Open Access
Article

mRNA-miRNA integrative analysis of diabetes-induced cardiomyopathy in rats

Mariana B. Lopes1,Renata C. C. Freitas1,Mario H. Hirata2,Rosario D. C. Hirata2,Adriana A. Rezende1,Vivian N. Silbiger1,Raul H. Bortolin1,Andre D. Luchessi1,*
1
Department of Clinical and Toxicological Analyses, Federal University of Rio Grande do Norte. General Cordeiro de Farias Av., Natal, Rio Grande do Norte, 59012-570, Brazil
2
Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo. 580 B17 Lineu Prestes Av., Butantan,05508-900. Sao Paulo, Brazil
DOI: 10.2741/S483 Volume 9 Issue 2, pp.194-229
Published: 01 March 2017
(This article belongs to the Special Issue Clinical applications of epigenetics)
*Corresponding Author(s):  
Andre D. Luchessi
E-mail:  
luchessi@outlook.com
Abstract

An integrative analysis of miRNA and mRNA expression profiles in left ventricle (LV) of diabetes-induced rats was performed to elucidate the role of miRNAs and their mRNAs target in diabetic cardiomyopathy (DCM). mRNA (GSE4745) and miRNA (GSE44179) datasets were downloaded from Gene Expression Omnibus 2R (GEO2R) and differentially expressed mRNAs and miRNAs were selected. Cardiotoxicity-related mRNAs (n=7) were analyzed by Ingenuity Pathway Analyses 6 (IPA) and regulatory miRNAs (n=639) were identified using TargetScan 7.1. web dataset. The integrative analysis was performed between miRNAs differentially expressed in GSE44179 and regulatory TargetScan-detected miRNAs of mRNAs differentially expressed in GSE4745. Pla2g2a and Hk2 mRNAs were up-and-down regulated, respectively, in GSE4745 on days 3 and 42 after diabetes-induction. The Pla2g2a regulatory miRNAs, rno-miR-877, rno-miR-320 and rno-miR-214, were down-regulated, and Hk2 regulatory miRNAs, rno-miR-17, rno-miR-187, rno-miR-34a, rno-miR-322, rno-miR-188, rno-miR-532 and rno-miR-21, were up-regulated in GSE44179 dataset. These results are suggestive that Pla2g2a and Hk2 mRNAs and their regulatory miRNAs play a role in DCM pathogenesis and they may be potential circulating biomarkers to detect early cardiovascular complications in diabetic patients.

Key words

In silico analysis,Biomarkers,Diabetic Cardiomyopathy,Gene Expression,MicroRNAs

2. Introduction

Diabetes is a group of heterogeneous metabolic disorders which has in common the hyperglycemia triggered by a defect in insulin action and/or secretion (1). Diabetes is one of the most common metabolic disorders in the world and its prevalence in adults has been increasing in the last decades (2,3). In 2013, 382 million people had diabetes; this number is expected to rise to 592 million by 2035 (2).

Chronic hyperglycemia leads to severe complications including microvascular and macrovascular diseases that may affect the life quality and survival rate of diabetic patients (1). The most common microvascular complications are diabetic nephropathy, peripheral neuropathy, autonomic neuropathy and retinopathy, while the macrovascular diseases include cerebrovascular disease, coronary artery disease (CAD) and peripheral vascular disease, which have an important relationship with atherosclerosis and diabetic cardiomyopathy (DCM) (1,4,5).

DCM has three important heart alterations associated with diabetes: 1) systolic and diastolic left ventricule (LV) dysfunction regardless of hypertension, CAD and other heart diseases (6); 2) evidence of myocardial structural and functional changes, such as myocardial hypertrophy, fibrosis and necrosis (7); and 3) heart failure (8). Additionally, metabolic disorders, such as depletion of glucose transporter 4, insulin resistance, increased free fatty acids, carnitine deficiency and alterations in calcium homeostasis, as well as myocardial fibrosis, small vessel disease and cardiac autonomic neuropathy and are involved in the pathogenesis of DCM (9–11).

Studies using diabetes-induced animal models have also shown structural, functional and molecular alterations in LV related to the hyperglycemic status (12–14). Insulin-like growth factor 1 receptor activation was shown to prevent diabetes-induced cardiac fibrosis and diastolic dysfunction (12). Inflammatory condition is triggered by hyperglycemia in diabetic patients, and has been associated with an over expression of many inflammatory mediators in LV, such as tumor necrosis factor-alfa, interleukin 1beta (13) and transforming growth factor beta (TGF β) (14). Also, in the hyperglycemic condition, the levels of the collagen degrading matrix metalloproteinase 2 (MMP-2) decreases, suggesting that normalizing the MMP-2 activity is possible to prevent cardiac fibrosis in STZ-induced cardiomyopathy (14).

Molecular mechanisms involved in DCM physiopathology are not completely elucidated. It has been reported that hyperglycemia-induced BNIP3 expression, a protein involved in mitochondrial function and apoptosis in the heart, may compromise cardiac cell survival and function (15). On the other hand, up-regulation of rno-miR-1 and rno-miR-206 related to down-regulation of Hsp60 mRNA target, in myocardium rats, neonatal ventricular cardiomyocytes, and H9C2 cells exposed to high levels of glucose, were associated with cardiomyocyte apoptosis (16). These studies provided relevant information to understand some of the genes involved in DCM mechanisms. However, a systematic biology approach has not been used to investigate a broader range of genes that could be involved in DCM physiopathology.

The systematic biology approach using an in silico analysis (17) may be an alternative approach in order to expand the comprehension of miRNA-regulated mRNA differential expression and its role in the development of DCM. Integrative analysis evaluating miRNA-mRNA target interactions has been performed to elucidate the pathogenesis of some diseases. Through in silico analysis using datasets of platelet miRNA and blood mRNA expression profiles of CAD in patients and healthy controls available at Gene Expression Omnibus (GEO) platform, investigators analyzed the prediction of miRNAs to target mRNAs dysregulated in CAD such as, TFEC-has-miR-545 and hsa-miR-585-SPOCK1 (18).

Thus, the interactions between miRNAs and mRNAs differentially expressed in LV of diabetes-induced rats were evaluated using bioinformatic tools, aiming to identify mRNAs and their regulatory miRNAs, which play a role in DCM pathogenesis.

3. Methods

3.1. Study design and experimental models

mRNA and miRNA expression profiles (GSE4745 and GSE44179, respectively) were downloaded from GEO datasets (19). GSE4745 is a microarray dataset of global mRNA expression in ventricles of Wistar rats with diabetes induced by streptozotocin (STZ) at three time points: 3 days (n=4), 28 days (n=4) and 42 days after STZ injection (n=4). Control rats were injected with citrate buffer at the same time points: 3 (n=4), 28 (n=4) and 42 (n=4). Diabetic rats showed increased blood glucose 4.3., 5.6. and 5.0. fold, and ventricle weight/body weight ratio of 0.9.1, 0.9.9 and 1.3.5 fold, respectively, at 3, 28 and 42 days after STZ-induction compared to controls (p-value <0.0.5). mRNA expression was analyzed by the microarray system using the platform: GPL85 (RGU34A) Affymetrix Rat Genome U34 Array. The investigators that performed GSE4745 data published a study which investigated the conversion of acyl-carnitine in a long-chain free fatty acid and the exported system in mitochondria of STZ-diabetic rat hearts (20).

GSE44179 is a microarray dataset of global miRNA expression in LV of diabetic (n=4) and non-diabetic (n=2) Wistar rats. Diabetes was induced by STZ followed by high fat diet for 12 weeks. Control rats (n=2) were fed with regular chow and citrate buffer injection. The diabetes rats’ blood levels of glucose (556 ± 108 mg/dL), total cholesterol (140 ± 55 mg/dL) and triglycerides (79 ± 21 mg/dL) were higher in diabetic than in control rats at the time of euthanasia (p-value <0.0.5). Intraperitoneal glucose tolerance test and Intraperitoneal insulin resistance test confirmed the glucose intolerance and insulin resistance in diabetic rats. DCM in rats was demonstrated by 1.6.-fold increase in a heart-to-body weight ratio and the presence of non-ischemic lesions, interstitial and perivascular fibrosis as well as myocytes atrophy and hypertrophy. miRNA expression was analyzed by the microarray system using the platform: GPL14613 (miRNA-2_0) Affymetrix Multispecies miRNA-2_0 array. The investigators that performed GSE44179 data evaluated the role of Cdc42 and Pak1 genes and rno-miR-30c in rats with DCM (21). The in silico analysis strategy used in this study is described in Figure1.

Figure 1. In silico analysis strategy of mRNA-miRNA differential expression data associated with diabetes-induced cardiotoxicity. Left ventricle of STZ-induced diabetic rats was used for microarray analysis. GEO2R: Gene Expression Omnibus 2R software; GEO, Gene Expression Omnibus; IPA, Ingenuity Pathway Analyses 6; MICRORNA, microRNA database.

3.2. Microarrays data processing

Rat LV mRNA expression from GSE4745 dataset was compared between diabetic and control rats of each experimental period (3, 28 and 42 days after STZ diabetes induction), using Gene Expression Omnibus 2R (GEO2R). GEO2R (22) is a tool which allows comparison of data from two or more groups of samples in order to identify genes that are differently expressed in experimental conditions. Three top lists of mRNAs differentially and significantly expressed (|FC| > 2; p-value <0.0.5) at each study period were selected. Additionally, when the mRNAs that were repeated in the top list were considered, only the mRNA with the best p-value and when p-value or FC were out of the cutoff, the mRNAs were not evaluated.

The list of top LV miRNAs differentially expressed (|FC| > 2; p-value <0.0.5) of diabetic and control rats from GSE44179 dataset were also selected using GEO2R. The repeated miRNAs of the top list were considered the only one which had the best p-value and when P-value or FC was out of the cutoff, the miRNAs were not evaluated.

3.3. DCM-related gene study

The mRNAs differentially expressed were filtered by |FC| > 2 and p-value <0.0.5 after the analysis by GEO2R and were uploaded into the Ingenuity Pathway Analyses 6 (IPA) software, to identify interactions between genes and to create networks including upstream regulators, signaling pathways, physiological systems and pathophysiological processes. The IPA-cardiac functional tool was used to select the genes involved in cardiotoxicity (hypertrophy, fibrosis and necrosis/cell death) and to generate a summary list of DCM-related mRNAs differential expression for each period of exposure to STZ, according to GSE4745 dataset.

3.4. Regulatory miRNAs of DCM-related mRNAs

TargetScan 7.1. web dataset (23) was used to search the regulatory miRNAs of the DCM-related mRNAs differentially expressed LV of rats at the three periods of the STZ treatment. The analysis uses algorithms for target site predictions based on miRNA-mRNA interactions and provides a context++ model of miRNA target efficacy which is the more predictive than any published model and at least as predictive as the most informative in vivo crosslink approaches. The miRNA-mRNA interactions according to IPA software and TargetScan 7.1. web dataset were constructed in the IPA tool.

3.5. Integrative mRNA-miRNA Analysis

The integrative analysis was performed using the miRNAs differentially expressed in GSE44179 dataset and the miRNAs selected by the TargetScan 7.1. web dataset predictive tools, as having a regulatory role on GSE4745 differentially expressed mRNAs. The Venn diagram was used to evaluate the number of miRNAs commonly found in both sets of miRNAs.

3.6. Statistical analysis

The Limma (linear models for microarray data) was used to summarize the results of the linear model, perform hypothesis tests and to adjust the p-values for multiple testing (24). The Fold-Change (FC) is a measuring of the changes in the expression level of a gene, and it was considered significant when |FC| > 2.0. between two experimental conditions (control and diabetic samples in both datasets). The Benjamini & Hochberg false discovery rate method was selected because it is the most commonly used method for adjustment of p-values for analysis of microarray data and provides a good balance between discovery of statistically significant genes and limitation of false positives; p-value <0.0.5 was considered significant. The context++ score generated by TargetScan 7.1. web dataset is a method used to predict miRNA target efficacy (23).

4. Results

4.1. mRNA and miRNA differentially expressed in rat LV

The analysis of mRNAs differentially expressed in LV of STZ-induced diabetic rats resulted in 3 lists of 85, 113 and 154 mRNAs that were differentially and significantly expressed considering |FC| > 2; p-value <0.0.5, significant values, respectively, at 3, 28 and 42 days after STZ induction, compared to control rats (Table 3).

The data from GSE44179 showed that 29 miRNAs were differentially and significantly expressed (|FC| > 2; p-value <0.0.5) in LV of rats with diabetes induced by high fat diet and STZ in comparison with non-diabetic rats. Eleven miRNAs were down-regulated: rno-mir-122, rno-mir-184, rno-mir-151, rno-miR-194, rno-mir-22, rno-mir-214, rno-miR-30-c2*, rno-mir-320, rno-mir-204, rno-mir-342 and rno-mir-877; and eighteen were up-regulated: rno-mir-34a, rno-miR-7a, rno-mir-532, rno-mir-21, rno-mir-200c, rno-miR-17-3p, rno-miR-7a*, rno-mir-186, rno-mir-203, rno-mir-322, rno-mir-187, rno-mir-92b, rno-mir-148b, rno-mir-466c, rno-mir-20b, rno-miR-9*, rno-mir-188 and rno-mir-199a compared to control rats (Table 4).

4.2. DCM-related differentially expressed mRNAs

The DCM-related gene analysis by the IPA cardiac function tool showed that seven differentially expressed mRNAs (GSE4745 dataset) were associated with cardiotoxicity (Table 1 and Table 5). Hk2 gene was associated with cardiac necrosis and cell death, at 3, 28 and 42 days after STZ-induced diabetes. Nppa and Txnip at 28 and 42 days, and Fstl1 and Hspb1 at 42 days, were also associated with cardiac necrosis and cell death by different mechanisms. The Pla2g2a gene was related to cardiac fibrosis at all periods studied, whereas Agtr1 and Nppa were associated with cardiac hypertrophy, after 28 and 42 days of the STZ treatment.

Table 1. DCM-related mRNAs differentially expressed in left ventricle of STZ-induced diabetic rats

Period

Categories

Dysfunctions

mRNAs

p-value

Day 3

Cardiac Necrosis/Cell Death

Survival Of Ventricular Myocytes

Hk21

0.03190

Cardiac Fibrosis

Perivascular Fibrosis

Pla2g2a 1

0.00462

Day 28

Cardiac Necrosis/Cell Death

Survival Of Ventricular Myocytes

Hk21

0.04030

Apoptosis Of Cardiomyocyte

Nppa, Txnip

0.06020

Cardiac Fibrosis

Perivascular Fibrosis

Pla2g2a1

0.00585

Cardiac Hypertrophy

Hypertrophy Of Cardiomyocyte

Agtr1, Nppa

0.04400

Day 42

Cardiac Necrosis/Cell Death

Survival Of Ventricular Myocytes

Hk21

0.04340

Cell Death Of Cardiomyocytes

Fstl1,Hspb1,Nppa, Txnip

0.00198

Apoptosis Of Cardiomyocytes

Fstl1, Nppa, Txnip

0.00915

Apoptosis Of Ventricular Myocytes

Fstl1

0.05550

Cardiac Fibrosis

Perivascular Fibrosis

Pla2g2a 1

0.00632

Cardiac Hypertrophy

Hypertrophy Of Cardiomyocytes

Agtr1, Nppa

0.05050

The relationship between cardiac dysfunction and DCM-related mRNAs carried out by IPA software using mRNAs downloaded from GSE4745 dataset.1 mRNAs differentially expressed in three time points (Hk2 and Pla2g2a). DCM: diabetic cardiomiopathy

Regarding the fold regulation of the DCM-related mRNAs at day 3 after STZ-induction, the Pla2g2a was up- regulated (LogFC 1.0.5) and Hk2 down-regulated (LogFC -1.8.82); at day 28, Hk2 and Agtr1a were up-regulated (LogFC 2.1.53 and 2.0.19, respectively) and Pla2g2a and Nppa were down-regulated (LogFC -1.0.45 and -1.2.12, respectively); and at day 42, Pla2g2a, Agtr1a, Nppa and Txnip were up-regulated (LogFC 1.7.35, 1.7.86, 2.9.04 and 1.6.17, respectively) Hk2, Fstl1 and Hspb1 were down-regulated (LogFC -4.1.59, -1.3.28 and -1.0.05, respectively).

4.3. Regulatory miRNAs of DCM-related mRNAs

The TargetScan 7.1. web dataset predicted regulatory miRNAs of the DCM-related mRNAs from the previous analysis of the GSE4745 dataset. miRNAs target Pla2g2a (23 miRNAs), Hk2 (175 miRNAs), Agtr1 (78 miRNAs), Nppa (22 miRNAs), Fstl1 (196 miRNAs), Hspb1 (11 miRNAs) and Txnip (134 miRNAs) (Table 6).

4.4. mRNA-miRNAs integrative analysis

The Venn diagram was performed to evaluate the relationship of miRNAs found differentially expressed in the GSE44179 and the regulatory miRNAs of DCM-related mRNAs differentially expressed in the periods evaluated in GSE4745 dataset (igure 2). Interestingly, ten miRNAs (rno-mir-214, rno-mir-320, rno-mir-877, rno-mir-34a, rno-mir-532, rno-mir-21, rno-miR-17-3p, rno-mir-322, rno-mir-187 and rno-mir-188) were differently expressed in the GSE44179 data (Table 4) and were associated with the DCM-related mRNAs in all periods evaluated, as shown in Table 2.

Table 2. DCM-related regulatory miRNAs and mRNAs targets differentially expressed in left ventricle of STZ-induced diabetic rats

GSE44179 data set

GSE4745 dataset

Regulatory miRNAS

logFC

p-value

Target mRNAS

Period (days)

Dysfunction

LogFC

p-value

rno-miR-184

-2.09↓

0.03708

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

rno-miR-17-3p

1.647↑

0.01334

Fstl1

42

CN

-1.328↓

0.00013

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

Txnip

42

CN

1.617↑

0.00006

rno-miR-187

1.355↑

0.02161

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

rno-miR-34a

2.606↑

0.00424

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

rno-miR-322

1.433↑

0.00451

Fstl1

42

CN

-1.328↓

0.00013

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

Txnip

42

CN

1.617↑

0.00006

rno-miR-214

-1.25↓

0.01773

Fstl1

42

CN

-1.328↓

0.00013

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

Pla2g2a

3

CF

1.050↑

0.00576

28

CF

-1.045↓

0.00071

42

CF

1.735↑

0.00009

Txnip

42

CN

1.617↑

0.00006

rno-miR-188

1.091↑

0.04111

Agtr1

28

CH

2.019↑

0.00064

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

rno-miR-532

2.149↑

0.04686

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

Txnip

42

CN

1.617↑

0.00006

rno-miR-21

2.133↑

0.00009

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

rno-miR-320

-1.18↓

0.02567

Fstl1

42

CN

-1.328↓

0.00013

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

Pla2g2a

3

CF

1.050↑

0.00576

28

CF

-1.045↓

0.00071

42

CF

1.735↑

0.00009

Txnip

42

CN

1.617↑

0.00006

rno-miR-342

-1.08↓

0.01603

Fstl1

42

CN

-1.328↓

0.00013

Hk2

3

CN

-1.882↓

0.00389

28

CN

2.153↑

0.00001

42

CN

-4.159↓

0.00004

Txnip

42

CN

1.617↑

0.00006

rno-miR-877

-1.01↓

0.02886

Pla2g2a

3

CF

1.050↑

0.00576

28

CF

-1.045↓

0.00071

42

CF

1.735↑

0.00009

CN: cardiac necrosis and cell death; CF: cardiac fibrosis; CH: cardiac hypertrophy; DCM: diabetic cardiomiopathy; logFC: Log2-fold change. Negative and positive logFC values indicate down (↓) and up (↑) regulation, respectively.
Table 3. Differentially expressed mRNAs in left ventricle at 3, 28 and 42 day after STZ-induction

Day 3

Day 28

Day 42

mRNA

FC

logFC

p-value

mRNA

FC

logFC

p-value

mRNA

FC

logFC

p-value

Acot1

14.0160

3.809

0.00129

Acot1

18.1136

-4.179

0.000155

Hmgcs2

134.9237

7.076

0.000000002

Cyp2e1

7.5632

2.919

0.00455

Hmgcs2

14.7128

-3.879

0.000517

Hspa1b/1a

102.1822

-6.675

0.000000057

Myh7

7.2200

2.852

0.00018

Cyp7a1

8.7362

3.127

0.001110

Acot1

92.7966

6.536

0.000001060

Spta1

7.0031

2.808

0.01359

Hmgcs2

7.4178

-2.891

0.000001

Alox15

25.8304

4.691

0.000000768

Pygl

6.3423

-2.665

0.00464

Dlg2

5.3591

-2.422

0.010300

Hspa1b/1a

24.4710

-4.613

0.000000229

Hmgcs2

5.6451

2.497

0.00003

Alox15

5.1982

-2.378

0.002760

Hmgcs2

23.9342

4.581

0.000000004

Myc

4.7272

2.241

0.00425

Tgm1

5.1946

-2.377

0.000153

Cyp2e1

23.0229

4.525

0.000038800

Penk

4.6719

2.224

0.00204

Pgf

4.9041

2.294

0.004670

Hspa1b/1a

21.9477

-4.456

0.000000274

Scg5

4.2018

-2.071

0.01159

Serpinb3a

4.9007

2.293

0.001250

Hk2

17.8642

-4.159

0.000043800

Kif4a

4.1382

-2.049

0.01291

Pik3c2g

4.7833

-2.258

0.000002

Hspa1b/1a

16.6910

-4.061

0.000002060

Vps33b

4.1325

2.047

0.00891

Gpam

4.7240

-2.240

0.002250

Hspa1a

15.7579

-3.978

0.000000133

Pik3r1

3.9917

-1.997

0.00870

Gpam

4.7076

-2.235

0.000095

Dbp

14.2313

-3.831

0.000000187

Cdk1

3.9504

-1.982

0.00032

Sctr

4.6332

2.212

0.009440

H19

12.2355

3.613

0.000000289

Gdf10

3.8960

1.962

0.00864

C2cd4b

4.6044

-2.203

0.000010

Rt1ba

10.2461

-3.357

0.000000229

Ddias

3.8825

1.957

0.00412

Pc

4.5726

2.193

0.000679

Cyp26b1

9.8015

3.293

0.000002470

Pik3c2g

3.6884

1.883

0.00150

Csap1

4.5253

2.178

0.007290

Cebpd

8.3166

3.056

0.000213000

Hk2

3.6859

-1.882

0.00389

Hk2

4.4475

2.153

0.000006

Rt1da

7.9173

-2.985

0.000005780

Pdzd4

3.4750

1.797

0.00126

Cbr1

4.0954

-2.034

0.000007

Dbp

7.6529

-2.936

0.000000179

Muc5ac

3.4726

1.796

0.00667

Agtr1a

4.0530

2.019

0.000638

Nppa

7.4850

2.904

0.000004540

Sbf2

3.3987

1.765

0.01505

Nr2f1

4.0250

-2.009

0.003610

Pik3c2g

7.4436

2.896

0.000001790

Igfbp5

3.2648

-1.707

0.00090

Ptgfr

3.7347

-1.901

0.002070

Col3a1

7.2000

-2.848

0.000126000

Clcnkb

3.2021

-1.679

0.00895

Adra1d

3.7115

1.892

0.000410

Nppa

7.0323

2.814

0.000030200

Asf1b

3.1777

-1.668

0.00899

Bdh1

3.6859

1.882

0.000156

Ucp3

6.8828

2.783

0.000003430

Kbtbd3

3.1711

-1.665

0.01990

Fam96b

3.6833

-1.881

0.000088

Ptgfr

6.8116

2.768

0.000022000

Dync1li2

3.1624

1.661

0.00356

Kcne1

3.6833

1.881

0.003550

Adra1d

6.7693

-2.759

0.000572000

Chad

3.1037

1.634

0.00262

Myl1

3.6503

1.868

0.007900

Pdp2

6.4442

-2.688

0.000003990

Spt1

3.1016

1.633

0.01112

Nalcn

3.5382

1.823

0.008440

Cd74

5.7438

-2.522

0.000119000

Aadat

3.0589

-1.613

0.00702

Hmgcr

3.5113

1.812

0.003730

Acsl6

5.6923

-2.509

0.000172000

Mmp16

3.0483

-1.608

0.01518

Penk

3.5016

-1.808

0.000279

Nr4a1

5.6256

-2.492

0.000132000

Krt19

3.0420

1.605

0.00771

Ckb

3.3104

1.727

0.000615

Cd74

5.4755

-2.453

0.000013600

Smarca2

3.0420

-1.605

0.01903

Jak3

3.2716

-1.710

0.000295

Kcnd3

5.2890

-2.403

0.000269000

Shbg

2.9752

-1.573

0.01231

Cyp2e1

3.2535

-1.702

0.005560

Higd1a

5.2561

-2.394

0.000034800

Tspy1

2.9649

1.568

0.01878

Cyp2c11

3.1755

-1.667

0.007660

Hsph1

5.2525

-2.393

0.000167000

Hbe2/Hbg1

2.8501

1.511

0.01923

Decr1

3.1210

-1.642

0.000047

Cyp2e1

5.1982

2.378

0.000050400

Cat

2.8324

1.502

0.01006

Myh7

3.0483

-1.608

0.000599

Ckb

5.0771

-2.344

0.000071900

Dbh

2.8304

1.501

0.01998

Acot2

3.0314

-1.600

0.000316

Nppa

4.9348

2.303

0.000030600

Idh1

2.7818

1.476

0.00075

Plcb2

3.0314

1.600

0.001680

Bdh1

4.8099

-2.266

0.000040600

Obp3

2.7779

1.474

0.00517

Mmp16

3.0147

-1.592

0.003840

Cckar

4.7999

2.263

0.000004480

Dio1

2.7721

1.471

0.00312

Asf1b

2.9526

1.562

0.015200

Tmem171

4.7800

2.257

0.000024700

Ascl2

2.7683

1.469

0.00531

Ppp2r2b

2.9322

1.552

0.011300

Klk1

4.6946

-2.231

0.000076600

Txnl4b

2.7094

1.438

0.00456

Cited2

2.8959

-1.534

0.010000

Cyp2e1

4.6784

2.226

0.000285000

Sult1a1

2.6963

1.431

0.00232

Pgd/8kif1b

2.8779

-1.525

0.006880

Mx2

4.5789

-2.195

0.000195000

Top2a

2.6519

-1.407

0.00294

Inhbb

2.8540

1.513

0.001360

Col15a1

4.5631

-2.190

0.000002720

Tfrc

2.6244

-1.392

0.01610

Cdk18

2.8461

1.509

0.000729

Aldoc

4.5284

2.179

0.000426000

Cfd

2.6099

1.384

0.01819

Fbxo21

2.8382

-1.505

0.007990

Cd74

4.5096

-2.173

0.000022100

Bdh1

2.6027

-1.380

0.01944

Ccl3

2.8031

1.487

0.013200

Dclk1

4.4816

-2.164

0.000697000

Ace

2.5633

-1.358

0.01129

Ckb

2.7625

1.466

0.001700

Cbr1

4.4260

2.146

0.000623000

Ckb

2.5580

-1.355

0.00266

Acot2/Acot1

2.7530

-1.461

0.000435

Ucp3

4.3711

2.128

0.000119000

Pdp2

2.5245

-1.336

0.00028

Cyp2f4

2.7454

1.457

0.015200

Col1a2

4.2841

-2.099

0.000055500

Eno3

2.5036

-1.324

0.01080

G0s2

2.7378

-1.453

0.001380

Kcnq1

4.2164

-2.076

0.000262000

Pdk4

2.4880

1.315

0.00053

Olr1687

2.7264

-1.447

0.000879

Hsph1

4.1612

-2.057

0.000034900

Ivns1abp

2.4538

1.295

0.00299

Pdk4

2.6963

-1.431

0.001600

Nr4a1

4.1468

-2.052

0.000022800

Jdp2

2.4538

1.295

0.00682

Acot2

2.6945

-1.430

0.002230

Entpd2

4.1468

-2.052

0.000099300

Vipr2

2.4217

1.276

0.01533

Gpc3

2.6907

-1.428

0.005410

Acot2

4.0418

2.015

0.000005900

Chrnb4

2.3768

-1.249

0.00157

Pc

2.6833

1.424

0.001740

Col1a1

4.0139

-2.005

0.000143000

Eci1

2.3359

-1.224

0.00328

Cybrd1

2.6647

-1.414

0.003530

Rt1dmb

3.9917

-1.997

0.000126000

Alox15

2.3166

1.212

0.00376

Aldoc

2.6647

-1.414

0.003550

Ntsr2

3.9231

-1.972

0.000220000

Krtap15

2.3118

-1.209

0.00114

Spink3

2.6463

1.404

0.003970

Slc2a1

3.8852

-1.958

0.000044700

Pgr

2.3086

-1.207

0.01783

Pdlim5

2.6372

-1.399

0.000054

Acot2

3.8211

1.934

0.000004130

Sult1a1

2.2990

1.201

0.00277

Pfkfb3

2.6372

-1.399

0.004420

Mgst1

3.7633

1.912

0.000003530

Decr1

2.2942

1.198

0.00071

Serpini2

2.6281

1.394

0.003560

Igfbp3

3.7347

1.901

0.000054800

Lphn3

2.2847

1.192

0.01906

Fshb

2.5991

1.378

0.006140

Rt1da

3.6528

-1.869

0.000549000

Cyss

2.2486

1.169

0.01124

Proc

2.5901

1.373

0.010700

Gstm5

3.6075

1.851

0.000004830

Lin7a

2.2423

1.165

0.01667

Ntsr2

2.5651

1.359

0.061900

Col3a1

3.6025

-1.849

0.000026800

Fdft1

2.2115

1.145

0.00040

Impa2

2.5580

-1.355

0.000296

Bhlhe41

3.5529

-1.829

0.000012300

Ache

2.2099

1.144

0.01281

Sctr

2.5527

1.352

0.000691

Arhgap1

3.5455

1.826

0.000132000

Ephx1

2.2084

1.143

0.00019

Hpd

2.5509

1.351

0.002100

Gpc3

3.5210

1.816

0.000290000

Fbxo21

2.1795

1.124

0.00455

Thy1

2.5298

1.339

0.011300

Slc2a4

3.5186

-1.815

0.000026800

Racgap1

2.1660

-1.115

0.00361

Gclc

2.5263

-1.337

0.008750

Scd

3.4629

-1.792

0.000018800

Casq1

2.1600

-1.111

0.00010

Decr1

2.5123

-1.329

0.000578

Rt1db1

3.4534

-1.788

0.000002920

Unc13c

2.1555

-1.108

0.01759

Atp2b2

2.5105

1.328

0.002400

Agtr1a

3.4486

1.786

0.000000860

Alox15

2.1332

1.093

0.00052

Nrgn

2.5001

-1.322

0.013100

Col1a1

3.3473

-1.743

0.000178000

Cbr1

2.1199

1.084

0.00235

Nolc1

2.4949

1.319

0.007160

Pla2g2a

3.3288

1.735

0.000089900

Mmadhc

2.1067

-1.075

0.00351

Bcat2

2.4915

1.317

0.000104

Scd

3.2535

-1.702

0.000216000

Hpn

2.1067

-1.075

0.01111

Amhr2

2.4880

1.315

0.011600

Col1a1

3.2513

-1.701

0.000119000

Spock2

2.1009

1.071

0.00407

Foxq1

2.4811

1.311

0.007980

Crybb1

3.2310

-1.692

0.000679000

Fam111a

2.0994

-1.070

0.01692

Figf

2.4777

-1.309

0.001470

Dnajb1

3.2109

-1.683

0.000164000

Alb

2.0965

1.068

0.00293

Hsd17b4

2.4657

-1.302

0.009540

Lum

3.1821

-1.670

0.000010500

Anxa6

2.0907

-1.064

0.00437

Ephx2

2.3522

-1.234

0.013500

Decr1

3.1362

1.649

0.000025200

Inha

2.0849

-1.060

0.00159

Timeless

2.3440

1.229

0.013900

Gstm5

3.1318

1.647

0.000015900

Pla2g2a

2.0705

1.05

0.00576

Slc2a1

2.3359

1.224

0.000744

Txnip

3.0674

1.617

0.000064400

Cnih2

2.0720

1.051

0.00531

Nppa

2.3166

-1.212

0.012100

Eno3

3.0293

-1.599

0.000058700

Prf1

2.0619

1.044

0.01278

Dnph1

2.3118

-1.209

0.003270

Col1a1

2.9980

-1.584

0.000446000

Ucp3

2.0449

1.032

0.00340

Gadd45a

2.2958

1.199

0.003560

Igfbp3

2.9876

1.579

0.000405000

Txnl4b

2.2942

-1.198

0.000910

Ckb

2.9180

-1.545

0.000065300

Ucp3

2.2910

-1.196

0.003880

Sult1a1

2.9120

1.542

0.000097000

Pbsn

2.2799

1.189

0.013800

Pfkp

2.8899

1.531

0.000094400

Ugt1a1

2.2454

-1.167

0.000501

Pdp2

2.8540

-1.513

0.000011600

Olr1

2.2191

-1.150

0.012300

Pcsk6

2.8461

-1.509

0.000116000

Aqp7

2.2069

-1.142

0.000621

Aqp1

2.7972

-1.484

0.000034900

Fcer1a

2.1856

1.128

0.001910

Entpd2

2.7837

-1.477

0.000012900

Ech1

2.1750

-1.121

0.000966

Pak3

2.7492

1.459

0.000382000

Ache

2.1750

1.121

0.012200

Pxmp2

2.7038

-1.435

0.000003700

Cd36

2.1435

-1.100

0.005400

Ctsk

2.6759

-1.420

0.000085500

P2ry1

2.1184

1.083

0.006230

Man2a1

2.6740

-1.419

0.000573000

Pxmp2

2.1170

1.082

0.000295

Vamp5

2.6317

1.396

0.000026000

Setd1b

2.1126

-1.079

0.010000

Cd36

2.6172

1.388

0.000039900

Slc40a1

2.1082

-1.076

0.001720

Scn1a

2.5740

1.364

0.000454000

Acot7

2.0936

-1.066

0.005670

Ngfrap1

2.5651

1.359

0.000164000

Slc2a4

2.0907

1.064

0.000907

Dnajb1

2.5385

-1.344

0.000096100

Clrn3

2.0864

1.061

0.004410

Gstt2

2.5368

1.343

0.000521000

Hk2

2.0835

1.059

0.000211

Cebpd

2.5245

1.336

0.000566000

Txnip

2.0835

-1.059

0.000479

Chordc1

2.5175

-1.332

0.000143000

Pla2g2a

2.0634

-1.045

0.000710

Fstl1

2.5105

-1.328

0.000134000

Kcna4

2.0520

-1.037

0.003230

H19

2.5019

1.323

0.000441000

Aqp1

2.0406

1.029

0.001390

Slc6a6

2.4915

1.317

0.000253000

Chrna1

2.0350

1.025

0.015200

Bdnf

2.4743

1.307

0.000579000

Scd

2.0335

1.024

0.002490

Dnaja1

2.4674

-1.303

0.000373000

Hmox1

2.0293

1.021

0.009060

Adh1

2.4572

-1.297

0.000243000

Pdp2

2.0153

1.011

0.0007697

Decr1

2.4083

1.268

0.000029000

Sparc

2.4033

-1.265

0.000222000

Cyp1a1

2.4016

1.264

0.000652000

Slc3a2

2.3999

1.263

0.000563000

Slc41a3

2.3983

1.262

0.000111000

Pcsk6

2.3933

-1.259

0.000036600

Cyp11a1

2.3834

-1.253

0.000012000

Pc

2.3424

-1.228

0.000410000

Tcap

2.3359

-1.224

0.000193000

Ros1

2.3054

-1.205

0.000178000

Slc3a2

2.2958

1.199

0.000441000

Cd36

2.2894

1.195

0.000101000

Ddit3

2.2815

-1.190

0.000436000

Ccnd1

2.2768

-1.187

0.000107000

Sparc

2.2752

-1.186

0.000146000

Maoa

2.2721

-1.184

0.000511000

Echs1

2.2517

-1.171

0.000345000

Nr1d2

2.2454

-1.167

0.000402000

Sparc

2.2268

-1.155

0.000104000

Ivd

2.2038

-1.140

0.000013700

Txnip

2.1977

1.136

0.000267000

Ppap2a

2.1780

1.123

0.000330000

Gstp1

2.1406

1.098

0.000785000

Klf10

2.1391

1.097

0.000481000

Alox15

2.1170

1.082

0.000590000

Rab11b

2.1155

1.081

0.000334000

Slc2a4

2.1111

-1.078

0.000571000

Ndufa4l2

2.0994

-1.070

0.000727000

Ptprs

2.0980

1.069

0.000164000

Aqp7

2.0965

1.068

0.000030400

Eno2

2.0922

1.065

0.000100000

Myc

2.0878

1.062

0.000344000

Insig1

2.0878

1.062

0.000362000

Aldh1a1

2.0835

-1.059

0.000169000

Sult1a1

2.0835

1.059

0.000607000

Gstm1

2.0748

1.053

0.000050700

Tns3

2.0720

1.051

0.000017700

Ptpn3

2.0634

-1.045

0.000757000

Lamb2

2.0520

1.037

0.000259000

Cst3

2.0392

1.028

0.000022500

Gstm1

2.0378

1.027

0.000068100

Dbi

2.0111

1.008

0.000022300

Hspb1

2.0069

-1.005

0.000329000

Table 4. Differentially expressed miRNAs list in left ventricle of STZ-induced diabetic rats.

miRNAs

FC

logFC

p-value

rno-mir-122

17.81475

-4.16

0.00946

rno-mir-34a

6.088134

2.606

0.00424

rno-miR-7a

4.559893

2.189

0.00378

rno-mir-532

4.435203

2.149

0.04686

rno-mir-21

4.386286

2.133

0.00009

rno-mir-184

4.260433

-2.09

0.03708

rno-mir-200c

4.027822

2.01

0.00390

rno-mir-151

3.317278

-1.73

0.02562

rno-miR-17-3p

3.131817

1.647

0.01334

rno-miR-7a*

3.088701

1.627

0.01492

rno-mir-186

2.751084

1.46

0.02763

rno-mir-203

2.741566

1.455

0.00089

rno-mir-322

2.700076

1.433

0.00451

rno-mir-187

2.557971

1.355

0.02161

rno-miR-194

2.489748

-1.32

0.03604

rno-mir-22

2.479415

-1.31

0.03703

rno-mir-92b

2.472551

1.306

0.01080

rno-mir-148b

2.399943

1.263

0.00289

rno-mir-214

2.381714

-1.25

0.01773

rno-miR-30-c2*

2.268911

-1.18

0.00497

rno-mir-320

2.267339

-1.18

0.02567

rno-mir-466c

2.233026

1.159

0.00071

rno-mir-204

2.222217

-1.15

0.02982

rno-mir-20b

2.185555

1.128

0.03483

rno-miR-9*

2.131693

1.092

0.03587

rno-mir-188

2.130216

1.091

0.04111

rno-mir-342

2.116969

-1.08

0.01603

rno-mir-199a

2.108183

1.076

0.01991

rno-mir-877

2.012516

-1.01

0.02886

Table 5. DCM-related mRNAs differentially expressed in ventricle of STZ-induced diabetic rats

Period

mRNA

FC

logFC

p-value

Day 3

Hk2

3.6859

-1.882

0.003890

Pla2g2a

2.0705

1.05

0.005760

Day 28

Hk2

4.4475

2.153

0.000006

Pla2g2a

2.0634

-1.045

0.000710

Agtr1a

4.0530

2.019

0.000640

Nppa

2.3166

-1.212

0.012100

Day 42

Hk2

17.8642

-4.159

0.000044

Pla2g2a

3.3288

1.735

0.000090

Nppa

7.4850

2.904

0.000004

Fstl1

2.5105

-1,328

0.000134

Hspb1

2.0069

-1.005

0.000329

Txnip

3.0674

1.617

0.000064

Table 6. DCM-related mRNAs differentially expressed in left ventricle 3, 28 and 42 days after STZ-induction and their regulatory miRNAs

mRNAs Target

miRNAs

Context++Score

Conservation

Agtr1

rno-miR-760-3p

-0.48

Poorly conserved sites

rno-miR-652-5p

-0.46

Poorly conserved sites

rno-miR-219a-5p

-0.45

Poorly conserved sites

rno-miR-711

-0.44

Poorly conserved sites

rno-miR-96-5p

-0.4

Poorly conserved sites

rno-miR-547-5p

-0.33

Poorly conserved sites

rno-miR-881-3p

-0.33

Poorly conserved sites

rno-miR-7a-1-3p

-0.3

Poorly conserved sites

rno-miR-1306-5p

-0.29

Poorly conserved sites

rno-miR-873-5p

-0.28

Poorly conserved sites

rno-miR-466b-2-3p

-0.28

Poorly conserved sites

rno-miR-466b-4-3p

-0.28

Poorly conserved sites

rno-miR-466b-2-3p

-0.27

Poorly conserved sites

rno-miR-466b-4-3p

-0.27

Poorly conserved sites

rno-miR-7a-5p

-0.26

Poorly conserved sites

rno-miR-7b

-0.26

Poorly conserved sites

rno-miR-3065-5p

-0.25

Poorly conserved sites

rno-miR-194-5p

-0.25

Poorly conserved sites

rno-miR-3085

-0.25

Poorly conserved sites

rno-miR-29b-1-5p

-0.25

Poorly conserved sites

rno-miR-93-3p

-0.23

Poorly conserved sites

rno-miR-3558-3p

-0.23

Poorly conserved sites

rno-miR-3587

-0.22

Poorly conserved sites

rno-miR-188-3p

-0.22

Poorly conserved sites

rno-miR-216a-3p

-0.21

Poorly conserved sites

rno-miR-139-3p

-0.21

Poorly conserved sites

rno-miR-344b-5p

-0.21

Poorly conserved sites

rno-miR-29b-1-5p

-0.21

Poorly conserved sites

rno-miR-215

-0.2

Poorly conserved sites

rno-miR-673-5p

-0.2

Poorly conserved sites

rno-miR-221-3p

-0.2

Poorly conserved sites

rno-miR-222-3p

-0.2

Poorly conserved sites

rno-miR-192-5p

-0.19

Poorly conserved sites

Agtr1

rno-miR-344g

-0.19

Poorly conserved sites

rno-miR-139-5p

-0.19

Poorly conserved sites

rno-miR-377-3p

-0.19

Poorly conserved sites

rno-miR-466b-4-3p

-0.19

Poorly conserved sites

rno-miR-466b-2-3p

-0.19

Poorly conserved sites

rno-miR-466b-2-3p

-0.19

Poorly conserved sites

rno-miR-466b-4-3p

-0.19

Poorly conserved sites

rno-miR-3547

-0.18

Poorly conserved sites

rno-miR-224-3p

-0.18

Poorly conserved sites

rno-miR-653-5p

-0.18

Poorly conserved sites

rno-miR-208a-3p

-0.18

Poorly conserved sites

rno-miR-208b-3p

-0.18

Poorly conserved sites

rno-miR-344b-5p

-0.17

Poorly conserved sites

rno-miR-344g

-0.17

Poorly conserved sites

rno-miR-3593-3p

-0.17

Poorly conserved sites

rno-miR-182

-0.17

Poorly conserved sites

rno-miR-452-5p

-0.17

Poorly conserved sites

rno-miR-383-3p

-0.17

Poorly conserved sites

rno-miR-592

-0.16

Poorly conserved sites

rno-miR-3596d

-0.16

Poorly conserved sites

rno-miR-98-3p

-0.16

Poorly conserved sites

rno-let-7b-3p

-0.15

Poorly conserved sites

rno-miR-3596d

-0.15

Poorly conserved sites

rno-let-7c-2-3p

-0.15

Poorly conserved sites

rno-let-7f-1-3p

-0.15

Poorly conserved sites

rno-let-7a-1-3p

-0.15

Poorly conserved sites

rno-miR-98-3p

-0.15

Poorly conserved sites

rno-miR-3575

-0.14

Poorly conserved sites

rno-miR-511-3p

-0.14

Poorly conserved sites

rno-miR-101a-5p

-0.14

Poorly conserved sites

rno-miR-544-3p

-0.14

Poorly conserved sites

rno-miR-499-5p

-0.14

Poorly conserved sites

rno-miR-26b-3p

-0.14

Poorly conserved sites

rno-let-7c-2-3p

-0.14

Poorly conserved sites

rno-let-7f-1-3p

-0.14

Poorly conserved sites

rno-let-7a-1-3p

-0.14

Poorly conserved sites

rno-miR-466c-3p

-0.14

Poorly conserved sites

rno-miR-139-5p

-0.13

Poorly conserved sites

rno-let-7f-2-3p

-0.13

Poorly conserved sites

rno-let-7b-3p

-0.13

Poorly conserved sites

rno-miR-466c-3p

-0.13

Poorly conserved sites

rno-miR-330-3p

-0.12

Poorly conserved sites

rno-miR-466c-3p

-0.12

Poorly conserved sites

rno-let-7f-2-3p

-0.12

Poorly conserved sites

rno-miR-149-5p

-0.11

Poorly conserved sites

rno-miR-9a-3p

-0.11

Poorly conserved sites

rno-miR-350

-0.11

Poorly conserved sites

rno-miR-204-3p

-0.11

Poorly conserved sites

rno-miR-466c-3p

-0.11

Poorly conserved sites

rno-miR-466b-2-3p

-0.11

Poorly conserved sites

rno-miR-466b-4-3p

-0.11

Poorly conserved sites

Agtr1

rno-miR-208b-5p

-0.1

Poorly conserved sites

rno-miR-466b-2-3p

-0.1

Poorly conserved sites

rno-miR-466b-4-3p

-0.1

Poorly conserved sites

rno-miR-3085

-0.09

Poorly conserved sites

rno-miR-674-5p

-0.09

Poorly conserved sites

rno-miR-196c-3p

-0.09

Poorly conserved sites

rno-miR-881-5p

-0.09

Poorly conserved sites

rno-miR-466c-3p

-0.09

Poorly conserved sites

rno-miR-871-5p

-0.08

Poorly conserved sites

rno-miR-3585-5p

-0.08

Poorly conserved sites

rno-miR-881-5p

-0.08

Poorly conserved sites

rno-miR-743a-5p

-0.08

Poorly conserved sites

rno-miR-466c-3p

-0.08

Poorly conserved sites

rno-miR-743a-5p

-0.07

Poorly conserved sites

rno-miR-323-3p

-0.07

Poorly conserved sites

rno-miR-26b-5p

-0.07

Poorly conserved sites

rno-miR-871-5p

-0.07

Poorly conserved sites

rno-miR-208a-5p

-0.06

Poorly conserved sites

rno-miR-26a-5p

-0.06

Poorly conserved sites

rno-miR-144-3p

-0.06

Poorly conserved sites

rno-miR-471-3p

-0.04

Poorly conserved sites

rno-miR-101b-3p

-0.04

Poorly conserved sites

rno-miR-101a-3p

-0.04

Poorly conserved sites

rno-miR-488-3p

-0.03

Poorly conserved sites

rno-miR-873-5p

-0.02

Poorly conserved sites

rno-miR-132-3p

-0.02

Poorly conserved sites

rno-miR-551b-5p

-0.02

Poorly conserved sites

rno-miR-543-3p

-0.02

Poorly conserved sites

rno-miR-212-3p

-0.01

Poorly conserved sites

rno-miR-32-3p

-0.01

Poorly conserved sites

rno-miR-19b-1-5p

-0.01

Poorly conserved sites

rno-miR-19b-2-5p

-0.01

Poorly conserved sites

rno-miR-3551-3p

-0.01

Poorly conserved sites

rno-miR-3551-3p

-0.01

Poorly conserved sites

rno-miR-3551-3p

-0.01

Poorly conserved sites

rno-miR-410-3p

-0.01

Poorly conserved sites

rno-miR-344b-1-3p

-0.01

Poorly conserved sites

Fstl1

rno-miR-31b

N/A

Poorly conserved sites

rno-miR-31b

N/A

Poorly conserved sites

rno-miR-598-5p

-0.62

Poorly conserved sites

rno-miR-1247-5p

-0.54

Poorly conserved sites

rno-miR-340-3p

-0.5

Poorly conserved sites

rno-miR-23a-5p

-0.48

Poorly conserved sites

rno-miR-337-5p

-0.46

Poorly conserved sites

rno-miR-874-5p

-0.43

Poorly conserved sites

rno-miR-6328

-0.41

Poorly conserved sites

rno-miR-3590-5p

-0.37

Poorly conserved sites

rno-miR-29b-3p

-0.35

Conserved sites

rno-miR-29c-3p

-0.35

Conserved sites

rno-miR-29a-3p

-0.35

Conserved sites

rno-miR-652-3p

-0.35

Poorly conserved sites

Fstl1

rno-miR-666-3p

-0.3

Poorly conserved sites

rno-miR-9a-5p

-0.29

Conserved sites

rno-miR-31a-3p

-0.29

Poorly conserved sites

rno-miR-540-5p

-0.28

Poorly conserved sites

rno-miR-191a-5p

-0.28

Poorly conserved sites

rno-miR-1193-5p

-0.27

Poorly conserved sites

rno-miR-203a-5p

-0.27

Poorly conserved sites

rno-miR-218a-2-3p

-0.27

Poorly conserved sites

rno-miR-208b-5p

-0.27

Poorly conserved sites

rno-miR-218a-5p

-0.27

Poorly conserved sites

rno-miR-504

-0.26

Poorly conserved sites

rno-miR-3557-3p

-0.26

Poorly conserved sites

rno-miR-872-5p

-0.26

Poorly conserved sites

rno-miR-29c-5p

-0.26

Poorly conserved sites

rno-miR-124-3p

-0.25

Conserved sites

rno-miR-667-5p

-0.25

Poorly conserved sites

rno-miR-582-3p

-0.25

Poorly conserved sites

rno-miR-137-3p

-0.24

Conserved sites

rno-miR-3064-3p

-0.24

Poorly conserved sites

rno-miR-345-5p

-0.24

Poorly conserved sites

rno-miR-346

-0.24

Poorly conserved sites

rno-miR-378a-3p

-0.23

Conserved sites

rno-miR-22-3p

-0.23

Conserved sites

rno-miR-499-3p

-0.23

Poorly conserved sites

rno-miR-322-3p

-0.23

Poorly conserved sites

rno-miR-200b-3p

-0.22

Conserved sites

rno-miR-200c-3p

-0.22

Conserved sites

rno-miR-18a-5p

-0.22

Poorly conserved sites

rno-miR-30b-3p

-0.22

Poorly conserved sites

rno-miR-412-3p

-0.22

Poorly conserved sites

rno-miR-342-5p

-0.22

Poorly conserved sites

rno-miR-429

-0.21

Conserved sites

rno-miR-206-5p

-0.21

Poorly conserved sites

rno-miR-216a-3p

-0.21

Poorly conserved sites

rno-miR-10a-5p

-0.21

Poorly conserved sites

rno-miR-208a-5p

-0.21

Poorly conserved sites

rno-miR-540-5p

-0.2

Poorly conserved sites

rno-miR-451-3p

-0.2

Poorly conserved sites

rno-miR-497-3p

-0.2

Poorly conserved sites

rno-miR-667-5p

-0.2

Poorly conserved sites

rno-miR-384-3p

-0.19

Poorly conserved sites

rno-miR-224-3p

-0.19

Poorly conserved sites

rno-miR-99a-3p

-0.19

Poorly conserved sites

rno-miR-99b-3p

-0.19

Poorly conserved sites

rno-miR-452-3p

-0.19

Poorly conserved sites

rno-miR-363-3p

-0.18

Conserved sites

rno-miR-134-5p

-0.18

Poorly conserved sites

rno-miR-3564

-0.18

Poorly conserved sites

rno-miR-378a-3p

-0.18

Poorly conserved sites

rno-miR-92a-2-5p

-0.18

Poorly conserved sites

rno-miR-615

-0.18

Poorly conserved sites

Fstl1

rno-miR-743b-5p

-0.18

Poorly conserved sites

rno-miR-3558-3p

-0.18

Poorly conserved sites

rno-miR-540-3p

-0.18

Poorly conserved sites

rno-miR-598-3p

-0.18

Poorly conserved sites

rno-miR-5132-5p

-0.17

Poorly conserved sites

rno-miR-298-3p

-0.17

Poorly conserved sites

rno-miR-327

-0.17

Poorly conserved sites

rno-miR-24-3p

-0.17

Poorly conserved sites

rno-miR-218a-5p

-0.17

Poorly conserved sites

rno-miR-880-3p

-0.17

Poorly conserved sites

rno-miR-32-5p

-0.16

Conserved sites

rno-miR-673-5p

-0.16

Poorly conserved sites

rno-miR-449a-3p

-0.16

Poorly conserved sites

rno-miR-499-5p

-0.16

Poorly conserved sites

rno-miR-741-3p

-0.16

Poorly conserved sites

rno-miR-24-3p

-0.16

Poorly conserved sites

rno-miR-3541

-0.16

Poorly conserved sites

rno-miR-1297

-0.16

Poorly conserved sites

rno-miR-652-5p

-0.16

Poorly conserved sites

rno-miR-138-5p

-0.16

Poorly conserved sites

rno-miR-488-5p

-0.15

Poorly conserved sites

rno-miR-15a-5p

-0.15

Poorly conserved sites

rno-miR-15b-5p

-0.15

Poorly conserved sites

rno-miR-125a-3p

-0.15

Poorly conserved sites

rno-miR-547-5p

-0.15

Poorly conserved sites

rno-miR-378a-5p

-0.15

Poorly conserved sites

rno-miR-877

-0.15

Poorly conserved sites

rno-miR-328a-3p

-0.15

Poorly conserved sites

rno-miR-328b-3p

-0.15

Poorly conserved sites

rno-miR-299a-3p

-0.15

Poorly conserved sites

rno-miR-299b-3p

-0.15

Poorly conserved sites

rno-miR-6323

-0.15

Poorly conserved sites

rno-miR-3594-5p

-0.15

Poorly conserved sites

rno-miR-540-5p

-0.15

Poorly conserved sites

rno-miR-218a-5p

-0.15

Poorly conserved sites

rno-miR-190b-5p

-0.15

Poorly conserved sites

rno-miR-497-5p

-0.14

Poorly conserved sites

rno-miR-16-5p

-0.14

Poorly conserved sites

rno-miR-204-3p

-0.14

Poorly conserved sites

rno-miR-218a-5p

-0.14

Poorly conserved sites

rno-miR-216a-5p

-0.14

Poorly conserved sites

rno-miR-15a-5p

-0.14

Poorly conserved sites

rno-miR-195-5p

-0.14

Poorly conserved sites

rno-miR-15b-5p

-0.14

Poorly conserved sites

rno-miR-140-3p

-0.14

Poorly conserved sites

rno-miR-327

-0.14

Poorly conserved sites

rno-miR-497-3p

-0.14

Poorly conserved sites

rno-miR-3594-5p

-0.14

Poorly conserved sites

rno-miR-25-3p

-0.13

Conserved sites

rno-miR-383-3p

-0.13

Poorly conserved sites

rno-miR-322-5p

-0.13

Poorly conserved sites

Fstl1

rno-miR-363-5p

-0.13

Poorly conserved sites

rno-miR-217-3p

-0.13

Poorly conserved sites

rno-miR-206-3p

-0.13

Poorly conserved sites

rno-miR-1b

-0.13

Poorly conserved sites

rno-miR-1-3p

-0.13

Poorly conserved sites

rno-miR-16-5p

-0.13

Poorly conserved sites

rno-miR-433-3p

-0.13

Poorly conserved sites

rno-miR-92a-2-5p

-0.13

Poorly conserved sites

rno-miR-190a-5p

-0.13

Poorly conserved sites

rno-miR-471-3p

-0.12

Poorly conserved sites

rno-miR-350

-0.12

Poorly conserved sites

rno-miR-486

-0.12

Poorly conserved sites

rno-miR-7578

-0.12

Poorly conserved sites

rno-miR-322-5p

-0.12

Poorly conserved sites

rno-miR-497-5p

-0.12

Poorly conserved sites

rno-miR-323-5p

-0.12

Poorly conserved sites

rno-miR-5132-3p

-0.12

Poorly conserved sites

rno-miR-30c-1-3p

-0.12

Poorly conserved sites

rno-miR-3580-5p

-0.12

Poorly conserved sites

rno-miR-92a-3p

-0.11

Conserved sites

rno-miR-92b-3p

-0.11

Conserved sites

rno-miR-495

-0.11

Poorly conserved sites

rno-miR-214-3p

-0.11

Poorly conserved sites

rno-miR-195-5p

-0.11

Poorly conserved sites

rno-miR-6327

-0.11

Poorly conserved sites

rno-miR-6315

-0.11

Poorly conserved sites

rno-miR-203b-3p

-0.11

Poorly conserved sites

rno-miR-18a-3p

-0.11

Poorly conserved sites

rno-miR-124-5p

-0.11

Poorly conserved sites

rno-miR-743b-5p

-0.11

Poorly conserved sites

rno-miR-3580-5p

-0.11

Poorly conserved sites

rno-miR-881-3p

-0.11

Poorly conserved sites

rno-miR-30c-2-3p

-0.11

Poorly conserved sites

rno-miR-20a-3p

-0.11

Poorly conserved sites

rno-miR-9a-3p

-0.11

Poorly conserved sites

rno-miR-3561-3p

-0.11

Poorly conserved sites

rno-miR-1949

-0.11

Poorly conserved sites

rno-miR-300-5p

-0.1

Poorly conserved sites

rno-miR-547-5p

-0.1

Poorly conserved sites

rno-miR-3084a-3p

-0.1

Poorly conserved sites

rno-miR-3084b-3p

-0.1

Poorly conserved sites

rno-miR-3084d

-0.1

Poorly conserved sites

rno-miR-330-3p

-0.1

Poorly conserved sites

rno-miR-497-3p

-0.1

Poorly conserved sites

rno-miR-547-3p

-0.1

Poorly conserved sites

rno-miR-741-3p

-0.1

Poorly conserved sites

rno-miR-125a-3p

-0.1

Poorly conserved sites

rno-miR-185-5p

-0.1

Poorly conserved sites

rno-miR-18a-3p

-0.1

Poorly conserved sites

rno-miR-221-5p

-0.1

Poorly conserved sites

rno-miR-205

-0.1

Poorly conserved sites

Fstl1

rno-miR-1896

-0.1

Poorly conserved sites

rno-miR-2985

-0.1

Poorly conserved sites

rno-miR-218a-1-3p

-0.1

Poorly conserved sites

rno-miR-675-3p

-0.09

Poorly conserved sites

rno-miR-3589

-0.09

Poorly conserved sites

rno-miR-6331

-0.09

Poorly conserved sites

rno-miR-451-3p

-0.09

Poorly conserved sites

rno-miR-6325

-0.09

Poorly conserved sites

rno-miR-6330

-0.09

Poorly conserved sites

rno-miR-139-5p

-0.09

Poorly conserved sites

rno-miR-370-3p

-0.09

Poorly conserved sites

rno-miR-370-5p

-0.09

Poorly conserved sites

rno-miR-653-5p

-0.09

Poorly conserved sites

rno-miR-138-5p

-0.09

Poorly conserved sites

rno-miR-3084b-3p

-0.09

Poorly conserved sites

rno-miR-3084d

-0.09

Poorly conserved sites

rno-miR-3084a-3p

-0.09

Poorly conserved sites

rno-miR-509-5p

-0.09

Poorly conserved sites

rno-miR-9a-3p

-0.08

Poorly conserved sites

rno-miR-1298

-0.08

Poorly conserved sites

rno-miR-136-5p

-0.08

Poorly conserved sites

rno-miR-452-5p

-0.08

Poorly conserved sites

rno-miR-183-5p

-0.08

Poorly conserved sites

rno-miR-27b-3p

-0.08

Poorly conserved sites

rno-miR-27a-3p

-0.08

Poorly conserved sites

rno-miR-743a-5p

-0.07

Poorly conserved sites

rno-miR-23a-5p

-0.07

Poorly conserved sites

rno-miR-761

-0.07

Poorly conserved sites

rno-miR-539-5p

-0.07

Poorly conserved sites

rno-miR-135a-5p

-0.07

Poorly conserved sites

rno-miR-135b-5p

-0.07

Poorly conserved sites

rno-miR-544-5p

-0.07

Poorly conserved sites

rno-miR-349

-0.07

Poorly conserved sites

rno-miR-1193-3p

-0.07

Poorly conserved sites

rno-miR-452-5p

-0.07

Poorly conserved sites

rno-miR-3553

-0.07

Poorly conserved sites

rno-miR-33-5p

-0.07

Poorly conserved sites

rno-miR-212-5p

-0.07

Poorly conserved sites

rno-miR-874-3p

-0.06

Poorly conserved sites

rno-miR-18a-3p

-0.06

Poorly conserved sites

rno-miR-871-5p

-0.06

Poorly conserved sites

rno-miR-3586-5p

-0.06

Poorly conserved sites

rno-miR-339-5p

-0.06

Poorly conserved sites

rno-miR-299b-3p

-0.06

Poorly conserved sites

rno-miR-299a-3p

-0.06

Poorly conserved sites

rno-miR-6323

-0.06

Poorly conserved sites

rno-miR-497-3p

-0.06

Poorly conserved sites

rno-miR-1193-5p

-0.06

Poorly conserved sites

rno-miR-873-5p

-0.06

Poorly conserved sites

rno-miR-200c-3p

-0.06

Poorly conserved sites

rno-miR-429

-0.06

Poorly conserved sites

Fstl1

rno-miR-200b-3p

-0.06

Poorly conserved sites

rno-miR-300-5p

-0.06

Poorly conserved sites

rno-let-7g-3p

-0.06

Poorly conserved sites

rno-miR-667-5p

-0.06

Poorly conserved sites

rno-miR-338-3p

-0.06

Poorly conserved sites

rno-miR-1193-5p

-0.06

Poorly conserved sites

rno-miR-222-5p

-0.05

Poorly conserved sites

rno-miR-382-3p

-0.05

Poorly conserved sites

rno-miR-505-5p

-0.05

Poorly conserved sites

rno-miR-3585-5p

-0.05

Poorly conserved sites

rno-miR-6328

-0.05

Poorly conserved sites

rno-miR-298-5p

-0.05

Poorly conserved sites

rno-miR-3569

-0.05

Poorly conserved sites

rno-miR-3589

-0.05

Poorly conserved sites

rno-miR-6325

-0.05

Poorly conserved sites

rno-miR-544-3p

-0.05

Poorly conserved sites

rno-let-7c-1-3p

-0.05

Poorly conserved sites

rno-miR-208a-3p

-0.05

Poorly conserved sites

rno-miR-208b-3p

-0.05

Poorly conserved sites

rno-miR-200a-5p

-0.05

Poorly conserved sites

rno-miR-203a-3p

-0.04

Conserved sites

rno-miR-214-3p

-0.04

Poorly conserved sites

rno-miR-3561-5p

-0.04

Poorly conserved sites

rno-miR-452-3p

-0.04

Poorly conserved sites

rno-miR-342-3p

-0.04

Poorly conserved sites

rno-miR-18a-3p

-0.04

Poorly conserved sites

rno-miR-764-5p

-0.04

Poorly conserved sites

rno-miR-759

-0.04

Poorly conserved sites

rno-miR-495

-0.04

Poorly conserved sites

rno-miR-3068-3p

-0.04

Poorly conserved sites

rno-miR-3084c-5p

-0.04

Poorly conserved sites

rno-miR-3084b-5p

-0.04

Poorly conserved sites

rno-miR-3557-5p

-0.04

Poorly conserved sites

rno-let-7a-2-3p

-0.04

Poorly conserved sites

rno-miR-488-3p

-0.04

Poorly conserved sites

rno-miR-223-5p

-0.03

Poorly conserved sites

rno-miR-212-5p

-0.03

Poorly conserved sites

rno-miR-1224

-0.03

Poorly conserved sites

rno-miR-497-3p

-0.03

Poorly conserved sites

rno-miR-499-5p

-0.03

Poorly conserved sites

rno-miR-382-5p

-0.02

Poorly conserved sites

rno-miR-881-5p

-0.02

Poorly conserved sites

rno-miR-761

-0.02

Poorly conserved sites

rno-miR-138-2-3p

-0.02

Poorly conserved sites

rno-miR-181a-2-3p

-0.02

Poorly conserved sites

rno-miR-23b-5p

-0.02

Poorly conserved sites

rno-miR-143-5p

-0.02

Poorly conserved sites

rno-miR-551b-5p

-0.02

Poorly conserved sites

rno-miR-3589

-0.02

Poorly conserved sites

rno-miR-1224

-0.02

Poorly conserved sites

rno-miR-3065-5p

-0.02

Poorly conserved sites

Fstl1

rno-miR-7a-1-3p

-0.02

Poorly conserved sites

rno-miR-19a-3p

-0.02

Poorly conserved sites

rno-miR-19b-3p

-0.02

Poorly conserved sites

rno-miR-330-3p

-0.02

Poorly conserved sites

rno-miR-3583-3p

-0.02

Poorly conserved sites

rno-miR-3560

-0.02

Poorly conserved sites

rno-miR-875

-0.02

Poorly conserved sites

rno-miR-873-3p

-0.02

Poorly conserved sites

rno-miR-449c-3p

-0.02

Poorly conserved sites

rno-miR-497-3p

-0.02

Poorly conserved sites

rno-miR-877

-0.02

Poorly conserved sites

rno-miR-20b-3p

-0.02

Poorly conserved sites

rno-miR-17-1-3p

-0.02

Poorly conserved sites

rno-miR-873-3p

-0.02

Poorly conserved sites

rno-miR-743a-5p

-0.02

Poorly conserved sites

rno-miR-871-5p

-0.02

Poorly conserved sites

rno-miR-881-5p

-0.02

Poorly conserved sites

rno-miR-126a-5p

-0.02

Poorly conserved sites

rno-miR-290

-0.02

Poorly conserved sites

rno-miR-292-5p

-0.02

Poorly conserved sites

rno-miR-293-5p

-0.02

Poorly conserved sites

rno-miR-181a-2-3p

-0.02

Poorly conserved sites

rno-miR-488-3p

-0.02

Poorly conserved sites

rno-miR-539-5p

-0.02

Poorly conserved sites

rno-miR-1297

-0.02

Poorly conserved sites

rno-miR-379-3p

-0.02

Poorly conserved sites

rno-miR-144-3p

-0.02

Poorly conserved sites

rno-miR-128-3p

-0.02

Poorly conserved sites

rno-miR-216b-3p

-0.02

Poorly conserved sites

rno-miR-325-3p

-0.02

Poorly conserved sites

rno-miR-200b-5p

-0.02

Poorly conserved sites

rno-miR-101a-5p

-0.02

Poorly conserved sites

rno-miR-485-5p

-0.02

Poorly conserved sites

rno-miR-421-5p

-0.02

Poorly conserved sites

rno-miR-325-3p

-0.01

Conserved sites

rno-miR-338-3p

-0.01

Poorly conserved sites

rno-miR-185-3p

-0.01

Poorly conserved sites

rno-miR-873-5p

-0.01

Poorly conserved sites

rno-miR-3588

-0.01

Poorly conserved sites

rno-miR-129-5p

-0.01

Poorly conserved sites

rno-miR-764-3p

-0.01

Poorly conserved sites

rno-miR-203a-3p

-0.01

Poorly conserved sites

rno-miR-186-5p

-0.01

Poorly conserved sites

rno-miR-186-3p

-0.01

Poorly conserved sites

rno-miR-495

-0.01

Poorly conserved sites

rno-miR-300-3p

-0.01

Poorly conserved sites

rno-miR-495

-0.01

Poorly conserved sites

rno-miR-495

-0.01

Poorly conserved sites

rno-miR-153-5p

-0.01

Poorly conserved sites

rno-miR-873-5p

-0.01

Poorly conserved sites

rno-miR-203a-3p

-0.01

Poorly conserved sites

Fstl1

rno-miR-325-3p

-0.01

Poorly conserved sites

rno-miR-3570

-0.01

Poorly conserved sites

rno-miR-493-5p

-0.01

Poorly conserved sites

rno-miR-320-3p

-0.01

Poorly conserved sites

rno-miR-411-3p

-0.01

Poorly conserved sites

rno-miR-3065-3p

-0.01

Poorly conserved sites

rno-miR-451-3p

-0.01

Poorly conserved sites

rno-miR-290

-0.01

Poorly conserved sites

rno-miR-292-5p

-0.01

Poorly conserved sites

rno-miR-293-5p

-0.01

Poorly conserved sites

rno-miR-295-5p

-0.01

Poorly conserved sites

Hk2

rno-miR-323-5p

-0.41

Poorly conserved sites

rno-miR-132-5p

-0.4

Poorly conserved sites

rno-miR-1839-3p

-0.36

Poorly conserved sites

rno-miR-380-5p

-0.33

Poorly conserved sites

rno-miR-9b-5p

-0.33

Poorly conserved sites

rno-miR-3561-3p

-0.27

Poorly conserved sites

rno-miR-615

-0.26

Poorly conserved sites

rno-miR-423-3p

-0.24

Poorly conserved sites

rno-miR-24-3p

-0.23

Poorly conserved sites

rno-miR-184

-0.22

Poorly conserved sites

rno-miR-499-3p

-0.22

Poorly conserved sites

rno-miR-101b-5p

-0.2

Poorly conserved sites

rno-miR-3551-5p

-0.2

Poorly conserved sites

rno-let-7d-5p

-0.19

Conserved sites

rno-miR-187-5p

-0.19

Poorly conserved sites

rno-miR-17-2-3p

-0.19

Poorly conserved sites

rno-miR-329-3p

-0.19

Poorly conserved sites

rno-miR-125a-5p

-0.18

Conserved sites

rno-miR-351-5p

-0.18

Conserved sites

rno-miR-7578

-0.18

Poorly conserved sites

rno-miR-6326

-0.18

Poorly conserved sites

rno-miR-187-5p

-0.18

Poorly conserved sites

rno-miR-362-3p

-0.18

Poorly conserved sites

rno-let-7g-5p

-0.17

Conserved sites

rno-miR-3577

-0.17

Poorly conserved sites

rno-miR-202-3p

-0.17

Poorly conserved sites

rno-miR-9a-5p

-0.16

Conserved sites

rno-let-7e-5p

-0.16

Conserved sites

rno-let-7a-5p

-0.16

Conserved sites

rno-let-7f-5p

-0.16

Conserved sites

rno-let-7i-5p

-0.16

Conserved sites

rno-miR-125b-5p

-0.16

Conserved sites

rno-miR-667-5p

-0.16

Poorly conserved sites

rno-miR-218b

-0.16

Poorly conserved sites

rno-miR-323-3p

-0.15

Conserved sites

rno-miR-3541

-0.15

Poorly conserved sites

rno-let-7b-5p

-0.14

Conserved sites

rno-miR-98-5p

-0.14

Conserved sites

rno-let-7c-5p

-0.14

Conserved sites

rno-miR-10b-3p

-0.14

Poorly conserved sites

Hk2

rno-miR-1912-3p

-0.14

Poorly conserved sites

rno-miR-3592

-0.14

Poorly conserved sites

rno-miR-9a-5p

-0.14

Poorly conserved sites

rno-miR-135a-5p

-0.14

Poorly conserved sites

rno-miR-135b-5p

-0.14

Poorly conserved sites

rno-miR-143-3p

-0.13

Conserved sites

rno-miR-149-3p

-0.13

Poorly conserved sites

rno-miR-219a-1-3p

-0.12

Poorly conserved sites

rno-miR-3577

-0.12

Poorly conserved sites

rno-miR-3559-5p

-0.12

Poorly conserved sites

rno-miR-6334

-0.12

Poorly conserved sites

rno-miR-139-5p

-0.11

Conserved sites

rno-miR-3102

-0.11

Poorly conserved sites

rno-miR-9a-5p

-0.11

Poorly conserved sites

rno-miR-192-5p

-0.11

Poorly conserved sites

rno-miR-215

-0.11

Poorly conserved sites

rno-miR-6326

-0.11

Poorly conserved sites

rno-miR-344a-5p

-0.11

Poorly conserved sites

rno-let-7a-2-3p

-0.1

Poorly conserved sites

rno-miR-337-3p

-0.1

Poorly conserved sites

rno-miR-743b-5p

-0.1

Poorly conserved sites

rno-miR-343

-0.1

Poorly conserved sites

rno-miR-9a-5p

-0.1

Poorly conserved sites

rno-miR-128-3p

-0.1

Poorly conserved sites

rno-miR-324-5p

-0.1

Poorly conserved sites

rno-miR-191a-3p

-0.1

Poorly conserved sites

rno-miR-206-5p

-0.1

Poorly conserved sites

rno-miR-541-5p

-0.1

Poorly conserved sites

rno-miR-741-5p

-0.1

Poorly conserved sites

rno-miR-376c-3p

-0.1

Poorly conserved sites

rno-miR-218a-1-3p

-0.09

Poorly conserved sites

rno-miR-133a-3p

-0.09

Poorly conserved sites

rno-miR-6331

-0.09

Poorly conserved sites

rno-miR-484

-0.09

Poorly conserved sites

rno-miR-6321

-0.09

Poorly conserved sites

rno-miR-347

-0.09

Poorly conserved sites

rno-miR-3571

-0.09

Poorly conserved sites

rno-miR-336-3p

-0.09

Poorly conserved sites

rno-miR-343

-0.08

Poorly conserved sites

rno-miR-344a-3p

-0.08

Poorly conserved sites

rno-miR-3561-3p

-0.08

Poorly conserved sites

rno-miR-133b-3p

-0.08

Poorly conserved sites

rno-miR-138-1-3p

-0.08

Poorly conserved sites

rno-miR-298-5p

-0.08

Poorly conserved sites

rno-miR-140-3p

-0.08

Poorly conserved sites

rno-miR-3084d

-0.07

Poorly conserved sites

rno-miR-3084b-3p

-0.07

Poorly conserved sites

rno-miR-3084a-3p

-0.07

Poorly conserved sites

rno-let-7g-3p

-0.07

Poorly conserved sites

rno-miR-202-3p

-0.07

Poorly conserved sites

rno-let-7f-2-3p

-0.07

Poorly conserved sites

Hk2

rno-miR-200a-3p

-0.07

Poorly conserved sites

rno-miR-141-3p

-0.07

Poorly conserved sites

rno-miR-201-5p

-0.07

Poorly conserved sites

rno-miR-141-5p

-0.06

Poorly conserved sites

rno-miR-3557-3p

-0.06

Poorly conserved sites

rno-miR-214-5p

-0.06

Poorly conserved sites

rno-let-7d-5p

-0.06

Poorly conserved sites

rno-miR-322-3p

-0.06

Poorly conserved sites

rno-miR-760-3p

-0.06

Poorly conserved sites

rno-miR-34a-5p

-0.06

Poorly conserved sites

rno-miR-412-3p

-0.06

Poorly conserved sites

rno-miR-216a-3p

-0.05

Poorly conserved sites

rno-let-7c-1-3p

-0.05

Poorly conserved sites

rno-miR-344g

-0.05

Poorly conserved sites

rno-miR-3120

-0.05

Poorly conserved sites

rno-miR-10b-3p

-0.05

Poorly conserved sites

rno-miR-188-3p

-0.05

Poorly conserved sites

rno-miR-448-5p

-0.05

Poorly conserved sites

rno-miR-879-5p

-0.05

Poorly conserved sites

rno-miR-485-5p

-0.05

Poorly conserved sites

rno-miR-501-3p

-0.05

Poorly conserved sites

rno-miR-500-3p

-0.05

Poorly conserved sites

rno-miR-3084a-5p

-0.05

Poorly conserved sites

rno-miR-140-5p

-0.05

Poorly conserved sites

rno-miR-344b-5p

-0.04

Poorly conserved sites

rno-miR-98-5p

-0.04

Poorly conserved sites

rno-let-7g-5p

-0.04

Poorly conserved sites

rno-miR-185-5p

-0.04

Poorly conserved sites

rno-miR-3587

-0.04

Poorly conserved sites

rno-miR-758-5p

-0.04

Poorly conserved sites

rno-miR-3084c-5p

-0.04

Poorly conserved sites

rno-miR-3084b-5p

-0.04

Poorly conserved sites

rno-miR-34c-5p

-0.04

Poorly conserved sites

rno-miR-34b-5p

-0.04

Poorly conserved sites

rno-miR-362-3p

-0.04

Poorly conserved sites

rno-miR-329-3p

-0.04

Poorly conserved sites

rno-miR-295-3p

-0.04

Poorly conserved sites

rno-miR-452-3p

-0.03

Poorly conserved sites

rno-miR-532-3p

-0.03

Poorly conserved sites

rno-miR-300-5p

-0.03

Poorly conserved sites

rno-miR-742-3p

-0.03

Poorly conserved sites

rno-let-7i-5p

-0.03

Poorly conserved sites

rno-let-7b-5p

-0.03

Poorly conserved sites

rno-let-7a-5p

-0.03

Poorly conserved sites

rno-let-7c-5p

-0.03

Poorly conserved sites

rno-let-7e-5p

-0.03

Poorly conserved sites

rno-let-7f-5p

-0.03

Poorly conserved sites

rno-miR-504

-0.03

Poorly conserved sites

rno-miR-3084d

-0.03

Poorly conserved sites

rno-miR-3084b-3p

-0.03

Poorly conserved sites

rno-miR-3084a-3p

-0.03

Poorly conserved sites

Hk2

rno-miR-452-3p

-0.03

Poorly conserved sites

rno-miR-135a-5p

-0.03

Poorly conserved sites

rno-miR-135b-5p

-0.03

Poorly conserved sites

rno-miR-6331

-0.03

Poorly conserved sites

rno-miR-880-5p

-0.03

Poorly conserved sites

rno-miR-32-3p

-0.03

Poorly conserved sites

rno-miR-211-3p

-0.03

Poorly conserved sites

rno-miR-449c-5p

-0.03

Poorly conserved sites

rno-miR-21-5p

-0.03

Poorly conserved sites

rno-miR-3553

-0.02

Poorly conserved sites

rno-miR-873-5p

-0.02

Poorly conserved sites

rno-miR-761

-0.02

Poorly conserved sites

rno-miR-214-3p

-0.02

Poorly conserved sites

rno-miR-665

-0.02

Poorly conserved sites

rno-miR-5132-3p

-0.02

Poorly conserved sites

rno-miR-33-3p

-0.02

Poorly conserved sites

rno-miR-185-3p

-0.02

Poorly conserved sites

rno-miR-145-3p

-0.02

Poorly conserved sites

rno-miR-181a-5p

-0.02

Poorly conserved sites

rno-miR-181d-5p

-0.02

Poorly conserved sites

rno-miR-181b-5p

-0.02

Poorly conserved sites

rno-miR-181c-5p

-0.02

Poorly conserved sites

rno-miR-425-5p

-0.02

Poorly conserved sites

rno-miR-6322

-0.02

Poorly conserved sites

rno-miR-679

-0.02

Poorly conserved sites

rno-miR-3544

-0.02

Poorly conserved sites

rno-miR-742-3p

-0.02

Poorly conserved sites

rno-miR-190a-3p

-0.02

Poorly conserved sites

rno-miR-672-5p

-0.02

Poorly conserved sites

rno-miR-377-5p

-0.02

Poorly conserved sites

rno-miR-665

-0.02

Poorly conserved sites

rno-miR-361-3p

-0.02

Poorly conserved sites

rno-miR-495

-0.02

Poorly conserved sites

rno-miR-222-5p

-0.02

Poorly conserved sites

rno-miR-568

-0.02

Poorly conserved sites

rno-miR-212-3p

-0.02

Poorly conserved sites

rno-miR-132-3p

-0.02

Poorly conserved sites

rno-miR-871-5p

-0.02

Poorly conserved sites

rno-miR-743a-5p

-0.02

Poorly conserved sites

rno-miR-881-5p

-0.02

Poorly conserved sites

rno-miR-3557-5p

-0.02

Poorly conserved sites

rno-miR-488-3p

-0.02

Poorly conserved sites

rno-miR-3542

-0.02

Poorly conserved sites

rno-miR-411-3p

-0.02

Poorly conserved sites

rno-miR-375-3p

-0.02

Poorly conserved sites

rno-miR-330-5p

-0.02

Poorly conserved sites

rno-miR-326-3p

-0.02

Poorly conserved sites

rno-miR-543-3p

-0.02

Poorly conserved sites

rno-miR-551b-5p

-0.02

Poorly conserved sites

rno-miR-449a-5p

-0.02

Poorly conserved sites

rno-miR-488-5p

-0.02

Poorly conserved sites

Hk2

rno-miR-29b-5p

-0.02

Poorly conserved sites

rno-miR-384-3p

-0.02

Poorly conserved sites

rno-miR-742-3p

-0.02

Poorly conserved sites

rno-miR-383-3p

-0.02

Poorly conserved sites

rno-miR-493-5p

-0.02

Poorly conserved sites

rno-miR-342-3p

-0.01

Poorly conserved sites

rno-miR-126b

-0.01

Poorly conserved sites

rno-miR-873-5p

-0.01

Poorly conserved sites

rno-miR-493-5p

-0.01

Poorly conserved sites

rno-miR-208a-5p

-0.01

Poorly conserved sites

rno-miR-208b-5p

-0.01

Poorly conserved sites

rno-miR-300-5p

-0.01

Poorly conserved sites

rno-miR-153-3p

-0.01

Poorly conserved sites

rno-miR-448-3p

-0.01

Poorly conserved sites

rno-miR-873-5p

-0.01

Poorly conserved sites

rno-miR-29b-5p

-0.01

Poorly conserved sites

rno-miR-146b-5p

-0.01

Poorly conserved sites

rno-miR-146a-5p

-0.01

Poorly conserved sites

rno-miR-497-3p

-0.01

Poorly conserved sites

rno-miR-297

-0.01

Poorly conserved sites

rno-miR-1188-3p

-0.01

Poorly conserved sites

rno-miR-770-5p

-0.01

Poorly conserved sites

rno-miR-764-3p

-0.01

Poorly conserved sites

rno-miR-452-3p

-0.01

Poorly conserved sites

rno-miR-344b-3p

-0.01

Poorly conserved sites

rno-miR-33-3p

-0.01

Poorly conserved sites

rno-miR-320-5p

-0.01

Poorly conserved sites

rno-miR-294

-0.01

Poorly conserved sites

rno-miR-3065-3p

-0.01

Poorly conserved sites

rno-miR-222-5p

-0.01

Poorly conserved sites

rno-miR-3591

-0.01

Poorly conserved sites

rno-miR-217-5p

-0.01

Poorly conserved sites

rno-miR-30e-3p

-0.01

Poorly conserved sites

rno-miR-30a-3p

-0.01

Poorly conserved sites

rno-miR-30d-3p

-0.01

Poorly conserved sites

rno-miR-141-5p

-0.01

Poorly conserved sites

rno-miR-10a-3p

-0.01

Poorly conserved sites

rno-miR-488-3p

-0.01

Poorly conserved sites

rno-miR-3593-3p

-0.01

Poorly conserved sites

Hspb1

rno-miR-336-3p

-0.67

Poorly conserved sites

rno-miR-509-3p

-0.4

Poorly conserved sites

rno-miR-138-5p

-0.36

Poorly conserved sites

rno-miR-138-1-3p

-0.34

Poorly conserved sites

rno-miR-199a-3p

-0.32

Poorly conserved sites

rno-miR-881-5p

-0.25

Poorly conserved sites

rno-miR-871-5p

-0.24

Poorly conserved sites

rno-miR-743a-5p

-0.24

Poorly conserved sites

rno-miR-291a-5p

-0.21

Poorly conserved sites

rno-miR-3559-5p

-0.17

Poorly conserved sites

rno-miR-10b-3p

-0.17

Poorly conserved sites

rno-miR-539-5p

-0.17

Poorly conserved sites

Nppa

rno-miR-667-5p

-0.81

Poorly conserved sites

rno-miR-450a-5p

-0.77

Poorly conserved sites

rno-miR-450b-5p

-0.77

Poorly conserved sites

rno-miR-216b-3p

-0.5

Poorly conserved sites

rno-miR-665

-0.46

Poorly conserved sites

rno-miR-3594-3p

-0.44

Poorly conserved sites

rno-miR-132-5p

-0.37

Poorly conserved sites

rno-miR-551b-3p

-0.35

Poorly conserved sites

rno-miR-362-3p

-0.29

Poorly conserved sites

rno-miR-3572

-0.25

Poorly conserved sites

rno-miR-488-3p

-0.25

Poorly conserved sites

rno-miR-30b-3p

-0.24

Poorly conserved sites

rno-miR-30c-1-3p

-0.24

Poorly conserved sites

rno-miR-30c-2-3p

-0.24

Poorly conserved sites

rno-miR-329-3p

-0.23

Poorly conserved sites

rno-miR-194-3p

-0.2

Poorly conserved sites

rno-miR-666-3p

-0.18

Poorly conserved sites

rno-miR-759

-0.18

Poorly conserved sites

rno-miR-463-3p

-0.17

Poorly conserved sites

rno-miR-298-5p

-0.17

Poorly conserved sites

rno-miR-3577

-0.17

Poorly conserved sites

rno-miR-471-3p

-0.16

Poorly conserved sites

rno-miR-542-3p

-0.15

Poorly conserved sites

Pla2g2a

rno-miR-92a-1-5p

-0.73

Poorly conserved sites

rno-miR-877

-0.61

Poorly conserved sites

rno-miR-296-3p

-0.59

Poorly conserved sites

rno-miR-410-5p

-0.38

Poorly conserved sites

rno-miR-653-3p

-0.36

Poorly conserved sites

rno-miR-146b-3p

-0.35

Poorly conserved sites

rno-miR-181b-2-3p

-0.34

Poorly conserved sites

rno-miR-494-5p

-0.34

Poorly conserved sites

rno-miR-3473

-0.33

Poorly conserved sites

rno-miR-3075

-0.32

Poorly conserved sites

rno-miR-6316

-0.32

Poorly conserved sites

rno-miR-380-5p

-0.32

Poorly conserved sites

rno-miR-496-5p

-0.32

Poorly conserved sites

rno-miR-214-3p

-0.31

Poorly conserved sites

rno-miR-711

-0.31

Poorly conserved sites

rno-miR-3557-5p

-0.28

Poorly conserved sites

rno-miR-336-3p

-0.27

Poorly conserved sites

rno-miR-761

-0.25

Poorly conserved sites

rno-miR-185-5p

-0.23

Poorly conserved sites

rno-miR-219a-2-3p

-0.22

Poorly conserved sites

rno-miR-107-5p

-0.21

Poorly conserved sites

rno-miR-103-2-5p

-0.21

Poorly conserved sites

rno-miR-103-1-5p

-0.15

Poorly conserved sites

rno-miR-320-5p

-0.01

Poorly conserved sites

Txnip

rno-miR-666-5p

-0.52

Poorly conserved sites

rno-miR-352

-0.51

Poorly conserved sites

rno-miR-678

-0.48

Poorly conserved sites

rno-miR-25-5p

-0.41

Poorly conserved sites

Txnip

rno-miR-26b-3p

-0.38

Poorly conserved sites

rno-miR-6329

-0.38

Poorly conserved sites

rno-miR-24-1-5p

-0.36

Poorly conserved sites

rno-miR-24-2-5p

-0.36

Poorly conserved sites

rno-miR-760-3p

-0.36

Poorly conserved sites

rno-miR-3068-5p

-0.35

Poorly conserved sites

rno-miR-675-5p

-0.33

Poorly conserved sites

rno-miR-485-5p

-0.31

Poorly conserved sites

rno-miR-3586-5p

-0.31

Poorly conserved sites

rno-miR-339-5p

-0.31

Poorly conserved sites

rno-miR-3552

-0.3

Poorly conserved sites

rno-miR-154-3p

-0.29

Conserved sites

rno-miR-6326

-0.29

Poorly conserved sites

rno-miR-3075

-0.28

Poorly conserved sites

rno-miR-493-3p

-0.27

Poorly conserved sites

rno-miR-15a-3p

-0.27

Poorly conserved sites

rno-miR-3587

-0.27

Poorly conserved sites

rno-miR-141-3p

-0.27

Poorly conserved sites

rno-miR-27a-5p

-0.27

Poorly conserved sites

rno-miR-185-5p

-0.26

Poorly conserved sites

rno-miR-6333

-0.26

Poorly conserved sites

rno-miR-200a-3p

-0.26

Poorly conserved sites

rno-miR-493-3p

-0.26

Poorly conserved sites

rno-miR-3085

-0.26

Poorly conserved sites

rno-miR-17-5p

-0.25

Conserved sites

rno-miR-20b-5p

-0.25

Conserved sites

rno-miR-3543

-0.25

Poorly conserved sites

rno-miR-450b-3p

-0.25

Poorly conserved sites

rno-miR-93-5p

-0.24

Conserved sites

rno-miR-105

-0.24

Conserved sites

rno-miR-106b-5p

-0.23

Conserved sites

rno-miR-20a-5p

-0.23

Conserved sites

rno-miR-291a-3p

-0.23

Conserved sites

rno-miR-483-3p

-0.23

Poorly conserved sites

rno-miR-1199-3p

-0.23

Poorly conserved sites

rno-miR-3064-3p

-0.23

Poorly conserved sites

rno-miR-20a-5p

-0.22

Conserved sites

rno-miR-106b-5p

-0.22

Conserved sites

rno-miR-204-3p

-0.22

Poorly conserved sites

rno-miR-130a-5p

-0.22

Poorly conserved sites

rno-miR-3541

-0.22

Poorly conserved sites

rno-miR-1306-5p

-0.22

Poorly conserved sites

rno-miR-93-5p

-0.21

Conserved sites

rno-miR-17-5p

-0.21

Conserved sites

rno-miR-20b-5p

-0.21

Conserved sites

rno-miR-3558-3p

-0.21

Poorly conserved sites

rno-miR-138-5p

-0.21

Poorly conserved sites

rno-miR-1193-3p

-0.2

Poorly conserved sites

rno-miR-325-5p

-0.2

Poorly conserved sites

rno-miR-142-3p

-0.2

Poorly conserved sites

rno-miR-129-5p

-0.2

Poorly conserved sites

Txnip

rno-miR-3566

-0.19

Poorly conserved sites

rno-miR-183-5p

-0.19

Poorly conserved sites

rno-miR-679

-0.19

Poorly conserved sites

rno-miR-342-3p

-0.19

Poorly conserved sites

rno-miR-3546

-0.18

Poorly conserved sites

rno-miR-3064-3p

-0.17

Poorly conserved sites

rno-miR-370-5p

-0.17

Poorly conserved sites

rno-miR-147

-0.17

Poorly conserved sites

rno-miR-352

-0.17

Poorly conserved sites

rno-miR-3543

-0.17

Poorly conserved sites

rno-miR-295-3p

-0.17

Poorly conserved sites

rno-miR-667-3p

-0.17

Poorly conserved sites

rno-miR-29a-5p

-0.16

Poorly conserved sites

rno-miR-377-3p

-0.16

Poorly conserved sites

rno-miR-337-3p

-0.16

Poorly conserved sites

rno-miR-1199-5p

-0.15

Poorly conserved sites

rno-miR-3556a

-0.15

Poorly conserved sites

rno-miR-3556b

-0.15

Poorly conserved sites

rno-miR-770-3p

-0.15

Poorly conserved sites

rno-miR-6315

-0.15

Poorly conserved sites

rno-miR-363-5p

-0.15

Poorly conserved sites

rno-miR-342-5p

-0.15

Poorly conserved sites

rno-miR-16-5p

-0.14

Conserved sites

rno-miR-195-5p

-0.14

Conserved sites

rno-miR-139-3p

-0.14

Poorly conserved sites

rno-miR-652-5p

-0.14

Poorly conserved sites

rno-miR-15b-5p

-0.13

Conserved sites

rno-miR-494-3p

-0.13

Poorly conserved sites

rno-miR-211-5p

-0.13

Poorly conserved sites

rno-miR-204-5p

-0.13

Poorly conserved sites

rno-miR-294

-0.13

Poorly conserved sites

rno-miR-3552

-0.13

Poorly conserved sites

rno-miR-322-5p

-0.12

Conserved sites

rno-miR-879-5p

-0.12

Poorly conserved sites

rno-miR-3068-5p

-0.12

Poorly conserved sites

rno-miR-214-3p

-0.12

Poorly conserved sites

rno-miR-193a-5p

-0.12

Poorly conserved sites

rno-miR-122-5p

-0.12

Poorly conserved sites

rno-miR-122-5p

-0.12

Poorly conserved sites

rno-miR-327

-0.11

Poorly conserved sites

rno-miR-17-2-3p

-0.11

Poorly conserved sites

rno-miR-6314

-0.11

Poorly conserved sites

rno-miR-1188-5p

-0.11

Poorly conserved sites

rno-miR-1843a-5p

-0.11

Poorly conserved sites

rno-miR-216a-5p

-0.11

Poorly conserved sites

rno-miR-3557-3p

-0.11

Poorly conserved sites

rno-miR-743a-3p

-0.11

Poorly conserved sites

rno-miR-6216

-0.11

Poorly conserved sites

rno-miR-96-3p

-0.11

Poorly conserved sites

rno-miR-15a-5p

-0.1

Conserved sites

rno-miR-141-3p

-0.1

Conserved sites

Txnip

rno-miR-22-3p

-0.1

Poorly conserved sites

rno-miR-499-3p

-0.1

Poorly conserved sites

rno-miR-204-3p

-0.1

Poorly conserved sites

rno-miR-7a-1-3p

-0.1

Poorly conserved sites

rno-miR-200a-3p

-0.09

Conserved sites

rno-miR-22-5p

-0.09

Poorly conserved sites

rno-miR-133a-5p

-0.09

Poorly conserved sites

rno-miR-320-3p

-0.09

Poorly conserved sites

rno-miR-376b-3p

-0.09

Poorly conserved sites

rno-miR-3068-5p

-0.09

Poorly conserved sites

rno-miR-3065-5p

-0.09

Poorly conserved sites

rno-miR-497-5p

-0.08

Conserved sites

rno-miR-3084a-5p

-0.08

Poorly conserved sites

rno-miR-542-3p

-0.08

Poorly conserved sites

rno-miR-3557-3p

-0.08

Poorly conserved sites

rno-miR-3575

-0.08

Poorly conserved sites

rno-miR-653-3p

-0.08

Poorly conserved sites

rno-miR-181b-2-3p

-0.08

Poorly conserved sites

rno-miR-20b-3p

-0.08

Poorly conserved sites

rno-miR-17-1-3p

-0.08

Poorly conserved sites

rno-miR-207

-0.08

Poorly conserved sites

rno-miR-152-3p

-0.07

Conserved sites

rno-miR-148b-3p

-0.07

Conserved sites

rno-miR-1188-3p

-0.07

Poorly conserved sites

rno-miR-130b-5p

-0.07

Poorly conserved sites

rno-miR-141-5p

-0.07

Poorly conserved sites

rno-miR-186-3p

-0.07

Poorly conserved sites

rno-miR-761

-0.07

Poorly conserved sites

rno-miR-216b-5p

-0.07

Poorly conserved sites

rno-miR-466d

-0.07

Poorly conserved sites

rno-miR-295-3p

-0.07

Poorly conserved sites

rno-miR-148a-3p

-0.06

Conserved sites

rno-miR-191a-3p

-0.06

Poorly conserved sites

rno-miR-6326

-0.06

Poorly conserved sites

rno-miR-3552

-0.06

Poorly conserved sites

rno-miR-150-5p

-0.06

Poorly conserved sites

rno-miR-150-5p

-0.06

Poorly conserved sites

rno-miR-205

-0.06

Poorly conserved sites

rno-miR-149-5p

-0.06

Poorly conserved sites

rno-miR-3568

-0.05

Poorly conserved sites

rno-miR-532-3p

-0.05

Poorly conserved sites

rno-miR-3564

-0.04

Poorly conserved sites

rno-miR-3085

-0.04

Poorly conserved sites

rno-miR-3573-3p

-0.04

Poorly conserved sites

rno-miR-301a-5p

-0.03

Poorly conserved sites

rno-miR-204-3p

-0.03

Poorly conserved sites

rno-miR-301a-5p

-0.03

Poorly conserved sites

rno-miR-301b-5p

-0.03

Poorly conserved sites

rno-miR-653-5p

-0.02

Poorly conserved sites

rno-miR-301b-5p

-0.02

Poorly conserved sites

rno-miR-873-3p

-0.02

Poorly conserved sites

Txnip

rno-miR-3074

-0.02

Poorly conserved sites

rno-miR-181b-5p

-0.02

Poorly conserved sites

rno-miR-181d-5p

-0.02

Poorly conserved sites

rno-miR-181a-5p

-0.02

Poorly conserved sites

rno-miR-181c-5p

-0.02

Poorly conserved sites

rno-miR-19b-1-5p

-0.02

Poorly conserved sites

rno-miR-19b-2-5p

-0.02

Poorly conserved sites

rno-miR-33-3p

-0.02

Poorly conserved sites

rno-miR-9a-3p

-0.02

Poorly conserved sites

rno-miR-214-3p

-0.02

Poorly conserved sites

rno-miR-449c-3p

-0.02

Poorly conserved sites

rno-miR-153-5p

-0.01

Poorly conserved sites

rno-miR-294

-0.01

Poorly conserved sites

rno-miR-673-5p

-0.01

Poorly conserved sites

rno-miR-27a-3p

-0.01

Poorly conserved sites

rno-miR-27b-3p

-0.01

Poorly conserved sites

rno-miR-532-3p

-0.01

Poorly conserved sites

rno-miR-668

-0.01

Poorly conserved sites

rno-miR-3561-5p

-0.01

Poorly conserved sites

rno-miR-761

-0.01

Poorly conserved sites

Figure 2. Venn diagram of MICRORNA-detected regulatory miRNAs of DCM-related mRNAs differentially expressed in LV of STZ-induced diabetic rats (GSE4745) and miRNAs differentially expressed in LV of STZ-induced and high-fat diet diabetic rats (GSE44179). A, GSE4745 (day 3) vs. GSE44179; B, GSE4745 (day 28) vs GSE44179; C, GSE4745 (day 42) vs GSE44179; D, Intersection of all periods evaluated in GSE4745.

The Hk2 was down-regulated at 3 and 42 days after the STZ-induction (logFC -1.8.82 and -4.1.59, respectively). It mRNA could be regulated by rno-mir-34a (LogFC 2.6.06), rno-mir-532 (LogFC 2.1.49), rno-mir-21 (LogFC 2.1.33), rno-miR-17-3p (LogFC 1.6.47), rno-mir-322 (LogFC 1.4.33), rno-mir-187 (LogFC 1.3.55), rno-mir-188 (LogFC 1.0.91), which are up- regulated in LV of diabetes-induced rats. Conversely, Pla2g2a, was up-regulated at 3 and 42 days (logFC 1.0.5 and 1.7.35, respectively) after diabetes-induction and could be regulated by rno-mir-214 (LogFC -1.2.5), rno-mir-320 (LogFC -1.1.8), rno-mir-877 (LogFC -1.0.1), considering their regulations and TargetScan 7.1. web dataset data (Table 2 and Table 4).

The mRNA-mRNA and miRNA-mRNA interactions according to the IPA software and TargetScan 7.1. web dataset are shown at Figure 3. Possible pathways associated with DCM development: gene-gene: Agtr1-Nppa, Agtr1-Txnip; miRNA-target mRNAs: Agtr1 (rno-miR-7a, rno-miR-194, rno-mir-188, rno-mir-204 and rno-mir-466c); Fstl1 (rno-mir-203, rno-mir-322, rno-mir-22, rno-mir-200c, rno-mir-342, rno-mir-877, rno-mir-204, rno-mir-92b, rno-mir-214, rno-miR-30-c2*, rno-miR-7a, rno-miR-17-3p, rno-mir-20b, rno-mir-186 and rno-mir-320); Txnip (rno-mir-20b, rno-mir-204, rno-mir-342, rno-mir-322, rno-mir-214, rno-miR-7a, rno-mir-22, rno-mir-320, rno-mir-186, rno-mir-148b, rno-mir-532 and rno-miR-17-3p); Pla2g2a (rno-mir-214, rno-mir-320 and rno-mir-877); Hk2 (rno-mir-34a, rno-mir-532, rno-mir-21, rno-miR-17-3p, rno-mir-322, rno-mir-187, rno-mir-188, rno-mir-214, rno-mir-320, rno-mir-184 and rno-mir-342); Hspb1 (rno-mir-199a); Nppa (rno-miR-30-c2* and rno-miR-194) and miRNA-miRNA: rno-mir-214-rno-mir-148.

Figure 3. IPA and MICRORNA network of miRNAs-mRNAs interactions associated with diabetes-induced cardiotoxicity in periods evaluated in GSE4745. A - Day 3 after STZ-induction; B - Day 28 after STZ-induction and C - Day 42 after STZ-induction.

5. Discussion

In this study, Pla2g2a was up-regulated in LV of diabetic rats in an acute and chronic condition, which is suggestive that it may be involved in LV dysfunction induced by hyperglycemia. PLA2G2A is a phospholipase A2 group II A which catalyses the hydrolyzes of the acyl group at the sn-2 position of glycerophospholipids forming non-esterified fatty acids and lysophospholipids and plays a critical role in inflammation (25). Transgenic mice expressing an extracellular group IIa phospholipase A2 (sPLA2) have a higher number of atherosclerotic lesions when maintained on a high-fat, high-cholesterol and a low-fat chow diet in comparison with non-transgenic littermates. Immunohistochemical staining indicated that sPLA2 was present in the atherosclerotic lesions of the transgenic mice, which suggests that sPLA2 may promote atherogenesis, in part, through its effects on lipoprotein levels, increasing LDL cholesterol and decreasing HDL cholesterol. These data are suggestive that increased sPLA2 is involved in lipid-driven atherosclerosis, which is an important risk factor for CAD and possible other chronic inflammatory diseases (26).

Another study involving the measurement of serum levels of sPLA2 activity and secretory phospolipase A2 type IIA (sPLA2-IIA) evaluated the increase of circulating sPLA2-activity and sPLA2-IIA in patients with stable CAD suggesting their relation with functional characteristics of coronary stenosis in these patients. Measuring these molecules could be a possibility to predict the severity of CAD (27). The prognostic value of the sPLA2 activity in patients with an acute coronary syndrome (ACS) was determined through a measurement of sPLA2 antigen levels and its activity in plasma samples. The results showed that the high plasma sPLA2 activity is a major independent predictor of death and new or recurrent myocardial infarction (MI) in patients with ACS (28). Based on these previous studies and the hyperglycemia-induced Pla2g2a up-regulation in rats LV, it is likely that this gene plays an important role in the pathopysiology of DCM.

Pla2g2a regulatory miRNAs, rno-miR-877, rno-miR-320 and rno-miR-214, were down-regulated in LV of rats exposed to a high glucose concentration, suggesting their involvement in the development of DCM. Despite the down regulation of rno-miR-877 in ventricles of diabetic rats observed in GSE44179 dataset, there are only a few studies about these miRNA, especially in DCM. Researchers evaluated the expression profiles of miRNAs in single-cell suspensions in the lung prepared from C57BL/6 mice, before and after myofibroblast differentiation of lung resident mesenchimal stem cells and observed that the miR-877-3p is highly up-regulated in the myofibroblast differentiation and in the fibrotic lung. In addition, they found that miR-877-3p sequestration inhibited the myofibroblast differentiation, suggesting a potential application of miR-877-3p as a fibrosis suppressor in pulmonary fibrosis therapy and as a fibrosis marker for predicting prognosis, which indentified that miR-877-3p, is a miRNA that acts as a supressor in pulmonary fibrosis (29).

Regarding rno-miR-320, an in vivo study using an animal model evaluated the role of rno-miR-320 in ischemia/reperfusion (I/R). They observed that miR-320 expression worsens myocardial I/R injury, while its inhibition protects against myocardial apoptosis, mainly via the Insulin Growth Factor 1 (IGF-1) pathway, affecting the levels of antiapoptotic signaling pathways. This suggests miR-320 may represent a valuable tool and potential therapeutic target for protection against I/R induced cardiac injury (30). Although, in our integrative analysis, the rno-miR-320 was down-regulated in DCM, the association of this miRNA with apoptosis may represent an important finding.

Rno-miR-214 is a bi-functional cardio-miR, which is involved in cardiac physiology (31). In the dataset analyzed, rno-miR-214 was down-regulated in LV of diabetic rats, which is suggestive of its role in DCM through the regulation of the Pla2g2a gene expression. Supporting our hypothesis, the miR-214 was also observed down-regulated in blood samples of patients with acute MI, and angina pectoris, suggesting that the low expression of hsa-miR-214 is associated with severity of coronary stenosis and it could be a promising biomarker for CAD (32). Moreover, a model of mmu-miR-214 knockout mice showed a loss of cardiac contractility, increased apoptosis, and excessive fibrosis in response to ischemia/reperfusion injury (33), supporting the role of this miR in DCM complication.

The analysis also showed that Hk2 mRNA was down-regulated and related to the high expression of its regulatory miRNAs (rno-miR-17, rno-miR-187, rno-miR-34a, rno-miR-322, rno-miR-188, rno-miR-532 and rno-miR-21) in LV of rats exposed to a high glucose concentration, suggesting their important role in the pathophysiology of DCM.

Hk2 is an isozyme which occurs in mammalian tissue and catalyzes glucose phosphorylation. It has an affinity for glucose and product inhibition for glucose-6-phosphate (34,35). Additionally, a study observed the role of mitochondria-bound hexokinase 2 (mTHK2) in cardio protection using hearts of ischemic preconditioning rats whose results suggest that mtHK2 stimulates reactive oxygen species (ROS) production and mitochondrial permeability transition pore opening on reperfusion, leading to MI, during ischemia (36). Moreover, a study using an animal model of heterozygous HK2-deficient mice displayed increased hypertrophy and heart failure in response to transverse aortic constriction, as well as, there being an increased ROS production and de novo hypertrophy, suggesting that the use of some methods to increase the HK2 levels could control the cardiac hypertrophy (37).

As for the regulatory miRNAs of Hk2, an in vitro study was performed to detect if whether the miR-17-5p is differentially expressed in ischemia and reperfusion mice model and neonatal rat ventricular cardiomyocytes (NRCVs) under oxidative stress. The investigators suggested that overexpression of miR-17-5p increases the damage in cardiomyocyte through reduction of cell viability and increasing apoptosis (38), this result reinforces the correlation of rno-miR-17 with apoptosis in cardiomyocites and it relation with Hk2 mRNA. The hsa-miR-187 was found differentially expressed in studies that analyzed doxorubicin (DOX)-cardiotoxicity induced in cell culture. They showed an early deregulation in miR-187 expression by real-time PCR analyses in human-induced pluripotent stem cell-derived cardiomyocytes exposed to DOX which was very important and links this miRNA to its use as an early sensitive cardiotoxicity biomarker (39, 40).

Regarding rno-miR-34, its miRNA has been associated with cardiac problems (41,42). In a previous in vivo study that induced cardiac injury in neonatal and adult hearts, it was observed that miR-34 could act in cardiac repair and regeneration through its regulation of mRNA targets such as B-cell lymphoma 2 (Bcl2), Cyclin D1 and Sirtuin 1 (Sirt1), and are related with the cell apoptosis precess (41). In addition, in an in vitro study using an in vitro anoxia and reoxygenation injury (ARI) model based on rat heart-derived H9c2 cells, it has suggested an important relation of it miRNA in cardiac function. The cells were treated with Resveratrol, a natural polyphenolic compound, which suppresses the effects of rno-miR-34a upregulation in anoxia and reoxygenation injury, suggesting a cardiac protective effect on cardiomyocytes in ARI (42).

Study using RNA sequencing also corroborates with our in silico results, showing an upregulation of rno-miR-322-3p in in vitro study using neonatal heart cells in hypertrophy model (43). In cardiac injury, the expression of rno-miR-322 in vivo was measured in the rat carotid artery after injury and in vitro in rat vascular smooth muscle cells (VSMC) proliferantion and in both analyses, the rno-miR-322 were up-regulated after vascular injury, suggesting that the miRNA could be a useful therapeutic target to inhibit VSMC dedifferentiation during a vascular occlusive disease (44).

Regarding rno-miR-21-5p, an unbiased quantitative miRNA microarray analysis the right and left ventricles of normal and pulmonary arterial hypertension rats observed an upregulation of rno-miR-21-5p in a pulmonary arterial hypertension condition (45). In mice, the mmu-miR-21-5p has been associated with increased cardiac fibrosis, and its upregulation was observed in the heart of a myocardial infarction animal model, suggesting that this miRNA may act regulationg the suppression in TGF-β via, and consequently increasing the production of collagen (46).

Rno-miR-188-3p participates in the suppression of autophagy and myocardial infarction by targeting ATG7 in an in vitro and in vivo model of myocardial infarction in rats (47). Another study of miRNA microarray assay concludes that rno-miR-188 is the most downregulated miRNA in homocysteine cardiac remodeling in vitro model which suggests that it miRNA acts in cardiac remodeling in cardiovascular diseases (48).

The association between miR-532 and heart disease was observed in a study evaluating miRNAs levels in endothelial-like cells of human volunteers. The endothelial-like cells were cultured under hypoxia and normoxia conditions and the hsa-miR-532 was up-regulated under hypoxia conditions when compared to normoxia conditions (49).

Therefore, up regulation of rno-miR-17, rno-miR-187, rno-miR-34a, rno-miR-322, rno-miR-188, rno-miR-532 and rno-miR-21 and down regulation of the Hk2 mRNA target could lead to a loss of cardio protection and consequently to the development of cardiac complications, including those associated with a hyperglycemic condition.

Despite the interesting findings of this in silico study, there are some limitations including the need to validate data from hyperglycemia-induced mRNAs and regulatory miRNAs interactions and roles in experimental models. Besides our focusing on hyperglycemia effects, two different animal models of diabetes (type 1 and 2) were used to investigate mRNA and miRNAs differentially expressed in LV rats. However, it has been shown that both models develop hyperglycemia leading to structural and functional alterations in LV in both types of diabetes (50).

In conclusion, the differential expression of Pla2g2a and Hk2 mRNA and their interactions with regulatory miRNAs rno-miR-877, rno-miR-320 and rno-miR-214 (Pla2g2a) and rno-miR-17, rno-miR-187, rno-miR-34a, rno-miR-322, rno-miR-188, rno-miR-532 and rno-miR-21 (Hk2) could be associated with DCM in rats. These miRNAs and mRNAs targets may be useful biomarkers to detect early cardiovascular complications of diabetic patients.

6. Acknowledgements

R.H.B. and R.C.C.F were recipient of fellowship from CAPES, Brazil. M.H.H. and R.D.C.H. are recipients of fellowships from CNPq, Brazil.

References

    1. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 38, S1–93 (2015).

    2. L Guariguata, DR Whiting, I Hambleton, J Beagley, U Linnenkamp, JE Shaw: Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract 103(2), 137-49 (2014)

    3. JE Shaw, RA Sicree, PZ Zimmet: Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 87, 4–14 (2010)

    4. VA Kangralkar, SD Patil, RM Bandivadekar: Oxidative Stress and Diabetes: a Review. Int J Pharm Appl, 1, 38–45 (2010)

    5. U Asmat, K Abad, K Ismail: (in press) Diabetes mellitus and oxidative stress - A concise review. Saudi Pharm J. (2015)

    6. BM Fisher, G Gillen, GB Lindop, HJ Dargie, BM Frier: Cardiac function and coronary arteriography in asymptomatic type 1 (insulin-dependent) diabetic patients: evidence for a specific diabetic heart disease. Diabetologia 29, 706–12 (1986)

    7. K Mizushige, L Yao, T Noma, H Kiyomoto, Y Yu, N Hosomi, K Ohmori, H Matsuo: Alteration in left ventricular diastolic filling and accumulation of myocardial collagen at insulin-resistant prediabetic stage of a type II diabetic rat model. Circulation 101, 899-907 (2000)

    8. TJ Regan, MM Lyons, SS Ahmed, GE Levinson, HA Oldewurtel, MR Ahmad, B Haider: Evidence for cardiomyopathy in familial diabetes mellitus. J Clin Invest 60, 885–99 (1977)

    9. ZY Fang, JB Prins, TH Marwick: Diabetic cardiomyopathy: evidence, mechanisms, and therapeutic implications. Endocr Rev 25, 543–67 (2004).

    10. C Voulgari, D Papadogiannis, N Tentolouris: Diabetic cardiomyopathy: from the pathophysiology of the cardiac myocytes to current diagnosis and management strategies. Vasc Heart Risk Manag. 6, 883–903 (2010).

    11. SA Hayat, B Patel, RS Khattar, RA Malik: Diabetic cardiomyopathy: mechanisms, diagnosis and treatment. Clinical Science 107, 539–57 (2004).

    12. K Huynh, JR McMullen, TL Julius, JW Tan, JE Love, N Cemerlang, H Kiriazis, XJ Du, RH Ritchie: Cardiac-specific IGF-1 receptor transgenic expression protects against cardiac fibrosis and diastolic dysfunction in a mouse model of diabetic cardiomyopathy. Diabetes 59, 1512–20 (2010)

    13. K Huynh, H Kiriazis, XJ Du, JE Love, SP Gray, KA Jandeleit-Dahm, JR McMullen, RH Ritchie: Targeting the upregulation of reactive oxygen species subsequent to hyperglycemia prevents type 1 diabetic cardiomyopathy in mice. Free Radic Biol Med 60, 307–17 (2013).

    14. D Westermann, S Rutschow, S Jäger, A Linderer, S Anker, A Riad, T Unger, HP Schulteiss, M Pauschinger. C Tschöpe: Contributions of inflammation and cardiac matrix metalloproteinase activity to cardiac failure in diabetic cardiomyopathy: the role of angiotensin type 1 reeceptor antagonism. Diabetes 56, 641–6 (2007)

    15. W Zhou, J Yang, DI Zhang, F Li, G Li, Y Gu, M Luo: Role of Bcl-2/adenovirus E1B 19 kDa-interacting protein 3 in myocardial cells in diabetes. Exp Ther Med 10, 67–73 (2015)

    16. ZX Shan, QX Lin, CY Deng, JN Zhu, LP Mai, JL Liu, YH Fu, XY Liu, YX Li, YY Zhang, SG Lin, XY Yu: MiR-1/miR-206 regulate Hsp60 expression contributing to glucose-mediated apoptosis in cardiomyocytes. FEBS Lett. 584, 3592–600 (2010)

    17. SA Fatumo, MP Adoga, OO Ojo, O Oluwagbemi, T Adeoye, I Ewejobi, M Adebiyi, E Adebiyi, C Bewaji, O Nashiru: Computational biology and bioinformatics in Nigeria. PLoS Comput Biol. 10, 1-7 (2014)

    18. F Chen, X Zhao, J Peng, L Bo, B Fan, D Ma. Integrated microRNA-mRNA analysis of coronary artery disease. Mol Biol Rep 41, 5505–11 (2014)

    19. GEO DataSets - NCBI. http://www.ncbi.nlm.nih.gov/gds/term= (2015)

    20. LK Gerber, BJ Aronow, M Matlib: Activation of a novel long-chain free fatty acid generation and export system in mitochondria of diabetic rat hearts. Am J Physiol Cell Physiol 291, C1198–207 (2006)

    21. SK Raut, A Kumar, GB Singh, U Nahar, V Sharma, A Mittal, R Sharma, M Khullar: miR-30c mediates upregulation of Cdc42 and Pak1 in diabetic cardiomyopathy. Cardiovasc Ther 33, 89–97 (2015)

    22. GEO2R web application – NCBI. http://www.ncbi.nlm.nih.gov/geo/geo2r/ (2015)

    23. V Agarwal, GW Bell, J-W Nam, DP Bartel: Predicting effective microRNA target sites in mammalian mRNAs. Elife 4:e05005, 1-38 (2015)

    24. GK Smyth: Limma: linear models for microarray data. In: Bioinformatics and Computational biology solutions using R and Bioconductor, R Gentleman, V Carey, S Dudoit, R Irizarry, W Huber (eds.), Springer, New York, 397-420.

    25. M Murakami, Y Taketomi, H Sato, K Yamamoto: Secreted phospholipase A2 revisited. J Biochem 150, 233–55 (2011)

    26. B Ivandic, LW Castellani, XP Wang, JH Qiao, M Mehrabian, M Navab, AM Fogelman, DS Grass, ME Swanson, MC de Beer, F de Beer, AJ Lusis: Role of group II secretory phospholipase A2 in atherosclerosis: 1. Increased atherogenesis and altered lipoproteins in transgenic mice expressing group IIa phospholipase A2. Arter Thromb vasc Biol. 19, 1284–90 (1999)

    27. O Muller, A Ntalianis, W Wijns, L Delrue, K Dierickx, R Auer, N Rodondi, F Mangiacapra, C Trana, M Hamilos, E Valentin, B De Bruyne, E Barbato, J Bartunek: Association of biomarkers of lipid modification with functional and morphological indices of coronary stenosis severity in stable coronary artery disease. J Cardiovasc Transl Res 6, 536-44 (2013)

    28. Z Mallat, G Steg, J Benessiano, ML Tanguy, KA Fox, JP Collet, OH Dabbous, P Henry, KF Carruthers, A Dauphin, CS Arguelles, J Masliah, B Hugel, G Montalescot, JM Freyssinet, B Asselain, A Tedgui: Circulating secretory phospholipase A2 activity predicts recurrent events in patients with severe acute coronary syndromes. J Am Coll Cardiol 46, 1249-57 (2005)

    29. C Wang, S Gu, H Cao, Z Li, Z Xiang, K Hu, X Han: miR-877-3p targets Smad7 and is associated with myofibroblast differentiation and bleomycin-induced lung fibrosis. Sci. Rep. 6:30122, 1-11 (2016)

    30. C-L Song, B Liu, H-Y Diao, Y-F Shi, J-C Zhang, Y-X Li, N Liu, Y-P Yu, G Wang, J-P Wang, Q Li: Down-regulation of microRNA-320 suppresses cardiomyocyte apoptosis and protects against myocardial ischemia and reperfusion injury by targeting IGF-1. Oncotarget 7(26), 39740-57 (2016)

    31. M Katoh. Cardio-miRNAs and onco-miRNAs: circulating miRNA-based diagnostics for non-cancerous and cancerous diseases. Front Cell Dev Biol 2, 1–19 (2014)

    32. HQ Lu, C Liang, ZQ He, M Fan, ZG Wu: Circulating miR-214 is associated with the severity of coronary artery disease. J Geriatr Cardiol 10, 34–8 (2013)

    33. AB Aurora, AI Mahmoud, X Luo, BA Johnson, E van Rooij, S Matsuzaki, KM Humphries, JA Hill, R Bassel-Duby, HA Sadek, EN Olson: MicroRNA-214 protects the mouse heart from ischemic injury by controlling Ca2+ overload and cell death. J Clin Invest. 122, 1222–32 (2012)

    34. R Nederlof, O Eerbeek, MW Hollmann, R Southworth, CJ Zuurbier: Targeting hexokinase II to mitochondria to modulate energy metabolism and reduce ischaemia-reperfusion injury in heart. Br J Pharmacol. 171, 2067–79 (2014)

    35. JE Wilson: Isozymes of mammalian hexokinase: structure, subcellular localization and metabolic function. J Exp Biol 206, 2049–57 (2003)

    36. P Pasdois, JE Parker, AP Halestrap: Extent of mitochondrial hexokinase II dissociation during ischemia correlates with mitochondrial cytochrome c release, reactive oxygen species production, and infarct size on reperfusion. J Am Heart Assoc. 2, 1-20 (2012)

    37. R Wu, E Wyatt, K Chawla, M Tran, M Ghanefar, M Laakso, CL Epting, H Ardehali: Hexokinase II knockdown results in exaggerated cardiac hypertrophy via increased ROS production. EMBO Mol Med. 4, 633–46 (2012)

    38. W Du, Z Pan, X Chen, L Wang, Y Zhang, S Li, H Liang, C Xu, Y Zhang, Y Wu, H Shan, Y Lu: By targeting Stat3 microRNA-17-5p promotes cardiomyocyte apoptosis in response to ischemia followed by reperfusion. Cell. Physiol. Biochem. 34, 955-65 (2014)

    39. U Chaudhari, H Nemade, JA Gaspar, J Hescheler, JG Hengstler, A Sachinidis: MicroRNAs as early toxicity signatures of doxorubicin in human-induced pluripotent stem cell-derived cardiomyocytes. Arch. Toxicol., 1-12 (2016)

    40. G Holmgren, J Synnergren, CX Andersson, A Lindahl, P Sartipy: MicroRNAs as pontential biomarkers for doxorubicin-induced cardiotoxicity. Toxicol. in vitro 34, 26-34 (2016)

    41. Y Yang, H-W Cheng, Y Qiu, D Dupee, M Noonan, Y-D Lin, S Fisch, K Unno, K-I Sereti, R Liao: MicroRNA-34-a plays a key role in cardiac repair and regeneration following myocardial infarction. Circ. Res. 117(5), 450-9 (2015)

    42. B Yang, S Ma, Y-B Wang, B Xu, H Zhao, Y-Y He, C-W Li, J Zhang, Y-K Cao, Q-Z Feng: Resveratrol exerts protective effects on anoxia/reoxygenation injury in cardiomyocytes via miR-34a/Sirt1 signaling pathway. Eur. Rev. Med. Pharmacol. Sci. 20, 2734-41 (2016)

    43. MN Hirt, T Werner, D Indenbirken, M Alawi, P Demin, A-C Kunze, J Stenzig, J Starbatty, A Hansen, J Fiedler, T Thum, T Eschenhagen: Deciphering the microRNA signature of pathological cardiac hypertrophy by engineered heart tissue- and sequencing-technology. J. Mol. Cell. Cardiol. 81, 1-9 (2015)

    44. E Merlet, F Atassi, RK Motiani, N Mougenot, A Jacquet, S Nadaud, T Capiod, M Trebak, A-M Lompré, A Marchand: miR-424/322 regulates vascular smooth muscle cell phenotype and neointimal formation in the rat. Cardiovasc. Res. 98, 458-68 (2013)

    45. SR Joshi, V Dhagia, S Gairhe, JG Edwards, IF McMurtry, SA Gupte: MicroRNA-140 is elevated and mitofusin-1 is down-regulated in the right ventricle of the Sugen5416/hypoxia/normoxia model of pulmonary arterial hypertension. Am. J. Physiol. Heart Circ. Physiol 311, H689-98 (2016)

    46. H Liang, C Zhang, T Ban, Y Liu, L Mei, X Piao, D Zhao, Y Lu, W Chu, B Yang: A novel reciprocal loop between microRNA-21 and TGFβRIII is involved in cardiac fibrosis. Int. J. Biochem. Cell. B. 44, 2152-60 (2012)

    47. K Wang, C-Y Liu, L-Y Zhou, J-X Wang, B Zhao, W-K Zhao, S-J Xu, L-H Fan, X-J Zhang, C-Q Wang, Y-F Zhao, P-F Li: APF IncRNA regulates autophagy and myocardial infarction by targeting miR-188-3p. Nat. Commun. 6:6779, 1-11 (2015)

    48. PK Mishra, N Tyagi, S Kundu, SC Tyagi: MicroRNAs are involved in homocysteine-induced cardiac remodeling. Cell Biochem. Biophys. 55(3), 153-62 (2009)

    49. J Mo, D Zhang, R Yang: MicroRNA-195 regulates proliferation, migration, angiogenesis and autophagy of endothelial progenitor cells by targeting GABARAPL1. Biosci. Rep. 36, 1-11 (2016)

    50. H Bugger, ED Abel: Molecular mechanisms of diabetic cardiomyopathy. Diabetologia 57, 660–71 (2014).

6. Acknowledgements

R.H.B. and R.C.C.F were recipient of fellowship from CAPES, Brazil. M.H.H. and R.D.C.H. are recipients of fellowships from CNPq, Brazil.

References

    1. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 38, S1–93 (2015).

    2. L Guariguata, DR Whiting, I Hambleton, J Beagley, U Linnenkamp, JE Shaw: Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract 103(2), 137-49 (2014)

    3. JE Shaw, RA Sicree, PZ Zimmet: Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 87, 4–14 (2010)

    4. VA Kangralkar, SD Patil, RM Bandivadekar: Oxidative Stress and Diabetes: a Review. Int J Pharm Appl, 1, 38–45 (2010)

    5. U Asmat, K Abad, K Ismail: (in press) Diabetes mellitus and oxidative stress - A concise review. Saudi Pharm J. (2015)

    6. BM Fisher, G Gillen, GB Lindop, HJ Dargie, BM Frier: Cardiac function and coronary arteriography in asymptomatic type 1 (insulin-dependent) diabetic patients: evidence for a specific diabetic heart disease. Diabetologia 29, 706–12 (1986)

    7. K Mizushige, L Yao, T Noma, H Kiyomoto, Y Yu, N Hosomi, K Ohmori, H Matsuo: Alteration in left ventricular diastolic filling and accumulation of myocardial collagen at insulin-resistant prediabetic stage of a type II diabetic rat model. Circulation 101, 899-907 (2000)

    8. TJ Regan, MM Lyons, SS Ahmed, GE Levinson, HA Oldewurtel, MR Ahmad, B Haider: Evidence for cardiomyopathy in familial diabetes mellitus. J Clin Invest 60, 885–99 (1977)

    9. ZY Fang, JB Prins, TH Marwick: Diabetic cardiomyopathy: evidence, mechanisms, and therapeutic implications. Endocr Rev 25, 543–67 (2004).

    10. C Voulgari, D Papadogiannis, N Tentolouris: Diabetic cardiomyopathy: from the pathophysiology of the cardiac myocytes to current diagnosis and management strategies. Vasc Heart Risk Manag. 6, 883–903 (2010).

    11. SA Hayat, B Patel, RS Khattar, RA Malik: Diabetic cardiomyopathy: mechanisms, diagnosis and treatment. Clinical Science 107, 539–57 (2004).

    12. K Huynh, JR McMullen, TL Julius, JW Tan, JE Love, N Cemerlang, H Kiriazis, XJ Du, RH Ritchie: Cardiac-specific IGF-1 receptor transgenic expression protects against cardiac fibrosis and diastolic dysfunction in a mouse model of diabetic cardiomyopathy. Diabetes 59, 1512–20 (2010)

    13. K Huynh, H Kiriazis, XJ Du, JE Love, SP Gray, KA Jandeleit-Dahm, JR McMullen, RH Ritchie: Targeting the upregulation of reactive oxygen species subsequent to hyperglycemia prevents type 1 diabetic cardiomyopathy in mice. Free Radic Biol Med 60, 307–17 (2013).

    14. D Westermann, S Rutschow, S Jäger, A Linderer, S Anker, A Riad, T Unger, HP Schulteiss, M Pauschinger. C Tschöpe: Contributions of inflammation and cardiac matrix metalloproteinase activity to cardiac failure in diabetic cardiomyopathy: the role of angiotensin type 1 reeceptor antagonism. Diabetes 56, 641–6 (2007)

    15. W Zhou, J Yang, DI Zhang, F Li, G Li, Y Gu, M Luo: Role of Bcl-2/adenovirus E1B 19 kDa-interacting protein 3 in myocardial cells in diabetes. Exp Ther Med 10, 67–73 (2015)

    16. ZX Shan, QX Lin, CY Deng, JN Zhu, LP Mai, JL Liu, YH Fu, XY Liu, YX Li, YY Zhang, SG Lin, XY Yu: MiR-1/miR-206 regulate Hsp60 expression contributing to glucose-mediated apoptosis in cardiomyocytes. FEBS Lett. 584, 3592–600 (2010)

    17. SA Fatumo, MP Adoga, OO Ojo, O Oluwagbemi, T Adeoye, I Ewejobi, M Adebiyi, E Adebiyi, C Bewaji, O Nashiru: Computational biology and bioinformatics in Nigeria. PLoS Comput Biol. 10, 1-7 (2014)

    18. F Chen, X Zhao, J Peng, L Bo, B Fan, D Ma. Integrated microRNA-mRNA analysis of coronary artery disease. Mol Biol Rep 41, 5505–11 (2014)

    19. GEO DataSets - NCBI. http://www.ncbi.nlm.nih.gov/gds/term= (2015)

    20. LK Gerber, BJ Aronow, M Matlib: Activation of a novel long-chain free fatty acid generation and export system in mitochondria of diabetic rat hearts. Am J Physiol Cell Physiol 291, C1198–207 (2006)

    21. SK Raut, A Kumar, GB Singh, U Nahar, V Sharma, A Mittal, R Sharma, M Khullar: miR-30c mediates upregulation of Cdc42 and Pak1 in diabetic cardiomyopathy. Cardiovasc Ther 33, 89–97 (2015)

    22. GEO2R web application – NCBI. http://www.ncbi.nlm.nih.gov/geo/geo2r/ (2015)

    23. V Agarwal, GW Bell, J-W Nam, DP Bartel: Predicting effective microRNA target sites in mammalian mRNAs. Elife 4:e05005, 1-38 (2015)

    24. GK Smyth: Limma: linear models for microarray data. In: Bioinformatics and Computational biology solutions using R and Bioconductor, R Gentleman, V Carey, S Dudoit, R Irizarry, W Huber (eds.), Springer, New York, 397-420.

    25. M Murakami, Y Taketomi, H Sato, K Yamamoto: Secreted phospholipase A2 revisited. J Biochem 150, 233–55 (2011)

    26. B Ivandic, LW Castellani, XP Wang, JH Qiao, M Mehrabian, M Navab, AM Fogelman, DS Grass, ME Swanson, MC de Beer, F de Beer, AJ Lusis: Role of group II secretory phospholipase A2 in atherosclerosis: 1. Increased atherogenesis and altered lipoproteins in transgenic mice expressing group IIa phospholipase A2. Arter Thromb vasc Biol. 19, 1284–90 (1999)

    27. O Muller, A Ntalianis, W Wijns, L Delrue, K Dierickx, R Auer, N Rodondi, F Mangiacapra, C Trana, M Hamilos, E Valentin, B De Bruyne, E Barbato, J Bartunek: Association of biomarkers of lipid modification with functional and morphological indices of coronary stenosis severity in stable coronary artery disease. J Cardiovasc Transl Res 6, 536-44 (2013)

    28. Z Mallat, G Steg, J Benessiano, ML Tanguy, KA Fox, JP Collet, OH Dabbous, P Henry, KF Carruthers, A Dauphin, CS Arguelles, J Masliah, B Hugel, G Montalescot, JM Freyssinet, B Asselain, A Tedgui: Circulating secretory phospholipase A2 activity predicts recurrent events in patients with severe acute coronary syndromes. J Am Coll Cardiol 46, 1249-57 (2005)

    29. C Wang, S Gu, H Cao, Z Li, Z Xiang, K Hu, X Han: miR-877-3p targets Smad7 and is associated with myofibroblast differentiation and bleomycin-induced lung fibrosis. Sci. Rep. 6:30122, 1-11 (2016)

    30. C-L Song, B Liu, H-Y Diao, Y-F Shi, J-C Zhang, Y-X Li, N Liu, Y-P Yu, G Wang, J-P Wang, Q Li: Down-regulation of microRNA-320 suppresses cardiomyocyte apoptosis and protects against myocardial ischemia and reperfusion injury by targeting IGF-1. Oncotarget 7(26), 39740-57 (2016)

    31. M Katoh. Cardio-miRNAs and onco-miRNAs: circulating miRNA-based diagnostics for non-cancerous and cancerous diseases. Front Cell Dev Biol 2, 1–19 (2014)

    32. HQ Lu, C Liang, ZQ He, M Fan, ZG Wu: Circulating miR-214 is associated with the severity of coronary artery disease. J Geriatr Cardiol 10, 34–8 (2013)

    33. AB Aurora, AI Mahmoud, X Luo, BA Johnson, E van Rooij, S Matsuzaki, KM Humphries, JA Hill, R Bassel-Duby, HA Sadek, EN Olson: MicroRNA-214 protects the mouse heart from ischemic injury by controlling Ca2+ overload and cell death. J Clin Invest. 122, 1222–32 (2012)

    34. R Nederlof, O Eerbeek, MW Hollmann, R Southworth, CJ Zuurbier: Targeting hexokinase II to mitochondria to modulate energy metabolism and reduce ischaemia-reperfusion injury in heart. Br J Pharmacol. 171, 2067–79 (2014)

    35. JE Wilson: Isozymes of mammalian hexokinase: structure, subcellular localization and metabolic function. J Exp Biol 206, 2049–57 (2003)

    36. P Pasdois, JE Parker, AP Halestrap: Extent of mitochondrial hexokinase II dissociation during ischemia correlates with mitochondrial cytochrome c release, reactive oxygen species production, and infarct size on reperfusion. J Am Heart Assoc. 2, 1-20 (2012)

    37. R Wu, E Wyatt, K Chawla, M Tran, M Ghanefar, M Laakso, CL Epting, H Ardehali: Hexokinase II knockdown results in exaggerated cardiac hypertrophy via increased ROS production. EMBO Mol Med. 4, 633–46 (2012)

    38. W Du, Z Pan, X Chen, L Wang, Y Zhang, S Li, H Liang, C Xu, Y Zhang, Y Wu, H Shan, Y Lu: By targeting Stat3 microRNA-17-5p promotes cardiomyocyte apoptosis in response to ischemia followed by reperfusion. Cell. Physiol. Biochem. 34, 955-65 (2014)

    39. U Chaudhari, H Nemade, JA Gaspar, J Hescheler, JG Hengstler, A Sachinidis: MicroRNAs as early toxicity signatures of doxorubicin in human-induced pluripotent stem cell-derived cardiomyocytes. Arch. Toxicol., 1-12 (2016)

    40. G Holmgren, J Synnergren, CX Andersson, A Lindahl, P Sartipy: MicroRNAs as pontential biomarkers for doxorubicin-induced cardiotoxicity. Toxicol. in vitro 34, 26-34 (2016)

    41. Y Yang, H-W Cheng, Y Qiu, D Dupee, M Noonan, Y-D Lin, S Fisch, K Unno, K-I Sereti, R Liao: MicroRNA-34-a plays a key role in cardiac repair and regeneration following myocardial infarction. Circ. Res. 117(5), 450-9 (2015)

    42. B Yang, S Ma, Y-B Wang, B Xu, H Zhao, Y-Y He, C-W Li, J Zhang, Y-K Cao, Q-Z Feng: Resveratrol exerts protective effects on anoxia/reoxygenation injury in cardiomyocytes via miR-34a/Sirt1 signaling pathway. Eur. Rev. Med. Pharmacol. Sci. 20, 2734-41 (2016)

    43. MN Hirt, T Werner, D Indenbirken, M Alawi, P Demin, A-C Kunze, J Stenzig, J Starbatty, A Hansen, J Fiedler, T Thum, T Eschenhagen: Deciphering the microRNA signature of pathological cardiac hypertrophy by engineered heart tissue- and sequencing-technology. J. Mol. Cell. Cardiol. 81, 1-9 (2015)

    44. E Merlet, F Atassi, RK Motiani, N Mougenot, A Jacquet, S Nadaud, T Capiod, M Trebak, A-M Lompré, A Marchand: miR-424/322 regulates vascular smooth muscle cell phenotype and neointimal formation in the rat. Cardiovasc. Res. 98, 458-68 (2013)

    45. SR Joshi, V Dhagia, S Gairhe, JG Edwards, IF McMurtry, SA Gupte: MicroRNA-140 is elevated and mitofusin-1 is down-regulated in the right ventricle of the Sugen5416/hypoxia/normoxia model of pulmonary arterial hypertension. Am. J. Physiol. Heart Circ. Physiol 311, H689-98 (2016)

    46. H Liang, C Zhang, T Ban, Y Liu, L Mei, X Piao, D Zhao, Y Lu, W Chu, B Yang: A novel reciprocal loop between microRNA-21 and TGFβRIII is involved in cardiac fibrosis. Int. J. Biochem. Cell. B. 44, 2152-60 (2012)

    47. K Wang, C-Y Liu, L-Y Zhou, J-X Wang, B Zhao, W-K Zhao, S-J Xu, L-H Fan, X-J Zhang, C-Q Wang, Y-F Zhao, P-F Li: APF IncRNA regulates autophagy and myocardial infarction by targeting miR-188-3p. Nat. Commun. 6:6779, 1-11 (2015)

    48. PK Mishra, N Tyagi, S Kundu, SC Tyagi: MicroRNAs are involved in homocysteine-induced cardiac remodeling. Cell Biochem. Biophys. 55(3), 153-62 (2009)

    49. J Mo, D Zhang, R Yang: MicroRNA-195 regulates proliferation, migration, angiogenesis and autophagy of endothelial progenitor cells by targeting GABARAPL1. Biosci. Rep. 36, 1-11 (2016)

    50. H Bugger, ED Abel: Molecular mechanisms of diabetic cardiomyopathy. Diabetologia 57, 660–71 (2014).

Share and Cite
Mariana B. Lopes, Renata C. C. Freitas, Mario H. Hirata, Rosario D. C. Hirata, Adriana A. Rezende, Vivian N. Silbiger, Raul H. Bortolin, Andre D. Luchessi. mRNA-miRNA integrative analysis of diabetes-induced cardiomyopathy in rats. Frontiers in Bioscience-Scholar. 2017. 9(2); 194-229.