Method For Gene Expression Analysis Research Articles

Selection of appropriate reference genes for quantitative real-time PCR in Oxytropis ochrocephala Bunge using transcriptome datasets under abiotic stress treatments.

Background: Oxytropis ochrocephala Bunge, an indigenous locoweed species in China, poses great threats to livestock on grasslands. There is a need for further genetic study in the plants per se, for understanding the basis of its acclimation mechanism in various unfavorable environmental conditions and to implement effective control measures. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is the most commonly used method for gene expression analysis. To facilitate gene expression studies and obtain more accurate qRT-PCR data, normalization relative to stable reference genes is required. The aim of this study was to select the most stable reference genes for transcriptional analysis in O. ochrocephala.Results: We selected 12 candidate reference genes, 18S ribosomal RNA (18S RNA), actin2/7 (ACT7), β-actin (ACTB), actin101 (ACT101), actin11 (ACT11), β-tubulin (TUB), α-tubulin (TUA), glyceraldehyde-3-phosphate dehydrogenase-1 (GAPDH1), GAPDH2, metallothionein-like protein (MET), fructose-bisphosphate aldolase (FBA) and histone H3 (HIS), from the transcriptome datasets of O. ochrocephala and determined the suitability by analyzing their expression levels when exposed to a range of abiotic stress conditions. By employing software packages including geNorm, NormFinder and BestKeeper, HIS, ACT7, and ACT101 were assessed as the most suitable set for normalization in all samples. When normalized with the most stable reference genes, the expression patterns of the three target genes were in accordance with those in the transcriptome data, indicating that the reference genes selected in this study are suitable.Conclusions: The study provided appropriate reference genes for accurate normalization in qRT-PCR analysis in O. ochrocephala and emphasized the importance of validating reference genes for gene expression analysis under specific experimental condition. The usage of inappropriate reference gene would cause misinterpretation.

Evaluating Robustness and Sensitivity of the NanoString Technologies nCounter Platform to Enable Multiplexed Gene Expression Analysis of Clinical Samples.

Analysis of clinical trial specimens such as formalin-fixed paraffin-embedded (FFPE) tissue for molecular mechanisms of disease progression or drug response is often challenging and limited to a few markers at a time. This has led to the increasing importance of highly multiplexed assays that enable profiling of many biomarkers within a single assay. Methods for gene expression analysis have undergone major advances in biomedical research, but obtaining a robust dataset from low-quality RNA samples, such as those isolated from FFPE tissue, remains a challenge. Here, we provide a detailed evaluation of the NanoString Technologies nCounter platform, which provides a direct digital readout of up to 800 mRNA targets simultaneously. We tested this system by examining a broad set of human clinical tissues for a range of technical variables, including sensitivity and limit of detection to varying RNA quantity and quality, reagent performance over time, variability between instruments, the impact of the number of fields of view sampled, and differences between probe sequence locations and overlapping genes across CodeSets. This study demonstrates that Nanostring offers several key advantages, including sensitivity, reproducibility, technical robustness, and utility for clinical application.

Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR.

Real-time quantitative PCR (RT-qPCR) is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis), a promising oilseed crop known for its polyunsaturated fatty acid (PUFA)-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt), BestKeeper, geNorm, and NormFinder) were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE), actin (ACT) and phospholipase A22 (PLA) were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13), cyclophilin (CYC) and elongation factor-1alpha (EF1α) were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII) were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi.

Involvement of Ca2+in Vacuole Degradation Caused by a Rapid Temperature Decrease inSaintpauliaPalisade Cells: A Case of Gene Expression Analysis in a Specialized Small Tissue

Saintpaulia (African violet) leaves are known to be damaged by a rapid temperature decrease when cold water is applied to the leaf surface; the injury is ascribed to the chloroplast damage caused by the cytosolic pH decrease following the degradation of the vacuolar membrane in the palisade cells. In this report, we present evidence for the involvement of Ca(2+) in facilitating the collapse of the vacuolar membrane and in turn in the temperature sensitivity of Saintpaulia leaves. In the presence of a Ca(2+) chelator (EGTA) or certain Ca(2+) channel inhibitors (Gd(3+) or La(3+)) but not others (verapamil or nifedipine), the pH of the vacuole, monitored through BCECF (2',7'-bis(carboxyethyl)-4 or 5-carboxyfluorescein) fluorescence, did not increase in response to a rapid temperature drop. These pharmacological observations are consistent with the involvement of mechanosensitive Ca(2+) channels in the collapse of the vacuolar membrane. The high level of expression of an MCA- (Arabidopsis mechanosensitive Ca(2+) channel) like gene, a likely candidate for a mechanosensitive Ca(2+) channel(s) in plant cells, was confirmed in the palisade tissue in Saintpaulia leaves by using a newly developed method of gene expression analysis for the specialized small tissues.

Exploring valid reference genes for quantitative real-time PCR analysis in Sesamia inferens (Lepidoptera: Noctuidae).

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (−8, −6, −4, −2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens.

Pathway activation profiling reveals new insights into age-related macular degeneration and provides avenues for therapeutic interventions.

Age-related macular degeneration (AMD) is a major cause of blindness in older people and is caused by loss of the central region of the retinal pigment epithelium (RPE). Conventional methods of gene expression analysis have yielded important insights into AMD pathogenesis, but the precise molecular pathway alterations are still poorly understood. Therefore we developed a new software program, "AMD Medicine", and discovered differential pathway activation profiles in samples of human RPE/choroid from AMD patients and controls. We identified 29 pathways in RPE-choroid AMD phenotypes: 27 pathways were activated in AMD compared to controls, and 2 pathways were activated in controls compared to AMD. In AMD, we identified a graded activation of pathways related to wound response, complement cascade, and cell survival. Also, there was downregulation of two pathways responsible for apoptosis. Furthermore, significant activation of pro-mitotic pathways is consistent with dedifferentiation and cell proliferation events, which occur early in the pathogenesis of AMD. Significantly, we discovered new global pathway activation signatures of AMD involved in the cell-based inflammatory response: IL-2, STAT3, and ERK. The ultimate aim of our research is to achieve a better understanding of signaling pathways involved in AMD pathology, which will eventually lead to better treatments.

Selection of reference genes for quantitative real-time PCR normalization in Panax ginseng at different stages of growth and in different organs.

Quantitative real-time reverse transcription PCR (qRT-PCR) has become a widely used method for gene expression analysis; however, its data interpretation largely depends on the stability of reference genes. The transcriptomics of Panax ginseng, one of the most popular and traditional ingredients used in Chinese medicines, is increasingly being studied. Furthermore, it is vital to establish a series of reliable reference genes when qRT-PCR is used to assess the gene expression profile of ginseng. In this study, we screened out candidate reference genes for ginseng using gene expression data generated by a high-throughput sequencing platform. Based on the statistical tests, 20 reference genes (10 traditional housekeeping genes and 10 novel genes) were selected. These genes were tested for the normalization of expression levels in five growth stages and three distinct plant organs of ginseng by qPCR. These genes were subsequently ranked and compared according to the stability of their expressions using geNorm, NormFinder, and BestKeeper computational programs. Although the best reference genes were found to vary across different samples, CYP and EF-1α were the most stable genes amongst all samples. GAPDH/30S RPS20, CYP/60S RPL13 and CYP/QCR were the optimum pair of reference genes in the roots, stems, and leaves. CYP/60S RPL13, CYP/eIF-5A, aTUB/V-ATP, eIF-5A/SAR1, and aTUB/pol IIa were the most stably expressed combinations in each of the five developmental stages. Our study serves as a foundation for developing an accurate method of qRT-PCR and will benefit future studies on gene expression profiles of Panax Ginseng.

Profiling of genetic switches using boolean implications in expression data.

Correlation analysis assuming coexpression of the genes is a widely used method for gene expression analysis in molecular biology. Yet growing extent, quality and dimensionality of the molecular biological data permits emerging, more sophisticated approaches like Boolean implications. We present an approach which is a combination of the SOM (self organizing maps) machine learning method and Boolean implication analysis to identify relations between genes, metagenes and similarly behaving metagene groups (spots). Our method provides a way to assign Boolean states to genes/metagenes/spots and offers a functional view over significantly variant elements of gene expression data on these three different levels. While being able to cover relations between weakly correlated entities Boolean implication method also decomposes these relations into six implication classes. Our method allows one to validate or identify potential relationships between genes and functional modules of interest and to assess their switching behaviour. Furthermore the output of the method renders it possible to construct and study the network of genes. By providing logical implications as updating rules for the network it can also serve to aid modelling approaches.

Reliable quantification of mRNA in archived formalin-fixed tissue with or without paraffin embedding.

Formalin fixation and paraffin embedding (FFPE) is a standard method for tissue sample storage and preservation in pathology archives. The Reverse Transcriptase Quantitative Polymerase Chain Reaction (RT-qPCR) is a useful method for gene expression analysis, but its sensitivity is significantly decreased in FFPE tissue due to the fixation process. This process results in chemical modifications of RNA, cross-links proteins to RNA, and degrades RNA in these archived samples, hindering the reverse transcription step of the conventional RT-pPCR method and preventing generation of a cDNA that is long enough for the subsequent quantitative PCR step. In this study, we used a multi-species RT-qPCR method originally developed to detect mRNA in tissue homogenate samples (Wang et al., 2011) and applied it to effectively detect a specific mRNA in formalin-fixed tissues with or without paraffin-embedding by targeting mRNA sequences as short as 24 nucleotides. Target sizes ranging from 24 to 91 nucleotides were evaluated using this multi-species RT-qPCR assay. Data generated with FFPE tissues demonstrated that use of short target sequences relieved the dependence on RNA quality and could reliably quantify mRNA. This method was highly sensitive, reproducible, and had a dynamic range of five orders of magnitude. Importantly, this method could quantify mRNA in prolonged formalin-fixed and FFPE tissue, where conventional RT-qPCR assays failed. Moreover, a similar result for small interfering RNA (siRNA)-mediated Apob mRNA knockdown was obtained from tissues fixed in formalin solution for 3months to 4years, and was found to be comparable to results obtained with frozen liver tissues. Therefore, the method presented here allows for preclinical and clinical retrospective and prospective studies on mRNA derived from archived FFPE and prolonged formalin-fixed tissue.

A method for quantitative analysis of standard and high-throughput qPCR expression data based on input sample quantity.

Over the past decade rapid advances have occurred in the understanding of RNA expression and its regulation. Quantitative polymerase chain reactions (qPCR) have become the gold standard for quantifying gene expression. Microfluidic next generation, high throughput qPCR now permits the detection of transcript copy number in thousands of reactions simultaneously, dramatically increasing the sensitivity over standard qPCR. Here we present a gene expression analysis method applicable to both standard polymerase chain reactions (qPCR) and high throughput qPCR. This technique is adjusted to the input sample quantity (e.g., the number of cells) and is independent of control gene expression. It is efficiency-corrected and with the use of a universal reference sample (commercial complementary DNA (cDNA)) permits the normalization of results between different batches and between different instruments – regardless of potential differences in transcript amplification efficiency. Modifications of the input quantity method include (1) the achievement of absolute quantification and (2) a non-efficiency corrected analysis. When compared to other commonly used algorithms the input quantity method proved to be valid. This method is of particular value for clinical studies of whole blood and circulating leukocytes where cell counts are readily available.

Hybrid feature selection method for gene expression analysis

Feature selection is important and necessary for disease classification and prediction using high-dimensional gene expression data. A hybrid method integrating sparse representation with a two-sample statistical t -test to construct features from high-throughput microarray data is presented. The approach takes account of gene interaction and reduces the variable dimension by sparse linear combination, as well as considers the discriminative power of genes using component regression. Under the recurrent independence rule for classification, the experiment results on real data demonstrate the improvements of this hybrid technique over conventional methods.

Selection of appropriate reference genes in eggplant for quantitative gene expression studies under different experimental conditions

Quantitative real-time polymerase chain reaction (RT-qPCR) has become one of the most widely used methods for gene expression analysis, and the evaluation of appropriate reference genes should be the first step to consider in experiments based on RT-qPCR. In this work, nine candidate reference genes, including 18sRNA, CYP, UBQ, GAPDH, TUB, TUA, EF1, ACTIN and RPOB, were investigated for their expression stability in five different eggplant sample pools using three algorithms: geNorm, NormFinder and RefFinder. The samples were collected under different experimental conditions, including those from different plant tissues, hormone treatments, biotic and abiotic stresses. Our results demonstrated that the expression stability varied from different experimental conditions between reference genes. In general, GAPDH and 18sRNA had a good performance under most experimental conditions, whereas TUB and RPOB exhibited poor stability. This study should provide guidelines for the selection of reference genes for gene expression studies in eggplant.

Computer analysis of the data on gene expression in brain cells obtained by microarray tests and high-throughput sequencing

The scope of neurobiological studies has been greatly expanded in the last few years. Such expansion is accompanied by the accumulation of a huge body of experimental data on the structure, function and evolution of the nervous system at different hierarchical levels of its organization. High-throughput sequencing technologies and microarrays permit analysis the gene expression for thousands of genes simultaneously taking into account cell location in the brain. In this work methods of gene expression analysis are briefly reviewed in the context of brain research. We have analyzed specific features of genes differentially expressed in brain cells. Some genes overexpressed in brain structures are associated with neurological diseases. A number of exons and active transcripts for genes differentially expressed in brain were calculated. The statistically significant difference in these parameters is shown for genes overexpressed in brain. Examples of such differentially expressed genes associated with neurological diseases are presented.

Simplified method for cell-specific gene expression analysis in Caenorhabditis elegans

In the neural circuit functional identities of individual neurons are mainly specified by their differential gene expression patterns. Unveiling functional roles of each neuron requires cell-specific interrogation of neural circuitry in the context of gene expressions. The mRNA tagging strategy in Caenorhabditis elegans is a powerful technique, in which cell-specific transcripts can be isolated by co-immunoprecipitating the complexes of mRNAs and epitope-tagged poly(A) binding protein (3× FLAG–PAB-1), expressed in target neurons. However, the conventional protocol requires laborious and time-consuming procedures; chromosomal integration of gene encoding 3× FLAG–PAB-1 and bleaching of obtained integrant animals for the isolation of huge amounts of synchronized animals. In this paper, we have presented a simplified methodology for cell-specific mRNA tagging analysis in C. elegans. We show that mRNA tagging was achieved using transgenic animals expressing 3× FLAG–PAB-1 as an extrachromosomal array under the control of the flp-18 promoter, without the chromosomal integration procedure. Furthermore, we successfully isolated cell-specific mRNAs from adult transgenic animals synchronously grown from eggs laid by gravid adults during a time window of 3h. This simplification facilitates the implementation of cell-specific gene expression analysis of C. elegans, which contributes to the understanding of neural circuitry at a cell-specific resolution.

Comprehensive selection of reference genes for gene expression normalization in sugarcane by real time quantitative rt-PCR.

The increasingly used real time quantitative reverse transcription-PCR (qRT-PCR) method for gene expression analysis requires one or several reference gene(s) acting as normalization factor(s). In order to facilitate gene expression studies in sugarcane (Saccharum officinarum), a non-model plant with limited genome information, the stability of 13 candidate reference genes was evaluated. The geNorm, NormFinder and deltaCt methods were used for selecting stably expressed internal controls across different tissues and under various experimental treatments. These results revealed that, among these 13 candidate reference genes, GAPDH, eEF-1a and eIF-4α were the most stable and suitable for use as normalization factors across all various experimental samples. In addition, APRT could be a candidate for examining the relationship between gene copy number and transcript levels in sugarcane tissue samples. According to the results evaluated by geNorm, combining CUL and eEF-1α in hormone treatment experiments; CAC and CUL in abiotic stress tests; GAPDH, eEF-1a and CUL in all treatment samples plus CAC, CUL, APRT and TIPS-41 in cultivar tissues as groups for normalization would lead to more accurate and reliable expression quantification in sugarcane. This is the first systematic validation of reference genes for quantification of transcript expression profiles in sugarcane. This study should provide useful information for selecting reference genes for more accurate quantification of gene expression in sugarcane and other plant species.

Versatile and efficient RNA extraction protocol for grapevine berry tissue, suited for next generation RNA sequencing

Background and Aims: New high-throughput tools for transcriptomic analysis such as RNA sequencing have been developed rapidly in recent years. These technologies provide new opportunities for biologists to improve the understanding of gene expression underlying important physiological processes. The sequencing of RNA by nextgeneration technologies is, in particular, dependent on the use of pure and un-degraded RNA. Many fruits from perennial crops share an elevated concentration of tannins and polysaccharides and a strong dilution of cytosolic content upon vacuole hypertrophy. The grapevine berry presents these characteristics together with high vacuole acidity, which has never been taken into account in previous protocols, and poses thereby a particular challenge for RNA extraction. Methods and Results: In order to counterbalance these limitations, we developed a new extraction protocol based on a tri-sodium-citrate extraction buffer that has a high buffer capacity and proved to be particularly suitable for low pH plant tissue. Conclusions: The proposed RNA extraction procedure produces consistently high-quality RNA (RNA integrity number > 8 up to 10; 260 nm/280 nm > 2; 260 nm/230 nm > 1.9) with an elevated yield [20 μg/g fresh mass (FM) for ripe berries up to 150 μg/FM for green berries]. The method was developed initially for berry tissues but proved also to be efficient for other grapevine tissues, such as nodes, roots, leaves, seeds, lignified shoots and flowers. Significance of the Study: The method is most suitable for modern gene expression analysis methods, such as RNA sequencing and microarray studies. Successful construction of cDNA libraries and high numbers of detected reads obtained by next-generation RNA sequencing underline the applicability of the protocol.

The use of laser microdissection in the identification of suitable reference genes for normalization of quantitative real-time PCR in human FFPE epithelial ovarian tissue samples.

Quantitative real-time PCR (qPCR) is a powerful and reproducible method of gene expression analysis in which expression levels are quantified by normalization against reference genes. Therefore, to investigate the potential biomarkers and therapeutic targets for epithelial ovarian cancer by qPCR, it is critical to identify stable reference genes. In this study, twelve housekeeping genes (ACTB, GAPDH, 18S rRNA, GUSB, PPIA, PBGD, PUM1, TBP, HRPT1, RPLP0, RPL13A, and B2M) were analyzed in 50 ovarian samples from normal, benign, borderline, and malignant tissues. For reliable results, laser microdissection (LMD), an effective technique used to prepare homogeneous starting material, was utilized to precisely excise target tissues or cells. One-way analysis of variance (ANOVA) and nonparametric (Kruskal-Wallis) tests were used to compare the expression differences. NormFinder and geNorm software were employed to further validate the suitability and stability of the candidate genes. Results showed that epithelial cells occupied a small percentage of the normal ovary indeed. The expression of ACTB, PPIA, RPL13A, RPLP0, and TBP were stable independent of the disease progression. In addition, NormFinder and geNorm identified the most stable combination (ACTB, PPIA, RPLP0, and TBP) and the relatively unstable reference gene GAPDH from the twelve commonly used housekeeping genes. Our results highlight the use of homogeneous ovarian tissues and multiple-reference normalization strategy, e.g. the combination of ACTB, PPIA, RPLP0, and TBP, for qPCR in epithelial ovarian tissues, whereas GAPDH, the most commonly used reference gene, is not recommended, especially as a single reference gene.

Defining reference genes for quantitative real-time PCR analysis of anther development in rice

Quantitative real-time polymerase chain reaction (qPCR) is one of the most accurate and widely used methods for gene expression analysis. However, the choice of reference genes for normalization is critical for accurate quantification of gene expression. As development of genomics, mining large-scale datasets such as microarray and RNA-sequencing data becomes a new approach for exploitation of new reference genes. In this study, we analyzed an RNA-sequencing dataset of rice anther and 167 microarray datasets involving different tissues and developing stages of rice anthers and pollens. We selected 12 candidate genes and other 5 reference genes, including ACT1, eEF-1α, GAPDH, Exp2, and CCDC72 used in previous studies, and evaluated their expression in eight tissues and different developmental stages of anthers in rice variety 9311 and Yuetai. UPF3, eIF4A-3, GAPDH, and PPP6 were identified as the most suitable reference genes for qPCR analysis of anther development in rice. The new candidate reference genes showed more stable expression than the traditionally used reference genes. These results provide a set of reliable reference genes for studies in rice anther developmental process.

Profiling of Genetic Switches using Boolean Implications in Expression Data

Summary Correlation analysis assuming coexpression of the genes is a widely used method for gene expression analysis in molecular biology. Yet growing extent, quality and dimensionality of the molecular biological data permits emerging, more sophisticated approaches like Boolean implications. We present an approach which is a combination of the SOM (self organizing maps) machine learning method and Boolean implication analysis to identify relations between genes, metagenes and similarly behaving metagene groups (spots). Our method provides a way to assign Boolean states to genes/metagenes/spots and offers a functional view over significantly variant elements of gene expression data on these three different levels. While being able to cover relations between weakly correlated entities Boolean implication method also decomposes these relations into six implication classes. Our method allows one to validate or identify potential relationships between genes and functional modules of interest and to assess their switching behaviour. Furthermore the output of the method renders it possible to construct and study the network of genes. By providing logical implications as updating rules for the network it can also serve to aid modelling approaches.

Selection of Suitable Reference Genes for Quantitative Real-time Polymerase Chain Reaction in Prunus mume during Flowering Stages and under Different Abiotic Stress Conditions

Mei (Prunus mume) is widely cultivated in eastern Asia owing to its favored ornamental characteristics and its tolerance for low temperatures. Reverse transcription quantitative real-time polymerase chain reaction (qRT-PCR) is a widely used method for gene expression analysis, requiring carefully selected reference genes to ensure data reliability. The aim of this study was to identify and evaluate reference genes for qRT-PCR in mei. Ten candidate reference genes were chosen, and their expression levels were assessed by qRT-PCR in four sample sets: 1) flowering mei; 2) mei undergoing abiotic stress; 3) different genotypes of Prunus species; and 4) all mei samples. The stability and suitability of the candidate reference genes were validated using commercially available software. We found that protein phosphatase 2A-1 (PP2A-1) and PP2A-2 were suitable reference genes for flowering with ubiquitin-conjugating enzyme E2 (UBC) also being suitable for different genotypes of Prunus species. UBC and actin (ACT) were most stably expressed under abiotic stress. Finally, the expression of an AGAMOUS homolog of Arabidopsis thaliana (PmAG) and a putative homolog of Group 2 late embryogenesis abundant protein gene in A. thaliana (PmLEA) were assessed to allow comparisons between selected candidate reference genes, highlighting the importance of careful reference gene selection.