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. 2022 Dec 19;16:11779322221142116. doi: 10.1177/11779322221142116

Sequence, Secondary Structure, and Phylogenetic Conservation of MicroRNAs in Arabidopsis thaliana

Muhammad Waqar Mazhar 1,, Nik Yusnoraini Yusof 2, Tayyaba Shaheen 1, Saira Saif 1, Ahmad Raza 3, Fatima Mazhar 4
PMCID: PMC9768830  PMID: 36570328

Abstract

MicroRNAs are small non-coding RNA molecules that are produced in a cell endogenously. They are made up of 18 to 26 nucleotides in strength. Due to their evolutionary conserved nature, most of the miRNAs provide a logical basis for the prediction of novel miRNAs and their clusters in plants such as sunflowers related to the Asteraceae family. In addition, they participate in different biological processes of plants, including cell signaling and metabolism, development, growth, and tolerance to (biotic and abiotic) stresses. In this study profiling, conservation and characterization of novel miRNA possessing conserved nature in various plants and their targets annotation in sunflower (Asteraceae) were obtained by using various computational tools and software. As a result, we looked at 152 microRNAs in Arabidopsis thaliana that had already been predicted. Drought tolerance stress is mediated by these 152 non-coding RNAs. Following that, we used local alignment to predict novel microRNAs that were specific to Helianthus annuus. We used BLAST to do a local alignment, and we chose sequences with an identity of 80% to 100%. MIR156a, MIR164a, MIR165a, MIR170, MIR172a, MIR172b, MIR319a, MIR393a, MIR394a, MIR399a, MIR156h, and MIR414 are the new anticipated miRNAs. We used MFold to predict the secondary structure of new microRNAs. We used conservation analysis and phylogenetic analysis against a variety of organisms, including Gossypium hirsutum, H. annuus, A. thaliana, Triticum aestivum, Saccharum officinarum, Zea mays, Brassica napus, Solanum tuberosum, Solanum lycopersicum, and Oryza sativa, to determine the evolutionary history of these novel non-coding RNAs. Clustal W was used to analyze the evolutionary history of discovered miRNAs.

Keywords: Arabidopsis thaliana, miRNAs, Solanum lycopersicum, Oryza sativa, phylogenetic analysis

Introduction

Sunflower (Helianthus annuus) belongs to the Asteraceae family. By cloning method, 700 types of miRNA were identified in plants; in 2012, miRNA was identified in Arabidopsis thaliana. All the processes of miRNA targets are based on coding and non-coding sequence.1 Previous studies show that RNA polymerase play important role in the transcription of the miRNA gene.2

In recent years, for the identification of miRNA scientists have used high throughput sequencing and computational analysis techniques.3 Almost all scientists have concluded that microRNAs involved in the regulatory function of flowering and non-flowing plants are conserved.4 Plants are damaged by 2 types of environmental stresses categorized as biotic and abiotic stress. Damage to living organisms by living organisms like parasites, bacteria, viruses, and fungi is known as abiotic stress as well as damage to a living organism by the source of nonliving factors called abiotic stress.5 To describe abiotic stress, we should study the function of different organisms that survived in different environments. Stress always affects the plant’s tissues. plants need enough water for their sufficient growth. Up and down movement of water expand plant cells, which causes plant growth. Enough amount of water expands the plant’s cells and transfers the minerals from the soil to the tip of the leaves but stress causes an imbalance in the plant’s routine processes.

According to research every year, we lost 50% of our food production due to abiotic stress. Abiotic stress affects plants’ fruits, crops, metabolism, respiration processes of plants, and at the end plant’s seeds. Seeds are used for next generation; hence, unhealthy seeds affect further production.6 H. annuus typically refer to annual species that tend to spread rapidly and can become aggressive.7 The plant family improvement depends on the genetically resistant varieties, seed productivity, modern cultivation, and biotic-abiotic stress tolerance. Plant improvement can be assessed by studying its genetic makeup and sowing in a different location.8 For the human, it acts as an important source of nutrients. Nutritionally, it is the main source of vital nutrients inkling carbohydrates, proteins, and dietary fibers, and provides almost 20% of the dietary energy supply. According to the miRNA database, H. annuus contains a total of 6 precursors and 7 mature microRNA that are compared with A. thaliana for the identification of novel microRNA.9 A. thaliana contained 205 precursors and 384 mature non-coding RNA. All data regarding miRNA are present in miRBase.

Methodology

Many tools are used as comparative genomics approaches to achieve novel and interesting information about miRNAs in plants and animals. In the initial step, identify sequences and reference sequences, and download them from the microRNA Registry Database. This miRBase Pre-miRNA database was available at https://www.mirbase.org/ freely. Pre-miRNA potential candidates were predicted by subjecting the downloaded mature and precursor miRNAs sequence through the Basic Local Alignment Tool. For this purpose, nucleotide BLAST available freely at Genbank of the National Center for Biotechnology Information (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch) was used. The miRNA* sequences, both mature and precursor, were subjected to BLAST against H. annuus expressed sequence tags (ESTs) sequentially using the BLASTn program following a maximum of up to 4 mismatches with miRNAs*.

EST single-tone selection

BLASTn program was used and the setting of the parameters was adjusted as expect values, 1000; low complexity, the sequence filter, database, others; organism, H. annuus; program selection, somewhat similar sequences; and all other parameters, by default. To identify the coding part of miRNA, we used BLASTx. BLASTx highlights coding regions.10

Prediction of miRNAs secondary structure

MFOLD, a secondary structure prediction tool was used to produce a stem-loop structure for the initially identified potential H. annuus. All the initial candidate sequences that failed to develop stable secondary structures were discarded. MFOLD software updated as UNAfold http://www.unafold.org/ and then clicked on MFOLD and then selected application (RNA fold form Version 2.3).11

UNAfold → MFOLD → Application → RNA fold form version

The setting of MFOLD parameters was adjusted as RNA sequence, linear; folding temperature, 37°C, ionic concentration, 1 mol/L of National Center for Biotechnology Information (NCBI) having no divalent ions; percent sub-optimality number, 5; maximum interior loop size 30.

Conservation and phylogenetic analysis

Clustal W was selected for phylogenetic analysis. Clustal W is used for multiple sequence alignment or the alignment of more than one sequence available at https://www.genome.jp/tools-bin/clustalw.

Results

New potential miRNAs in sunflower

In all research, we predicted 152 miRNAs that performed regulatory process against drought-tolerant stress in A. thaliana. miRNAs that respond to drought stress are 156a, 156b, 156c, 156d, 156e, 156f, 158a, 159a, 164a, 164b, 165a, 165b, 166a, 166b, 166c, 166d, 166e, 166f, 166g, 168a, 168b, 169a, 170, 171a, 172a, 172b, 173, 156b, 319a, 319b, 169b, 169c, 169d, 169e, 169f, 169g, 169h, 169i, 169j, 169k, 169l, 169m, 169n, 171b, 171c, 172c, 172d, 339a, 339b, 394a, 394b, 397a, 397b, 398a, 398b, 398c, 399a, 399b, 399c, 399d, 399e, 399f, 400, 401, 402, 403, 404, 408, 159g, 156h, 158b, 159c, 319c, 164c, 172e, 417, 418, 414, 415, 416, 419, 420, 426, 427a, 427b, 427c, 827, 830, 833a, 835, 836, 837, 839, 841a, 842b, 844, 845a, 846, 848, 850, 851, 847, 855, 854a, 854b, 854c, 856, 857, 858, 859, 860, 861, 865, 845b, 870, 1886, 1888a, 2933a, 2933b, 2936, 3434, 774b, 4221, 854e, 5021, 5024, 5025, 5026, 5029, 5641, 5642a, 858b, 833b, 156i, 156j, 5652, 5653, 5654, 5655, 5656, 5658, 5188, 1888b, 5666, 5996, 8121, 8165, 8170, 8178, 8180, and 8181. All these miRNA sequences are reported in A. thaliana.

Prediction of novel miRNA

In A. thaliana, after identifying the 152 microRNA sequences, we performed local alignment of these sequences by BLASTn with the parameters of somewhat similarities and H. annuus in organisms and selected those BLAST sequences that were 80% to 100% similar. So in local alignment, we got 19 sequences of A. thaliana against H. annuus. The accession numbers of these 19 sequences are XR_002550943, XR_002552183, XR_002552875, XR_002554296, XR_002556375, XR_002562643, XR_002570335, XR_002574508, XR_2575503, XR_002579567, XR_002582121, XR_002587840, XR_002549854, XR_002592285, XR_004862999, XR_004863001, XR_004865012, XR_004869948, and XR_004890935 (see in Table 1).

Table 1.

Novel microRNA in Helianthus annuus that is predicted with the reference of Arabidopsis thaliana sequences.

H. annuus miRNA Accession no by BLASTn Novel miRNA sequences
1 MIR156 ACCESSION TTTCGTTATTATCATCTATTCTTGTGGCACGAG
a XR_002550943 AAAGAGAAGTTTGGTTGAGAACTGACAGAAG
AGAGTGAGCACAGGCC
ACCESSION CTCAAACTTTATGCACTCTTTTACTTCTGTTGA
XR_004869948 TTATGTTCTTTGATGGGATGATATATATGGTT
ACAAAGATGAAGAAAGCTGACAGAAGAGAGT
GAGCATATGCAACCAGTTGTATATAGAGTATG
CATTTATTGGGA
2 MIR164 ACCESSION GACATGTAAAGCGAGTGGGTGGGTTTATAAG
a XR_002562643 ATTACTAAGGTGGGTGTTGAGCAAGATGGAG
AAGCAGGGCACGTGCATTACAAACTCATCAT
GCAAAACTTCATTCAAATTTCAACAAAACACC
CTTTCTCAGGTTTGA
3 MIR165 ACCESSION 5p
a XR_002587840 TCTCTTTCCCACCTATACCATCACCATTTACAC
CCATCTTTCTCTCACTAAAACTGTACCCAAAA
GATGA
ACAAGAAGAAAAGAACTGAAGCTGAAAGCTG
TTTTCTTTTGAGGGGAATGTTGTCTGGCTCGA
GGCCACT
3p
AAATGATGTTTGTGAAATGTTTGATTACTGCG
AGAAGTTACTGATCTGGTGTCGTCGGACCAGG
CTTCATTCCCCCCAATTGTGGCTTCCTGTGTTC
TAAAAGAATTGTTTTTTCTTGAATCTACATGTT
TCCA
ACCESSION 5p
XR_002549854 GAGGTCTTGGGTTCAAGTCCCACTGACGACAG
GAATAAAAGAAATTTGCCGTTAAAAAAAAAT
GAAGAAGAAGATTGGGGTAATGATGAGTTCT
GAGAATCTAACAAAATTCCAGAAACAGGATG
3p
TTCATAATCACATAATTGATCAATCTTTGTTG
ATCAATGATTAAAGATTAGAATCTTGTGTTGT
CGGACCAGGCTTCATTCCCCTC
ACCESSION 5p
XR_002552183 TTCTTTTGAGGGGAATGTTGTTTGGCTCGAGG
TCATTAGAAACCATGGATCTTTATCTCTCTCTA
TATAT
ATATGTATGTATATATATTGATGTATGTA
3p
ATCCATCATCTATGGTCTTTGTTGATCAATGA
GTTTTAGATTAATTATATAAAGTGTTAAAGAG
AGTATC
TTGATCATTGGATCTGGTGTGCTCGGACCAGG
CTTCATTC
ACCESSION 5p
XR_002582121 GAAGAGAAGAAGAAGCTATATCTTTTGAGGG
GAATGTTGTTTGGCTCGAGGTCAATAGAAACC
AAAGATCTATATCTCTTTTTCTCTAACTGTTAA
TAAAGATGTACATATATATGTATGTATATGAT
GTTATAGTCAAC
3p
GGTTATTCATTTAGAGTGTTGAATGAGAGAAA
CTTGATCATTGGATGATCTGCTGTACTCGGAC
CAGGCTTCATTCCCCCCAATTGTTGCTTCA
ACCESSION 5p
XR_002570335 CAATCTTTCTCCCTCTCTCTAAGATCACACCTA
AAAGATGAACACATTGAAAGCCTTTTTATCTT
TTGAGGGGATTGTTGTCTGGCTCGAGGCCACT
AGAAAGCCTAGATCTTTCTCTCTCTATATACA
TATCTATATCA
3p
GGGATTGTTGTCTGGCTCGAGGCCACTAGAAA
GCCTAGATCTTTCTCTCTCTATATACATATCTA
TATCACAGTCAACGCAACCATTGATTACTGAG
AGAGATTCTTGATCTGGTGTCGTCGGACCAGG
CTTCATTCCCC
4 MIR170 ACCESSION GATGTTGGTTCGGTTCAATAAGAACTCAATGT
XR_004890935 TCAAATGATGCATTGAACGTTGCTTTTTGATT
GAGCCGTGCCAATATCACGTGCATGTTGCTTC
TAAATTTCCACAAGTCTTTTGTAAACTTCTGTG
AAAAGGACCTA
5 MIR172 ACCESSION AGAATCTTGATGATGCTGCATCGGAAATCAAT
a XR_002592285 TGACCACTTTAAAAATCAACGCATCAAATACG
ATTTTGTTGGATCTCATACAAACAAAGGTAAT
CTTT
ACCESSION TATAGATTGGCTGGAATCTAAGCACAAGGGT
XR_002556375 GTGTTTTTTCTGTAGATTTAATAATGAAAATA
CTGATCACACACCAGAAAAGAGAAATAGGGC
TTTGCTGTTATTGTATTTTTTTATTGTATTTAGT
TTGAAGATTTTG
ACCESSION AGAAAGAAAAAGAAAGTGGTTTATGGGCCCC
XR_004865012 TTGATGGTTTGAGAATCTTGATGATGCTGCAG
CGGCAATTGCTGGCTAATTATGATCTTTAAAA
CTGGATTATGGTAAGTTGTGACCATGTAGATT
TAATCTTAAAATA
6 MIR172 ACCESSION 5p
b XR_004862999 TCAAACAACATCAGCAGGTAGCAGCTCCACCT
CCTCAGTCACCAGCGCCGACTGCCGCTGCTCC
GCCTCT
GCCCTCCGGCTGCTCCGCCTTCGACGATTGCT
GCCGAAACTTTGTTT
3P
ACTAAGTAGCTATTAGCTAATTTTTGTTCTTGT
TTAATTTTGAATTCAGGCTGTTTTGAGTTGTGG
GATC
AAGCTAGAACAAGATTT
7 MIR319 ACCESSION AATTAGCTGCCGACTCATTCATTTAACCACTC
a XR_004863001 AGTAGAAAAGGGTTCACTTTATGCTACTTTGA
TTGAGTGAATGATGCGGGAGATAGTTTTCATC
CCTTGCTAATCTGTACTTGGACTGAAGGGAGC
TCCCTCGTTCTT
8 MIR393 ACCESSION 5P
a XR_002552875 TCCCTCTCTCTCTCTCTCTCTCTCTCTCTCTCTC
TCTCTCTCTTACACACACATCTCTCTCCCCGTC
TCTATATGTGCGAAGATTACAACGGTAGCTAA
AGGACGCATCCAAAGGGATCGCATTGATCCT
AAATCCCATA
3P
CGCATAGTATATGGGTATGATATACCGAGTTG
GGATCATGCTATCCTTTTGGATTCCTTCTTCGG
TTGCTTCTAACTTTATAAATATCACACGCACA
AGCCAAGAACAATCAAAGATGGAAGAGAATG
TGATGTTTGATT
9 MIR394 ACCESSION CTTTAGGGTTTTTAGGGTTTCTTTCATGGTGGT
a XR_002554296 TTAATAAAGAGTTTCCAGCAGATTTCTTTGGC
ATTCTGTCCACCTCCATATTCATTGATCTATGT
ATCTCACTGTTGTGTAAATGTGTAATTAGGGT
TTATTGGTTT
10 MIR399 ACCESSION GGTCGGAAGAAAAGGAGCTGAGACAGCTGGA
c XR_002574508 TGTTTTGAAGCAGGCAATTGTGTTTGGGCTGG
GTGAAGACAACTGGCTCTGGGCACGATAACG
CAAGGGGTTTTTCCATGCGCCTGCCAATAGAA
ATATGCGGTATAGT
11 MIR156h ACCESSION ATGTTGATGAAACGGGTTGAAGTGTCTCGATG
XR_002579567 ATGTTGTTGACAGAAGATAGAGAGCACAGAT
GACGAAGTTGCAGCTAATATTTGGCATCTTTT
TTCTTTGTGCCCTCTATTGTTCTGTCATCATCA
CATATCTTCTTC
12 MIR414 ACCESSION ATATTCATTGAGTTATTATTATTTTATGAAAAT
XR_002575503 TTTCATGTTCTTTGAAACTTATCATGTCTTATG
AAATCGTTTCAGTCCTCAGTCTTAGGGGCTGT
TTGGTTGCCTCTTAATGGCTCCATTAAGAAGC
TTGGCCTCTGAATCGGTCAGACATGGGGTGT

These 19 sequences code for different miRNAs that were novel. In our research, we predicted 12 novel miRNAs in sunflowers against A. thaliana. These novel predicted miRNAs are MIR156a, MIR164a, MIR165a, MIR170, MIR172a, MIR172b, MIR319a, MIR393a, MIR394a, MIR399a, MIR156h, and MIR414 (see in Table 2).

Table 2.

Conservation analysis of Helianthus annuus with other organisms such as Gossypium hirsutum, H. annuus, Arabidopsis thaliana, Triticum aestivum, Saccharum officinarum, Zea mays, Brassica napus, Solanum tuberosum, Solanum lycopersicum, and Oryza sativa.

G. hirsutum H. annus A. thaliana T. aestivum S. officinarum Z. mays B. napus S. tuberosum S. lycopersicum O. sativa
MIR156a present present present present present present present present present present
MIR164a present Non present present Non present present present present present
MIR165a Non non present non non Non non non non non
MIR170 non non present non non Non non non non non
MIR172a present non present non non present present present present present
MIR172b present non present non non present present present present present
MIR319a non non present present non present non present present present
MIR393a present non present Non non present present present present present
MIR394a present non present non non present present non present present
MIR399c present non present present non present present present present present
MIR156h non non present present present present non present non present
MIR414 non non present non non non non non non present

Novel sunflower miRNAs structures predicted from A. thaliana

In our research, we predicted 12 novel microRNAs in the sunflower that respond against drought stress (MIR156a, MIR164a, MIR165a, MIR170, MIR172a, MIR172b, MIR319a, MIR393a, MIR394a, MIR399a, MIR156a, and MIR414). Here, we explain the miRNAs structures on the base of both 5 and 3 prime by MFOLD.

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Ancestral conservation of H. annuus

In addition, novel sunflower precursor miRNAs were selected for conservation studies. For this process, all novel miRNAs selected to evaluate their conservation in other plants. For conservation studies, we selected 10 different types of plants like Gossypium hirsutum, H. annuus, A. thaliana, Triticum aestivum, Saccharum officinarum, Zea mays, Brassica napus, Solanum tuberosum, Solanum lycopersicum, and Oryza sativa. Using the same process, many researchers have determined precursor conservation and phylogenetic analysis in different plants.

Phylogenetic analysis of non-coding microRNAs

The study of the evolutionary history of a species or a group of organisms or a particular characteristic of an organism. Here we have done phylogenetic analysis by clustal W.

Phylogenetic analysis of MIR156a

The phylogenetic analysis of mir156a is described in Figures 1 and 2. According to the MIR156a phylogenetic analysis, H. annuus with the Accession number “XR_002550943” and “XR_4869948” shows close relation with T. aestivum, B. napus, A. thaliana, G. hirsutum, O. sativa, Z. mays, and S. officinarum.

Figure 1.

Figure 1.

MIR156a.

XR_002550943.

Figure 2.

Figure 2.

MIR 156.

XR_004869948.

Phylogenetic analysis of MIR164a

The phylogenetic analysis of mir164a is described in Figure 3. According to the phylogenetic analysis of MIR164a, H. annuus with the Accession number “XR_002562643” shows close relation with T. aestivum, B. napus, A. thaliana, O. sativa, Z. mays, S. lycopersicum, and G. hirsutum and shows a distance relationship with S. tuberosum.

Figure 3.

Figure 3.

MIR164a.

XR_002562643.

Phylogenetic analysis of MIR172b

The phylogenetic analysis of mir172b is described in Figure 4. According to the phylogenetic analysis of MIR172b, H. annuus with the Accession number “XR_004862999” shows close relation with A. thaliana, Z. mays, S. lycopersicum, S. tuberosum and shows a distance relationship with G. hirsutum.

Figure 4.

Figure 4.

MIR172b.

XR_004862999.

Phylogenetic analysis of MIR172a

Phylogenetic analysis of mir172a is described in Figures 5 to 7. According to the phylogenetic analysis of MIR172a, H. annuus with the Accession number “XR_002592285” and “XR_002556375” shows close relation with A. thaliana, Z. mays, S. lycopersicum, O. sativa, B. napus and with “XR_004865012” shows close relationship with G. hirsutum.

Figure 5.

Figure 5.

MIR 172a (XR_002592285).

Figure 7.

Figure 7.

MIR172a (004865012).

Figure 6.

Figure 6.

MIR172a (002556375).

Phylogenetic analysis of MIR319

The phylogenetic analysis of mir319 is described in Figure 8. According to the phylogenetic analysis of MIR319, H. annuus with the Accession number “XR_004863001” shows close relation with A. thaliana, S. lycopersicum, and T. aestivum.

Figure 8.

Figure 8.

MIR319(XR_004863001).

Phylogenetic analysis of MIR393a

The phylogenetic analysis of mir393 is described in Figure 9. According to the phylogenetic analysis of MIR93a, H. annuus with the Accession number “XR_002552875” shows close relation with A. thaliana, G. hirsutum, O. sativa, S. tuberosum, and Z. mays.

Figure 9.

Figure 9.

MIR393a(XR_002552875).

Phylogenetic analysis of MIR394

The phylogenetic analysis of mir393 is described in Figure 10. According to the phylogenetic analysis of MIR94, H. annuus with the Accession number “XR_002554296” shows a distance relation with A. thaliana, G. hirsutum, O. sativa, B. napus, S. lycopersicum, and Z. mays.

Figure 10.

Figure 10.

XR_002554296.

Phylogenetic analysis of MIR399

The phylogenetic analysis of mir399 is described in Figure 11. According to the phylogenetic analysis of MIR94, H. annuus with the Accession number “XR_002574508” shows a distance relation with A. thaliana, G. hirsutum, O. sativa, B. napus, S. lycopersicum, and Z. mays.

Figure 11.

Figure 11.

MIR399(XR_002574508).

Discussion

Sunflower is the fourth biggest oil-seed crop in the world. The seeds of sunflowers are used in food as well as their dried stalk is used as fuel. It has previously been used as an ornamental plant and was also used in ancient ceremonies.12 Moreover, different parts of sunflowers are used in body painting, decorations, and making dyes for the textile industry. Its oil is used in the manufacturing of margarine and salad dressings, and cooking. With roasted seeds, a coffee type could be made. In industry, it is used in cosmetics and paints. Due to its lack of anti-nutritional factors and high nutritional values, it is a potential source of protein for human consumption. Due to its metabolic, physiological, and morphological adaptation strategies, the sunflower is one of the most important oil-seed crops and is resistant to various abiotic stresses. This crop is of special interest for its adaptation to limited water availability, high temperatures, high salinity, and heavy-metal concentrations in soil. The dried stems which are used for fuel contain potassium and phosphorous which can be composed and returned to the soil as fertilizer.13

MiRNAs arise from primary longer RNA transcripts that include a self-complementary fold-back, from which the mature miRNAs are excised. They are short RNA molecules containing 19-24 nucleotides in size.14,15 They are familiar as regulators of gene expression by binding to open reading frames (ORF) or untranslated regions (UTR) of specific mRNAs, targeting them for directing or cleavage translation inhibition at the mRNA level. It has been demonstrated that around 60% of protein-coding genes are targets of miRNAs and are modulated by these small RNAs.

miRNAs are derived from hairpin pre-miRNA from which both miRNA and the imperfectly complementary miRNA* strands are released. Their sequences are not conserved between plants and animals, and even not have been seen in fungi. Many miRNAs within the kingdom have an ancient origin, some being completely conserved among sunflower, Arabidopsis, rice, and even liverworts, mosses, and hornworts.16

By regulating gene expression, miRNA plays a vital role to regulate the developmental processes of organisms.17 The negative regulation of miRNAs in gene expression in both plants and animals has been demonstrated.18 MicroRNAs have been revealed to modulate diverse developmental processes, including polarity, identity, and organ separation, and to regulate their function and biogenesis.18 In our study, we used the miRBase database to find miRNAs from A. thaliana that were tolerant against drought stress that was 152 in strength and then performed local alignment of these miRNAs against sunflower and found 12 novel miRNAs (MIR156a, MIR164a, mir165a, mir170, mir172a, mir172b, mir319a, mir393a, mir394a, mir399c, mir156h, and mir414). The secondary structure of these 12 novel miRNAs, including forward and reverse strands, was forecasted by MFOLD software by using default parameters. Later, conservation and phylogenetic analysis were done by selecting 10 different organism type such as G. hirsutum, H. annuus, A. thaliana, T. aestivum, S. officinarum, Z. mays, B. napus, S. tuberosum, S. lycopersicum, and O. sativa. In our study, all novel miRNAs are present in only A. thaliana.

In our study, mir-156a is present in all species; mir-164 is present in all except H. annus and S. officin;19 mir-165a and mir-170 are present in only A. thaliana; mir-172a and mir172-b are present in all except H. annus, T. aestiyum, and S. officin;20 mir-319a is present in all except G. hirsutum, H. annus, S. officin, and Z. mays; mir-393a is present in all except H. annus, T. aestiyum, and S. officin; mir-394a is present in all except H. annus, T. aestiyum, S. officin, and B. napus; mir-399c is present in all except H. annus and T. aestiyum; mir-156h is present in all except G. hirsutum, H. annus, B. napus, and S. lycopersicum; and mir-414 is absent in all except A. thaliana, and O. sativa.

Conclusions

Twelve novel miRNAs (MIR156a, MIR164a, mir165a, mir170, mir172a, mir172b, mir319a, mir393a, mir394a, mir399c, mir156h, and mir414) were identified against drought stress in A. thaliana. We targeted these miRNAs to cope with the drought tolerance in sunflowers. In our study, all novel miRNAs are present in only A. thaliana. Moreover, different parts of sunflowers are used in body painting, decorations, and making dyes for the textile industry. Its oil is used in the manufacturing of margarine and salad dressings, and cooking. With roasted seeds, a coffee type could be made. In industry, it is used in cosmetics and paints. The improvement method also increases the production of sunflowers and benefits economically.

Footnotes

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research study is self-funded.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author Contributions: All authors have contributed to this study.

Availability of Data and Materials: The data associated with a paper are available on demand through email contact of co-author waqarmazhar63@gmail.com.

Ethical Approval: All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

Consent for Publication: This study is based on research.

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