Identifying Origin of Replication (ORI) sites in genomic sequence using Python-based programming and Motif analysis in Bioinformatics

Year : 2024 | Volume : | : | Page : –
By
vector

Kashif Raza Siddique,

  1. Student, Department of Biotechnology, Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, India

Abstract document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_112468’);});Edit Abstract & Keyword

ORI sites serve a critical function in DNA replication serving as the beginning point of the process. Identifying the spots appropriately means a lot and is important for the biologists working in the lab. Detecting the ORI is not only vital for the detection of replication sites but is also important in numerous biological processes. In this study, we offer a unique approach employing Python-based motif analysis to discover the ORI sites within the supplied genomic sequence. It also highlights the problems of finding the ORI site and what are the alternatives. The sequence of the nucleotides or the genome sequence of the organisms that are utilized in this study as a reference for the detection of ORI has been supplied in the reference section. In this study, we discuss the method will discovering the ORI of different organisms, we also share open-source Python programs and the genomic sequence that we utilized while completing this research. This research contributes to advance the field of bioinformatics by establishing a user-friendly framework for ORI site discovery, simplifying key exploration into DNA replication mechanisms and genome dynamics. In this paper, we have also spoken about the motif and the features. Also defined the circadian cycle and gene expressions and talked about the evening elements. Using skew arrays will increase the results and it will undoubtedly aid in detecting the ORI of complicated organisms like E. coli.

Keywords: ORI sites, DNA replication, Python-based motif analysis, Genome sequence, Bioinformatics

How to cite this article:
Kashif Raza Siddique. Identifying Origin of Replication (ORI) sites in genomic sequence using Python-based programming and Motif analysis in Bioinformatics. Research & Reviews: A Journal of Bioinformatics. 2024; ():-.
How to cite this URL:
Kashif Raza Siddique. Identifying Origin of Replication (ORI) sites in genomic sequence using Python-based programming and Motif analysis in Bioinformatics. Research & Reviews: A Journal of Bioinformatics. 2024; ():-. Available from: https://journals.stmjournals.com/rrjobi/article=2024/view=0

Full Text PDF

Full Text PDF

References
document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_ref_112468’);});Edit

  1. Jacob F, Brenner S, Cuzin F. On the regulation of DNA replication in bacteria. Cold Spring Harb Symp Quant Biol. 1963; 28:329-48. https://doi.org/10.1101/sqb.1963.028.01.048.
  2. Messer W. The bacterial replication initiator DnaA. DnaA and oriC, the bacterial mode to initiate DNA replication. FEMS Microbiol Rev. 2002; 26:355-74. https://doi.org/10.1111/j.1574-6976.2002.tb00620.x.
  3. Harrison PW, Lower RP, Kim NK, Young JPW. Introducing the bacterial ‘chromid’: not a chromosome, not a plasmid. Trends Microbiol. 2010; 18:141-8. https://doi.org/10.1016/j.tim.2009.12.010.
  4. Gao F. Bacteria may have multiple replication origins. Front Microbiol. 2015; 6:324. https://doi.org/10.3389/fmicb.2015.00324.
  5. Zakrzewska-Czerwińska J, Jakimowicz D, Zawilak-Pawlik A, Messer W. Regulation of the initiation of chromosomal replication in bacteria. FEMS Microbiol Rev. 2007; 31:378-87. https://doi.org/10.1111/j.1574-6976.2007.00070.x.
  6. Leonard AC, Grimwade JE. The orisome: structure and function. Front Microbiol. 2015; 6:545. https://doi.org/10.3389/fmicb.2015.00545.
  7. Krause M, Rückert B, Lurz R, Messer W. Complexes at the replication origin of Bacillus subtilis with homologous and heterologous DnaA protein. J Mol Biol. 1997; 274:365-80. https://doi.org/10.1006/jmbi.1997.1404.
  8. Brilli M, Fani R, Mengoni A, Ferri L, Bazzicalupo M, Biondi EG, et al. The diversity and evolution of cell cycle regulation in alpha-proteobacteria: a comparative genomic analysis. BMC Syst Biol. 2010; 4:52. https://doi.org/10.1186/1752-0509-4-52.
  9. Jaworski P, Zakrzewska-Czerwińska J, Zawilak-Pawlik A, Nowaczyk M, Weigel C, Messer W. Unique and universal features of epsilon proteobacteria origins of chromosome replication and DnaA-DnaA box interactions. Front Microbiol. 2016; 7:1555. https://doi.org/10.3389/fmicb.2016.01555.
  10. Richardson TT, Harran O, Murray H. The bacterial DnaA-trio replication origin element specifies single-stranded DNA initiator binding. Nature. 2016; 534:412-6. https://doi.org/10.1038/nature17962.
  11. Ryan VT, Grimwade JE, Camara JE, Crooke E, Leonard AC. Escherichia coli prereplication complex assembly is regulated by the dynamic interplay among fis, IHF, and DnaA. Mol Microbiol. 2004; 51:1347-59. https://doi.org/10.1046/j.1365-2958.2003.03906.x.
  12. Bramhill D, Kornberg A. Duplex opening by dnaA protein at novel sequences in the initiation of replication at the origin of the E. coli chromosome. Cell. 1988; 52:743-55. https://doi.org/10.1016/0092-8674(88)90412-6.
  13. Kowalski D, Eddy MJ. The DNA unwinding element: a novel, cis-acting component that facilitates the opening of the Escherichia coli replication origin. EMBO J. 1989; 8:4335-44.
  14. Marczynski GT, Rolain T, Taylor JA. Redefining bacterial origins of replication as centralized information processors. Front Microbiol. 2015; 6:610. https://doi.org/10.3389/fmicb.2015.00610.
  15. Song C, Zhang S, Huang H. Choosing a suitable method for the identification of replication origins in microbial genomes. Front Microbiol. 2015; 6:1049. https://doi.org/10.3389/fmicb.2015.01049.
  16. Song J, Ware A, Liu S-L. Wavelet to predict bacterial ori and ter: a tendency towards a physical balance. BMC Genomics. 2003; 4:17. https://doi.org/10.1186/1471-2164-4-17.
  17. Gao F, Zhang C-T. Ori-finder: a web-based system for finding oriCs in unannotated bacterial genomes. BMC Bioinformatics. 2008;9:79. https://doi.org/10.1186/1471-2105-9-79.
  18. Kundal S, Lohiya R, Shah K. iCorr: Complex correlation method to detect the origin of replication in prokaryotic and eukaryotic genomes. arXiv. 2016.
  19. Maderankova D, Sedlar K, Vitek M, Skutkova H. The identification of replication origin in bacterial genomes by cumulated phase signal. In: 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE; 2017. https://doi.org/10.1109/cibcb.2017.8058561.
  20. Zhang G, Gao F. Quantitative analysis of the correlation between AT and GC biases among bacterial genomes. PLoS One. 2017;12 https://doi.org/10.1371/journal.pone.0171408.
  21. Lobry J. A simple vectorial representation of DNA sequences for the detection of replication origins in bacteria. Biochimie. 1996;78:323-6. https://doi.org/10.1016/0300-9084(96)84764-x.
  22. Mackiewicz P. Where does bacterial replication start? Rules for predicting the oriC region. Nucleic Acids Res. 2004;32:3781-91. https://doi.org/10.1093/nar/gkh699.
  23. Luo H, Zhang C-T, Gao F. Ori-finder 2, an integrated tool to predict replication origins in the archaeal genomes. Front Microbiol. 2014; 5:482. https://doi.org/10.3389/fmicb.2014.00482.
  24. Gao F, Zhang C-T. DoriC: a database of oriC regions in bacterial genomes. Bioinformatics. 2007; 23:1866-7. https://doi.org/10.1093/bioinformatics/btm255.
  25. Gao F, Luo H, Zhang C-T. DoriC 5.0: an updated database of oriC regions in both bacterial and archaeal genomes. Nucleic Acids Res. 2012;41 https://doi.org/10.1093/nar/gks990.
Ahead of Print Subscription Review Article
Volume
Received 10/03/2024
Accepted 26/04/2024
Published 11/11/2024
208