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Register a new userGenetic code evolution as an initial driving force for molecular evolution
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There is an intrinsic relationship between the molecular evolution in primordial period and the properties of genomes and proteomes of contemporary species. The genomic data may help us understand the driving force of evolution of life at molecular level. In absence of evidence, numerous problems in molecular evolution had to fall into a twilight zone of speculation and controversy in the past. Here we show that delicate structures of variations of genomic base compositions and amino acid frequencies resulted from the genetic code evolution. And the driving force of evolution of life also originated in the genetic code evolution. The theoretical results on the variations of amino acid frequencies and genomic base compositions agree with the experimental observations very well, not only in the variation trends but also in some fine structures. Inversely, the genomic data of contemporary species can help reconstruct the genetic code chronology and amino acid chronology in primordial period. Our results may shed light on the intrinsic mechanism of molecular evolution and the genetic code evolution.
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In this paper it is shown that within a Combined Genetic Code Table, realized through a combination of Watson-Crick Table and Codon Path Cube it exists, without an exception, a strict distinction between two classes of enzymes aminoacyl-tRNA synthetases, corresponding two classes of amino acids and belonging codons. By this, the distinction itself is followed by a strict balance of atom number within two subclasses of class I as well as two subclasses of class II of amino acids.
The transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of paramount importance to the controlling and combating of coronavirus disease 2019 (COVID-19) pandemic. Currently, near 15,000 SARS-CoV-2 single mutations have been recorded, having a great ramification to the development of diagnostics, vaccines, antibody therapies, and drugs. However, little is known about SARS-CoV-2 evolutionary characteristics and general trend. In this work, we present a comprehensive genotyping analysis of existing SARS-CoV-2 mutations. We reveal that host immune response via APOBEC and ADAR gene editing gives rise to near 65% of recorded mutations. Additionally, we show that children under age five and the elderly may be at high risk from COVID-19 because of their overreacting to the viral infection. Moreover, we uncover that populations of Oceania and Africa react significantly more intensively to SARS-CoV-2 infection than those of Europe and Asia, which may explain why African Americans were shown to be at increased risk of dying from COVID-19, in addition to their high risk of getting sick from COVID-19 caused by systemic health and social inequities. Finally, our study indicates that for two viral genome sequences of the same origin, their evolution order may be determined from the ratio of mutation type C$>$T over T$>$C.
The premise of genetic analysis is that a causal link exists between phenotypic and allelic variation. Yet it has long been documented that mutant phenotypes are not a simple result of a single DNA lesion, but rather are due to interactions of the focal allele with other genes and the environment. Although an experimentally rigorous approach, focusing on individual mutations and isogenic control strains, has facilitated amazing progress within genetics and related fields, a glimpse back suggests that a vast complexity has been omitted from our current understanding of allelic effects. Armed with traditional genetic analyses and the foundational knowledge they have provided, we argue that the time and tools are ripe to return to the under-explored aspects of gene function and embrace the context-dependent nature of genetic effects. We assert that a broad understanding of genetic effects and the evolutionary dynamics of alleles requires identifying how mutational outcomes depend upon the wild-type genetic background. Furthermore, we discuss how best to exploit genetic background effects to broaden genetic research programs.
The paper represents three supplements to the source paper, q-bio/0610044 [q-bio.OT], with three new series of harmonic structures of the genetic code, determined by Gauss arithmetical algorithm; by Table of Minimal Adding, as in (Rakocevic, 2011a: Table 4; 2011b: Table 4); all structures in relation to Binary-code tree (Rakocevic, 1998). The determination itself is realized through atom and nucleon number balancing and nuancing of molekular polarity. In the first supplement the word is about some additional harmonic structures in relation to a previous our paper (Rakocevic, 2004); in the second one about the relation that structures with the polarity of protein amino acids. In the third supplement we give new ideas about the genetic code by an inclusion of the notions cipher of the genetic code and the key of that cipher.
It is shown that there is a sense in splitting Genetic Code Table (GCT) into three parts using the harmonic mean, calculated by the formula H (a, b) = 2ab / (a + b), where a = 63 and b = 31.5. Within these three parts, the amino acids (AAs) are positioned on the basis of the validity of the evident regularities of key parameters, such as polarity, hydrophobicity and enzyme-mediated amino acid classification. In addition, there are obvious balances of the number of atoms in the nucleotide triplets and corresponding amino acid groups and/or classes.
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