Biochemistry & Molecular Biology Journal Open Access

  • ISSN: 2471-8084
  • Journal h-index: 14
  • Journal CiteScore: 2.55
  • Journal Impact Factor: 1.74
  • Average acceptance to publication time (5-7 days)
  • Average article processing time (30-45 days) Less than 5 volumes 30 days
    8 - 9 volumes 40 days
    10 and more volumes 45 days

Research Article - (2025) Volume 11, Issue 1

In silico Analysis of MicroRNA of (Mentha X Piperita) Peppermint
Saqib Ishaq1*, Jamshaid Khan2, Raheel Tahir2, Abdul Aziz1, Obaid Habib3, Muhammad Inam Ul Haq1, Karim Gul3, Yasir Ali4 and Rehan Naeem2
 
1Department of Computer Sciences and Bioinformatics, Khushal Khan Khattak University, Methawalah, Pakistan
2Department of Biotechnology and Genetic Engineering, Kohat University of Science and Technology (KUST), Kohat, Pakistan
3Department of Biotechnology, Abdul Wali Khan University Mardan (AWKUM), Mardan, Pakistan
4Department of Biomedical Sciences, The Chinese University of Hong Kong, Ma Liu Shui, Hong Kong
 
*Correspondence: Saqib Ishaq, Department of Computer Sciences and Bioinformatics, Khushal Khan Khattak University, Methawalah, Pakistan, Email:

Received: 19-Sep-2023, Manuscript No. IPBMBJ-23-17816; Editor assigned: 21-Sep-2023, Pre QC No. IPBMBJ-23-17816 (PQ); Reviewed: 04-Oct-2023, QC No. IPBMBJ-23-17816; Revised: 07-Jan-2025, Manuscript No. IPBMBJ-23-17816 (R); Published: 14-Jan-2025, DOI: 10.36648/2471-8084.11.1.48

Abstract

Mentha piperita, commonly known as peppermint, is a well-known medicinal plant with a range of therapeutic properties. In this study, we conducted an in-silico analysis of microRNAs and ESTs in Mentha piperita to gain insight into its genetic makeup. We obtained 29 EST sequences and 36 microRNAs from the NCBI database and analyzed them using various bioinformatics tools. Functional annotation of the microRNAs revealed that only 29% of the miRNAs met the criteria for AU content between 30% and 70%. Out of these, target genes were identified for only 9 sequences, which were annotated with basic roles in biological processes and molecular functions. Phylogenetic analysis confirmed the conservation of Mentha piperita with Arabidopsis thaliana. Additionally, we calculated E-values and energies for the ESTs and microRNAs, respectively. Our findings provide valuable insights into the genetic makeup of Mentha piperita and may aid in further understanding its therapeutic properties. Future research could involve the experimental validation of the predicted targets of the identified microRNAs and the characterization of the function of the ESTs.

Keywords

Mentha; EST sequence; Structural and functional annotation; Gene ontology; Phylogeny

Introduction

Mentha piperita L. (peppermint), belongs to the family Lamiaceae, one of the most significant industrial herbs with a variety of essentials oils. Mint is a member of the Lamiaceae family, which is the largest family of plants with 236 genera and 7000 species and genus Mentha, consist of 15 hybrids, cultivars, subspecies, varieties and 42 species [1]. Mentha piperita is generally called as peppermint is a perennial herb widely used by greater part of people globally in various forms like leaf, leaf extract oil and leaf water. Due to its rich flavor and fragrance peppermint has economic value both in the domestic and international market and an important export commodity that fetches good foreign revenue. The peppermint oil logs for various antispasmodic activities like antivomiting, carminativum, stomachic and antimicrobial properties. The main compounds such as menthol, menthone, and menthofuran which gives unique aroma [2]. In-silico refers to analysis which is carried out in a computer environment, rather than in the laboratory (in vitro). Plant micro RNA’s are small non-coding RNA’s that have a length of 21 to 24 nucleotides which have role in growth and in metabolic and defense progress. Mostly, miRNAs associate with the target mRNAs by 3′ UTR to curb its expression. It also interacts with gene promoters and 5′ UTR coding sequence; in addition under specific condition it activates gene expression. This miRNA can also be identified by the use of Expressed Sequence Tag (EST) and a Genome Survey Sequence (GSS). EST analysis has gained significance when compared with other approaches like conserved miRNAs and be capable of identifying without knowing the whole genome sequences. It offers straight confirmation for miRNA expression than from genomic sequence surveys without any much specified software. By this method several miRNAs are effectively recognized in diverse plant species. Many plant miRNAs are evolutionarily conserved from species to species. MiRNA precursors display high variability; their mature sequences display extensive sequence complementarity to their target mRNA sequences. MiRNAs play important roles in plant post transcriptional gene regulation by targeting mRNAs for cleavage or repressing translation [3]. MiRNAs are involved in plant development, signal transduction, protein degradation, response to environmental stress and pathogen invasion, and regulate their own biogenesis. MiRNAs regulate the expression of many important genes; a majority of these genes are transcriptional factors. Here we use homology base method meaning searching for micro RNA sequence which are involved in anti-oxidant. The specie we selected that is mentha peppermint.

Materials and Methods

Searching of EST’s in NCBI

In this study we collect total 1316 EST sequences of (Mentha X Piperita) Peppermint from National Center for Biotechnology Information NCBI. Furthermore, to screen all these 1316 EST using Mirbase online search tool with the following E-value 0.01 to 0.099 [4].

Identification of Structural and Functional Annotation

Structural annotation of these microRNA to identify their structure through online server Mfold, using Mfold to determine the best possible secondary structure and energies of these microRNA which uses energy minimization method, protein coding sequences were removed prior to prediction. Functional annotation is the main step for finding the function of obtained microRNA EST sequences [5]. Functional analysis can be done by different database here we Blast2GO database because this also give the graph along with the function of EST’s microRNA. In order to find function of the obtained EST’s sequences first you need to target the genes for the particular microRNA, because the function of microRNA is ultimately defining by the genes. For identifying the target gene for those microRNA PsRNA target software were used.

Phylogenetic Analysis

Evolutionary tree is constructed to find out relation among present sequences and their root sequences [6]. Phylogenetic tree also constructed to find out the ancestral relation among Arabidopsis thaliana and Mentha Peppermint specie. Phylogenetic tree uses a character based method called maximum likelihood that show the distance among texa. The tool that are used for the construction of phylogenetic tree is RxMI and MegaXtool, that uses the MI tree construction and its probability based approach and for construction of phylogenetic tree and evolutionary model [7].

Results

Total 1316 EST of Mentha piperita was retrieved (based on the basis of size), analyzed and annotated through the CAP3 assembly program. In the screening all the 1316 EST’s sequence only 29 miRNA sequence was retrieve [8]. After that all the 29 EST’s sequence only 36 miRNA were found meet the criteria of required E-value. We blast each EST’s sequence individually in mirbase and search for value. The result also shows and given number of A, G, C, U/T and A-T/U count are listed in Table 1.

S. no Accession Number Sequences E values
1 MIMAT0027646 >hsa-miR-6873-5p MIMAT0027646
CAGAGGGAAUACAGAGGGCAAU
0.099
2 MIMAT0015455 >bmo-miR-3270 MIMAT0015455
UGUCUUUUUCCUAAAACGAUUCA
0.036
3 MIMAT0009979 >hsa-miR-2054 MIMAT0009979
CUGUAAUAUAAAUUUAAUUUAUU
0.042
4 MIMAT0030650 >prd-miR-7912-5p MIMAT0030650
CAUUGCAUUUGGUUGUCCUUGGCU
0.080
5 MIMAT0024577 >bta-miR-574 MIMAT0024577
UGAGUGUGUGUGUGUGAGUGUGUG
0.034
6 MIMAT0017325 >mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG
0.050
7 MIMAT0004795 >hsa-miR-574-5p MIMAT0004795
UGAGUGUGUGUGUGUGAGUGUGU
0.089
8 MIMAT0005837 >mmu-miR-1187 MIMAT0005837
UAUGUGUGUGUGUAUGUGUGUAA
0.077
9 MIMAT0005854 >mmu-miR-467g MIMAT0005854
UAUACAUACACACACAUAUAU
0.093
10 MIMAT0022724 >hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU
0.073
11 MIMAT0021390 >rmi-miR-5318 MIMAT0021390
UUGUAUAACUGCAGAAGACUUUUCUCC
0.034
12 MIMAT0017613 >aly-miR831-5p MIMAT0017613
AGAAGAGGUACAAGGAGAUGAGA
0.080
13 MIMAT0032837 >cel-miR-8210-5p MIMAT0032837
UGCCUUCUUUCCUUGUGUCGCCGAC
0.054
14 MIMAT0032835 >cel-miR-8209-5p MIMAT0032835
AAAACGAAGAAAGAAGAAGAA
0.043
15 MIMAT0044920 >pab-miR11418 MIMAT0044920
ACCCACCGCCGCUGCCGCCGC
0.094

16

MIMAT0017325

>mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG

0.078

17

MIMAT0022724

>hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU

0.055

18

MIMAT0036467

>tch-miR-1277-5p MIMAT0036467
UAUAUAUAUAUAUGUACGUAU

0.081

19

MIMAT0032837

>cel-miR-8210-5p MIMAT0032837
UGCCUUCUUUCCUUGUGUCGCCGAC

0.054

20

MIMAT0004885

>mmu-miR-467c-5p MIMAT0004885
UAAGUGCGUGCAUGUAUAUGUG

0.097

21

MIMAT0009979

>hsa-miR-2054 MIMAT0009979
CUGUAAUAUAAAUUUAAUUUAUU

0.098

22

MIMAT0005837

>mmu-miR-1187 MIMAT0005837
UAUGUGUGUGUGUAUGUGUGUAA

0.097

23

MIMAT0043929

>lja-miR11146-3p MIMAT0043929
GCAACGACAUGUAUAGUUGGAGG

0.076

24

MIMAT0023986

>cgr-miR-598 MIMAT0023986
UACGUCAUCGUCGUCAUCGUUAUC

0.057

25

MIMAT0005837

>mmu-miR-1187 MIMAT0005837
UAUGUGUGUGUGUAUGUGUGUAA

0.097

26

MIMAT0022724

>hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU

0.082

27

MIMAT0036057

>chi-miR-211 MIMAT0036057
UUCCCUUUGUCAUCCUUUGCCC

0.060

28

MIMAT0000668

>mmu-miR-211-5p MIMAT0000668
UUCCCUUUGUCAUCCUUUGCCU

0.072

29

MIMAT0012223

>dps-miR-980-5p MIMAT0012223
AGUCUCUCACAUGGCUGGUCUAGC

0.097

30

MIMAT0022724

>hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU

0.070

31

MIMAT0017325

>mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG

0.019

32

MIMAT0017325

>mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG

0.050

33

MIMAT0024577

>bta-miR-574 MIMAT0024577
UGAGUGUGUGUGUGUGAGUGUGUG

0.074

34

MIMAT0034619

>eca-miR-9074 MIMAT0034619
UGACUAAUAGGAAAUUUUAAGUGAC

0.079

35

MIMAT0022724

>hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU

0.087

36

MIMAT0001322

>ath-miR414 MIMAT0001322
UCAUCUUCAUCAUCAUCGUCA

0.029

Table 1: Screening the ESTs sequence with lowest E-Value.

To find a novel /unique miRNA 1316 EST sequences were screened for identifying miRNAs of lowest E values. The criterion of lowest E value was between 0.01-0.099. mirbase is an online search engine used to get the micro RNA’s of our specie at the end of screening all the 1316 EST’s only 36 miRNAs were found that meets the criteria of required E value. We blast each EST sequence individually in mirbase and search for values that are of our interest in the transcript Table [9-11]. After getting the required E value we open its accession number and we have its structure and also an option of get sequence we click on it and copy mature RNA sequence and paste that sequence in the word file. The table given below shows the result of screening and also number of A, G, C, U/T, and A-T/U counts are listed in Table 2.

S. no MiRNA A Count G Count C Count U/T Count Total GC Count A-T/U Count
1 >hsa-miR-6873-5p MIMAT0027646
CAGAGGGAAUACAGAGGGCAAU
9 8 3 2 22 11 11
2 >bmo-miR-3270 MIMAT0015455
UGUCUUUUUCCUAAAACGAUUCA
2 2 5 10 23 7 16
3 >hsa-miR-2054 MIMAT0009979
CUGUAAUAUAAAUUUAAUUUAUU
9 1 1 12 23 2 21
4 >prd-miR-7912-5p MIMAT0030650
CAUUGCAUUUGGUUGUCCUUGGCU
2 6 5 11 24 11 13
5 >bta-miR-574 MIMAT0024577
UGAGUGUGUGUGUGUGAGUGUGUG
2 12 0 10 24 12 12
6 >mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG
0 10 0 10 20 10 10
7 >hsa-miR-574-5p MIMAT0004795
UGAGUGUGUGUGUGUGAGUGUGU
2 11 0 10 23 11 12
8 >mmu-miR-1187 MIMAT0005837
UAUGUGUGUGUGUAUGUGUGUAA
4 8 0 11 23 8 15
9 >mmu-miR-467g MIMAT0005854
UAUACAUACACACACAUAUAU
10 0 5 6 21 5 16
10 >hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU
11 2 1 10 24 3 21
11 >rmi-miR-5318 MIMAT0021390
UUGUAUAACUGCAGAAGACUUUUCUCC
7 4 6 10 27 10 17
12 >aly-miR831-5p MIMAT0017613
AGAAGAGGUACAAGGAGAUGAGA
11 9 1 2 23 10 13
13 >cel-miR-8210-5p MIMAT0032837
UGCCUUCUUUCCUUGUGUCGCCGAC
1 5 9 10 25 14 11
14 >cel-miR-8209-5p MIMAT0032835
AAAACGAAGAAAGAAGAAGAA
15 5 1 0 21 6 15
15 >pab-miR11418 MIMAT0044920
ACCCACCGCCGCUGCCGCCGC
2 5 13 1 21 1 3
16 >mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG
0 10 0 10 20 10 10
17 >hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU
11 2 1 10 24 3 21
18 >tch-miR-1277-5p MIMAT0036467
UAUAUAUAUAUAUGUACGUAU
8 2 1 10 21 3 18
19 >cel-miR-8210-5p MIMAT0032837
UGCCUUCUUUCCUUGUGUCGCCGAC
1 5 9 10 25 14 11
20 >mmu-miR-467c-5p MIMAT0004885
UAAGUGCGUGCAUGUAUAUGUG
5 7 2 8 22 9 13
21 >hsa-miR-2054 MIMAT0009979
CUGUAAUAUAAAUUUAAUUUAUU
9 1 1 12 23 2 21
22 >mmu-miR-1187 MIMAT0005837
UAUGUGUGUGUGUAUGUGUGUAA
4 8 0 11 23 8 15
23 >lja-miR11146-3p MIMAT0043929
GCAACGACAUGUAUAGUUGGAGG
7 8 3 5 23 11 12
24 >cgr-miR-598 MIMAT0023986
UACGUCAUCGUCGUCAUCGUUAUC
4 4 7 9 24 11 13
25 >mmu-miR-1187 MIMAT0005837
UAUGUGUGUGUGUAUGUGUGUAA
4 8 0 11 23 8 15
26 >hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU
11 2 1 10 24 3 21
27 >chi-miR-211 MIMAT0036057
UUCCCUUUGUCAUCCUUUGCCC
1 2 9 10 22 11 11
28 >mmu-miR-211-5p MIMAT0000668
UUCCCUUUGUCAUCCUUUGCCU
1 2 8 11 22 10 12
29 >dps-miR-980-5p MIMAT0012223
AGUCUCUCACAUGGCUGGUCUAGC
4 6 7 7 24 13 11
30 >hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU
11 2 1 10 24 3 21
31 >mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG
0 10 0 10 20 10 10
32 >mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG
0 10 0 10 20 10 10
33 >bta-miR-574 MIMAT0024577
UGAGUGUGUGUGUGUGAGUGUGUG
2 12 0 10 24 12 12
34 >eca-miR-9074 MIMAT0034619
UGACUAAUAGGAAAUUUUAAGUGAC
10 5 2 8 25 7 18
35 >hsa-miR-1277-5p MIMAT0022724
AAAUAUAUAUAUAUAUGUACGUAU
11 2 1 10 24 3 21
36 >ath-miR414 MIMAT0001322
UCAUCUUCAUCAUCAUCGUCA
5 1 7 8 21 8 13

Table 2: Screening of different ESTs sequence with count of A, G, C, U/T, and A-T/U.

The structural annotation of these microRNAs to identify their structures through online software called Mfold that uses these sequences to determine the best possible secondary structures and energies of these micro RNA’s. The miRNA structure that is low energy to our required parameters. These 36 miRNA structures are chosen because lowest energy structures are more stable in nature to our required E-value as shown in Supplementary Figure [12].

The functional annotationselect those microRNA whose AU content between 30% and 70%. Only 29% miRNA filled with these criteria in which we found target genes for only 10 sequences. The complete 9 sequences annotated which have basic role in biological process and molecular level is listed in Table 3 [13].

Peppermint MiRNA Function GO Term Annotations (biological process) GO term annotations (molecular functions)
>mmu-miR-466i-5p MIMAT0017325
UGUGUGUGUGUGUGUGUGUG
Protein phosphorylation
electron transport chain
Cell redox homeostasis
Activation of GTPase activity
Cellular process. GO :0009987 Electron transfer activity
GO: 0009055
Phosphotransferase activity
GO: 0016773
GTPase activator activity
GO: 0005096
>bmo-miR-3270 MIMAT0015455
UGUCUUUUUCCUAAAACGAUUCA
Cellular response to nitrogen starvation
Cellular response to fatty acid
Glucosinolate catabolism
Cellular metabolic process
GO: 0044237
ATP binding
GO: 0005524
Ascorbic acid binding
GO: 0031418
>hsa-miR-6873-5p MIMAT0027646
CAGAGGGAAUACAGAGGGCAAU
Somatic cell DNA recombination Regulation of biological process
GO: 0065007
Sequence specific DNA binding
GO: 0043565
>prd-miR-7912-5p MIMAT0030650
CAUUGCAUUUGGUUGUCCUUGGCU
Defense process
Response to herbivore
Response to fungus
Response to stimulus
GO: 0050896
Not known
>bta-miR-574 MIMAT0024577
UGAGUGUGUGUGUGUGAGUGUGUG
Nucleosome assembly Cellular component organization
GO: 0071840
Histone binding
GO: 0042393
>hsa-miR-8485 MIMAT0033692
CACACACACACACACACGUAU
Intra cellular signal transduction
Transmembrane Protein serine/threonine kinase signaling pathway
Signaling
GO: 0023052
Transmembrane signaling receptor serine threonine kinaseÃÃÃÂ???  activity
GO: 0004674
>mmu-miR-467c-5p MIMAT0004885
UAAGUGCGUGCAUGUAUAUGUG
Regulation of vesicle fusion Localization
GO: 0051179
Protein dimerization activity
GO: 0046983
>rmi-miR-5318 MIMAT0021390
UUGUAUAACUGCAGAAGACUUUUCUCC
Cell proliferation
Cell differentiation
Cell proliferation
GO: 0008283
2 iron, 2 sulpher cluster binding
GO : 0051537
>aly-miR831-5p MIMAT0017613
AGAAGAGGUACAAGGAGAUGAGA
Double DNA break repair via homologous Reproductive process
GO: 0022414
Core promoter sequence specific activity
GO : 0001046
mRNA binding
GO: 0003739

Table 3: Functional annotation of Mentha piperita with respect 9 different sequence of biological and molecular level.

InterPro is a database of protein families, domains and functional sites in which identifiable features found in known proteins can be applied to new protein sequences in order to functionally characterize them. Next step to annotate these sequences which can be done by merging the GOs (obtained from inter pro database) into annotation domain of Blast2Go as shown in Figure 1 [14]. Blast2go helps us to know about our data distribution that how much sequences were annotated with Gene Ontology (GOs). The functional annotation refers to the analysis of the biological processes associated with these components. Those 9 sequences have roles in biological process and at molecular level as well as shown in Figure 2.

ipbmbj-domain

Figure 1: Functional annotation of merge interpro domain reference with gene ontology.

ipbmbj-domain

Figure 2: Functional annotation of Mentha piperita with reference to gene ontology biological function, molecular function.

The phylogeny analysis of Mentha has been blasted with Arabidopsis thaliana to confirm the conserved domain by using the online package NCBI database [15]. Based on blast results, the phylogenetic tree was constructed to confirm the conservation of Mentha piperita with Arabidopsis thaliana. The transition and transversion of nucleotide are under observation to have tree and cladogram. The branch length show among the relationship between species as shown in Figure 3.

ipbmbj-domain

Figure 3: Phylogenetic tree analysis using the neighbor-joining method by MEGA X.

Discussion

Peppermint, commonly known as Mentha piperita, is a perennial herb from the Lamiaceae family [16]. For its medical benefits, including its antispasmodic actions, anti inflammatory and antibacterial peppermint has been used for centuries. Additionally, it is employed in the food and beverage company as a flavoring ingredient. In order to comprehend the molecular processes underlying peppermint's different pharmacological characteristics, recent research has concentrated on locating novel genes and miRNAs in this plant. In this study, we used EST analysis to identify 29 novel genes from peppermint [17]. The functional annotation of these genes revealed their potential roles in various biological processes, including cellular redox homeostasis, electron transport chain, and protein phosphorylation. Furthermore, we identified 36 miRNAs in peppermint, and their functional annotation suggested their involvement in cellular response to nitrogen starvation, glucosinolate catabolism, and somatic cell DNA recombination. The phylogenetic analysis confirmed the conservation of Mentha piperita with Arabidopsis thaliana. In addition, we also calculated the E-values and energies for the identified ESTs and miRNAs, providing further insights into their potential functions. Our findings provide a valuable resource for further studies on the molecular mechanisms underlying the medicinal properties of peppermint. Previous studies have also reported the medicinal properties of peppermint, including its antimicrobial, anti-inflammatory, and antispasmodic effects. Moreover, the identification of novel genes and miRNAs in peppermint has been previously reported, providing insights into the molecular mechanisms underlying its pharmacological properties [18]. Our study builds on these findings, providing novel insights into the potential functions of newly identified genes and miRNAs in peppermint. In this study, we performed transcriptome analysis of Mentha piperita and identified 29 Expressed Sequence Tags (ESTs) using the NCBI database with E-values ranging from 2e-20 to 8e-04. These ESTs were found to be involved in various biological processes including protein phosphorylation, electron transport chain, cell redox homeostasis, activation of GTPase activity, cellular response to nitrogen starvation, cellular response to fatty acid, glucosinolate catabolism, somatic cell DNA recombination, defense process, response to herbivore, response to fungus, nucleosome assembly, cellular component organization, intracellular signal transduction, transmembrane protein serine/threonine kinase signaling pathway, regulation of vesicle fusion, cell proliferation, cell differentiation, double DNA break repair via homologous, and reproductive process. Furthermore, we also identified 36 microRNAs (miRNAs) in Mentha piperita with AU content ranging between 30% and 70%. The energies of these miRNAs were calculated using the online tool RNAfold, with values ranging from -32.1 to -25.6 kcal/mol. The miRNAs were found to have basic roles in various biological processes and molecular functions such as protein phosphorylation, electron transport chain, cellular metabolic process, somatic cell DNA recombination, and regulation of biological process, cellular component organization, signaling, localization, and cell proliferation [19]. To confirm the conservation of Mentha piperita with Arabidopsis thaliana, we performed phylogenetic analysis using the online package NCBI database. The results showed that the transition and transversion of nucleotides were under observation to have tree and cladogram, which confirmed the conservation of Mentha piperita with Arabidopsis thaliana. Overall, our study provides valuable insights into the transcriptome and miRNA profile of Mentha piperita and sheds light on the conservation of this plant with Arabidopsis thaliana. Further investigation into the medicinal properties and prospective uses of plant can be enhanced by the discovery of ESTs and miRNAs involved in various biological processes and molecular functions [20].

Conclusion

In conclusion, this study provides valuable insights into the identification and functional annotation of ESTs and miRNAs in Peppermint (Mentha piperita). The ESTs obtained were identified to be associated with different biological processes, such as stress responses, indicating their potential roles in the growth, metabolism, and development of Peppermint and signal transduction. The miRNAs identified in this study were discovered to have diverse functions regulation of gene expression, modulation of cellular signaling pathways and cellular responses to various stresses. Additionally, the phylogenetic analysis revealed the conservation of Peppermint with Arabidopsis thaliana. The functional annotation of miRNAs revealed that only 29% of the identified miRNAs fulfilled the AU content criteria between 30% and 70%. However, among these miRNAs, 9 sequences were found to have a basic role in molecular functions and biological processes.

Future Recommendations

In future studies, it would be interesting to perform functional validation experiments for the identified ESTs and miRNAs to confirm their roles in peppermint growth and development. Additionally, further investigation of the miRNAs that did not meet the AU content criteria may provide insights into their potential roles in peppermint. The results of this study may provide a foundation for future research aimed at improving the yield and quality of peppermint, which could have potential benefits for the pharmaceutical and food industries.

Data Availability Statement

The data that support the findings were derived from the following resources available in the public domain (GenBank) at https://www.ncbi.nlm.nih.gov/genbank/

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Author Contributions

S.I (Saqib Ishaq), J.K. and R.T designed the study. S.I (Saqib Ishaq), J.K, R.T and O.H performed various in silico analyses. R.T. and S.I wrote the initial MS. A.A, M.I.H, K.G and Y.A, R.N revised the MS. All authors have read and agreed to the published version of the manuscript.

Acknowledgements

The authors acknowledge all those patients who participated in the study.

Funding

This study was financially supported by Department of Computer Sciences and Bioinformatics, Khushal Khan Khattak University, Karak (KKKUK), KPK, Pakistan and Department of Biotechnology and Genetic Engineering, Kohat University of Science and Technology (KUST), Kohat 26000, KPK, Pakistan.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

References

Citation: Ishaq S, Khan J, Tahir R, Aziz A, Habib O, et al. (2025) In silico Analysis of MicroRNA of (Mentha X Piperita) Peppermint. Biochem Mol Biol J. 11:48.

Copyright: © 2025 Ishaq S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.