Co-Evolution of the Genetic Code and Ribozyme Replication

Stevenson, David S.

doi:10.1006/jtbi.2002.3013

Cited by 6 publications

(4 citation statements)

References 79 publications

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“…Tenet 3. Biosynthetic imprint on codon allocations CET is supported by or consistent with a range of studies, (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)44,45,59,61,62) but there are also two reappraisals of CET regarding its supposition of a significant biosynthetic imprint on the code. (63,64) The first reappraisal (63) yielded a random probability of 0.001 for codon-biosynthesis correlations within the code, which was weaker evidence for an imprint than the CET estimate of 0.0002 (25) but still highly significant.…”

Section: Gly Ala Ser Asp Glu Val Leu Ile Pro Thr Phe Tyr Arg His Trp mentioning

confidence: 62%

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Coevolution theory of the genetic code at age thirty

2005

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The coevolution theory of the genetic code, which postulates that prebiotic synthesis was an inadequate source of all twenty protein amino acids, and therefore some of them had to be derived from the coevolving pathways of amino acid biosynthesis, has been assessed in the light of the discoveries of the past three decades. Its four fundamental tenets regarding the essentiality of amino acid biosynthesis, role of pretran synthesis, biosynthetic imprint on codon allocations and mutability of the encoded amino acids are proven by the new knowledge. Of the factors that guided the evolutionary selection of the universal code, the relative contributions of Amino Acid Biosynthesis: Error Minimization: Stereochemical Interaction are estimated to first approximation as 40,000,000:400:1, which suggests that amino acid biosynthesis represents the dominant factor shaping the code. The utility of the coevolution theory is demonstrated by its opening up experimental expansions of the code and providing a basis for locating the root of life.

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Section: Gly Ala Ser Asp Glu Val Leu Ile Pro Thr Phe Tyr Arg His Trp mentioning

confidence: 62%

“…The formation of amino acids by biosynthetic pathways guided the development of the genetic code. (23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42) Expanding codons. Initially not all the triplet codons were utilized, and the number of effective codons increased from a smaller number to the present day 64.…”

Section: Introductionmentioning

confidence: 99%

Coevolution theory of the genetic code at age thirty

2005

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“…The standard genetic code table is published in a multitude of scientific papers and books. Numerous papers have been published in an attempt to explain the origin of the genetic code (Barbieri, 2003;Beebe et al, 2003b;Crick, 1968;Di Giulio, 1997, 1999a,b, 2000, 2001a,b, 2002Di Giulio and Medugno, 1998, 1999, 2001Freeland et al, 2003;Guimaraes, 2004;Jukes, 1993;Jukes and Osawa, 1993;Knight et al, 1999;Osawa et al, 1992;Ribas de Pouplana et al, 1998;Schimmel, 2000, 2001c;Ronneberg et al, 2000Ronneberg et al, , 2001Schimmel and Ribas de Pouplana, 1999;Schimmel and Wang, 1999;Seligmann and Amzallag, 2002;shCherbak, 2003;Skouloubris et al, 2003;Stevenson, 2002;Trevors, 2003;Wang and Schultz, 2002;Woese et al, 2000;Wong, 1975Wong, , 1988Xue et al, 2003;Yarian et al, 2002;Yarus and Christian, 1989;Yarus, 2000). All code origin models have problems and lack detail.…”

Section: The Role Of Natural Selectionmentioning

confidence: 99%

Chance and necessity do not explain the origin of life

Trevors

Abel

2004

Cell Biology International

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Where and how did the complex genetic instruction set programmed into DNA come into existence? The genetic set may have arisen elsewhere and was transported to the Earth. If not, it arose on the Earth, and became the genetic code in a previous lifeless, physical-chemical world. Even if RNA or DNA were inserted into a lifeless world, they would not contain any genetic instructions unless each nucleotide selection in the sequence was programmed for function. Even then, a predetermined communication system would have had to be in place for any message to be understood at the destination. Transcription and translation would not necessarily have been needed in an RNA world. Ribozymes could have accomplished some of the simpler functions of current protein enzymes. Templating of single RNA strands followed by retemplating back to a sense strand could have occurred. But this process does not explain the derivation of "sense" in any strand. "Sense" means algorithmic function achieved through sequences of certain decision-node switch-settings. These particular primary structures determine secondary and tertiary structures. Each sequence determines minimum-free-energy folding propensities, binding site specificity, and function. Minimal metabolism would be needed for cells to be capable of growth and division. All known metabolism is cybernetic--that is, it is programmatically and algorithmically organized and controlled.

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“…Numerous theories exist for explaining how carbonbased life forms of life originated, 38,39 and specifically how eukaryotic organisms arose from earlier precursors. [40][41][42] Although many aspects of the evolutionary arguments presented will undoubtedly apply to prokaryotes or even viruses, the ultimate goal is to understand how the human genome encodes complex phenotypes.…”

Section: Incremental Evolution Of Cellular Systemsmentioning

confidence: 99%

The evolution of signaling complexity suggests a mechanism for reducing the genomic search space in human association studies

et al. 2004

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The size complexity of the human genome has been traditionally viewed as an obstacle that frustrates efforts aimed at identifying the genetic correlates of complex human phenotypes. As such complex phenotypes are attributed to the combined action of numerous genomic loci, attempts to identify the underlying multi-locus interactions may produce a combinatorial sum of false positives that drown out the real signal. Faced with such grim prospects for successfully identifying the genetic basis of complex phenotypes, many geneticists simply disregard epistatic interactions altogether. However, the emerging picture from systems biology is that the cellular programs encoded by the genome utilize nested signaling hierarchies to integrate a number of loosely coupled, semiautonomous, and functionally distinct genetic networks. The current view of these modules is that connections encoding inter-module signaling are relatively sparse, while the gene-to-gene (protein-to-protein) interactions within a particular module are typically denser. We believe that each of these modules is encoded by a finite set of discontinuous, sequence-specific, genomic intervals that are functionally linked to association rules, which correlate directly to features in the environment. Furthermore, because these environmental association rules have evolved incrementally over time, we explore theoretical models of cellular evolution to better understand the role of evolution in genomic complexity. Specifically, we present a conceptual framework for (1) reducing genomic complexity by partitioning the genome into subsets composed of functionally distinct genetic modules and (2) improving the selection of coding region SNPs, which results in an increased probability of identifying functionally relevant SNPs. Additionally, we introduce the notion of 'genomic closure,' which provides a quantitative measure of how functionally insulated a specific genetic module might be from the influence of the rest of the genome. We suggest that the development and use of theoretical models can provide insight into the nature of biological systems and may lead to significant improvements in computational algorithms designed to reduce the complexity of the human genome.

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Co-Evolution of the Genetic Code and Ribozyme Replication

Cited by 6 publications

References 79 publications

Coevolution theory of the genetic code at age thirty

Coevolution theory of the genetic code at age thirty

Chance and necessity do not explain the origin of life

The evolution of signaling complexity suggests a mechanism for reducing the genomic search space in human association studies

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