Natural Science

Volume 10, Issue 9 (September 2018)

ISSN Print: 2150-4091   ISSN Online: 2150-4105

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The Most Primitive Extant Ancestor of Organisms and Discovery of Definitive Evolutionary Equations Based on Complete Genome Structures

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DOI: 10.4236/ns.2018.109034    431 Downloads   827 Views   Citations
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ABSTRACT

Evolutionary divergence has been characterized based on morphological and molecular features using rationale based on Darwin’s theory of natural selection. However, universal rules that govern genome evolution have not been identified. Here, a simple, innovative approach has been developed to evaluate biological evolution initiating the origin of life: whole genomes were divided into several fragments, and then differences in normalized nucleotide content between nucleotide pairs were compared. Intramolecular nucleotide differences in complete mitochondrial genomes reflect evolutionary divergence. The values of (G – C), (G – T), (G – A), (C – T), (C – A) and (T – A) reflect biological evolution, and these values except for (G – C) and (T – A) change inversely to positive from negative along biological evolution of bacterial genomes. More highly evolved organisms, such as primates and birds, seem to have greater levels of (C – T) in mitochondria. Based on nucleotide content structures, Monosiga brevicollis mitochondria may be the most primitive extant ancestor of the species examined here. The two normalized nucleotide contents are universally expressed by a linear regression line, (X – Y)/(X + Y) = a(X – Y) + b, where X and Y are nucleotide contents and (a) and (b) are constants. The value of (G + C), (G + A), (G + T), (C + A), (C + T) and (A + T) was ~0.5. Plotting (X – Y)/(X + Y) against X/Y showed a logarithmic function (X – Y)/(X + Y) = a lnX/Y + b, where (a) and (b) are constant. Nucleotide content changes are expressed by a definitive equation, (X – Y) ≈ 0.25 ln(X/Y).

Cite this paper

Sorimachi, K. (2018) The Most Primitive Extant Ancestor of Organisms and Discovery of Definitive Evolutionary Equations Based on Complete Genome Structures. Natural Science, 10, 338-369. doi: 10.4236/ns.2018.109034.

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