RG: Reference Genes; GAPDH: Glyceraldehyde 3-Phostphate Dehydrogenase; YWHAZ: Tyrosine 3-Monooxygenase/ Tryptophan 5-Monooxygenase Activation Protein; B2M: Beta-2 Microglobulin; EIF4A2: Eukaryotic Translation Initiation Factor 4A2; ATP5β: ATP Synthase H+ Transporting Mitochondrial F1 Complex β Subunit; ACTB: Beta Actin; CYC1: Cytochrome C1; CVD: Cardiovascular Disease; MetS: Metabolic Syndrome; RT-PCR: Reverse Transcriptase Polymerase Chain Reaction

Transcriptome analysis of metabolic tissues can provide important insights into the pathogenesis of disease, aging, and the effectiveness of targeted interventions. Gene expression studies in the heart are particularly pertinent due to the current rise in cardiometabolic disease in an increasingly obese population. Obesity presents an increased risk of cardiovascular disease (CVD), in part through association with other features of the metabolic syndrome (MetS) such as insulin resistance, hypertension, dyslipidemia, fatty liver disease, pro-inflammatory state, and ectopic fat accumulation. Specifically type 2 diabetes, MetS and CVD coincide in 42.9-99% of individuals [1]. Despite recognition of candidate disease gene loci (chromosome 3p and q), extremely few disease alleles (alpha-ketoglutarate-dependent dioxygenase FTO) have been identified [1,2]. Therefore, it is likely that obesity induced alterations in gene expression stoichiometry within key metabolic tissues, such as the heart, play a major role in long term organ function. For example, preliminary evidence has shown that repetitive ischemia and reperfusion in diet induced obese mice is associated with significant down-regulation of fatty acid metabolism transcripts [3]. Nonetheless the diet altered cardiac transcriptome is surprisingly uncharacterized. The lack of insightful gene expression studies may result from utilization of an inappropriate reference gene (RG) as an internal control.

Quantitative real-time PCR provides a sensitive, specific and reproducible means of determining comparative gene mRNA expression profiles. However, an increasing number of reports have shown that RT-PCR data accuracy is highly dependent on appropriate normalization strategies [4]. It is now recognized that expression of classic RG can vary across tissue type and experimental condition [5]. In addition, it has recently it has been shown that a significant number of metabolic genes in the heart are under the transcriptional control of an intrinsic circadian clock and 24hr expression pattern [6]. Interestingly, specific disruption of the core molecular clock components can results in a MetS phenotype [7]. Therefore, selection of a constitutively expressed cardiac RG, which maintains stability irrespective of time of day or pathological conditions, is essential. In this study, we compared the expression the of seven RGs in the heart of control and high fat fed mice during both the night and day, in order to determine stably expressed RGs for use in gene expression studied investigating the pathogenesis of cardiometabolic disease.

Animal procedures were carried out in accordance with the UK Animals (Scientific Procedures) Act 1986. C57/BL6J mice were used in this study. All animals were maintained under a 12h light/dark cycle (lights on at 07.00h), and at a constant temperature of 22 ± 2°C. Newlyweaned offspring (3 weeks old) were randomly allocated to one of two diets: standard laboratory chow (control; 20.6% kcal fat; RM-1 Special Dietary Services, UK), or a high fat diet (45% kcal fat; Special Dietary Services, UK). At 15 weeks of age, offspring were killed by cervical dislocation at 2 time points during the 24h light-dark period at either 3 pm (Zeitgeber Time 8 or ZT8; eight hours into the light or day period), and at 3am (ZT20; eight hours into the dark or night period). Thus resulting in four groups: (1) control fed-daytime levels, (2) control fednight time levels, (3) high fat fed-daytime levels, and (4) high fat fednight time levels. Heart tissue was immediately snap frozen in liquid nitrogen and stored at -80°C.

Total RNA was isolated from 0.025g of whole heart tissue (n=5 per ZT and dietary group) using Trifast reagent (Peqlab, Germany) according to manufacturer's instructions. One microgram of total RNA from each sample was reverse transcribed to using M-MLV transcriptase (Promega, UK) was then added to each sample. Samples were then incubated at 37°C for one hour, 42°C for ten minutes, followed by an enzyme activation step at 75°C for ten minutes.

Stability and expression of the RGs was determined at ZT8 and ZT20, otherwise referred to as day and night respectively, across both C and HF mice by quantitative real time reverse transcriptase polymerase chain reaction (qRT-PCR; Applied Biosystems 7500 Fast Real-Time PCR Thermal Cycler). The RGs, namely ACTB, GAPDH, YWHAZ, B2M, EIF4A2, ATP5β and CYC1 (see Table 1) were taken from a geNorm Reference Gene Selection Kit with Perfect Probe (Primer Design, UK) and PCR reactions were prepared as according to instructions. PCR amplification was performed for 50 cycles. Following an initial enzyme activation step for 10 minutes at 95°C, each cycle consisted of denaturation for 15 seconds at 95°C, annealing for 30 seconds at 50°C and 15 seconds at 72°C. Analysis of duplicated samples indicate that the intra-assay coefficients of variability (CV) was>5%.

Table 1: Primary functions of RGs used.

The stability in expression of RGs was analysed using qBasePLUS software (Biogazelle). We used qBasePLUS software version 1.5 based on geNorm and qBase technology. From this a stability measure (M) was generated by geometric averaging of multiple target genes and mean pair-wise variation of a gene from all other target genes in a given sample [8]. Genes with the lowest M values are deemed the most stable.

Methods used for RT-PCR are highly susceptible to error since small experimental variations have the capacity to produce large errors in gene quantification. For this reason, and to facilitate comparison of gene quantification between samples, it is important to normalise the expression of genes of interest against stable RGs; ideally highly expressed and unaffected by time, or experimental conditions. Such gene(s) can only be identified through an appropriate selection strategy specific for the tissue and set of experimental conditions [9].

We analysed the expression stability of each experimental group separately, in order to show the variation incurred due to high fat dietary intervention and time of day. Firstly, Figure 1A shows that B2M and CYC1 are the two least stable, but ATP5ß and EIF4A2 are the most stably expressed housekeeping genes in heart tissue taken during the day from the control-fed group. Subtle alterations occur in heart tissues taken at night compared to tissues sampled during the day in the control-fed group and YWHAZ replaces EIF4A2 as the most stably expressed gene (Figure 1B). High fat fed mice exhibiting features of the MetS, including significantly increased systolic blood pressure [10], show altered RG expression pattern during the day (Figure 1C). Notably, ATP5ß reverts from high to lowest stability. Finally, heart tissue that was taken during the night from high fat fed mice (Figure 1D) also exhibit an altered RG expression pattern compared to tissues from control-fed animals (Figure 1B). Most notably, CYC1 expression becomes relatively stable at night, whilst night time expression of EIF4A2 destabilises. It is clear from this data that RG expression is subject to diet and circadian-induced alterations.

Figure 1: Stability of reference gene (RG) expression at either daytime or night time in the hearts of mice fed either a control (A and C) or high fat diet (B and D). Housekeeping gene expression in individual groups; * = the most stably expressed RGs, whereas # = the least stable RGs. (E.) Stability ranking for all groups. (F.) Mean Ct value±SEM for each gene when all groups and time points are combined.

We also analysed the expression stability of all experimental groups in order to determine the most stable RGs overall (Figure 1E). Whilst B2M and GAPDH were the most unstable RGs, YWHAZ and ACTB were the most stable overall. In further support of this finding the mean Ct value for each RG is presented in Figure 1F, and clearly demonstrates that the error is reduced as stability of the gene increases (and M value decreases). For gene of interest in a cardiometabolic or circadian study, B2M would be a particularly unsuitable RG. In contrast, an average of the most stable genes (i.e. YWHAZ and ACTB) would be recommended to generate accurate comparative gene expression data.

Few studies have investigated the appropriate selection of stable RGs in murine hearts under various experimental conditions, and none in a model of diet induced MetS and at different times of the day [5]. Our study has demonstrated that murine heart RG expression does indeed exhibit dietary and circadian modulations. In addition, we are the first to use an appropriate selection strategy to identify robust RGs, namely ACTB and YWHAZ.

These observed RG alterations are in concordance with recent findings. For example, GAPDH and B2M have been shown to vary according to the sex and age of the mice, and due to specific experimental conditions such as neurodegeneration and denervation status [11]. We now show this variance is also observed according to diet and time of day, and a move away from classic RG which are influenced by these factors should be considered in designing experimental.

Until recently experiments involving heart failure have commonly used GAPDH and 18S ribosomal RNA (18S rRNA) as reference genes [5]. Previous work from our group has shown that RG expression within the hypothalamus of the brain are influenced by a HF diet intervention; hypothalamic GAPDH expression was significantly elevated in high fat-fed mice, whereas ACTB was found to be amongst the most stable [9]. We also show that GAPDH vary in the heart in offspring challenged with a high fat diet at different times of the day. In confirmation, recent studies that have shown changes in GAPDH expression result from undernutrition and hyperinsulinemia [12]. The protein product of GAPDH is a key glycolytic enzyme involved in carbohydrate metabolism (see Table 1). Therefore, GAPDH expression may be responsive to carbohydrate status thus explaining the instability of this RG in such studies involving nutritional interventions. Since suboptimal nutrition and obesity are potential factors in the pathogenesis of heart failure it is likely that inaccurate data may be generated from inappropriate normalisation using RGs such as B2M and GAPDH.

Accurate gene of interest quantification is imperative to prevent erroneous experimental data. It is therefore surprising that 90% of gene analyse studies use only a single RG to normalise gene of interest data [13]. RG are mostly chosen through inappropriate selection strategies, not taking experimental variation into account. Recent studies have highlighted the role of altered circadian rhythms in cardiac physiology. Blood pressure, heart rate and cardiac output have all been shown to express a tightly controlled diurnal rhythm, as have a number of cardiovascular pathologies such as myocardial infarction [14]. Epidemiological studies have shown that individuals with altered sleep wake cycles are at increased risk of developing MetS and CVD risk factors [15]. Therefore, studies exploring the role of circadian physiology in CVD pathogenesis are timely, and at present the underlying molecular mechanisms are beginning to be investigated. We have shown that RG expression does indeed change across a lightdark period and must be considered in the experimental design.

In summary, we found ACTB and YWHAZ to be the most stable RG, not only in heart tissue of high fat fed mice exhibiting features of the human MetS but also across the 24h light-dark period. Therefore, for gene expression studies in metabolic or circadian models, an average of the most stable RGs (YWHAZ and ACTB) would be recommended for the most accurate comparative gene expression data. This study provides important information for reference gene selection, and will aid further transcriptome investigations into MetS, CVD and heart organ function.

This work is funded by the Biotechnology and Biological Sciences Research Council (BBSRC to FRC).