systems and classical biology approaches unraveled role of ......2020/07/29 · systems and...

Systems and classical biology approaches unraveled role of

olfactory receptors in progression of kidney fibrosis

Ali Motahharynia1, Shiva Moein1, 2 *, Farnoush Kiyanpour1, Kobra Moradzadeh1, Yousof Gheisari1, 2

1. Regenerative Medicine Research Center, Isfahan University of Medical Sciences,

Isfahan, Iran 2. Department of Genetics and Molecular Biology, Isfahan University of Medical

Sciences, Isfahan, Iran

* Corresponding Author:

Shiva Moein, PhD. Regenerative Medicine Research Center, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran Tel/Fax: +98-3136687087. Email: [email protected] ORCID: 0000-0002-6019-9504

.CC-BY-NC-ND 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is

The copyright holder for this preprintthis version posted August 7, 2020. ; https://doi.org/10.1101/2020.07.29.225425doi: bioRxiv preprint

https://doi.org/10.1101/2020.07.29.225425

http://creativecommons.org/licenses/by-nc-nd/4.0/

Abstract

The olfactory receptors (ORs) which are mainly known as odor-sensors in the olfactory

epithelium are distributed in several non-sensory tissues. Despite the specified role of some

of these receptors in normal physiology of the kidney, little is known about their potential

effect in renal disorders. In this study, using the holistic view of systems biology, it was

determined that ORs are significantly changed during the progression of kidney fibrosis.

For further validation, common differentially expressed ORs resulted from reanalysis of two

time-course microarray datasets were selected for experimental evaluation in a validated

murine model of unilateral ureteral obstruction. Transcriptional analysis demonstrated

considerable changes in the expression pattern of Olfr433, Olfr129, Olfr1393, and Olfr161

during the progression of kidney fibrosis. In conclusion, our results highlight the impact of

systems biology in determination of the underlying mechanisms of chronic diseases and

indicate the importance of time-course approaches to unravel the patterns of gene

expression. The novel ORs proposed in this study could be the subject of further functional

investigations in the kidney.

Key words: Chronic Renal Failure; Systems Biology; Microarray; Gene Network Analysis;

Olfactory Receptor; obstruction-induced renal fibrosis



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Introduction

Olfactory receptors (ORs), belonging to a super-family of G protein-coupled receptors,

are well-recognized for their role in odor-sensation in the olfactory epithelium (OE). This

family of receptors was first discovered by Linda Buck and Richard Axel, leading to a Nobel

prize in 2004 (Buck & Axel, 1991; Watts, 2004). More investigations on ORs determined

that they are not only expressed in the OE but also non-sensory organs (Massberg & Hatt,

2018). The study by Parmentier et al. determined the functionality of these receptors in

sperm chemotaxis during fertilization (Parmentier et al., 1992). Furthermore, it was

demonstrated that these receptors have roles in cytoskeletal remodeling, pulmonary

hyperplasia (An & Liggett, 2018), angiogenesis (Kim et al., 2015), as well as heart

metabolism in the cardiovascular system (Jovancevic et al., 2017). Besides, identification

of the role of these receptors in other parts of the body, such as skin (Busse et al., 2014;

Gelis et al., 2016; Tsai et al., 2017), gastrointestinal tract (Braun, Voland, Kunz, Prinz, &

Gratzl, 2007; Kalbe et al., 2016; C. Wu et al., 2015), and the immune system (Clark,

Nurmukhambetova, Li, Munger, & Lees, 2016; Li et al., 2013) highlights the importance of

further investigations on their function in the body.

One of the tissues, in which the presence and function of ORs is investigated, is the

kidney (Halperin Kuhns et al., 2019; Miyamoto et al., 2016; Peti-Peterdi, Kishore, &

Pluznick, 2016; Pluznick et al., 2009; Rajkumar, Aisenberg, Acres, Protzko, & Pluznick,

2014; Shepard & Pluznick, 2017). Studies using unsupervised high-throughput techniques

have discovered the existence of these receptors in the kidney (Feldmesser et al., 2006;

Flegel, Manteniotis, Osthold, Hatt, & Gisselmann, 2013). Nevertheless, few studies have

specifically focused on their role in renal function. The study by Pluznick et al. determined

the Olfr78 role in blood pressure regulation through interactions with the byproducts of gut

microbiota (Pluznick et al., 2013). Furthermore, Shepard et al. demonstrated that Olfr1393

participates in glucose transportation in both normal and pathological states of the kidney

(Shepard et al., 2016; Shepard, Koepsell, & Pluznick, 2019). Considering the magnitude of

this gene family (around 1000 genes in the mouse and 400 genes in the human) as well as

their role in chemo-sensation, more investigations are needed to uncover the role of other

OR subtypes in kidney function and hemostasis (Halperin Kuhns et al., 2019; Shepard &

Pluznick, 2016).

In order to understand key molecular mechanisms underlying the progression of kidney

fibrosis, a time-course microarray dataset was reanalyzed. Studying the modular structure

of the constructed network determined a subset of ORs with a significant change in

expression. Likewise, this finding was additionally confirmed by analysis of another time-

course dataset with similar traits. Experimental evaluation of common ORs between two



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datasets determined incremental expression patterns during progression of kidney fibrosis.

These results provide an initial clue about the importance of ORs functions in the

progression of kidney fibrosis.

Results

In order to investigate the underlying molecular mechanisms activated during the

progression of chronic kidney disease, two time-course microarray datasets, GSE36496 and

GSE96571 were analyzed. GSE36496 contains transcriptomic data of the UUO and sham-

operated C57BL/6 mice at days 1, 2, 5, and 9 post-operation. The results of this study by

Wu et al. suggest CEBPB and HNF4A signaling pathways as important regulators of kidney

fibrosis (B. Wu & Brooks, 2012). The other dataset, GSE96571 which is also deposited by

Wu et al. comprises the UUO and sham samples at hours 0.5, 1, 3, 5, 7, 12 as well as days

1,3,5, and 7 post-operation. The single-time point analysis of this dataset by Wu et al.

determined overexpression of stress responder genes in the first hours of obstruction besides

nephrotoxic damage-related genes at later time points (B. Wu et al., 2018). This dataset was

used for validation of our findings from the first dataset.

Unsupervised evaluation of microarray dataset determined high quality of the fibrotic

model

The quality assessment of the GSE36496 dataset by PCA demonstrated the separation of

sham and UUO groups from each other. Furthermore, the UUO samples were separated

based on the times of harvest, which determines the model quality (Figure 1a). This result

was also validated by the hierarchical clustering (Figure 1b). The DEGs were determined

using the LIMMA Package of R software, which according to our recent study, is the most

reliable tool for the time-course analysis of microarray data (Moradzadeh, Moein, Nickaeen,

& Gheisari, 2019). A Comparison of the UUO and sham samples determined 2583 DEGs

with an adjusted p-value < 0 .05. The DEGs were used for the construction of a gene

interaction network and further topological analysis (Figure 1c).

ORs constitute a dense module in the interactome map of kidney fibrosis

In order to discover the functional units of the network, module analysis was performed.

Modules are individual units of biological network, which are similar in physical, chemical,

or functional aspects and supposed to have a specific function in the networks (Choobdar et

al., 2019; Lecca & Re, 2015). Assessment of densely connected regions of the network,

based on the clustering coefficient, revealed 36 significant modules. The first and second

modules were mainly related to Nduf and ORs signaling pathways (Figure 1d and e).



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NADH:ubiquinone oxidoreductase supernumerary subunits (NDUF) family of genes are

expressed in the mitochondria and their relation to kidney fibrosis has previously been

demonstrated by Granata et al. (Granata et al., 2009). The relationship between ORs and

progression of chronic renal failure has also been investigated by only one study which

determined the contribution of Olfr1393 in diabetes (Shepard et al., 2019).

For further investigation on the role of ORs in kidney fibrosis, another time-course UUO

dataset was analyzed. LIMMA results determined 3176 DEGs (adjusted p-value < 0.05),

which were further used for construction of a gene interaction network (Figure 1f).

Topological analysis of the constructed network revealed 44 significant modules, of which

ORs-related module obtained the first rank (Figure 1g). For validation of the results of

microarray data analysis, common differentially expressed ORs (Olfr433, Olfr129,

Olfr1393, Olfr161, and Olfr622) between two datasets were selected for in vivo expression

analysis (figure 1h).

Histopathological analysis of the UUO model validated the robustness of the

constructed model

In order to experimentally evaluate the expression of selected ORs, mouse model of

UUO was performed. Both UUO and sham-operated mice were followed over 21 days

(Figure 2a). For validation of the quality of the constructed model, the histopathological

analysis was done. Assessment of the sections revealed significant diffused tubulointerstitial

fibrosis along with glomerular injuries, increased mesangial matrix, and diffused

glomerulosclerosis in UUO-operated mice compared to the sham group over 21 days of

UUO treatment (p-value < 0.05), all of which determined the robustness of constructed

UUO model (Figure 2b and c).

Gene expression patterns demonstrated significant changes in ORs in the fibrotic

kidney

As ORs belong to a highly conserved superfamily which most of them have a similar

sequence, the specificity of designed primers was checked and validated by sanger

sequencing (Supplementary data 1).

The expression of Olfr433, Olfr129, Olfr1393, Olfr161, and Olfr622 was evaluated over

21 days in a time-course manner in both UUO and sham-operated mice (Figure 3). Except

for Olfr1393, other genes demonstrated upregulation over time in comparison to the sham

group. To test whether these changes between the sham and UUO group were significant

during time, a two-way ANOVA analysis was applied. The results of the analysis



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determined significant changes in patterns of expression in the UUO group compared to

sham for all the genes except for Olfr622 (p-value < 0.05).

Considering the patterns of expression over time revealed that Olfr433, Olfr129, Olfr161,

and Olfr622 had a sharp downregulation from day 3 to day 6. Although Olfr433 and Olfr161

expression continued with a smoother augmenting response, Olfr129 and Olfr622 had a

second sharp peak at day 12 followed by a reduction in the consecutive days. Furthermore,

the expression of sham in these four genes over time revealed oscillatory patterns, which is

an initial clue about the inherent rhythmic pattern of OR genes in the kidney.

Discussion

In order to acquire a holistic view of molecular mechanisms of kidney fibrosis, two time-

course microarray datasets were reanalyzed. Gene interaction map evaluation determined

the modular structure of densely connected ORs in both networks. In the next step, to

validate in silico results, the common ORs between two datasets were selected for further

in vivo analysis in a validated model of ureteral obstruction.

Although the relationship between some of the ORs and normal physiology of the kidney

has been determined in recent years (Pluznick et al., 2013; Pluznick et al., 2009; Shepard et

al., 2016), few studies have focused on the role of ORs in pathological states of the kidney.

The study by Shepard et al. has investigated the role of Olfr1393 in diabetes (Shepard et al.,

2019). Additionally, our previous bioinformatics analysis determined a significant change

in the expression of ORs in the rat model of Ischemia-reperfusion injury (Moradzadeh &

Gheisari, 2019). To the best of our knowledge, this is the first study that has focused on the

role of ORs during the progression of kidney fibrosis. Based on in silico and in vivo

investigations, we identified five ORs, which according to our experimental evaluation, four

of them were significantly related to the progression of kidney fibrosis in the mouse model

of UUO. As these ORs have unknown ligands, deorphanizing them and functional

investigations with activation-inhibition approaches would be of the matter of investigations

in the future.

One of the advantages of this study is the time-course design of the models. Time-course

study designs can better demonstrate the dynamism of cellular behavior and also reduces

misinterpretations that may occur in single-point studies (Bar-Joseph, Gitter, & Simon,

2012; Rabieian, Moein, Khanahmad, Mortazavi, & Gheisari, 2018). Unfortunately, due to

cost and difficulty, such study designs are less considered by investigators and most of the

gene expression studies are performed statically (Abedi, Fatehi, Moradzadeh, & Gheisari,

2019). In the current study, both reanalyzed microarray datasets had time-series design and

analyzed with a time-course analysis approach. Likewise, the in vivo model was developed



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in a time-course manner, both in sham and UUO groups. Following sham over time reduces

the misinterpretations caused by single-time point sampling of the control group and leads

to a better perspective from the dynamism of normal function.

Evaluation of Olfr433, Olfr129, Olfr1393, Olfr161, and Olfr622 expression determined

different patterns of gene expression over 21 days. For distinguishing real changes from

noisy fluctuations, we compared the patterns of gene expression in control and treatment

groups based on the parameters that we have discussed in our recent study (Rabieian et al.,

2018). Accordingly, as the magnitude of difference between sham and UUO groups was

significant, and the number of time points that one group was higher or lower than the other

group was consistent, the expression changes seen in ORs expression were considered real

and not noisy fluctuations. Furthermore, evaluations determined rhythmic patterns in ORs

expression in sham groups somehow similar to the rhythmic patterns, which is not far from

the oscillatory function of the kidney (Firsov & Bonny, 2018; Hara et al., 2017). Since these

findings are only an initial clue about the rhythmic expression patterns of OR genes, further

investigations on the relation of ORs expression patterns with kidney function would be of

interest.

Taken together, our in silico and in vivo investigations validate the expression changes

of novel ORs during the progression of kidney fibrosis. Our time-course evaluations

determined rhythmic patterns of ORs expression and highlighted the importance of time-

course study designs in deciphering dynamism of genes behavior over the course of the

disease. However, future studies are required to further investigate these findings. This study

is a good example of the potential capacity of systems biology unsupervised top-down

strategy to unravel the neglected aspects of disease pathogenesis.

Material and Methods

Microarray Data analysis

The GSE36496 microarray dataset deposited by Wu et al. was downloaded from the gene

expression omnibus (GEO) database (Barrett et al., 2013; B. Wu & Brooks, 2012). The

quality of the data was assessed by Principal Component Analysis (PCA) and hierarchical

clustering using ggplot2 and pheatmap package of R software, respectively (Kolde, 2019;

R Core Team, 2019; Wickham, 2016). For determination of the significantly expressed

genes in this time-course dataset, we applied linear models for microarray data (LIMMA),

a package of R software. (Smyth, 2004). Using the multiple comparison method of LIMMA,

the sham and unilateral ureteral obstruction (UUO) groups were compared with each other

at different time points and differentially expressed genes (DEGs) determined by False



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Discovery Rate < 0.05 (Benjamini–Hochberg). The second dataset GSE96571 deposited by

Wu et al. was also analyzed in the same way and DEGs were determined according to the

previously mentioned criteria (B. Wu, Gong, Kennedy, & Brooks, 2018).

Network Construction and topological analysis

The DEGs were used for the construction of a gene-interaction network using Cluepedia

plugin (version 1.5.5) of Cytoscape software (version 3.7.2) (Bindea, Galon, & Mlecnik,

2013; Shannon et al., 2003). The interaction data for activation, binding, inhibition, and

post-translational modification with a confidence rate of 0.8, was retrieved from the search

tool for the retrieval of interacting genes/proteins (STRING) database (STRING-ACTION-

SCORE_v10.0_10090_09.06.2015) (Szklarczyk et al., 2017). Based on the clustering

coefficient parameter, the densely connected sites of the network with a cutoff point of 4

were determined by molecular complex detection (MCODE) plugin (version 1.5.1) as

structural modules (Bader & Hogue, 2003). The gene-interaction network for GSE96571

microarray dataset was also constructed, and the structural modules were investigated using

the same method.

Animal model of Unilateral Ureteral Obstruction

Male C57BL/6 mice aged 6-8 weeks were obtained from Pasteur Institute (Tehran, Iran).

Animal care and experiments were according to the National Institutes of Health’s Guide

for the Care and Use of Laboratory Animals. Ketamine and Xylazine (Alfasan, Woerden,

Netherland) were injected intraperitoneally for anesthesia at the dose of 115 and 11.5 mg/kg,

respectively. During anesthesia and operation, mice were kept on a 37.5 °C plate. After a

mid-abdominal incision, the left ureter was isolated from surrounding tissues, double

ligated, and the incision was sutured. Sham operation was performed with the same

procedure, except for the ligation of the ureter. The mice were harvested 1, 3, 6, 9, 12, 15,

18, and 21 days after surgery. For each time point, two UUO and two sham-operated mice

were allocated. Besides, four untreated mice were used as normal controls. After sacrificing

with cervical dislocation, the left kidney was harvested and coronal sections were prepared.

The anterior part was kept in 3.7% formaldehyde in PBS for histopathological study and the

posterior part was sustained in liquid nitrogen for RNA extraction.

Histopathological Evaluation

The formalin-fixed kidney tissues were paraffin-embedded and 5µm sections were

prepared. Hematoxylin and eosin (H&E) as well as Masson trichrome staining were carried

out and histopathological evaluations were performed in a blinded manner. In random



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cortical fields, the existence of increased mesangial matrix, diffused glomerulosclerosis, and

mesangial cell proliferation was assessed between two experimental groups. Moreover, for

each section, the percentage of cortex area affected by fibrosis that included interstitial

cortical fibrosis, tubular loss with minimal fibrosis, and periglomerular fibrosis was

determined as described previously (Moghadasali et al., 2015).

Statistical Analysis

To compare the significance of histopathological differences between sham and UUO

groups, the two-way ANOVA test was applied using the ‘anova2’ function of MATLAB

software (MathWorks, 2019a).

Gene Expression Assessment

Total RNA of the lower part of the left kidney was extracted using RNX-plus (CinnaGen,

Tehran, Iran) according to the manufacturer’s instruction. Afterward, the concentration of

the extracted RNA was measured by Epoch microplate spectrophotometer (BioTek,

Winooski, Vermont). Since ORs sequence contains only the exon coding region, to

eliminate DNA contamination, the samples were treated with DNase I (Thermo Fisher,

Waltham, Massachusetts). To validate this procedure, mock controls were also employed.

Subsequently, random hexamer primered cDNA synthesis was done using the first-strand

cDNA synthesis kit (YektaTajhiz, Tehran, Iran). Specific primers for the selected ORs, Hprt

and Tfrc were designed using AlleleID software version 6.2 (Supplementary Table 1) (Apte

& Singh, 2007). Real-time quantitative polymerase chain reaction (RT-qPCR) was

performed using RealQ Plus 2x Master Mix Green with high ROXTM (Ampliqon, Odense,

Denmark) by Rotor-gene 6000 cycler (Qiagen, Hilden, Germany). The expression of genes

was normalized by considering Hprt and Tfrc as internal control genes. The results of RT-

qPCR were analyzed using the relative expression software tool (REST) version 1 (Pfaffl,

Horgan, & Dempfle, 2002).

Statistical Analysis

To compare gene expression patterns in UUO and sham groups, the two-way ANOVA

test was applied using the ‘anova2’ function of MATLAB software (MathWorks, 2019a).

The fold changes of the UUO group were considered as response values.

PCR products sequencing

PCR was performed by T100™ Thermal Cycler (Bio-Rad, Hercules, California) using

Taq DNA Polymerase 2x Master Mix RED (Ampliqon, Odense, Denmark), then the PCR



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products were cloned into the PTZ57R vector using TA Cloning™ kit (ThermoFisher,

Waltham, Massachusetts). Cloned products were transformed into competent TOP10 E. coli

by incubating on ice with a subsequent heat-shock at 37°C. Transformed colonies were

cultured on LB-Agar (Sigma-Aldrich, St. Louis, Missouri) plate treated with ampicillin

followed by overnight incubation at 37°C. Afterward, plasmid extraction from bacteria was

performed using Solg™ Plasmid Mini-prep Kit (SolGent, Daejeon, South Korea). Sanger

sequencing of samples was done using both forward and reverse universal M13 (-40)

primers by Bioneer biotech company (Daejeon, South Korea).

Acknowledgments: This study was supported by Isfahan University of Medical Sciences

(grant number: 398439).

Competing interests: The authors declare no competing interests.



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https://doi.org/10.1101/2020.07.29.225425


Figure 1. Network analysis of two microarray datasets on mouse model of ureteral obstruction.

PCA analysis and heatmap clustering of GSE36496 dataset demonstrated good quality of samples

regarding treatment and time of harvest (a, b). Gene interaction network created from 2583 DEGs

of GSE36496 dataset (c). The first- (d) and the second-ranked (e) modules resulted from topological

analysis of the network constitute NDUF and OR gene families, respectively. Gene Interaction

network from 3176 DEGs of GSE96571 dataset (f). The top-ranked module from topological

analysis of constructed network is constituted of Olfactory receptors (g). The overlap between

differentially expressed ORs of GSE36496 and GSE96571 datasets (h).

a

Rapgef5Utp18

Tcn2Tcp1Hip1

Arhgap9

Zeb1Tap2Tagln

Stx3Sucla2Suclg2

Adgrb3Kcnh8

Stx1a

Thy1

Tlr6

Zfyve16

Tlr1

Timm17aTjp2

Srprb

Serpinb9

Sod2Slit3

Sptan1Srpk2

Serpinb6a

Tnfrsf11aTnfrsf1bTraf1Trpc1Trpc4TstTxn1Uxt

Zfp521

WarsVamp8

Crb3

Wdr36

Sec22b

Sipa1Sept8

SelplgSema4a

Cox15

Cd226Xrcc5

Smg7Atf6Hibch

Pip5k1aPcsk5Pax7

Sept5Serpine1

Lilra6

Lgmn

Pdha1

Mrvi1Mdh1Mdh2

Me1Grap2

Grpel1Mttp

Mmp16Mmp11

Prdx1

Ddr2P2rx7

Slc11a1Nfs1Nf2

Orc2Ntn3

Mrpl40

Ryr3

Serpinf1Satb1

Rasa3

Sap18

Rgl2

S100a10

Cavin1

Rabggtb

Ptpn18

Rasgrp2

Rab23

Ptprs

Fpr2Fkbp1bFcgr1Fhit

FxnFstl1Fmod

Celf2Cd300c2

Eps8Evl

Fbln1Fbln2

Epm2a

GabpaGpd1Gabpb1GcGpd2Fth1

Stx2

Eif4a1Epha3Epb41l2

Ephb3Ephb6

Eif2s1

GclcGna12H2-DMb2Hcfc1Hdac6Foxa2Hspd1Idh3g GclmItpr3Kcnab1LifrKcnh3Anxa1Lrp1

Efnb2Eef2kAsap1

Dok2

Cyp4a10Dab2Cyp4a14

Mfn2Idh3bLtfLrp8

Ppargc1bZfp369Galnt10Il17rdMfap2Matk

Inpp5dInhba Igfbp2Il18 Ifngr1Il13ra1

Txnrd1Dkk3

Braf

C1s1C1ra

Map3k15Dok3

Timm10Timm13PdhxTjp3

Timm9

Col6a2Col6a3

Col3a1

Dpysl2Fes

Col1a2 Col1a1

Arhgdig Col6a1

Gnb4

Abl1

Sema4g

Bcap31ClpxTcirg1

Cops6Sh3pxd2b

Map4k4

Psmd12

Rhod

Rhobtb1

Prex1

Psmd10

Sh3kbp1

Btk

Cep131

Csnk1d

Pcnt

Psmb5

Nck1

Gng12

Cep250

Plxna2

Psmb4

Plxna1

Gng8

Rhot2Cep164

Rac2

Psme1

Syk Dapp1

Dpysl4

Dpysl3Psmd3

Csnk1e

Nox4Nsfl1cC1s2Mapk8ip3Dock6

Fgd3

Prdx6b

Rgs14Nhp2Pgrmc1Timm23ClppRasa4Mpc1RabggtaStx8Cfhr2Elp5Cd320

Rps24

Panx1

Ilk

Ppp3cc

Tsc1

Trpv4

Ccl25

Flna

Tuba1c

Mmp2

Lamb2

Pgr

Thrb

Tgfb3

Cd40

Cyfip1

Lama4

Plxnb1Lamc1

Tubb2a

Rab7b

Vcam1Wdr12

Ikbke

Pes1

Mapk3

Col6a4

Ticam1

Dync2h1

Abl2

Pard3

Arhgef12

Pard6g

Cyfip2

Arhgef6

Chad

Bak1

Bmp7

Pak1

Trib3

Dkc1

Park7

Ccl22

Rb1

Timp2

TgfaTapbpSnai2Ret

Tgfbr2

Tgfb1i1

Prkcz

Ncf2

Ncf1

Mknk1

Kirrel

Klrc1

Nfkbie

Itgb2

Col5a1Col11a1

Ntrk1

Cxcr4

Dld

Fn1

Igf1

Fcer1gFcgr3

Col5a2

Ccr1

Gata4Gata6

Elmo1Plxnb3

Csf1rHspa9

Fgfr3

Cd8b1

Ngfr

Mrpl46

Fgfr1

PccbSdhdSdha

Kras

MmachcGpx7Mfn1

Dctn4Atg12

Snx2Dph2

Slc25a37Sdhb

Ssr3

Nip7Slc9a3r2Polr1eNsa2Maea

CubnChchd3

Bcl2

Nop10PpihCysltr1Kcnmb4Nectin1Gtf2ird1Lat2Cd200r1Sphk2Rapgef4Gosr2Vps29Ykt6Fxyd1 Adrm1Suclg1Mbtps1Rgs19Higd1a

Pycard

IscuVta1

Pmpca

Exosc7Sike1Cyp4a31Exosc1Pam16

Atg10Mrpl33

Olfr1056

Olfr433

Olfr399Olfr906

Olfr1406Olfr608

Olfr622Srgap3

Olfr248

Olfr1276

Olfr1030

Olfr1350

Olfr129Olfr374

Olfr313

Gys2

Ablim2Galnt11

H2afj

Kdm4a

Mrps35Lilra5Rasgrp4

Spg7Naf1

Arhgap1

StradbC1ql3Zfpm1

RalgapbNol6

Coro1b

Kcng1

Mrps12

Rgma

Mapk7Mmp17

Olfr114

Dlat

Ralgapa2

Il12b

Ifna1

Prkg1Il15

Creb3

Nedd4

Rasa2

Cd74

Fzd2

Med20

Med25

Polr3g

Wnt1

Med8

Noc3l

Rras2

H2-K1

Gli1Dok1

Cd47Ncam1

H2-Q10

Atf4

Mapk8

Pik3cd

Wdr18

Nrg1 Sdad1

Bcl2l1

Traf6 Chuk Ptpn1

Robo1

Ncf4Grb2

Eif6 Ikbkg

Itgb4

Med9

Polr1d

Prkcg

Egfr

Itgb1

Gemin5

Cox7b

Sdc4

Myl9

Cox6b1

Apob

Tpm2

Gpc6

Tpm1

Lmod1

Cyc1

Nup160

Uqcr11

Uqcr10

Uqcrh

Atp5md

Uqcrfs1

Cox6a1

Cox4i1

Acta2

Agrn

Cox5a Apoe

Actg2

Sorbs1

Itgb5

Gpc1

Cox7c

Cox6c

Gpc4

Sdc2

Cox8a

Seh1l

Uqcrb

Nup43

Uqcrc2

Uqcrc1

Nup214

Uqcrq

Nup54

Nup205

Atp5mpl

Nup50

Ncbp2

Polr2b

Polr2h

Alyref2

Polr2l

Olfr187

Olfr1307

Olfr69

Olfr24

Grk3

Olfr1447

Olfr1469

Olfr373

Olfr1393

Arrb2

Olfr497

Olfr1260

Olfr43

Olfr1270

Olfr478

Olfr1099

Olfr161

Olfr447

Gtf2f2

Pcbp2

Ybx1

Cstf2

Dnajc8

Rbm5

Prpf4

Olfr584

Cd44

Olfr1371

Ndufaf1

Ndufs5

Dcn

Erbb2

Cdc42

Akt1

Ndufa4

Ndufab1

Ndufa2

Ndufs3

Ndufa8

Ndufs4

Ndufs7

Ndufa5

Ndufb2Ndufc2

Ndufa13

Ndufb8

Ndufb6

Ndufs6

Ndufs2Ndufs1

Ndufv1

Atp5d

Atp5g1

Atp5f1

Atp5c1 Atp5b

Atp5g3

Atp5o

Atp5e

Atp5j2

Atp5a1

Smad5

Mrps2

Bmp2

Mmp14

Ncor2

Stat6

Srebf2

Sod1

Csk

Nfatc4

Csf2rb

Prkab2

Slc9a1

Cxcl12

Mef2d

Snap23

Ghr

Irf8

Ndufa1

Ndufb9

Ndufb3

Ndufa12

Ndufa9

Ndufb5

Ndufc1

Gtf2a1

Rnmt

Bub3

Trem2

Adcy7

Card11

Med28

Grb10H2-M3

H2-Q1 Brap

Eif4e2H2-M11

Itga2Lpar1Nfix

Dmd

Nfic

Nfkb1

Wnt2

Wnt8bSfrp1

Stam2

Lrp6

Grk2

Arrb1

Nckap1l

Wasf1

Lpar3

Helz2

TyrobpMalt1Vim

Rangap1

Nfkbia

Tmod1

Prkcq

Rela

Plcb2

Thbs4

Thbs2

Coro1a

Col17a1Col18a1

Clcn5

Patj

Celf1Cyp17a1

Cycs

Dnajc5CtssCtsb

Anxa2C3ar1

C2

Bdkrb2Bgn

Canx

Atp6v0a1

CfhCebpz

Cd4CcsCcnd2

Cat

Arpc1bAtp1b2

Atp6v1aAtp6v1b2

Prdx6Boc

PccaEhmt2Mmadhc

EtfbEtfa

Ccdc88aFermt3

Macrod1

Il1rl2Nod1

Exoc6

AlplActc1

Slc8a2Acadm

Vps4aRims2

Rab31Rrn3PpifDph3Pik3r6Ric8aDuox1Nat10Usp6nlMaged1

Anxa4Slc25a5Gfer

Alox5Alox5ap

Ifitm2

Cpt1cMccc2

Sorcs2

Ntf5Dlst

Elp4Mrps5

Clip3

Snx27Kansl1

OsbpCar12

Dock8Dock11Senp2

Rrp7aPpa2

Pank1Svip

Cd200r3

Dnaja3Pla1aMrpl1Pag1

Nras

Pik3r2

Derl1

Ptk2b

Pmpcb

Tram1LrpprcRrp1bDis3Rint1

Shq1

Tm7sf2Plce1

CltbCyld

Arpc5lOpa1

Abcb6

Fblim1

Pik3cb

Mccc1

Mpc2Chp2

Wars2Stx18Bbs7

Chchd4

Col4a3bp

Rmdn3

Gpx8Anapc13Rab13

Zfp593Tomm20

gg

Ndufs5

Ndufa8

Ndufb9

Ndufc2

Ndufb6

Ndufa4

Ndufs7

Ndufa2

Ndufa12

Ndufa1

Ndufa13

Ndufa9

Ndufs1

Ndufv1Ndufc1

Ndufa5 Ndufs3

Ndufs4

Ndufb8

Ndufs2 Ndufb5

Ndufab1

Ndufb2

Ndufb3

Ndufaf1

Ndufs6

Olfr1260

Arrb2

Olfr69

Olfr161

Olfr1099

Olfr447

Olfr1393

Olfr1270

Olfr497

Olfr1307

Olfr373

Grk3

Olfr584

Olfr1371

Olfr187

Olfr43

Olfr24

Olfr1447

Olfr1469

Olfr478

d

e

c

Tnfrsf1b

Mapk1

Pak1

Myod1

Rac2

Tiam1

Tgm1Heatr1TfpiMlh3Nol10Tnrc6cUnkTada2aWdr18Hip1Rhot2GnptgAgap3Tnrc6b

Tnfrsf18Tnfaip1Tmod1Tle1Thy1Cdc14b

Th

Myd88

Pik3r5

Itga4

Itga11

ItgavItga3

Itga1

Rnf31Sh3pxd2bItgb1bp2Psg17Cop1

Ceacam1Nphp4Npat

Rb1

Hspb6Ppp1r9aDhrs9

Tnfsf18Taf7

Pacsin2Pacsin1Dlg2Arih1

Pla2g3Rab8bCnot1Tpcn2Ppfia1Palb2

Thumpd1

Gcg

EmsyRsf1

Zfp592Gcn1l1Gak

NppaEcpas

Cdc14aArfgap1Zmynd8RalgapbKat14Slc30a1Mapkap1Zfp64Smyd2Pcgf2Smc5

Pla2g16Cd226Vdac2Vamp1UtrnUnc5cUgt8aUsp12TyrTtnTrpc2Top2b

Dync2li1Arhgef11Fbxl21Slc39a14Ifitm6Eif1Stxbp4Strap

Srpk2Znrf4Stat4

Sptbn1Serpina1b

Sp100Sox17Sod1Slc34a1Sin3b

Tspan32Plekhg5Epb41Ern2

Kif26bEif2s3yLtbp1

Nlrc4

Sel1lSerpinf1Scn1b

RykRasgrp2

Rag1Rad51dRad51b

Shc1

Kif20a

Slu7Ptpro

Tomm70aTwistnbSnf8

Mrpl17Sh2d2a

Eif2ak4Galnt13Pla2g4f

Mapk14

Rab4b

Polr3a

Rab6a

Ptma

Ntrk2

Igf1

H2-Q10

Ptpn22

Eif2ak2Prnp

Prom1Cyth1

Ptpn18Ptpn2

Pou4f1Pms2Plp1

Syne2Hist1h2afHist1h2aa

Hist3h2aVapa

Bin1Cttnbp2Dhrs4

Stx7Krr1Ddx56Ppp1r10Mcrs1Lsm4Fbxo6

Efna5

Fbxl7GnptabPfn4Taok2Lin28bAtp6v1g3Arhgap32

Frmd6Zfyve27Vwc2Vwc2lChd7Apol10bPpp1r12bLgr6

TollipDnmt3lCldn8Cpsf4Copg1Cntn6Tomm40

Cnot4ReckTimm23

Iqgap2Paf1Rcan1Stx8Kcnj1B4galt6Ykt6Tspan3

PlgPrkchPip5k1cPikfyve

Nckap1

Polr3c

Pea15aPigrPdcd6ipPcsk1Pbx1Pax8Pak3

Rassf5

MttpMtcp1Msx2Msx1Msh6Ascl1Mesp2MfngMitfTrpm1Mmp10Mpdz

Ubc

Ap1s3

Eif2s3x

Mapk8Mapk9

Gng2

Itgb1

Itgb8

Anapc4

Pabpc1Sgk1Otx2Oprl1Ctnnd2Nos2Cd244a

H2-K1

H2-D1

Baiap2

Nkx2-9Nkx2-3NefmNfixNfiaNeurod1

Fgfr1

Erbb3

Jun

Col1a1Col2a1

Ncf4Nbr1Naip6MyogMuc5ac

Nprl3MarcoMcoln3Zfp369Cd180LtaLhx3LdlrCog1Kpna2Klra2

Kras

Vegfa

Nras

Kifap3Kif1bKif11Khsrp

Icam1

Kcnk4Kcnk2Itsn1ItgaeIsl1Inhbe

Inhbb

Cbl

IhhIfit1IgfalsIgfbp2IappHspd1

Hoxd3Hoxb1

Apoa1

TbpAdcy2

Stat5b

Traf3ip1

Taf1d

Nsmce2Mob1bPdhbCol4a3bpPold3Gipc1Atg3Derl1Poldip2Rmdn3Dctn4Fgfr1op2Map1lc3bPrpf18Fbxo5Oxct1Edem3Chmp3Tex12Atg4bDiabloExosc1Dzip1Timm50

Rasa1

Mlh1

Pla2g12aKlf15PigylArfgap3VirmaEef1e1AsphCubnOxct2aWtapDctn5Sh3rf1GhrlCysltr1Cacna1hTbc1d1Pidd1Xrcc2IcmtBrd4Akap10Prl2a1Ube2d2aMbtps1

Dpm3Rtn4Prpf31

Nmrk2Ebna1bp2

Esam

Atp5mplDpf3

Usp46Smyd3

Wdr20Tnfsf13

St13Spag9Chd6Nectin4Suds3Ddx42

Sgip1Prdm4

Rspo3Fance

B3gat3Lin9

Atg7Fblim1Actr3

Plce1Whrn

Mvb12a

MecomEtv2Drosha

En2Eif4g2Eif1aDpm2

GalcGabrg2Gabrb3Gabra3

Gja5GfapGcgrUsp15Gas6

GartGalnt4

Dnmt3aDnm1Dmc1Dlg1DldDiaph1Ddit3

Cd55Cd55bDbnlDcx

Cyp1b1Crmp1CraddCplx2Chl1

Ttc30b

Mcm10

Anapc13

Ift172Cltc

Ift22Ift20Orc3

Ttf1

Hoxa1HiraHcfc1H2-DMb2H1f0Grb7

Glycam1

Cd44

Fos

F5

Fcgr2bMyh7

Fbn1

Plxnb2

Erbb2

Ap2s1

Foxo1

Dpm1Dok1

Anapc5

Ep300Esrrb

Esrra

Med27

Med6

Med25

Med10

Med16

Rxra

Med1

Snrnp70

Etf1

Rps20Smg1

Rpl35aUpf2

Rps18 Rpl21

Gspt2

Rplp0

Sh3gl2

Cavin1

Ppp3r1

Ppp3cb

Ppp3ca

Pole2

Pola2

Kitl

Kdr

Lyn

Mcm2

Kcnj9Kcnj6

H2-Ab1 Flt1 Fgf7 Fgf17Fgf10

Nr1d1

Lep

Rarb

Nr2e1

Angptl4

Usp49

Rorb

Esr2

Ndufa7

Ndufab1

Exoc2

Rab14

Ndufa11

Ndufa12Ndufa3Ndufs5

Rala

Aaas

Nup214

Psmf1

Gtf2h2

Tubb3Il6

Psmd5

Psmd9

Psmd12CcnhNelfbEloa

Psma5

Nelfa

Gngt2 Gng3

Il23a

Nupl1

Nup93

Tubb6

Ctdp1

Fgf2

Ssr1

Stk3

Serpinb6c

Senp2

Rps6kb1

Bmpr1b

Gpc2

Myl12b

Serpinb1a

Tctn1

Lpar3

Nxt1

Cops4Cops5

Gabbr2

Tiam2

Gpc6

Akt3Ntrk1

Socs6Gabbr1

Trip4

Kctd10Tmem67

Foxo3

Cops7aCops6

Insr

Il4Cyp4a10Igf1r Cpt2

Gja1Cpt1a

Fgfr2

Sfrp2

Serpinb2

Ngfr

Nfatc2

Mmp9

Serpinb8

Wnt9a

Serpinb6a

Chd3

Tpm1

Wnt1

Thrap3

Cc2d2a

Ctnnb1

Cops2

Cdkn1aCasp3

Cacna1b

Cacna1a

Atf2

Acta2

Agrn

Mta3

Apoe

Arf1

Dync2h1

Cald1

Tmem17

Olfr1206

Olfr1428

Olfr1220

Olfr1157

Olfr263Olfr31

Cav2

Arhgap35

Eif4e2

Vamp3

MafCcl27a

Trp53bp2

Ints5

Cxcl16

Rictor

Vav2

Ccl2

Pard3

Wasf1

Col5a1

Lama3

Ccl24

H2-M10.6

Cxcl14

Ccl11

Casp7

Epha4Cacng2

Cacng5

Sox9

Gata4

Ncam1Slc2a4

Cacna2d1

Bmp2

Gnao1

Olfr1271Olfr39Akt1

Olfr569

Olfr836

Olfr494

Olfr288

Olfr1467

Olfr96

Olfr18

Olfr780

Olfr394

Olfr414

Olfr1496

Olfr1459

Tle4

Mapk7

Pdx1

Wt1

Ccl6

Gli3

Tln2

Socs4

Flna

Nfkb1

Lama4 Fn1

Wwtr1

Kcnc2

Kcnf1

Exoc7

Cacnb1

Cacna1e

Bdnf

Bcl2l1

Braf

Rapgef1

Wwp1

Foxo6Stk4

Psenen

Actr2

Cdt1

Rnf41

Bambi

Prkacb

Dll1Drd4

Hras

Chrm4Cdh1

Cd8a

Porcn

Was Atf6 Tbpl1Mapk8ip3

Lats2

Trpc6Tnfrsf1a

Tlr6

Apaf1

Elk4Fas

Gab1Fgf11

Egr2 Dnmt3bCsk

Csf1Chrd

Fzd10

Csnk1a1

Hdac8

Smarca2

Sar1b

Cd4

Cd14

Brca1

Bmp4

App

Rasa2

Ppp2r2b

Tsc1

Ppp2r3c

Pias1

Cdk6

Cdh4

Cdc25b

Olfr323

Itk

Olfr330 Olfr796

Rela

Smurf1

Ifng

Runx2

Fasl

Olfr874

Olfr63Olfr1393

Olfr1234

Gata6

Hey2

Il10

Il18

Ilk

Gata3

Pax3

Pax2

Ntn1

Nf2

Myf5

Matk

Itgb2

Ret

Rab4a

Pecam1

Prkg2

Pdgfd

Tjp2

Eif5

Tbc1d4

H2-Q2

Pln

Snap23

Ccl12

Ptch1Abcc8

Hmga1

Olfr675

Olfr741

Rps6ka1

Olfr1015

Grk5

Cd247

Eif4ebp1Olfr1256

Olfr700

Olfr1463

Olfr1100 Olfr142 Olfr2 Olfr555Fzd4Olfr355

Fzd2

Olfr493

Olfr926

Olfr161

Olfr738

Olfr95

Olfr305

Olfr668

Olfr488

Olfr282

Il22ra1

Eif5b

Exoc3

Exoc4

Kcng1

Kcnc3

Kcnc1

Kcnh1

Kcna2

LeprNdufv1

Il2ra

Ifngr1

Exoc5

Tubb2a

Tuba3a

Srp68

Tcp1

Ssr4

Psme3Psmc3

Srprb

Psmb5 Nup62 Il5raIl12b

Il11

Sgo2a

Nde1

Clasp1

Nuf2

FynRps27

Zwint

Cenpm

Nup98

Ercc6l

Kif18a

Ahctf1

Stag2

Cct3

Cct6a

Cntf

Csf2rb

Actb

Kif2a

Nudc

Bub3

Pafah1b1

Xpo1

Eif4a2

Eif3a

Cdc7

Ap1m1

Tgs1

Adcy7

Arrb1

Chd9

Ap1s2

Sult2a2

Snrpd1

Polr2f

Pabpn1

Cpsf3

Hnrnph1

Cstf1

Srsf11

Hnrnpa0

Hnrnpr

Snrpb2

Polr2a

Pcbp2

Ppp2r1a

Sfi1

Nek2

Cdk1

Ccp110

Cep76

Cep164

Cdk5rap2

Ywhae

Tubgcp5

Cntrl

Cep63

Taf13

Stat1 Sult2a8

Ttc30a1

Egfr

Mdm2

Ifna13

Ifna4

Klrc1

Raf1

Il1b Htr1d

Ppp2r5e

Jak2

Cyfip1

Nrg1

Tapbp

Bms1

Utp6

Ppp2r5d

Tgfb1

Notch1

Notch4

Pparg

Psen1

Myh6

Myh1

Il2

Ppp2r5cMap2k6Dapp1

Wasf2

Ets2

Ets1

Ezr

Tlr4

Frs2

Tfap4Rrbp1Tfcp2l1Pum1Ak7

RbsnSla2

Nanog

Pax6

Shh

Them4Akap13

Anapc15Sirt4Sv2c

Gorasp1Ifitm7

Myh10Sec24aNkrfMzt1

Snx27Clip3

H2al1m

Smad5

Ezh2

Ccr4

Ccr9

Rapgef4

Pcna

Ccr2

B2m

Atm

Fzd6

Grm6Zzz3

Casp8

Cd59aCalb2C9Bnip3lGlb1Bcl10

Ap2m1

Nos1

Cd9

CebpgCdh9

Dock2Mrpl3Vangl2AmnUbe2nSmarca5Pard6g

Ncor1

Vps37cPrickle1

Fkbp6QarsPrmt6

E2f1

SharpinFancmCog4Trrap

BckdhaBcat2Atp6v0eAtp6v1aAtp5g1Atp5f1Atp5a1

Aplp2ApohArl4a

Atp2a2

Trem2Chrdl1Pik3ap1

Mmp1a

ApcSlc25a5

Actl6b

Slc25a4Ank3Scgb3a2Aebp2

McamGlrx

Adra2aPwp2Adgrv1

Apol7cTmbim6

f

Olfr96Olfr323

Olfr1100Olfr1256

Olfr1234Olfr741

Olfr1220Olfr1393

Olfr569 Olfr668

Olfr142 Olfr700Olfr874

Olfr836

Olfr1496

Olfr493Olfr738

Olfr161

Olfr488

Olfr926

Olfr780

Olfr31

Olfr1428

Olfr263

Olfr414

Olfr95

Olfr1271

Olfr1015

Olfr494Olfr18

Olfr675

Olfr796

Olfr305

Olfr355

Olfr1206

Olfr39

Olfr394

Olfr288 Olfr1157

Olfr1459

Olfr1467

Olfr2

Olfr63

Olfr330

Olfr1463Olfr555

Olfr282

g

ActivationBindingInhibitionPost-Translational Modification

h

Olfr1015Olfr1100

Olfr113

Olfr1157

Olfr1165

Olfr120

Olfr1206

Olfr1220Olfr1234

Olfr1256

Olfr1271

Olfr1284 Olfr1289

Olfr131

Olfr134

Olfr1352

Olfr138

Olfr140

Olfr1412

Olfr142Olfr1428

Olfr144

Olfr1459

Olfr1463

Olfr1467

Olfr1471

Olfr1489

Olfr1496

Olfr1501

Olfr1508Olfr18

Olfr186Olfr197

Olfr2

Olfr22-ps1

Olfr282

Olfr288

Olfr305

Olfr31

Olfr323

Olfr330

Olfr344

Olfr355

Olfr39

Olfr394

Olfr414Olfr42

Olfr488

Olfr493

Olfr494Olfr523

Olfr551

Olfr555

Olfr569 Olfr619

Olfr780

Olfr796

Olfr811Olfr836

Olfr862

Olfr629

Olfr63

Olfr649Olfr668

Olfr675

Olfr700

Olfr738

Olfr741

Olfr746Olfr768

Olfr874 Olfr926

Olfr95

Olfr957

Olfr96

Olfr960

Olfr960

Olfr996

GSE96571n = 82

Olfr1030

Olfr1056

Olfr1099

Olfr114

Olfr1260 Olfr1270

Olfr1276Olfr1307 Olfr1350

Olfr1371

Olfr1406

Olfr1447

Olfr1469

Olfr187

Olfr24Olfr313

Olfr373 Olfr374Olfr399

Olfr415

Olfr43

Olfr447

Olfr478Olfr497

Olfr584

Olfr608 Olfr69

Olfr906

GSE36496 n = 33

b

PC1

-10

-20

20-20

10

PC2

SamplesUUO-day 1

UUO-day 2

UUO-day 5

UUO-day 9Sham-day 1to day 9

Olfr129Olfr161

Olfr622

Olfr433Olfr1393

n = 5 Common ORs

2 1 0 -1



https://doi.org/10.1101/2020.07.29.225425


Figure 2. Histopathologic evaluation of UUO-operated mice over 21 days. The scheme of

experimental design (a). Trichrome and H&E-stained renal sections in normal, sham (day-21), and

UUO operated mice at days 1, 3, 6, 9, 12, 15, 18, and 21 post-surgery. Yellow, red, and black arrows

stand for increased mesangial matrix, mesangial cell proliferation, and diffuse glomerulosclerosis,

respectively (b). The percentages of glomeruli with increased mesangial matrix (p-value = 0) as well

as cortical fibrosis (p-value = 3.25077e-10) for sham and UUO-operated mice. Data are mean ±

SEM (c).

b

2 cm0 1 2 cm0 1 2 cm0 1 2 cm0 1 2 cm0 1

2 cm0 1 2 cm0 1 2 cm0 1 2 cm0 1 2 cm0 1

��ɤT ��ɤT ��ɤT ��ɤT

��ɤT ��ɤT ��ɤT ��ɤT ��ɤT

��ɤT ��ɤT ��ɤT

��ɤT ��ɤT ��ɤT ��ɤT ��ɤT

��ɤT

��ɤT ��ɤT

Gro

ss

Normal UUO day-1

UUO day-9 UUO day-12 UUO day-15 UUO day-18 UUO day-21

Sham day-21

Tric

hrom

eTr

ichr

ome

Gro

ssH

&EH

&E

a

�

��

��

��

��

��

��

� � � � � � � � ��

��

� ��

��

��

Perc

ent o

f Affe

cted

Glo

mer

uli

��

� � � � � � � � ��

��

��

��

��

� ��

Perc

ent o

f Are

a

Cortical Fibrosis

Days Days

UUOSham

Days

0 3 6 9 12 15 18 211

Increased Mesangial Matrix

c

UUO day-6UUO day-3

Sham: n = 2 UUO: n = 2



https://doi.org/10.1101/2020.07.29.225425


Figure 3. Expression level of common ORs between two datasets in mouse mode of UUO over

21 days. Statistical analysis (two-way ANOVA) determined significant changes between UUO and

sham group for Olfr433, Olfr129, Olfr1393, and Olfr161 (p-value < 0.05).

Fold

Cha

nge

Days

Olfr161

3 6 9 12 15 18 210

10

15

20

25

0

5

Olfr433

3 6 9 12 15 18 210

1

2

3

4

0

5

6

7

8

Olfr622

3 6 9 12 15 18 210

10

15

20

25

0

5

Olfr1393

3 6 9 12 15 18 210

1.0

1.5

2

0.5

Olfr129UUOSham

3 6 9 12 15 18 210

10

15

20

0

5

Gene NameTreatment

p-value (main effect)

Olfr433 0 *

Olfr129 0.0002 *

Olfr1393 0 *

Olfr161 0.0007 *

Olfr622 0.0822



https://doi.org/10.1101/2020.07.29.225425


Supplementary Table 1

Supplementary Data 1: Sanger sequencing results

Gene Gene ID Forward primer Reverse primer

Primers list

258324

258859

259087

258712

258463

Size(bp)

84

95

117

Olfr433

Olfr622

Olfr1393

Olfr161

Olfr129 GGTATAACTGAGTGCTGCCTACTG CCCACGATTCATTCGGGTTGTAT

GTCTTGGGAAACCTGCTCATCAT AGTGGTGGAGGAGAAGCATACAT

CCTGGCTTGGAGAATGTTCACTGT ATAGGCTGGTGGAGACTTGGCTC

CTCCGACCTCTTGCCTTCC CCTGAATCTGCCTGAACCAA

CGTCCACTGCACTATACT GTTCAAGAAGCCTCCTACC

96

125

Hprt

Tfrc

CGTCGTGATTAGCGATGATG AGTCTTTCAGTCCTGTCCATAA

TGCATTGCGGACTGTAGAG CCCACCAAACAAGTTAGAGAAT

126

97

15452

22042



https://doi.org/10.1101/2020.07.29.225425


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