Literature DB >> 23555558

Induction of olfaction and cancer-related genes in mice fed a high-fat diet as assessed through the mode-of-action by network identification analysis.

Youngshim Choi1, Cheol-Goo Hur, Taesun Park.   

Abstract

The pathophysiological mechanisms underlying the development of obesity and metabolic diseases are not well understood. To gain more insight into the genetic mediators associated with the onset and progression of diet-induced obesity and metabolic diseases, we studied the molecular changes in response to a high-fat diet (HFD) by using a mode-of-action by network identification (MNI) analysis. Oligo DNA microarray analysis was performed on visceral and subcutaneous adipose tissues and muscles of male C57BL/6N mice fed a normal diet or HFD for 2, 4, 8, and 12 weeks. Each of these data was queried against the MNI algorithm, and the lists of top 5 highly ranked genes and gene ontology (GO)-annotated pathways that were significantly overrepresented among the 100 highest ranked genes at each time point in the 3 different tissues of mice fed the HFD were considered in the present study. The 40 highest ranked genes identified by MNI analysis at each time point in the different tissues of mice with diet-induced obesity were subjected to clustering based on their temporal patterns. On the basis of the above-mentioned results, we investigated the sequential induction of distinct olfactory receptors and the stimulation of cancer-related genes during the development of obesity in both adipose tissues and muscles. The top 5 genes recognized using the MNI analysis at each time point and gene cluster identified based on their temporal patterns in the peripheral tissues of mice provided novel and often surprising insights into the potential genetic mediators for obesity progression.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23555558      PMCID: PMC3608641          DOI: 10.1371/journal.pone.0056610

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


Introduction

Microarray analysis has enabled the use of whole-genome expression profiling to understand the mechanisms underlying obesity and metabolic complications and to identify key genetic mediators. Statistical approaches used to analyze microarray data can be classified into 2 major categories: methods that identify differentially expressed genes [1], [2] and those that classify genes according to the functional dependency (e.g., hierarchical clustering) [3]. Although microarray analysis has yielded some promising results, it is not a very practical method considering the fact that identification of genes directly affected by a condition is difficult from the hundreds to thousands of genes that exhibit changes in expression. To overcome this problem, Berneardo et al. developed a model-based approach that accurately distinguishes a compound's targets from the indirect responders [4]. This approach, namely, the mode-of-action by network identification (MNI), involves the reverse engineering of a network model of regulatory interactions in an organism of interest by using a training dataset of whole-genome expression profiles. The MNI algorithm has been applied successfully to identify disease mediators as well as drug targets by studying gene-expression data from yeast [4], humans (A. Ergun and J.J. Collins, unpublished data), bacteria, and other organisms (X.H., unpublished data). Differential expression can be studied from a static or temporal viewpoint. In a static experiment, the arrays are obtained irrespective of time, essentially taking a snapshot of gene expression. On the other hand, in a temporal experiment, the arrays are collected over a time course, facilitating the study of the dynamic behavior of gene expression. Most previously obtained microarray datasets were static, that is, the results obtained on the basis of the measurement of gene expression at a single time point [5]. Since the regulation of gene expression is a dynamic process, it is important to identify and characterize the changes in gene expression over time. Therefore, numerous time-series microarray experiments have been performed to study such biological processes such as abiotic stress, disease progression, and drug responses [6]–[8]. Microarray analysis for studying the mechanisms underlying obesity was first reported by Soukas et al. in 2000 [9]. They used approximately 6,500 murine genes in pairs of adipose tissues in ob/ob mice and wild-type lean mice. Subsequently, many such studies were conducted: more than 30 microarray approaches have been exploited in assessing the changes in gene expression in the adipose tissues, liver, hypothalamus, skeletal muscles, small intestines, and kidneys of lean and obese animals or human subjects. A frequent limitation of these studies is that they are not time-resolved and do not necessarily provide information of an end-point or disease stage. Considerably less is known about the key genetic mediators of HFD-induced obesity and the dynamics of changes in metabolic processes related to this condition. To gain more insight into the genetic mediators associated with the onset and progression of diet-induced obesity and metabolic diseases, we studied the molecular changes in response to the HFD by using an integrative time-resolved approach.

Materials and Methods

Ethics statement

All animal experiments were performed in accordance with the Korean Food and Drug Administration (KFDA) guidelines. Protocols were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of the Yonsei Laboratory Animal Research Center (YLARC) (Permit #: 2011-0061). All mice were maintained in the specific pathogen-free facility of the YLARC.

Animals and diets

Five-week-old male C57BL/6N mice were obtained from Orient Bio (Gyeonggi-do, South Korea). All animals were housed in specific pathogen-free conditions, with 21±2.0°C temperature, 50±5% relative humidity, and a 12 h-light/12 h-dark cycle. From a week before the diet intervention was started, all animals were fed standard chow. At the beginning of the study, mice were divided into 2 groups: (1) control group fed the normal diet (ND, n = 40) and (2) a group fed the high-fat diet (HFD, n = 40). Mice were provided food and water ad libitum. The body weight and food intake were monitored throughout the study. At 2, 4, 8, and 12 weeks after the initiation of the study, 10 animals from each group were killed. Tissues were snap-frozen immediately in liquid nitrogen and stored at −80°C until further processing.

RNA extraction for microarray analysis

Total RNA was extracted from the epididymal and subcutaneous fat tissues and gastrocnemius muscle of each mouse by using Trizol (Invitrogen, CA, USA), according to the manufacturer's recommendations. Concentrations and purity of RNA samples were determined using a Nano Drop ND-1000 spectrophotometer (Nano Drop Technologies, Inc., Wilmington, DE, USA). RNA preparations were considered suitable for array hybridization only if samples showed intact 18S and 28S rRNA bands and displayed no chromosomal peaks or RNA degradation products. The integrity of the RNA samples was determined using a Bioanalyzer 2100 System (Agilent Technologies, Palo Alto, CA, USA).

Real-time quantitative PCR

Real-time PCR amplification was performed with the SYBR Premix Ex Taq kit (Takara, Kyoto, Japan) on a Light Cycler 2 (Roche Applied Science, Indianapolis, USA). The initial denaturation step was at 95°C for 10 s, followed by 40 cycles of amplification at 95°C for 3 s and 60°C for 40 s. mRNA expression was determined using the relative standard curve method and normalized to the housekeeping gene. The primers (sense and antisense, respectively) were as follows: Gli2, 5′- GCC AAC CAG AAC AAG CAG AA-3′, 5′- CGC TTA TGA ATG GTG ATG GG -3′; Gucy2c, 5′- GTG CGG TTA CTG CTC TTC CA -3′, 5′- TTG TCC ATC ATC AGG ACG CT -3′; Olfr1181, 5′- CCT GAC AGT CAT GGC CTT TG -3′, 5′- ACC CAG GAA GCC CAG ATA AA -3′; Atp8b3, 5′- GTT TGA GCA GGA TGT GAC CG -3′, 5′- GGC TTG CAT GAA AAT GCT GT -3′; Tmem46, 5′- TTT TCC AGC AGC AGG AGC TA -3′, 5′- GCT GAG GAG AAA AGG GAT GC -3′; Pthr2, 5′- ATG CAA GGG AGA AAC CCA TC -3′, 5′- TAG ATC CTC CCA CAC AGC CA -3′; Cdh7, 5′- TGG ACT GGG CAT TTT CAA GA -3′, 5′- GGG GAT CAG CAT CTC GAT TT -3′; Mep1b, 5′- GAT GGC CAC ATA CCA TTC CA -3′, 5′- TAA GGC GAT AGC GCT CAA AA -3′; Lamc3, 5′- GAC ATG GGC TCT TGC TAC GA -3′, 5′- CGT TCT CGA ACT CAG GCA GA -3′; GAPDH, 5′- GGA GAT TGT TGC CAT CAA CG -3′, 5′- TTT GCC GTG AGT GGA GTC AT -3′.

Microarray hybridization and data analysis

Equal amounts of total RNA were pooled from 10 mice in each experimental group and subjected to microarray experiments in triplicate. For analysis, 2 μg total RNA was labeled and amplified using the Universal Linkage System antisense RNA (aRNA) labeling kit (Kreatech Diagnostics, Amsterdam, The Netherlands). The Cy5-labeled aRNAs were resuspended in 10 μL of hybridization solution (GenoCheck, Korea). The labeled aRNAs were hybridized to the NimbleGen mouse whole genome 12-plex array (Roche NimbleGen, Inc., WI, USA) that contained 60-mer probes representing 42,576 genes (average 3 probes per target). The arrays were scanned using a GenePix 4000B microarray scanner. The data were extracted from the scanned images using NimbleScan software version 2.4 (Roche NimbleGen), and the Robust Multichip Average algorithm was used to generate gene expression values. The normalized and log-transformed intensity values were then analyzed using GeneSpring GX 10 (Agilent Technologies, Santa Clara, CA, USA) and GenePlex (Istech, Inc., Seoul, South Korea). The details of labeling, hybridization, scanning, and normalization of the data are provided on the NimbleGen website (http://www.nimblegen.com). Gene expression levels between the ND and HFD samples were assessed by comparing the average expression ratios of each group. Hierarchical clustering was performed in GeneSpring GX 7.3.1 software (Agilent Technologies, Santa Clara, CA), using average gene expression values under HFD condition divided by the median of ND gene expression, per time-point.

MNI algorithm

We constructed a compendium dataset consisting of hundreds of expression profiles in the organism of interest; that the expression profiles were downloaded from the Gene Expression Omnibus, a public repository of microarray studies. The MNI algorithm was applied, using the method developed by Xing et al. [10], and was configured to output the top 200 mediators for each sample and generate the associated Z-scores for those probe sets. The Z-score for probe sets that were not within the list of the top 100 probe sets identified as mediators for a given sample were set to zero. To identify a characteristic list of genes within each group, the Z-scores across samples and probe sets for corresponding genes were averaged and ranked. The top 100 genes within that list were selected to be reported as significant genetic mediators. A higher average Z-score is an indication of higher number of occurrences of a gene on the lists generated by the MNI algorithm in each group. The 100 highest ranked genes were classified according to the biological process in which they are involved as per the criteria established by the GO.

Results

Effect of HFD feeding on visceral adiposity

The body weight gains of mice fed the 2 diets over the 12-week period are shown in Figure 1A. The difference in body weight between the 2 groups continued to increase over the course of experimental feeding: the difference was about 45% by 12 weeks. The increase in body weight associated with the HFD was partially attributed to the expansion of visceral adipose tissues. The masses of the epididymal, perirenal, mesenteric, and retroperitoneal fat pads of the mice fed HFD for 12 weeks were 42%, 40%, 54%, and 42%, respectively; the difference in the masses was larger in the HFD-fed mice than in the ND-fed group (Figure 1B–F). Moreover, HFD-fed mice exhibited significant reductions in the wet weights of the gastrocnemius (−13%) and soleus (−16%) muscles at 12 weeks compared with those in the ND-fed mice (Figure 1G and H).
Figure 1

Changes in body weight, visceral fat-pad weights, and muscle masses over time.

(A) Body weight gain. (B) Total visceral fat-pad weight. (C) Epididymal fat-pad weight. (D) Perirenal fat-pad weight. (E) Mesenteric fat-pad weight. (F) Retroperitoneal fat-pad weight. (G) Gastrocnemius muscle mass. (H) Soleus muscle mass. Data are presented as means ± SEM. *P<0.05.

Changes in body weight, visceral fat-pad weights, and muscle masses over time.

(A) Body weight gain. (B) Total visceral fat-pad weight. (C) Epididymal fat-pad weight. (D) Perirenal fat-pad weight. (E) Mesenteric fat-pad weight. (F) Retroperitoneal fat-pad weight. (G) Gastrocnemius muscle mass. (H) Soleus muscle mass. Data are presented as means ± SEM. *P<0.05.

Transcription response of WAT and muscle to HFD during the 12-week time-course

Gene expression profiling in the WAT and muscle of mice was assessed through the oligonucleotide microarray analysis. Among 25,291 genes on the NimbleGen Mouse Whole Oligo 12-plex chip used in this study, 21,890 genes (86%) were identified as known genes. After determination of the temporal effects of the HFD across 12-week time-course, we focused on dissecting the HFD specific effects on the transcriptome of epididymal and subcutaneous fats and muscle. Microarray data were analyzed by hierarchical clustering of enriched functional groups of genes (based on Gene Ontology) and the major results are graphically illustrated in a heat map (Figure 2). The HFD elicited distinct changes in gene expression in epididymal and subcutaneous fats and muscle of mice over time, and most significant changes were shown in epididymal fat tissue. Specifically, prominent expression changes were observed at the early phase (week 2 to week 4) and the enrichment of lipid metabolism and inflammatory processes were significant among the up-regulated HFD-responsive genes, whereas G-protein coupled receptor protein signaling pathway and electron transport were most significant among the down-regulated HFD-responsive genes in the epididymal fat tissue.
Figure 2

Heatmap of differentially expressed transcript sets.

Values used for clustering are average HFD vs. ND per time-point expression ratio. The branches of the condition tree are colored so to discriminate three subclusters with the largest distance, corresponding to three tissues of the time-course: epididymal adipose tissue (red), subcutaneous adipose tissue (blue) and gastrocnemious muscle (green). This is summarized in the color bar underneath the cluster diagram.

Heatmap of differentially expressed transcript sets.

Values used for clustering are average HFD vs. ND per time-point expression ratio. The branches of the condition tree are colored so to discriminate three subclusters with the largest distance, corresponding to three tissues of the time-course: epididymal adipose tissue (red), subcutaneous adipose tissue (blue) and gastrocnemious muscle (green). This is summarized in the color bar underneath the cluster diagram.

MNI analysis of the time course treatment with the HFD

To elucidate the time course and metabolic processes underlying obesity progression induced by the HFD, we determined the gene expression profiles of the epididymal and subcutaneous fat tissues and gastrocnemius muscle of mice by using oligonucleotide microarray analysis. Each of these data was queried against the reconstructed network (MNI algorithm), and the resulting potential genetic mediators in each case were ranked according to the Z-score statistic. The lists of top 5 potential genetic mediators for obesity progression in the epididymal and subcutaneous fat tissues and gastrocnemius muscle of mice fed the HFD for 2, 4, 8, and 12 weeks are shown in Tables 1, 2, 3. The most characteristic genes across all tissues in the list were associated with cancer; the genes in this category included Nek11, Gli2, Tmem46, Mep1b, Ccdc109b, Rab23, Patz1, and Hdac9. The second representative functional theme was related to olfactory transduction, and these genes included Olfr1181, Olfr1173, Olfr855, Olfr1056, Olfr716, and Tmem16b. To validate the microarray results quantitatively, we analyzed the mRNA expression levels of top-ranked genes by real-time PCR. In all cases, a strong correspondence between the microarray data and the real-time PCR results was observed (Figure 3). We also measured the basal expression levels of selected genes including several olfactory receptors in the epididymal fat tissues of ND- or HFD-fed mice, using real-time PCR. The results indicated that the basal expression levels of highly ranked olfactory genes (Olfr1181, Olfr513, Olfr960, and Olfr1245) were comparable to those of top five genes (Gli2, Gucy2c, Atp8b3, and Tmem46) identified by MNI analysis at week 4 in the epididymal adipose tissue (Figure S1).
Table 1

List of top 5 genes identified by the MNI analysis at each time point in the epididymal fat tissue of HFD-induced obese mice.

RankGene accession No.Gene symbolDescriptionFunctionFold change
Epididymal fat tissue
2 week1NM_023173Dusp12Dual specificity phosphatase 12Insulin resistance2.52
2NM_172461Nek11NIMA (never in mitosis gene a)-related expressed kinase 11Cancer0.43
3NM_145489AI661453Expressed sequence AI661453Unknown0.23
4NM_177078Adrbk2Adrenergic receptor kinase, beta 2Bipolar disorder2.73
5NM_013679Svs6Seminal vesicle secretory protein 6Unknown0.77
4 week1XM_136212Gli2GLI-Kruppel family member GLI2Cancer2.73
2NM_145067Gucy2cGuanylate cyclase 2cCancer0.34
3NM_001011816Olfr1181Olfactory receptor 1181Olfactory transduction5.47
4NM_026094Atp8b3ATPase, Class I, type 8B, member 3ATP binding3.25
5NM_145463Tmem46Transmembrane protein 46Cancer0.55
8 week1NM_199155Tas2r110Taste receptor, type 2, member 110Sensory perception of taste2.81
2AK138164Cntn5Contactin 5Cell adhesion0.33
3NM_152220Stx3Syntaxin 3Arachidonic acid binding1.81
4NM_178924Upk1bUroplakin 1BEpithelial cell differentiation1.79
5NM_028622Lce1cLate cornified envelope 1CUnknown0.32
12 week1NM_139270Pthr2Parathyroid hormone receptor 2Parathyroid hormone receptor activity2.39
2NM_172853Cdh7Cadherin 7, type 2Calcium ion binding2.42
3NM_008586Mep1bMeprin 1 betaCancer0.33
4NM_011836Lamc3Laminin gamma 3Cell adhesion0.49
5NM_145463Tmem46Transmembrane protein 46Cancer0.59
Table 2

List of top 5 genes identified by the MNI analysis at each time point in the subcutaneous fat tissue of HFD-induced obese mice.

RankGene accession No.Gene symbolDescriptionFunctionFold change
Subcutaneous fat tissue
2 week1NM_025779Ccdc109bCoiled-coil domain containing 109BCancer0.54
2NM_001025438Camk2dCalcium/calmodulin-dependent protein kinase II, deltaCalmodulin binding0.65
3AB211064L1td1LINE-1 type transposase domain containing 1Unknown2.61
4NM_026345Mansc1MANSC domain containing 1Unknown3.03
5NM_207566Olfr1173Olfactory receptor 1173Olfactory transduction1.97
4 week1NM_008529Ly6eLymphocyte antigen 6 complex, locus EAdrenal gland development1.31
2NM_146524Olfr855Olfactory receptor 855Olfactory transduction1.57
3NM_018744Sema6aSema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6ANervous system development0.73
4AB211064L1td1LINE-1 type transposase domain containing 1Unknown3.13
5NM_183015Ccnb3Cyclin B3Cell cycle2.58
8 week1NM_153111FevFEV (ETS oncogene family)Nervous system development0.39
2AB211064L1td1LINE-1 type transposase domain containing 1Unknown2.8
3NM_147018Olfr1056Olfactory receptor 1056Olfactory transduction0.73
4NM_008999Rab23RAB23, member RAS oncogene familyCancer0.56
5NM_080644Cacng5Calcium channel, voltage-dependent, gamma subunit 5Calcium ion transport0.36
12 week1NM_001024852Auts2Autism susceptibility candidate 2Mental retardation0.53
2NM_178046SvilSupervillinUnknown0.57
3NM_018764Pcdh7Protocadherin 7Cell adhesion1.82
4NM_146604Olfr716Olfactory receptor 716Olfactory transduction3.08
5BC0894894930474M22RikRIKEN cDNA 4930474M22 geneUnknown1.9
Table 3

List of top 5 genes identified by the MNI analysis at each time point in the gastrocnemius muscle of HFD-induced obese mice.

RankGene accession No.Gene symbolDescriptionFunctionFold change
Gastrocnemius muscle
2 week1NM_019574Patz1POZ (BTB) and AT hook containing zinc finger 1Cancer1.8
2NM_020610Nrip3Nuclear receptor interacting protein 3Inflammation0.42
3NM_024124Hdac9Histone deacetylase 9Cancer0.55
4XM_975536Armc4Armadillo repeat containing 4Unknown0.54
5NM_139226Onecut3One cut domain, family member 3DNA binding1.34
4 week1NM_153589Tmem16bTransmembrane protein 16BOlfactory transduction0.74
2NM_175540Eda2rEctodysplasin A2 isoform receptorAlopecia0.88
3NM_008355Il13Interleukin 13Inflammation1.57
4NM_010608Kcnk3Potassium channel, subfamily K, member 3Ion transport1.22
5XM_129809Ogfrl1Opioid growth factor receptor-like 1Unknown0.7
8 week1NM_024124Hdac9Histone deacetylase 9Cancer0.6
2NM_011990Slc7a11Solute carrier family 7Amino acid transport0.7
3NM_1754209330176C04RikRIKEN cDNA 9330176C04 geneUnknown2.17
4NM_016961Mapk9Mitogen activated protein kinase 9Insulin resistance0.59
5NM_027462Wars2Tryptophanyl tRNA synthetase 2 (mitochondrial)Vasculogenesis0.56
12 week1NM_008114Gfi1Growth factor independent 1BHematopoiesis0.74
2NM_145435PyyPeptide YYInsulin resistance1.49
3NM_138648Olr1Oxidized low density lipoprotein (lectin-like) receptor 1Inflammation0.33
4NM_177861Tmem67Transmembrane protein 67Mental retardation0.54
5XM_887155Igsf10Immunoglobulin superfamily, member 10Unknown0.42
Figure 3

Quantitative PCR.

Quantitative real-time PCR analysis of the mRNA expression on selected gene targets identified by MNI analysis in the epididymal fat tissues of mice. Results are presented as the average ± SEM of at least 3 separate experiments.

Quantitative PCR.

Quantitative real-time PCR analysis of the mRNA expression on selected gene targets identified by MNI analysis in the epididymal fat tissues of mice. Results are presented as the average ± SEM of at least 3 separate experiments.

Functional analysis of the highly ranked genetic mediators

We next focused on the GO-annotated pathways that were significantly overrepresented among the highly ranked genetic mediators. For our analysis, we subjected the 100 highest ranked genes identified by MNI analysis in the epididymal and subcutaneous fat tissue and gastrocnemius muscle of mice with diet-induced obesity to pathway analysis based on the GO biological process annotations (Tables 4, 5, 6). We found that the olfactory transduction was highly enriched in the epididymal and subcutaneous fat tissue and gastrocnemius muscle of the HFD-fed mice compared to the ND-fed mice at all time points. Even the second representative functional theme of epididymal fat was related to cancer at all time points. The pathways thought to be associated with obesity progression in the epididymal fat as per the MNI analysis included Wnt signaling pathway, melanogenesis, chemokine signaling pathway, focal adhesion, MAPK signaling pathway, purine metabolism, regulation of actin cytoskeleton, neuroactive ligand-receptor interaction, and extracellular matrix (ECM)-receptor interaction. In the subcutaneous fat, other pathways identified by the MNI analysis for obesity progression included calcium signaling pathway, gonadotropin-releasing hormone (GnRH) signaling pathway, axon guidance, cell cycle, and tyrosine metabolism. In the gastrocnemius muscle, besides the olfactory transduction mentioned above, the over-represented groups identified according to GO biological processes for obesity progression were those involved in the various cellular processes such as neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, pathways associated with cancer, insulin signaling pathway, pathways associated with colorectal cancer, adipocytokine signaling pathway, type II diabetes mellitus, and cell adhesion molecules.
Table 4

The enriched pathways among top 100 genetic mediators identified by the MNI analysis at each time point in the epididymal fat tissue of HFD-induced obese mice.

GO ontologyRanked pathway genes (rank)
Epididymal fat tissue
2 weekOlfactory transductionAdrbk2 (4), Olfr513 (6), Olfr433 (15), Camk2g (28), Olfr1245 (29), Olfr1143 (36), Olfr996 (55), Olfr960 (57), Arrb2 (79)
Wnt signaling pathwayCamk2g (28), Rhoa (31), Wnt10a (95)
MelanogenesisCamk2g (28), Adcy5 (80), Wnt10a (95)
Chemokine signaling pathwayRhoa (31), Arrb2 (79), Adcy5 (80)
Focal adhesionRhoa (31), Lamc3 (44), Bcl2 (77)
Pathways in cancerRhoa (31), Bcl2 (77), Wnt10a (95)
4 weekOlfactory transductionCamk2g (17), Olfr513 (27), Olfr960 (31), Olfr1245 (43), Arrb2 (55)
Pathways in cancerGli2 (1), Lamc3 (9), Bcl2 (58), Fgf5 (65)
MAPK signaling pathwayArrb2 (55), Fgf5 (65), Mapkapk5 (75)
Purine metabolismGucy2c (2), Nme7 (47), Cant1 (85)
8 weekOlfactory transductionOlfr536 (11), Olfr513 (31), Olfr654 (37), Camk2g (74), Olfr652 (99)
Focal adhesionFlnc(16), Bcl2 (64), Col6a2 (83), Rhoa (86), Mylk (96),
Regulation of actin cytoskeletonFgf5 (26), Rhoa (86), Mylk (96)
Pathways in cancerFgf5 (26), Bcl2 (64), Rhoa (86)
12 weekOlfactory transductionOlfr16 (6), Camk2g (10), Olfr715 (24), Olfr1245 (32), Olfr536 (36), Olfr1143 (52)
Neuroactive ligand-receptor interactionPth2r (1), Agtrl1 (16), Vipr2 (27), P2rx6 (74)
Focal adhesionLamc3 (4), Bcl2 (75), Col6a2 (76), Rhoa (88)
ECM-receptor interactionLamc3 (4), Cd44 (59), Col6a2 (76)
Pathways in cancerLamc3 (4), Bcl2 (75), Rhoa (88)
Table 5

The enriched pathways among top 100 genetic mediators identified by the MNI analysis at each time point in the subcutaneous fat tissue of HFD-induced obese mice.

GO ontologyRanked pathway genes (rank)
Subcutaneous fat tissue
2 weekOlfactory transductionCamk2b (2), Olfr1173 (5), Olfr823 (9), Guca1a (41), Olfr411 (49), Olfr1408 (51), Olfr875 (64)
Calcium signaling pathwayCamk2b (2), Cacna1d (15), Htr4 (45), Ryr1 (96)
GnRH signaling pathwayCamk2b (2), Cacna1d (15), Cga (48)
4 weekOlfactory transductionOlfr855 (2), Olfr888 (13), Olfr305 (36), Olfr1173 (49), Olfr395 (52), Olfr411 (55), Olfr823 (83), Olfr1409 (89)
Axon guidanceSema6a (3), Abl1 (23)
Cell cycleCcnb3 (5), Abl1 (23)
Regulation of actin cytoskeletonVav3 (9), Ssh2 (25)
Tyrosine metabolismFah (26), Aoc3 (27)
MAPK signaling pathwayCacna1d (28), Hspa1a (44)
8 weekOlfactory transductionOlfr1056 (3), Olfr960 (15), Olfr1408 (26), Olfr855 (35), Olfr609 (42), Olfr1173 (49), Olfr411 (71), Olfr205 (91), Olfr1121 (94)
Focal adhesionShc4 (63), Diap1 (77), Lamb2 (82), Vav3 (83)
12 weekOlfactory transductionOlfr716 (4), Olfr45 (16), Olfr960 (19), Olfr1173 (32), Olfr411 (34), Olfr1408 (43), Olfr855 (45), Olfr875 (96)
GnRH signaling pathwayCacna1d (29), Cga (58)
Chemokine signaling pathwayVav3 (33), Gng3 (79), Shc4 (84)
Table 6

The enriched pathways among top 100 genetic mediators identified by the MNI analysis at each time point in the gastrocnemius muscle of HFD-induced obese mice.

GO ontologyRanked pathway genes (rank)
Gastrocnemius muscle
2 weekOlfactory transductionClca3 (6), Olfr739 (14), Olfr488 (40), Olfr474 (55)
4 weekOlfactory transductionOlfr800 (28), Olfr978 (33), Olfr474 (49), Olfr488 (73)
Neuroactive ligand-receptor interactionOprl1 (30), Mc1r (78), Tbxa2r (89), Tspo (97)
Cytokine-cytokine receptor interactionEda2r (2), Il13 (3), Cx3cl1 (91)
Pathways in cancerDcc (10), Amn (71), Mlh1 (85)
8 weekOlfactory transductionClca3 (9), Olfr739 (48), Olfr1305 (64), Olfr1395 (80), Olfr140 (81), Olfr63 (85), Olfr689 (86)
Pathways in cancerMapk9 (4), Dcc (15), Mapk10 (78), Grb2 (87), Mitf (89)
Insulin signaling pathwayMapk9 (4), Irs3 (40), Mapk10 (78), Grb2 (87)
Colorectal cancerMapk9 (4), Dcc (15), Mapk10 (78), Grb2 (87)
Adipocytokine signaling pathway Type II diabetes mellitusMapk9 (4), Irs3 (40), Mapk10 (78)
12 weekOlfactory transductionOlfr689 (22), Olfr488 (24), Olfr347 (38), Olfr1204 (69)
Cell adhesion molecules (CAMs)Cd22 (23), Nlgn3 (44), Ptprm (62)
Cytokine-cytokine receptor interactionEda2r (43), Ppbp (53), Cx3cl1 (57)

Representative time-course profile clusters

We subjected the 40 highest ranked genes identified by MNI analysis at each time point in the epididymal and subcutaneous fat tissues and gastrocnemius muscle of mice with diet-induced obesity to clustering based on their temporal pattern. Figure 4 shows genes that were observed to have decreasing ranking across time point, with a peak at 2 week. Biological processes controlled by genes in this cluster included regulation of insulin resistance (EA: Dusp12), cancer (EA: Nek11, A4gnt; SA: Srp9), inflammation (EA: Siglece; M: Nrip3, Sez6l), and olfactory transduction (EA: Olfr 513, 433; SA: Olfr 823) (Tables 7, 8, 9). The genes shown in Figures 5 and 6 exhibited the highest rank at the intermediate time points of 4 and 8 weeks, respectively. For both clusters, the majority of genes in this category were associated with cancer (EA: Gli2, Gucy2c, Lsm1, Duoxa1, Lasp1; SA: Vav3, Kcnrg, Tle6, Rab23; M: Dcc, Rassf2, Perp, Pdgfr1), inflammation (SA: Btn2a2, Def6; M: ll13, Rap1gds1), insulin resistance (SA: Neurod4; M: Mapk9), and olfactory transduction (EA: Olfr 1181, 960, 536, 654, 527; SA: Olfr 855, 888, 305, 1056, 960, 685, 1048; M: Olfr 699, 800, 978, 232, 872) (Tables 10, 11, 12, 13, 14, 15). Figure 7 shows genes that exhibited increasing ranking across all time points, with a peak at 12 week. Biological processes for genes in this cluster included regulation of adipogenesis (EA: Smad7, Adhfe1), food intake (M: Pyy), inflammation (EA: Folr2, Pde7a, Vipr2; SA: Rfxdc2, Aqp5, Cpb2), cancer (M: Lin28, Gstm1, Safb2), and olfactory transduction (EA: Olfr 16, 1000; SA: Olfr 716, 45; M: Olfr 689, 347) (Tables 16, 17, 18). The genes shown in Figure 8 exhibited a constant high MNI ranking throughout the time course. This cluster contained genes related to cancer (EA: Tmem46; SA: Trim62; M: Hdac9), insulin resistance (EA: Camk2g), hepatic fibrosis (M: Tmem67), and olfactory transduction (SA: Olfr 1173, 411, 855) (Table 19).
Figure 4

Results of MNI analysis at week 2.

Genes that exhibited decreasing ranking across time points as revealed by the MNI analysis, with a peak at 2 week in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Table 7

List of genes that exhibited decreasing ranking across time point as revealed by the MNI analysis, with a peak at 2 week in the epididymal adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Epididymal adipose tissue
Insulin resistance
NM_023173Dusp12Dual specificity phosphatase 122.51.82.11.7
Inflammation
NM_031181SigleceSialic acid binding Ig-like lectin E2.11.91.71.7
Cancer
NM_172461Nek11NIMA (never in mitosis gene a)-related expressed kinase 110.40.50.60.6
XM_286168A4gntAlpha-1,4-N-acetylglucosaminyltransferase2.01.71.61.5
Olfactory transduction
NM_146723Olfr513Olfactory receptor 5130.30.30.30.4
NM_146717Olfr433Olfactory receptor 4332.12.01.91.5
Others
NM_022318Popdc2Popeye domain containing 22.62.01.81.9
XM_901428EG629397Predicted gene, EG6293971.81.71.51.4
XM_899101Camsap1Calmodulin regulated spectrin-associated protein 1-like 13.42.22.32.6
NM_177769Elmod1ELMO domain containing 11.71.61.51.4
NM_010768MatkMegakaryocyte-associated tyrosine kinase2.31.81.71.8
NM_177078Adrbk2Adrenergic receptor kinase, beta 22.72.12.22.1
NM_013679Svs6Seminal vesicle secretory protein 60.80.70.70.7
XM_486653EG434760Predicted gene, EG4347600.40.50.40.4
NM_001030297Tmprss11cTransmembrane protease, serine 11c1.91.52.01.7
NM_0263384921517D21RikRIKEN cDNA 4921517D21 gene2.92.52.82.0
NM_133879Zbtb4Zinc finger and BTB domain containing 480.40.20.30.5
NM_001034875Gm1006Gene model 1006, (NCBI)2.12.11.72.0
NM_016802RhoaRas homolog gene family, member A2.12.11.72.0
NM_177887BC022651cDNA sequence BC0226511.81.41.61.5
NM_207670GraspGRIP1 associated protein1.41.21.31.3
NM_183124Defb41Defensin beta 410.70.80.80.7
Table 8

List of genes that exhibited decreasing ranking across time point as revealed by the MNI analysis, with a peak at 2 week in the subcutaneous adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Subcutaneous adipose tissue
Cancer
NM_012058Srp9Signal recognition particle 90.50.60.70.5
Olfactory transduction
NM_146673Olfr823Olfactory receptor 8230.60.60.70.7
Others
NM_025779Ccdc109bCoiled-coil domain containing 109B0.50.70.70.6
NM_001025438Camk2dCalcium/calmodulin-dependent protein kinase II, delta0.80.80.80.8
AB211064L1td1LINE-1 type transposase domain containing 13.12.81.91.9
NM_008748Dusp8Dual specificity phosphatase 80.60.60.80.8
XM_905633Armcx4Armadillo repeat containing, X-linked 41.92.02.42.4
NM_001034860EG229571Predicted gene, EG2295711.61.51.41.4
XM_898433AK129128cDNA sequence AK1291282.31.81.91.4
XM_355152Gm967Gene model 967, (NCBI)0.50.60.60.7
NM_016869CorinCorin0.70.70.80.8
NM_153386Clrn1Clarin 11.31.21.31.3
NM_029911Kcnk10Potassium channel, subfamily K, member 100.70.70.80.8
NM_026943Snrpd2Small nuclear ribonucleoprotein D20.60.80.70.7
NM_134000Traf3ip2Traf3 interacting protein 21.51.31.21.2
NM_023790Wdr5WD repeat domain 541.81.31.30.9
XM_9872161700072O05RikRIKEN cDNA 1700072O05 gene0.60.60.60.7
XM_1466329030420J04RikRIKEN cDNA 9030420J04 gene2.52.12.01.5
NM_015756Shroom3Shroom family member 31.91.41.31.5
Table 9

List of genes that exhibited decreasing ranking across time point as revealed by the MNI analysis, with a peak at 2 week in the muscle of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Muscle
Inflammation
NM_020610Nrip3Nuclear receptor interacting protein 30.40.50.70.5
BC065117Sez6lSeizure related 6 homolog like1.71.71.71.3
Others
NM_019574Patz1POZ (BTB) and AT hook containing zinc finger 11.81.41.31.5
XM_975536Armc4Armadillo repeat containing 40.50.40.50.6
NM_139226Onecut3One cut domain, family member 31.31.41.31.2
NM_177596EG210853Predicted gene, EG2108530.40.60.70.7
NM_1754556430502M16RIkRIKEN cDNA 6430502M16 gene2.31.61.71.7
NM_010243Fut9Fucosyltransferase 90.80.90.90.9
NM_024178Alg14Asparagine-linked glycosylation 14 homolog (yeast)0.40.50.60.6
NM_138954Rfpl4Ret finger protein-like 40.60.80.70.7
XM_9002150610010O12RikRIKEN cDNA 0610010O12 gene1.61.31.41.3
NM_0256795730470L24RikRIKEN cDNA 5730470L24 gene0.80.80.80.8
NM_027588Nt5c1b5′-nucleotidase, cytosolic IB0.70.70.70.6
NM_177239Mysm1Myb-like, SWIRM and MPN domains 10.50.60.50.7
XM_1265376030468B19RikRIKEN cDNA 6030468B19 gene1.61.41.31.2
NM_0280471500002O20RikRIKEN cDNA 1500002O20 gene1.31.21.31.2
U66058Lig3Ligase III, DNA, ATP-dependent0.80.80.80.8
Figure 5

Results of MNI analysis at week 4.

Genes that exhibited the highest rank at the intermediate time point of 4 week as revealed by the MNI analysis in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Figure 6

Results of MNI analysis at week 8.

Genes that exhibited the highest rank at the intermediate time point of 8 week as revealed by the MNI analysis in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Table 10

List of genes that exhibited the highest ranking at the intermediate time point of 4 week as revealed by the MNI analysis in the epididymal adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Epididymal adipose tissue
cancer
XM_136212Gli2GLI-Kruppel family member GLI22.22.72.41.8
NM_145067Gucy2cGuanylate cyclase 2c0.40.30.50.5
NM_138721Lsm1U7 snRNP-specific Sm-like protein LSM100.30.90.80.6
NM_145395Duoxa1Dual oxidase maturation factor 11.71.71.71.5
NM_010688Lasp1LIM and SH3 protein 12.12.52.82.3
olfacroty transduction
NM_001011816Olfr1181Olfactory receptor 11813.15.52.93.9
NM_146279Olfr960Olfactory receptor 9602.42.32.11.8
Others
NM_026094Atp8b3ATPase, Class I, type 8B, member 32.53.32.52.1
NM_029857Tmco4Transmembrane and coiled-coil domains 40.50.30.60.4
NM_181419BC050092cDNA sequence BC0500922.23.42.82.6
NM_145514Wdr26WD repeat domain 260.40.30.40.4
XM_125673Cxxc6CXXC finger 62.42.92.21.8
BC0194046030465E24RikRIKEN cDNA 6030465E24 gene1.41.71.61.6
NM_028015Lass5Longevity assurance homolog 5 (S. cerevisiae)2.43.52.42.3
NM_010184Fcer1aFc receptor, IgE, high affinity I, alpha polypeptide0.60.50.70.6
NM_007378Abca4ATP-binding cassette, sub-family A (ABC1), member 41.71.91.81.5
NM_0296072310003C23RikRIKEN cDNA 2310003C23 gene0.40.30.40.5
NM_001033541EG331493Predicted gene, EG3314931.31.51.41.4
NM_019656Tspan6Tetraspanin 62.02.82.42.2
NM_027366Ly6g6eLymphocyte antigen 6 complex, locus G6E1.71.51.51.4
BC096543B930095G15RikRIKEN cDNA B930095G15 gene3.63.82.72.7
NM_133199Scn4aSodium channel, voltage-gated, type IV, alpha0.40.40.50.5
NM_027661Hsfy2Heat shock transcription factor, Y linked 21.41.41.51.3
Table 11

List of genes that exhibited the highest ranking at the intermediate time point of 4 week as revealed by the MNI analysis in the subcutaneous adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Subcutaneous adipose tissue
Inflammation
NM_175938Btn2a2Butyrophilin, subfamily 2, member A21.62.41.81.5
Cancer
NM_020505Vav3Vav 3 oncogene1.31.61.41.5
NM_206974KcnrgPotassium channel regulator1.31.71.51.3
NM_053254Tle6Transducin-like enhancer of split 6, homolog of drosophila E(spl)0.70.60.80.7
olfactory transduction
NM_146524Olfr855Olfactory receptor 8551.71.62.01.6
NM_146424Olfr888Olfactory receptor 8880.60.50.60.7
NM_146616Olfr305Olfactory receptor 3050.70.60.60.7
Others
NM_018744Sema6aSema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6A0.80.70.70.8
NM_183015Ccnb3Cyclin B31.82.61.51.8
NM_134220V1ri3Vomeronasal 1 receptor, I31.62.31.61.7
NM_026082Dock7Dedicator of cytokinesis 71.62.21.51.4
NM_153761Mill2MHC I like leukocyte 20.70.60.70.8
NM_001031621Abca17ATP-binding cassette, sub-family A (ABC1), member 171.31.71.41.4
NM_175013Pgm5Phosphoglucomutase 51.51.51.51.3
NM_178712Gpr64G protein-coupled receptor 641.31.61.61.4
NM_177839TnnTenascin N0.80.70.80.9
NM_198644Zfat1ZFAT zinc finger 12.12.72.12.0
NM_145512Sft2d2SFT2 domain containing 21.21.51.41.3
NM_029012Sppl3Signal peptide peptidase 30.70.50.70.7
NM_009594Abl1v-abl Abelson murine leukemia oncogene 10.70.70.70.8
NM_177710Ssh2Slingshot homolog 2 (Drosophila)0.70.60.80.7
NM_010176FahFumarylacetoacetate hydrolase0.70.70.80.8
NM_009675Aoc3Amine oxidase, copper containing 31.21.41.31.3
XM_149023Gm553Gene model 553, (NCBI)2.01.91.81.6
XM_9872161700072O05RikRIKEN cDNA 1700072O05 gene0.60.60.60.7
NM_173784Ubtd2Ubiquitin domain containing 21.62.01.61.4
NM_1831314930451I11RikRIKEN cDNA 4930451I11 gene1.82.21.81.4
NM_027661Hsfy2Heat shock transcription factor, Y linked 21.93.00.50.9
XM_354998Ccdc78Coiled-coil domain containing 781.21.51.31.2
NM_001033407Gm815Gene model 815, (NCBI)0.70.50.70.7
Table 12

List of genes that exhibited the highest ranking at the intermediate time point of 4 week as revealed by the MNI analysis in the muscle of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Muscle
Inflammation
NM_008355Il13Interleukin 131.31.61.31.3
NM_145544Rap1gds1RAP1, GTP-GDP dissociation stimulator 11.31.51.51.4
Cancer
NM_007831DccDeleted in colorectal carcinoma0.80.60.60.7
NM_175445Rassf2Ras association (RalGDS/AF-6) domain family 20.60.50.70.7
olfactory transduction
NM_153589Tmem16bTransmembrane protein 16B0.70.70.70.7
NM_001011862Olfr699Olfactory receptor 6990.50.40.60.7
NM_146548Olfr800Olfactory receptor 8000.70.50.60.6
NM_147105Olfr978Olfactory receptor 9780.70.50.50.7
Others
NM_175540Eda2rEctodysplasin A2 isoform receptor0.80.90.80.9
NM_010608Kcnk3Potassium channel, subfamily K, member 31.11.21.21.2
XM_129809Ogfrl1Opioid growth factor receptor-like 10.80.70.80.8
NM_011776Zp3Zona pellucida glycoprotein 31.82.01.51.4
NM_009130Scg3Secretogranin III0.60.50.70.8
NM_173732BC030440cDNA sequence BC0304401.31.21.21.2
XM_356935EG383229Predicted gene, EG3832291.31.51.21.3
XM_992003Thsd7aThrombospondin, type I, domain containing 7A1.51.31.41.4
NM_178005Lrrtm2Leucine rich repeat transmembrane neuronal 20.80.70.70.8
NM_011012Oprl1Opioid receptor-like 11.31.61.51.4
NM_028968Ifitm7Interferon induced transmembrane protein 70.60.40.60.6
NM_1752045830406J20RikRIKEN cDNA 5830406J20 gene1.61.91.71.5
NM_013903Mmp20Matrix metallopeptidase 20 (enamelysin)0.70.70.80.8
NM_177860EG329763Predicted gene, EG3297630.80.70.70.7
Table 13

List of genes that exhibited the highest ranking at the intermediate time point of 8 week as revealed by the MNI analysis in the epididymal adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Epididymal adipose tissue
Olfactory transduction
NM_146520Olfr536Olfactory receptor 5360.60.60.50.5
NM_146379Olfr654Olfactory receptor 6541.92.42.81.9
NM_001011776Olfr527Olfactory receptor 5271.71.51.81.8
Others
NM_199155Tas2r110Taste receptor, type 2, member 1101.92.52.82.8
AK138164Cntn5Contactin 50.40.40.30.5
NM_152220Stx3Syntaxin 31.81.41.81.8
NM_178924Upk1bUroplakin 1B1.41.81.81.7
NM_028622Lce1cLate cornified envelope 1C0.50.40.30.5
NM_0278159030624J02RikRIKEN cDNA 9030624J02 gene0.70.70.80.7
NM_008633Mtap4Microtubule-associated protein 41.41.41.41.2
NM_020518Vsig2V-set and immunoglobulin domain containing 22.01.82.11.8
NM_138311H1fooH1 histone family, member O, oocyte-specific0.60.60.50.5
NM_153124St8sia5ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 50.80.70.70.7
XM_898823FlncFilamin C, gamma (actin binding protein 280)0.50.50.40.4
NM_181419BC050092cDNA sequence BC0500922.23.42.82.6
XM_001004783EG544848Predicted gene, EG5448480.50.60.50.5
NM_009608Actc1Actin, alpha, cardiac1.82.32.72.3
NM_010203Fgf5Fibroblast growth factor 50.50.50.50.5
NM_011827HcstHematopoietic cell signal transducer2.02.22.01.7
NM_026825Lrrc16Leucine rich repeat containing 161.41.51.71.5
NM_029415Slc10a6Solute carrier family 10 (sodium/bile acid cotransporter family), member 60.50.40.30.5
U10093Klra7Killer cell lectin-like receptor, subfamily A, member 71.21.21.21.2
NM_007379Abca2ATP-binding cassette, sub-family A (ABC1), member 20.50.60.50.4
NM_001039878StrnStriatin, calmodulin binding protein 40.60.60.50.6
Table 14

List of genes that exhibited the highest ranking at the intermediate time point of 8 week as revealed by the MNI analysis in the subcutaneous adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Subcutaneous adipose tissue
Insulin resistance
NM_007501Neurod4Neurogenic differentiation 40.80.80.60.7
Inflammation
NM_027185Def6Differentially expressed in FDCP 61.92.03.01.7
Cancer
NM_008999Rab23RAB23, member RAS oncogene family0.80.80.60.7
olfactory transduction
NM_147018Olfr1056Olfactory receptor 10560.80.90.70.8
NM_146279Olfr960Olfactory receptor 9601.41.61.71.9
NM_001011857Olfr685Olfactory receptor 6850.80.80.70.9
NM_146764Olfr1408Olfactory receptor 14080.60.60.70.7
Others
NM_153111FevFEV (ETS oncogene family)0.70.50.40.6
NM_080644Cacng5Calcium channel, voltage-dependent, gamma subunit 50.60.60.40.5
NM_153592Erlin2ER lipid raft associated 21.31.31.61.3
NM_183036Defb38Defensin beta 381.62.12.82.0
NM_207022Tas2r118Taste receptor, type 2, member 1182.01.62.92.1
XM_132900LOC625758Hypothetical LOC6257582.02.42.61.5
NM_001008424CdsnCorneodesmosin0.80.70.60.7
NM_025346Rmnd5bRequired for meiotic nuclear division 5 homolog B (S. cerevisiae)1.61.92.82.0
NM_176846Exph5Exophilin 50.50.70.50.5
NM_146107Actr1bARP1 actin-related protein 1 homolog B (yeast)0.50.60.30.6
XM_986681Sytl2Synaptotagmin-like 21.31.51.31.4
XM_618920LOC544808Hypothetical LOC5448081.71.61.71.9
XM_110525Cnksr1Connector enhancer of kinase suppressor of Ras 11.31.51.41.3
NM_172263Pde8bPhosphodiesterase 8B0.80.70.60.8
NM_025638Gdpd1Glycerophosphodiester phosphodiesterase domain containing 10.30.40.50.4
NM_0265202900009I07RikRIKEN cDNA 2900009I07 gene0.80.70.50.7
Table 15

List of genes that exhibited the highest ranking at the intermediate time point of 8 week as revealed by the MNI analysis in the muscle of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Muscle
Insulin resistance
NM_016961Mapk9Mitogen activated protein kinase 90.80.70.60.8
Cancer
NM_022032PerpPERP, TP53 apoptosis effector0.60.70.50.7
NM_026840PdgfrlPlatelet-derived growth factor receptor-like0.80.70.70.8
Olfactory transduction
NM_146686Olfr232Olfactory receptor 2320.60.60.60.7
NM_146560Olfr872Olfactory receptor 8721.31.31.31.2
Others
NM_027462Wars2Tryptophanyl tRNA synthetase 2 (mitochondrial)0.70.80.60.7
XM_903020Osbpl7Oxysterol binding protein-like 71.21.41.61.4
XM_484317EG432803Predicted gene, EG4328030.70.80.60.8
NM_001031772Lin28Lin-28 homolog B (C. elegans)0.70.70.70.7
NM_001001602Dab2ipDisabled homolog 2 (Drosophila) interacting protein1.51.92.21.5
NM_145582Atpbd3ATP binding domain 30.70.60.60.6
AK014527Cep192Centrosomal protein 1921.31.41.61.3
NM_028127Frmd6FERM domain containing 60.60.70.60.8
NM_1722866430548M08RikRIKEN cDNA 6430548M08 gene1.21.21.21.1
NM_011105PkdrejPolycystic kidney disease (polycystin) and REJ (sperm receptor for egg jelly, sea urchin homolog)-like1.51.92.02.2
XM_983096LOC666331Hypothetical protein LOC6663311.21.31.61.4
NM_024196Tbc1d2TBC1 domain family, member 200.80.80.70.8
NM_198306Galnt9UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 90.80.61.00.7
AK014852Glb1Galactosidase, beta 1 like 31.41.41.41.5
NM_001004182EG434008Predicted gene, EG4340080.80.70.70.7
NM_011284Rpa2Replication protein A21.61.51.91.4
NM_025381Atp6v1fATPase, H+ transporting, lysosomal V1 subunit F1.41.31.31.4
NM_010571Irs3Insulin receptor substrate 30.60.70.60.8
Figure 7

Results of MNI analysis at week 12.

Genes that exhibited increasing ranking across time points as revealed by the MNI analysis, with a peak at 12 week in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Table 16

List of genes that exhibited increasing ranking across time points as revealed by the MNI analysis, with a peak at 12 week in the epididymal adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Epididymal adipose tissue
NM_175236Adhfe1Alcohol dehydrogenase, iron containing, 10.60.60.70.6
AF015260Smad7MAD homolog 7 (Drosophila)0.70.60.70.5
Inflammation
NM_008035Folr2Folate receptor 2 (fetal)0.70.70.70.6
NM_008802Pde7aPhosphodiesterase 7A2.11.92.22.7
NM_009511Vipr2Vasoactive intestinal peptide receptor 22.22.02.01.8
Cancer
NM_008586Mep1bMeprin 1 beta0.50.50.50.3
NM_181321Tmc6Transmembrane channel-like gene family 61.81.81.72.3
Olfactory transduction
NM_008763Olfr16Olfactory receptor 161.42.51.22.3
NM_001011695Olfr1000Olfactory receptor 10002.22.22.53.0
Others
NM_139270Pthr2Parathyroid hormone receptor 22.23.12.82.4
NM_172434Tnrc4Trinucleotide repeat containing 41.31.51.41.5
NM_173402Rgs12Regulator of G-protein signaling 120.70.70.70.5
XM_977897B230217C12RikRIKEN cDNA B230217C12 gene1.81.41.81.8
EG433070EG433070Predicted gene, EG4330701.71.82.02.5
NM_175259Tmem58Transmembrane protein 581.51.31.51.6
NM_026412D2Ertd750eDNA segment, Chr 2, ERATO Doi 750, expressed0.70.60.70.6
NM_181323C130090K23RikRIKEN cDNA C130090K23 gene1.51.41.81.5
NM_175406Atp6v0d2ATPase, H+ transporting, lysosomal V0 subunit D21.41.41.51.3
NM_007725Cnn2Calponin 20.60.60.60.5
NM_001033274Brd1Bromodomain containing 11.72.22.22.3
Table 17

List of genes that exhibited increasing ranking across time points as revealed by the MNI analysis, with a peak at 12 week in the subcutaneous adipose tissue of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Subcutaneous adipose tissue
Inflammation
NM_001024852Auts2Autism susceptibility candidate 20.80.90.80.5
NM_001033536Rfxdc2Regulatory factor X domain containing 2 homolog (human)1.21.41.31.4
NM_009701Aqp5Aquaporin 50.70.70.80.6
XM_285901Gm792Gene model 792, (NCBI)0.70.60.50.4
NM_019775Cpb2Carboxypeptidase B2 (plasma)1.71.61.52.5
Cancer
NM_009050RetRet proto-oncogene1.21.31.21.5
Olfactory transduction
NM_146604Olfr716Olfactory receptor 7161.91.72.03.1
NM_146963Olfr45Olfactory receptor 451.61.51.92.2
Others
NM_178046SvilSupervillin0.70.80.70.6
NM_018764Pcdh7Protocadherin 71.51.41.31.8
NM_030061Spink12Serine peptidase inhibitor, Kazal type 121.41.41.31.7
NM_178741Klhl8Kelch-like 8 (Drosophila)1.31.31.31.6
NM_175696C530028O21RikRIKEN cDNA C530028O21 gene1.31.31.21.5
NM_1777114932411G14RikRIKEN cDNA 4932411G14 gene0.70.60.70.5
NM_181579Pof1bPremature ovarian failure 1B1.71.81.62.2
XM_4896124921511H13RikRIKEN cDNA 4921511H13 gene1.31.41.21.6
NM_172456Endogl1Endonuclease G-like 11.61.91.42.2
NM_001033488Gm1964Gene model 1964, (NCBI)1.51.41.51.5
NM_181318Rasgef1bRasGEF domain family, member 1B0.70.80.80.6
NM_183017Ttll12Tubulin tyrosine ligase-like family, member 120.80.60.70.7
NM_010075Dpp6Dipeptidylpeptidase 61.11.21.21.3
NM_026175Sf3a1Splicing factor 3a, subunit 11.51.41.71.9
Table 18

List of genes that exhibited increasing ranking across time points as revealed by the MNI analysis, with a peak at 12 week in the muscle of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Muscle
Insulin resistance
NM_145435PyyPeptide YY1.41.41.31.5
Inflammation
NM_138648Olr1Oxidized low density lipoprotein (lectin-like) receptor 10.50.60.50.3
NM_009132ScinScinderin0.60.60.70.7
Cancer
NM_145833Lin28Lin-28 homolog (C. elegans)0.70.70.70.7
NM_010358Gstm1Glutathione S-transferase, mu 11.31.41.41.3
NM_001029979Safb2Scaffold attachment factor B20.70.70.70.6
Olfactory transduction
NM_146750Olfr689Olfactory receptor 6890.60.70.70.5
NM_146943Olfr347Olfactory receptor 3471.21.31.21.5
Others
NM_009372Tgif1TG interacting factor 11.21.10.80.6
XM_887155Igsf10Immunoglobulin superfamily, member 100.70.50.60.4
NM_009418Tpp2Tripeptidyl peptidase II1.21.41.21.5
NM_008118GifGastric intrinsic factor0.80.70.70.8
NM_026972Cd209bCD209b antigen0.90.80.60.7
NM_145358Camkk2Calcium/calmodulin-dependent protein kinase kinase 2, beta1.21.21.31.2
BC051526Cd22CD226 antigen0.80.90.90.7
NM_0299464931407K02RikRIKEN cDNA 4931407K02 gene1.31.11.21.3
NM_1726524632411B12RikRIKEN cDNA 4632411B12 gene1.71.41.41.9
NM_011598Fabp9Fatty acid binding protein 9, testis0.80.80.90.7
NM_011023Otx1Orthodenticle homolog 1 (Drosophila)0.70.70.70.5
NM_019579Mpp5Membrane protein, palmitoylated 50.50.50.60.3
NM_007555Bmp5Bone morphogenetic protein 50.90.90.80.8
NM_001039047Trim58Tripartite motif-containing 581.31.21.51.5
NM_020049Slc6a14Solute carrier family 6 (neurotransmitter transporter), member 140.80.60.70.6
Figure 8

Results of MNI analysis throughout the time course.

Genes that exhibited a constant high MNI ranking throughout the time course as revealed by the MNI analysis in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Table 19

List of genes that exhibited a constant high MNI ranking throughout the time course as revealed by the MNI analysis in the peripheral tissues of mice.

Gene accession No.Gene symbolDescriptionFold change (HFD/ND)
2wk4wk8wk12wk
Epididymal adipose tissue
Insulin resistance
NM_001039138Camk2gCalcium/calmodulin-dependent protein kinase II gamma0.60.50.60.5
Others
NM_145463Tmem46Transmembrane protein 460.60.60.70.6
Subcutaneous adipose tissue
olfactory transduction
NM_207566Olfr1173Olfactory receptor 11732.02.31.92.7
NM_146709Olfr411Olfactory receptor 4111.51.41.41.6
NM_146524Olfr855Olfactory receptor 8551.71.62.01.6
Others
NM_178110Trim62Tripartite motif-containing 621.61.81.61.8
Muscle
Cancer
NM_024124Hdac9Histone deacetylase 90.60.50.60.6
Others
NM_177861Tmem67Transmembrane protein 670.70.60.70.5

Results of MNI analysis at week 2.

Genes that exhibited decreasing ranking across time points as revealed by the MNI analysis, with a peak at 2 week in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Results of MNI analysis at week 4.

Genes that exhibited the highest rank at the intermediate time point of 4 week as revealed by the MNI analysis in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Results of MNI analysis at week 8.

Genes that exhibited the highest rank at the intermediate time point of 8 week as revealed by the MNI analysis in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Results of MNI analysis at week 12.

Genes that exhibited increasing ranking across time points as revealed by the MNI analysis, with a peak at 12 week in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Results of MNI analysis throughout the time course.

Genes that exhibited a constant high MNI ranking throughout the time course as revealed by the MNI analysis in the peripheral tissues of mice. (A) Epididymal adipose tissue. (B) Subcutaneous adipose tissue. (C) Muscle.

Discussion

Animals use their olfactory system to monitor the chemical environment for molecules that reveal food sources or toxic substances and signal the presence of predators [11]. There are numerous olfactory receptors of different types, with as many as 1,000 in the mammalian genome that represent approximately 3% of the human genomeentire genetic information [12]. The information related to odor gathered by these olfactory receptors is funneled through a common signaling pathway. When an olfactory receptor binds to its odorant, it activates a single species of G protein, the olfactory trimeric G protein (Golf), which in turn activates the olfactory isoform of adenylate cyclase (AC3) [12]. Converging evidence has demonstrated that the olfactory system is a target for hormones related to metabolism and food-intake regulation; it adapts its function to nutritional needs by promoting or inhibiting food foraging [13]. Recent studies have found that obese patients display decreased olfactory acuity [14] and are significantly more likely to have absolute olfactory dysfunction or anosmia [15]. Furthermore, Simchen et al. showed that the abilities to detect and identify odors have been found to decrease as body mass index (BMI) increases in subjects less than 65 years old, independent of any linkage to food odor or gender [16]. Recently, the elements of olfactory-like chemosensory signaling have been found to also present in nonolfactory tissues such as testis [17], brain [18], and heart [19]. To our knowledge, this is the first study that shows a differential mRNA expression and high MNI ranking of olfactory receptors in the epididymal and subcutaneous fat tissues and muscles between ND and HFD-fed mice (Tables 1, 2, 3). These results imply that the olfactory receptors and the molecules involved in olfactory transduction might be the mediators of HFD-induced obesity progression in the peripheral tissues. This hypothesis is supported by the fact that the increased cAMP production by AC3 activates cAMP responsive element binding (CREB) protein, leading to increased adipogenesis in an obese mouse model. Furthermore, mice lacking AC3, which is a downstream regulator of olfactory receptors, exhibit obesity that is apparently caused by low locomotor activity, hyperphagia, and leptin insensitivity [20]. In future studies, it will be intriguing to further investigate the role of individual olfactory receptors in peripheral tissues, such as the pancreas, liver, muscle, and fat, to better understand the activation process of these signaling pathways and their physiological roles. Cancer-related genes such as Nek11, A4gnt, Srp9, Gli2, Gucy2c, Lsm1, Duoxa1, Lasp1, Ret, Bex2, Vav3, Kcnrg, Tle6, Rab23, Dcc, Rassf2, Perp, Pdgfr1, Lin28, Gstm1, Safb2, Tmem46, and Hdac9 were remarkably overrepresented in time-course clusters identified by the MNI analysis in the epididymal and subcutaneous fat tissues and gastrocnemius muscle of mice with diet-induced obesity (Figs. 4, 5, 6, 7, 8). Of these 23 genes, 6 are known breast cancer-related genes (Lsm1, Duoxa1, Ret, Bex2, Rassf2, and Safb2). Lsm1 is a transforming oncogene that is amplified and overexpressed in breast cancer [21] and might affect either cell cycle progression or apoptosis [22]. Duoxa1, which was originally identified as a numb-interacting protein, was recently shown to function as a maturation factor in breast cancer [23]. Ret exhibits both estrogen- and retinoic acid-dependent transcriptional modulation in breast cancer [24]. Bex2 has a significant role in promoting cell survival and growth in breast cancer cells [25], [26], and Rassf2 might function as a tumor suppressor gene in in vitro cell migration and cell cycle progression [27]. The expression of Safb2 protein, which functions as estrogen receptor co-repressor and growth inhibitor, was lost in approximately 20% of breast cancers [28]. Many studies have attempted to determine the relationship between diet and breast cancer. Dietary fat is a source of endogenous estrogen and has been suggested as a possible risk factor for breast cancer [29]. To our knowledge, this is the first study showing an association between these 6 genes involved in breast cancer development and HFD-induced obesity in a rodent model. Colon cancer-related genes such as Nek11, Gucy2c, Srp9, Tle6, and Pdgfrl were also overrepresented in the time-course clusters identified by the MNI analysis in the epididymal and subcutaneous fat tissues and gastrocnemius muscle of mice with diet-induced obesity (Figs. 4, 5, 6, 7, 8). Nek11, a member of the NIMA-related kinase family, phosphorylates Cdc25a and controls its degradation; Cdc25a phosphorylation is required for cell cycle progression in colorectal cancer cells [30]. Gucy2c and Srp9 have been shown to be overexpressed in colorectal cancer cells and were recently shown to function as a candidate biomarker for colon cancer [31], [32]. Tle6 is recurrently overexpressed in human colon cancer and enhances cell proliferation, colony formation, migration, and xenograft tumorigenicity [33]. Pdgfrl acts as a tumor suppressor and inhibits the growth of colorectal cancer cells [34]. Epidemiological studies indicate that both high body weight and high body mass index (BMI) were significantly associated with an increased colon cancer risk. Intra-abdominal visceral obesity, high plasma glucose levels, HbA1C, and C-peptide were also found to be associated with increased risk of colorectal cancer [35]–[38]. The current study showed that the above-mentioned genes that are involved in the regulation of colon cancer might play a genetic role in the development of obesity. No mechanistic insights have been reported to explain the relationship between the regulation of cancer-related genes in the adipose tissue or muscle and cancer susceptibility. It could be probable that the changes in the expression of cancer-related genes in the adipose tissue may accompany the regulation of same genes in epithelial tissues such as breast or colon. Genes that were found to have the highest rank at the early phase and return to baseline after several weeks might be considered genetic mediators of acute-phase response in metabolic processes related to HFD-induced obesity. Dusp12 was one of the 58 genes that were observed to have decreasing ranking during the development of obesity, with a peak at 2 week. Previous studies identified several single nucleotide polymorphisms in this gene associated with type 2 diabetes in different populations, including Caucasians and Chinese [39]. Dusp12 is a glucokinase-associated protein that participates in glycolysis in the liver and dephosphorylation of cytoplasmic glucokinase in the pancreatic beta cells [40]. Therefore, Dusp12 might play a role in the regulation of glycolysis during the early stages of obesity. When glycolysis was decreased, whole-body glucose disposal was also reduced, indicating a decrease in glucose utilization in the peripheral tissues in response to the HFD. The latter likely results from an impaired glucose transport that precedes impaired insulin signaling. Def6 and Mapk9 were one of the 145 genes that were found to have the highest rank at the intermediate time points of 4 or 8 weeks during the development of obesity. Def6, a novel type of activator for Rho GTPase, is expressed in myeloid cells, and disruption of Def6 expression leads to defects in toll-like receptor 4 (TLR4) signaling and innate immune responses [41]. Rho GTPases have been shown to be recruited to the cytosolic domain of TLR and the closely related interleukin 1 receptor (IL-1R) and to regulate the production of proinflammatory cytokines [42], [43]. In the present study, the high MNI ranking of Def6 in the subcutaneous adipose tissue of HFD-fed mice suggested that it might participate in the regulation of obesity-induced inflammation through TLR4 signaling. Mapk9, which is ubiquitously expressed, can invoke transcription factors such as c-Jun and many other apoptosis-related proteins [44]. Interestingly, recent studies have shown that the knockdown of Mapk9 leads to reduced serum levels of glucose, insulin, and homeostatic model assessment and therefore reverses insulin resistance in HFD-fed mice [45]. These findings provide supporting evidences to the high MNI ranking of Mapk9 associated with HFD-induced obesity observed in the present study. However, further studies are required to elucidate the precise function of Mapk9 in the development of HFD-induced type 2 diabetes. Smad7, Adhfe1, and Pyy are one of the 65 genes that showed increasing ranking during the development of obesity, with a peak at 12 weeks. Smad7 was initially characterized as a factor induced by shear stress in vascular endothelial cells [46]. Only recently, new functions of Smad7 were elucidated: it inhibits transforming growth factor-β (TGF-β)-activated responses [46]. TGF-β is known to inhibit adipose differentiation of preadipocyte cell lines and primary cultures [47] and to block adipogenesis in vivo [48]. This suggests that Smad7 enhances adipogenesis through the inhibition of TGF-β signaling. Adhfe1 was characterized as a hydroxyacid-oxoacid transhydrogenase that catalyzes the conversion of γ-hydroxybutyrate to succinic semialdehyde [49]. Recently, Adhfe1 was suggested to play a role in adipocyte differentiation. The expression of Adhfe1 transcript is tightly linked to the phenotype of mature adipocytes both in vivo and in vitro, although the mechanisms underlying Adhfe1-mediated regulation of adipogenesis remain poorly understood [50]. Pyy, which is expressed and secreted in endocrine intestinal cells, plays a role in reducing appetite and caloric intake [51]. Recently, plasma Pyy concentrations were found to be decreased in both obese humans [52] and diet-induced obese mice [53]. These studies might suggest that Smad7 and Adhfe1 play a role in obesity by amplifying the aggressive effect of adipogenesis. Camk2g and Tmem67 are one of the 8 genes that exhibited a constant high MNI ranking from 2 to 12 weeks. The increase of cytosolic Ca2+ in the beta cells is central to the initiation of insulin secretion under physiological conditions [54]. Recent findings suggest that Camk2g involved in the regulation of calcium in the islet beta cells is a candidate gene for type 2 diabetes [55]. The Tmem67 gene mediates a fundamental developmental stage of ciliary formation and epithelial morphogenesis [56]. In addition, defects in the Tmem67 gene resulted in Meckel syndrome type 3, Joubert syndrome type 6, and nephronophthisis 11, which show many clinical phenotypic similarities, including hepatic fibrosis [56], [57]. Consumption of fat-rich diets seems to play an important role in the pathogenesis of hepatic steatosis and its progression to fibrosis [58]. The constantly high MNI ranking of Tmem67 from 2 to 12 weeks associated with a HFD suggests that Tmem67 might participate in the development of hepatic fibrosis. In summary, this study is the most comprehensive investigation of the gene expression patterns conducted using a time-resolved approach to gain insight into the development of HFD-induced obesity in a mouse model. A reverse-engineered gene network was used for the first time for the identification of key genetic mediators and pathways that have been implicated in the initiation and advancement of obesity. We highlighted the sequential induction of distinct olfactory receptors and stimulation of cancer-related genes during the development of obesity. To our knowledge, the proposed changes in the olfactory transduction machinery as per the MNI ranking have not been previously reported. These putative mechanisms clearly need further investigation. The top 5 genes recognized through the MNI analysis at each time points (2, 4, 8, and 12 weeks) and gene clusters identified based on their temporal patterns in the 3 different tissues (visceral and subcutaneous adipose tissues and muscle) of mice need special attention as potential genetic mediators for obesity progression. The basal expression levels of some target genes identified by MNI analysis. Quantitative real-time PCR analysis of the basal expression on highly ranked olfactory genes and top 5 genes at week 4 in the epididymal adipose tissues of (A) ND- or (B) HFD-fed mice. Results are presented as the average ± SEM of at least 3 separate experiments. (TIF) Click here for additional data file.
  58 in total

Review 1.  Steroid hormone receptors in cancer development: a target for cancer therapeutics.

Authors:  Nihal Ahmad; Raj Kumar
Journal:  Cancer Lett       Date:  2011-01-01       Impact factor: 8.679

2.  Expression and functional characterization of platelet-derived growth factor receptor-like gene.

Authors:  Feng-Jie Guo; Wei-Jia Zhang; Ya-Lin Li; Yan Liu; Yue-Hui Li; Jian Huang; Jia-Jia Wang; Ping-Li Xie; Guan-Cheng Li
Journal:  World J Gastroenterol       Date:  2010-03-28       Impact factor: 5.742

3.  NEK11: linking CHK1 and CDC25A in DNA damage checkpoint signaling.

Authors:  Claus Storgaard Sørensen; Marina Melixetian; Ditte Kjaersgaard Klein; Kristian Helin
Journal:  Cell Cycle       Date:  2010-02-03       Impact factor: 4.534

4.  Impaired postprandial releases/syntheses of ghrelin and PYY(3-36) and blunted responses to exogenous ghrelin and PYY(3-36) in a rodent model of diet-induced obesity.

Authors:  Junying Xu; Terry A McNearney; J D Z Chen
Journal:  J Gastroenterol Hepatol       Date:  2011-04       Impact factor: 4.029

5.  Disruption of the Jnk2 (Mapk9) gene reduces destructive insulitis and diabetes in a mouse model of type I diabetes.

Authors:  Anja Jaeschke; Mercedes Rincón; Beth Doran; Judith Reilly; Donna Neuberg; Dale L Greiner; Leonard D Shultz; Aldo A Rossini; Richard A Flavell; Roger J Davis
Journal:  Proc Natl Acad Sci U S A       Date:  2005-05-02       Impact factor: 11.205

6.  Gastric bypass does not influence olfactory function in obese patients.

Authors:  Brynn E Richardson; Eric A Vanderwoude; Ranjan Sudan; Donald A Leopold; Jon S Thompson
Journal:  Obes Surg       Date:  2012-02       Impact factor: 4.129

7.  Polycystic kidney and hepatic disease with mental retardation is nephronophthisis 11 caused by MKS3/TMEM67 mutations.

Authors:  Tomás Seeman; Eva Seemanová; Gudrun Nuernberg; Peter Nuernberg; Sabine Janssen; Edgar A Otto
Journal:  Pediatr Nephrol       Date:  2010-07-06       Impact factor: 3.714

8.  BEX2 regulates mitochondrial apoptosis and G1 cell cycle in breast cancer.

Authors:  Ali Naderi; Ji Liu; Ian C Bennett
Journal:  Int J Cancer       Date:  2010-04-01       Impact factor: 7.396

9.  GUCY2C reverse transcriptase PCR to stage pN0 colorectal cancer patients.

Authors:  Alex Mejia; Stephanie Schulz; Terry Hyslop; David S Weinberg; Scott A Waldman
Journal:  Expert Rev Mol Diagn       Date:  2009-11       Impact factor: 5.225

10.  Lack of association between genetic polymorphisms within DUSP12 - ATF6 locus and glucose metabolism related traits in a Chinese population.

Authors:  Cheng Hu; Rong Zhang; Congrong Wang; Xiaojing Ma; Jie Wang; Yuqian Bao; Kunsan Xiang; Weiping Jia
Journal:  BMC Med Genet       Date:  2011-01-06       Impact factor: 2.103

View more
  6 in total

Review 1.  Therapeutic potential of ectopic olfactory and taste receptors.

Authors:  Sung-Joon Lee; Inge Depoortere; Hanns Hatt
Journal:  Nat Rev Drug Discov       Date:  2019-02       Impact factor: 84.694

2.  Piperine, a component of black pepper, decreases eugenol-induced cAMP and calcium levels in non-chemosensory 3T3-L1 cells.

Authors:  Yeo Cho Yoon; Sung-Hee Kim; Min Jung Kim; Hye Jeong Yang; Mee-Ra Rhyu; Jae-Ho Park
Journal:  FEBS Open Bio       Date:  2014-11-27       Impact factor: 2.693

3.  Olfactory receptor 10J5 responding to α-cedrene regulates hepatic steatosis via the cAMP-PKA pathway.

Authors:  Tao Tong; Sang Eun Ryu; Yeojin Min; Claire A de March; Caroline Bushdid; Jérôme Golebiowski; Cheil Moon; Taesun Park
Journal:  Sci Rep       Date:  2017-08-25       Impact factor: 4.379

4.  Olfactory receptor gene abundance in invasive breast carcinoma.

Authors:  Shirin Masjedi; Laurence J Zwiebel; Todd D Giorgio
Journal:  Sci Rep       Date:  2019-09-24       Impact factor: 4.379

5.  Identification and characterization of novel single nucleotide polymorphism markers for fat deposition in muscle tissue of pigs using amplified fragment length polymorphism.

Authors:  Pantaporn Supakankul; Tanavadee Kumchoo; Supamit Mekchay
Journal:  Asian-Australas J Anim Sci       Date:  2016-09-09       Impact factor: 2.509

6.  Regulation of Adipogenesis and Thermogenesis through Mouse Olfactory Receptor 23 Stimulated by α-Cedrene in 3T3-L1 Cells.

Authors:  Tao Tong; Jinju Park; Cheil Moon; Taesun Park
Journal:  Nutrients       Date:  2018-11-16       Impact factor: 5.717

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.