Quantitative evaluation and selection of reference genes in mouse oocytes and embryos cultured in vivo and in vitro
© Mamo et al; licensee BioMed Central Ltd. 2007
Received: 19 October 2006
Accepted: 06 March 2007
Published: 06 March 2007
Real-time PCR is an efficient tool to measure transcripts and provide valuable quantitative information on gene expression of preimplantation stage embryos. Finding valid reference genes for normalization is essential to interpret the real-time PCR results accurately, and understand the biological dynamics during early development. The use of reference genes also known as housekeeping genes is the most widely applied approach. However, the different genes are not systematically compared, and as a result there is no uniformity between studies in selecting the reference gene. The goals of this study were to compare a wide selection of the most commonly used housekeeping genes in mouse oocytes and preimplantation stage embryos produced under different culture conditions, and select the best stable genes for normalization of gene expression data.
Quantitative real time PCR method was used to evaluate 12 commonly used housekeeping genes (Actb, Gapdh, H2afz, Hprt, Ppia, Ubc, Eef1e1, Tubb4, Hist2h2aa1, Tbp, Bmp7, Polr2a) in multiple individual embryos representing six different developmental stages. The results were analysed, and stable genes were selected using the geNorm software. The expression pattern was almost similar despite differences in the culture system; however, the transcript levels were affected by culture conditions. The genes have showed various stabilities, and have been ranked accordingly.
Compared to earlier studies with similar objectives, we used a unique approach in analysing larger number of genes, comparing embryo samples derived in vivo or in vitro, analysing the expression in the early and late maternal to zygote transition periods separately, and using multiple individual embryos. Based on detailed quantification, pattern analyses and using the geNorm application, we found Ppia, H2afz and Hprt1 genes to be the most stable across the different stages and culture conditions, while Actb, the classical housekeeping gene, showed the least stability. We recommend the use of the geometric averages of those three genes for normalization in mouse preimplantation-stage gene expression studies.
Preimplantation embryo development is a dynamic developmental process recognized by four distinct phases  that vary in stage and duration from species to species (reviewed in ). These phases span the time after fertilization until the formation of blastocyst, and further differentiation to the inner cell mass (ICM) and trophectoderm. During preimplantation stage embryo development, the expression of some active transcripts peculiar to each stage has been described earlier [3–5]. The different developmental stages are marked with variations in the cell number, total and poly (A) RNA contents [6–8]. Understanding such biological dynamics during early embryonic development would yield insights into the complex molecular pathways controlling early development , and further refinement of assisted reproductive technology (ART) in mammals .
Common methods of RNA detection and analyses were described elsewhere [11, 12]. However, technical limitations and dearth of starting material have restricted accurate, quantitative analysis of mRNA abundance for genes of interest in mammalian oocytes and early embryos, using the classical molecular biology approaches [12–14]. Real time PCR has been a quantitative method of choice to understand the comparative roles of different transcripts in the preimplantation-stages of embryo development, and to corroborate the results of microarray and other gene expression studies. It has greatly improved the quantitative gene expression studies, due to its speed, ease of use, reproducibility, high sensitivity, and absence of radioactive materials . The values of real time PCR quantitative results, besides good experimental and primer designs, lie in the accurate applications of all the procedures like quality RNA isolation, cDNA synthesis, dilutions made, pippeting, use of appropriate controls, and final analysis . Moreover, embryonic samples have additional sources of variations. Unlike cell lines and single-organ tissues, the cells comprising the embryo have inherently a vastly heterogeneous nature, which leads to greater variation in the endogenous biological processes, and greater variation in the sensitivity of the cells to the treatment . There is high probability that any of these factors can introduce intra- and inter assay variations for which normalization is required.
Besides standardizing most of these procedures to control variations, different normalization procedures were used so far. The pros and cons of different normalization approaches were described in a recent review . Internal reference genes, which are also known as housekeeping genes, are used in most experiments to normalize the results of gene expressions, albeit variations in selecting the type of gene. Different studies have used the most commonly known reference genes that include β-actin (Actb), glyceraldehydes-3-phosphate dehydrogenase (Gapdh), hypoxantin-guanine phosphoribosyl transferase (Hprt1), and 18S ribosomal RNA [17, 18]. Owing to the pattern variations of these genes under different conditions, their unconditional uses were frequently criticized [18–20]. A number of studies started to address the issue by evaluating normalizer genes for different species, including ovine , and bovine [13, 14, 22]. In a recent mouse study , the results were based on comparisons of only a few genes and developmental stages.
In the present study, the goals were to compare the expression of a wider selection of the most commonly used housekeeping genes (12 genes) in mouse oocytes and different preimplantation-stage embryos and finally select the best stable genes for normalization. To our knowledge, for the first time, comparisons of the early and late phases of the maternal to zygotic development control transitions (MZT), and embryos derived both in vivo or produced in vitro (IVP) have been made in the same study, to make the results more widely applicable.
Primer screening and PCR efficiency analyses
Reference genes selected for the study, and sizes of the PCR products.
Product size (bp)
Actin, beta, cytoplasmic
Hypoxanthine guanine phosphoribosyl transferase
H2A histone family, member Z
Peptidylprolyl isomerase A
Eukaryotic translation elongation factor 1 epsilon 1
Tubulin, beta 4
Histone 2, H2aa1
TATA box binding protein
Bone morphogenetic protein 7
Polymerase (RNA) II (DNA directed)
Gene expression profile analyses at different developmental stages
Gene expression profile analyses in different culture conditions
Gene expression stability analysis
Recognizing the variations of the dynamics in gene expression of different tissues , developmental stages , and treatment conditions [25, 26], the identification of stable normalizer genes for each experimental condition was frequently suggested [17, 27, 28]. The use of unconfirmed reference genes for normalization is misleading the interpretation of the gene expression results [29, 30]. As a result, RNA mass quantity was frequently used for normalization. However, this approach has been challenged for not considering the variations during the subsequent enzymatic reactions, its impracticality for normalizing mRNA transcripts and small samples like microdissected tissues and embryos . On the other hand, the competitive PCR procedure of adding exogenous template, although used by others [32, 33], has also been criticized for its laborious procedures [34, 12], and competition with endogenous sequences for primers and nucleotides during the PCR reactions . Moreover, the method is not accounting for the quality and quantity of the input RNA , although the reference gene expression stability can be affected by RNA quality . The use of housekeeping genes for normalization is a widely used approach in most experiments, and a number of publications appeared to suggest housekeeping genes for different experimental conditions.
Recently, two groups [12, 36] published their finding, on appropriate housekeeping genes for mouse oocytes and preimplantation-stage embryos. Despite the valuable contributions of the Jeong et al.  in examining the effects of different RNA isolation and detection techniques on the selection of reference genes, the recommendations on the reference gene aspect was constrained by the limited number of genes compared, developmental stages and culture systems considered. Taking into consideration the broad options (for selections) of reference genes, and the different embryo production systems used for various experiments, it is imperative to consider wider options to come to meaningful recommendations. Although the later work  tried to address the issue of reference genes, the aspect on the embryo was constrained by its design to consider advanced peri-implantation and post-implantation stage embryos only (days 3.5, 7.5, 9.5 and 11.5), which is not a representative of full preimplantation developmental period. Moreover, two of the selected genes in our experiment (Ppia and H2afz) were not considered, and the use of pooled samples is another difference from our experiment.
Our approach to select the appropriate housekeeping genes focused on the use of multiple individual embryos, as compared to pooled samples. The results of various previous studies [37, 38] have supported the use of individual samples as compared to the pooled ones in depicting the true biological variations. Moreover, to comply with the scarcity of materials in the embryo samples, advantages of early signal detection and strong correlation coefficients were leading to the selection of seven genes for further quantification and evaluations. Comparison of these genes can make our recommendations applicable to use even in studies of rare transcripts. Thus, we believe that our approach has enabled to identify the most stable housekeeping genes for normalization in the systems examined.
One of the interesting observations in this study was the transcript variation between the early and late 2-cell stage embryos. In most studies so far, 2-cell stage was taken in a holistic analysis without due regard for the different time courses. In mouse embryo development, the 2-cell stage is a bridge from the maternal phase to the embryonic phase of development control (maternal-zygotic transition, MZT), and marked by a lag in the development (developmental block). Thus, compared to other stages, the fractional analysis of transcripts at this stage is important, as it enables to identify the most stable genes for normalization even under major transcript shifts during development. The observations in this study with variations in transcript levels among the early and late 2-cell stage embryos support this concept.
Primer sequences and parameters of standard curves for the selected genes used in the experiment
The effects of culture conditions and developmental stages on the expression of the genes were studied in detail for a wide selection of reference genes and compared both under in vivo and in vitro culture systems. Our result shows that it is possible to use the same selected genes for both culture systems, however culture conditions affected the transcript levels. Therefore, calculation of different normalization factors, which is sample specific, is necessary.
The stable expression of the three reference genes (Ppia, H2afz and Hprt1) concomitant with the advancing developmental stage warrants their selection as normalizer for mouse preimplantation stage embryo gene expression analysis. The least stability observed for β-actin in both culture conditions, imply its inappropriateness as reference gene. Results of the current study and those in other mammalian species revealed the need for system specific reference genes. Although the selected reference genes were evaluated under in vivo, and our in vitro culture conditions (CZB-Hepes), we suggest further evaluation under various in vitro culture (KSOM, SOF, M16, etc) conditions.
All chemicals, unless stated otherwise, were purchased from Sigma-Aldrich Chemical Inc. (St. Louis, USA).
Female ICR (CD1) mice, aged 7 to 8 weeks old, were induced to superovulate by intraperitoneal administration of 5.0 IU pregnant mare serum gonadotropin (PMSG, Folligon® Intervet, The Netherlands), and then 48 h later, by 5.0 IU of human chorionic gonadotropin (hCG, Choregon®, Richter Gedeon Rt., Hungary). Donor female mice were humanly killed at 16 h post hCG injection and cumulus oocyte complexes were collected from the ampullae of the oviducts with subsequent removal of the cumulus cells using hyaluronidase (1 mg/ml) in CZB-Hepes buffer. Seven oocytes were individually collected for mRNA isolation. Finally, the matured oocytes were washed three times in RNAse-free water, collected individually in 2 μl drops of RNase-free water and stored at -80°C until RNA extraction.
Embryo production and culture conditions
Female ICR mice, aged 7 to 8 weeks old, were induced to superovulate as described earlier. Each injected female was mated with a single, more than 10 weeks old male of the same strain, which was subsequently verified by the presence of vaginal plug. Female mice were humanly killed, at specific times for each developmental stage, and in vivo samples of early (38 h) and late (46 h) 2-cell stage embryos, 8-cell stage embryos (65 h), early (93 h) and expanded blastocysts (93 h) were collected.
For the IVP samples of the same developmental stages, pronuclear zygotes were flushed by opening the ampullae at 20 hr post-hCG administration and, the cumulus cells were removed using hyaluronidase in CZB-Hepes buffer. The zygotes were then selected based on the presence of two pronuclei and cultured in a group of 20 in CZB medium as described earlier , until the proper developmental stage [early 2-cell (38 h), late 2-cell (47 h), 8-cell (87 h), early blastocyst (94 h) and expanded blastocyst (111 h)].
Finally, the different culture source and developmental-stage embryos were washed three times in RNAse-free water, collected individually in 2-μl drops of RNase-free water and stored at -80°C until RNA extraction.
RNA isolation and cDNA synthesis
The procedures of RNA isolation and cDNA synthesis were as described in our earlier works [15, 49]. Briefly, messenger RNA was isolated individually from 6 embryos per developmental stage and culture condition using Dynabeads® mRNA DIRECT™ Micro Kit (Dynal A.S, Oslo, Norway), following the manufacturer's instructions. The individually frozen embryos were lysed and incubated with pre-washed magnetic Dynabeads that can base pair with poly (A) tails of mRNA molecules. After hybridisation and subsequent repeated washes with buffers, the RNA was eluted in RNase-free water and reverse transcribed into cDNA, using M-MLV RT kit (Invitrogen, Carlsbad, CA) in a final 20-μl reaction volume. Minus RT reaction was performed to check the absence of contaminating residual DNA.
Primer design and real time PCR analysis
A total of twelve genes, most commonly used as housekeeping for normalization, were selected for evaluation throughout the different developmental stages and culture conditions. Primers were designed for these genes at the exon-exon border using Primer Express Software (Applied Biosystems, Foster City, CA), optimised and initially screened using similar concentration templates. Details of the primers are described in Table 1 and Table 2.
The details of real time PCR reaction procedures were as described earlier . During quantification of the transcripts, the assay for each gene consisted of six replicates per stage, six different preimplantation embryo developmental stages, negative and positive controls. All genes were compared from the same stock to avoid inter-assay template variations. Each sample in a run consisted of 0.08 embryo equivalent cDNA template, 300 nM of each primer, and 50% SYBR® Green JumpStart™ Taq ReadyMix™ in 25-μl reaction volume. The reaction conditions were template denaturation and polymerase activation at 95°C for 2 min followed by 45 cycles of 95°C denaturation for 15 sec, 60°C annealing for 20 sec and 72°C extension for 30 sec. The reactions were carried out using the Rotor-Gene™ 3000 real time PCR machine (Corbett Research, Mortlake, Australia), and the results were analysed with the integrated Rotor-Gene software (version 6.0.27). At the end of PCR reactions, melt curve analyses were performed for all genes, and the specificity as well as integrity of the PCR products were confirmed by the presence of a single peak. For the selected genes, the expected sizes of the products were also confirmed by gel electrophoresis on a 2% agarose gel stained with ethidium bromide and visualized under UV light. For calculating PCR efficiencies, standard curves were generated from assays made with serial dilutions of cDNA preparations using 5-pooled blastocysts. Moreover, to ensure the comparability of PCR assays, three independent serial dilutions were made that enabled us to determine the CT values and PCR efficiencies of the individual assay, and calculate the correlation between them. PCR efficiency (E) was calculated with the equation (E = (10[-1/slope] - 1) × 100).
geNorm and expression stability analysis
Analysis of the gene expression stability over the different embryonic stages was performed using the geNorm software . The analysis relies on the principle that the expression ratio of two ideal internal control genes is identical in all samples, regardless of the experimental condition or cell type, and determined as the standard deviation of the logarithmically transformed expression ratios . Using the software, the internal control gene stability measure value (M) was calculated as the average pair wise variation of a particular gene with respect to the rest of the genes, and ranking was made based on these values. The lower the M value, the more stable the expression of the gene under consideration. The most stable reference genes were identified by stepwise exclusions of the least stable gene and recalculating the M values.
The work was supported by Wellcome Trust (Grant No.070246), EU FP6 (MEXT-CT-2003-509582), EU FP6 (LSHG-CT-2006-518240), EU FP6 (MRTN-CT-2006-035468) and Hungarian National Science Fund (OTKA No. T046171).
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