Informational polymers were born in the primitive Earth but nothing is known about the way(s) from which efficient prebiotic synthetic routes arose. However, in a possible scenario for the origin of life there was a time in which informational genetic polymers played primary roles. Possible ‘ fossils ’ of that primitive era (billions of years ago) may be considered the archaea domain (Howland 2000). Nucleotide sequence data of archaea genes and codifying mRNA in eukarya (mammals) were obtained from the Institute for Genomic Research (TIGR) and the GeneBank library (http://cmr. tigr.org/tigr-scripts/CMR/CmrHomePage.cgi. and http://www.ncbi. nlm.nih.gov/). Random sequence data (white noise) were obtained from the algorithm by Press & Teukolsky (1992). Nucleotide sequences were analysed as random walks, where each base represents a different step in a two-dimensional space; vice versa, the uniform and random distributed data points over the unit interval algorithm-generated were divided in 16 intervals to which A,C,G,T (U) letters were attributed. Nonlinear parameters (relative LZ complexity, largest Lyapunov exponent, Hurst exponent, correlation dimension, entropy, BDS statistic, Manhattan and Euclidean fractal dimensions) of nucleotide sequences and computer-generated random sequences were evaluated making use of Chaos Data Analyser (Sprott & Rowlands 1995) or Gates’ formulation (fractal dimensions (Gates 1986)). Our data show that the values of nonlinear parameters obtained from the archaea are lower than the values of randomly generated sequences (p<0.01) and higher than the values from eukarya (p<0.05). These data are in agreement with the ones by Weiss et al. (2000), showing a significant reduction of the Shannon entropy (x1%) in protein sequences compared to random polypeptides. Our results suggest that in the primitive Earth informational polymers might be originated from slightly edited random strings and that during biologic evolution the distance from pure randomness increased. Deviation from pure randomness should be arisen from some constraints like the secondary structure of the biologic macromolecules, and, in eukarya, from chromatin interactions, according to the neoselectionist theory of genome evolution (Bernardi 2007). Howland, J. L. The Surprising Archaea. Oxford University Press, 2000. Press, W. H. & Teukolsky, S. A. (1992). Portable random number generators. Comput. Phys. 6, 522–524. Sprott, J. C. & Rowlands, G. (1995). Chaos data Analyser. Physics Academic Software. Gates, M. A. (1986). A simple way to look at DNA. J. Theor. Biol. 119, 319–328. Weiis, O. et al. (2000). Information content of protein sequences. J. Theor. Biol. 206, 379–386. Bernardi, G. (2007). The neoselectionist theory of genome evolution. PNAS 104(20), 8385–8390.

Bianciardi, G. (2008). Information Polymers in the Primitive Earth: nonlinear analysis of archaea genomes and eukaryotic exons compared to computer-generated random sequences. INTERNATIONAL JOURNAL OF ASTROBIOLOGY, 7, 78-78.

Information Polymers in the Primitive Earth: nonlinear analysis of archaea genomes and eukaryotic exons compared to computer-generated random sequences

BIANCIARDI, GIORGIO
2008

Abstract

Informational polymers were born in the primitive Earth but nothing is known about the way(s) from which efficient prebiotic synthetic routes arose. However, in a possible scenario for the origin of life there was a time in which informational genetic polymers played primary roles. Possible ‘ fossils ’ of that primitive era (billions of years ago) may be considered the archaea domain (Howland 2000). Nucleotide sequence data of archaea genes and codifying mRNA in eukarya (mammals) were obtained from the Institute for Genomic Research (TIGR) and the GeneBank library (http://cmr. tigr.org/tigr-scripts/CMR/CmrHomePage.cgi. and http://www.ncbi. nlm.nih.gov/). Random sequence data (white noise) were obtained from the algorithm by Press & Teukolsky (1992). Nucleotide sequences were analysed as random walks, where each base represents a different step in a two-dimensional space; vice versa, the uniform and random distributed data points over the unit interval algorithm-generated were divided in 16 intervals to which A,C,G,T (U) letters were attributed. Nonlinear parameters (relative LZ complexity, largest Lyapunov exponent, Hurst exponent, correlation dimension, entropy, BDS statistic, Manhattan and Euclidean fractal dimensions) of nucleotide sequences and computer-generated random sequences were evaluated making use of Chaos Data Analyser (Sprott & Rowlands 1995) or Gates’ formulation (fractal dimensions (Gates 1986)). Our data show that the values of nonlinear parameters obtained from the archaea are lower than the values of randomly generated sequences (p<0.01) and higher than the values from eukarya (p<0.05). These data are in agreement with the ones by Weiss et al. (2000), showing a significant reduction of the Shannon entropy (x1%) in protein sequences compared to random polypeptides. Our results suggest that in the primitive Earth informational polymers might be originated from slightly edited random strings and that during biologic evolution the distance from pure randomness increased. Deviation from pure randomness should be arisen from some constraints like the secondary structure of the biologic macromolecules, and, in eukarya, from chromatin interactions, according to the neoselectionist theory of genome evolution (Bernardi 2007). Howland, J. L. The Surprising Archaea. Oxford University Press, 2000. Press, W. H. & Teukolsky, S. A. (1992). Portable random number generators. Comput. Phys. 6, 522–524. Sprott, J. C. & Rowlands, G. (1995). Chaos data Analyser. Physics Academic Software. Gates, M. A. (1986). A simple way to look at DNA. J. Theor. Biol. 119, 319–328. Weiis, O. et al. (2000). Information content of protein sequences. J. Theor. Biol. 206, 379–386. Bernardi, G. (2007). The neoselectionist theory of genome evolution. PNAS 104(20), 8385–8390.
Bianciardi, G. (2008). Information Polymers in the Primitive Earth: nonlinear analysis of archaea genomes and eukaryotic exons compared to computer-generated random sequences. INTERNATIONAL JOURNAL OF ASTROBIOLOGY, 7, 78-78.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/4861
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