Normalisation genes for expression analyses in the brown alga model Ectocarpus siliculosus
© Le Bail et al; licensee BioMed Central Ltd. 2008
Received: 24 February 2008
Accepted: 18 August 2008
Published: 18 August 2008
Brown algae are plant multi-cellular organisms occupying most of the world coasts and are essential actors in the constitution of ecological niches at the shoreline. Ectocarpus siliculosus is an emerging model for brown algal research. Its genome has been sequenced, and several tools are being developed to perform analyses at different levels of cell organization, including transcriptomic expression analyses. Several topics, including physiological responses to osmotic stress and to exposure to contaminants and solvents are being studied in order to better understand the adaptive capacity of brown algae to pollution and environmental changes. A series of genes that can be used to normalise expression analyses is required for these studies.
We monitored the expression of 13 genes under 21 different culture conditions. These included genes encoding proteins and factors involved in protein translation (ribosomal protein 26S, EF1alpha, IF2A, IF4E) and protein degradation (ubiquitin, ubiquitin conjugating enzyme) or folding (cyclophilin), and proteins involved in both the structure of the cytoskeleton (tubulin alpha, actin, actin-related proteins) and its trafficking function (dynein), as well as a protein implicated in carbon metabolism (glucose 6-phosphate dehydrogenase). The stability of their expression level was assessed using the Ct range, and by applying both the geNorm and the Normfinder principles of calculation.
Comparisons of the data obtained with the three methods of calculation indicated that EF1alpha (EF1a) was the best reference gene for normalisation. The normalisation factor should be calculated with at least two genes, alpha tubulin, ubiquitin-conjugating enzyme or actin-related proteins being good partners of EF1a. Our results exclude actin as a good normalisation gene, and, in this, are in agreement with previous studies in other organisms.
Brown algae (Phaeophyceae) are multi-cellular marine organisms that grow along temperate, tropical and polar coasts. Many of them are subject to frequent changes in their local environment, because they are uncovered at low tide, and are hence exposed to desiccation, and to variations in osmotic pressure due to rain or evaporation. In addition, pollution of the coasts, due to human activities, constitutes an additional source of abiotic stress, to which they must develop adaptive mechanisms. Expression analyses of genes involved in the perception of the stress, and in the establishment of the appropriate responses, provide a means to decipher the molecular mechanisms potentially involved in such adaptations. Despite the availability of medium scale cDNAs libraries for several different species of the brown algae (Laminaria, Sargassum, and Fucus), this task has been hindered by the lack of genome-scale resources. In 2004, Peters et al.  have compared a range of features in several species of Phaeophyceae and concluded that Ectocarpus siliculosus was the best candidate to consider for such developments. Recently, the genome of this alga has been sequenced, offering a unique opportunity to survey the expression of gene families in brown algae (Genoscope, J.M. Cock, unpublished data). E. siliculosus is a small filamentous alga, extensively studied over the last two centuries for its complex life cycle and its physiological features (reviewed in ). The genome is currently being annotated, allowing the initiation of both large scale and targeted surveys of the Ectocarpus genes, such as microarrays or real-time RT-PCR respectively.
Compared to high-throughput microarray techniques, real-time quantitative RT-PCR only allows assays of gene expression to be carried out at relatively low throughput (10–20 genes in 10–50 samples). Nonetheless, this technique has been adopted by a large community as a standard method for gene expression studies, because of its high reliability, and its rapidity of execution [3, 4]. This technique is now widely used for a large number of animal and plant organisms, as well as for bacteria and viruses.
A few years after the emergence of this technique, a need for a reliable normalisation method became insistent. Different methods of identifying normalisation genes, such as geNorm , NormFinder  and BestKeeper , were then developed. This was followed by a wave of reports on the identification of the best normalisation genes from a broad range of species and specific tissues. These biological materials included human tissues [8–10] and viruses , as well as tissues from a variety of animals such as cow , pig , horse , dolphin , fishes [16, 17], worm  and others. In parallel, a similar extension of the use of this technique was observed in plant research, for rice , poplar , potato , grapevine , and for plant pathogens .
In the brown alga E. siliculosus, the expression level of 20 genes specific to the two generations in the life-cycle of this alga was recently reported in a mutant impaired in development . Additional developmental and physiological studies are underway, including studies aimed at assessing the resistance of this alga to environmental changes. Hence, the availability of a set of housekeeping genes for normalising the expression levels of genes of interest is a pre-requisite to any valuable conclusion, especially since this organism lives in a frequently changing environment.
In this paper, we propose optimal normalisation genes for expression analyses in E. siliculosus. Thirteen housekeeping genes that have been reported to be good potential candidates in the previously cited literature, were chosen for this task. Their expression was examined by Q-RT-PCR in a diversity of algal samples corresponding to growth kinetic series, osmotic stress experiments, and chemical treatments. Namely, the candidate genes are involved in the synthesis and the dynamics of the cytoskeleton, in the synthesis, folding and degradation of proteins, and in the metabolism of carbon, all of these processes being known to be only moderately affected by the fluctuation of growth conditions.
Treatments applied to E. siliculosus and choice of housekeeping genes
Several different stresses were tested in this study. Chemical agents tested included H2O2, a reactive oxygen species produced by many organisms, including seaweeds, under conditions of abiotic and biotic stresses . We also tested heavy metals such as copper, which are among the most significant pollution actors in marine environments worldwide. Diuron and atrazine are herbicides that inhibit photosynthesis by blocking the d1 protein of photosystem II [26, 27]. Diuron is also an additive of antifouling paints, which prevent growth of organisms on ships' hulls. In addition pathogen or grazer attacks were mimicked by wounding E. siliculosus tissues with a razor blade. We also tested the effect of oxylipins. These are oxygenated derivatives of polyunsaturated fatty acids which play a major role in inflammatory processes, allergies, and, in a wide sense, defensive stress responses to infection, drugs, and xenobiotics . In land plants, C18 derived jasmonates play a pivotal role in defense induced mechanisms . In mammals, oxidation of the C20 arachidonic acid produces derivatives such as leukotriens and prostaglandins. As brown algae are able to produce oxylipins typical of both land plants and animals , their putative action on the induction of stress signalling pathways is of particular interest. Finally, as the metabolism and the physiology of brown algae are regulated to a large extent by diurnal rhythms, a time series of samples taken over a single day was also analysed.
Culture conditions and duration.
Type of treatment
450 mM NaCl
55 μg. L-1
450 mM NaCl
450 mM NaCl
Candidate housekeeping genes tested in this study.
Description of trace archive
Oligonucleotides – Forward – Reverse
PCR product length (bp)
p34-arc subunit of the actin-related protein complex ARP2/3
ARP2 subunit of the actin-related protein complex ARP2/3
Dynein light chain protein
Translation elongation factor 1 alpha
Glucose 6 phosphate dehydrogenase
Translation initiation factor eIF2 alpha
Translation intiation factor eIF4E
Ribosomal protein 26S
Ubiquitin conjugating enzyme
Quantification and data analysis
Normfinder analysis of the expression stability of the 13 genes.
In this study, the three methods used to identify the best normalisation genes were concordant, as previously reported in other studies . Comparison of the three methods indicates that EF1a is the most reliable gene to normalise gene expression in experiments aiming at quantitatively measuring the transcriptional response to abiotic stresses and chemical treatments. The V pairwise analysis shows that two genes are sufficient for a proper expression normalisation. The choice of the second gene, however, will depend on the type of experiment that is being carried out. For osmotic stresses and chemical treatments, TUA can be used reliably, while for the diurnal cycle ARP2.2 is more relevant.
As a brown alga, E. siliculosus is member of the kingdom of the Heterokonta, which is phylogenetically very distant from animals and land plants . Interestingly, and despite this evolutionary distance, a consensus seems to emerge from similar analyses performed in organisms belonging to distant lineages. The gene coding for the elongation factor of protein translation EF1a was shown to be the best reference genes in salmon  and in several plants such as in rice , grapevine  and potato . The alpha tubulin encoding gene was also reported to be one of the best reference genes for horse tissues  and in poplar . On the other hand, actin genes have been very often reported as exhibiting highly variable levels of expression in both human and animals tissues [10, 12, 16–18], and in plants . In this study, we have shown that this is also true for E. siliculosus.
Despite the fact that ubiquitin and related enzymes (UBCE) are not commonly used as normalisation genes, in this study, they were found to be quite suitable. Interestingly, Czechowski et al.  showed, using microarray analysis, that genes of the ubiquitin complex, comprising an ubiquitin conjugating enzyme such as UBCE, and several E3-ubiquitin protein ligases, were very stably expressed. They also pointed out that genes with fairly low levels of expression such as UBCE may be of particular interest for normalising expression levels of genes that are expressed at moderate to low levels, such as transcription factors. This latter example illustrates how microarray analyses may be useful to find additional normalisation genes, which can be then tested by Q-PCR for their suitability.
E. siliculosus is recognised as the genomic and genetic model of brown macroalgae [1, 2]. As the genome sequence is currently in the phase of expert annotation, the community interested in E. siliculosus is likely to grow in the near future. The results presented in this paper pave the way for further studies on different aspects of E. siliculosus biology including development/morphogenesis and abiotic/biotic stress responses. In addition, they will be helpful for comparison with results from microarray hybridizations, which are currently in progress.
Culture conditions and treatments
E. siliculosus (Ectocarpales, Phaeophyceae) unialgal strain 32 (CCAP accession 1310/4, origin san Juna de Marcona, Peru) was cultivated in 10 L plastic flasks in a culture room at 14°C using filtered and autoclaved natural seawater enriched in Provasoli nutrients . Light was provided by Philips daylight fluorescence tubes with a photon flux density of 40 μmol. m-2 .s-1 for 14 hours per day. Cultures were bubbled with filtered (0.22 μm) compressed air to avoid CO2 depletion. To conduct the chemical treatment experiments, algal tissues were transferred into Petri dishes containing artificial seawater enriched with Provasoli (ASW) for at least 18 h before treatments in order to acclimatize the cultures to the change of growth conditions. They were then treated with different chemicals for 3 and/or 6 h (see Table 1) during the light phase. The treatments were 10 mM H2O2 (final concentration), 42 μg.L-1 Diuron, 55 μg.L-1 atrazine, 5 μM 13-HOTrE and 15(S)-HEPE. Algae were also incubated in 10 μM CuSO4 for 3 and 6 h. An equal volume of solvent (ASW or DMSO 1%) was used in each corresponding control treatment. Wounding was carried out by damaging the tissues with a razor blade. To perform saline stress and an additional H2O2 treatment, tissues were transferred to ASW for one week before applying the stress. The NaCl concentration in control ASW was 450 mM, while it was 60 mM and 1.5 M in ASW used to submit the alga to hyposaline and hypersaline conditions respectively. In addition, H2O2 was added at 1 mM final concentration to the control ASW for generating oxidative stress. Treatments were applied for 6 h before harvesting the tissues for RNA extraction. To collect samples through the diurnal cycle, algae were incubated in ASW and tissue harvested every 6 h during one day. The first sample was taken 30 min after the beginning of the light period. The summary of the culture conditions is presented in Table 1.
Three biological replicates were obtained for each treatment and these were used for total RNA extraction.
The protocol used for RNA extraction was based on the method developed by Apt et al.  with some modifications. Frozen tissue was ground in liquid nitrogen and immediately incubated in the presence of extraction buffer (100 mM Tris-HCl pH 7.5, 2% CTAB, 1.5 M NaCl, 50 mM EDTA, 50 mM DTT). The sample was shaken at room temperature for 30 min, then one volume of chlorophorm:isoamylic alcohol (24:1, V/V) was added and the sample shaken again for 25 min. After centrifugation, the upper phase was transferred to a new tube and mixed with 0.3 V of absolute ethanol to precipitate the polysaccharides, and extracted with 1 V of chlorophorm. After centrifugation the upper phase was transferred to a fresh tube and RNA was precipitated by addition of 0.25 V of 12 M LiCl and β-mercapto-ethanol to 1% final concentration, overnight at -20°C. After centrifugation, the pellet was resuspended for DNAse treatment by an RNAse-free DNAse I (Turbo DNAse, Ambion) according to the manufacturer's instructions, in order to eliminate any residual genomic DNA from the preparation. An extraction was then carried out by adding Phenol-Chlorophorm (1:1, V/V). After centrifugation the upper phase was transferred to a fresh tube, and extracted with 1 V of chlorophorm:isoamylic alcohol (24:1, V/V) and centrifuged again. The upper phase was precipitated with 0.3 M NaAc pH 5.5 and 75% ice cold ethanol by incubating overnight at 20°C. After centrifugation, the supernatant was removed, and the pellet washed with 80% ethanol. After centrifugation and drying on ice, the pellet was resuspended in an appropriate volume of RNAse-free water.
Quantification of RNAs and cDNA synthesis
Nucleic acid concentrations were measured by the absorbance at OD260 using a NanoDrop ND-1000 spectrophotometer. The purity of the RNA samples was assessed by measuring the ratio OD260/OD280 and OD230/OD260 (see Additional file 3). RNA integrity was then verified on 1.5% agarose gel stained with ethidium bromide (see Additional file 4). From each RNA sample, 1.4 μg was reverse transcribed to cDNA using oligo(dT)12–18 and the Superscript™ First Strand synthesis for RT-PCR (Invitrogen) according to the manufacturer's instructions, and subsequently diluted with nuclease free water to 1 ng.μl-1 cDNA.
Protocol for DNA extraction
Frozen tissue was ground in liquid nitrogen and then in a wheaton potter with 15 ml of extraction buffer (100 mM Tris-HCl pH7.5; 1.5 M NaCl; 2% CTAB; 50 mM EDTA; 50 mM DTT) per g of wet tissue. The suspension was then mixed vigorously at room temperature for at least 30 min. Proteins were degraded with 25 units of proteinase K for 2 h at 55°C, and then extracted with chlorophorm/isoamyl alcohol for several minutes. Polysaccharides were precipitated with progressive addition of 0.2 – 0.3 V of ethanol, and then extracted with 1 V of chloroform after spinning at 10,000 g and 20°C for 20 min. Nucleic acids were recovered from the upper phase by addition of 0.25 V of 12 M LiCl and 1% of β-mercaptoethanol, incubation at -20°C overnight and spinning at 10,000 g and 4°C for 1 h. The supernatant was precipitated with 0.6 V isopropanol, 0.3 M NaAc pH 5.2, left at 4°C for 30 min, and then spun down for 30 min at 13,000 g. The pellet was then dissolved in 400 μl H2O, and precipitated again with ethanol and NaAc. DNA was dissolved in 500 μl of TE (10 mM Tris-HCl pH 8.0; 1 mM EDTA), 5.4 M CsCl (density 1.66) and 250 μg.mL-1 of ethidium bromide. Spinning at 90,000 g for 24 h at room temperature allowed the recovery of a band containing ultrapure genomic DNA under UV. Ethidium bromide was extracted 4–5 times with TE-saturated butanol and CsCl eliminated by successive ethanol precipitations.
All the genes were quantified on the same lot of cDNAs, to minimize experimental variation that could be due to cDNA synthesis. For each gene, a pair of oligonucleotide sequences was designed in the 3' UTR of the genes when the sequence was known, or in the 3'coding sequence using Primer Express TM1.0 (PE Applied Biosystems, Foster City, CA, USA) (Table 2). The Q-PCR reactions were performed in a 96-well thermocycler (Biorad, Opticon) with SYBRgreen reaction mix from ABgene (AB-1162/B), for 15 min at 95°C, followed by 41 runs of 15 sec at 95°C and 1 min at 60°C. Each sample was technically duplicated. E. siliculosus genomic DNA was used as a quantification reference. A dilution series ranging from 37 to 48671 copies of the E. siliculosus genome was prepared and tested for each gene. The amplification efficiency was tested using this dilution series (Table 2). The specificity of amplification was checked with a dissociation curve obtained by heating the samples from 65°C to 95°C (Table 2). In addition to the DNAse-I treatments of RNAs, the absence of a genomic DNA contaminants was checked, by amplifying an intron sequence on the cDNAs. The number of copies of contaminant gDNA was subtracted from all other values, prior to any further analyses.
actin-related protein 2/3
artificial sea water
dimethyl sulfoxide Dyn: dynein
translation elongation factor alpha
glucose 6-phosphate dehydrogenase
translation initiation factor 2 A
translation initiation factor 4E
ribososomal protein 26S
ubiquitin conjugating enzyme
We thank Julia Morales (Station Biologique de Roscoff) for her help concerning the identification of the IF2A and EFI4 genes, and Bernard Billoud (Atelier de Bioinformatique de l'Université Pierre et Marie Curie Paris-6) for his assistance with statistical analyses. ALB and P-O dF are granted by the French Ministère de l'Enseignement Supérieur et de la Recherche. SD has received funding from the European community's Sixth Framework Programme (ESTeam n° contract MESTCT 2005-020737).
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