ToxSci Advance Access originally published online on August 17, 2006
Toxicological Sciences 2006 94(1):226-233; doi:10.1093/toxsci/kfl082
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Background Gene Expression in Rat Kidney: Influence of Strain, Gender, and Diet
* Toxicology and Environmental Research and Consulting, The Dow Chemical Company, Midland, MI 48674
Analytical Sciences, The Dow Chemical Company, Midland, MI 48674
1To whom correspondence should be addressed at The Dow Chemical Co., 1803 Building, Washington St., Midland, MI 48674. Fax: (989) 638-9863. E-mail: bhaskargollap{at}dow.com.
Received June 13, 2006; accepted August 15, 2006
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ABSTRACT |
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In order to gain better insight into factors (strain, gender, and diet) influencing background variability in kidney gene expression, we examined the transcriptomes of male and female Crl:CD(SD)IGSBR (Sprague-Dawley [SD]) and CDF(Fischer 344)/CrlBR rats maintained for 19 days on three different diets (ad libitum [AL], diet restriction—75% of AL, and casein-based phytoestrogen-free diet). Kidney RNA was analyzed using Agilent Rat oligo microarrays (approximately 20,000 genes). Principal component analysis demonstrated that strain and gender have the most impact on the variability in gene expression, while diet had a lesser effect. The majority of the affected genes differed by a magnitude of four-fold or less between strains/gender, with some previously known to be sex-hormone regulated (SLC22A7 and SLC21A1). One gene of particular interest was ornithine decarboxylase, a significant marker of cell proliferation and tumor promotion, which was expressed at an 18-fold greater level in SD rats. Further analysis revealed that the difference in expression was due to the use of an alternate polyadenylation signal resulting in the production of two different sizes of transcripts. These results demonstrate that gender and strain have significant influence on gene expression which could be a confounder when comparing results, especially when it involves predictive fingerprint/patterns.
Key Words: kidney; microarray; ornithine decarboxylase; gender; strain; diet.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAREFERENCES |
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To ensure the safety of people and the environment, toxicology testing is performed on drugs, pesticides, and chemicals. Many of these tests require the use of rodent models, primarily the rat, to evaluate and establish safe levels of chemical exposure. Potential confounders that influence toxicity study results include effects of animal strain, gender, supplier, diet, and age (reviewed by Kacew, 2001
). Gender differences are primarily due to the specific hormones present in males and females, which cause physiological and protein/gene expression differences that may or may not affect the response to a chemical. Strain effects are at the genetic level which can lead to a strain that is more or less susceptible to a chemical treatment. Often, strains are classified as having some type of susceptibility to a certain toxicity; however, if the appropriate dosage is used most strains will respond with similar effects (Kacew et al., 1995). Fischer 344 and Sprague-Dawley (SD) are the two most commonly used strains of rats for pharmacology and toxicology studies. Fischer 344 is an isogenic strain which has been genetically stable over many generations. On the other hand, the SD rat is an outbred strain and therefore can change genetically over just a few generations (Kacew, 2001).
Another confounder that can have an impact on toxicological studies is diet. There has been a great deal of interest in the area of diet restriction (DR) and its effect on health. DR has been shown to increase life span (Weindruch and Walford, 1982), decrease tumor incidences (Hursting et al., 2003), and alter drug-metabolizing enzymes (Manjgaladze et al., 1993; Stott et al., 2004). It has been observed that over the last 30 years, Fischer 344 and SD rats have had a steady decrease in survival and an increase in the incidence of spontaneous tumors; free choice feeding, ad libitum (AL), has been implicated as a contributing factor for these effects (Keenan et al., 1994; Rao et al., 1990). Therefore, changes in feed consumption alone, from either toxicity or palatability changes of the chemical-containing chow, could influence the results of a study. Another dietary factor that can influence results is the source and composition of macronutrients (soy vs. casein) and micronutrients within the diets. Most commonly used diets are soy based and contain large amounts of phytochemicals, of which many are estrogenic, and have been reported to alter the expression of drug-metabolizing enzymes (Bear and Teel, 2000; Ciolino et al., 1999; Kelly et al., 2000; Ronis et al., 1999). Diet composition has been shown to cause increased incidences of nephrocalcinosis (Clapp et al., 1982) and altered severity of polycystic kidney disease (Meyer et al., 1978; Sondergaard and Blom, 1979).
The work presented here utilizes microarray technology to examine the effect of strain, gender, and diet on gene expression in the rat kidney. To study the effect these factors have on baseline kidney gene expression, Agilent 22K rat oligo microarrays were used to analyze male and female (Agilent, Palo Alto, CA) Crl:CD(SD)IGSBR (SD rats) and CDF(F-344)/CrlBR (Fischer 344, F344) rats on various diets. Rats were placed on AL diet, restricted diet (75% of the average daily ad libitum consumption), or phytoestrogen-free (PF) (casein-based, AL) diet. Here we report that gender and strain have greater influence on kidney gene expression than diet. During the course of this investigation, it was also discovered that the polyadenylation signal usage of ornithine decarboxylase (ODC) is different between SD and F344 rats.
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MATERIALS AND METHODS |
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Chemicals and reagents.
Total RNA Isolation Mini Kit, Rat oligo microarrays, Low RNA Input Fluorescent Linear Amplification Kits, and Hybridization Kits were purchased from Agilent Technologies. Cyanine 3-cytidine-5'-triphosphate (CTP) and cyanine 5-CTP were purchased from Perkin-Elmer/NEN Life Sciences (Boston, MA). RNAlater tissue collection, RNA stabilization solution, and RNA storage solution were purchased from Ambion (Austin, TX). Taqman Reverse Transcription and SYBR Green PCR Core reagents were purchased from Applied Biosystems (Foster City, CA).
Animals.
Five-week-old male and female CDF(F-344)/CrlBR and Crl:CD(SD)IGSBR rats were purchased from Charles River (Raleigh, NC for F344 and Portage, MI for SD). Upon arrival, the laboratory veterinarian evaluated the animals individually for overall health. Animals were housed individually in stainless steel cages in environmentally controlled rooms and provided either PMI Certified Rodent Lab Diet #5002 in meal form or casein-based PMI Certified Rodent Lab Diet #5K96 in pelleted form (PMI Nutrition International, St Louis, MO). Municipal water was provided ad libitum. The study was approved by the Institutional Animal Care and Use Committee of The Dow Chemical Company laboratory for Toxicology and Environmental Research and Consulting and conducted in accordance with National Institutes of Health Guide to the Care and Use of Laboratory Animals guidelines.
Feeding regimen.
Twenty-four hours after arrival, animals were randomized by weight within the respective gender/strains, and then divided into three feeding regimen groups with five rats per group. Group 1, identified as "ad libitum" (AL), was allowed to feed on PMI Certified Rodent Lab Diet #5002 freely without any daily feed intake restriction. Group 2 rats, identified as "restricted" (DR), were also fed the PMI #5002 diet with daily feed intake restricted to 75% of the AL group. Ration levels for the DR group were based on the previous 24-h average food consumption of the AL group. Group 3, identified as "phytoestrogen-free" (PF), was allowed to feed freely on casein-based PMI Certified Rodent Lab Diet #5K96 without any daily intake restriction. The animals were subjected to this feeding regimen for 19 days until the time of necropsy at which time animals were anesthetized with carbon dioxide and exsanguinated by cardiac puncture. Male and female animals were necropsied on different days; however, strain/diet order was maintained to minimize time of day differences. Kidneys were quickly excised, rinsed in ice-cold PBS, and weighed. A single kidney was preserved in five volumes of RNAlater placed at 4°C overnight and then archived at –80°C. Body and relative kidney weights were analyzed by one-way analysis of variance (ANOVA). Any significant findings were analyzed using Tukey's honestly significantly different mean separation procedure.
RNA isolation and microarray screening.
Approximately 10 mg of kidney from individual animals from the respective diet, gender, and strain groups was pooled. Kidney cross sections were taken from the middle region containing both medulla and cortex. Total RNA was isolated using Agilent Total RNA Isolation Mini Kit according to manufacturer's protocol and quantified by spectrophotometry. RNA used for real-time PCR was DNase treated and quantified by spectrophotometry. RNA integrity was confirmed by using an Agilent Bioanalyzer.
Agilent's Low RNA Input Fluorescent Linear Amplification kit was used to generate fluorescently labeled cRNA target for hybridization onto Agilent Rat Oligo 22K (V2) microarrays. SD-male-AL (SD male on AL diet) was used as a reference for all arrays and was hybridized along with all 12 samples on two separate dye swapped arrays (Fig. 1). Labeled cRNA was generated using 2 µg sample RNA or 5 µg of SD-male-AL reference RNA, which was used on all arrays run at that time. For each array, equal amounts of cRNA were fragmented, hybridized, and washed according to the manufacturer's directions. All arrays were scanned and data extracted using an Agilent DNA microarray scanner and Feature Extraction 7.1.1 software, respectively.
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Gene expression analysis.
Extracted data were analyzed using GeneSpring 6.2 software (Agilent) and data were normalized using an intensity-dependent, Lowess (Cleveland and Devlin, 1988
), approach. The cross-gene error model within GeneSpring was utilized to enhance the statistical power of the analysis. After normalization, genes were filtered based on having a signal intensity of 35 or greater and containing no flagged values. This list of genes (10,826) was used to perform principal component analysis (PCA), hierarchical clustering (Pearson's correlation), and further statistical evaluations. To identify gender- or strain-specific gene effects, two-way ANOVA was performed on each diet separately. A multiple testing correction, Benjamini and Hochberg false discovery rate (Benjamini and Hochberg, 1995), was used at a p value of < 0.05. A three-way ANOVA was not performed on the data set because of the limitations in the GeneSpring software. To identify genes having significantly altered expression due to diet, gender and strain combinations (e.g., Fischer male) were evaluated independently utilizing one-way ANOVA (p value < 0.005) followed by post hoc analysis using Tukey test. A different statistical test was employed for identifying diet-specific gene expression changes since few to no genes were identified as being significantly altered in expression when using the false discovery rate parameters employed for gender/strain. The lower alpha value for the one-way ANOVA adequately compensated for the false discovery rate.
Real-time PCR analysis.
Real-time reverse transcriptase–PCR (RT-PCR) was used to verify the results obtained from the microarray analysis. Selected genes were chosen from those that were statistically significant or showed a greater then two-fold change in a gender/strain manner compared to SD-male-AL. RT-PCR primers were either obtained from SuperArray (Frederick, MD) or design using Primer Express Version 2.0 primer design software (PE Applied Biosystems) based on gene sequences obtained from the GenBank database. Primer sets obtained from SuperArray were Cyp2D10, SOD3 (superoxide dismutase), Art, Slc-22A7, Cyp4A12, Cyp2D26, Arg1, Enpp1, Enpp6, ODC (designated ODC-5'), and Cpe (carboxypeptidase E). Primers designed in-house were ODC-CDS (coding sequence), ODC-3', and ODC-5'3' (Table 1). Complementary DNA (cDNA) was synthesized with random hexamer primers and total RNA using a Reverse Transcription kit (PE Applied Biosystems) according to the manufacturer's instructions. RT-PCR was performed using 10 ng of cDNA utilizing a SYBR Green PCR Reagent kit (PE Applied Biosystems) according to the manufacturer's instructions on a Prism 5700 Sequence Detection system (PE Applied Biosystems). All samples were run in triplicate and normalized to GAPDH expression. Normalized threshold cycle values were divided by the value obtained from the SD-male-AL rats to produce final relative fold change. Dissociation curve results were examined to confirm the production of a single PCR product. In Table 5, the values representing amounts of ODC messenger RNA (mRNA) in the kidney were calculated using the relative standard curve method. RNA was diluted to generate the standard RT-PCR curve for ODC using the ODC-3' primers and GAPDH. Each dilution of the target or glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was amplified in triplicate and the mean response for the target gene was normalized to that for GAPDH. Values generated for the target gene of interest that produced a measurable signal in the linear range of the standard curve were used to determine the amount of mRNA present for each condition.
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RESULTS |
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Body and Kidney Weight
The terminal body weights of rats from the three feeding regimens, within each gender/strain combination except SD female, were identified as being significantly different (p < 0.05; Table 2). Groups of rats on DR had statistically lower body weights than either AL or PF fed groups in each gender/strain. Though the terminal body weight of DR SD female rats was not found to be significantly different from that of the other diets, it tended to be lower. However, feeding regimen did not seem to have an effect on relative kidney weight (data not shown).
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Principal Component Analysis (PCA)
To determine which parameter(s) had the most influence on gene expression, PCA was performed using genes considered to be expressed (10,826 genes). Based on the two components identified, representing 75.6% (component 1—65%, component 2—10.6%) of the variance, gender and strain had the most influence on kidney gene expression (Fig. 2). Examining the proximity of the gender and strain clusters on the graph, it appears that gender has the stronger influence on gene expression. Hierarchical clustering (Fig. 3) also reveals that gender and strain have the strongest influence on kidney gene expression and of these, gender has the greater effect. Diet has the least influence on kidney gene expression; however, for both strains of male rats, DR has the most influence on their gene expression based on the distance away from the main gender/strain clusters in PCA. For the females, the PF diet has the greatest effect of the diets on the kidney (Fig. 2).
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(female), 
(male), 
(AL), 
(PF), • (DR).
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Gender- and Strain-Specific Expression
Two-way ANOVA was used to identify gender- and strain-specific genes for each type of diet. Table 3 shows the number of genes that were significantly altered by gender or strain for each diet. For both AL and PF diets, gender caused a greater number of gene expression differences than did strain, whereas DR altered very few genes for either gender or strain. For the PF diet, it is interesting to note that gender had a greater influence than strain on the number of differentially expressed genes. No genes were identified as having significant interaction between strain and gender in the analysis. A full list of gender- and strain-specific genes can be obtained from the supplemental data. A total of 78 strain-specific and 110 gender-specific gene expression changes were identified, and 106 of these have expression levels greater than two-fold compared to SD-male-AL (44 strain-specific and 70 gender-specific genes). Comparison of strain-specific genes across all the diets revealed only three genes in common (ODC and two unknown genes), and for gender-specific genes across the diets only one gene was common. The latter is similar to the mouse gene for prolyl oligopeptidase based on sequence homology. Statistical analysis was performed on data from the three diets for each gender/strain combination revealing very few genes being altered within the context of the number that are identified by chance based on the p value used (data not shown). Supplemental data contain the full list of differentially expressed genes among the three diets.
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Real-Time PCR
Real-time reverse transcriptase PCR (RT-PCR) was performed on several of the genes identified as significantly changed along with a few that were not identified statistically but were altered an average of two-fold or greater (Table 4). Gene expression was analyzed for both gender and strain but only those on AL diet. All the genes that were identified as significantly altered from microarray analysis were confirmed using RT-PCR. However, of the genes tested by RT-PCR that were not statistically identified in the microarray analysis, only two of the four had RT-PCR results indicating altered expression. One of these genes, CYP4a12 was reexamined, since it is known to be regulated by testosterone (Holla et al., 2001
), using new primers with similar results (data not shown). The second gene, Enpp1, had a 2.5-fold decrease in microarray expression in F344 males and females which was not confirmed by RT-PCR.
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Ornithine Decarboxylase
ODC was identified as having significant strain differences in expression from one of two probes on the array (Table 5). Examination of the probe sequences determined that they were both located in the 3'-untranslated region (UTR) of ODC with the nonresponsive probe showing no expression change upstream of the first polyadenylation signal and the responsive probe located between two polyadenylation signals (Fig. 4). RT-PCR analysis using primer sets located in the 5' UTR (ODC-5'), coding region (ODC-CDS), and 3' UTR (ODC-3') between the polyadenylation signals (Fig. 4) revealed that there was relatively no difference between strains at the 5' UTR and coding region, however, the primer set between the polyadenylation signals in the 3' UTR showed a large (> 150-fold) difference in expression between strains (Table 5). The RT-PCR confirms the data seen with the two microarray probes which indicates a differential preference in polyadenylation signal usage between the two strains of rats. To determine if the SD rats were utilizing both polyadenylation signals, quantitative RT-PCR was performed using a primer set just upstream of the first polyadenylation signal (ODC-5'3') and a primer set between the two polyadenylation signals (ODC-3'). In SD rats, the ODC-5'3' primer set detected more ODC mRNA than the ODC-3' primer set (Table 5) which indicates that SD produces both a long and short version of the ODC transcript. Finally, both male and female SD and F344 livers were examined to determine if there was also a differential use in ODC polyadenylation signals. Table 5 shows a similar strain-specific pattern of polyadenylation signal usage in the liver as was seen in kidney along with a gender-specific change.
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DISCUSSION |
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Evaluation of the effects of several common experimental parameters on rat kidney at the transcript level revealed that gender and strain (SD and F344) had the greatest influence on expression, whereas diet had only a minimal effect. It should be noted that the experiments were conducted using age-matched, but not weight-matched rats. Consequently, it is possible that the body weight differences could have contributed to the differential gene expressions observed between the two strains. Alternatively, it is also conceivable that differential expression of critical genes could have contributed to the differences in the body weights observed between the age-matched rats of these two strains. Additionally, since a three-way ANOVA was not performed, it is likely that some interactions among the variables examined might not have been identified. Nevertheless, the PCA (Fig. 2) showed that the three different diets (AL, PF, and DR) tended to cluster together in a gender/strain-specific manner. PCA analysis also revealed that gender has the greatest influence on gene expression relative to strain and diet based on the larger separation between the male and female clusters. The larger influence of gender on gene expression is also demonstrated by hierarchical clustering where both strains of a gender align next to each other (Fig. 2). Not surprisingly, sex hormones can have a great impact on gene expression; however, there are other factors that can also influence gender-dependent differences in gene expression. One example is the gender-specific secretion patterns of growth hormone by the pituitary gland which has been demonstrated in both rodents (Jansson et al., 1985
) and humans (Veldhuis, 1996). It has also been previously demonstrated that strain can have an influence on gene expression in many different species (Sandberg et al., 2000; Walker et al., 2004; Wang et al., 2005). Finally, diet content and number of calories consumed have been shown to alter gene expression in numerous tissues, i.e., muscle and liver (Dhahbi et al., 2004; Manjgaladze et al., 1993; Naciff et al., 2004; Sreekumar et al., 2002). In this study, diet had only a minimal effect on gene expression in the kidney. However, it is interesting to note that PCA indicated that DR in males and PF in females are most dissimilar from AL (Fig. 2). Finally, the larger separation between diets for SD males in the PCA analysis (Fig. 2) is likely an artifact of using SD-male-AL as the reference for all arrays. A more appropriate, less biased reference would have been a commercially available universal RNA reference; however, it is unlikely that the major findings of this paper would have changed. Microarray results were confirmed using RT-PCR which resulted in relatively good concordance across gender and strain except for two genes, CYP4a12 and Enpp1. These genes did show a greater than two-fold change using microarrays but were not statistically identified as altered nor were they confirmed by RT-PCR. The latter findings likely resulted from the primers used. These genes are members of a larger family which share sequence homology and the primers used likely cross-hybridized with other CYP4a or Enpp products that were present. This was further supported by the fact that the fold change seen in the microarray results was consistent across all the diets (data not shown).
Gender and strain expression differences observed corroborate the findings of other researchers using a variety of rat strains. Gender differences have been reported in WKY rats for renal angiotensinogen (Agt) (Ellison et al., 1989), rat renal Oat2 (Slc22a7) which is caused by the female pattern of growth hormone secretion (Buist et al., 2003), and extracellular SOD in smooth muscle cells (SOD3) (Strehlow et al., 2003). CYP2d26 and CYP2d10 both appear to have altered expression in a gender- and strain-dependent manner which is in agreement with what has been seen with CYP2d activity by testosterone in rat brain (Baum and Strobel, 1997) and between Wistar and Dark Agouti strains in renal microsome activity (Masubuchi et al., 1996). Finally, carboxy-peptidase E (Cpe) was shown in our microarray and RT-PCR to have higher expression in females of both SD and F344 strains; however, researchers looking at the pituitary found diethylstilbestrol had no effect on Cpe expression in female SD but decreased Cpe expression in F344 (Gregg et al., 1996). In our study, ODC shows a slight relative increase in both female kidney and liver. In contrast, both in the mouse and rat kidney, ODC expression has been shown to be increased with androgen treatment (Baik et al., 1992; Crozat et al., 1992).
The most significant difference seen was in ODC expression. Renal ODC was discovered to utilize two polyadenylation signals differentially between SD and F344 (Table 5). ODC is the first and rate-limiting step in the conversion of ornithine to polyamines which play essential roles in cell growth, differentiation, and malignant development (Pegg, 1986). ODC enzyme activity demonstrates diverse and rapid changes in response to many growth promoting stimuli to cells, such as drugs, mitogens, hormones, and tumor promoters (Russell, 1985). Due to the importance of ODC and polyamines, the amount and production of ODC protein is regulated at several levels: transcriptional, translational, and posttranslational (Heby and Persson, 1990; Law et al., 1996; Persson et al., 1996). At the translational level, it has been shown that both the 5' and 3' UTRs contribute to this regulation (Grens and Scheffler, 1990; Lorenzini and Scheffler, 1997; Lövkvist Wallstrom, et al., 2001). It has been demonstrated that the hamster 3' UTR can cause a partial release of the inhibitory effect produced by the 5' UTR of ODC (Grens and Scheffler, 1990). Later experiments examined this 3' UTR effect on translation and determined that it did not involve direct interaction with the 5' UTR but rather was mediated by a factor expressed in cells released from serum starvation (Lorenzini and Scheffler, 1997). Therefore, based on this literature, the identification of the differential polyadenylation signal usage between the F344 and SD indicates that a possible difference in ODC translational control between the two strains may exist. This translation difference may only be manifested when the system is perturbed requiring a rapid response at the protein level. It is also interesting to note that humans, like F344, only use the first polyadenylation site (Hickok et al., 1987).
It has been well established that multiple forms of ODC mRNA exist depending on which polyadenylation signal is utilized. Rodents have at least two forms (Berger et al., 1984; Gilmour et al., 1985; Kontula et al., 1984; van Kranen et al., 1987) and humans only have one form representing the use of the first polyadenylation signal (Hickok et al., 1987). The ratio of the large (2.6 kb) and small (2.2 kb) mRNA forms of ODC can differ based on the organ, strain, and/or gender of the rat (Alcivar et al., 1989; Crozat et al., 1992; Longo et al., 1993; Lorenzini et al., 1996; Majesky et al., 1990). In most of these instances, the ratio remains consistent across all time points after some form of treatment. However, in the progression of hepatocellular carcinoma induced by treatment with diethylnitrosamine, there was a change in the ratio between the two ODC mRNAs (Pascale et al., 1993). In the control liver and nodules formed at 10 weeks, the small mRNA is the dominant form. However, in the 30-week nodules and the hepatocellular carcinoma the ratio is about equal between the two forms (Pascale et al., 1993). This change in ratio indicates that there has been some alteration in the control of the polyadenylation signal usage. The purpose of having two transcript sizes of ODC mRNA could be the ability to respond to a stimulus. It has already been shown that the ODC 3' UTR has an effect on translation; unfortunately the difference on translation between the two sizes of 3' UTR has not been determined. Earlier work has shown that two different strains of mice, Mus domesticus and Mus pahari, have very different amounts of ODC protein and activity when induced by androgen but with similar mRNA levels (Johannes and Berger, 1992). Several lines of evidence indicate that this effect is due to a difference in the efficiency of translation. Johannes and Berger (1992) indicated that a 12-base deletion in the 5' UTR may be the cause; however, their analysis by Northern blotting demonstrates a major difference in the ODC polyadenylation signal usage between the two strains. This difference in 3' UTR length could also be contributing to an altered efficiency of translation between the two strains for ODC. An example of a gene that changes its polyadenylation signal usage is eukaryotic initiation factor 2
in response to T-cell activation (Miyamoto et al., 1996). These examples support the possibility that the difference in ODC polyadenylation signal usage may be important during response to various stimuli.
In conclusion, using a PCA approach for microarray data determined that gender and strain have a greater influence on the gene expression in the kidney than did diet. The difference seen in gene expression among these common variables illustrates that caution is needed when identifying genes to comprise fingerprints/patterns for the identification of toxicity and/or chemical classes. Significantly, several of the genes identified could be involved in spontaneous kidney diseases that are seen in a gender/strain-specific manner such as chronic progressive glomerulonephropathy in F344 and nephrocalcinosis in females (Rao, 2002). These strain- and sex-specific gene differences could be useful in identifying a preferred and relevant model for toxicology studies to evaluate hazard and risk to humans. The two strains examined in this study are commonly employed in hazard evaluation studies in laboratories around the world. In particular, it was determined that ODC, a gene essential for cell growth, differentiation, and malignant development, utilizes different polyadenylation signals between the two strains. The potential role of this differential polyadenylation in spontaneous and chemically induced renal tumors remains to be elucidated.
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SUPPLEMENTARY DATA |
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The following supplementary data are available online at http://toxsci.oxfordjournals.org/.
Supplementary Data 1: All statistically significant gender-specific genes with ratio values.
Supplementary Data 2: All statistically significant strain-specific genes with ratio values.
Supplementary Data 3: All statistically significant diet-specific genes with ratio values.
Supplementary Data 4: Full data set with average ratio of dye swapped arrays.
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