Characterizing exons and introns by regularity of nucleotide strings

详细信息    查看全文

• 作者：Tonya Woods ; Thanawadee Preeprem ; Kichun Lee ; Woojin Chang…
• 关键词：Regularity ; Cumulative evolutionary slope ; Exons ; Introns ; Wavelets
• 刊名：Biology Direct
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：11
• 期：1
• 全文大小：2,122 KB
• 参考文献：1.Hou Y, Lin S. Insights into social insects from the genome of the honeybee Apis mellifera. PLoS ONE. 2009; 4(9):6978. doi:10.​1371/​journal.​pone.​0006978 .CrossRef
  2.Wong GK-S, Passey DA, Huang Y-z, Yang Z, Yu J. Is “Junk” DNA mostly intron DNA?Genome Res. 2000; 10(11):1672–8.PubMedCentral CrossRef PubMed
  3.Chorev M, Carmel L. The function of introns. Front Genet. 2012; 3(55):1–15.
  4.Zhu L, Zhang Y, Zhang W, Yang S, Chen JQ, Tian D. Patterns of exon-intron architecture variation of genes in eukaryotic genomes. BMC Genomics. 2009; 10(1):47.PubMedCentral CrossRef PubMed
  5.Haimovich AD, Byrne B, Ramaswamy R, Welsh WJ. Wavelet analysis of DNA walks. J Comput Biol. 2006; 13(7):1289–98.CrossRef PubMed
  6.Ieviņa N, Chipens G, Kalvinsh I. Internal regularity and quantization of gene parameters. Acta Universitatis Latviensis. 2006; 710(1):139–53.
  7.Paxia S, Rudra A, Zhou Y, Mishra B. A random walk down the genomes: DNA evolution in valis. Computer. 2002; 35(7):73–9.CrossRef
  8.Peng CK, Buldyrev S, Goldberger A, Havlin S, Sciortino F, Simons M, Stanley H. Long-range correlations in nucleotide sequences. Nature. 1992; 356(1):168–70.CrossRef PubMed
  9.Buldyrev S, Goldberger A, Havlin S, Mantegna R, Matsa M, Peng CK, et al.Long-range correlation properties of coding and noncoding DNA sequences: Genbank analysis. Phys Rev E. 1995; 51(5):5084.CrossRef
  10.Boekhorst RT, Abnizova I, Nehaniv C. Discriminating coding, non-coding and regulatory regions using rescaled range and detrended fluctuation analysis. BioSystems. 2008; 91(1):183–94.CrossRef
  11.Stoffer DS, Tyler DE, Wendt DA. The spectral envelope and its applications. Stat Sci. 2000; 15(3):224–253.CrossRef
  12.Voss RF. Evolution of long-range fractal correlations and 1/f noise in DNA base sequences. Phys Rev Lett. 1992; 68(25):3805.CrossRef PubMed
  13.Afreixo V, Ferreira PJ, Santos D. Fourier analysis of symbolic data: a brief review. Digital Signal Process. 2004; 14(6):523–30.CrossRef
  14.Yin C, Yau SS-T. Prediction of protein coding regions by the 3-base periodicity analysis of a DNA sequence. J Theor Biol. 2007; 247(4):687–94.CrossRef PubMed
  15.Cattani C, Scalia M, Mattioli G. Entropy distribution and information content in DNA sequences. In: International Conference on Potential Theory and Complex Analysis: 2006. p. 8–11.
  16.Bai FL, Liu YZ, Wang TM. A representation of DNA primary sequences by random walk. Math Biosci. 2007; 209(1):282–91.CrossRef PubMed
  17.Arneodo A, Vaillant C, Audit B, Argoul F, d’Aubenton-Carafa Y, Thermes C. Multi-scale coding of genomic information: From DNA sequence to genome structure and function. Phys Rep. 2011; 498(2):45–188.CrossRef
  18.Pinho AJ, Neves AJ, Afreixo V, Bastos CA, Ferreira PJS. A three-state model for DNA protein-coding regions. Biomed Engi IEEE Trans. 2006; 53(11):2148–55.CrossRef
  19.Mallat S. A Wavelet Tour of Signal Processing: The Sparse Way. Waltham, MA: Academic Press; 2008.
  20.Vidakovic B, Vol. 503. Statistical Modeling by Wavelets. Hoboken, NJ: John Wiley & Sons; 1999.CrossRef
  21.2-D wavelet-based spectra with applications. Comput Stat Data Anal. 2011; 55(1):738–51.
  22.Ramírez-Cobo P, Lee KS, Molini A, Porporato A, Katul G, Vidakovic B. A wavelet-based spectral method for extracting self-similarity measures in time-varying two-dimensional rainfall maps. J Time Series Anal. 2011; 32(4):351–63.CrossRef
  23.The Honeybee Genome Sequencing Consortium. Insights into social insects from the genome of the honeybee Apis mellifera. Nature. 2006; 443(26):931–49.PubMedCentral
  24.Elder D. Split gene origin and periodic introns. J Theor Biol. 2000; 207(1):455–72.CrossRef PubMed
  
• 作者单位：Tonya Woods (1)
  Thanawadee Preeprem (2)
  Kichun Lee (3)
  Woojin Chang (4)
  Brani Vidakovic (1)
  
  1. H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive NW, Atlanta, 30332, USA
  2. Faculty of Pharmaceutical Sciences, Ubon Ratchathani University, Ubon Ratchathani, Thailand
  3. Hanyang University, Seoul, Korea
  4. Seoul National University, Seoul, Korea
  
• 刊物主题：Life Sciences, general;
• 出版者：BioMed Central
• ISSN：1745-6150

文摘

Background Translation of nucleotides into a numeric form has been approached in many ways and has allowed researchers to investigate the properties of protein-coding sequences and noncoding sequences. Typically, more pronounced long-range correlations and increased regularity were found in intron-containing genes and in non-transcribed regulatory DNA sequences, compared to cDNA sequences or intron-less genes. The regularity is assessed by spectral tools defined on numerical translates. In most popular approaches of numerical translation the resulting spectra depend on the assignment of numerical values to nucleotides. Our contribution is to propose and illustrate a spectra which remains invariant to the translation rules used in traditional approaches.