Elucidation of various molecular mechanisms, previously unknown, occurred after discovery of the polymerase chain reaction (PCR) method in the scientific community, which has become prominent in numerous research studies involving animal production (Oliveira et al., 2014; Teixeira et al., 2017; Lopes et al., 2020).

The relative quantification of reverse transcription PCR (RT-qPCR) is an accurate and sensitive method to quantify mRNA levels of target genes. However, data processing can affect interpretation of results (Lisowski et al., 2008), being necessary a normalization to correct inevitable experimental variations. The most common method of data normalization is the reference genes, which generally have a relatively stable expression pattern in tissues, since they are required for basic cellular processes (Chapman and Waldenström, 2015). However, it is becoming increasingly apparent that the stability of some usual reference genes can change according to species, tissue types, and experimental conditions (Lisowski et al., 2008; Kaur et al., 2018; Lozano-Villegas et al., 2021).

Therefore, selecting reference genes with less variation has become a requirement for RT-qPCR analysis, and an important factor for obtaining reliable results. If gene expression is normalized with a reference gene that fluctuate under experimental conditions, relevant changes in expression of the target genes can easily be missed or overemphasized (Chapman and Waldenström, 2015).

Various studies have already described selection of reference genes associated with different experimental conditions in bovines and have selected reference genes related to the mammary gland, fat, liver (Saremi et al., 2012; Bonnet et al., 2013), skeletal muscle (Mberema and Sparagano, 2017), somatic cells (Muhaghegh-Dolatabady et al., 2017), blood (Lozano-Villegas et al., 2021), and kidney, pituitary gland, and thyroid (Lisowski et al., 2008). However, there are no studies regarding the reference genes more suitable to muscle, liver, and jejunum in Zebu cattle under nutritional stress.

The hypothesis of this study is that the stability of reference genes differs among genetic groups and diets, and that this may result in errors in analysis of gene expression. Thus, this study aimed to evaluate the stability of candidate reference genes and select the genes that can be used for normalizing RT-PCR in the liver, skeletal muscle, and jejunum tissues of Nellore or Nellore × Angus steers fed different diets.

Levels of gene expression were determined from values of the Quantification cycle (Cq) of the seven reference genes evaluated in the different tissues of the animals, regardless of their genetic group and diets. Simultaneous evaluation of the effect of breeds and diets on muscle, liver, and jejunum tissue (Figure 1) showed that the lowest mean Cq values were 11.9, 11.9, and 13.7 and the highest were 25.7, 27, and 27.4, respectively.

Figure 1

The ranking of candidate reference genes was obtained by the RefFinder program from the geometric mean of the results from the software programs GeNorm, BestKeeper, NormFinder, and Delta Cq. The minimum number of genes for tissues, breeds, and the combination between variables were determined by pairwise analysis by the GeNorm algorithm (Vandesompele et al., 2002). Vandesompele et al. (2002) proposed 0.15 as the cutoff value for the paired variation. After inclusion of the second reference gene, a substantial reduction in the V value (0.15) was observed in GeNorm, showing the need for at least two and at most four reference genes for normalization of the study for the different conditions of this study (Tables 3-5). For the muscle of pure and crossbred animals fed WSC four reference genes were needed (Table 3); on the other hand, for liver (Table 4) and jejunum (Table 5), the minimum number of genes was three.

Table 3

Breed	Diet	Reference gene1
		18S	ACTB	CASC3	EEF1A2	GAPDH	HMBS	UBC
Pure- and crossbred	WSC/WSCB	x	x	x
Pure- and crossbred	WSC	x	x	x	x
Pure- and crossbred	WSCB	x	x	x
Purebred	WSC/WSCB	x	x		x
Purebred	WSC	x	x		x
Purebred	WSCB		x		x
Crossbred	WSC/WSCB	x	x	x	x
Crossbred	WSC	x	x	x	x
Crossbred	WSCB	x	x

PCR - polymerase chain reaction; WSC - whole shelled corn; WSCB - whole shelled corn and sugarcane bagasse.

Table 4

Breed	Diet	Reference gene1
		18S	ACTB	CASC3	EEF1A2	GAPDH	HMBS	UBC
Pure- and crossbred	WSC/WSCB	x	x				x
Pure- and crossbred	WSC	x	x				x
Pure- and crossbred	WSCB	x	x				x
Purebred	WSC/WSCB	x	x				x
Purebred	WSC	x	x				x
Purebred	WSCB	x						x
Crossbred	WSC/WSCB		x			x
Crossbred	WSC		x			x	x
Crossbred	WSCB	x	x				x

PCR - polymerase chain reaction; WSC - whole shelled corn; WSCB - whole shelled corn and sugarcane bagasse.

Table 5

Breed	Diet	Reference gene1
		18S	ACTB	CASC3	EEF1A2	GAPDH	HMBS	UBC
Pure- and crossbred	WSC/WSCB		x	x		x
Pure- and crossbred	WSC		x	x		x
Pure- and crossbred	WSCB		x			x
Purebred	WSC/WSCB	x	x			x
Purebred	WSC		x			x
Purebred	WSCB		x			x
Crossbred	WSC/WSCB		x	x		x
Crossbred	WSC		x	x		x
Crossbred	WSCB		x	x		x

PCR - polymerase chain reaction; WSC - whole shelled corn; WSCB - whole shelled corn and sugarcane bagasse.

The results obtained showed that the ranking (more stable to the less stable gene) for the muscle according to the RefFinder program were Ribosomal Protein 18S (18S), Beta-actin (ACTB), Cancer susceptibility candidate 3 (CASC3), Eukaryotic translation elongation factor 1 alpha 2 (EEF1A2), Glyceraldehyde-3-phosphate (GAPDH), Hydroxymethylbilane synthase mRNA (HMBS), and Ubiquitin C (UBC) (Table 6), being 18S, ACTB, CASC3, and EEF1A2 (Table 3) the most stable genes. The use of CASC3 in purebred animals and of EEF1A2 was expendable in comparing the different genetic groups and diets simultaneously (Table 3). For the liver, the ranking of the reference genes (RefFinder method) was HMBS, ACTB, 18S, CASC3, GAPDH, UBC, and EEF1A2 (Table 7) and the most stable genes were HMBS, ACTB, 18S, and GAPDH (Table 4). In the crossbred animals receiving the two diets or only WSC, GAPDH was more stable than the 18S gene that was selected in purebred animals. Finally, in the jejunum, the most stable reference genes were GAPDH, ACTB, CASC3, and 18S (Table 5), considering that the ranking of the reference genes were GAPDH, ACTB, CASC3, UBC, HMBS, 18S, and EEF1A2 (Table 8). In general, there was a small effect of diet on the reference genes in the tissues.

Table 6

Method	<------- More stable Less stable ------->
	1	2	3	4	5	6	7
Delta Cq	18S	CASC3	ACTB	EEFIA2	GAPDH	HMBS	UBC
BestKeeper	EEFIA2	GAPDH	18S	ACTB	HMBS	CASC3	UBC
NormFinder	18S	CASC3	ACTB	GAPDH	EEFIA2	HMBS	UBC
GeNorm	18S | ACTB		CASC3	EEFIA2	GAPDH	HMBS	UBC
RefFinder	18S	ACTB	CASC3	EEFIA2	GAPDH	HMBS	UBC

Table 7

Method	<------- More stable Less stable ------->
	1	2	3	4	5	6	7
Delta Cq	HMBS	ACTB	18S	GAPDH	UBC	CASC3	EEFIA2
BestKeeper	CASC3	18S	ACTB	HMBS	GAPDH	UBC	EEFIA2
NormFinder	18S	HMBS	ACTB	GAPDH	UBC	CASC3	EEFIA2
GeNorm	ACTB | HMBS		GAPDH	18S	UBC	CASC3	EEFIA2
RefFinder	HMBS	ACTB	18S	CASC3	GAPDH	UBC	EEFIA2

Table 8

Method	<------- More stable Less stable ------->
	1	2	3	4	5	6	7
Delta Cq	GAPDH	ACTB	CASC3	HMBS	18S	EEFIA2	UBC
BestKeeper	UBC	GAPDH	CASC3	ACTB	EEFIA2	18S	HMBS
NormFinder	GAPDH	ACTB	CASC3	HMBS	18S	EEFIA2	UBC
GeNorm	ACTB | GAPDH		CASC3	HMBS	18S	EEFIA2	UBC
RefFinder	GAPDH	ACTB	CASC3	UBC	HMBS	18S	EEFIA2

A reference gene should have expression near the target gene; however, that is not always possible. Thus, the general directives recommend that the Cq values be from 15 to 30 (Wan et al., 2010). In spite of the wide variation found in the Cq of the genes tested (Figure 1), the values found in this study are at the established interval (15 < Cq < 30), except the 18S gene. Although it had very low Cq, the 18S gene was considered stable for muscle and liver according to the RefFinder program.

In addition, other studies have also found a wide variation in Cq in evaluating reference genes in plants or animals under different experimental conditions (Ling et al., 2014; Olias et al., 2014; Robledo et al., 2014; Gentile et al., 2016; Die et al., 2017; Fernandes-Brum et al., 2017).

Some studies have already described the selection of reference genes associated with different tissues and conditions in bovines (Table 9) and showed that the choice of genes is highly dependent on experimental conditions and that most of the studies were carried out with milk cattle and taurine cattle. Saremi et al. (2012) found different reference genes recommended for the liver and muscle tissues of bovines fed conjugated linoleic acid (CLA). Lisowski et al. (2008) evaluated different cattle breeds in different developmental stages and likewise found that two or more reference genes are necessary and that they differ according to the tissue/organ evaluated (liver, kidney, pituitary gland, or thyroid gland).

Table 9

Animal	Tissue	Experimental conditions	No. of genes tested	No. of genes for normalization	More stable genes	Less stable genes	Authors
Bovine	Muscle, mammary gland, and liver	Limousin, Angus, and Blond d’Aquitaine steers and Holstein and Normande cows - difference in physiological status, adiposity, and nutrition	8	3 or more	UXT, EIF3K, and RPLP0	-	Bonnet et al. (2013)
Indian cattle	Blood	Heat stress	11	3	RPS15a, B2M, and RPS9	RPL4	Kishore et al. (2013)
Dairy cattle	Mammary gland, liver, muscle, and fat tissues	Dairy cows supplemented with CLA	7	3 or more	EMD, POLR2A, and LRP10 in the fat tissues and muscle	-	Saremi et al. (2012)
					MARVELD1, EMD, and LRP10 in the mammary gland
					HPCAL1, LRP10, and E1F3K in the liver
Dairy cattle	Milk somatic cells	Lactation stages: early (25±5 d in milk), mid (160±15 d in milk), and late (275±25 d in milk) lactation	9	4	PPP1R11, ACTB, UBC, and GAPDH	RN18S1	Varshney et al. (2012)
Bovine	Longissimus dorsi (skeletal muscle)	20 bovine individuals selected for long- chain omega-3 fatty acids	10	3	EEF1A2, HMBS, and SF3AI	GAPDH, 18S, and RPII	Pérez et al. (2008)
Bull of dairy and beef cattle	Liver, kidney, pituitary gland, and thyroid gland	6-, 9-, and 12-month-old bulls of dairy and beef cattle breeds	6	2 or more	ACTB and TBP in the liver	SDHA and HPRT1 in the liver	Lisowski et al. (2008)
					GAPDH and YWHAZ in the kidney	HPRT1 and TBP in the kidney
					GAPDH and SDHA in the pituitary	ACTB and YWHA2 in the pituitary
					TBP and HPRTI in the thyroid	SDHA and GAPDH in the thyroid
Dairy cows	Mammary gland	During lactation cycle	9	3	UXT, RPS9, and RPS15	ACTB and GAPDH	Bionaz and Loor (2007)

N - Nellore; NA - Nellore × Angus; WSC - whole shelled corn; WSCB - whole shelled corn and sugarcane bagasse; B×D - breed and diet interaction; SEM - standard error of the mean.

Studies carried out prior to publication of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE guidelines) used only one reference gene (Hamalainen et al., 2001; Deindl et al., 2002; Glare et al., 2002) to normalize RT-qPCR data. However, after its publication, the use of two or more reference genes has been recommended to ensure stable expression under all experimental conditions (Bustin et al., 2009). In this study, as a consequence of the data analysis by the GeNorm software, the need for at least two, and up to four, reference genes was shown for normalization of the study for the different breeds and diets studied and for the skeletal muscle, liver, and jejunum tissues. Likewise, Pérez et al. (2008) and Saremi et al. (2012) showed the need for three genes for muscle; and Lisowski et al. (2008) and Saremi et al. (2012) showed the need for two to three reference genes for the liver. However, we did not find studies that investigated the reference genes more suitable for the jejunum of bovines, which is important for studies of gene expression of membrane transport proteins.

A review of literature regarding reference genes in gene expression studies showed that since the publication of the MIQE, the most common choice of reference genes were ACTB (used in 38% of the studies) and GAPDH (37%); the 18S gene (12%) was a little less used in vertebrates (Chapman and Waldenström, 2015). For the tissues evaluated, at least one of the three genes cited above was stable, making them strong candidates for reference genes in studies with RT-qPCR in zebu cattle and their crosses. The ACTB was among the more stable reference genes under all the conditions in this study (Tables 3-5). One of the reasons for this is that ACTIN is the most abundant protein in eukaryotic cells (Nakajima-Iijima et al., 1985). There are at least six ACTIN isoforms in vertebrates: four types in muscle (skeletal, cardiac, vascular smooth, and stomach smooth actins) and two non-muscular types (β-cytoplasmic and γ-cytoplasmic actins) (Vandekerckhove and Weber, 1979), and they are expressed in all types of tissues, as shown in the results of this study, making this gene an optimal normalizer (Tables 3-5).

The EEF1A2 gene was considered the least stable reference gene under most of the conditions studied in the liver and jejunum, and UBC was the least stable in muscle (Tables 6-8). Both are genes expressed under diverse conditions; however, in this study, there was greater variation in relation to the tissues studied. The EEF1A gene has two isoforms, EEF1A1 and EEF1A2, that codify the second most abundant protein (after ACTIN) and catalyzes bonding of tRNA to the ribosomal site. The isoform EEF1A2 is present especially in the brain, heart, and muscle (Lee and Surh, 2009). The expression of this gene in muscle was greater and more stable, with a mean Cq value of 17.6 (Figure 1a), compared with liver (Figure 1b) and jejunum (Figure 1c) tissues, with mean values of 27 and 26.2, respectively. In the latter two tissues, this gene was selected as one of the three least stable (Tables 7 and 8), whereas for muscle, the gene was stable in the purebred and crossbred animals, regardless of the diet fed (Table 6).

In muscle, the UBC gene was highly variable in the breeds and diets studied, and thus, it is not considered a good normalizer for this tissue (Figure 1a). A possible explanation for this is that the gene codifies a protein that participates in selective degradation of short-lived proteins in eukaryotic cells and is involved in immune response and cell development and death (Hershko and Ciechanover, 1998).

Based on the results that show differences in the stability of candidate reference genes, statistical analyses were performed using the more stable and less stable genes found in this study to reveal possible errors in analysis of gene expression of target genes.

Fatty Acid Synthase (FASN) and Acyl-CoA Oxidase 1 (ACOX) are genes involved in synthesis and oxidation of saturated fatty acids, and the protein coded by ACOX is the first enzyme of beta-oxidation of fatty acids in the peroxisomes (Schulz, 1996). The gene FASN, in its turn, codifies the enzyme responsible for the final steps of de novo synthesis of long-chain fatty acids from acetyl-CoA, malonyl-CoA, and NADPH (Ladeira et al., 2016). When the more stable genes were used for normalization of the study (Figure 2), both FASN and ACOX target genes in the muscle tissue were more expressed in WSC diets, and FASN was also more expressed in crossbred animals. However, upon normalizing the data with the less stable genes, statistical differences were not found for the diets studied, and only tendencies were found for the breeds in both genes. Therefore, these results show that the wrong choice of reference genes would lead to misinterpretation and distortion of results.

Figure 2 N - Nellore; NA - Nellore × Angus; WSC - whole shelled corn; WSCB - whole shelled corn and sugarcane bagasse; B×D - breed and diet interaction; SEM - standard error of the mean.

The target gene Stearoyl-CoA Desaturase (SCD1) was evaluated in the liver (Figure 3), and Maltase-Glucoamylase 2 (MGAM) and Solute Carrier Family 2 Member 1 (SLC2A1) in the jejunum (Figure 4). The SCD1 gene is present throughout the organism and is highly expressed in the liver (Ntambi and Miyazaki, 2004). It is responsible for codifying an enzyme responsible for desaturation of long-chain fatty acids, thus acting in regulation of membrane fluidity (Ntambi et al., 1988; Ntambi and Miyazaki, 2004). Evaluation of expression of the SCD1 gene in the liver showed that upon using the more stable genes, statistical effects of the diets and breeds would not be found. In contrast, with the use of the less stable genes, the inclusion of sugarcane bagasse in the diet would increase expression of the gene in the tissue (Figure 3). In the jejunum, the MGAM gene is expressed in the brush border of the small intestine membrane and codifies an enzyme responsible for hydrolyzing maltose into glucose (Mochizuki et al., 2010). Statistical differences were not found in expression of the MGAM gene in the breeds and diets evaluated when the less stable reference genes were used. However, upon using the more stable ones, there was a tendency that the diets containing sugarcane bagasse would result in greater expression of the gene in the jejunum (Figure 4). Finally, the SLC2A1, which is expressed in the enterocytes of the small intestine and codifies the sodium-glucose linked transporter (SGLT1), has its expression similar for diets and breeds, regardless of selection of more stable or less stable genes (Figure 4). In this case, there was statistical difference for diets in both groups of reference genes used as normalizers in this study. However, the relative expression with the use of the less stable genes was much greater, which can also lead to poor interpretation of data by authors.

Figure 3 N - Nellore; NA - Nellore × Angus; WSC - whole shelled corn; WSCB - whole shelled corn and sugarcane bagasse; B×D - breed and diet interaction; SEM - standard error of the mean.

Figure 4

It can be inferred that the choice of reference genes highly affects the results of analyses of gene expression that can occur due to differences brought about under determined metabolic conditions of determined tissues. Thus, there is the possibility of results exhibiting wide variation in gene expression. In the present study, there were few variations in the expression and stability of reference genes among the genetic groups and the diets studied within a specific tissue. However, analysis of the expression of the reference genes among the tissues showed that expressions of GAPDH and EEF1A2 were greater and less stable in muscle compared with the liver and jejunum. Therefore, these genes would likely not be considered ideal for normalization of studies comparing these three tissues.

The more stable genes for zebu animals and their crosses were 18S, ACTB, and CASC3 for muscle tissue; HMBS, ACTB, and 18S for liver tissue; and GAPDH, ACTB, and CASC3 for jejunum tissue, regardless of the breed and diet. Comparison of the more stable and less stable genes as a reference for normalization of target genes shows that the wrong choice of these genes will lead to misleading interpretation of the results.