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Genome Wide Computational Identification of Tuna (Thunnus orientalis) MicroRNAs and Their Targets

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Abstract

Applying genome-wide computational-based approaches (using the draft genome sequence published in recent years) and following a set of strict filtering criteria, a total of 48 potentially conserved microRNAs belonging to 30 families were identified from economically important fish tuna (Thunnus orientalis). Using BLAST and RNA hybrid program a total of 19 potential miRNA targets were also identified in this study, which includes a number of signaling molecules (serine/threonine-protein kinase, GTPase activating protein etc.) and transcription factors (F-box protein, zinc finger protein etc.). This study provides the basis for gaining a better understanding of miRNA-mediated gene regulatory processes in fishes.

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References

  • Barozai MYK (2012) Identification and characterization of the microRNAs and their targets in Salmo salar. Gene 499:163–168. doi:10.1016/j.gene.2012.03.006

    Article  Google Scholar 

  • Borchert GM, Lanier W, Davidson BL (2006) RNA polymerase III transcribes human microRNAs. Nat Struct Mol Biol 13:1097–1101. doi:10.1038/nsmb1167

    Article  Google Scholar 

  • Gorodkin J, Havgaard JH, Enster M, Sawera M, Jensen P, Öhman M, Fredholm M (2006) MicroRNA sequence motifs reveal asymmetry between the stem arms. Comput Biol Chem 30:249–254. doi:10.1016/j.compbiolchem.2006.04.006

    Article  Google Scholar 

  • Hagen JW, Lai EC (2008) MicroRNA control of cell-cell signaling during development and disease. Cell Cycle 7:2327–2332

    Article  Google Scholar 

  • Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucl Acid S 41:95–98

    Google Scholar 

  • Huang Y, Zou Q, Ren HT, Sun XH (2015) Prediction and characterization of microRNAs from eleven fish species by computational methods. Saudi J Biol Sci 22:374–381. doi: 10.1016/j.sjbs.2014.10.005

    Article  Google Scholar 

  • Huang Y, Zou Q, Wang ZB (2014) Computational identification of miRNA genes and their targets in mulberry. Russ J Plant Physiol 61:537–542. doi:10.1134/S1021443714040104

    Article  Google Scholar 

  • Krüger J, Rehmsmeier M (2006) RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 34:W451–W454. doi:10.1093/nar/gkl243

    Article  Google Scholar 

  • Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG (2007) Clustal W and Clustal X version 2.0. Bioinformatics 23:2947–2948. doi:10.1093/bioinformatics/btm404

    Article  Google Scholar 

  • Nakamura Y, Mori K, Saitoh K, Oshima K, Mekuchi M, Sugaya T, Shigenobu Y, Ojima N, Muta S, Fujiwara A, Yasuike M, Oohara I, Hirakawa H, Chowdhury VS, Kobayashi T, Nakajima K, Sano M, Wada T, Tashiro K, Ikeo K, Hattori M, Kuhara S, Gojobori T, Inouye K (2013) Evolutionary changes of multiple visual pigment genes in the complete genome of Pacific bluefin tuna. Proc Natl Acad Sci USA 110:11061–11066. doi:10.1073/pnas.1302051110

    Article  Google Scholar 

  • Naya L, Paul S, Valdés-López O, Mendoza-Soto AB, Nova-Franco B, Sosa-Valencia G, Reyes JL, Hernández G (2014) Regulation of copper homeostasis and biotic interactions by microRNA 398b in common bean. PLoS One 9(1):e84416. doi:10.1371/journal.pone.0084416

    Article  Google Scholar 

  • Paul S (2017) Identification and characterization of microRNAs and their targets in high-altitude stress-adaptive plant maca (Lepidium meyenii Walp). 3 Biotech 7(2):103. doi:10.1007/s13205-017-0734-5

    Article  Google Scholar 

  • Paul S, Kundu A, Pal A (2011) Identification and validation of conserved microRNAs along with their differential expression in roots of Vigna unguiculata grown under salt stress. Plant Cell Tiss Org 105:233–242. doi:10.1007/s11240-010-9857-7

    Article  Google Scholar 

  • Rogers K, Chen X (2013) Biogenesis, turnover, and mode of action of plant microRNAs. Plant Cell 25:2383–2399. doi:10.1105/tpc.113.113159

    Article  Google Scholar 

  • Saetrom P, Snøve O, Nedland M, Grünfeld TB, Lin Y, Bass MB, Canon JR (2006) Conserved microRNA characteristics in mammals. Oligonucleotides 16:115–144. doi:10.1089/oli.2006.16.115

    Article  Google Scholar 

  • Stenvang J, Petri A, Lindow M, Obad S, Kauppinen S (2012) Inhibition of microRNA function by antimiR oligonucleotides. Silence 3:1. doi:10.1186/1758-907X-3-1

    Article  Google Scholar 

  • Sun K, Lai EC (2013) Adult-specific functions of animal microRNAs. Nat Rev Genet 14:535–548

    Article  Google Scholar 

  • Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol 30:2725–2729. doi:10.1093/molbev/mst197

    Article  Google Scholar 

  • Wang L, Yao J (2014) The microRNAs important for ovarian and early embryonic development in cattle. Turk J Vet Anim Sci 38:599–605

    Article  Google Scholar 

  • Yang W, Liu X, Zhang J, Feng J, Li C, Chen J (2010) Prediction and validation of conservative microRNAs of Solanum tuberosum L. Mol Biol Rep 37:3081–3087. doi:10.1007/s11033-009-9881-z

    Article  Google Scholar 

  • Zhang B, Pan X, Cobb GP, Anderson TA (2006) Plant microRNA: a small regulatory molecule with big impact. Dev Biol 289:3–16

    Article  Google Scholar 

  • Zhang B, Pan X, Stellwag EJ (2008) Identification of soybean microRNAs and their targets. Planta 229:161–182. doi:10.1007/s00425-008-0818-x

    Article  Google Scholar 

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Authors and Affiliations

  1. Azul Natural S.A. de C.V, Durango, 34190, Mexico

    Sangita Chowdhury Paul & Sujay Paul

  2. Institute of Biotechnology, National Autonomous University of Mexico, Morelos, 62210, Mexico

    Sangita Chowdhury Paul

  3. School of Engineering and Sciences, Monterrey Institute of Technology and Higher Education, Querétaro, 76130, Mexico

    Ashutosh Sharma

  4. Biotechnology Research Center (CEIB), Autonomous University of Mexico State, Cuernavaca, 62209, Mexico

    Richa Mehta

  5. Division of Plant Biology, Bose Institute, Kolkata, 700054, India

    Sujay Paul

Authors
  1. Sangita Chowdhury Paul
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  2. Ashutosh Sharma
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  3. Richa Mehta
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  4. Sujay Paul
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Correspondence to Sujay Paul.

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Paul, S.C., Sharma, A., Mehta, R. et al. Genome Wide Computational Identification of Tuna (Thunnus orientalis) MicroRNAs and Their Targets. Ocean Sci. J. 53, 727–734 (2018). https://doi.org/10.1007/s12601-018-0041-z

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  • DOI: https://doi.org/10.1007/s12601-018-0041-z

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