied in lines such as v. mitchell and v are genetically dissimilar, as demonstrated in mapping studies, and vary in a number of other ways, including growth habit and amenability to propagation in culture. here we have used multiple developmental stages of flowers and leaves of these two petunia lines to identify genes that show reliable robustness as candidates for use in normalization of relative transcript abundance. the experiments were carried out in two different laboratories, with different pcr machines and different purification and amplification conditions. we found that the final shortlist of valuable genes was different between lines suggesting the necessity of performing reference gene stability measurements as part of the experimental design where differences in gene expression in petunia is tested.  petunia lines, developmental stages and selection of genes for normalization two very different petunia lines were used for the analyses. mitchell, also known as w is a doubled haploid line obtained from anther culture of an interspecific petunia hybrid; it is characterized by vigorous growth, exceptional fertility, strong fragrance and white flowers. v is an inbred line of modest growth habit and fertility featuring deep purple petals and pollen. from each line we harvested flowers representing four developmental stages, from young flower buds to open flowers shortly before anthesis, and two leaf developmental stages, young and full-sized. potentially useful rg were selected based on review of the relevant literature, from which we identified genes previously used for normalization or routinely used as controls for northern blots or rt-pcr. from the original list we developed a short list of nine, including genes encoding actin-, cyclophilin-, elongation factor 1α, ubiquitin glyceraldehyde-3-phosphate dehydrogenase, gtp-binding protein ran, sand protein, ribosomal protein s and b-tubulin. the products of these genes are associated with a wide variety of biological functions. moreover, these genes are described as not co-regulated, a prerequisite for using one of the algorithms to identify stably expressed genes reliably. selected candidate reference genes accessions are shown as identifiers of solanaceae genomics network and arabidopsis tair databases. homologous arabidopsis genes were determined on the basis of tblastx e-values strategy for data mining and statistical analysis the genes described above were selected to test for stability of transcript levels through leaf and flower development in two petunia lines, mitchell and v as the aim of the present work is to find if we could obtain a similar rank of genes irrespective of the petunia line, growth conditions or sample processing, we developed all the data mining procedures separately for each line. cycle threshold values were determined and expression stability, i.e., the constancy of transcript levels, ranked. as a strategy for calculating relative expression quantities we applied the qbaseplus software, taking into account for each reaction its specific pcr efficiency. rescaling of normalized quantities employed the sample with the lowest ct value. with qbaseplus we measured expression stability and coefficients of variation. relative quantities were transferred to genorm for computing m stability values. it is worth noting that the procedure for computing m values differs between genorm and qbaseplus. finally, we used the combined stability measurements produced by genorm, normfinder, bestkeeper and qbaseplus to establish a consensus rank of genes by applying rankaggreg. the input to this statistical package was a matrix of rank-ordered genes according to the different stability measurements previously computed. rankaggreg calculated spearman footrule distances and the software reformatted this distance matrix into an ordered list that matched each inital order as closely as possible this consensus rank list was obtained by means of the cross-entropy monte carlo algorithm present in the software. ct values and variability between organs and developmental stages in mitchell and v30 real-time pcr reactions were performed on the six cdna samples obtained from each petunia line with the nine primer pairs representing the candidate rg. in order to assess run reliability non-template controls were added and three technical repetitions were included for each biological replicate. ct values were defined as the number of cycles required for normalized fluorescence to reach a manually set threshold of 20% total fluorescence. product melting analysis and/or gel electrophoresis allowed for the discarding of non-specific products. moreover, we considered only ct technical repetitions differing by less than one cycle. the ct values obtained for all the genes under study differed between the two petunia lines. the range of values was consistently narrower in mitchell than in v this could indicate that gene expression in general is less variable in mitchell than in v however these data correspond to averages derived from all the samples and further analysis showed that in fact v exhibited more constant levels of tested transcripts at the single organ level or developmental stage. for mitchell samples ubq was the most highly expressed gene overall, with a ct of, and sand the lowest, with a ct of. in contrast, the highest and lowest expressed genes in v were ef1α and act, with cts of and, respectively. analysis of variance of ct values between organs was performed separately for mitchell and v samples. since ct values were not normally distributed, we calculated kruskall-wallis and a post-hoc pairwise rank sum wilcoxon test, both non-parametrical, using a bonferroni correction and a significance cut-off of. in mitchell the genes ran rps and ubq showed significant differences in transcript levels between developmental stages. ran transcript levels differed significantly between leaf a and flowers c and d, rps differed in flower d from the rest of floral stages analysed, and ubq transcript levels differed significantly between leaf a and flower d. for v the overall ct variability was higher than that seen in mitchell; in fact, expression of all the genes analysed showed significant differences between one or more sets of organs and/or developmental stages. expression of the genes gapdh and tub differed between leaves a and c, while levels of other measured transcripts were essentially the same in the two leaf stages. in contrast, during flower development, we could distinguish genes that showed two levels of significantly different ct values, those that showed three and others that differed at each developmental stage analysed. stability of gene expression in mitchell and v30 data from each of the two chosen petunia lines were analyzed separately. as a first approach, we applied data as a unique population and transferred it to normfinder, bestkeeper, genorm and qbaseplus according to the flowchart plotted in figure in a second approach, we subdivided data into several subpopulations, corresponding to unique developmental stages, then, piped this data into the qbaseplus and genorm tools. the results of both sets of analyses are presented in tables and and additional files and m values computed by genorm and qbaseplus allow to rank optimal reference genes. for each organ and mix of organs the two top-ranked genes are shown. the number of genes required for a reliable quantification is established using a pairwise variation cut-off of; n is the the minimum number of control genes required na means that no one pairwise variation was under the proposed cut-off. gene expression data were analyzed using five statistical parameters in both petunia lines. each column refers to a gene suitability ranking computed by one statistical tool, taking into account all data of a petunia line. ct values were log-transformed and used as input for the normfinder tool, which fitted this data into a mathematical model based on six independent groups corresponding to single developmental stages. estimates for stability of gene expression are based on the comparison between inter- and intra-group variability. in the mitchell line, the gene exhibiting the most stable level of expression was ef1α and cyp and ef1α represented the best combination. in v normfinder estimated ubq as the most stably expressed gene, and ran and ubq as the best combination of two genes. ct values and one efficiency value for each primer pair served as input for the bestkeeper package. this program was intended to establish the best-suited standards out of the nine rg candidates, and to merge them in a normalization factor called the bestkeeper index. because bestkeeper software is designed to determine a reliable normalization factor but not to compute the goodness of each rg independently, we took as the stability-of-expression value the coefficient of determination of each gene to the bestkeeper index. bestkeeper calculated the highest reliability for cyp in line mitchell and v finding gapdh as the least suitable gene in mitchell and tub in v qbaseplus and genorm calculate m stability values by a slightly different procedure. this parameter is defined as the average pair-wise variation in the level of transcripts from one gene with that of all other reference genes in a given group of samples; it is inversely related to expression stability. however, because the inclusion of a gene with highly variable expression can alter the estimation of the rest, genorm performs a stepwise exclusion of the least stably expressed genes. taking into account the entire dataset from mitchell with genorm, ran and sand were calculated to be the most stably expressed genes, gapdh the least. in v rps and ubq were calculated to be the genes of least variable expression, whereas gapdh was the most variable. in terms of qbaseplus m values, ef1α was valued as the best gene for mitchell and gapdh the worst; for v act was ranked as the most valuable gene and gapdh was the worst. considering each developmental stage separately, we found that m values were consistently higher in mitchell than in v suggesting more variable levels of rg expression in mitchell. flower stage d exhibited the most stable expression pattern in both lines. it is noteworthy that stability of transcript levels between reproductive and vegetative modules differed in the two lines. in general, m values calculated with qbaseplus, were higher in flowers stage c and d than in leaves from mitchell, whereas v showed an opposite trend. a remarkable case was gapdh, with an m value four times higher in mitchell than in v at leaf stage c, whereas it was three times lower in mitchell compared to v at flower stage a. mean cv value, a measurement of the variation of relative quantities of rna for a normalized reference gene, showed little difference between lines, with a value of in mitchell and in v for data analysed as a whole. determination of the number of genes for normalization quantification of gene expression relative to multiple reference genes implies the calculation of a normalization factor that merges data from several internal genes. determination of the minimal number of its components is estimated by computing the pairwise variation of two sequential nfs as the standard deviation of the logarithmically transformed nfn/nfn+ ratios, reflecting the effect of including an additional gene. if the pairwise variation value for n genes is below a cut-off of, additional genes are considered not to improve normalization. the number of genes required for normalization was determined to be two for both mitchell and v except when either different floral developmental stages or vegetative and reproductive stages were mixed. the pv values showed the same trend as that seen for stability measurements, i.e., the developmental stage with the lowest average pv was flower stage d, both in mitchell and v in contrast, gene expression in leaves of mitchell showed more variability, with higher pv values, than those of v. consensus list of similarities between lines the different software programs used to determine gene suitability for normalization of gene expression give slightly different results and statistical stability values for each gene. we arranged the internal genes in five lists according to the rank positions generated by each of the five statistical approaches, m values by genorm and qbaseplus, normfinder stability value, coefficient of determination to bestkeeper and cv of qbaseplus. these lists were used to create an aggregate order, with the aim of obtaining an optimal list of genes for each petunia line. the results of the merged data revealed that the most adequate of the genes tested for normalization in mitchell are ef1α, sand and rps13; the three showing the lowest reliability are tub, act and gapdh. for v the best candidate genes are cyp, ran and act, while the three lowest ranking are ef1α, sand and gapdh. thus none of the genes found as highly reliable coincide between the lines. despite of that, gapdh was highly unstable in both lines. discussion identification of robust normalization genes for petunia we have attempted to identify a set of genes suitable for normalization of transcript levels in p. hybrida. since several petunia lines are used for research, we based this work on two that are extensively used for different purposes. in an effort to reflect different growth environments typical of distinct lab setups, plants of each line were grown in a set of conditions, differing in photoperiod, thermoperiod and growth substrate between lines. rna was isolated using different rna extraction kits, and amplifications were carried out using different reagents and pcr machines. the experimental design aimed to maximize potential variability in transcript abundance for the putative rg under study. highly contrasting results would suggest that every laboratory do a pilot experiment to identify genes suitable for use in normalization; similar results between the two systems would point to a set of genes reliable for broad application, minimally for the lines and developmental stages described. our findings in terms of line-associated variability were not in accordance with the results from a soybean study comparing different cultivars. results of that study suggested no highly relevant cultivar influence on rg suitability. a similar study has been reported in coffee, for which average m stability values for leaves from different cultivars were lower than that for different organs of a single cultivar. our result suggests that there are differences in gene expression between same tissues from different lines as well as different tissues from the same line. noise in gene expression patterns development of petals, like that of many tissues and organs in petunia, is characterized by a spatial and temporal gradient of cell division that is eventually replaced by cell expansion. however the experiments described here used whole flower tissues including full petals along with sepals, stamens and carpels. this imposes a general requirement that any gene emerging as robust be differentially regulated to a huge extent neither in the various tissues analyzed together nor in these tissues at different stages of maturation. one interesting aspect of our findings was the identification of flower stage c as a particularly noisy developmental stage compared to early or fully developed flowers. the transition between cell division and expansion in petals, or other flower tissues during this developmental stage, might explain the increased noise. an alternative non-exclusive explanation is that the intermediate stages of flower development are generally less tightly defined than the open flower stage. leaf development similarly consists of cell growth followed with cell expansion. however, an important difference between floral and leaf development is that leaves perform their essential function, e.g., photosynthesis, from a very early stage such that developing leaf tissue is always a mixture of at least three processes: growth, cell morphogenesis and differentiated cell function. this combination of processes might account for the increased gene expression noise observed. number of genes required for normalization of gene expression in petunia gathering data from several rg into a normalization factor is currently an accepted method of accurate relative quantification of gene expression. moreover, this method has been statistically and empirically validated. ideally the number of genes required should be low enough to make experimental procedures affordable, and high enough to merit confidence in the conclusions. the pv value obtained for both mitchell and v was very low. although the value tended to be higher in mitchell, the number of genes deemed necessary for normalization was the same for both lines: using the proposed cut-off of and comparing single developmental stages, the required number was two for mitchell and v the requirement for only two genes is low compared to the results reported for other phylogenetically related species and will require significantly less work than the previously suggested minimum of three genes. data mining strategies and consensus list of genes for normalization the present research aims to identify the control genes best suited for use in gene expression studies in several organs of two petunia lines. the candidate rg combined classical and recently identified genes. since each software package can introduce bias, we employed several tools in our analysis. as discussed by other authors, genorm bases its stability measurement on pairwise comparisons of relative expression quantities of all the panel of genes in the material of interest requiring a suite of non-coregulated rg. bestkeeper and normfinder examine primarily ct values, whereas qbaseplus and genorm evaluate rq, a consequence of which is that pcr efficiency dissimilarities can affect stability measurements. nevertheless, some of these algorithms are intrinsically biased because they assume that data are normally distributed. for instance bestkeeper is based on pearson correlation analysis, which requires normally distributed and variance homogeneous data. the author described this problem and suggested further versions of the software in which spearman and kendall tau correlation should be used. however, those versions are currently not available. our plant material diverged in the variability of statistical outputs amongst lines. v showed a high variability in terms of raw expression data and low in terms of expression stability measurements, whereas mitchell showed the opposite responses. our global analysis merged different statistics, some of which are ct-based and others rq-based, with the aim of counteracting this biasing influence. summarizing the results of our entire dataset analysis, genorm recommended use of ran and sand genes for mitchell and rps and ubq for v and discouraged use of gapdh for both lines. non-suitability of gapdh has been described by several authors. regarding to solanaceae, its unsuitability has been confirmed in tomato but it was selected as a stable rg in coffee. due to its sequential exclusion of the least stable gene in the m value calculus algorithm, genorm m values can differ from those of qbaseplus. qbaseplus corresponded with genorm, evaluating ef1α as the most reliable gene in line mitchell but differed in line v recommending act as the best candidate. ef1α suitability has been confirmed in potato during biotic and abiotic stress, atlantic salmon and several developmental stages of xenopus laevis. expression of act genes differs depending on the family member. act2/ has been reported as a stably expressed gene whereas act was reported as unstable. it is worth noting that the act gene used in this study corresponds to an act  altogether, there were strong similarities between the different programs but the coincidence in assigning best and worst genes was not absolute. the fact that each program identified slightly different genes as best suited for normalization prompted us to merge the data in an unsupervised way and giving identical weight to the output of the different programs. we used the rankaggreg program for this purpose. our results show that gapdh was the worst gene to use in normalization in both lines. in contrast, the suggested genes did not coincide and were ef1α and sand in mitchell, whilst cyp and ran were the genes of choice in v in conclusion, we provide a list of genes in discrete developmental stages that show m values below. a normalization factor including two genes should be enough for reliable quantification. nevertheless we propose a reference gene stability test when performing gene expression studies in petunia. 
in an effort to identify endogenous genes meeting these criteria nine reference genes were tested in two petunia lines. ideally expression of these genes should be independent of the morphogenetic process or environmental condition tested as well as the methods used for rna purification and analysis. the least adequate gene turned out to be gapdh indicating that it should be rejected as reference gene in petunia. the absence of correspondence of the best-suited genes suggests that assessing reference gene stability is needed when performing normalization of data from transcriptomic analysis of flower and leaf development. the genes identified as optimal for transcriptomic analysis of mitchell and v were ef1α in mitchell and cyp in v whereas the least suitable gene was gapdh in both lines. growth conditions differed in mitchell and v and different methods were used for rna isolation and analysis. identification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development.
 identification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development. ideally expression of these genes should be independent of the morphogenetic process or environmental condition tested as well as the methods used for rna purification and analysis.  in an effort to identify endogenous genes meeting these criteria nine reference genes were tested in two petunia lines. growth conditions differed in mitchell and v and different methods were used for rna isolation and analysis. four different software tools were employed to analyze the data. we merged the four outputs by means of a non-weighted unsupervised rank aggregation method. the genes identified as optimal for transcriptomic analysis of mitchell and v were ef1α in mitchell and cyp in v whereas the least suitable gene was gapdh in both lines.  the least adequate gene turned out to be gapdh indicating that it should be rejected as reference gene in petunia. the absence of correspondence of the best-suited genes suggests that assessing reference gene stability is needed when performing normalization of data from transcriptomic analysis of flower and leaf development. 