Literature DB >> 33141822

Whole egg consumption increases gene expression within the glutathione pathway in the liver of Zucker Diabetic Fatty rats.

Joe L Webb1,2, Amanda E Bries1,2, Brooke Vogel1, Claudia Carrillo1, Lily Harvison1, Timothy A Day3, Michael J Kimber3, Rudy J Valentine4, Matthew J Rowling1,2, Stephanie Clark1, Elizabeth M McNeill1,2,5, Kevin L Schalinske1,2.   

Abstract

Nutrigenomic evidence supports the idea that Type 2 Diabetes Mellitus (T2DM) arises due to the interactions between the transcriptome, individual genetic profiles, lifestyle, and diet. Since eggs are a nutrient dense food containing bioactive ingredients that modify gene expression, our goal was to examine the role of whole egg consumption on the transcriptome during T2DM. We analyzed whether whole egg consumption in Zucker Diabetic Fatty (ZDF) rats alters microRNA and mRNA expression across the adipose, liver, kidney, and prefrontal cortex tissue. Male ZDF (fa/fa) rats (n = 12) and their lean controls (fa/+) (n = 12) were obtained at 6 wk of age. Rats had ad libitum access to water and were randomly assigned to a modified semi-purified AIN93G casein-based diet or a whole egg-based diet, both providing 20% protein (w/w). TotalRNA libraries were prepared using QuantSeq 3' mRNA-Seq and Lexogen smallRNA library prep kits and were further sequenced on an Illumina HighSeq3000. Differential gene expression was conducted using DESeq2 in R and Benjamini-Hochberg adjusted P-values controlling for false discovery rate at 5%. We identified 9 microRNAs and 583 genes that were differentially expressed in response to 8 wk of consuming whole egg-based diets. Kyto Encyclopedia of Genes and Genomes/Gene ontology pathway analyses demonstrated that 12 genes in the glutathione metabolism pathway were upregulated in the liver and kidney of ZDF rats fed whole egg. Whole egg consumption primarily altered glutathione pathways such as conjugation, methylation, glucuronidation, and detoxification of reactive oxygen species. These pathways are often negatively affected during T2DM, therefore this data provides unique insight into the nutrigenomic response of dietary whole egg consumption during the progression of T2DM.

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Year:  2020        PMID： 33141822      PMCID： PMC7608885          DOI： 10.1371/journal.pone.0240885

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

Type 2 Diabetes Mellitus (T2DM) is an insulin independent metabolic disease characterized by chronic hyperglycemia and concomitant insulin resistance and it is estimated that greater than 415 million adults worldwide have T2DM [1]. Oxidative stress is a potential key mediator in the pathogenesis of T2DM and may underlie the progressive development of hyperglycemia and insulin resistance [2]. More specifically, reports demonstrate that glutathione (a major intracellular antioxidant) enzymes are diminished in the liver and brain of T2DM animal models [3]. Sekhar and colleagues examined the ability of patients with uncontrolled and controlled T2DM to synthesize glutathione via measuring isotopically labelled glycine [4]. They reported that patients with uncontrolled T2DM were severely deficient in the ability to maintain glutathione metabolism in cardiac tissue [5], which may be, in part, due to hyperglycemia decreasing L-cysteine concentrations [6] and the reduced flux of methionine to cysteine [7]. Because of the deleterious effects of hyperglycemia on organ function, it is important to consider the global transcriptomic effects of T2DM. Similar to humans, the Zucker Diabetic Fatty (ZDF) rat model of T2DM also displays increased oxidative stress [8], whereby endogenous protective antioxidants like glutathione are similarly downregulated in ZDF rats [9]. The gene expression profiles in animal models of T2DM, such as the ZDF rat, is consistent with gene expression profiles of humans with T2DM [8], making this a suitable model to explore the global gene expression effects of diet in the ZDF rat. Dietary treatments with bioactive foods such as cocoa or Shenyuan granules [9, 10] in ZDF rats have been shown to reduce oxidative stress or attenuate renal injury in the presence of T2DM-related nephropathy [11]. Consumption of eggs as a bioactive food during T2DM in humans remains controversial [12-15], but eggs have been shown to display antioxidative properties, which may be beneficial during the progression of T2DM [16]. Additionally, our laboratory has consistently reported that long-term whole egg (WE) consumption improves metabolic parameters during T2DM such as the maintenance of circulating vitamin D concentrations, decreased weight gain, and nephroprotection via reduced proteinuria in male ZDF rats [17, 18]. These are important findings, as vitamin D deficiency, increased adiposity, and kidney failure have collectively been suggested to exacerbate oxidative stress during T2DM [19]. While the literature surrounding the effects of dietary WE on insulin resistance during T2DM is inconclusive in both rodent [20] and human population studies [21], there are no studies to date examining the molecular mechanisms underlying how WE consumption affects the transcriptome across multiple tissues. Longitudinal, prospective, and comprehensive meta-analyses have been performed to assess the independent risk factors of increased dietary egg consumption on chronic diseases [22, 23]. Because of the highly controversial science of whole egg consumption on increased cardiovascular disease in patients with T2DM, it is important to examine the possible underlying molecular targets and drivers of whole egg consumption on disease. Ultimately, analyzing the transcriptomic impact of egg consumption would provide us with a better understanding of the nutrigenomic actions that dietary egg consumption contributes to T2DM, and bridge the gap in our understanding of how whole eggs may affect the physiological progression of T2DM. Therefore, the objective of this study was to determine the influence of WE consumption on gene and microRNA expression profiles in a ZDF rat model of progressive T2DM. We examined the transcriptomes from the adipose, liver, kidney, and prefrontal cortex (PFC) tissues to determine how WE consumption alters gene expression and examined whether these changes correspond to altered microRNA expression profiles in T2DM.

Results and discussion

Whole eggs have predominantly been criticized for their associated risk of developing chronic diseases [24], yet the benefits of WE consumption have also been reported [13]. For instance, several groups have suggested that WE provide antioxidant properties [13, 25], either through antioxidant peptides in the egg yolk [11] or other reactive oxygen species-reducing nutrients [26]. Other studies examining the role of quail egg consumption in rat models of T2DM have demonstrated upregulation of glutathione metabolism in alloxan-induced T2DM in Wistar rats [25] and improved oxidative stress profiles in streptozotocin-injected rats [27]. Raza and colleagues [27] identified that in diabetic rat liver glutathione content and glutathione S-transferase (GST) activity were decreased 65% while also observing that brain glutathione and GST activity were increased two-fold as a result of a T2DM phenotype.

Total RNASeq differential expression

When comparing the WE versus casein (CAS) in ZDF rats and their lean controls, differential expression analyses of the mRNAseq data resulted in 583 differentially expressed genes (DEGs) across four tissues in both genotypes (. contains the results from DESeq2 with the results for each gene across all four tissues with data on individual genes. contains raw mRNA read counts for each tissue and rat across both genotypes. Among the lean controls, 13 genes were differentially expressed in the adipose tissue, 32 in the liver, and 6 in the kidney. Notably, none of the genes were differentially expressed in the PFC between dietary treatments in the lean rats. In the ZDF rats, dietary WE consumption resulted in 532 total DEGs across all tissues where 50 genes were differentially expressed in adipose tissue, 474 in the liver, 6 in the kidney and 2 genes in the PFC following multiple testing correction using the false discovery rate (FDR) threshold of 5%. We demonstrated that consuming WE-based diets for 8 wk resulted in significant alterations in oxidative stress pathways, as well as glutathione metabolism pathways. While there were tissue-specific changes in gene expression, glutathione metabolism was altered in the kidney and liver among ZDF rats, and in the kidney of lean controls were significantly upregulated. Overall, these data highlight how consumption of WE-based diets can provide beneficial effects through modifying gene expression of oxidative reduction targets. 1All genes were analyzed using DESeq2 for differential analysis. 2Abbreviations used: ZDF, Zucker Diabetic Fatty; L2FC, log2 fold change; PFC, prefrontal cortex. 3 Benjamini-Hochberg adjusted P-values controlling for false discovery rate at 5%, where P< 0.05 was considered significant. We previously demonstrated that WE consumption for 8 wk is effective at improving serum vitamin D status and providing nephroprotective benefits [17, 18]; however, despite our gene expression findings in this study we still have yet to elucidate the mechanism underlying how WE consumption leads to decreased weight gain [28, 29]. We also identified that ZDF rats fed WE upregulated 11 genes involved in glutathione metabolism in the liver and kidney. In the PFC, WE consumption had differing effects whereby in the lean PFC, WE consumption did not change the transcriptome, whereas in the ZDF rats WE consumption strongly downregulated the expression of 2, AY172581 exon transcripts. These exon transcripts have yet to be characterized and future proteomic studies may reveal their biological importance. Across both genotypes, the most significantly altered genes were involved in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of: glutathione metabolism, metabolic pathways, steroid biosynthesis, and cholesterol metabolism. After controlling for the genetic background differences of our ZDF rats, a combined analysis indicated that 428 unique genes were differentially expressed across these tissues as a product of WE consumption. Moreover, 13 different glutathione metabolism genes were significantly upregulated across the liver and kidney in both genotypes suggesting that increased whole egg consumption, may increase glutathione metabolism independent of T2DM, and attenuate the decreased glutathione metabolism during diabetes. To visualize the global differences in the transcriptomes based on dietary treatment, we performed principal component analysis (PCA) and generated volcano plots for genes that exhibited ≥1.5-fold change, respectively. displays the samples in a three-dimensional principal component space, whereby samples are colored in red or black to distinguish either WE or CAS, respectively. In the mRNA samples, rats on the same dietary treatment (i.e. black or red) clustered together, while animals belonging to different dietary treatments separated, indicating distinctly different patterns across global mRNA expression. These results were further visualized using volcano plots for each tissue as presented in These volcano plots demonstrate the degree to which genes were upregulated or downregulated across each tissue. For instance, volcano plots indicate a relatively equal number of upregulated and downregulated genes in the lean PFC following WE consumption, whereas WE consumption primarily resulted in downregulated gene expression in the ZDF PFC.

Principle component analysis.

Samples in the first three principle component space are colored in red or black for either WE or CAS, respectively. Each panel displays PCA results using microRNA data or mRNA data are colored by dietary treatment groups with A) ZDF microRNA, B) ZDF mRNA, C) lean microRNA, D) lean mRNA.

Volcano plots.

Genes upregulated (green) or downregulated (red) by WE consumption, correspond to a 1.5 decrease or increase in log fold changes. Each panel corresponds to a tissue in a given genotype: A) lean adipose; B) lean PFC; C) lean kidney; D) lean liver; E) ZDF adipose; F) ZDF PFC; G) ZDF kidney; and H) ZDF liver. During T2DM, reports indicate that genes within the oxidative stress-related pathways upregulated [26]. Evans et al. suggested that oxidative stress was driven by the hyperglycemic environment concomitant with increased concentrations of free fatty acids in the plasma [26]. Corbett et al. [30] reported that protective antioxidant genes such as glutathione peroxidase are downregulated during T2DM, and both glutathione s-transferases (GSTs) and glutathione-dependent enzymes are important in the regulation of pathophysiological alterations in numerous chronic diseases, especially T2DM [30]. Previous work has shown that dietary intervention with direct glutathione supplementation was protective against diabetic nephropathy in an insulin dependent streptozotocin-induced T1DM model [27]. This current study provides new transcriptomic evidence supporting our previous report demonstrating that WE consumption protects against diabetic nephropathy, where WE consumption leads to altered gene expression in the kidney. In this study, we noted that the strongest alterations in glutathione metabolism were in the liver, potentially because hepatic glutathione is produced at much higher concentrations (10 mM), whereas intracellular glutathione concentrations are approximately 1–2 mM [31]. This body of previous work is important in relation to our findings that several GSTs and glutathione-dependent enzymes are significantly altered during WE consumption in lean controls and during diabetes in the kidneys and livers across both genotypes. Future mechanistic studies identifying the beneficial impact of these two enzymes in chronic diseases like T2DM are warranted. Outside of the glutathione pathways, we also observed that there were significant differences in early growth response-1 (Egr-1) gene expression following WE consumption. Egr-1 has been implicated in the onset of insulin-resistance, as previous studies in insulin-resistant T2DM mice identified that loss of function in Egr-1 restores insulin sensitivity via increased phosphorylation of the insulin receptor substrate-1 tyrosine kinase [32]. Notably, we observed a 30% decrease in hepatic Egr-1 expression in the ZDF rats fed WE. This is an interesting finding as research by Garnett et al. [33] determined that exposing beta cells to hyperglycemic conditions resulted in a temporal and dose-dependent increase in Egr-1 transcription and translation. Furthermore, Egr-1 null mice are known for their inability of displaying diabetic and obese phenotypes [34] owing to their increased energy expenditure. These data suggest that consumption of WE may lead to altered Egr-1 expression which may play a key role in regulating energy expenditure. We also demonstrated that WE consumption resulted in tissue-specific alterations in gene expression and that there were distinct transcriptomic differences between genotypes. WE consumption did not influence gene expression in the PFC of lean animals, while 2 genes were significantly altered in the ZDF PFC. There were more stark differences when comparing the liver tissues between the two genotypes, where more than 400 genes were altered in ZDF livers that were not altered in the liver of lean controls. It has been shown that T2DM impacts a variety of tissues [1] but previous studies have provided very little evidence of how T2DM alters the nutrigenomic responses to foods in specific tissues. It is still unknown which specific egg components lead to phenotypic differences in gene expression and future studies should focus on identifying the specific egg constituents that mediate these gene expression differences. These collective findings are likely mediated through the alteration of several genes; therefore, we aimed to further examine microRNA changes involved in the underlying progression of T2DM during WE consumption.

MicroRNA sequencing differential expression

We examined if endogenously expressed microRNA profiles in the adipose, liver, kidney, and prefrontal cortex tissues would be altered following 8 wk consumption of dietary WE. Differential expression analyses of the ZDF microRNA data resulted in 1 differentially expressed microRNA in the adipose tissue, none in the liver, none in the kidney and 2 in the PFC that surpassed multiple testing correction. Among the lean rats, there were 2 marginally differentially expressed microRNAs in the adipose tissue, 4 in the liver, none in the kidney and none in the PFC that survived multiple testing correction. presents the differentially expressed microRNAs in the adipose, liver, kidney, and PFC tissues across both genotypes. contains results from DESeq2 with the results for each microRNA across all four tissues and raw microRNA read counts are contained in . 1All miRNAs were analyzed using DESeq2 for differential analysis. 2Abbreviations used: ZDF, Zucker Diabetic Fatty; WE, whole egg; CAS, casein; L2FC, log2 fold change; and PFC, prefrontal cortex. 3Benjamini-Hochberg adjusted P-values controlling for false discovery rate at 5%, where P< 0.05 was considered significant. Based on the microRNA sequencing analysis, 9 microRNAs were differentially expressed following multiple testing correction. Several of these microRNAs have been previously correlated with gestational diabetes or show to be altered in the plasma of individuals with diabetes. Very few studies to date have examined the tissue-specific changes of endogenous microRNA expression in response to dietary patterns and this is the first study to demonstrate that endogenous microRNA expression in the liver, adipose, and PFC can be altered following 8 wks of WE consumption. Future studies should focus on identifying if similar foods such as quail eggs alter microRNA expression in these tissues and determine the smallest effective dosage of egg required to recapitulate these changes in microRNAs.

Mapping between microRNAs and target genes

Next, we sought to determine if these significantly altered microRNAs were responsible for the tissue-specific differential expression of their predicted target genes. MicroRNA mapping analyses of the differentially expressed microRNAs and their target genes demonstrates that in each of the tissues with differentially expressed microRNAs, key target genes of these microRNAs were altered. For instance, in the lean liver microRNA-181a-3p was upregulated and two of its mRNA target genes were differentially expressed, Cytochrome P450 Family 7 Subfamily A Member 1 (Cyp7a1) and stearoyl-CoA desaturase (Scd). Similarly, in the lean adipose, microRNA-125b-5p was downregulated while its target gene phosphoglycolate phosphatase (Pgp) was upregulated. The microRNAs in the PFC and kidney tissue did not map to any differentially expressed genes. summarizes the mapping between microRNAs and their gene targets. 1All miRNAs were analyzed using DESeq2 for differential analysis. 2Abbreviations used: miR, microRNAS; rno, rattus norvegicus; WE, whole egg; and L2FC, log2 fold change. 3Gene targets for Rattus Norvegicus and humans were determined by DRSC Integrative Ortholog Prediction Tool. While examining the relationship between significantly altered microRNAs and their target genes, we identified that in the livers of lean rats fed WE, the upregulated microRNA-181a-5p affected target genes involved in steroid hormone biosynthesis such as Cyp7a1 and Scd. Notably, only Cyp7a1 was upregulated in the liver of ZDF rats fed the WE-based diet while both Scd and Cyp7a1 were upregulated in the livers of lean control rats. In rodent models of diabetes, liver expression of Cyp7a1 has been shown to be decreased and thought to play a key role in regulating whole body energy homeostasis [35]. Similarly, transgenic mice overexpressing Cyp7a1 were shown to become resistant to weight gain and fatty liver disease [35]. Experiments examining the role of Scd in rat hepatocytes has demonstrated that Scd expression regulates hepatic insulin resistance during diabetes [36], but very few studies have determined the expression of Scd genes in the context of dietary consumption. Based on the data, WE consumption more strongly upregulated hepatic expression of Cyp7a1 in ZDF animals than in the lean controls and this might suggest that WE consumption can prevent or reverse the loss of hepatic Cyp7a1 expression due to diabetes. In our lean rats, we also identified that microRNA-125b-5p was downregulated in adipose tissue where its gene target Pgp was strongly upregulated. Pgp is known to hydrolyze glycerol-3-phosphate into glycerol, and overexpression experiments in rodents showed that upregulation of Pgp leads to a reduction in body weight gain and improves hepatic glucose regulation [37]. Additionally, we observed the upregulation of liver microRNA-9a-5p, which has been correlated with gestational diabetes in humans [38]. While the gene targets of microRNA-9a-5p were not differentially expressed in the liver, future studies should look into whether endogenous microRNA expression fluctuates in response to consuming other eggs, such as quail eggs, or egg yolk alone.

KEGG and GO functional enrichment analysis

To further examine the molecular function of the identified DEGs, KEGG pathway analysis indicated that the most prevalent pathways influenced by dietary WE across multiple tissues in the ZDF rats were: glutathione metabolism; oxidation-reduction; metabolism of xenobiotics; steroid hormone biosynthesis; and fatty acid synthesis pathways. In the livers of lean control rats, the most significantly expressed pathways included metabolic pathways and retinol metabolism. All the differentially expressed genes that map to KEGG and gene ontology (GO) pathways analyses are presented in To further investigate the specific genes involved in the glutathione metabolism pathways, genes were categorized into the corresponding reactions identified by Reactome.org in Glutathione metabolism functions in antioxidant defense, signal transduction, cytokine production, and other cellular processes such as detoxification. The role of GST, GSTK, GSTO dimers, and GPX1 which function in glutathione conjugation, glucuronidation, methylation, and detoxification of reactive oxygen species, respectively, are detailed within . These reactions within glutathione metabolism are essential for recycling of glutathione disulfide or the conjugation of GSH that can be utilized in redox reactions.

Differentially expressed genes involved in glutathione metabolism.

This figure was adapted from D’Eustachio, P., and Jassal, B. from the Reactome [39]. Glutathione metabolism reactions can be categorized into glutathione conjugation, glucuronidation, methylation, or detoxification of reactive oxygen species. All genes are listed within each reaction category followed by their corresponding log2fold change in parentheses for each given tissue. Abbreviations used: ZDF, Zucker Diabetic fatty rat; GSSG, glutathione disulfide; GSH, glutathione; AS3MT, arsenite 3-methyltransferase; AdoMet, S-adenosyl methionine; AdoHcy, S-adenosyl homocysteine; CDNB, 1-chloro-2, 4-dinitrobenzene; DNPSG, S-(2,4-dinitrophenyl)glutathione; glu, glutamate; cys, cysteine; gly, glycine; gGluCys, gamma-glutamyl-L-cysteine; GST, glutathione s-transferase; and GPX, glutathione peroxidase. KEGG pathway analysis highlighted that in addition to an upregulation of glutathione metabolism pathways, several of the same gene products mediate metabolism of xenobiotics, a pathway upregulated in our rats fed WE-based diets. Xenobiotic metabolism has previously been shown to be downregulated during insulin dependent T1DM [27], where in this study these pathways were upregulated in response to feeding WE-based diets. These observed effects appear to be tissue specific, as these alterations were the most prominent in ZDF liver, whereas one gene, glutathione s-transferase p (Gstp1), was differentially upregulated in the kidney of ZDF rats while glutathione s-transferase mu 1 (Gstm1) was upregulated in the lean kidney. These findings support the previous observation that WE consumption affects obese phenotypes differently than a lean phenotype [17], in part, due to the different transcriptomic responses to dietary WE. We previously hypothesized that these differences in response to WE consumption were not due to satiety, because there was increased food intake in the WE group [18]; the present study identifies a potential molecular response to egg partially explaining these previous findings. Other suggested mechanisms that might explain differences between obese and lean genotypes include thermogenesis [40], altered methylation patterns [41], intestinal microbiome alterations [42], and changes in energy expenditure [43]. While there have been numerous studies highlighting differences in the microbiota between obese and lean phenotypes in rats [42] and humans [40], one recent study examining WE consumption concluded that it did not influence the intestinal microbiome in postmenopausal women [44]. Taken together, these observations support the idea that phenotypic alterations during T2DM may depend strongly on obesity status and energy expenditures on a molecular level, potentially in response to changes in the transcriptome.

qPCR analyses

Finally, we examined the relationship between our qPCR data for several genes to validate the results from the Quantseq analysis. Confirmatory analysis with qPCR demonstrated that across the genes selected, the qPCR data highly correlates with the mRNA Quantseq results (R2 = 0.72; ) indicating strong similarities between these two methods.

Strengths and limitations

The strengths and limitations of this study should be addressed to better understand how these results fit into the larger context of the current literature. It is estimated that in 2019, people in the United States consumed on average, 5.6 eggs per week [45]. The dose of egg used in this study would equate to roughly 14 eggs per day for a human. While our study demonstrated that consuming a large dose of WE may alter gene expression of various metabolic pathways, particularly during T2DM, this quantity of egg would not be a standard dietary practice in humans. We do recognize that our whole egg dosage was high, but the goal was to examine whether there was a transcriptomic response from consuming dietary whole egg in a T2DM model. It is worth noting that our laboratory has previously reported in ZDF rats that even smaller dosages, such as the human equivalent of <2 eggs/day, significantly reduced weight gain in the ZDF rat and therefore may be effective in identifying oxidative stress outcomes from long-term dietary whole egg consumption [18]. After the examination of the transcriptome following our high WE-based diet, it is warranted to examine these specific genes in a follow-up intervention study. Future studies will focus on titrating down the egg dosages to discern the smallest dosage to elicit similar transcriptomic responses to egg consumption that will be more translatable to human consumption patterns. Overall, our findings are significant as we are the first to report that whole hen egg consumption promotes glutathione metabolism expression during T2DM and alters the transcriptome of multiple tissues using next-generation sequencing. Additionally, we provide evidence supporting the idea that egg consumption modifies endogenous microRNA expression in a tissue-specific manner. In summary, we examined whether feeding WE modifies expression of microRNAs or gene expression profiles across multiple tissues in a diabetic versus a lean rat model. Across all tissues examined with next generation sequencing, we identified that 9 microRNAs were differentially expressed in response to consuming WE. Additionally, we have shown that these microRNAs were related to tissue-specific changes in gene expression, and that 8 wk of consuming diets high in whole egg modified 583 genes across the PFC, kidney, liver, and adipose tissue. KEGG/GO analyses identified that glutathione metabolism was highly upregulated in response to feeding WE and qPCR results validated the sequencing results. These data suggest that high WE consumption may provide beneficial effects during T2DM by improving glutathione metabolism gene expression across multiple tissues and decreasing gene expression in oxidative stress pathways.

Materials and methods

The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus [46] and are accessible through GEO Series accession number GSE157491 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE157491). All protocols used within this study have been made publicly available at protocols.io. Protocols have been zipped into one file and can be accessed at dx.doi.org/10.17504/protocols.io.bjgakjse.

Animal housing and experimental design

This animal study was approved by the Institutional Animal Care and Use Committee (IACUC) at Iowa State University. All animal care was performed according to Laboratory Animal Resources Guidelines at Iowa State University. Male ZDF (fa/fa) rats (n = 12) and their lean controls (fa/+; n = 12) were obtained at 6-wk of age (Charles River, Wilmington, MA). Rats were dual-caged and acclimated for 72 h in conventional cages in a temperature-controlled room (25°C) with a 12-h light-dark cycle. Rats were randomly assigned to an experimental diet ( consisting of either a casein (CAS)-based diet, or a WE-based diet containing dried WE powder (Rose Acre Farms). 1All ingredients were purchased from Envigo except for dried whole egg (Rose Acre Farms, Guthrie Center, IA), as well as l-methionine and choline bitartrate (Sigma-Aldrich). Abbreviations used: CAS, casein-based diet, WE, whole egg-based diet. 2 Total protein and lipid content provided by 435 g of dried WE was 46% (200 g) and 42% (183 g), respectively. 3 To formulate all diets such that protein was provided at 20% (w/w). Both diets provided 20% protein (w/w) from either vitamin-free CAS or WE powder. To match the diets for total lipid content (18.3%), corn oil was added to the control diet. Both diets were prepared in-house weekly by mixing all ingredients into a powdered form and administered daily in a standard amount for both lean and ZDF rats. For the remainder of the study, rats were fed ad libitum for 8 wk and at the end of the experimental period, rats were anesthetized with a dissociative agent combination of ketamine:xylaxine (90:10 mg/kg body weight) via an intraperitoneal injection of 1μL/g body weight. Two methods of animal euthanasia were performed according to the American Veterinary Medical Association guidelines for the Euthanasia of Animals: 2020 edition [47]. Cardiac exsanguination of whole blood on the anesthetized rat was performed and serum was subsequently stored at −80°C for downstream analysis. The second method of exsanguination was the procurement of organs. Following cardiac puncture, tissues were immediately excised, weighed, and snap frozen in liquid nitrogen for storage at −80°C in RNALater.

RNA extraction and analysis

Tissue samples (20 mg) were rapidly thawed on ice and largeRNA and smallRNA fractions were extracted from the same isolate using the RNA SPLIT Kit (Lexogen) according to the manufacturer’s instructions. Briefly, samples were homogenized in an isolation buffer and phase separated using a phenol/chloroform extraction followed by a spin column-based purification procedure. All samples were aliquoted and stored at −80°C for downstream analysis. Following extraction, sample concentrations for the largeRNA fraction were analyzed using a Qubit 2.0 fluorometer (Thermo Fisher) using the Qubit™ Broad Range RNA Assay Kit. RNA integrity was assessed using the Bioanalyzer 2100 (Agilent Technologies) and samples with low RNA integrity number (RIN) values <5 were discarded and re-extracted. SmallRNA concentrations were measured using a Qubit 2.0 fluorometer (Thermo Fisher) using the Qubit™ microRNA Assay Kit.

TotalRNA and smallRNA sequencing

Libraries for totalRNA were prepared using an automated protocol according to the manufacturer’s instructions for half reactions on the QuantSeq 3' mRNA-Seq Library Prep Kit (Lexogen) using a MANTIS® Liquid Handler pipetting robot (Formulatrix). All totalRNA samples were multiplexed together across two lanes on an Illumina High-Seq 3000. SmallRNA Libraries were prepared manually using the SmallRNA-Seq Library Prep Kit (Lexogen). Briefly, 100 ng of enriched smallRNA was used as input and 3’ and 5’ adapters were ligated followed by column purifications. Subsequently, the ligation products were reverse transcribed and double stranded cDNA libraries were generated. Finally, individual sample barcodes for multiplexing were introduced via 17 cycles of PCR. All libraries were assessed on the Bioanalyzer 2100 (Agilent) to examine if adapter dimers formed during PCR. All libraries were further prepared using a bead purification module (Lexogen) and pooled into a single sample at 2 nM (20 μL reaction) for sequencing.

Sequencing quality control and adapter trimming

For both totalRNA and smallRNA samples, the resulting FASTQ files were analyzed using Fast-QC [48] and sequencing adapters were trimmed using on BBDUK [49] with an example of the trimming procedure: bbduk.sh in = reads.fq out = clean.fq maq = 10 ref = /bbmap/resources/adapters.fa. For smallRNA samples, reads were additionally trimmed using the literal flag to remove the Lexogen specific sequence “5’-TGGAATTCTCGGGTGC CAAGGAACTCCAGTCAC– 3’” following similar trimming procedures. Briefly, any read segments that matched Illumina Truseq or Nextera adapters, along with reads containing integrity scores <10 were trimmed out.

Alignment and read quantification

For totalRNA, reads were mapped to the Ensembl release 94 of the Rattus Norvegicus RNO_6.0 genome using RNA STAR [50]. TotalRNA read counts were generated during the read alignment using the—genecounts function in STAR. For smallRNA samples, reference fasta files from www.RNACentral.org were downloaded for microRNA, piwiRNA, snRNA, nRNA, rRNA, and tRNA. Indexes were generated using Bowtie [50] and alignment was conducted using the smallrnaseq python tool [51]. Read counts for all reference indices and IsomiRs were generated using the smallrnaseq python tool.

Data filtering and normalization

Following read count generation, Quantseq gene expression data was merged into a single data frame for analysis in R (version 3.6.0). Genes were discarded from the analysis if there were <3 samples without a single read for that given gene. TotalRNA data initially generated read counts for 32,883 genes and over 50% of the trimmed reads from each sample mapped to the RNO_6 version 94 genome. Prior to normalization, remaining gene counts across all four tissues contained between 8,700–12,000 genes for analysis. The microRNA data originally generated read counts for over 350 microRNAs and the formal analysis was conducted on 60–150 targets across each tissue. For totalRNA and smallRNA fractions, all samples were normalized using the Trimmed Mean of M values (TMM) method [52]. Briefly, TMM accounts for variable depth between samples by normalizing them according to the weighted trimmed mean of the log expression ratios across all samples prior to analysis.

Differential expression analysis

All differential expression analyses were conducted using R (version 3.6.0). Differential expression was conducted using DESeq2 from Bioconductor. DESeq-DataSetFromMatrix generated p-values and Benjamini-Hochberg [53] adjusted P-values controlling false discovery rate (FDR) at 5%. Significance was determined at adj P<0.05.

Heatmaps, principal component analysis, and volcano plots

Principal Component Analysis (PCA) was used to visualize sample relatedness across treatments and tissues. Subsequent hierarchical clustering grouped samples according to transcriptomic relatedness, while volcano plots were constructed to visualize samples with absolute log-fold changes >1.5. All figures were generated with MatplotLib in Python version 3.2.0rc1.

KEGG/GO pathway analysis

Biological pathways for each DEG were generated using the KEGG pathway analysis and GO analysis conducted via the Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.7 software tool.

qPCR validation analyses

TotalRNA from each tissue was aliquoted and frozen at -80○C, and 2 μg of total RNA was reverse-transcribed into cDNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Catalog # 4368813). cDNA was diluted to 250 ng/μL and qPCR reactions were performed using 250 ng of total cDNA with primers at 300 nM concentration in 10 μL FastStart Sybr Green Master (Roche) according to the manufacturer’s instructions. Briefly, the thermocycling protocol followed a pre-incubation at 95°C for 10 minutes, followed by 45 cycles of 3-Step amplification: 1) denature at 95°C for 20 seconds; 2) anneal and extend at 60°C for 20 seconds; and 3) elongate at 72°C for 20 seconds. All qPCR reactions were conducted in a Roche LightCycler 96 Real-Time PCR System. Primers sequences for qPCR are as follows: Fatty Acid Synthase FWD: GGCGAGTCTATGCCACTATTC, REV: GCTGATACAGAGAACGGATGAG; Indolethylamine N-methyltransferase FWD: CTGGAGAAGGAGACGGTAGAA, REV: CGGGCAACCACGAAGTATAA; Cytochrome P450, family 2, subfamily c, polypeptide 22 FWD: AGAGAGAGAGAGAGAGAGAGAGA, REV: GAGACCCTCTGCATCTCAATAC; 18S Ribosomal Subunit FWD: AAGACGAACCAGAGCGAAAG, REV:TCGGAACTACGACGGTATCT; Cytochrome P450, family 51 FWD: CCTTCCAGTGGTGCTCTTATT, REV: CTAAGCCACTACCCAAAGACTATAC. In all qPCR experiments, 18s RNA expression was used to normalize gene expression within each tissue sample that was processed in triplicate. All data were analyzed using the Livak Delta-Delta CT method [54].

MicroRNA bioinformatic analysis

All microRNA fastq files were processed using the smallrnaseq [51] package in python. Smallrnaseq automates standard bioinformatic processes for quantification and analysis of small non-coding RNA species such as microRNA quantification and novel microRNA prediction. Briefly, smallrnaseq uses bowtie to align fastq files to user defined reference fasta sequences and all reference sequences were downloaded from www.RNAcentral.org (version 14). Following alignment to the Rattus Norvegicus genome and reference tRNA, rRNA, microRNA, lncRNA, and snRNA files, novel microRNA predictions are conducted using microRNADeep2. Additionally, differential expression was automated using the DEseq2 package in R.

qPCR correlation with mRNA sequencing.

Log fold change comparisons between qPCR and mRNA sequencing of several genes suggesting strong relationship between these two methods. (TIF) Click here for additional data file.

mRNA raw read counts.

Raw microRNA counts used in the analysis for comparing dietary treatment groups. (XLSX) Click here for additional data file.

mRNA DeSEQ2 summary statistics.

Summary statistics for the mRNA data from the DeSEQ2 analysis in R. (XLSX) Click here for additional data file.

MicroRNA DeSEQ2 summary statistics.

Summary statistics for the microRNA data from the DeSEQ2 analysis in R. (XLSX) Click here for additional data file.

Raw microRNA read counts.

Raw microRNA read counts used in the analyses. (XLSX) Click here for additional data file.

KEGG/GO analysis.

Gene ontology pathways that were upregulated/downregulated for each set of differentially expressed genes within each tissue using the DAVID database. (XLSX) Click here for additional data file.
Table 1

Differentially expressed genes in the liver, kidney, adipose and PFC tissues stratified according to each genotype-.

GenotypeTissueEnsembl_ID (ENSRNO)SymbolGene NameL2FCP-value3
ZDFAdipose DownregulatedG00000011039Gch1GTP cyclohydrolase 1-2.712.1E-05
G00000040108RGD1565355similar to fatty acid translocase/CD36-2.652.7E-07
G00000011024Zdhhc20zinc finger DHHC-type palmitoyltransferase 20-2.491.2E-04
G00000006946Arhgap9Rho GTPase activating protein 9-2.492.6E-06
G00000006715Ccr1C-C motif chemokine receptor 1-2.397.4E-06
G00000032546Dot1lDOT1 like histone lysine methyltransferase-2.121.9E-06
G00000034230Fcrl1Fc receptor-like 1-2.096.9E-05
G00000019283P2ry2purinergic receptor P2Y2-2.071.2E-04
G00000022975Nfam1NFAT activating protein with ITAM motif 1-1.923.1E-04
G00000013917Igsf10immunoglobulin superfamily, member 10-1.912.4E-05
G00000049115Ccr5C-C motif chemokine receptor 5-1.894.3E-07
G00000015895B4galt6beta-1,4-galactosyltransferase 6-1.845.1E-05
G00000020479Pik3c2aphosphatidylinositol-4-phosphate 3-kinase, catalytic subunit type 2 alpha-1.832.2E-04
G00000061379C7complement C7-1.821.8E-04
G00000011927Sdc3syndecan 3-1.822.3E-04
G00000026644Glipr1GLI pathogenesis-related 1-1.776.4E-05
G00000011946Ptnpleiotrophin-1.744.8E-05
G00000013922Dok2docking protein 2-1.612.7E-04
G00000013526Rassf4Ras association domain family member 4-1.603.1E-06
G00000001989Alcamactivated leukocyte cell adhesion molecule-1.571.5E-05
G00000016643Lpcat2lysophosphatidylcholine acyltransferase 2-1.522.9E-04
G00000003835Slc43a2solute carrier family 43 member 2-1.521.6E-04
G00000019077Lipalipase A, lysosomal acid type-1.513.8E-05
G00000009347Arhgap25Rho GTPase activating protein 25-1.492.1E-04
G00000000257Smpd3sphingomyelin phosphodiesterase 3-1.472.8E-04
G00000012616Ppt1palmitoyl-protein thioesterase 1-1.412.7E-04
G00000009331HckHCK proto-oncogene, Src family tyrosine kinase-1.304.6E-05
G00000010183Gask1bgolgi associated kinase 1B-1.262.7E-04
G00000017022Cerkceramide kinase-1.253.2E-04
G00000008465Tmem176btransmembrane protein 176B-1.232.4E-04
G00000010208Timp1TIMP metallopeptidase inhibitor 1-1.201.8E-04
ZDFAdipose UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000015072Ptgr1prostaglandin reductase 11.152.2E-04
G00000010389Ndrg2NDRG family member 21.302.0E-04
G00000037446Pxmp2peroxisomal membrane protein 21.302.3E-04
G00000002896Prdx6peroxiredoxin 61.373.1E-04
G00000019328Phgdhphosphoglycerate dehydrogenase1.453.4E-04
G00000021316Tmem98transmembrane protein 981.482.1E-04
G00000046858MGC109340similar to Microsomal signal peptidase 23 kDa subunit (SPase 22 kDa subunit) (SPC22/23)1.529.7E-05
G00000017012Coq7coenzyme Q7, hydroxylase1.564.5E-05
G00000021524Mrapmelanocortin 2 receptor accessory protein1.691.6E-04
G00000017226Slc2a4solute carrier family 2 member 41.871.8E-04
G00000002579Parm1prostate androgen-regulated mucin-like protein 11.897.0E-06
G00000001001Retnresistin1.953.0E-05
G00000008615Mal2mal, T-cell differentiation protein 22.091.6E-04
G00000019412RhbgRh family B glycoprotein2.121.3E-05
G00000009715Me1malic enzyme 12.132.0E-06
G00000012404Thrspthyroid hormone responsive2.432.4E-06
G00000019914Tlcd3bTLC domain containing 3B2.474.8E-10
G00000045636Fasnfatty acid synthase3.251.7E-11
G00000049911LOC102556347carbonyl reductase [NADPH] 1-like4.336.0E-18
LeanAdipose DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000016700Tcf21transcription factor 21-2.823.2E-06
LeanAdipose UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000013733Ppp4r1protein phosphatase 4, regulatory subunit 12.682.4E-05
G00000009536Pgpphosphoglycolate phosphatase2.693.4E-05
G00000031789Rangap1RAN GTPase activating protein 12.973.9E-05
G00000005082Irf6interferon regulatory factor 63.251.3E-05
G00000031934EnahENAH, actin regulator3.262.4E-05
G00000011296Cenpncentromere protein N3.342.8E-05
G00000056550Epb41l4berythrocyte membrane protein band 4.1 like 4B3.511.9E-05
G00000021589Nexmifneurite extension and migration factor4.432.9E-05
G00000008713Slc41a2solute carrier family 41 member 24.514.8E-07
G00000033262Reep6receptor accessory protein 64.721.0E-05
G00000003098Prom1prominin 15.252.6E-06
G00000015403Cd52CD52 molecule7.662.5E-07
ZDFPFC DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000033932AY172581.22–201AY172581.22–201-5.211.1E-05
G00000032112AY172581.14AY172581.14-4.731.5E-05
ZDFPFC UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
None
LeanPFC DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
None
LeanPFC UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
None
ZDFKidney DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000020204Srp19signal recognition particle 19-1.723.3E-05
G00000004794Rtn1reticulon 1-2.015.1E-05
G00000055471Ywhahtyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, eta-1.295.5E-05
G00000003357Col3a1collagen type III alpha 1 chain-1.466.4E-05
ZDFKidney UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000018237Gstp1glutathione S-transferase pi 12.045.2E-07
G00000018940CNT1solute carrier family 28 member 11.657.8E-05
LeanKidney DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000020151Cdh1cadherin 1-1.081.4E-05
G00000013062Cyp24a1cytochrome P450, family 24, subfamily a, polypeptide 1-1.304.3E-06
G00000012956Tgm2transglutaminase 2-1.343.5E-05
G00000004019Phlda1pleckstrin homology-like domain, family A, member 1-2.302.7E-08
LeanKidney UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000029726Gstm1glutathione S-transferase mu 11.401.5E-05
G00000053811Arg2arginase 21.513.5E-05
G00000000576Anapc16anaphase promoting complex subunit 162.113.3E-05
ZDFLiver DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000014320Inhbainhibin subunit beta A-4.773.2E-12
G00000007923Cgref1cell growth regulator with EF hand domain 1-3.744.4E-09
G00000004307Tor3atorsin family 3-3.556.1E-18
G00000034190Ighmimmunoglobulin heavy constant mu-3.381.4E-16
G00000003802Pttg1PTTG1 regulator of sister chromatid separation-3.351.2E-05
G00000007060Plin2perilipin 2-3.316.8E-28
G00000045636Fasnfatty acid synthase-3.311.5E-10
G00000022256Cxcl10C-X-C motif chemokine ligand 10-3.304.4E-04
G00000009019Slc6a6solute carrier family 6 member 6-3.096.0E-11
G00000025691Pla2g7phospholipase A2 group VII-3.034.5E-06
G00000020035Cyp17a1cytochrome P450-3.002.1E-09
G00000020480Fads1fatty acid desaturase 1-2.931.5E-13
G00000000658Acacbacetyl-CoA carboxylase beta-2.914.0E-18
G00000030154Cyp4a2cytochrome P450-2.885.0E-04
G00000021802Isg15ISG15 ubiquitin-like modifier-2.722.4E-03
G00000001052Slc25a30solute carrier family 25-2.581.8E-09
G00000001963Mx2MX dynamin like GTPase 2-2.562.1E-03
G00000040151Sdr16c6short chain dehydrogenase/reductase family 16C-2.556.3E-04
G00000017914Cavin3caveolae associated protein 3-2.511.4E-14
G00000006859Insig1insulin induced gene 1-2.503.4E-13
G00000006204Slc30a3solute carrier family 30 member 3-2.473.0E-07
G00000016353Nim1kNIM1 serine/threonine protein kinase-2.403.6E-08
G00000016011Plekhg1pleckstrin homology and RhoGEF domain containing G1-2.407.8E-05
G00000028137Mki67marker of proliferation Ki-67-2.381.5E-04
G00000014476EvlEnah/Vasp-like-2.373.4E-04
G00000008022Apaf1apoptotic peptidase activating factor 1-2.367.1E-05
G00000053891Phf11PHD finger protein 11-2.346.4E-08
G00000010819Hspa4lheat shock protein family A (Hsp70) member 4 like-2.326.9E-06
G00000021150Plcb3phospholipase C beta 3-2.313.1E-05
G00000001414Serpine1serpin family E member 1-2.271.2E-04
G00000016924AclyATP citrate lyase-2.255.5E-17
G00000045560Gvin1GTPase-2.252.1E-06
G00000020503Cbln3cerebellin 3 precursor-2.221.4E-06
G00000052444Samd9sterile alpha motif domain containing 9-2.223.3E-04
G00000005209Spred1sprouty-related-2.211.7E-05
G00000010888Ankrd33bankyrin repeat domain 33B-2.202.1E-06
G00000047218Clic5chloride intracellular channel 5-2.201.7E-03
G00000009481Ddhd1DDHD domain containing 1-2.192.0E-04
G00000022242Cxcl9C-X-C motif chemokine ligand 9-2.161.3E-05
G00000008807Rp1RP1-2.084.7E-05
G00000014426Loxlysyl oxidase-2.071.9E-03
G00000015498Il17rbinterleukin 17 receptor B-2.072.3E-04
G00000051965Smad4SMAD family member 4-2.078.7E-04
G00000017512Aldh3b1aldehyde dehydrogenase 3 family-2.051.0E-04
G00000057092Slfn4schlafen family member 4-2.056.2E-06
G00000012685Adck1aarF domain containing kinase 1-2.041.8E-03
G00000011268Chd5chromodomain helicase DNA binding protein 5-2.022.3E-03
G00000032374Paqr9progestin and adipoQ receptor family member 9-2.013.3E-14
G00000020272Elapor1endosome-lysosome associated apoptosis and autophagy regulator 1-1.971.0E-04
G00000061118LOC102551095uncharacterized LOC102551095-1.969.6E-05
G00000061527Gckglucokinase-1.934.4E-07
G00000053460Acot3acyl-CoA thioesterase 3-1.911.4E-04
G00000005043Cpeb2cytoplasmic polyadenylation element binding protein 2-1.912.0E-03
G00000017332Dapk2death-associated protein kinase 2-1.873.8E-04
G00000034013Acacaacetyl-CoA carboxylase alpha-1.864.5E-05
G00000017611Tnp1transition protein 1-1.862.0E-03
G00000012603Sestd1SEC14 and spectrin domain containing 1-1.851.2E-03
G00000025558Palm2paralemmin 2-1.845.7E-06
G00000018461Pdgfrbplatelet derived growth factor receptor beta-1.821.0E-03
G00000016123Rnf144bring finger protein 144B-1.805.5E-17
G00000013111Mettl3methyltransferase-like 3-1.786.7E-04
G00000045679Apoa1apolipoprotein A1-1.781.1E-11
G00000001926Cldn1claudin 1-1.781.8E-06
G00000005600Nr4a2nuclear receptor subfamily 4-1.774.2E-04
G00000012148Triotrio Rho guanine nucleotide exchange factor-1.767.0E-04
G00000004626Slc34a2solute carrier family 34 member 2-1.768.7E-05
G00000009360Sh3bp1SH3-domain binding protein 1-1.742.2E-03
G00000010890Bmp1bone morphogenetic protein 1-1.711.8E-07
G00000011820Acp3acid phosphatase 3-1.691.1E-04
G00000007591Slc45a3solute carrier family 45-1.688.9E-05
G00000006170Bach2BTB domain and CNC homolog 2-1.681.2E-03
G00000028895Rtp4receptor (chemosensory) transporter protein 4-1.665.3E-05
G00000002773Rgs4regulator of G-protein signaling 4-1.655.0E-04
G00000007234Cyp51cytochrome P450-1.641.2E-09
G00000020918Ccnd1cyclin D1-1.647.0E-09
G00000028941Zbed3zinc finger-1.638.4E-06
G00000012681Lgals9galectin 9-1.632.8E-13
G00000001640Tomm70translocase of outer mitochondrial membrane 70-1.632.6E-03
G00000009117Otub2OTU deubiquitinase-1.621.9E-04
G00000005726Pclopiccolo (presynaptic cytomatrix protein)-1.626.2E-04
G00000051171G6pcglucose-6-phosphatase-1.611.6E-04
G00000016552Hmgcs13-hydroxy-3-methylglutaryl-CoA synthase 1-1.604.4E-15
G00000004577Fez2fasciculation and elongation protein zeta 2-1.601.9E-04
G00000000547Tspyl4TSPY-like 4-1.595.0E-04
G00000017120Abhd2abhydrolase domain containing 2-1.591.9E-07
G00000015906Tgif1TGFB-induced factor homeobox 1-1.561.1E-03
G00000008144Irf1interferon regulatory factor 1-1.542.4E-06
G00000007319Trib3tribbles pseudokinase 3-1.548.5E-06
G00000018467Mitd1microtubule interacting and trafficking domain containing 1-1.521.9E-03
G00000023238Dgkddiacylglycerol kinase-1.521.2E-05
G00000020776Dhcr77-dehydrocholesterol reductase-1.511.1E-05
G00000033824Gpd2glycerol-3-phosphate dehydrogenase 2-1.515.5E-04
G00000003442Adora1adenosine A1 receptor-1.502.3E-06
G00000025689Abhd1abhydrolase domain containing 1-1.502.1E-07
G00000018198Dapk1death associated protein kinase 1-1.485.3E-04
G00000029668Wfdc21WAP four-disulfide core domain 21-1.451.6E-04
G00000006280Pcsk9proprotein convertase subtilisin/kexin type 9-1.444.7E-07
G00000008215Trim47tripartite motif-containing 47-1.441.3E-04
G00000014013Map4k4mitogen-activated protein kinase kinase kinase kinase 4-1.431.1E-05
G00000018627Plekhb1pleckstrin homology domain containing B1-1.438.9E-05
G00000007713Tmcc3transmembrane and coiled-coil domain family 3-1.432.6E-05
G00000000987Ptcd1pentatricopeptide repeat domain 1-1.431.0E-03
G00000014702Elovl2ELOVL fatty acid elongase 2-1.432.8E-11
G00000037595Gpbp1l1GC-rich promoter binding protein 1-like 1-1.412.3E-04
G00000001205Agpat31-acylglycerol-3-phosphate O-acyltransferase 3-1.413.8E-09
G00000019776Sh3gl3SH3 domain containing GRB2 like 3-1.404.1E-05
G00000012622Mmp15matrix metallopeptidase 15-1.401.9E-03
G00000023856Agxtalanine—glyoxylate and serine—pyruvate aminotransferase-1.397.5E-11
G00000042560Bag4BCL2-associated athanogene 4-1.381.2E-03
G00000013841Dcaf1DDB1 and CUL4 associated factor 1-1.382.1E-03
G00000019995Dnajc18DnaJ heat shock protein family (Hsp40) member C18-1.372.4E-04
G00000019996Slc16a1solute carrier family 16 member 1-1.361.6E-04
G00000023226S100a10S100 calcium binding protein A10-1.352.2E-04
G00000006227Ifih1interferon induced with helicase C domain 1-1.357.5E-04
G00000019005Pde8aphosphodiesterase 8A-1.341.5E-03
G00000021259Prnpprion protein-1.331.7E-03
G00000055909Apoa4apolipoprotein A4-1.332.6E-10
G00000008012Abcb4ATP binding cassette subfamily B member 4-1.334.1E-10
G00000021405Cyp2c7cytochrome P450-1.321.0E-08
G00000012181Lpllipoprotein lipase-1.315.3E-05
G00000056041AABR07062570-1.302.5E-03
G00000016815Tmem135transmembrane protein 135-1.294.1E-05
G00000019422Egr1early growth response 1-1.291.1E-05
G00000054077Aabr07024870-1.291.4E-03
G00000008194Znfx1zinc finger-1.285.5E-04
G00000009076Ttpalalpha tocopherol transfer protein like-1.271.7E-03
G00000005825Lyz2lysozyme 2-1.262.7E-05
G00000032293PolgDNA polymerase gamma-1.262.9E-04
G00000008586Aldh1l2aldehyde dehydrogenase 1 family-1.263.5E-04
G00000010805Fabp4fatty acid binding protein 4-1.252.5E-03
G00000016044Mab21l3mab-21 like 3-1.251.0E-04
G00000000459Psmb9proteasome 20S subunit beta 9-1.257.4E-04
G00000015124Gpamglycerol-3-phosphate acyltransferase-1.251.4E-03
G00000020871Ltbp4latent transforming growth factor beta binding protein 4-1.222.1E-03
G00000016516Mbpmyelin basic protein-1.221.2E-04
G00000007324Plxna2plexin A2-1.222.4E-07
G00000001821Adipoqadiponectin-1.212.7E-03
G00000020573Efna1ephrin A1-1.191.7E-04
G00000004606Meis1Meis homeobox 1-1.198.3E-04
G00000001647Ets2ETS proto-oncogene 2-1.179.1E-09
G00000059043Itchitchy E3 ubiquitin protein ligase-1.171.4E-03
G00000006787Dhcr2424-dehydrocholesterol reductase-1.161.9E-12
G00000015121N4bp1Nedd4 binding protein 1-1.153.0E-04
G00000042771Apol3apolipoprotein L-1.147.6E-08
G00000023664Leprleptin receptor-1.122.5E-03
G00000000451RT1-BaRT1 class II-1.121.1E-03
G00000012782Cemip2cell migration inducing hyaluronidase 2-1.111.0E-05
G00000014766Galtgalactose-1-phosphate uridylyltransferase-1.111.7E-05
G00000014718Acsl3acyl-CoA synthetase long-chain family member 3-1.111.4E-03
G00000017428Map1bmicrotubule-associated protein 1B-1.101.7E-03
G00000018517Trim21tripartite motif-containing 21-1.092.0E-03
G00000001426Prkrip1PRKR interacting protein 1-1.092.2E-03
G00000028448Elovl1ELOVL fatty acid elongase 1-1.082.2E-03
G00000005695Mgpmatrix Gla protein-1.071.2E-03
G00000017558Tubb2atubulin-1.077.2E-04
G00000012876Slc6a13solute carrier family 6 member 13-1.077.1E-05
G00000018960Syne1spectrin repeat containing nuclear envelope protein 1-1.077.3E-05
G00000017993Abcb10ATP binding cassette subfamily B member 10-1.058.6E-05
G00000007545Angptl4angiopoietin-like 4-1.044.1E-07
G00000007990Adipor2adiponectin receptor 2-1.041.1E-04
G00000020134Upf1UPF1-1.035.1E-04
G00000027434Fitm2fat storage-inducing transmembrane protein 2-1.021.7E-05
G00000048315Eif2ak2eukaryotic translation initiation factor 2-alpha kinase 2-1.026.7E-05
G00000005642Frs2fibroblast growth factor receptor substrate 2-1.027.7E-04
G00000014604Sigmar1sigma non-opioid intracellular receptor 1-1.014.9E-09
G00000002175Clockclock circadian regulator-1.012.4E-04
G00000042785Sesn2sestrin 2-1.001.7E-05
G00000023463Parp9poly (ADP-ribose) polymerase family-0.993.5E-04
G00000043377Fdpsfarnesyl diphosphate synthase-0.991.6E-03
G00000000593Rev3lREV3 like-0.982.0E-03
G00000019283P2ry2purinergic receptor P2Y2-0.981.0E-03
G00000024061Rarbretinoic acid receptor-0.982.7E-03
G00000017220Tcirg1T-cell immune regulator 1-0.983.3E-04
G00000021032Sphk2sphingosine kinase 2-0.972.3E-05
G00000001585Nrip1nuclear receptor interacting protein 1-0.971.1E-03
G00000003882Cep350centrosomal protein 350-0.965.2E-04
G00000005292Trip11thyroid hormone receptor interactor 11-0.962.4E-06
G00000046889Dbidiazepam binding inhibitor-0.962.3E-05
G00000000664Tpst2tyrosylprotein sulfotransferase 2-0.952.1E-03
G00000014900CremcAMP responsive element modulator-0.952.0E-03
G00000024115C6complement C6-0.932.9E-04
G00000030225Clpxcaseinolytic mitochondrial matrix peptidase chaperone subunit X-0.923.8E-05
G00000038012Commd6COMM domain containing 6-0.911.8E-04
G00000007302Fbn1fibrillin 1-0.911.4E-03
G00000018420Slc22a7solute carrier family 22 member 7-0.904.1E-04
G00000002635DexiDexi homolog-0.891.6E-06
G00000007728Gsdmdgasdermin D-0.892.3E-03
G00000026942RGD1311595similar to KIAA2026 protein-0.882.9E-05
G00000034066Hspa8heat shock protein family A (Hsp70) member 8-0.873.0E-04
G00000019372Pcpyruvate carboxylase-0.878.5E-06
G00000000177Plpp2phospholipid phosphatase 2-0.879.6E-04
G00000056703AtrxATRX-0.862.0E-04
G00000016219Vnn1vanin 1-0.861.5E-04
G00000014338Slc25a25solute carrier family 25 member 25-0.866.6E-04
G00000013391Sorbs2sorbin and SH3 domain containing 2-0.849.9E-06
G00000016692Hsdl2hydroxysteroid dehydrogenase like 2-0.831.3E-04
G00000024145Trim65tripartite motif-containing 65-0.835.9E-05
G00000010947Mmp14matrix metallopeptidase 14-0.831.7E-03
G00000018584Ptmaprothymosin alpha-0.831.5E-05
G00000008274XpcXPC complex subunit-0.833.6E-04
G00000011261Ttc14tetratricopeptide repeat domain 14-0.832.7E-03
G00000047386Smg1SMG1-0.822.7E-03
G00000007400Srebf2sterol regulatory element binding transcription factor 2-0.824.0E-04
G00000028801Gsapgamma-secretase activating protein-0.822.1E-03
G00000007700Inhbcinhibin subunit beta C-0.815.3E-04
G00000013178Cmipc-Maf-inducing protein-0.816.6E-04
G00000032394Tympthymidine phosphorylase-0.805.0E-04
G00000031709Ppfibp1PPFIA binding protein 1-0.796.6E-04
G00000003020Slc25a47solute carrier family 25-0.791.5E-03
G00000019450Etf1eukaryotic translation termination factor 1-0.781.6E-03
G00000010497RGD1305807hypothetical LOC298077-0.771.7E-05
G00000000184Tmprss6transmembrane serine protease 6-0.753.7E-04
G00000004709Foxn3forkhead box N3-0.732.2E-04
G00000007681Brd3bromodomain containing 3-0.722.1E-03
G00000033593Osbpl9oxysterol binding protein-like 9-0.727.9E-04
G00000002212Hsd17b13hydroxysteroid (17-beta) dehydrogenase 13-0.705.2E-06
G00000053550Itga1integrin subunit alpha 1-0.681.6E-03
G00000030700COX3cytochrome c oxidase subunit 3-0.672.8E-04
G00000020425Stim1stromal interaction molecule 1-0.661.0E-03
G00000057814NsdhlNAD(P) dependent steroid dehydrogenase-like-0.662.0E-05
G00000056371Pik3caphosphatidylinositol-4-0.661.5E-03
G00000016266Mphosph10M-phase phosphoprotein 10-0.652.2E-03
G00000015441Il4rinterleukin 4 receptor-0.651.8E-03
G00000009102Fermt2fermitin family member 2-0.622.2E-03
G00000005015Rabep1rabaptin-0.621.8E-03
G00000020151Cdh1cadherin 1-0.602.4E-03
G00000013135Ptpn12protein tyrosine phosphatase-0.582.7E-04
G00000057623Copb1COPI coat complex subunit beta 1-0.534.7E-04
G00000011140Prxl2aperoxiredoxin like 2A-0.512.0E-03
G00000018849Tcerg1transcription elongation regulator 1-0.512.0E-03
G00000008305Sc5dsterol-C5-desaturase-0.472.0E-03
G00000009263Ifi27interferon-0.472.2E-03
G00000004345Daam1dishevelled associated activator of morphogenesis 1-0.462.7E-03
G00000016963Trip12thyroid hormone receptor interactor 12-0.431.7E-03
ZDFLiver UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000003119GcGC0.451.1E-03
G00000000610Cisd1CDGSH iron sulfur domain 10.467.7E-04
G00000019629Lamp1lysosomal-associated membrane protein 10.508.8E-05
G00000000701Iscuiron-sulfur cluster assembly enzyme0.514.0E-05
G00000037850Mtarc2mitochondrial amidoxime reducing component 20.516.0E-04
G00000019048Sod2superoxide dismutase 20.542.8E-04
G00000007967Sdhbsuccinate dehydrogenase complex iron sulfur subunit B0.541.8E-03
G00000013928Dspdesmoplakin0.541.5E-03
G00000016794Phyhd1phytanoyl-CoA dioxygenase domain containing 10.552.0E-03
G00000019626Slc27a5solute carrier family 27 member 50.558.8E-05
G00000028368Etnk2ethanolamine kinase 20.551.4E-03
G00000011535Gcshglycine cleavage system protein H0.569.9E-04
G00000008921Dynll2dynein light chain LC8-type 20.561.5E-03
G00000030449Gsta4glutathione S-transferase alpha 40.561.1E-03
G00000018604TufmTu translation elongation factor0.592.2E-03
G00000017672Akr1c14aldo-keto reductase family 10.593.1E-04
G00000020994Slc25a39solute carrier family 250.597.3E-04
G00000047708Gstz1glutathione S-transferase zeta 10.591.1E-04
G00000013704Cps1carbamoyl-phosphate synthase 10.605.4E-04
G00000043404Uroc1urocanate hydratase 10.601.6E-05
G00000007395Baatbile acid CoA:amino acid N-acyltransferase0.605.3E-04
G00000017577Bphlbiphenyl hydrolase like0.606.8E-04
G00000007069Adhfe1alcohol dehydrogenase0.624.9E-04
G00000023538Aldh5a1aldehyde dehydrogenase 5 family0.624.9E-04
G00000006653Slc38a4solute carrier family 380.621.2E-04
G00000001333Azgp1alpha-2-glycoprotein 10.628.6E-06
G00000016339Uoxurate oxidase0.632.8E-05
G00000061876Tas1r2taste 1 receptor member 20.632.4E-04
G00000006916Sardhsarcosine dehydrogenase0.638.6E-05
G00000029549Eci3enoyl-Coenzyme A delta isomerase 30.638.9E-04
G00000048723Pros1protein S0.644.9E-04
G00000009005Slco2a1solute carrier organic anion transporter family0.642.7E-05
G00000007839Slc16a7solute carrier family 16 member 70.648.2E-04
G00000010389Ndrg2NDRG family member 20.655.7E-04
G00000014165Ssr1signal sequence receptor subunit 10.651.0E-04
G00000029735Pid1phosphotyrosine interaction domain containing 10.651.9E-03
G00000033466Aponapolipoprotein N0.651.1E-03
G00000000158Cdo1cysteine dioxygenase type 10.656.6E-06
G00000008364Catcatalase0.671.1E-03
G00000061883Aqp9aquaporin 90.681.3E-03
G00000021916Slc16a12solute carrier family 160.682.5E-03
G00000007743Mgst1microsomal glutathione S-transferase 10.681.8E-05
G00000003653Fhfumarate hydratase0.681.6E-03
G00000013223Fahfumarylacetoacetate hydrolase0.692.4E-04
G00000014700Ttc36tetratricopeptide repeat domain 360.698.4E-05
G00000030862Atp6v1hATPase H+ transporting V1 subunit H0.694.9E-04
G00000030667Ppm1bprotein phosphatase0.714.7E-06
G00000004139Ndel1nudE neurodevelopment protein 1-like 10.723.8E-05
G00000007927Mettl7bmethyltransferase like 7B0.725.0E-05
G00000004147Abca8aATP-binding cassette0.731.4E-03
G00000029726Gstm1glutathione S-transferase mu 10.741.3E-03
G00000003370Otcornithine carbamoyltransferase0.746.8E-06
G00000013039Add1adducin 10.744.2E-04
G00000014727Fahd1fumarylacetoacetate hydrolase domain containing 10.754.2E-04
G00000059463Slc39a1solute carrier family 39 member 10.761.6E-03
G00000004302Pahphenylalanine hydroxylase0.763.4E-07
G00000029651Rdh16retinol dehydrogenase 160.768.2E-04
G00000028746Gsto1glutathione S-transferase omega 10.773.2E-04
G00000018426NEWGENE_2134apolipoprotein C10.771.3E-06
G00000001053Tmed2transmembrane p24 trafficking protein 20.776.7E-04
G00000016173Cyp1a2cytochrome P4500.776.7E-04
G00000004089Enpp2ectonucleotide pyrophosphatase/phosphodiesterase 20.783.5E-04
G00000042274Fbxo31F-box protein 310.782.3E-03
G00000000186Tstthiosulfate sulfurtransferase0.788.6E-05
G00000048812Gpx1glutathione peroxidase 10.795.0E-04
G00000047986Sult2a1sulfotransferase family 2A member 10.792.5E-03
G00000006345Sec61bSEC61 translocon subunit beta0.796.2E-04
G00000009779Krt8keratin 80.792.2E-03
G00000006623Cd302CD302 molecule0.801.5E-04
G00000005987Suoxsulfite oxidase0.811.1E-03
G00000061890Ust5rintegral membrane transport protein UST5r0.812.3E-04
G00000020879NagsN-acetylglutamate synthase0.813.3E-04
G00000008902Pon1paraoxonase 10.829.7E-07
G00000018904Dtymkdeoxythymidylate kinase0.822.1E-03
G00000023116Agmoalkylglycerol monooxygenase0.824.0E-05
G00000047816Ccscopper chaperone for superoxide dismutase0.841.3E-04
G00000012142Glyatglycine-N-acyltransferase0.845.6E-07
G00000021206Plaat3phospholipase A and acyltransferase 30.847.5E-04
G00000012962Nudt16nudix hydrolase 160.851.9E-04
G00000050315Dcxrdicarbonyl and L-xylulose reductase0.862.9E-06
G00000000024Hebp1heme binding protein 10.862.7E-04
G00000000386Pbld1phenazine biosynthesis-like protein domain containing 10.871.3E-05
G00000007378Acox2acyl-CoA oxidase 20.877.0E-05
G00000003307Gcdhglutaryl-CoA dehydrogenase0.872.2E-08
G00000002205Ociad1OCIA domain containing 10.871.4E-03
G00000014645Aldh7a1aldehyde dehydrogenase 7 family0.888.2E-08
G00000008638Angptl3angiopoietin-like 30.882.9E-09
G00000011351Mat1amethionine adenosyltransferase 1A0.893.6E-05
G00000009421Ivdisovaleryl-CoA dehydrogenase0.891.9E-09
G00000036894Cisd3CDGSH iron sulfur domain 30.894.0E-04
G00000014128EcsitECSIT signaling integrator0.901.6E-03
G00000017619Aldh1a1aldehyde dehydrogenase 1 family0.903.1E-05
G00000018662Amacralpha-methylacyl-CoA racemase0.903.9E-07
G00000020000Tmem219transmembrane protein 2190.905.2E-04
G00000001957Sult1e1sulfotransferase family 1E member 10.902.8E-06
G00000051860Rnase4ribonuclease A family member 40.911.3E-09
G00000014160Tcp1t-complex 10.912.2E-04
G00000048114Echdc3enoyl CoA hydratase domain containing 30.912.7E-07
G00000003291Creg1cellular repressor of E1A-stimulated genes 10.921.3E-07
G00000008837Ass1argininosuccinate synthase 10.927.7E-04
G00000018159Anxa4annexin A40.922.3E-04
G00000010993Dpm1dolichyl-phosphate mannosyltransferase subunit 10.929.1E-04
G00000019982Ethe1ETHE10.922.4E-05
G00000023177Esrp2epithelial splicing regulatory protein 20.939.8E-07
G00000013409Gclmglutamate cysteine ligase0.933.0E-04
G00000001806Fetubfetuin B0.932.9E-04
G00000017291Sordsorbitol dehydrogenase0.947.2E-09
G00000053362Gabarapl1GABA type A receptor associated protein like 10.941.4E-07
G00000021174Macrod1mono-ADP ribosylhydrolase 10.957.1E-05
G00000014268Abca2ATP binding cassette subfamily A member 20.959.8E-04
G00000049771Gstt1glutathione S-transferase theta 10.968.4E-05
G00000011226Timm8a1translocase of inner mitochondrial membrane 8A10.964.5E-06
G00000005175Sgpp1sphingosine-1-phosphate phosphatase 10.972.0E-03
G00000049464Cyp2c13cytochrome P4500.976.0E-10
G00000002210Hsd17b11hydroxysteroid (17-beta) dehydrogenase 110.974.4E-10
G00000012786Pgrmc1progesterone receptor membrane component 10.991.2E-07
G00000004327Ddcdopa decarboxylase0.994.8E-05
G00000046357Adh5alcohol dehydrogenase 5 (class III)0.991.2E-11
G00000054049Prelid2PRELI domain containing 20.997.6E-04
G00000004442DglucyD-glutamate cyclase0.991.6E-03
G00000014876Lpin2lipin 21.003.9E-04
G00000012911Erlin1ER lipid raft associated 11.006.8E-04
G00000055314Msrb1methionine sulfoxide reductase B11.001.1E-07
G00000006619Dnajc9DnaJ heat shock protein family (Hsp40) member C91.016.5E-04
G00000018937Gstm7glutathione S-transferase1.011.6E-04
G00000027016Cobll1cordon-bleu WH2 repeat protein-like 11.011.4E-04
G00000046007Cldn3claudin 31.022.8E-04
G00000033609Irx1iroquois homeobox 11.022.0E-03
G00000017777Ahcyadenosylhomocysteinase1.021.5E-05
G00000019180Acsl4acyl-CoA synthetase long-chain family member 41.021.0E-08
G00000022932Serhl2serine hydrolase-like 21.031.5E-04
G00000016484Gstk1glutathione S-transferase kappa 11.031.5E-07
G00000003620Fmo3flavin containing dimethylaniline monoxygenase 31.041.7E-05
G00000032895Cyp4f4cytochrome P4501.045.0E-08
G00000032737F7coagulation factor VII1.052.1E-04
G00000023816Aph1aaph-1 homolog A1.051.6E-03
G00000015205Cyb5acytochrome b5 type A1.069.6E-07
G00000008079Ugp2UDP-glucose pyrophosphorylase 21.064.1E-08
G00000011559Cnn3calponin 31.075.6E-05
G00000013484Gsta1glutathione S-transferase alpha-11.074.2E-10
G00000050595Mup5major urinary protein 51.071.5E-04
G00000026775Pmpcapeptidase1.083.9E-04
G00000001338Hpd4-hydroxyphenylpyruvate dioxygenase1.087.7E-06
G00000001618Ripk4receptor-interacting serine-threonine kinase 41.092.3E-03
G00000000768Ubdubiquitin D1.102.4E-05
G00000007508Lrtm2leucine-rich repeats and transmembrane domains 21.101.8E-08
G00000031769Chchd7coiled-coil-helix-coiled-coil-helix domain containing 71.104.4E-04
G00000013291Cyp2c23cytochrome P4501.104.4E-07
G00000017188Cyp27a1cytochrome P4501.111.7E-08
G000000583271.137.4E-04
G00000025079Fam126bfamily with sequence similarity 1261.134.7E-04
G00000061215Crymcrystallin1.142.1E-04
G00000017752Mccc2methylcrotonoyl-CoA carboxylase 21.161.8E-05
G00000016166Pdlim1PDZ and LIM domain 11.167.7E-07
G00000010079Ca3carbonic anhydrase 31.174.7E-10
G00000013728Polg2DNA polymerase gamma 21.176.2E-04
G00000062298Rpl13aribosomal protein L13A1.192.6E-03
G00000013751Plpbppyridoxal phosphate binding protein1.192.3E-06
G00000001442Porcytochrome p450 oxidoreductase1.191.2E-09
G00000042253Ecdecdysoneless cell cycle regulator1.206.0E-04
G00000020254Per2period circadian regulator 21.203.1E-04
G00000007949Rgnregucalcin1.218.8E-08
G00000003253Qdprquinoid dihydropteridine reductase1.213.4E-09
G00000003515Ephx1epoxide hydrolase 11.227.9E-07
G00000011039Gch1GTP cyclohydrolase 11.232.8E-07
G00000038746Bco2beta-carotene oxygenase 21.246.3E-07
G00000005861Hsd11b1hydroxysteroid 11-beta dehydrogenase 11.244.3E-09
G00000000588Slc16a10solute carrier family 16 member 101.241.6E-05
G00000020202Asrgl1asparaginase and isoaspartyl peptidase 11.252.7E-03
G00000017826Mtrr5-methyltetrahydrofolate-homocysteine methyltransferase reductase1.261.6E-03
G00000033700Bud23BUD231.271.7E-03
G00000000281Prodh1proline dehydrogenase 11.282.1E-11
G00000042084Acsm2acyl-CoA synthetase medium-chain family member 21.303.4E-09
G00000006972Zfp189zinc finger protein 1891.301.5E-03
G00000027784Tskutsukushi1.327.2E-04
G00000012387Glyatl2glycine-N-acyltransferase-like 21.337.3E-07
G00000011714Sat2spermidine/spermine N1-acetyltransferase family member 21.336.9E-05
G00000045799Rup2urinary protein 21.347.8E-04
G00000021924Cyp2c22cytochrome P4501.359.3E-08
G00000018494Ppp1r3cprotein phosphatase 11.364.1E-11
G00000004693Pbx1PBX homeobox 11.361.4E-03
G00000001258Snx8sorting nexin 81.372.0E-04
G00000020698Rnd2Rho family GTPase 21.376.0E-05
G000000512271.386.2E-04
G00000052810Cyp2c11cytochrome P4501.392.0E-11
G00000012436Adh6alcohol dehydrogenase 6 (class V)1.414.4E-15
G00000015936Gng5G protein subunit gamma 51.412.6E-03
G00000018413Per3period circadian regulator 31.421.6E-04
G00000016967Hfehomeostatic iron regulator1.422.9E-07
G00000001376Mettl7amethyltransferase like 7A1.433.1E-04
G00000056940Cited2Cbp/p300-interacting transactivator1.441.5E-11
G00000015002Abhd15abhydrolase domain containing 151.441.5E-04
G00000032959Adh7alcohol dehydrogenase 7 (class IV)1.457.6E-09
G00000050232LOC680406similar to Urinary protein 2 precursor (RUP-2)1.461.5E-09
G00000020700Rnaseh2cribonuclease H21.487.7E-04
G00000011635Ces2ecarboxylesterase 2E1.492.9E-08
G00000015354Aox1aldehyde oxidase 11.542.6E-12
G00000061450Homer2homer scaffold protein 21.542.5E-05
G00000009629Car2carbonic anhydrase 21.552.9E-05
G00000042111Sult1c2asulfotransferase family1.552.3E-03
G00000057072Slc12a3solute carrier family 12 member 31.553.1E-04
G00000004009Xpnpep2X-prolyl aminopeptidase 21.571.1E-08
G00000013313Nceh1neutral cholesterol ester hydrolase 11.578.8E-07
G00000015438LOC501233LRRGT000801.581.2E-13
G00000015076Cyp26b1cytochrome P4501.626.3E-04
G00000016456Il33interleukin 331.654.2E-18
G00000001766Tfrctransferrin receptor1.671.1E-04
G00000011718C1rlcomplement C1r subcomponent like1.681.2E-06
G00000013949Idh2isocitrate dehydrogenase (NADP(+)) 21.682.3E-16
G00000018740Ugt1a6UDP glucuronosyltransferase family 1 member A61.696.1E-14
G00000016807Oatornithine aminotransferase1.721.2E-05
G00000025418Armc9armadillo repeat containing 91.744.5E-04
G00000023778Gcnt2glucosaminyl (N-acetyl) transferase 2 (I blood group)1.776.8E-05
G00000056596Alas15'-aminolevulinate synthase 11.802.3E-15
G00000046643Cyp3a9cytochrome P4501.825.3E-04
G00000003260Nr1i3nuclear receptor subfamily 11.846.4E-05
G00000001158Abcg1ATP binding cassette subfamily G member 11.863.0E-05
G00000020250Pcgf6polycomb group ring finger 61.889.2E-04
G00000006420Rbm38RNA binding motif protein 381.892.0E-04
G00000012458Cyp2e1cytochrome P4501.911.3E-19
G00000002258Tmem150ctransmembrane protein 150C1.949.3E-05
G00000013982Hsd17b2hydroxysteroid (17-beta) dehydrogenase 21.945.1E-04
G00000021027DbpD-box binding PAR bZIP transcription factor1.943.2E-05
G00000004437Map2k6mitogen-activated protein kinase kinase 62.071.1E-08
G00000032246Acsm3acyl-CoA synthetase medium-chain family member 32.192.3E-16
G00000014490Bdh23-hydroxybutyrate dehydrogenase 22.212.5E-14
G00000036687AlyrefAly/REF export factor2.238.9E-04
G00000015519Ces1dcarboxylesterase 1D2.246.9E-32
G00000009598Ncaph2non-SMC condensin II complex2.413.8E-05
G00000043131LOC100360095urinary protein 1-like2.434.9E-19
G00000034191Fmo1flavin containing dimethylaniline monoxygenase 12.462.8E-25
G00000005985Kcnma1potassium calcium-activated channel subfamily M alpha 12.821.6E-04
G00000011250Inmtindolethylamine N-methyltransferase2.903.9E-21
G00000058904Tex13btestis expressed 13B3.105.9E-15
G00000012772Nqo1NAD(P)H quinone dehydrogenase 13.111.5E-12
G00000001388Sdsserine dehydratase3.291.7E-09
G00000056847Gsta3glutathione S-transferase alpha 33.403.1E-21
G00000001242Gstt3glutathione S-transferase3.661.2E-85
G00000051912Acnat2acyl-coenzyme A amino acid N-acyltransferase 23.748.9E-05
G00000009488Cyp7a1cytochrome P450 family 7 subfamily A member 14.191.4E-18
LeanLiver DownregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000029668Wfdc21WAP four-disulfide core domain 21-2.721.3E-04
G00000020480Fads1fatty acid desaturase 1-2.534.0E-08
G00000006859Insig1insulin induced gene 1-2.323.2E-05
G00000057557Prlrprolactin receptor-2.272.3E-04
G00000055909Apoa4apolipoprotein A4-1.932.3E-04
G00000030154Cyp4a2cytochrome P450-1.752.2E-08
G00000019776Sh3gl3SH3 domain containing GRB2 like 3-1.628.9E-05
G00000046889Dbidiazepam binding inhibitor-1.611.1E-05
G00000014702Elovl2ELOVL fatty acid elongase 2-1.601.8E-05
G00000032297Msmo1methylsterol monooxygenase 1-1.563.6E-05
G00000007234Cyp51cytochrome P450-1.564.9E-05
G00000020989Tm7sf2transmembrane 7 superfamily member 2-1.456.6E-05
LeanLiver UpregulatedEnsembl_ID (ENSRNO)Gene SymbolGene NameL2FCP-value
G00000001376Mettl7amethyltransferase like 7A1.161.7E-04
G00000048114Echdc3enoyl CoA hydratase domain containing 31.171.2E-04
G00000023116Agmoalkylglycerol monooxygenase1.211.7E-04
G00000002643UgdhUDP-glucose 6-dehydrogenase1.297.6E-05
G00000015354Aox1aldehyde oxidase 11.331.2E-04
G00000004089Enpp2ectonucleotide pyrophosphatase/phosphodiesterase 21.349.6E-05
G00000034191Fmo1flavin containing dimethylaniline monoxygenase 11.371.7E-04
G00000013291Cyp2c23cytochrome P4501.471.1E-04
G00000003809Sat1spermidine/spermine N1-acetyl transferase 11.583.9E-05
G00000018740Ugt1a6UDP glucuronosyltransferase family 1 member A61.802.6E-05
G00000015519Ces1dcarboxylesterase 1D1.945.6E-10
G00000033570Arhgap8Rho GTPase activating protein 82.031.5E-04
G00000051912Acnat2acyl-coenzyme A amino acid N-acyltransferase 22.051.1E-04
G00000001158Abcg1ATP binding cassette subfamily G member 12.211.1E-04
G00000001388Sdsserine dehydratase2.298.0E-06
G00000047613AABR07048463.1AABR07048463.12.341.4E-06
G00000013552Scdstearoyl-CoA desaturase2.364.8E-06
G00000001242Gstt3glutathione S-transferase2.931.4E-09
G00000021924Cyp2c22cytochrome P4503.225.2E-15
G00000009488Cyp7a1cytochrome P450 family 7 subfamily A member 13.361.5E-09

1All genes were analyzed using DESeq2 for differential analysis.

2Abbreviations used: ZDF, Zucker Diabetic Fatty; L2FC, log2 fold change; PFC, prefrontal cortex.

3 Benjamini-Hochberg adjusted P-values controlling for false discovery rate at 5%, where P< 0.05 was considered significant.

Table 2

Differentially expressed microRNAs in WE vs CAS-based diets in ZDF rats and their lean controls-.

GenotypeTissueMicroRNAL2FCNon adjustedp-valueP-value3
ZDFAdipose Downregulatedrno-miR-221-3p-1.609.53E-050.007
ZDFPFC Upregulatedrno-miR-29a-3p0.590.00010.022
ZDFPFC Upregulatedrno-miR-151-5p0.890.00050.036
LeanAdipose Downregulatedrno-miR-125a-5p-1.480.00220.069
LeanAdipose Downregulatedrno-miR-125b-5p-1.780.00290.069
LeanLiver Upregulatedrno-miR-9a-5p1.899.08E-050.0063
LeanLiver Upregulatedrno-miR-181a-5p1.100.00070.024
LeanLiver Upregulatedrno-miR-10b-5p1.370.00110.024
LeanLiver Downregulatedrno-miR-192-5p-0.570.00130.024

1All miRNAs were analyzed using DESeq2 for differential analysis.

2Abbreviations used: ZDF, Zucker Diabetic Fatty; WE, whole egg; CAS, casein; L2FC, log2 fold change; and PFC, prefrontal cortex.

3Benjamini-Hochberg adjusted P-values controlling for false discovery rate at 5%, where P< 0.05 was considered significant.

Table 3

Differentially expressed microRNAs and their corresponding target genes that were differentially regulated by dietary WE consumption-.

MicroRNATissueGene NameL2FCNon-adjp-valueHuman SymbolEnsembl Rat ID (RNOG)Rat SymbolGene Name
miR-125b-5p(down regulated)lean adiposePgp2.690.00003PGP00000009536Pgpphosphoglycolate phosphatase
rno-miR-181a-5p(up regulated)leanliverCYP7A13.360.000000001Cyp7a100000009488Cyp7a1Cytochrome P450 Family 7 Subfamily A Member 1
rno-miR-181a-5p(up regulated)leanliverScd2.350.0000048Scd00000013552SCDstearoyl-CoA desaturase

1All miRNAs were analyzed using DESeq2 for differential analysis.

2Abbreviations used: miR, microRNAS; rno, rattus norvegicus; WE, whole egg; and L2FC, log2 fold change.

3Gene targets for Rattus Norvegicus and humans were determined by DRSC Integrative Ortholog Prediction Tool.

Table 4

Composition of the CAS and WE based diets fed to lean and ZDF rats for 8 wk.

CASWE
Ingredient (g/kg)
Casein200-
Whole Egg2-435
Cornstarch417365
Corn Oil183-
Glucose Monohydrate150150
Mineral Mix3535
Vitamin Mix1010
Choline Bitartrate22
L-methionine33
Biotin (1%)-0.4
Macronutrients (% total kcal)3
Protein1717
Carbohydrate4848
Fat3535
Caloric Content4,7154,715

1All ingredients were purchased from Envigo except for dried whole egg (Rose Acre Farms, Guthrie Center, IA), as well as l-methionine and choline bitartrate (Sigma-Aldrich). Abbreviations used: CAS, casein-based diet, WE, whole egg-based diet.

2 Total protein and lipid content provided by 435 g of dried WE was 46% (200 g) and 42% (183 g), respectively.

3 To formulate all diets such that protein was provided at 20% (w/w).

  43 in total

Review 1.  The role of oxidative stress in the pathogenesis of type 2 diabetes mellitus micro- and macrovascular complications: avenues for a mechanistic-based therapeutic approach.

Authors:  Franco Folli; Domenico Corradi; Paolo Fanti; Alberto Davalli; Ana Paez; Andrea Giaccari; Carla Perego; Giovanna Muscogiuri
Journal:  Curr Diabetes Rev       Date:  2011-09

2.  Differential gene expression between Zucker Fatty rats and Zucker Diabetic Fatty rats: a potential role for the immediate-early gene Egr-1 in regulation of beta cell proliferation.

Authors:  Kay E Garnett; Philip Chapman; Julie A Chambers; Ian D Waddell; David S W Boam
Journal:  J Mol Endocrinol       Date:  2005-08       Impact factor: 5.098

3.  The effect of a high-egg diet on cardiovascular risk factors in people with type 2 diabetes: the Diabetes and Egg (DIABEGG) study-a 3-mo randomized controlled trial.

Authors:  Nicholas R Fuller; Ian D Caterson; Amanda Sainsbury; Gareth Denyer; Mackenzie Fong; James Gerofi; Katherine Baqleh; Kathryn H Williams; Namson S Lau; Tania P Markovic
Journal:  Am J Clin Nutr       Date:  2015-02-11       Impact factor: 7.045

4.  Dietary Whole Egg Reduces Body Weight Gain in a Dose-Dependent Manner in Zucker Diabetic Fatty Rats.

Authors:  Cassondra J Saande; Joseph L Webb; Paige E Curry; Matthew J Rowling; Kevin L Schalinske
Journal:  J Nutr       Date:  2019-10-01       Impact factor: 4.798

Review 5.  Global aetiology and epidemiology of type 2 diabetes mellitus and its complications.

Authors:  Yan Zheng; Sylvia H Ley; Frank B Hu
Journal:  Nat Rev Endocrinol       Date:  2017-12-08       Impact factor: 43.330

6.  Egg consumption may improve factors associated with glycemic control and insulin sensitivity in adults with pre- and type II diabetes.

Authors:  Shirin Pourafshar; Neda S Akhavan; Kelli S George; Elizabeth M Foley; Sarah A Johnson; Behnam Keshavarz; Negin Navaei; Anis Davoudi; Elizabeth A Clark; Bahram H Arjmandi
Journal:  Food Funct       Date:  2018-08-15       Impact factor: 5.396

7.  Egg consumption and risk of type 2 diabetes: a meta-analysis of prospective studies.

Authors:  Luc Djoussé; Owais A Khawaja; J Michael Gaziano
Journal:  Am J Clin Nutr       Date:  2016-01-06       Impact factor: 7.045

8.  Diet-induced thermogenesis in man: thermic effects of single proteins, carbohydrates and fats depending on their energy amount.

Authors:  H Karst; J Steiniger; R Noack; H D Steglich
Journal:  Ann Nutr Metab       Date:  1984       Impact factor: 3.374

9.  Alterations in glutathione redox metabolism, oxidative stress, and mitochondrial function in the left ventricle of elderly Zucker diabetic fatty rat heart.

Authors:  Haider Raza; Annie John; Frank C Howarth
Journal:  Int J Mol Sci       Date:  2012-11-30       Impact factor: 5.923

10.  Dietary obesity-induced Egr-1 in adipocytes facilitates energy storage via suppression of FOXC2.

Authors:  Jifeng Zhang; Yuan Zhang; Tingwan Sun; Fang Guo; Shengping Huang; Menisha Chandalia; Nicola Abate; Daping Fan; Hong-Bo Xin; Y Eugene Chen; Mingui Fu
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379
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  2 in total

1.  Indole-3-Acetic Acid Alters Intestinal Microbiota and Alleviates Ankylosing Spondylitis in Mice.

Authors:  Jun Shen; Lianjun Yang; Ke You; Tao Chen; Zhihai Su; Zhifei Cui; Min Wang; Weicong Zhang; Bin Liu; Kai Zhou; Hai Lu
Journal:  Front Immunol       Date:  2022-02-04       Impact factor: 7.561

2.  RNA Sequencing Reveals Key Metabolic Pathways Are Modified by Short-Term Whole Egg Consumption.

Authors:  Amanda E Bries; Joe L Webb; Brooke Vogel; Claudia Carrillo; Timothy A Day; Michael J Kimber; Rudy J Valentine; Matthew J Rowling; Stephanie Clark; Kevin L Schalinske; Elizabeth M McNeill
Journal:  Front Nutr       Date:  2021-05-10
  2 in total

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