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Article

In Silico Analysis of miRNA-Mediated Genes in the Regulation of Dog Testes Development from Immature to Adult Form

by
Vanmathy R. Kasimanickam
1 and
Ramanathan K. Kasimanickam
2,*
1
Center for Reproductive Biology, College of Veterinary Medicine, Washington State University, Pullman, WA 99164, USA
2
Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, WA 99164, USA
*
Author to whom correspondence should be addressed.
Animals 2023, 13(9), 1520; https://doi.org/10.3390/ani13091520
Submission received: 11 March 2023 / Revised: 22 April 2023 / Accepted: 25 April 2023 / Published: 30 April 2023
(This article belongs to the Section Animal Reproduction)

Abstract

:

Simple Summary

The objective of this investigation was to elucidate the association of miRNA-mediated genes in the regulation of dog testes development from immature to adult form by in-silico analysis. In silico analysis of differentially expressed (DE) testis miRNAs between healthy immature and mature dogs were performed using miRNet, STRING, and ClueGo programs. The determination of mRNA and protein expressions of predicted pivotal genes and their association with miRNA were studied. The predicted genes are involved in the governing of several key biological functions (cell cycle, cell proliferation, growth, maturation, survival, and apoptosis) in the testis as they evolve from immature to adult forms, mediated by several key signaling pathways (ErbB, p53, PI3K-Akt, VEGF, and JAK-STAT), cytokines and hormones (estrogen, GnRH, relaxin, thyroid hormone, and prolactin). Elucidation of DE-miRNA predicted genes’ specific roles, signal transduction pathways, and mechanisms, by mimics and inhibitors, which could perhaps offer diagnostic and therapeutic targets for infertility, cancer, and birth control.

Abstract

High-throughput in-silico techniques help us understand the role of individual proteins, protein–protein interaction, and their biological functions by corroborating experimental data as epitomized biological networks. The objective of this investigation was to elucidate the association of miRNA-mediated genes in the regulation of dog testes development from immature to adult form by in-silico analysis. Differentially expressed (DE) canine testis miRNAs between healthy immature (2.2 ± 0.13 months; n = 4) and mature (11 ± 1.0 months; n = 4) dogs were utilized in this investigation. In silico analysis was performed using miRNet, STRING, and ClueGo programs. The determination of mRNA and protein expressions of predicted pivotal genes and their association with miRNA were studied. The results showed protein–protein interaction for the upregulated miRNAs, which revealed 978 enriched biological processes GO terms and 127 KEGG enrichment pathways, and for the down-regulated miRNAs revealed 405 significantly enriched biological processes GO terms and 72 significant KEGG enrichment pathways (False Recovery Rate, p < 0.05). The in-silico analysis of DE-miRNA’s associated genes revealed their involvement in the governing of several key biological functions (cell cycle, cell proliferation, growth, maturation, survival, and apoptosis) in the testis as they evolve from immature to adult forms, mediated by several key signaling pathways (ErbB, p53, PI3K-Akt, VEGF and JAK-STAT), cytokines and hormones (estrogen, GnRH, relaxin, thyroid hormone, and prolactin). Elucidation of DE-miRNA predicted genes’ specific roles, signal transduction pathways, and mechanisms, by mimics and inhibitors, which could perhaps offer diagnostic and therapeutic targets for infertility, cancer, and birth control.

1. Introduction

MicroRNAs (miRNAs) play a key role in the differentiation, development, maintenance, and functions of various tissues. Spermatogenesis is a sequence of complex processes [1,2], which are regulated by pathways mediated by miRNAs [3,4]. The genome of testicular cells is actively transcribed into RNAs that involves many non-coding RNAs consisting of circular RNAs (circRNAs) and miRNAs to regulate and generate phase-specific gene expression patterns [5,6]. In mouse testis, pachytene, round, and elongated spermatocytes showed the highest levels of miRNA expressions [7,8,9]. Numerous miRNAs are preferentially expressed in the testis and male germ cells of humans and mice [5,6,7,8,9]. However, the biological functions of many miRNAs involved in spermatogenesis and testicular function are largely unknown. It should be noted that diminution of the Dicer gene upsets the proliferation and differentiation of mouse spermatogenic germ cells [10,11,12].
Dicer is an endonuclease enzyme that belongs to the ribonuclease III (RNase III) family. It activates the RNA-induced silencing complex (RISC), which is essential for RNA interference. The RISC contains dsRNA binding proteins, including protein kinase RNA activator (PACT) and transactivation response RNA binding protein (TRBP) that process pre-microRNAs into mature microRNAs (miRNAs) that target specific mRNA species for regulation. Dicer plays an important role in spermatogenesis [13,14]. MiRNAs along with dicer act as a post-transcriptional regulatory unit in testicular tissue development and spermatogenesis [15,16]. Therefore, miRNAs can be targeted for evaluating male fertility and can serve as useful biomarkers.
It is conceivable that miRNAs can regulate meiosis and thus spermatogenesis [17] by regulating mRNA degradation and disrupting mRNA translation [18,19]. While recent studies focused on miRNA tissue expression in rodents and humans, miRNA data for dogs are lacking [20,21]. We recently reported miRNA expression patterns between sexually immature and mature canine testes [20].
The objective of this investigation was to elucidate miRNA–mRNA interaction of differentially expressed (DE) miRNAs between immature and mature canine testis by constructing a protein–protein network and performing cluster gene analysis to elucidate key biological functions.

2. Materials and Methods

2.1. miRNA Data Profiling

The DE-miR data used in this investigation were obtained from the testes of healthy Labrador-mix dogs (young: 2.2 ± 0.13 months; n = 4 and adult: 11 ± 1.0 months; n = 4) undergoing elective castrations [20]. Briefly, RNA was isolated from the testis using the TRIzol homogenization method, and RNA concentration and quality were determined [20,21]. Then, RNA samples were reverse-transcribed using a Micro Script II RT kit (Qiagen, Frederick, MD, USA). Micro Script HiSpec buffer (5X) was used to prepare cDNA for mature miRNA profiling, which was performed using miRNome miScript miRNA polymerase chain reaction (PCR) array kits. The Canine miScript miRNA PCR Array plate (Qiagen) included primers for 84 mature miRNAs and controls (Table 1). The controls were cel-miR-39-3p (H01 and H02), SNORD61 (H03), SNORD68 (H04), SNORD72 (H05), SNORD95 (H06), SNORD96A (H07), RNU6-2 (H08), miRTC (H09 and H10), and PPC (H11 and H12). SNORDs and RNU6-2 served as internal normalizers. Two reverse transcription controls and two positive controls ensured the efficiency of the array, reagents, and instrument performance.
In order to obtain miRNA-predicted gene datasets from young and adult dogs, the miRNet web tool (http://www.mirnet.ca/) (accessed on 4 March 2022) [22,23] was used to analyze retrieved miRNA datasets, and then Protein–Protein Interaction (PPI) networks of co-expressed genes were designed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) online database (http://stringdb.org/) (accessed on 4 March 2022) [24] and ClueGo (accessed on 4 March 2022) [25].

2.2. Conserved Nucleotide Sequences

Nucleotide sequences of differentially expressed canine miRNAs were retrieved from miRBase, (www.mirbase.org) (accessed on 4 March 2022) and compared with those of homo sapiens for similarities [22,23].

2.3. Identification of Target Genes of Differentially Expressed miRNAs

The target and predicted genes of DE-miRNAs were retrieved using miRNet (http://www.mirnet.ca/) (accessed on 4 March 2022) [24,25]. This tool integrated data from different miR databases (TarBase, miRTarBase, and miRecords) and identified target and predicted genes. The integration analysis was performed separately for upregulated and downregulated DE-miRNAs.

2.4. Gene Ontology Enrichment and KEGG Analysis

The protein–protein interaction (PPI) network for DE-miRNAs’ predicted target genes was identified using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) online database (http://stringdb.org/) (accessed on 4 March 2022) [26]. Gene Ontology (GO) functional annotation for biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for integrated target genes of DE-miRNAs. A p-value of <0.05 was regarded as statistically significant.

2.5. Identification and Analysis of Hub Gene

The protein–protein interaction (PPI) for DE-miRNAs from STRING database was exported to Cytoscape software (version 3.9) and visualized [27]. The top 30 hub genes were selected (the top 30 nodes of the PPI network) using the Maximal Clique Centrality (MCC) method [28], which has a better performance in terms of its precision in predicting the top essential proteins. Further analysis was performed using ClueGO [29] to integrate GO terms as well as KEGG pathways and create a functionally nested or organized GO/pathway term (k score = 3). This task analyzes one set of genes or compares two lists of genes and comprehensively visualizes functionally grouped terms [29].

2.6. Real-Time Polymerase Chain Reaction for Determination of mRNA Expression of Hub Genes

Total RNA extraction and complementary DNA synthesis were performed as previously described [30]. Briefly, testis samples for each animal were used to extract RNA by TRizol Invitrogen, Carlsbad, CA, USA) tissue homogenization method. The RNA concentration and quality were determined using a NanoDrop-1000 spectrophotometer (Thermo Scientific, Rockford, IL, USA), and all RNA samples were treated with DNAse I (Invitrogen) to remove the DNA contaminant. Complementary DNA was synthesized using the iScript cDNA synthesis kit (Bio-Rad Laboratories Inc., Hercules, CA, USA) from each biological replicate and stored at −20 °C.
Specific primer pairs (Table 2) for the hub genes were designed using primer-BLAST (www.ncbi.nlm.nih.gov/tools/primer-blast/, accessed on 10 January 2022). Prior to real-time PCR, ethidium bromide-stained electrophoresis gel for the amplicon of the expected size was performed (Supplementary file S1). Real-time PCR for each sample was carried out using Fast SYBR Green Master Mix (Applied Biosystems, Foster City, CA, USA) as described [25] following the manufacturer’s instructions. Endogenous control glyceraldehyde-3-phosphate dehydrogenase (GADPH) was used to normalize the threshold cycle (CT) values. Fold comparisons were made between the mature and immature groups.
Statistical analysis was performed using SAS Analytics software (9.4 version; SAS Institute, Cary, NC, USA). A p value ≤ 0.05 is considered as statistically significant. Analysis of variance (ANOVA) was used to calculate statistical significance. All mRNA data are expressed as mean ± SEM. The correlation (r) between miRNA and mRNA was calculated using PROC CORR of SAS (Pearson correlation coefficient).

2.7. Protein Immunoblots

Western blots for each testis tissue sample from mature and immature dogs were performed separately by methods described previously [30]. Briefly, protein extraction methods included: the addition of protease and phosphatase inhibitor to the testis sample, homogenization, lysate incubation at 4 °C for 45 min, centrifugation (at 12,000× g for 20 min), and determination of protein concentrations. Protein lysates (60 μg/lane) were then electrophoresed through 12% SDS-PAGE gel (Bio-Rad Laboratories, Philadelphia, PA, USA) and then transferred onto a PVDF membrane (Bio-Rad Laboratories). Samples were incubated in 10% goat serum in PBS to block non-specific binding. After overnight incubation at 4 °C with primary antibodies [mouse monoclonal to DNMT1 (Catalog # MA5-16169) and rabbit polyclonal to PTEN (Catalog # 600-401-859) from Thermo Fisher Scientific, Waltham, MA, USA; and mouse polyclonal to actin (sc-47778) from Santa Cruz Biotechnology, Santa Cruz, CA, USA], membranes were washed in buffer containing 2% animal serum and 0.1% detergent. The membranes were then incubated in secondary antibodies [goat anti-mouse IgG-FITC for DNMTA1 and β-actin (sc-2010; Santa Cruz Biotechnology), and goat anti-rabbit IgG-FITC for PTEN (sc-2012; Santa Cruz Biotechnology) for 1 h at room temperature. The blots were then washed and scanned using the Pharos FX Plus system (Bio-Rad Laboratories). FITC fluorophore was excited at 488 nm and read at the emission wavelength of 530 nm. All possible negative controls, equivalent concentrations of nonspecific IgG or normal serum in place of the primary antibody, were included.

3. Results

For MiRNA-associated gene quantitative profiling, 32 upregulated and 12 downregulated miRNAs were included for in-silico analysis (Figure 1). Similarities of the nucleotide sequences of differentially expressed canine miRNAs were comparable with those of homo sapiens (Table 3). These up- and down-regulated miRNAs were submitted to elucidate predicted genes. Of 32 upregulated miRNAs submitted, 31 predicted 560 genes (Supplementary file S2) and of 12 downregulated miRNAs, 11 predicted 53 genes (Supplementary file S3).
Figure 2A shows the PPI for the upregulated miRNAs (546 nodes; 3134 edges; PPI enrichment p < 1.0 × 10−16) and reveals 978 significantly enriched biological processes GO terms (False Recovery Rate, p < 0.05) and 127 significant (False Recovery Rate, p < 0.05) KEGG enrichment pathways (Supplementary file S4). Figure 2B shows the PPI for the down-regulated miRNAs (53 nodes and 138 edges, PPI enrichment p < 1.11 × 10−14) and reveals 405 significantly enriched biological processes GO terms (False Recovery Rate, p < 0.05) and 72 significant (False Recovery Rate, p < 0.05) KEGG enrichment pathways (Supplementary file S5).
The top-ranked 30 hub genes using Maximal Clique Centrality (MCC) method for upregulated miRNAs and downregulated miRNAs were screened and presented in Figure 3A and 3B, respectively. Table 4 shows the hub genes and their roles, tissue expression, and protein–protein interactions (up to six closely related genes), for up-and down-regulated miRNAs in adult dog testis. Canine miRNAs and associated hub genes are presented in Table 5. Further, the top 30 upregulated and downregulated hub genes’ associated KEGG pathways are presented in Table 6.
To interpret functionally nested gene ontology and pathway annotation networks for the predicted genes of adult dog testis, ClueGo nested network analysis was performed, and the results are presented in Supplementary files S6 and S7 for up- (29 GO term groups and 23 KEGG pathway groups) and down-regulated miRNAs (8 GO term groups and 2 KEGG pathway groups), respectively. For up-regulated hub genes, a functionally grouped network with terms as nodes (Figure 4A), GO-pathway terms specific for genes (Figure 4B), and a chart with functional groups including specific terms (Figure 4C) is presented. Similarly, for down-regulated hub genes, functionally grouped networks with terms as nodes (Figure 5A), GO-pathway terms specific for genes (Figure 5B), and a chart with functional groups including specific terms (Figure 5C) is presented.
The mRNA expressions for CDKN1A, EGFR, JUN, NOTCH1, and PIK3R1 were greater (p < 0.05) in abundance in mature compared to immature dog testis (p < 0.05; Figure 6); whereas the mRNA expressions for DNMT1, PTEN, ESR1, and TIMP3 were lower in abundances in mature compared to the immature testis (p < 0.05; Figure 6). The mRNA expressions of hub genes for upregulated miRNA were in greater abundance and the mRNA expressions of hub genes for downregulated miRNA were in lower abundance (p < 0.05). There was a positive association for the miRNA–mRNA pair (Figure 7; r = 0.60; p < 0.05). The relative expressions of miRNA and associated hub gene mRNA in mature dog testis were also provided in Table 7.
Protein immunoblots were performed to recognize the PTEN, DNMT1, and β-actin (reference gene) proteins. The PTEN, DNMT1, and β-actin proteins were 47, ~180, and 42 kDa, respectively (Supplementary file S8).

4. Discussion

In the present study using DE-miRNAs between immature and adult dog testis samples, we identified 613 genes involved in the regulation of testis development. The GO biological functional enrichment showed that genes were mainly enriched in regulation of cellular process, cellular response to stimulus, developmental process, cell population proliferation, cell death, cell differentiation, apoptotic process, and cell metabolic process. The KEGG pathway enrichment showed that genes were mainly enriched in cancer biology, PI3K-Akt signaling pathway, AGE-RAGE signaling pathway, p53 signaling pathway, cellular senescence, hormone signaling pathway and human papillomavirus infection. Furthermore, we performed bioinformatics analysis to identify the potential key genes based on random selection algorithm, GO semantic similarity, PPI network, and cluster analysis. The results showed the involvement of differentially expressed genes in growth, sexual development, the maintenance of gluconeogenesis and lipid metabolism, cell proliferation, Sertoli and spermatogonial stem cells division and growth, cell cycle (cell cycle progression at G1-S phase), maturation, cell survival, and apoptosis. These key genes functioned as the essential molecules that might have mediated the testis development process between the immature and adult dogs.
Micro RNAs critically regulate the proliferation and/or early differentiation of stem cell populations in testis [31]. In mouse, deletion of both miR-34b and miR-34c led to sterility, resulting in reduced sperm count, changed sperm morphology, and abnormal motility [32]. It has been cited that miR-34c-5p could be used as biomarkers of germ cell maturation [33,34,35]. The differences in expressions of cfa-miR-34b and cfa-miR-34c were vast between mature and immature testis in the current investigation. The cfa-miR-34b and cfa-miR-34c associated with hub genes NOTCH1 and MYC regulates the cell cycle, cellular fate determination, cell proliferation, cell differentiation, and cellular apoptosis. MicroRNA-34b expression was associated with meiotic-specific cells from the murine testis [36] and miR-34c was highly expressed in pachytene spermatocytes and round spermatids when compared with testicular somatic cells and other tissues in adult mice [37]. In humans, miR-34b was downregulated in asthenozoospermic and oligoasthenozoospermic sperm compared with normal sperm, suggesting its function is critical beyond sperm production [38]. The enhanced expression of miR-34c in the germ cells during the later steps of spermatogenesis indicates its functional significance in meiosis and spermiogenesis. Retinoic acid receptor gamma is one of the target genes of miR-34c, indicating the critical role of retinoic acid signaling in the control of meiosis [39]. MicroRNA-34 is intrinsically linked to the p53 tumor suppressor gene and the established Wnt cascade [40]. Wnt/b-catenin signaling is essential for the regulation of spermatogenesis [41], and the gene p53 is important for the biogenesis of acrosome and nuclear shaping during spermiogenesis. Previous studies demonstrated that Sertoli proliferation and differentiation can be mediated through the Wnt/β-catenin signaling pathway [42,43], mTOR signaling pathway [44,45,46], and TGF-β signaling pathway [47,48]. PTEN, PI3K/AKT, and STAT signaling pathways were found to be involved in bull sperm cell apoptosis [49]. Recent study on analysis of miRNAs and target mRNAs between immature and mature bull testis showed enrichment during Sertoli proliferation and differentiation, and sperm apoptosis [50]. Further, several differentially expressed genes enriched in metabolic pathways were involved in fat metabolism, including fatty acid degradation, adipocytokine signaling, and PPAR signaling pathway [50].
In the current study, cfa-miR-7a was upregulated in adult testis and EGF was identified as one of its target genes. Further, this upregulated miRNA in adult testis-associated hub genes CDH1 and MET interacted with EGF and EGFR. The ErbB signaling pathway-associated genes found were CDKN1A, EGFR, JUN, KRAS, MYC, and PIK3R1. The CDKN1A is the primary p53 target gene that mediates cell-cycle arrest [51,52]. LH signaling was reduced in CDKNIA knockout mice plausibly affecting pubertal development [53]. The EGF mediates spermatogonial proliferation through its receptors ErbB1, ErbB2, and ErbB4 in the testis [54]. It is possible that EGF mediates spermatogonial proliferation through its receptors on Sertoli cells via activation of MAPK cascade and/or PI3K cascade by elevating the expressions of SCF, Ig-NRG1, and EGFRs (ERBBRs) [55,56]. Further, KRAS expression patterns showed preferential tissue activation suggesting different cellular functions [57,58]. Interestingly, cfa-miR-125a was downregulated in adult testis and its associated hub genes were ERBB2 and ERBB3. Aberrant EGFR activation is a significant factor in the development and progression of multiple cancers [59] suggesting that a balanced expression is warranted in testis development.
In the current study, the upregulated cfa-miR-29c-associated gene was PIK3R1, and its signals are important for cell activities, including cell growth and division, migration, production of new proteins, transport of materials within cells, and cell survival. Studies suggest that PI3K signaling may be involved in the regulation of several hormones, including insulin. NF-kappaB and PI3K-Akt pathways are among PI3 K-associated pathways. PI3K-Akt pathway is an intracellular signal transduction pathway that promotes metabolism, proliferation, cell survival, growth, and angiogenesis in response to extracellular signals [60]. This is mediated through serine and/or threonine phosphorylation of a range of downstream substrates. The PI3K-Akt pathway engages in many stages of male reproduction, including the regulation of the hypothalamus–pituitary–gonad axis during spermatogenesis, the proliferation and differentiation of spermatogonia and somatic cells, and the regulation of sperm autophagy and testicular endocrine function in the presence of endocrine disrupting chemicals [61]. Further, the PI3K-Akt pathway is required for the stimulatory actions of FSH [62]. It should be noted that the activation of PI3K by EGF occurs via the association of the p85 subunit of PI3K (PIK3R1) with the activated EGFR [63]. PIK3R1/p85a is the most abundant isoform in normal tissues [64] but its expression is reduced in cancer suggesting that it regulates cell proliferation. In the current study, cluster analysis revealed PI3K-Akt pathway was regulated by associated genes BCL2L11, CCND1, CCNE1, CDK4, CDK6, CDKN1A, EGFR, FGFR1, JAK2, KDR, KRAS, MCL1, MET, MYC, PIK3R1, PTEN, and RELA.
Current investigation revealed that upregulated canine miR-15a and miR-378 were associated with hub gene VEGFA, which regulates neovascularization and cord formation, and potentially acts through the PI3K pathway during testis morphogenesis [65]. Further, VEGF signaling regulates germ cell proliferation and promotes testicular regeneration via direct action on germ cells and the enhancement of vascularization. Associated genes KDR, KRAS, and PIK3R1 in the VEGF signaling pathway in the current study, may regulate the testis morphogenesis and regeneration.
Regulation of testis development by hormones has been described in [66]. Cluster analysis in the current investigation revealed the involvement of associated genes EGFR, JUN, KRAS, and MMP2 in the regulation of the GnRH signaling pathway. The FSH regulates Sertoli cell proliferation during fetal and early postnatal life by activating cAMP/PKA/ERK1/2 and PI3K/Akt/mTORC1 dependent pathways, and by increasing the transcriptional activity of c-MYC and HIF2 and the expression of CCND1 [67]. The CCND1 is a hub gene for upregulated canine miRNAs 15a, 16, 19a and 20a, and MYC is a hub gene for upregulated miR-34c in mature testis in the current investigation, suggesting the involvement in the Sertoli cell proliferation as indicated in the previous studies. Insulin and IGF1 regulate testicular functions by activating PI3K/Akt and ERK1/2 signaling pathways. Mice lacking INSR and IGF1R in Sertoli cells showed a 72% reduction in testis size and a 79% reduction in daily sperm production [68,69]. Relaxin is another member of the insulin-related peptide family involved in Sertoli cell proliferation [66,70]. Associated genes EGFR, JUN, KRAS, MMP2, PIK3R1, and RELA engage in the relaxin signaling pathway in the current study, could have contributed to Sertoli cell proliferation. Genes IGF1, AMH, hedgehog (DHH), and platelet-derived growth factor (PDGF) seem to regulate Leydig cell differentiation and function. The IGF1 stimulated differentiation and mitosis of Leydig cells [71]. Equally, the decrease in estrogen production inhibited Leydig cell differentiation in prepubertal and adult rat testes [72]. Since IGF1, DHH, and PDGF are Sertoli cells paracrine factors, it seems reasonable to speculate that thyroid hormone actions on Leydig cells might be, at least in part, mediated through Sertoli cells. Relaxin-induced Sertoli cell proliferation involves the activation of a Gi protein and the activation of EKR1/2 and PI3K/Akt pathways [66,70]. Activin A along with FSH regulates Sertoli cell proliferation during the fetal and postnatal period via the SMAD pathway [73,74]. The NOTCH1 is identified as a hub gene for upregulated cfa-miR-34c in the current investigation. NOTCH1-IC forms a transcriptional complex with SMAD, a component of established TGF-β signaling, and regulates the expression of HES1 by binding to the promoter [75]. These signal cross-talks are sophisticated regulation processes during cell fate determination and cancer development [76]. Interestingly, Nemo-like kinase (NLK) was a hub gene for downregulated miR-181a, -181b. The NLK phosphorylates the NOTCH1 protein. NLK-mediated phosphorylation does not interfere with the nuclear localization of NOTCH1-IC but decreases the association of the Notch active transcription complex [77]. Inhibin B is the main circulating inhibin produced by Sertoli cells; however, inhibin B has no role by itself but plays a role in the modulation of activin A-induced Sertoli cell proliferation [66,67].
Cytokines play an important regulatory role in the development and normal function of the testis. They signal via the adapter protein MyD88 to activate NFκB; and TGFβs and activins, which signal through serine/threonine kinase receptor subunits to activate SMAD transcription factors. It has been shown that IL1α and IL1β increased DNA synthesis and Sertoli cell number in vitro and IL1α had a more potent effect than IL1β [78]. TNFR1 has been detected in Sertoli cells and probably mediates TNFα biological actions, pro-inflammatory and immunoregulatory responses, and apoptosis [79]. A chemokine, CXCL8, was identified as one of top 30 hub genes in the current study. It should be noted that PTEN (hub gene for upregulated miR-22 and downregulated miR-214) loss induces a selective upregulation of CXCL8 signaling that sustains cell growth and survival [80]. In the current study, cluster analysis revealed involvement of T and B cell receptor signaling pathway regulated by CDK4, JUN, KRAS, PIK3R1, and RELA genes. This regulation could have contributed to the development and normal function of the testis.
Androgen-dependent regulation of Sertoli cell proliferation is an indirect effect probably exerted through the secretion of a paracrine factor [66,67]. Direct effects of androgens on Sertoli cells seem to be related to maturation of this cell type. Estrogens play important roles in the regulation of testis development and spermatogenesis. Associated genes EGFR, ESR1, JUN, KRAS, MMP2, and PIK3R1 were involved in the estrogen signaling pathway in the current study. ESR was a hub gene for miR-18a. -19a, and -22 in the current study. Estrogens increase proliferation of Sertoli cells through ERα and GPER and on the other hand, at the end of the proliferative period it promotes cessation of proliferation and cell maturation through ERβ [66,67]. ERα promotes cell proliferation through the activation of NFκB in a PI3K- and a ERK1/2-dependent manner and that this is accompanied by CCND1 induction [81]. GPER activates Src/PI3K/Akt pathway which participates in E2-induced Sertoli cell proliferation via regulating the expression of S-phase kinase-associated protein 2 (SKP2) [82]. The ERβ promotes cell cycle exit and cell maturation through the activation of CREB in a PI3K-dependent manner and this leads to the expression of the Sertoli cell differentiation markers—CDKN1B, GATA1 (isoform GATA6 was a hub gene for down-regulated cfa-miR-181a and -181b), and DMRT1 [66,67]. Role of thyroid hormone and retinoic acid in the cessation of proliferation and in maturation of Sertoli cells. Thyroid hormone regulated Sertoli cell maturation is through TRα1 and AIMP1 (p43) receptors. The mechanisms participating in these processes involve the regulation of CX43, c-MYC (MYC was identified as a hub gene for upregulated cfa-miR-34b and MYCN a hub gene for miR-101), P21CIP1 (CDKN1A a hub gene for upregulated cfa-miR-106a), and P27KIP1 (CDKN1B a hub gene for down-regulated cfa-miR-181a) [83,84,85]. Cluster analysis revealed associated genes CCND1, ESR1, FOXO1, KRAS, MYC, NOTCH1, and PIK3R1 involved in the regulation of the thyroid signaling pathway.
Studies observed positive (upregulated–upregulated; complement) or negative (upregulated–downregulated; reverse complement) associations between miRNA and mRNA pairs [86]. It should be noted that miRNAs can activate gene expression directly or indirectly in response to different cell types and environments and in the presence of distinct cofactors. The biological outcome of miRNA–mRNA interaction can be altered by several factors contributing to the binding strength and repressive effect of a potential target site. Interestingly, it has been reported that significant miRNA–mRNA associations were complementing in normal tissue and miRNA–mRNA whereas associations were reverse complementing in the same tissue in diseased conditions [87]. The association between miRNA and hub gene mRNA expressions was positive in the current study.
Collectively, in the current study, GO analysis of differentially expressed genes showed that the down-regulated genes were significantly enriched in a large number of GO terms. Further, the GO analysis showed that most GO terms were downregulated, indicating that these DEGs may have played important roles in the development of the testis of immature dogs. However, the upregulated genes enriched in the GO terms were related to meiosis, protein ubiquitination, and fertilization of adult dogs. This suggests that a large number of genes with key roles in male reproduction traits are highly expressed in mature testis. Interestingly these genes are not expressed or expressed in low abundance in immature dog testis. Similar results were reported in a bull study [50]. Our analysis identified differentially expressed genes and differentially expressed miRNAs associated with male reproduction and elaborated cluster networks between miRNAs and genes regulating testis structure and function. This outcome provides significant insights into the molecular mechanisms of male fertility and spermatogenesis and will be valuable for future genetic and epigenetic studies of testis development and maturity.

5. Conclusions

The complex relationship between miRNA and gene interaction is a vital component of miRNA functional analysis in the testis development process. Abnormal expression of miRNAs and/or any regulation disturbance can lead to impaired germ cells, abnormal spermatogenesis, and even neoplasia. The present in-silico analysis showed the involvement of canine testicular miRNAs in structure and function. The DE-miRNAs between immature and adult canine testis and their associated genes involved in several regulatory pathways play a crucial role during the immature testis transition to the adult testis. A focused study of individual miRNA molecules may elucidate specific functions or problems, endorse the development of anti-oncogenic reagents and infertility/subfertility treatments, and bolster novel contraceptive technologies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani13091520/s1, Supplementary file S1: The ethidium bromide-stained electrophoresis gel, with amplicons of expected sizes. Supplementary file S2: Upregulated miRNAs- and miRNet-based target and predicted genes in cows with metritis. Supplementary file S3: Downregulated miRNAs- and miRNet-based target and predicted genes in cows with metritis. Supplementary file S4: STRING-based protein–protein interaction network predicted biological processes, cellular components, molecular functions, and KEGG pathways for upregulated miRs predicted genes. Supplementary file S5: STRING-based protein–protein interaction network predicted biological processes, cellular components, molecular functions, and KEGG pathways for downregulated miRs predicted genes. Supplementary file S6: ClueGo-based protein–protein interaction predicted biological processes, cellular components, molecular functions, and KEGG pathways for upregulated miRNAs predicted hub genes. Supplementary file S7: ClueGo-based protein–protein interaction predicted biological processes, cellular components, molecular functions, and KEGG pathways for downregulated miRNAs predicted hub genes. Supplementary file S8: Representative Western blots of isozymes PTEN, phosphatase and tensin homolog; DNMT1, DNA methyltransferase 1; and ACTB, beta actin.

Author Contributions

Conceptualization, V.R.K. and R.K.K.; methodology, V.R.K. and R.K.K.; software, V.R.K. and R.K.K.; validation, V.R.K. and R.K.K.; formal analysis, V.R.K. and R.K.K.; investigation, V.R.K. and R.K.K.; resources, V.R.K. and R.K.K.; data curation, V.R.K. and R.K.K.; writing—original draft preparation, V.R.K. and R.K.K.; writing—review and editing, V.R.K. and R.K.K.; visualization, V.R.K. and R.K.K.; supervision, V.R.K. and R.K.K.; project administration, V.R.K. and R.K.K.; funding acquisition, V.R.K. and R.K.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This project was determined to be exempt from IACUC review per WSU IACUC Policy 21 (https://iacuc.wsu.edu/documents/2019/04/policy-21.pdf/) (accessed on 7 March 2022) and covered under the WSU Tissue Use Protocol #04070.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available from the corresponding author on reasonable request.

Acknowledgments

The authors thank the College of Veterinary medicine, Washington State University for the support.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Up- and down-regulated microRNAs in adult canine testis compared with immature testis used for in silico analysis.
Figure 1. Up- and down-regulated microRNAs in adult canine testis compared with immature testis used for in silico analysis.
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Figure 2. STRING protein–protein interaction (PPI) network. (A) PPI network of predicted genes (74) for the upregulated miRNAs (72 nodes and 281 edges, PPI enrichment p < 1.0 × 10−16). (B) PPI network of predicted genes (123) for the downregulated miRNAs (120 nodes and 189 edges, PPI enrichment p < 1.11 × 10−14). The color nodes represent proteins. The edges represent interactions.
Figure 2. STRING protein–protein interaction (PPI) network. (A) PPI network of predicted genes (74) for the upregulated miRNAs (72 nodes and 281 edges, PPI enrichment p < 1.0 × 10−16). (B) PPI network of predicted genes (123) for the downregulated miRNAs (120 nodes and 189 edges, PPI enrichment p < 1.11 × 10−14). The color nodes represent proteins. The edges represent interactions.
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Figure 3. Protein–Protein Interaction (PPI) network of hub genes of DE-miRNAs. (A) PPI network of top genes for highly upregulated miRNAs. (B) PPI network of the top genes for downregulated miRNAs. DE-miRNAs are differentially expressed microRNAs; Black lines indicate interactions between genes. The PPI among hub genes for upregulated miRNAs was greater compared with hub genes for down-regulated miRNAs. The color red to yellow denotes a high to a low degree of expression. Black lines indicate interactions between genes.
Figure 3. Protein–Protein Interaction (PPI) network of hub genes of DE-miRNAs. (A) PPI network of top genes for highly upregulated miRNAs. (B) PPI network of the top genes for downregulated miRNAs. DE-miRNAs are differentially expressed microRNAs; Black lines indicate interactions between genes. The PPI among hub genes for upregulated miRNAs was greater compared with hub genes for down-regulated miRNAs. The color red to yellow denotes a high to a low degree of expression. Black lines indicate interactions between genes.
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Figure 4. ClueGO analysis of upregulated hub genes in adult dog testis. (A) Functionally grouped network with terms as nodes linked, based on their kappa score levels (≥0.4), where only the label of the most significant term per group is shown. The node size represents the term enrichment significance. Functionally related groups partially overlap. The color gradient shows the gene proportion of each cluster associated with the term. (B) GO-pathway terms specific for upregulated genes. The bars represent the number of genes associated with the terms. The percentage of genes per term is shown as a bar label. (C) Overview chart with functional groups including specific terms for upregulated genes. The color gradient shows the gene proportion of each cluster associated with the term. (** p < 0.001).
Figure 4. ClueGO analysis of upregulated hub genes in adult dog testis. (A) Functionally grouped network with terms as nodes linked, based on their kappa score levels (≥0.4), where only the label of the most significant term per group is shown. The node size represents the term enrichment significance. Functionally related groups partially overlap. The color gradient shows the gene proportion of each cluster associated with the term. (B) GO-pathway terms specific for upregulated genes. The bars represent the number of genes associated with the terms. The percentage of genes per term is shown as a bar label. (C) Overview chart with functional groups including specific terms for upregulated genes. The color gradient shows the gene proportion of each cluster associated with the term. (** p < 0.001).
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Figure 5. ClueGO analysis of downregulated hub genes in adult dog testis. (A) Functionally grouped network with terms as nodes linked, based on their kappa score levels (≥0.4), where only the label of the most significant term per group is shown. The node size represents the term enrichment significance. Functionally related groups partially overlap. The color gradient shows the gene proportion of each cluster associated with the term. (B) GO-pathway terms specific for upregulated genes. The bars represent the number of genes associated with the terms. The percentage of genes per term is shown as a bar label. (C) Overview chart with functional groups including specific terms for upregulated genes. The color gradient shows the gene proportion of each cluster associated with the term. (** p < 0.001).
Figure 5. ClueGO analysis of downregulated hub genes in adult dog testis. (A) Functionally grouped network with terms as nodes linked, based on their kappa score levels (≥0.4), where only the label of the most significant term per group is shown. The node size represents the term enrichment significance. Functionally related groups partially overlap. The color gradient shows the gene proportion of each cluster associated with the term. (B) GO-pathway terms specific for upregulated genes. The bars represent the number of genes associated with the terms. The percentage of genes per term is shown as a bar label. (C) Overview chart with functional groups including specific terms for upregulated genes. The color gradient shows the gene proportion of each cluster associated with the term. (** p < 0.001).
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Figure 6. mRNA expression of hub genes in mature and immature canine testis. * Relative to immature dog testis (mRNA expression 1 fold) (p ≤ 0.05); CDKN1A, cyclin dependent kinase inhibitor 1A; EGFR, epidermal growth factor receptor; JUN, Jun proto-oncogene, AP-1 transcription factor subunit; KRAS, KRAS proto-oncogene, GTPase; MYC, MYC proto-oncogene, bHLH transcription factor; PIK3R1, phosphoinositide-3-kinase regulatory subunit 1; GADPH, glyceraldehyde-3-phosphate dehydrogenase (endogenous control).
Figure 6. mRNA expression of hub genes in mature and immature canine testis. * Relative to immature dog testis (mRNA expression 1 fold) (p ≤ 0.05); CDKN1A, cyclin dependent kinase inhibitor 1A; EGFR, epidermal growth factor receptor; JUN, Jun proto-oncogene, AP-1 transcription factor subunit; KRAS, KRAS proto-oncogene, GTPase; MYC, MYC proto-oncogene, bHLH transcription factor; PIK3R1, phosphoinositide-3-kinase regulatory subunit 1; GADPH, glyceraldehyde-3-phosphate dehydrogenase (endogenous control).
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Figure 7. Correlation coefficient (r) of mean relative expressions of miRNA and mRNA pairs. ● Each point represents at least one miRNA-mRNA pair.
Figure 7. Correlation coefficient (r) of mean relative expressions of miRNA and mRNA pairs. ● Each point represents at least one miRNA-mRNA pair.
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Table 1. miScript canine miRNA polymerase chain reaction array.
Table 1. miScript canine miRNA polymerase chain reaction array.
Well123456789101112
Acfa-let-7acfa-let-7bcfa-let-7ccfa-let-7fcfa-let-7gcfa-miR-1cfa-miR-101cfa-miR-103cfa-miR-106acfa-miR-106bcfa-miR-10bcfa-miR-122
Bcfa-miR-124cfa-miR-125acfa-miR-125bcfa-miR-126cfa-miR-130acfa-miR-133acfa-miR-133bcfa-miR-137cfa-miR-141cfa-miR-143cfa-miR-145cfa-miR-146a
Ccfa-miR-146bcfa-miR-148acfa-miR-150cfa-miR-15acfa-miR-15bcfa-miR-16cfa-miR-17cfa-miR-181acfa-miR-181bcfa-miR-182cfa-miR-183cfa-miR-184
Dcfa-miR-18aCfa-miR-191Cfa-miR-192Cfa-miR-195Cfa-miR-196aCfa-miR-19aCfa-miR-200aCfa-miR-200bCfa-miR-200cCfa-miR-203Cfa-miR-204Cfa-miR-205
ECfa-miR-20acfa-miR-21cfa-miR-210cfa-miR-214cfa-miR-218cfa-miR-22cfa-miR-222cfa-miR-223cfa-miR-224cfa-miR-23acfa-miR-23bcfa-miR-24
Fcfa-miR-25cfa-miR-26acfa-miR-27acfa-miR-27bcfa-miR-29bcfa-miR-29ccfa-miR-30bcfa-miR-30ccfa-miR-30dcfa-miR-31cfa-miR-335cfa-miR-342
Gcfa-miR-34acfa-miR-34bcfa-miR-34ccfa-miR-375cfa-miR-378cfa-miR-451cfa-miR-499cfa-miR-7cfa-miR-9cfa-miR-92acfa-miR-93cfa-miR-96
Hcel-miR-39-3pcel-miR-39-3pSNORD61SNORD68SNORD72SNORD95SNORD96ARNU6-2miRTCmiRTCPPCPPC
Table 2. Forward and reverse primer sequence for quantitative real-time polymerase chain reaction amplification of mRNA for canine testis samples.
Table 2. Forward and reverse primer sequence for quantitative real-time polymerase chain reaction amplification of mRNA for canine testis samples.
GenePrimer Sequence (5′–3′)Product LengthAccession Number
CDKN1AF: CCTCGGAGGAGGTGCCAT187XM_038683340.1
R: CGTCTCGGTGACGAAGTCAA
EGFRF: TAGGATCAGGGCCCGCAG187XM_038423676.1
R: GCAACTTCCTGGATGGTCTTT
JUNF: CCTTCTACGACGATGCCCTC101XM_038666089.1
R: GTTCAGGGTCATGCTCTGCT
NOTCH1F: CAGTGCAATGAGGGACCAGT274XM_038438708.1
R: AGCATCCTCCACTCTCTGTCT
PIK3R1F: CACAACCTGCAAACATTGCC160XM_038659066.1
R: AGGTCCCATCGGCTGTATC
DNMT1F: CTCTACGGTGTGTGCAGTGT209XM_038428673.1
R: CAGGTGACCACGCTTACAGT
PTENF: CATCATCAAGGAGATCGTCAGCAG217NM_001003192.1
R: ATGTCTTTCAGCACACAGATTGTA
ESR1F: CACGGAGCTACACGCACAT74NM_001286958.2
R: GGCTTGTAGAAGTCAAGGGCT
TIMP3F: CCTCCAAGAACGAGTGCCTT161NM_001284439.1
R: GGGGTCTGTGGCATTGATGA
GAPDHF: AACATCATCCCTGCTTCCAC234NM_001003142.2
R: GACCACCTGGTCCTCAGTGT
CDKN1A, cyclin-dependent kinase inhibitor 1A; EGFR, epidermal growth factor receptor; JUN, jun proto-oncogene, AP-1 transcription factor subunit; NOTCH1, notch receptor 1; DNMT1, DNA methyltransferase 1; PIK3R1, phosphoinositide-3-kinase regulatory subunit 1; PTEN, phosphatase and tensin homolog; ESR1, estrogen receptor 1; TIMP3, tissue inhibitor of metalloproteinases 3; GADPH, glyceraldehyde-3-phosphate dehydrogenase.
Table 3. Differentially expressed microRNAs sequence for dog and human.
Table 3. Differentially expressed microRNAs sequence for dog and human.
miRNA IDSequence
cfa-miR-34bAGGCAGUGUAAUUAGCUGAUUG
hsa-miR-34bUAGGCAGUGUCAUUAGCUGAUUG
cfa-miR-34cAGGCAGUGUAGUUAGCUGAUUGC
hsa-miR-34cAGGCAGUGUAGUUAGCUGAUUGC
cfa-miR-146bUGAGAACUGAAUUCCAUAGGCU
hsa-miR-146bUGAGAACUGAAUUCCAUAGGCUG
cfa-miR-29bUAGCACCAUUUGAAAUCAGUGUU
hsa-miR-29bUAGCACCAUUUGAAAUCAGUGUU
cfa-miR-122UGGAGUGUGACAAUGGUGUUUG
hsa-miR-122UGGAGUGUGACAAUGGUGUUUG
cfa-miR-29cUAGCACCAUUUGAAAUCGGUUA
hsa-miR-29cAUCUCUUACACAGGCUGACCGAUUUCUCCUGGUGUUCAGAGUCUGUUUUUGUCUAGCACCAUUUGAAAUCGGUUAUGAUGUAGGGGGA
cfa-miR-375 GCCCCGCGACGAGCCCCUCGCACAAACCGGACCUGAGCGUUUUGUUCGUUCGGCUCGCGUGAGGCAGGGG
hsa-miR-375GCGACGAGCCCCUCGCACAAACC
cfa-miR-9UCUUUGGUUAUCUAGCUGUAUGA
hsa-miR-9UCUUUGGUUAUCUAGCUGUAUGA
cfa-miR-7UGGAAGACUAGUGAUUUUGUUGU
hsa-miR-7UGGAAGACUAGUGAUUUUGUUGUU
cfa-miR-18aUAAGGUGCAUCUAGUGCAGAUA
hsa-miR-18aUAAGGUGCAUCUAGUGCAGAUAG
cfa-miR-335UCAAGAGCAAUAACGAAAAAUGU
hsa-miR-335UCAAGAGCAAUAACGAAAAAUGU
cfa-miR-15aUAGCAGCACAUAAUGGUUUGU
hsa-miR-15aUAGCAGCACAUAAUGGUUUGUG
cfa-miR-200bCAUCUUACUGGGCAGCAUUGGA
hsa-miR-200bCAUCUUACUGGGCAGCAUUGGA
cfa-miR-22AAGCUGCCAGUUGAAGAACUGU
hsa-miR-22AAGCUGCCAGUUGAAGAACUGU
cfa-miR-19aUGUGCAAAUCUAUGCAAAACUGA
hsa-miR-19aUGUGCAAAUCUAUGCAAAACUGA
cfa-miR-15bUAGCAGCACAUCAUGGUUUA
hsa-miR-15bUAGCAGCACAUCAUGGUUUACA
cfa-miR-16UAGCAGCACGUAAAUAUUGGCG
hsa-miR-16UAGCAGCACGUAAAUAUUGGCG
cfa-miR-192CUGACCUAUGAAUUGACAGCC
hsa-miR-192CUGACCUAUGAAUUGACAGCC
cfa-miR-106aAAAGUGCUUACAGUGCAGGUAG
hsa-miR-106aAAAAGUGCUUACAGUGCAGGUAG
cfa-miR-96UUUGGCACUAGCACAUUUUUGCU
hsa-miR-96UUUGGCACUAGCACAUUUUUGCU
cfa-miR-210ACUGUGCGUGUGACAGCGGCUGA
hsa-miR-210CUGUGCGUGUGACAGCGGCUGA
cfa-miR-133bUUUGGUCCCCUUCAACCAGCUA
hsa-miR-133bUUUGGUCCCCUUCAACCAGCUA
cfa-miR-378ACUGGACUUGGAGUCAGAAGGC
hsa-miR-378ACUGGACUUGGAGUCAGAAGGC
cfa-miR-200aCAUCUUACCGGACAGUGCUGGA
hsa-miR-200aCAUCUUACCGGACAGUGCUGGA
cfa-miR-141AACACUGUCUGGUAAAGAUGG
hsa-miR-141UAACACUGUCUGGUAAAGAUGG
cfa-miR-124UAAGGCACGCGGUGAAUGCCA
hsa-miR-124UAAGGCACGCGGUGAAUGCCAA
cfa-miR-143UGAGAUGAAGCACUGUAGCUC
hsa-miR-143UGAGAUGAAGCACUGUAGCUC
cfa-miR-191CAACGGAAUCCCAAAAGCAGCU
hsa-miR-191CAACGGAAUCCCAAAAGCAGCUG
cfa-miR-1UGGAAUGUAAAGAAGUAUGUA
hsa-miR-1UGGAAUGUAAAGAAGUAUGUAU
cfa-miR-20aUAAAGUGCUUAUAGUGCAGGUAG
hsa-miR-20aUAAAGUGCUUAUAGUGCAGGUAG
cfa-miR-145GUCCAGUUUUCCCAGGAAUCCCU
hsa-miR-145GUCCAGUUUUCCCAGGAAUCCCU
cfa-miR-101UACAGUACUGUGAUAACUGA
hsa-miR-101UACAGUACUGUGAUAACUGAA
cfa-miR-137UUAUUGCUUAAGAAUACGCGU
hsa-miR-137UUAUUGCUUAAGAAUACGCGUAG
cfa-miR-203GUGAAAUGUUUAGGACCACUAG
hsa-miR-203GUGAAAUGUUUAGGACCACUAG
cfa-miR-184UGGACGGAGAACUGAUAAGGGU
hsa-miR-184UGGACGGAGAACUGAUAAGGGU
cfa-miR-214ACAGCAGGCACAGACAGGCAGU
hsa-miR-214ACAGCAGGCACAGACAGGCAGU
cfa-miR-130aCAGUGCAAUGUUAAAAGGGCAU
hsa-miR-130aCAGUGCAAUGUUAAAAGGGCAU
cfa-miR-181bAACAUUCAUUGCUGUCGGUG
hsa-miR-181bAACAUUCAUUGCUGUCGGUGGGU
cfa-miR-148aUCAGUGCACUACAGAACUUUGU
hsa-miR-148aUCAGUGCACUACAGAACUUUGU
cfa-miR-196aUAGGUAGUUUCAUGUUGUUGGG
hsa-miR-196aUAGGUAGUUUCAUGUUGUUGGG
cfa-miR-125aUCCCUGAGACCCUUUAACCUGU
hsa-miR-125aUCCCUGAGACCCUUUAACCUGUGA
cfa-miR-224CAAGUCACUAGUGGUUCCGUUU
hsa-miR-224UCAAGUCACUAGUGGUUCCGUUUAG
cfa-miR-342UCUCACACAGAAAUCGCACCCGU
hsa-miR-342UCUCACACAGAAAUCGCACCCGU
cfa-miR-181aAACAUUCAACGCUGUCGGUGAG
hsa-miR-181aAACAUUCAACGCUGUCGGUGAGU
Letter in bold denotes differences in sequences. Nucleotide sequences of differentially expressed canine and human miRNAs were retrieved from miRBase, (www.mirbase.org) (accessed 4 March 2022).
Table 4. (A) Upregulated top 30 hub genes, and their roles, human tissue expression, and protein–protein interactions (up to 6 closely related genes); (B) Downregulated top 30 hub genes, and their roles, human tissue expression and protein–protein interactions (up to 6 closely related genes).
Table 4. (A) Upregulated top 30 hub genes, and their roles, human tissue expression, and protein–protein interactions (up to 6 closely related genes); (B) Downregulated top 30 hub genes, and their roles, human tissue expression and protein–protein interactions (up to 6 closely related genes).
Top Hub GenesRolesTissue ExpressionsPPIs
(A)
PTENRegulation of cell division and growth; Sertoli cell and spermatogonial stem cellstestis, prostateCSNK2A1, NEDD4, PDGFRB, SLC9A3R1, SPOP, USP7
CCNA2Regulation of cell cycletestis, prostateCDC6, CDK2, CDKN1A, CDKN1B, E2F1, SKP2,
CCNE1Cell cycle regulation and progression; cell proliferationtestis, prostateCDK2, CDC25A, CDKN1A, CDKN1B, FBXW7, SKP2,
KRASrelays signals from outside the cell to the cell’s nucleustestis, prostateARAF, CALM1, PIK3CG. RAF1, RALGDS. RASSF5
VEGFAendothelial cell proliferation, promotion of cell migration, inhibition of apoptosistestis, prostateFLT1, KDR, DLL4, HIF1A, MYOD1, STAT3, RUNX2, MYC,
CDK4Regulation of cell cycle progression, G1 phasetestis, prostateCCND1, CCND2, CCND3, CDKN1A, CDNK1B, RB1
CDH1Regulation of cell–cell adhesions, mobility and proliferation; spermatogenic stem cells and type A spermatogonia testis, prostateCBLL1, CDC27, CTNNA1, CTNNB1, CTNND1, EGFR
MMP2Regulate space between cells, cell architecture.testis, prostateCCL7, COL1A1, COL5A1, TIMP2, TIMP3, TIMP4
CDK6Regulation of cell cycle progression, G1 phasetestis, prostateCCND1, CCND2, CDKN2A, CDKN2B, CDKN2C, RB1
ESR1maintenance of gluconeogenesis and lipid metabolism; regulate cell proliferation; growth sexual developmenttestis, prostateEP300, NCOA1, NCOA2, NR2F1, CREBBP, TRIM24,
MYCRegulates cell cycle, and proliferation and apoptosis testis, prostateBRCA1, FBXW7, MAX, RAF1, RUVBL1, SMARCA4
FGFR1Cell proliferation, differentiation, survival and migrationtestis, prostateFGF1, FRS2, GRB14, NCAM1, NEDD4, PLCG1,
PIK3R1Cell proliferation and survivaltestis, prostateERBB3, GAB1, GRB2, IRS1, KHDRBS1, PIK3CA
METCell growth and survivaltestis, prostateCBL, EGFR, GAB1, GRB2, HGF, PLXNB1, SRC
MCL1Regulates cell apoptosistestis, prostateBAD, BAX, BCL2L11, BIK, BMF, TPT1
RELARegulates all types of cellular processes, including cellular metabolism, chemotaxistestis, prostateCREBBP, HDAC1, NFKB1, NFKB2, NFKBIA, NR3C1
CDKN1ARegulates cell cycle progression at G1-S phasetestis, prostateCCND1, CDK2, CDK4, GADD45G, PCNA, TSG101
EGFRDirects the behavior of epithelial cells; regulates cell migrationtestis, prostateEGF, GRB2, PTPN1, SHC1, SOS1, SRC
KDRPromotes proliferation, survival, migration and differentiation of endothelial cellstestis, prostateCDH5, SHC1, SHC2, SRC, VEGFA, VEGFC
NOTCH1cellular fate determination, cell proliferation, cell differentiation and cellular apoptosistestis, prostateDTX1, FBXW7, JAG1, PSEN1, RBPJ, SMAD3
CXCL8protein coding gene attracts neutrophils, basophils, and T-cellstestis, prostateACKR1, CCL5, CXCR2, RELA, SDC1, TNFAIP6
JAK2protein coding gene regulates cell growthtestis, prostateEPOR, PTPN1, IRS3, PTPN11, SH2B1, SOCS1, STAT5B
EZH2Regulates cell fate determinationtestis, prostateDNMT1, EED, HDAC1, RBBP4, SUZ12, VAV1
MYCNRegulates cell growth and division and apoptosistestis, prostateAURKA, EZH2, FBXW7, MAX, SP1, ZBTB17
JUNProtein coding gene regulates cell proliferation and apoptosistestis, prostateATF3, FOS, FOSL1, FOSL2, JDP2, MAPK8
BCL2L11Regulates anti- and pro-apoptic regulatorstestis, prostateBCL2, BCL2A1, BCL2L1, BCL2L2, DYNLL1, MCL1
FOXO1Protects cell from oxidative stress; regulates cell proliferationtestis, prostateAKT1, AR, CREBBP, ESR1, SIRT1, YWHAZ,
CCND1Regulates cell cycle progression at G1-S phasetestis, prostateAR, CDK2, CDK4, CDK6, CDKN1A, CDKN1B
ATMRegulates cell proliferationtestis, prostateABL1, AP1B1, BRCA1, FANCD2, TRFF1, TP53,
(B)
LIN28Posttranscriptional regulator of genes involved in developmental timing and self-renewal in stem cellstestis, prostateDHX36, IGF2BP3, LARP1, L1TD1, ZCCHC11
NLKNegative regulator in cell proliferationtestis, prostateFAM222A, LEF1, MYB, PKM, MAP3K7, SMAD4
GATA6Regulation of cellular differentiation and organogenesistestis, prostateCDK9, EP300, EGLN3, KLF2, NKX2-1, EP300,
KRT5Regulation of cell structural framework testis, prostateALOX12, EGFR, KRT14, LARP7, PKP2, SUMO2
CDX2Regulation of cell growth and differentiationtestis, prostateCREBBP, EP300, GSK3B, HNF1A, PAX6, RELA
DNMT1Regulates DNA methylation; maintain a transcriptionally repressive state of genes in undifferentiated stem cellstestis, prostateDNMT3B, HDAC1, PCNA, RB1, UHRF1, USP7
TIMP3regulation of cell growth, cell death, angiogenesis, and invasiontestis, prostateADAM17, AGTR2, ASGR2, IFI30, MMP2, MMP3
CDKN1BOppose cell cycle progression; regulators of cell proliferation testis, prostateCCND1, CCND3, CCND2, CDK2, CDK4, STMN1
NCOA2Regulates cell growth, development, and homeostasistestis, prostateAR, ESR1, NR3C1, PPARG, RXRA, VDR
ESR1maintenance of gluconeogenesis and lipid metabolism; regulate cell proliferation; growth sexual developmenttestis, prostateEP300, NCOA1, NCOA2, NR2F1, CREBBP, TRIM24,
TP53regulates cell division by keeping cells from proliferating in an uncontrolled waytestis, prostateBCL2L1, DAXX, HSPA9, HMGB1, MDM2, TOPORS
HOXA5Regulates morphogenesis and differentiationtestis, prostateELAVL1, FOXO1, FOXA2, MEIS1, PRMT6, TWIST1
BCL2Regulation of apoptosistestis, prostateBAD, BAX, BBC3, BCL2L11, BID, BIK
AKT2Regulation of cell proliferation, growth and survivaltestis, prostateAPPL1, CHUK, HSP90AA1, SH3RF1, TTC3, TCL1A
TCL1ACo-activator of AKT kinases Enhances cell proliferation, stabilizes mitochondrial membrane potential and promotes cell survivaltestis, prostateAKT1, AKT2, EP300, FOS, JUN, JUNB
KLF4Prevents differentiation of stem cellsovary, uterus, placentaCREBBP, CTBP1, EP300, HDAC2, KLF6, SP1
SOCS3maintenance of cell shape and integrityovary, uterus, placentaEGFR, IL6ST, JAK2, LEPR, PTPN11
IKBKBRegulation of cell growth and apoptosis testis, prostateCDC37, CHUK, IKBKG, NFKB1, NFKB1A, TRAF2
PTENRegulation of cell division and growth; sertoli cell and spermatogonial stem cellstestis, prostateCSNK2A1, NEDD4, PDGFRB, SLC9A3R1, SPOP, USP7
TP63Regulation of epithelial morphogenesis, and adult stem/progenitor celltestis, prostateDAXX, HNRNPAB, HIPK2, ITCH, TP53, TP73
ERBB2Regulation of cell membrane; regulates cell proliferation and anti-apoptosistestis, prostateEGFR, ERBB3, ERBB4, ERBIN, GRB2, PIK3R1
ABL1Regualtes cell growth, survival, cell adhesion, cell migration; cytoskeleton remodelingtestis, prostateCRK, ABI1, DOK1, NCK1, RAD51, RIN1
PIK3CBcell adhesion; immune (PIK3) and inflammatory responsestestis, prostatePIK3R1, PIK3R2, PIK3R3, HCK, IRS1
CDCK6prevents cell proliferation and regulates negatively cell differentiationtestis, prostateCDKN2A, CDKN2B, RB1, CDKN2D, CCND1, CCND3,
E2F6regulation of DNA replication, DNA repair, mitosis, and cell fate.testis, prostateKDM5C, PCGF6, RING1, RYBP, TFDP1, TFDP2
ELAVL1Anti-proliferation of cell, negatively affects meiotic divisiontestis, prostateAGO2, CHEK2, HNRNPA1, IGF2BP1, RBM3, TNPO2
HOXA11Regulates cell proliferation and differentiationtestis, prostateFOXO1, HDAC1, HDAC2, MEIS1, PGBD3, YY1
DNMT3BRegulation of DNA methylationtestis, prostateDNMT1, DNMT3A, EED, EZH2, HDAC1, UBE2I
Table 5. (A). Upregulated miRNAs and associated hub genes. (B). Downregulated miRNAs and associated hub genes.
Table 5. (A). Upregulated miRNAs and associated hub genes. (B). Downregulated miRNAs and associated hub genes.
miRNAHub Gene
(A)
cfa-miR-1MET
cfa-miR-7EGFR
cfa-miR-9CDH1, FOXO1
cfa-miR-15aCCND1, JUN, MCL1, VEGFA
cfa-miR-15bCCNE1
cfa-miR-16CCND1, CCNE1, FGFR1, JUN, MCL1, VEGFA
cfa-miR-18aESR1
cfa-miR-19aCCND1, BCL2L11, ESR1, PTEN
cfa-miR-20aCCND1, VEGFA
cfa-miR-22ESR1, PTEN
cfa-miR-29bMCL1, MMP2, PIK3R1
cfa-miR-29cPIK3R1
cfa-miR-34bMYC, NOTCH1
cfa-miR-34cNOTCH1
cfa-miR-96FOXO1
cfa-miR-101ATM, EZH2, MCL1, MYCN
cfa-miR-106aCDKN1A, RB1, VEGFA
cfa-miR-124CDK4, CDK6, EZH2, RELA
cfa-miR-143KRAS
cfa-miR-145CCNA2, MYC
cfa-miR-192RB1
cfa-miR-375JAK2
cfa-miR-378VEGFA
(B)
cfa-miR-125a-5pERBB2, ERBB3, LIN28, TP53
cfa-miR-130aCSF1, HOXA4
cfa-miR-137CDK6, E2F6, KLF4, NCOA2
cfa-miR-148aDNMT1, DNMT3B
cfa-miR-181aBCL2, CDKN1B, CDX2, ELAVL1, ESR1, GATA6, HOXA11, NLK
cfa-miR-181bCDX2, ESR1, GATA6, NLK, TCL1A, TIMP3
cfa-miR-184AKT4
cfa-miR-196aANXA1, IKBKB, KRT5
cfa-miR-203ABL1, SOCS3, TP63
cfa-miR-214PTEN
cfa-miR-342DNMT1
Table 6. KEGG pathways associated with the top 30 upregulated and down-regulated hub genes.
Table 6. KEGG pathways associated with the top 30 upregulated and down-regulated hub genes.
Upregulated Hub Genes Associated KEGG PathwayDown Regulated Hub Genes Associated KEGG Pathway
ErbB signaling pathwayErbB signaling pathway
Cell cyclep53 signaling pathway
p53 signaling pathwayNeurotrophin signaling pathway
MitophagyProlactin signaling pathway
PI3K-Akt signaling pathwayAdipocytokine signaling pathway
Apoptosis
Longevity regulating pathway
Cellular senescence
VEGF signaling pathway
Adherens junction
JAK-STAT signaling pathway
Th1 and Th2 cell differentiation
T cell receptor signaling pathway
B cell receptor signaling pathway
GnRH signaling pathway
Estrogen signaling pathway
Prolactin signaling pathway
Thyroid hormone signaling pathway
Relaxin signaling pathway
AGE-RAGE signaling pathway in diabetic complications
Cancer
Table 7. Relative expressions of miRNA and associated hub gene mRNA in mature dog testis.
Table 7. Relative expressions of miRNA and associated hub gene mRNA in mature dog testis.
mRNAmiRNAmRNA Relative ExpressionmiRNA Relative Expression
CDKN1Acfa-miR-106a 3.12.63
EGFRcfa-miR-73.74.35
JUNcfa-miR-15a 5.23.43
JUNcfa-miR-165.22.75
NOTCH1cfa-miR-34b6.11175.42
NOTCH1cfa-miR-34c6.1662.79
PIK3R1cfa-miR-29b323.59
DNMT1cfa-miR-148a0.460.32
PTENcfa-miR-2140.340.2
ESR1cfa-miR-181b0.430.29
TIMP3cfa-miR-181b0.40.29
mRNA and miRNA expression relative to immature dog testis (p ≤ 0.05).
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Kasimanickam, V.R.; Kasimanickam, R.K. In Silico Analysis of miRNA-Mediated Genes in the Regulation of Dog Testes Development from Immature to Adult Form. Animals 2023, 13, 1520. https://doi.org/10.3390/ani13091520

AMA Style

Kasimanickam VR, Kasimanickam RK. In Silico Analysis of miRNA-Mediated Genes in the Regulation of Dog Testes Development from Immature to Adult Form. Animals. 2023; 13(9):1520. https://doi.org/10.3390/ani13091520

Chicago/Turabian Style

Kasimanickam, Vanmathy R., and Ramanathan K. Kasimanickam. 2023. "In Silico Analysis of miRNA-Mediated Genes in the Regulation of Dog Testes Development from Immature to Adult Form" Animals 13, no. 9: 1520. https://doi.org/10.3390/ani13091520

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