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Bayesian analysis of plant DNA size distribution via non-additive statistics

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Abstract

We report an analysis of Cucurbitaceae DNA species through a non-additive statistics formalism. Such formalisms encompass power-law correlations. Our analysis focuses on the distribution of the length of DNA bases. We compared two models for fitting the data, single and double q-exponentials, via Bayesian analysis. Our data set was retrieved from a catalog of proteins (NCBI). The results indicate that the short-range correlations, always present in coding DNA sequences, are appropriately captured through the double q-exponential, adequately describing the cumulative length distribution of DNA bases. We also found two very distinctive q-ranges for introns and exons for all chromosomes, for both Cucurbitaceae subspecies analyzed in this work.

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Data Availability Statement

The DNA code data that support the findings of this study are available in NCBI [43].

References

  1. H.J. Jeffrey, Nucl. Acids Res. 18, 2163 (1990)

    Article  Google Scholar 

  2. A. Kocyan, L.-B. Zhang, H. Schaefer, S.S. Renner, Mol. Phylogenet. Evol. 44, 553 (2007)

    Article  Google Scholar 

  3. Y. Akashi, N. Fukuda, T. Wako, M. Masuda, K. Kato, Euphytica 125, 385 (2002)

    Article  Google Scholar 

  4. N. Dwivedi, O. Dhariwal, S.G. Krishnan, D. Bhandari, Genet. Resour. Crop Evol. 57, 443 (2010)

    Article  Google Scholar 

  5. P. Sebastian, H. Schaefer, I.R. Telford, S.S. Renner, Proc. Natl. Acad. Sci. 107, 14269 (2010)

    Article  ADS  Google Scholar 

  6. O.O. Lucky, U.O. John, I.E. Kate, O.O. Peter, O.E. Jude, Asian Pac. J. Trop. Biomed. 2, S1261 (2012)

    Article  Google Scholar 

  7. T. Tatlioglu, in Genetic Improvement of Vegetable Crops, (Elsevier, 1993) pp. 197–234

  8. J. D. Mccreight, H. Nerson, and R. Grumet, in Genetic Improvement of Vegetable Crops (Elsevier, 1993) pp. 267–294

  9. S. B. D. Melo et al., UFERSA (2015)

  10. J.-F. Chen, J.E. Staub, J. Jiang, Genet. Resour. Crop Evol. 45, 301 (1998)

    Article  Google Scholar 

  11. D.-H. Koo, Y. Hur, D.-C. Jin, J.-W. Bang, Mol. Cells 13, 413 (2002)

    Google Scholar 

  12. A. Singh, R. Roy, Caryologia 27, 153 (1974)

    Article  Google Scholar 

  13. R. Rp, Cytologia 35, 561 (1970)

    Article  Google Scholar 

  14. A. Ramachandran, P. Seshadri, Indian J. Lepr. 58, 623 (1986)

    Google Scholar 

  15. K. Arumuganathan, E. Earle, Plant Mol. Biol. Rep. 9, 208 (1991)

    Article  Google Scholar 

  16. P.F. Cavagnaro, D.A. Senalik, L. Yang, P.W. Simon, T.T. Harkins, C.D. Kodira, S. Huang, Y. Weng, BMC Genom. 11, 1 (2010)

    Article  Google Scholar 

  17. J. Garcia-Mas, A. Benjak, W. Sanseverino, M. Bourgeois, G. Mir, V.M. González, E. Hénaff, F. Câmara, L. Cozzuto, E. Lowy et al., Proc. Natl. Acad. Sci. 109, 11872 (2012)

    Article  ADS  Google Scholar 

  18. D. Li, H.E. Cuevas, L. Yang, Y. Li, J. Garcia-Mas, J. Zalapa, J.E. Staub, F. Luan, U. Reddy, X. He et al., BMC Genom. 12, 1 (2011)

    Article  Google Scholar 

  19. C.-K. Peng, S.V. Buldyrev, A.L. Goldberger, S. Havlin, F. Sciortino, M. Simons, H.E. Stanley, Nature 356, 168 (1992)

    Article  ADS  Google Scholar 

  20. W. Li, K. Kaneko, EPL (Europhys. Lett.) 17, 655 (1992)

    Article  ADS  Google Scholar 

  21. W. Li, Comput. Chem. 21, 257 (1997)

    Article  Google Scholar 

  22. A. Arneodo, E. Bacry, P. Graves, J.-F. Muzy, Phys. Rev. Lett. 74, 3293 (1995)

    Article  ADS  Google Scholar 

  23. A. Audit, C. Thermes, C. Vaillant, Phys. Rev. Lett. 86, 6 (2001)

    Article  Google Scholar 

  24. A. Colliva, R. Pellegrini, A. Testori, M. Caselle, Phys. Rev. E 91, 052703 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  25. A. Provata, Y. Almirantis, J. Stat. Phys. 106, 23 (2002)

    Article  Google Scholar 

  26. Y. Almirantis, A. Provata, J. Stat. Phys. 97, 233 (1999)

    Article  ADS  Google Scholar 

  27. A. Provata, Y. Almirantis, Fractals 8, 15 (2000)

    Article  Google Scholar 

  28. P. Katsaloulis, T. Theoharis, A. Provata, Phys. A 316, 380 (2002)

    Article  Google Scholar 

  29. P. Katsaloulis, T. Theoharis, W. Zheng, B. Hao, A. Bountis, Y. Almirantis, A. Provata, Phys. A 366, 308 (2006)

    Article  Google Scholar 

  30. A. Provata, T. Oikonomou, Phys. Rev. E 75, 056102 (2007)

    Article  ADS  Google Scholar 

  31. M. Gell-Mann and C. Tsallis, Nonextensive Entropy: Interdisciplinary Applications (Oxford University Press, 2004)

  32. G. Kaniadakis, Eur. Phys. J. B 70, 3 (2009)

    Article  ADS  MathSciNet  Google Scholar 

  33. T. Oikonomou, A. Provata, Eur. Phys. J. B-Condens. Matter Complex Syst. 50, 259 (2006)

    Article  Google Scholar 

  34. T. Oikonomou, A. Provata, U. Tirnakli, Phys. A 387, 2653 (2008)

    Article  Google Scholar 

  35. D. Moreira, E. Albuquerque, L. Da Silva, D. Galvao, Phys. A 387, 5477 (2008)

    Article  Google Scholar 

  36. E.L. Albuquerque, U. Fulco, V. Freire, E. Caetano, M. Lyra, F. de Moura, Phys. Rep. 535, 139 (2014)

    Article  ADS  MathSciNet  Google Scholar 

  37. R. Silva, J. Silva, D. Anselmo, J. Alcaniz, W. da Silva, M. Costa, Phys. A 545, 123735 (2020)

    Article  MathSciNet  Google Scholar 

  38. U. Von Toussaint, Rev. Mod. Phys. 83, 943 (2011)

    Article  ADS  Google Scholar 

  39. K.E. Hines, Biophys. J. 108, 2103 (2015)

    Article  ADS  Google Scholar 

  40. M.I. Bogachev, A.R. Kayumov, A. Bunde, PLoS ONE 9, e112534 (2014)

    Article  ADS  Google Scholar 

  41. C. Tsallis, J. Stat. Phys. 52, 479 (1988)

    Article  ADS  Google Scholar 

  42. C. Tsallis, Introduction to Nonextensive Statistical Mechanics: Approaching a Complex World (Springer Science and Business Media, 2009)

  43. National center for biotechnology information (ncbi), https://www.ncbi.nlm.nih.gov, accessed: 2021-06-17

  44. R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria ( 2020)

  45. P. G. Kinas and H. A. Andrade, Introdução à análise bayesiana (com R) (Consultor Editorial, 2017)

  46. F. Feroz, M.P. Hobson, Mon. Not. R. Astron. Soc. 384, 449 (2008)

    Article  ADS  Google Scholar 

  47. F. Feroz, M. Hobson, M. Bridges, Mon. Not. R. Astron. Soc. 398, 1601 (2009)

    Article  ADS  Google Scholar 

  48. F. Feroz, M. P. Hobson, E. Cameron, and A. N. Pettitt, arXiv preprint arXiv:1306.2144 ( 2013)

  49. J. Skilling, in AIP Conference Proceedings, Vol. 735 ( American Institute of Physics, 2004) pp. 395–405

  50. J. Buchner, A. Georgakakis, K. Nandra, L. Hsu, C. Rangel, M. Brightman, A. Merloni, M. Salvato, J. Donley, D. Kocevski, Astron. Astrophys. 564, A125 (2014)

    Article  ADS  Google Scholar 

  51. R. Trotta, Contemp. Phys. 49, 71 (2008)

    Article  ADS  Google Scholar 

  52. H. Jeffreys, The Theory of Probability (OUP Oxford, 1998)

  53. W. da Silva, R. Silva, Eur. Phys. J. Plus 136, 1 (2021)

    Article  ADS  Google Scholar 

Download references

Acknowledgements

The authors thank Dr. William J. da Silva for technical discussions on the Bayesian analysis. This study was financed in part by CNPq (Conselho Nacional de Desenvolvimento Científico e tecnológico) and by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES). RS thanks CNPq (Grant No. 307620/2019-0) for financial support.

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Authors and Affiliations

  1. Departamento de Física, Universidade do Estado do Rio Grande do Norte, Mossoró, 59610-210, Brazil

    M. M. F. de Lima, V. D. Mello & D. H. A. L. Anselmo

  2. Departamento de Física, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil

    R. Silva

  3. Departamento de Ciências Vegetais, Universidade Federal Rural do Semi-Árido, Mossoró, RN, 59625-900, Brazil

    G. H. Nunes S

  4. Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil

    U. L. Fulco

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  1. M. M. F. de Lima
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  3. R. Silva
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  4. U. L. Fulco
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  5. V. D. Mello
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Correspondence to D. H. A. L. Anselmo.

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de Lima, M.M.F., S, G.H.N., Silva, R. et al. Bayesian analysis of plant DNA size distribution via non-additive statistics. Eur. Phys. J. Plus 137, 495 (2022). https://doi.org/10.1140/epjp/s13360-022-02707-6

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