Skip to content
2000
image of An Analysis of the Interactions between the 5' UTR and Introns in Mitochondrial Ribosomal Protein Genes

Abstract

Background

The 5' UTR plays a crucial role in gene regulation, which may be through its interaction with introns. Hence, there is a need to further study this interaction.

Objective

This study aimed to investigate the interactions between 5' UTR and introns and their correlation with species evolution.

Methods

The optimally matched segments between 5' UTR and introns were identified using Smith-Waterman local similarity matching, and the biological statistical methods were applied to compare the optimally matched segments between different species.

Results

The interactions between 5' UTR and introns were found to be primarily mediated by weak bonds and demonstrated a directional change with species evolution. Additionally, a large proportion of the optimally matched segments were very similar to miRNA and siRNA in terms of length and matching rate characteristics.

Conclusion

The weak bonds in the interactions between the 5' UTR and the introns could enhance the flexibility of expression regulation, and an important correlation was found between the characteristic distributions of the optimally matched segments and species evolution. Additionally, the length and matching rate of a large proportion of optimally matched segments were very similar to those of miRNA and siRNA. In conclusion, it is highly probable that quite a few of the optimally matched segments are some kinds of functional non-coding RNAs.

Loading

Article metrics loading...

/content/journals/cbio/10.2174/0115748936357583250207100102
2025-02-10
2025-05-04
Loading full text...

Full text loading...

References

  1. Chu Y. Yu D. Li Y. Huang K. Shen Y. Cong L. Zhang J. Wang M. A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions. Nat. Mach. Intell. 2024 6 4 449 460 10.1038/s42256‑024‑00823‑9 38855263
    [Google Scholar]
  2. Ryczek N. Łyś A. Makałowska I. The functional meaning of 5′ UTR in protein-coding genes. Int. J. Mol. Sci. 2023 24 3 2976 10.3390/ijms24032976 36769304
    [Google Scholar]
  3. Weber R. Ghoshdastider U. Spies D. Duré C. Valdivia-Francia F. Forny M. Ormiston M. Renz P.F. Taborsky D. Yigit M. Bernasconi M. Yamahachi H. Sendoel A. Monitoring the 5′UTR landscape reveals isoform switches to drive translational efficiencies in cancer. Oncogene 2023 42 9 638 650 10.1038/s41388‑022‑02578‑2 36550360
    [Google Scholar]
  4. Tietze L. Lale R. Importance of the 5′ regulatory region to bacterial synthetic biology applications. Microb. Biotechnol. 2021 14 6 2291 2315 10.1111/1751‑7915.13868 34171170
    [Google Scholar]
  5. Jia R. Li Z. Wang X. Poly(rC) binding protein 1 represses the translation of STAT3 through 5′ UTR. Curr. Gene Ther. 2022 22 5 397 405 10.2174/1566523222666220511162934 35549870
    [Google Scholar]
  6. Wang H. Li A. Bian H. Jin L. Ma S. Wang H. Yang Y. Bravo A. Soberón M. Liu K. Transcriptional regulation of Cry2Ab toxin receptor ABCA2 gene in insects involves GATAe and splicing of a 5′ UTR intron. Pestic. Biochem. Physiol. 2024 206 106211 10.1016/j.pestbp.2024.106211 39672621
    [Google Scholar]
  7. Shah H. Khan K. Badshah Y. Mahmood Ashraf N. Shabbir M. Trembley J.H. Afsar T. Abusharha A. Razak S. Investigation of UTR variants by computational approaches reveals their functional significance in PRKCI gene regulation. Genes 2023 14 2 247 10.3390/genes14020247 36833174
    [Google Scholar]
  8. Wongfieng W. Jumnainsong A. Chamgramol Y. Sripa B. Leelayuwat C. 5′ UTR and 3′ UTR regulation of MICB expression in Human cancer cells by novel microRNAs. Genes (Basel) 2017 8 9 213 10.3390/genes8090213 28850101
    [Google Scholar]
  9. Lakshmi Jayaraj K. Thulasidharan N. Antony A. John M. Augustine R. Chakravartty N. Sukumaran S. Uma Maheswari M. Abraham S. Thomas G. Lachagari V.B.R. Seshagiri S. Narayanan S. Kuriakose B. Targeted editing of tomato carotenoid isomerase reveals the role of 5′ UTR region in gene expression regulation. Plant Cell Rep. 2021 40 4 621 635 10.1007/s00299‑020‑02659‑0 33449143
    [Google Scholar]
  10. Dossa K. Zhou R. Li D. Liu A. Qin L. Mmadi M.A. Su R. Zhang Y. Wang J. Gao Y. Zhang X. You J. A novel motif in the 5′‐UTR of an orphan gene ‘ Big Root Biomass ’ modulates root biomass in sesame. Plant Biotechnol. J. 2021 19 5 1065 1079 10.1111/pbi.13531 33369837
    [Google Scholar]
  11. Kim W. Shin J.C. Lee K.H. Kim K.T. PTBP1 positively regulates the translation of circadian clock gene, Period1. Int. J. Mol. Sci. 2020 21 18 6921 10.3390/ijms21186921 32967200
    [Google Scholar]
  12. Jia L. Mao Y. Ji Q. Dersh D. Yewdell J.W. Qian S.B. Decoding mRNA translatability and stability from the 5′ UTR. Nat. Struct. Mol. Biol. 2020 27 9 814 821 10.1038/s41594‑020‑0465‑x 32719458
    [Google Scholar]
  13. Wang D. Yang C. Deng Y. Cao X. Xu W. Han Z. Li Q. Yang Y. Yuan X. Conserved RNA secondary structure in Cherry virus A 5′-UTR associated with translation regulation. Virol. J. 2022 19 1 91 10.1186/s12985‑022‑01824‑z 35619168
    [Google Scholar]
  14. Kan Q. Li Q. Post-transcriptional and translational regulation of plant gene expression by transposons. Curr. Opin. Plant Biol. 2023 75 102438 10.1016/j.pbi.2023.102438 37619514
    [Google Scholar]
  15. Lee C.Y. Joshi M. Wang A. Myong S. 5′UTR G-quadruplex structure enhances translation in size dependent manner. Nat. Commun. 2024 15 1 3963 10.1038/s41467‑024‑48247‑8 38729943
    [Google Scholar]
  16. Mutsuro-Aoki H. Teramura H. Tamukai R. Fukui M. Kusano H. Schepetilnikov M. Ryabova L.A. Shimada H. Dissection of a rice OsMac1 mRNA 5′ UTR to uncover regulatory nlms that are responsible for its efficient translation. PLoS One 2021 16 7 e0253488 10.1371/journal.pone.0253488 34242244
    [Google Scholar]
  17. Chowdhury I.R. Viktorova E. Samal S.K. Belov G.A. The effect of 5′ and 3′ non-translated regions on the expression of a transgene from a Newcastle disease virus vector. Virus Res. 2024 341 199309 10.1016/j.virusres.2024.199309 38181903
    [Google Scholar]
  18. Luo L. Jea J.D.Y. Wang Y. Chao P.W. Yen L. Control of mammalian gene expression by modulation of polyA signal cleavage at 5′ UTR. Nat. Biotechnol. 2024 42 9 1454 1466 10.1038/s41587‑023‑01989‑0 38168982
    [Google Scholar]
  19. Zuccotti P. Peroni D. Potrich V. Quattrone A. Dassi E. Hyperconserved nlms in Human 5′ UTRs shape essential post-transcriptional regulatory networks. Front. Mol. Biosci. 2020 7 220 10.3389/fmolb.2020.00220 33005630
    [Google Scholar]
  20. Li R. Song X. Gao S. Peng S. Analysis on the interactions between the first introns and other introns in mitochondrial ribosomal protein genes. Front. Microbiol. 2022 13 1091698 10.3389/fmicb.2022.1091698 36569058
    [Google Scholar]
  21. Bo S. Li H. Zhang Q. Lu Z. Bao T. Zhao X. Potential relations between post-spliced introns and mature mRNAs in the Caenorhabditis elegans genome. J. Theor. Biol. 2019 467 7 14 10.1016/j.jtbi.2019.01.031 30710554
    [Google Scholar]
  22. Zhang Q. Li H. Zhao X. Zheng Y. Zhou D. Distribution bias of the sequence matching between exons and introns in exon joint and EJC binding region in C. elegans. J. Theor. Biol. 2015 364 295 304 10.1016/j.jtbi.2014.09.009 25234235
    [Google Scholar]
  23. Zhang Q. Li H. Zhao X. Zheng Y. Meng H. Jia Y. Xue H. Bo S. Analysis on the preference for sequence matching between mRNA sequences and the corresponding introns in ribosomal protein genes. J. Theor. Biol. 2016 392 113 121 10.1016/j.jtbi.2015.12.003 26707402
    [Google Scholar]
  24. Zhao X. Li H. Bao T. Analysis on the interaction between post-spliced introns and corresponding protein coding sequences in ribosomal protein genes. J. Theor. Biol. 2013 328 33 42 10.1016/j.jtbi.2013.03.002 23499990
    [Google Scholar]
  25. Zhang H. Wang Y. Tang X. Dou S. Sun Y. Zhang Q. Lu J. Combinatorial regulation of gene expression by uORFs and microRNAs in Drosophila. Sci. Bull. (Beijing) 2021 66 3 225 228 10.1016/j.scib.2020.10.012 36654327
    [Google Scholar]
  26. Zhang H. Zhou J. Li J. Wang Z. Chen Z. Lv Z. Ge L. Xie G. Deng G. Rui Y. Huang H. Chen L. Wang H. N6-methyladenosine promotes translation of VEGFA to accelerate angiogenesis in lung cancer. Cancer Res. 2023 83 13 2208 2225 10.1158/0008‑5472.CAN‑22‑2449 37103476
    [Google Scholar]
  27. Xue C. Qiu F. Wang Y. Li B. Zhao K.T. Chen K. Gao C. Tuning plant phenotypes by precise, graded downregulation of gene expression. Nat. Biotechnol. 2023 41 12 1758 1764 10.1038/s41587‑023‑01707‑w 36894598
    [Google Scholar]
  28. Nelson A.R. Henkin T.M. Agris P.F. tRNA regulation of gene expression: Interactions of an mRNA 5′-UTR with a regulatory tRNA. RNA 2006 12 7 1254 1261 10.1261/rna.29906 16741230
    [Google Scholar]
  29. Ignatov D. Vaitkevicius K. Durand S. Cahoon L. Sandberg S.S. Liu X. Kallipolitis B.H. Rydén P. Freitag N. Condon C. Johansson J. An mRNA-mRNA interaction couples expression of a virulence factor and its chaperone in Listeria monocytogenes. Cell Rep. 2020 30 12 4027 4040.e7 10.1016/j.celrep.2020.03.006 32209466
    [Google Scholar]
  30. Podlaski F. Cornwell S. Wong K. McKittrick B. Kim J.H. Jung D. Jeon Y. Jung K.B. Tolias P. Windsor W.T. Peptide nucleic acids containing cationic or amino-alkyl modified bases promote enhanced hybridization kinetics and thermodynamics with single-strand DNA. ACS Omega 2023 8 37 33426 33436 10.1021/acsomega.3c03184 37744819
    [Google Scholar]
  31. Abraham Punnoose J. Thomas K.J. Chandrasekaran A.R. Vilcapoma J. Hayden A. Kilpatrick K. Vangaveti S. Chen A. Banco T. Halvorsen K. High-throughput single-molecule quantification of individual base stacking energies in nucleic acids. Nat. Commun. 2023 14 1 631 10.1038/s41467‑023‑36373‑8 36746949
    [Google Scholar]
  32. Nguyen H.A. Hoffer E.D. Dunham C.M. Importance of a tRNA anticodon loop modification and a conserved, noncanonical anticodon stem pairing in tRNACGGPro for decoding. J. Biol. Chem. 2019 294 14 5281 5291 10.1074/jbc.RA119.007410 30782843
    [Google Scholar]
  33. Mahmoudi-Lamouki R. Kadkhoda S. Hussen B.M. Ghafouri-Fard S. Emerging role of miRNAs in the regulation of ferroptosis. Front. Mol. Biosci. 2023 10 1115996 10.3389/fmolb.2023.1115996 36876051
    [Google Scholar]
  34. Chen M. Medarova Z. Moore A. Role of microRNAs in glioblastoma. Oncotarget 2021 12 17 1707 1723 10.18632/oncotarget.28039 34434499
    [Google Scholar]
  35. Statello L. Guo C.J. Chen L.L. Huarte M. Gene regulation by long non-coding RNAs and its biological functions. Nat. Rev. Mol. Cell Biol. 2021 22 2 96 118 10.1038/s41580‑020‑00315‑9 33353982
    [Google Scholar]
  36. Sanchez Calle A. Kawamura Y. Yamamoto Y. Takeshita F. Ochiya T. Emerging roles of long non‐coding RNA in cancer. Cancer Sci. 2018 109 7 2093 2100 10.1111/cas.13642 29774630
    [Google Scholar]
  37. Hu B. Zhong L. Weng Y. Peng L. Huang Y. Zhao Y. Liang X.J. Therapeutic siRNA: State of the art. Signal Transduct. Target. Ther. 2020 5 1 101 10.1038/s41392‑020‑0207‑x 32561705
    [Google Scholar]
  38. Burghgraeve N. Simon S. Barral S. Fobis-Loisy I. Holl A.C. Ponitzki C. Schmitt E. Vekemans X. Castric V. Base-pairing requirements for small RNA-mediated gene silencing of recessive self-incompatibility alleles in Arabidopsis halleri. Genetics 2020 215 3 653 664 10.1534/genetics.120.303351 32461267
    [Google Scholar]
  39. Deogharia M. Gurha P. The “guiding” principles of noncoding RNA function. Wiley Interdiscip. Rev. RNA 2022 13 4 e1704 10.1002/wrna.1704 34856642
    [Google Scholar]
  40. Betting V. Joosten J. Halbach R. Thaler M. Miesen P. Van Rij R.P. A piRNA-lncRNA regulatory network initiates responder and trailer piRNA formation during mosquito embryonic development. RNA 2021 27 10 1155 1172 10.1261/rna.078876.121 34210890
    [Google Scholar]
  41. Yoshihama M. Uechi T. Asakawa S. Kawasaki K. Kato S. Higa S. Maeda N. Minoshima S. Tanaka T. Shimizu N. Kenmochi N. The human ribosomal protein genes: Sequencing and comparative analysis of 73 genes. Genome. Res. 2002 12 3 379 390 10.1101/gr.214202 11875025
    [Google Scholar]
  42. Zhang Q. Li H. Zhao X. Xue H. Zheng Y. Meng H. Jia Y. Bo S. The evolution mechanism of intron length. Genomics 2016 108 2 47 55 10.1016/j.ygeno.2016.07.004 27449197
    [Google Scholar]
  43. Cui J.G. Zhao Y. Sethi P. Li Y.Y. Mahta A. Culicchia F. Lukiw W.J. Micro-RNA-128 (miRNA-128) down-regulation in glioblastoma targets ARP5 (ANGPTL6), Bmi-1 and E2F-3a, key regulators of brain cell proliferation. J. Neurooncol. 2010 98 3 297 304 10.1007/s11060‑009‑0077‑0 19941032
    [Google Scholar]
  44. Volpe T.A. Kidner C. Hall I.M. Teng G. Grewal S.I.S. Martienssen R.A. Regulation of heterochromatic silencing and histone H3 lysine-9 methylation by RNAi. Science 2002 297 5588 1833 1837 10.1126/science.1074973 12193640
    [Google Scholar]
  45. Lim LP Lau NC Garrett-Engele P Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 2005 433 7027 769 10.1038/nature03315
    [Google Scholar]
  46. Friman E.T. Flyamer I.M. Marenduzzo D. Boyle S. Bickmore W.A. Ultra-long-range interactions between active regulatory nlms. Genome Res. 2023 33 8 1269 1283 10.1101/gr.277567.122 37451823
    [Google Scholar]
  47. Knanghat R. Senapati S. Toward greater DNA stability by leveraging the proton-donating ability of protic ionic liquids. J. Phys. Chem. B 2024 128 18 4301 4314 10.1021/acs.jpcb.3c08479 38682809
    [Google Scholar]
  48. Szatyłowicz H. Sadlej-Sosnowska N. Characterizing the strength of individual hydrogen bonds in DNA base pairs. J. Chem. Inf. Model. 2010 50 12 2151 2161 10.1021/ci100288h 21090609
    [Google Scholar]
  49. Mak C.H. Hydration waters make up for the missing third hydrogen bond in the A·T base pair. ACS Phys. Chem. Au 2024 4 2 180 190 10.1021/acsphyschemau.3c00058 38560756
    [Google Scholar]
  50. Bhai S. Ganguly B. Role of pH in the stability of cytosine-cytosine mismatch and canonical AT and GC base pairs mediated with silver ion: A DFT study. Struct. Chem. 2022 33 1 35 47 10.1007/s11224‑021‑01814‑x
    [Google Scholar]
  51. Gu M. Yi X. Xiao Y. Zhang J. Lin M. Xia F. Programming the dynamic range of nanobiosensors with engineering poly-adenine-mediated spherical nucleic acid. Talanta 2023 256 124278 10.1016/j.talanta.2023.124278 36681039
    [Google Scholar]
  52. Ghosh S. Takahashi S. Ohyama T. Liu L. Sugimoto N. Elucidating the role of groove hydration on stability and functions of biased DNA duplexes in cell-like chemical environments. J. Am. Chem. Soc. 2024 146 47 32479 32497 10.1021/jacs.4c09388 39505325
    [Google Scholar]
  53. Xing H. Wigham C. Lee S.R. Pereira A.J. de Campos L.J. Picco A.S. Huck-Iriart C. Escudero C. Perez-Chirinos L. Gajaweera S. Comer J. Sasselli I.R. Stupp S.I. Zha R.H. Conda-Sheridan M. Enhanced hydrogen bonding by urea functionalization tunes the stability and biological properties of peptide amphiphiles. Biomacromolecules 2024 25 5 2823 2837 10.1021/acs.biomac.3c01463 38602228
    [Google Scholar]
  54. Long R. Guo Z. Han D. Liu B. Yuan X. Chen G. Heng P.A. Zhang L. siRNADiscovery: A graph neural network for siRNA efficacy prediction via deep RNA sequence analysis. Brief. Bioinform. 2024 25 6 bbae563 10.1093/bib/bbae563 39503523
    [Google Scholar]
  55. Pasquinelli A.E. MicroRNAs and their targets: Recognition, regulation and an emerging reciprocal relationship. Nat. Rev. Genet. 2012 13 4 271 282 10.1038/nrg3162 22411466
    [Google Scholar]
  56. Shang R. Lee S. Senavirathne G. Lai E.C. microRNAs in action: Biogenesis, function and regulation. Nat. Rev. Genet. 2023 24 12 816 833 10.1038/s41576‑023‑00611‑y 37380761
    [Google Scholar]
  57. Riolo G. Cantara S. Marzocchi C. Ricci C. miRNA targets: From prediction tools to experimental validation. Methods Protoc. 2020 4 1 1 10.3390/mps4010001 33374478
    [Google Scholar]
  58. Gu D. Ahn S.H. Eom S. Lee H.S. Ham J. Lee D.H. Cho Y.K. Koh Y. Ignatova E. Jang E.S. Chi S.W. AGO-accessible anticancer siRNAs designed with synergistic miRNA-like activity. Mol. Ther. Nucleic Acids 2021 23 1172 1190 10.1016/j.omtn.2021.01.018 33664996
    [Google Scholar]
  59. Farberov L. Ionescu A. Zoabi Y. Shapira G. Ibraheem A. Azan Y. Perlson E. Shomron N. Multiple copies of microRNA binding sites in long 3′ UTR variants regulate axonal translation. Cells 2023 12 2 233 10.3390/cells12020233 36672174
    [Google Scholar]
  60. O’ Lee D.J. Introducing a model of pairing based on base pair specific interactions between identical DNA sequences. J. Phys. Condens. Matter 2018 30 7 075102 10.1088/1361‑648X/aaa043 29219116
    [Google Scholar]
  61. Li R. Mak C.H. A deep dive into DNA base pairing interactions under water. J. Phys. Chem. B 2020 124 27 5559 5570 10.1021/acs.jpcb.0c03069 32525678
    [Google Scholar]
  62. Nemes K. Gil J.F. Liebe S. Mansi M. Poimenopoulou E. Lennefors B.L. Varrelmann M. Savenkov E.I. Intermolecular base‐pairing interactions, a unique topology and exoribonuclease‐resistant noncoding RNAs drive formation of viral chimeric RNAs in plants. New Phytol. 2024 241 2 861 877 10.1111/nph.19346 37897070
    [Google Scholar]
  63. Mondal M. Gao Y.Q. Sequence‐dependent clustering properties of nucleotides fragments in an ionic solution. J. Chin. Chem. Soc. (Taipei) 2023 70 3 297 316 10.1002/jccs.202200425
    [Google Scholar]
  64. Li J. Sun X. Lv M. Han Z. Zhong X. Zhang W. Hu R. Feng W. Ma M. Huang Q. Zhou X. ncRNA-mediated SOX4 overexpression correlates with unfavorable outcomes and immune infiltration in hepatocellular carcinoma. BMC Gastroenterol. 2024 24 1 265 10.1186/s12876‑024‑03346‑0 39143462
    [Google Scholar]
  65. Sun Y. Liu X. Shan X. Wang Y. Zhong C. Lu C. Guan B. Yao S. Huo Y. Sun R. Wei M. Dong Z. Comprehensive investigation of differentially expressed ncRNAs, mRNAs, and their ceRNA networks in the regulation of shell color formation in clam, Cyclina sinensis. Gene 2024 911 148346 10.1016/j.gene.2024.148346 38452877
    [Google Scholar]
  66. Zhu K. Wang T. Li S. Liu Z. Zhan Y. Zhang Q. NcRNA: Key and potential in hearing loss. Front. Neurosci. 2024 17 1333131 10.3389/fnins.2023.1333131 38298898
    [Google Scholar]
/content/journals/cbio/10.2174/0115748936357583250207100102
Loading
/content/journals/cbio/10.2174/0115748936357583250207100102
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test