Identification of Optimal Reference Genes for RT-Qpcr in the Rat

Home , PPIB, RPLP0

ORIGINAL ARTICLE Identiﬁcation of optimal reference genes for RT-qPCR in the rat hypothalamus and intestine for the study of obesity

B Li, EK Matter, HT Hoppert, BE Grayson, RJ Seeley and DA Sandoval

BACKGROUND: Obesity has a complicated metabolic pathology, and defining the underlying mechanisms of obesity requires integrative studies with molecular end points. Real-time quantitative PCR (RT-qPCR) is a powerful tool that has been widely utilized. However, the importance of using carefully validated reference genes in RT-qPCR seems to have been overlooked in obesity-related research. The objective of this study was to select a set of reference genes with stable expressions to be used for RT-qPCR normalization in rats under fasted vs re-fed and chow vs high-fat diet (HFD) conditions. DESIGN: Male long-Evans rats were treated under four conditions: chow/fasted, chow/re-fed, HFD/fasted and HFD/re-fed. Expression stabilities of 13 candidate reference genes were evaluated in the rat hypothalamus, duodenum, jejunum and ileum using the ReFinder software program. The optimal number of reference genes needed for RT-qPCR analyses was determined using geNorm. RESULTS: Using geNorm analysis, we found that it was sufficient to use the two most stably expressed genes as references in RT-qPCR analyses for each tissue under specific experimental conditions. B2M and RPLP0 in the hypothalamus, RPS18 and HMBS in the duodenum, RPLP2 and RPLP0 in the jejunum and RPS18 and YWHAZ in the ileum were the most suitable pairs for a normalization study when the four aforementioned experimental conditions were considered. CONCLUSIONS: Our study demonstrates that gene expression levels of reference genes commonly used in obesity-related studies, such as ACTB or RPS18, are altered by changes in acute or chronic energy status. These findings underline the importance of using reference genes that are stable in expression across experimental conditions when studying the rat hypothalamus and intestine, because these tissues have an integral role in the regulation of energy homeostasis. It is our hope that this study will raise awareness among obesity researchers on the essential need for reference gene validation in gene expression studies.

International Journal of Obesity (2014) 38, 192–197; doi:10.1038/ijo.2013.86 Keywords: reference gene; hypothalamus; intestine; RT-qPCR; rat

INTRODUCTION isolation, reverse transcription and real-time PCR. To overcome The worldwide incidence of obesity has led to an increasing need these variables, a reference gene is used for normalizing gene for understanding the molecular mechanisms that drive this expression. However, this assumes that the expression of the epidemic. Obesity is the combined consequence of genetic, reference gene remains constant in all cell/tissue types and under behavioral and environmental factors that drive an imbalance speciﬁc experimental conditions. Unfortunately, increasing data between energy intake and energy expenditure toward an have shown that no single gene has constant expression across all 7–9 increase in adiposity.1 Hormones and peptides secreted from cell types or under all physiological/pathological conditions. adipose tissue and the gastrointestinal tract act as signals Therefore, to obtain accurate gene expression information, it is representing the current energy status to the central nervous imperative that stable reference genes be chosen for the speciﬁc system (CNS).2 The hypothalamus is a particularly important CNS type of tissue and experimental condition. Several algorithms, 9 10 11 region that is responsive to these peripheral signals to initiate including the geNorm, NormFinder, BestKeep and 12 changes in food intake and/or energy expenditure in order to comparative DCt (cycle thresholds) method, have been tightly regulate the overall energy balance.3 Gut-to-brain signaling developed for selection of suitable reference genes and are 13 is also thought to be important for lipid sensing4 and glucose widely used. Recently, ReFinder, a web-based program that sensing.5 Owing to the increase in the frequency and success of integrates four mathematical programs, that is, geNorm, bariatric surgery in the treatment of obesity, attention has turned NormFinder, BestKeeper and comparative DCt, was developed to understanding the mechanisms underlying the gut–brain axis to provide a convenient and adequate means for reference gene 12 in regulating energy homeostasis.6 evaluation. The use of at least three reference genes for the RT-qPCR has become a valuable method for gene expression correct normalization of RT-qPCR data has been proposed by 9 analysis and is used extensively in obesity research. In order to Vandesompele and is a recommended approach for normalizing 9,14 avoid measuring the absolute amount of messenger RNA within a RT-qPCR data. sample, data are analyzed relative to the control group. However, Rodents, such as mice and rats, have been commonly used in errors are introduced in the technique through the process of RNA studying diet-induced obesity and diabetes. Surprisingly, the

Department of Internal Medicine, Division of Endocrinology University of Cincinnati College of Medicine, Cincinnati, OH, USA. Correspondence: Dr B Li, Division of Endocrinology/ Metabolism, Metabolic Diseases Institute, University of Cincinnati, 2170 E. Galbraith Rd., Cincinnati, OH 45237, USA. Email: [email protected] Received 16 December 2012; revised 28 March 2013; accepted 28 April 2013; accepted article preview online 24 May 2013; advance online publication, 25 June 2013 Optimal reference genes for RT-qPCR for the study of obesity BLiet al 193 evaluation of reference genes in obesity research has received To measure the expression values of 13 candidate genes for all tissue types, little attention.15 In most gene expression studies, a single gene, a combination of 13 (genes) Â 4 (tissue types) plate-runs were executed. including ACTB and RPS18, is still commonly used without any The threshold value was manually set to 0.2 to guarantee the mention of whether these genes are affected by the experimental comparability between the Cts obtained from different genes and different conditions.16–18 In other fields, it has been realized that the runs. expression stability of reference genes is influenced by the conditions under which the studies are conducted.19–21 Therefore, Data analysis and statistics we studied 13 commonly used reference genes in the rat The gene expression stabilities of the 13 candidate reference genes from hypothalamus, duodenum, jejunum and ileum across different each tissue were determined by ReFinder. Upon input of Ct values, the diets and feeding schemes typically used in obesity research to ReFinder invokes four commonly used computational programs, geNorm, determine which reference genes would be most appropriate for NormFinder, BestKeeper and the comparative DCt method, to process these particular investigations. We found that the expression those data. The processed ranking results from each program were levels of several commonly used reference genes, such as RPS18 in aggregated by ReFinder to generate gene expression stability rank orders. the hypothalamus or ACTB in the intestine, fluctuated across the On the basis of their rankings from each program, ReFinder assigns an appropriate weight to each individual reference gene and then calculates diet and nutrition conditions we tested. These data underscore the geometric mean of the weights for each gene to reach its overall final the systematic validation of reference genes in obesity research. ranking, the comprehensive ranking order, among all 13 candidate genes. The details of the calculation procedures have been previously described.22 We used the comprehensive rank order in our results. MATERIALS AND METHODS The gene expression stabilities of the 13 candidate genes were analyzed Animals under four separate conditions for each tissue: (1) fasted vs re-fed under chow diet; (2) fasted vs re-fed under HFD; (3) chow vs HFD in fasted Male long-Evans rats were single-housed under controlled conditions condition; and (4) chow vs HFD in fasted then re-fed condition. Twelve Cts (12:12-h light–dark cycle, 50–60% humidity, 25 1C with free access to water from each individual gene were analyzed under each of the four and food except where noted) in the Metabolic Diseases Institute at the conditions described above for each tissue. We also did an overall University of Cincinnati. Rats were fed either a high-fat diet (HFD) (n 12) ¼ evaluation of gene expression stabilities in pooled conditions, in which 24 (Cat #: D03082706; 20% fat (butter fat), 16.6% protein and 52% Ct values of each candidate gene were analyzed for each tissue from carbohydrate, 4.54 kcal g À 1, Research Diets, New Brunswick, NJ, USA) or chow/fasted, chow/re-fed, HFD/fasted and HFD/re-fed animals. chow (Cat #: 7912; 5.8% fat (ether extract), 19.1% protein and 44.3% The optimal numbers of reference genes required for accurate normal- carbohydrate, 3.11 kcal g À 1, Harlan-Teklad, Indianapolis, IN, USA) (n 12) ¼ ization were determined by pairwise variation (V /V ) using geNorm. for 8 weeks before the experiments. All procedures for animal use were n n þ 1 A V value (n ¼ the number of reference genes desired) represents the approved by the University of Cincinnati Institutional Animal Care and Use n/n þ 1 pairwise variation between two sets of reference genes, with the second Committee. set containing an additional gene. A large variation means that the added gene has a significant effect and should be included in normalization Animal groups and tissue collection analyses. To calculate V values, Cts from all candidate genes were input into a geNorm excel-based program. An arbitrary cutoff value of 0.15 for Rats were assigned to one of the four treatment groups (n ¼ 6/group): V is adopted9 to assist the evaluation of optimal gene numbers. For chow/fasted, chow/re-fed, HFD/fasted and HFD/re-fed. All rats were fasted n/n þ 1 example, if V is 0.22 and V is 0.12, then three reference genes are overnight with free access to water and then half of the rats were re-fed for 2/3 3/4 recommended for RT-qPCR analyses. As the V value is 0.12 (less than the 2 h. At the end of the 2-h feed in the dark cycle, all rats were individually 3/4 cutoff value), using four reference genes will not make a significant impact placed in a CO chamber and killed by decapitation. The brain, duodenum, 2 on RT-qPCR analyses. jejunum and ileum were taken quickly and flash-frozen in sub-zero 2- methylbutane and stored at À 80 1C until RNA isolation. RESULTS RNA isolation and cDNA synthesis Transcription profiles of 13 candidate reference genes The hypothalamus was quickly dissected from a semi-frozen brain. Total The expression level of 13 candidate genes (Table 1) was RNA was isolated from the hypothalamus, duodenum, jejunum and ileum using RNeasy mini-columns (Qiagen, Valencia, CA, USA). Genomic DNA was evaluated as the threshold cycle (Ct) in the rat hypothalamus, eliminated by DNase I on column treatment with RNase-free DNase set duodenum, jejunum and ileum that were treated under chow/ (Qiagen). RNA integrity was confirmed by visualizing an approximate 2:1 fasted, chow/re-fed, HFD/fasted and HFD/re-fed conditions ratio of 28S to 18S band on the 1% agarose gel stained by ethidium (Figure 1, for each gene, n ¼ 6/group). These genes were selected bromide. RNA purity was confirmed with absorbance ratio of 42.0 at from an ABI rat endogenous control array gene card (Applied 260 nm/280 nm using NanoVue (GE Healthcare, Piscataway, NJ, USA). One Biosystems). They were chosen because they were routinely used microgram of total RNA was used to generate cDNA using iScript following as reference genes for normalization, and they are expected to the manufacturer’s protocol (Bio-Rad, Hercules, CA, USA). complementary have minimal differential expression across different tissues and DNA was synthesized from all RNA samples for each tissue at the same experimental conditions. time to minimize experimental variations. The Cts across the candidate housekeeping genes ranged from 20.6 to 31.22 in the hypothalamus (Figure 1a), from 19.13 to 32.27 Primers and qPCR in the duodenum (Figure 1b), from 17.97 to 31.51 in the jejunum TaqMan Gene Expression Assays (Applied Biosystems (ABI) (Carlsbad, CA, (Figure 1c) and from 17.98 to 31.67 in the ileum (Figure 1d). The USA)) were used for qPCR. Pre-optimized (with nearly 100% efficiency) wide range of Ct values suggested that these candidate genes had primers/probes of the 13 candidate reference genes (Table 1) were different expression levels in the four tissues examined. Among purchased from ABI. qPCR reactions were set at 10 ml, with 5 ml of TaqMan the 13 candidate genes, ACTB mRNA was the most abundant, Gene Expression Master Mix, 0.5 ml of primer/probe, 2 mlof6Â diluted whereas TBP mRNA was the least abundant in all four tissues. cDNA and 2.5 mlofH2O. Plates were run on the ABI Prism 79000HT Fast Real-Time PCR System (ABI, Carlsbad, CA, USA). All qPCRs were run in duplicate on the same thermal cycles (at 95 1C for 10 min, followed by 40 Gene expression stability analysis of candidate reference genes cycles of 0.01 s at 95 1C and of 20 s at 60 1C). qPCR reactions were set up as follows: 24 cDNA samples per tissue type were prepared from 24 rats: 6 Hypothalamus. When comparing re-fed with fasted conditions, chow/fasted, 6 chow/re-fed, 6 HFD/fasted and 6 HFD/re-fed. qPCR was run the most stably expressed reference genes within the hypotha- using the 24 cDNA samples in duplicate on one 96-well plate for each lamus were PGK1 and B2M in rats fed chow and PGK1 and HPRT in gene. One negative control was also set up in parallel using H2O. Such a rats fed HFD. When comparing chow or HFD, the most stable plate represents a typical reaction setup for one gene per tissue type. reference genes were B2M and ACTB in fasted rats and RPLP2 and

& 2014 Macmillan Publishers Limited International Journal of Obesity (2014) 192 – 197 Optimal reference genes for RT-qPCR for the study of obesity BLiet al 194 Table 1. Candidate reference genes and catalog numbers (ABI)

Symbol Gene name Accession number Function Cat. No.

ACTB Actin, beta NM_031144.2 Cytoskeletal structural protein 4352931E B2M beta-2 microglobulin NM_012512.2 Assembly and surface expression of MHC class I Rn00560865_m1 molecules HMBS Hydroxymethylbilane synthase NM_013168.2 Heme synthesis, porphyrin metabolism Rn00565886_m1 HPRT1 Hypoxanthine NM_012583.2 Generation of purine nucleotides through the purine Rn01527840_m1 phosphoribosyltransferase 1 salvage pathway PGK1 Phosphoglycerate kinase I NM_053291.3 Phosphoprotein glycolyosis Rn00821429_g1 PPIB Peptidylprolyl isomerase B NM_022536.1 Endoplasmic reticulum cyclosporine-binding protein Rn00574762_m1 RPLP0 Ribosomal protein large, P0 NM_022402.2 Protein synthesis Rn00821065_g1 RPLP2 Ribosomal protein large, P2 NM_001030021.1 Protein synthesis Rn01479927_g1 RPL32 Ribosomal protein L32 NM_013226.2 Protein synthesis Rn00820748_g1 RPS18 Ribosomal protein S18 NM_213557.1 Protein synthesis Rn01428915_g1 TBP TATA box-binding protein NM_001004198.1 General RNA polymerase II transcription factor Rn01455648_m1 UBC Ubiquitin C NM_017314.1 Involved in muscle protein metabolism Rn01789812_g1 YWHAZ Tyrosine 3-monoxygenase/tryptophan NM_013011.3 Belongs to the 14-3-3 family of proteins that mediate Rn00755072_m1 5-monoxygenase activation protein, signal transduction by binding to phosphoserine- zeta polypeptide containing proteins

Figure 1. Distribution of the threshold cycle (Ct) values of 13 candidate reference genes. The boxes show the Ct of each gene in the hypothalamus (a), duodenum (b), jejunum (c) and ileum (d). The black center line indicates the median Ct. Samples were pooled from all four conditions: chow/fasted, chow/re-fed, HFD/fasted and HFD/re-fed. Data are presented as mean±s.e.m. (n ¼ 24).

YWHAZ in re-fed rats. When the pooled conditions were HFD. When comparing diets, RPLP0 and HMBS were identified as considered, the reference genes that expressed consistently were the most stable genes in fasted rats and RPLP2 and YWHAZ were B2M and RPLP0. The expression of TBP and PPIB genes was the the most stable genes in fed rats. RPLP2 and RPLP0 were found to most volatile across all conditions in this tissue (Table 2). be the most stable genes under the pooled conditions. ACTB was among the genes with the least stable expression across all Duodenum. In the rat duodenum, when comparing fasted vs conditions (Table 4). re-fed condition, the most stable genes were HPRT and RPLP2 in rats fed chow and HMBS and RPS18 in rats fed HFD. When Ileum. In the rat ileum, when comparing fasted with re-fed comparing diets, the most stable genes were RPLP0 and RPS18 in conditions, HMBS and RPLP2 were identified as the genes with the fasted rats and HMBS and RPS18 in re-fed rats. Under the pooled most stable expression in rats fed chow and RPS18 and RPLP2 conditions, RPS18 and HMBS were found to be the most stably were the genes with the most stable expression in rats fed HFD. expressed genes, and ACTB and PGK1 were among the least stably However, when comparing diets, YWHAZ and RPS18 were found to expressed genes across all conditions (Table 3). be the most stable genes in fasted rats and RPS18 and RPLP2 were the most stable genes in re-fed rats. When the pooled conditions Jejunum. In the jejunum, when comparing fasted with re-fed were considered, RPS18 and YWHAZ were found to be the most conditions, the most stably expressed genes were identified as stably expressed genes, and again ACTB was found to be among RPS18 and HPRT in rats fed chow and HMBS and YWHAZ in rats fed the least stable genes across all experimental conditions (Table 5).

International Journal of Obesity (2014) 192 – 197 & 2014 Macmillan Publishers Limited Optimal reference genes for RT-qPCR for the study of obesity BLiet al 195 Table 2. Rank order of reference gene expression stability in the Table 4. Rank order of reference gene expression stability in the hypothalamus jejunum

Rankinga,b Chow HFD Fasted Re-fed Pooled Rankinga,b Chow HFD Fasted Re-fed Pooled fasted vs fasted vs chow vs chow vs conditions fasted vs fasted vs chow vs chow vs conditions re-fed re-fed HFD HFD re-fed re-fed HFD HFD

1 PGK1 PGK1 B2M RPLP2 B2M 1 RPS18 HMBS RPLP0 RPLP2 RPLP2 2 B2M HPRT ACTB YWHAZ RPLP0 2 HPRT YWHAZ HMBS YWHAZ RPLP0 3 RPS18 ACTB UBC B2M ACTB 3 RPLP13 RPLP0 YWHAZ HPRT HPRT 4 RPLP0 RPS18 RPLP0 RPLP0 HMBS 4 RPLP2 TBP RPS18 RPS18 HMBS 5 ACTB RPL32 HMBS RPS18 UBC 5 UBC HPRT B2M RPLP13 RPS18 6 HMBS B2M HPRT HPRT YWHAZ 6 HMBS B2M RPLP2 HMBS B2M 7 YWHAZ UBC YWHAZ HMBS HPRT 7 RPLP0 RPLP2 ACTB PGK1 YWHAZ 8 HPRT HMBS RPS18 UBC RPS18 8 PGK1 RPLP13 RPLP13 UBC PGK1 9 RPLP2 YWHAZ RPL32 ACTB RPLP2 9 B2M PGK1 TBP RPLP0 RPLP13 10 UBC RPLP0 PGK1 PGK1 PGK1 10 PPIB RPS18 PGK1 B2M UBC 11 RPL32 RPLP2 RPLP2 RPL32 RPL32 11 YWHAZ ACTB HPRT TBP ACTB 12 PPIB PPIB PPIB PPIB PPIB 12 TBP UBC UBC ACTB TBP 13 TBP TBP TBP TBP TBP 13 ACTB PPIB PPIB PPIB PPIB aThe ranking order is the recommended comprehensive ranking by aThe ranking order is the recommended comprehensive ranking by ReFinder. Gene expression stability decreases as the ranking order number ReFinder. Gene expression stability decreases as the ranking order number increases. bTop two ranked genes are in bold. increases. bTop two ranked genes are in bold.

Table 3. Rank order of reference gene expression stability in the duodenum Table 5. Rank order of reference gene expression stability in the ileum

a,b Ranking Chow HFD Fasted Re-fed Pooled Rankinga,b Chow HFD Fasted Re-fed Pooled fasted vs fasted vs chow vs chow vs conditions fasted vs fasted vs chow vs chow vs conditions re-fed re-fed HFD HFD re-fed re-fed HFD HFD

1 HPRT HMBS RPLP0 HMBS RPS18 1 HMBS RPS18 YWHAZ RPS18 RPS18 2 RPLP2 RPS18 RPS18 RPS18 HMBS 2 RPLP2 RPLP2 RPS18 RPLP2 YWHAZ 3 HMBS RPLP2 RPLP2 RPLP2 HPRT 3 RPL32 RPL32 PPIB YWHAZ RPLP2 4 RPS18 RPLP0 HMBS PPIB RPLP2 4 UBC HMBS HMBS RPL32 RPL32 5 RPLP0 RPL32 HPRT RPL32 PPIB 5 RPS18 UBC RPLP2 PPIB UBC 6 PPIB B2M YWHAZ HPRT YWHAZ 6 YWHAZ YWHAZ PGK1 UBC PPIB 7 YWHAZ HPRT RPL32 YWHAZ RPL32 7 PGK1 PGK1 UBC HMBS HMBS 8 UBC YWHAZ PPIB UBC RPLP0 8 RPLP0 PPIB RPLP0 HPRT RPLP0 9 RPL32 PPIB UBC B2M UBC 9 PPIB HPRT RPL32 RPLP0 HPRT 10 TBP UBC B2M TBP B2M 10 HPRT RPLP0 ACTB TBP ACTB 11 PGK1 PGK1 ACTB RPLP0 ACTB 11 ACTB ACTB HPRT PGK1 PGK1 12 B2M ACTB PGK1 ACTB TBP 12 TBP B2M B2M ACTB TBP 13 ACTB TBP TBP PGK1 PGK1 13 B2M TBP TBP B2M B2M a The ranking order is the recommended comprehensive ranking by aThe ranking order is the recommended comprehensive ranking by ReFinder. Gene expression stability decreases as the ranking order number b ReFinder. Gene expression stability decreases as the ranking order number increases. Top two ranked genes are in bold. increases. bTop two ranked genes are in bold.

Optimal reference genes required for normalization that different sets of reference genes suit different experimental 15,19–21 The optimal numbers of reference genes needed for RT-qPCR conditions and different types of tissue. However, no analyses were determined in pooled conditions for each tissue by previous research has identified the most stably expressed reference genes within the rat hypothalamus or small intestine the pairwise variation method (Vn/n 1) using geNorm software. þ under different dietary and feeding conditions for energy Figures 2a–d show that V2/3 values were 0.042, 0.063, 0.079 and 0.052 for the hypothalamus, duodenum, jejunum and ileum, homeostasis studies. Therefore, our study is the first attempt in respectively. As they are all smaller than the recommended cutoff this area to provide first-hand evidence on the necessity of value of 0.15, it indicates that, under the pooled conditions used in reference gene optimization. this study, using two reference genes for normalization would be This study was designed (1) to evaluate gene expression sufficient to obtain accurate data. stability across different dietary conditions among 13 commonly used endogenous control genes and (2) identify the reference genes most suitable for obesity studies that use RT-PCR analysis in the rat hypothalamus and intestine. Our data confirmed that DISCUSSION expression of many of the 13 commonly used reference genes can The concept that reference genes used for normalization in RT- be affected at different levels by both tissues and conditions used PCR analyses should be validated before use was initially in experiments (Tables 2–5). As a result, the ranking order in gene suggested in 200223 and has been realized in various scientific expression stability among the 13 candidate genes from each research disciplines such as plant sciences,22,24,25 cancer,26–28 stem tissue was found to vary across different experimental settings. For cell29–31 and cardiovascular research.32–34 A few data have been example, in the rat hypothalamus and jejunum, there was no published from metabolic research on rodents, which clearly show single pair of reference genes that was stable across all conditions,

& 2014 Macmillan Publishers Limited International Journal of Obesity (2014) 192 – 197 Optimal reference genes for RT-qPCR for the study of obesity BLiet al 196

Figure 2. Pairwise variation (Vn/n þ 1) of 13 candidate reference genes. To derive the numbers of reference genes needed for accurate RT-qPCR, Vn/n þ 1 was calculated using geNorm software by inputting the Ct of each candidate gene from each tissue, the hypothalamus (a), duodenum (b), jejunum (c) and ileum (d). Vn/n þ 1, n ¼ the number of reference genes desired, represents the pairwise variation between two sets of reference genes with the second set containing an additional gene. The cutoff value of V is 0.15.

suggesting that gene expression in these two tissues was more course of obesity development, it is necessary to carefully select susceptible to the changes in experimental conditions. Our studies the reference genes used in RT-qPCR analyses. Unfortunately, in also showed that TBP and PPIB were consistently the least stable studies reported by several groups,35,36,39,40 ACTB was frequently reference genes in the hypothalamus, whereas ACTB was regularly used as the sole reference gene for normalization in RT-qPCR scored among the least stable reference genes in the rat intestine analyses of the hypothalamus and intestine. On the basis of our under all but three conditions (Tables 3–5). findings in this study, the expression of ACTB is one of the least Theoretically, the more the number of genes that are evaluated, consistent in the intestine and can fluctuate quite widely in the the better the chances of finding the most suitable reference hypothalamus (Tables 3–5). Therefore, depending on the experi- genes for the normalization study. However, it would be difficult mental condition, the use of ACTB alone could lead to either over- to screen a large number of candidate reference genes because of or underestimation of the role of the target gene. cost and time restraints. A special issue of the journal Method that In 2011, Lavin et al.41 published a study on the effect of HFD on focused on qPCR in gene expression analyses suggested that a anti-inflammation. In an experiment under conditions similar to preliminary screening of 10 candidate reference genes should that used in our study, the researchers reported that in mice fed be the standard for qPCR analyses and that the candidate an HFD for 10–12 weeks no difference was observed in the reference genes should represent different biological pathways expression of inflammation-related genes such as F4/80, CD11b and have abundant expression levels.23 Thus, our selection of 13 and IL1a between fed and fasted conditions. However, in mice candidate reference genes, which are indeed involved in different fed a low-fat diet, gene expressions of these inflammatory genes biological pathways and have abundant expression levels in the were downregulated in fasted vs fed condition. As their gene four tissues used in our study, meets this standard, and suggests expression analyses were based on a single reference gene, ACTB, that the optimal reference genes we found should be adequate which we now know can vary under the conditions that change for studies examining energy homeostasis. energy homeostasis, their experimental design may have been In our experiment, we used two diets, HFD (D03082706, flawed. Research Diets) and chow (7012, Harlan-Teklad), to maximize the To ensure the data quality of gene expressions, it is differences in caloric load. HFD contains 20% fat (butter fat), 16.6% recommended to use three reference genes in RT-qPCR normal- protein and 52% carbohydrate, with a total calorie of ization studies.9,14 However, because of cost and time constraints, 4.54 kcal g À 1. Chow contains 5.8% fat (ether extract), 19.1% it may not be always feasible to include that many reference protein and 44.3% carbohydrate, with an energy density of genes in an analysis. Our data analyzed using geNorm (Figure 2) 3.1 kcal g À 1. We chose these two diets to maximize differences in indicated that two reference genes were adequate for RT-qPCR the caloric load, but we cannot exclude the possibility that analyses under the experimental conditions we used. Therefore, differences in macro- and/or micronutrient contents between under certain conditions, it would be sufficient to use two carefully these two diets may have influenced the optimal reference gene selected reference genes in RT-qPCR analyses. selection. However, although less ideal, in obesity research it is In conclusion, our study demonstrated that expression of 13 common practice to use diets that are not perfectly candidate reference genes commonly used in obesity research matched.17,18,21,35–38 Thus, we believe that our results provide was differentially affected by dietary and feeding conditions, as valuable information for obesity research. well as by tissue. We have identified that B2M and RPLP0 in the The lack of stability in expression of reference genes in each hypothalamus, RPS18 and HMBS in the duodenum, RPLP2 and tissue across the various laboratory conditions exemplifies the RPLP0 in the jejunum and RPS18 and YWHAZ in the ileum were the complex physiological responses to changes in feeding condi- suitable pairs for normalization study when all four experimental tions. In order to identify accurate gene expression during the conditions (chow/fasted, chow/re-fed, HFD/fasted and HFD/re-fed)

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