Introduction

MicroRNAs (miRNAs) are the most recently discovered regulatory molecules that hold promise to be used as biomarkers. These are small (17–22 nucleotides) non-coding RNAs that are highly conserved across species1. A single miRNA is capable of targeting several genes, so the study of miRNAs provides an enhanced perspective of gene regulatory mechanisms, than that obtained from mRNAs or single genes. The role of miRNAs has been implicated in disease, growth and metabolism of skeletal muscle2. Their role in muscle cell proliferation and development has been well established3,4. Several reports are available describing the miRNA expression in skeletal muscles of cattle5,6, pig7, goat8,9 and sheep10,11. Such studies have contributed to a better understanding of the regulatory role of miRNAs in muscling traits. The hyper-muscling in Texel sheep is a result of altered sequence of target site for miR-1 and miR-206, which causes inhibition of the myostatin gene12. Polymorphisms have been identified in muscle specific miRNAs (myomirs) that are associated with muscle and meat quality traits in pigs13. MicroRNAs have also been associated with intramuscular adipocyte differentiation in cattle, buffalo, sheep and poultry14,15,16,17. The importance of miRNAs in regulating meat tenderness and intra-muscular fat in beef has been well elucidated18,19,20,21.

Since muscles form meat, it would be beneficial to know the molecular drivers that regulate their development and metabolism. Several meat type sheep breeds are found in India. Well known among them are Madgyal, Deccani, Bandur (Mandya), Hassan and Kilakarsal22. Bandur sheep are distributed in Karnataka and are known for their favourable organoleptic meat quality23. However, another sheep population (local sheep), found in the same area, are not preferred by consumers, even though the fodder, management and geographical conditions are same for both. Earlier investigations have established that the skeletal muscles of Bandur sheep have low shear force values23. Significant differences in back fat thickness, colour and muscle tenderness have also been reported between Bandur and local sheep24. Although the mRNA of skeletal muscles of Bandur and local sheep have been profiled24, no information is available on the differential expression of miRNAs regulating their expression. Therefore, the study was taken up with the aim to elucidate the regulatory miRNAs in Bandur and local sheep populations with diverse carcass and muscle traits.

Results

Summary of miRNA sequencing data

Each library from the skeletal muscles of Bandur and local sheep generated 18 to 30 million raw reads with 46–48% GC content (Table 1). The raw sequence data have been submitted to the NCBI Sequence Read Archive with Accessions SRR6346733–SRR6346740. Since only 106 precursors and 153 mature miRNAs were available in miRBase at the time of submission of this manuscript, the reads were also mapped to Human (GRCH38), as well as Bovine (ARS-UCD 1.2) reference assemblies. Mapping rate was 84% and 78% for human and bovine, respectively. A total of 400 known miRNAs were identified across all samples, of which 67, 320 and 13 were from the human, bovine and ovine database respectively. In Bandur sheep samples, 499 novel miRNA could be identified. More than 30% of the miRNAs in Bandur and local sheep had an expression of ≥ 1000 RPKM. Myomirs or miRNAs specific to skeletal muscles identified in our data included oar-miR-1, oar-miR-133b, oar-miR-206 and oar-miR-486.

Table 1 MicroRNA data statistics of skeletal muscles of Local and Bandur sheep.
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Differentially expressed miRNAs

Of the 400 known miRNAs in our study, 100 were found to be significantly differentially expressed (padj ≤ 0.05). Out of these, 49 were up-regulated and 51 were down-regulated in Bandur sheep. Some of the up-regulated miRNAs included oar-miR-185, oar-miR-107, oar-let-7d, oar-let-7b and oar-let-7e while oar-miR-10b, oar-miR-143, oar-miR-30, oar-miR-10a and oar-miR-23a were down-regulated in Bandur. The four myomirs detected in our data were found to be differentially expressed. Myomirs, oar-miR-1 and oar-miR-206 were over-expressed while oar-miR-133b and oar-miR-486 showed lower expression in Bandur sheep. Table 2 lists the miRNAs differentially expressed in Bandur that are known to be associated with muscle growth and development in sheep11.

Table 2 Differentially expressed miRNAs (padj ≤ 0.05) in Bandur related to sheep muscle growth and development.
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Prediction of target genes and pathways

A total of 11,062 target genes were identified for both up and down regulated miRNAs. The list of genes was used as input for over-representation analysis using ConsensusPathDB25,26. More emphasis was laid on GO terms associated with muscle biology and /meat traits. The most relevant GO terms for biological process included transcription factor binding, ubiquitin-like protein transferase activity, protein kinase activity, phospholipid binding etc. The enriched cellular components were cytoskeletal part, endoplasmic reticulum part, peptidase complex, protein acetyl transferase complex, proteasome complex, ribosome, ubiquitin-protein transferase regulator activity etc. Significant molecular functions associated with muscle traits were hydrolase activity, protein dimerization activity, cytoskeletal protein binding, kinase regulator activity, ubiquitin-like protein transferase activity, transcription factor binding etc. (Fig. 1).

Figure 1
figure 1

Top 10 gene ontology terms for biological process (BP), cellular component (CC) and molecular function (MF) associated with muscle traits in Indian sheep.

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The predicted target genes were used to identify biological pathways using pathway-based sets (p ≤ 0.01) incorporated in ConsensusPathDB25,26. The top 25 canonical pathways are listed in Table S1. The differentially expressed target genes were associated with metabolism of proteins, lipids, RNA, post translational protein modification, EGFR1, Signaling by Rho GTPases, Signaling by Receptor Tyrosine Kinases, miR-targeted genes in muscle cell, PI3K-Akt signaling pathway, Cellular responses to stress etc.

All the up-regulated miRNAs in Bandur sheep were used for gene target prediction and genes associated with tenderness/meat quality (identified from published literature) were filtered from the dataset. The genes list was then compared with our previous data on mRNA of Bandur sheep24 and only those genes that were differentially expressed were selected. A total of 32 miRNAs were identified as potential candidates for regulating meat tenderness (Table S2). On comparing the target genes for these miRNAs with previous data on mRNA24, it was observed that HSPA8 was a common target gene for 9 miRNAs while CASP3 and CAPN15 were targets of 8 miRNAs each.

miRNAs with log2 fold change ≥ ( ±) 3.0

To underscore the most pertinent biological functions, all miRNAs with a fold change (FC) of ≥ ( ±) 3.0 were subjected to further analysis. A total of 45 miRNAs exhibited a log2 FC of ≥ ( ±) 3.0 (Table S3). These miRNAs belonged to the let-7, miRmiR-148 and miRmiR-33 families. The functional relevance of these miRNAs was determined using TAM 2.027. The top 25 functional categories (padj ≤ 0.05, FDR ≤ 0.05) are depicted in Fig. 2. The enriched functional categories were cell proliferation, epithelial to mesenchymal transition, apoptosis, lipid metabolism, adipocyte differentiation, glucose metabolism, besides others.

Figure 2
figure 2

Top 25 functional categories for predicted target genes of differentially expressed miRNAs (log2 fold change ≥ ( ±) 3.0) using TAM 2.027.

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Network analysis

The differentially expressed miRNAs (≥ 3.0 log2 FC) were used for construction of interaction network for identification of important genes and transcription factors. The network consisted of 1044 nodes and each miRNA having more than 5 interactions (Fig. 3). Important genes identified in the network were ANKRD49, BCL2L1, BTG2, DDX6, FASN, FOS, HSPA8, KCTD10, PPAP2B, SLC12A5, SLC1A4, SLC13A4 and SLC25A19. A sub-network was further visualized to ascertain the interactions between miRNAs with ≥ 10 degrees, having 46 nodes and 51 edges. (Fig. 4). MicroRNAs miR-21, miR-155, miR-143, miR-221, miR-23a, miR-29a, miR-122, miR-424, miR-29c, let-7b, miR-27b, miR-15a and let-7c were observed to be highly connected. The significant target genes thus detected included HSPA8, FOS, ACSL5, BTG2 and PPAP2B. Another network based on transcription factors (human) as targets of these 13 highly connected miRNAs is shown in Fig. 5. Major transcription factors associated with these miRNAs were NFKB1, NFKB2, FOS, JUN, MYB, MYOCD, MYC, TGFB1, PPARG, BCL2L2, DDX5, DDX6.

Figure 3
figure 3

MicroRNA—target gene interaction network of differentially expressed miRNA (log2 FC ≥ ( ±) 3.0) constructed using miRNet.

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Figure 4
figure 4

MicroRNA to target gene sub-network of differentially expressed miRNAs with more than 10 interactions created using miRNet.

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Figure 5
figure 5

MicroRNA-transcription factors network of differentially expressed miRNAs with more than 10 interactions created using miRNet.

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Validation by quantitative real time PCR (qRT-PCR)

Quantitative real time PCR was performed for validating the expression of some randomly selected differentially expressed miRNAs. The analysis revealed that the expression pattern (up-regulated or down-regulated) of miR-1, miR-100, miR-133b, miR-185, miR-206, miR-214, miR-378, miR-495-5p, miR-210, miR-432, miR-107 and let-7b was comparable by both RNA sequencing and qRT-PCR (Fig. 6).

Figure 6
figure 6

Validation of sequencing data by comparing log2 fold change between RNAseq and qRT-PCR data, for selected miRNAs across Bandur and local sheep. qRT-PCR data was normalized using 5S-rRNA and U6 genes.

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Discussion

Muscle fibres, intramuscular fat, nutrition, post mortem processing along with genetics play an important role in determining the quality of meat. Several genes have been reported to be associated with meat tenderness28, intramuscular fat29 and post mortem proteolysis30. The role of regulatory elements influencing the gene expression is gaining emphasis in recent times. MicroRNAs are one such class of regulatory molecules that post-transcriptionally affect the expression of genes. Knowledge of miRNAs in skeletal muscles of various livestock species provides the possibility of identifying key regulators of muscle traits that can be used as biomarkers21,31. Several studies have identified and profiled miRNAs in the skeletal muscles of sheep11,12. However, there is dearth of information on molecular regulators for meat type sheep in India. This study investigated the differential expression of miRNAs in Indian sheep with contrasting carcass and muscling traits24. MicroRNAs most abundantly expressed in Bandur and local sheep included miR-206, let-7b and miR-1 (> 50,000 RPKM). MiR-206 and miR-1 are important myomiRs known to target several genes influencing skeletal muscle development and differentiation3. Recent studies have expanded our understanding of the role of miR-1 and miR-206 in muscle development and disease32. Some of the genes regulated by miR-1are HDAC4 and YY1 that are directly involved in muscle development33. Moreover, miR-1 and miR-206 have been reported to be under transcription repression by YY1. They are involved in inhibition of expression of myostatin which leads to muscle hypertrophy in Texel sheep12. Both miR-1 and miR-206 were observed to be highly expressed in caprine skeletal muscles9. Although let-7 family of miRNAs is not specific to muscle tissue, it is highly conserved across species and mainly promotes differentiation during the developmental process34,35. In sheep, eight types of let-7 family genes have been reported34. Let-7b is known to mediate skeletal muscle growth in chicken36. Let-7 family was also observed to be highly expressed in lean pigs37. However, the exact role of let-7 family in muscle development is still not understood.

Among the up-regulated differentially expressed microRNAs, miR-185 along with miR-107 affects cell cycle regulation38. MiR-185 has also been implicated in regulating lipid metabolism and LDL uptake39. It has been reported that over expression of miR-107 inhibited bovine myoblasts differentiation and protected cells from apoptosis40. The down-regulated miR-486, in our study, is known to promote differentiation of myoblasts via PI3K/AKT signaling41 and has been reported to show higher expression during muscle differentiation42. However, it was also observed to be down-regulated in cattle43 and pig7. MiR-133a/b on the other hand promotes both proliferation and differentiation via MAPK1/MAPK3 signaling44. It also affects oxidative stress control and cell fate regulation4, while miR-10 is involved in protein metabolism45. Our results indicate that the differentially expressed miRNAs in Bandur and local sheep were mainly implicated in myogenesis and lipid metabolism. These observations are consistent with our previous study on mRNAs of the same animals24. Even though the shear force estimates between the two sheep populations under investigation were significantly different, we did not find miR-182, miR-183 and miR-338 to be differentially expressed. In contrast, these miRNAs were observed to be differentially expressed in cattle with contrasting estimated breeding values for shear force21. A comparison of the two studies however, would not be feasible as the study was specific to beef tenderness, while ours is a preliminary investigation into the differentially expressed miRNA in sheep populations with different carcass and muscling characteristics.

Of the total target genes identified, we focused only on those that are potentially related to muscling traits. As a consequence, the functional terms associated with these target genes were protein and lipid metabolism as well as muscle development. All the target genes (11062) were used for pathway analysis and the enriched pathways were also suggestive of protein and lipid metabolism. Other pathways associated with meat quality traits included PI3K-Akt signaling, EGFR, cellular response to stress, JAK STAT and focal adhesion. The major pathways relevant to skeletal muscles are Ras- Erk-MAPK, PI3K-Akt and calcineurium46. Current advances in our understanding of muscle development reveal that PI3K-Akt is a major signaling cascade for muscle differentiation and hypertrophy47,48. This signaling pathway has also been reported to stabilize the hypoxia inducible factor (HIF-1α), suggestive of its role in post-mortem protein proteolysis49.The PI3K-Akt pathway along with PPAR signaling was also enriched in bovine50 and porcine51 adipose tissue. It was identified as an enriched cluster of down-regulated genes in Bandur sheep24. EGFR is another widely investigated pathway that regulates myogenesis52. Besides, the PI3K-Akt signaling can be activated by the EGFR (a tyrosine kinase receptor) during cell proliferation and survival53. Although the JAK-STAT pathway regulates several hormones and cytokines, it is also known to enhance hypertrophy in the skeletal muscles54. Moreover, it leads to increased uptake of glucose, lipolysis and fatty acid oxidation by activating AMPK, PI3K and IL6 pathways55. The key pathways known to be involved in muscle metabolism and development were observed to be enriched in our study. The enrichment of cellular response to stress and fatty acid metabolism pathways corroborate our previous results on mRNA expression in Bandur sheep24.

If we consider only those target genes that are associated with meat tenderness, we observed that the genes CAPN15, CASP3 and HSPA8, were targets of maximum number miRNAs. HSPA8 and CASP3 are involved in cellular stress response especially apoptosis56 while CAPN15 is known for its role in muscle protein degradation57. Both caspase and calpain belong to a family of cysteine proteases that are intricately involved in apoptotic and necrotic pathways. Apoptosis or programmed cell death is a complex process mediated by the intrinsic (mitochondrial) and extrinsic (cell death) pathways. Caspases or cysteine proteases are major mediators of apoptosis. CASP3 forms the link between the extrinsic and intrinsic pathways that brings about the morphological and biochemical changes in the cell in response to stress58. Although caspases have been extensively studied, the role calpain is still not well understood. However, calpains are important regulators of apoptosis having crosstalk with the caspase cascade59. HSPA8 belongs to the family of heat shock proteins 70 (HSP70) that is induced in response to oxidative stress. Up-regulation of HSP70 hinders the activity of caspase thereby, inhibiting apoptosis58. Oxidative stress has been recognized as a major factor affecting post mortem proteolysis which in turn impacts muscle protein quality and shelf‐life of meat60. In light of these observations, it is reasonable to infer that post mortem proteolysis may play a crucial role in determining the muscle quality in the investigated sheep.

The network analysis revealed miR-21, miR-155, miR-143, miR-221 and miR-23a as the nodal miRNAs, with multiple targets. All of these miRNAs identified by the network analysis are implicated in development, proliferation and/or differentiation of skeletal muscles61,62,63. Although most of these associations are known in the context of human diseases mainly cancer, not enough evidence is available in support of their role in muscling traits. MiR-21, up-regulated in Bandur sheep (log2 FC = 4) formed the focal point of the network with 42 interactions. It has been revealed that miR-21 targets TGFβ1 via the PI3K-Akt -mTOR signaling in development of skeletal muscle of pig64. It has been acknowledged as an oncomiR that represses a number of genes of the apoptotic pathway65. It was also identified as one of the hub miRNA related to feed efficiency in Nellore cattle43. The PI3K signaling regulates not only growth and proliferation but also angiogenesis, cell survival and apoptosis. Transcription factors NFKB1, NFKB2, TGFB266, MYC67 and BCL2L268 have also been associated with apoptosis and cell survival in the PI3K signaling cascade. Post mortem proteolysis is mainly governed by the physiological processes of cell survival and apoptosis that contribute to tenderization of muscle protein21,69. Although the PI3K signaling is integrated into several cellular pathways, the identification of nodal miRNA and transcription factors in our study further lend support to its relevance in apoptosis and cell survival.

Molecular factors that repress the oxidative stress leading to apoptosis may find potential application in improvement of meat quality in addition to muscular disease. The hub miRNAs identified in our study form putative regulatory candidates for future research on meat quality traits in Indian sheep. Our results provide insight into the biological pathways and regulatory molecules in skeletal muscles of sheep.

Materials and methods

Samples

Four rams of Bandur and four local sheep, in the two-tooth stage (12–19 months) were selected. The phenotypes, carcass measurements and muscle tenderness of the animals used in this study have been previously described24. The animals were slaughtered according to standard commercial ‘halal’ procedures. All ethical norms and guidelines were followed, with approval from Institutional Animal Ethics Committee, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana, India (F.No. NBAGR/IAEC/2017, dated 21.01.2017). Immediately after slaughter, the longissimus thoracis muscle was collected in RNALater solution.

Micro RNA sequencing

Total RNA was extracted using TRIzol method and purified using RNeasy kit (Qiagen). Four biological replicates from Bandur as well as local sheep, with RIN value ≥ 7.0 (Agilent Bioanalyzer) were used for library preparation. Sequencing libraries were generated by Illumina Trueseq small RNA Sample Prep kit using 1 µg of total RNA. The libraries were normalized to a concentration of 2 nM using Tris–HCl 10 mM, pH 8.5. All the samples were purified, indexed, diluted and sequenced on Illumina HiSeq 2000 platform.

Data analysis

FastQC (v 0.11.5)70 was used to assess the quality of the samples. Clean reads, after removal of adapters, were used to map the miRNA against the ovine genome assembly v4.0 (Oar_v4.0), available in NCBI), using miRNAkey71. miRDeep* software (v37.0.0) was used for identification of known and novel miRNAs in data72. Minimum free energy for novel miRNAs was calculated by using RNAfold tool (v2.4.3) from ViennaRNA package (v2.0)73,74. DESeq package (v1.28.0), which uses a negative binomial distribution, was used for differential analysis75. The gene expression differences between groups were tested using an exact test in this software. Expression levels of miRNA reads were normalized as reads per kilobase million (RPKM). Only those differentially expressed miRNA with padj ≤ 0.05 were used for further analysis.Target genes were identified using both human and cattle species in miRTarBase76. The functional and pathway categorization of the target genes was carried out using ConsensusPathDB25,26 and TAM 2.027. The software miRNet77,78 was used for network construction.

Validation by quantitative real time PCR (qRT-PCR)

Twelve random miRNAs from the list of differentially expressed miRNAs with p-value ≤ 0.05 were selected for qRT-PCR. Primer sequences were selected from literature or designed using sRNAPrimerDB software79 (Table S4). Stem loop PCR method was used for amplification80. Total RNA including miRNA was extracted from the skeletal muscle tissue of Bandur and Local sheep using TRIzol reagent as per the manufacturer’s instructions. The samples were purified and enriched using miRNeasy Micro Kit (Qiagen) to remove genomic DNA contamination. cDNA was synthesized from 250 ng purified RNA isolated from longissimus thoracis of local and Bandur sheep using Thermo Scientific RevertAid First Strand cDNA Synthesis Kit, as per manufacturer’s protocol. Gene amplification by qRT-PCR was performed in Roche RT system (2 step PCR). A 10 μl reaction mixture consisting of 25 ng of template, 0.3 μl of forward and reverse primers each (2 nmol/μl) and 5 μl of SYBR green mix (2x) was prepared. The amplification programme was 95 °C for 10 min, followed by 45 cycles of 95 °C for 10 s, 58 °C for 10 s and 72 °C for 10 s. A standard curve calculation by using four points of cDNA serial dilutions was used to determine the efficiency of reaction. All reactions were performed in triplicates. 5S-rRNA and U6 snRNA were used as internal control genes.

Normalization for all the miRNA was done using the geometric mean of both the reference genes and 2−ΔΔCt method was used for calculating the relative gene expression81.