One ancestor for two codes viewed from the perspective of two complementary modes of tRNA aminoacylation

<p>Abstract</p> <p>Background</p> <p>The genetic code is brought into action by 20 aminoacyl-tRNA synthetases. These enzymes are evenly divided into two classes (I and II) that recognize tRNAs from the minor and major groove sides of the acceptor stem, respectively. We have reported recently that: (1) ribozymic precursors of the synthetases seem to have used the same two sterically mirror modes of tRNA recognition, (2) having these two modes might have helped in preventing erroneous aminoacylation of ancestral tRNAs with complementary anticodons, yet (3) the risk of confusion for the presumably earliest pairs of complementarily encoded amino acids had little to do with anticodons. Accordingly, in this communication we focus on the acceptor stem.</p> <p>Results</p> <p>Our main result is the emergence of a palindrome structure for the acceptor stem's common ancestor, reconstructed from the phylogenetic trees of Bacteria, Archaea and Eukarya. In parallel, for pairs of ancestral tRNAs with complementary anticodons, we present updated evidence of concerted complementarity of the second bases in the acceptor stems. These two results suggest that the first pairs of "complementary" amino acids that were engaged in primordial coding, such as Gly and Ala, could have avoided erroneous aminoacylation if and only if the acceptor stems of their adaptors were recognized from the same, major groove, side. The class II protein synthetases then inherited this "primary preference" from isofunctional ribozymes.</p> <p>Conclusion</p> <p>Taken together, our results support the hypothesis that the genetic code <it>per se </it>(the one associated with the anticodons) and the operational code of aminoacylation (associated with the acceptor) diverged from a common ancestor that probably began developing before translation. The primordial advantage of linking some amino acids (most likely glycine and alanine) to the ancestral acceptor stem may have been selective retention in a protocell surrounded by a leaky membrane for use in nucleotide and coenzyme synthesis. Such acceptor stems (as cofactors) thus transferred amino acids as groups for biosynthesis. Later, with the advent of an anticodon loop, some amino acids (such as aspartic acid, histidine, arginine) assumed a catalytic role while bound to such extended adaptors, in line with the original coding coenzyme handle (CCH) hypothesis.</p> <p>Reviewers</p> <p>This article was reviewed by Rob Knight, Juergen Brosius and Anthony Poole.</p

On origin of genetic code and tRNA before translation

Go to: Background Synthesis of proteins is based on the genetic code - a nearly universal assignment of codons to amino acids (aas). A major challenge to the understanding of the origins of this assignment is the archetypal "key-lock vs. frozen accident" dilemma. Here we re-examine this dilemma in light of 1) the fundamental veto on "foresight evolution", 2) modular structures of tRNAs and aminoacyl-tRNA synthetases, and 3) the updated library of aa-binding sites in RNA aptamers successfully selected in vitro for eight amino acids. Go to: Results The aa-binding sites of arginine, isoleucine and tyrosine contain both their cognate triplets, anticodons and codons. We have noticed that these cases might be associated with palindrome-dinucleotides. For example, one-base shift to the left brings arginine codons CGN, with CG at 1-2 positions, to the respective anticodons NCG, with CG at 2-3 positions. Formally, the concomitant presence of codons and anticodons is also expected in the reverse situation, with codons containing palindrome-dinucleotides at their 2-3 positions, and anticodons exhibiting them at 1-2 positions. A closer analysis reveals that, surprisingly, RNA binding sites for Arg, Ile and Tyr "prefer" (exactly as in the actual genetic code) the anticodon(2-3)/codon(1-2) tetramers to their anticodon(1-2)/codon(2-3) counterparts, despite the seemingly perfect symmetry of the latter. However, since in vitro selection of aa-specific RNA aptamers apparently had nothing to do with translation, this striking preference provides a new strong support to the notion of the genetic code emerging before translation, in response to catalytic (and possibly other) needs of ancient RNA life. Consistently with the pre-translation origin of the code, we propose here a new model of tRNA origin by the gradual, Fibonacci process-like, elongation of a tRNA molecule from a primordial coding triplet and 5'DCCA3' quadruplet (D is a base-determinator) to the eventual 76 base-long cloverleaf-shaped molecule. Go to: Conclusion Taken together, our findings necessarily imply that primordial tRNAs, tRNA aminoacylating ribozymes, and (later) the translation machinery in general have been co-evolving to ''fit'' the (likely already defined) genetic code, rather than the opposite way around. Coding triplets in this primal pre-translational code were likely similar to the anticodons, with second and third nucleotides being more important than the less specific first one. Later, when the code was expanding in co-evolution with the translation apparatus, the importance of 2-3 nucleotides of coding triplets "transferred" to the 1-2 nucleotides of their complements, thus distinguishing anticodons from codons. This evolutionary primacy of anticodons in genetic coding makes the hypothesis of primal stereo-chemical affinity between amino acids and cognate triplets, the hypothesis of coding coenzyme handles for amino acids, the hypothesis of tRNA-like genomic 3' tags suggesting that tRNAs originated in replication, and the hypothesis of ancient ribozymes-mediated operational code of tRNA aminoacylation not mutually contradicting but rather co-existing in harmony

On Primordial Sense–Antisense Coding

The genetic code is implemented by aminoacyl-tRNA synthetases (aaRS). These twenty enzymes are divided into two classes that, despite performing same functions, have nothing common in structure. The mystery of this striking partition of aaRSs might have been concealed in their sterically complementary modes of tRNA recognition that, as we have found recently, protect the tRNAs with complementary anticodons from confusion in translation. This finding implies that, in the beginning, life increased its coding repertoire by the pairs of complementary codons (rather than one-by-one) and used both complementary strands of genes as templates for translation. The class I and class II aaRSs may represent one of the most important examples of such primordial sence-antisence (SAS) coding (Rodin and Ohno, 1995). In this report, we address the issue of SAS coding in a wider scope. We suggest a variety of advantages that such coding would have had in exploring a wider sequence space before translation became highly specific. In particular, we confirm that in Achylia klebsiana a single gene might have originally coded for an HSP70 chaperonin (class II aaRS homolog) and an NAD-specific GDH-like enzyme (class I aaRS homolog) via its sense and antisense strands. Thus, in contrast to the conclusions in (Williams et al., 2009), this could indeed be a “Rosetta stone” (eroded somewhat, though) gene for the SAS origin of the two aaRS classes (Carter and Duax, 2002)

On origin of genetic code and tRNA before translation

Abstract Background Synthesis of proteins is based on the genetic code - a nearly universal assignment of codons to amino acids (aas). A major challenge to the understanding of the origins of this assignment is the archetypal "key-lock vs. frozen accident" dilemma. Here we re-examine this dilemma in light of 1) the fundamental veto on "foresight evolution", 2) modular structures of tRNAs and aminoacyl-tRNA synthetases, and 3) the updated library of aa-binding sites in RNA aptamers successfully selected in vitro for eight amino acids. Results The aa-binding sites of arginine, isoleucine and tyrosine contain both their cognate triplets, anticodons and codons. We have noticed that these cases might be associated with palindrome-dinucleotides. For example, one-base shift to the left brings arginine codons CGN, with CG at 1-2 positions, to the respective anticodons NCG, with CG at 2-3 positions. Formally, the concomitant presence of codons and anticodons is also expected in the reverse situation, with codons containing palindrome-dinucleotides at their 2-3 positions, and anticodons exhibiting them at 1-2 positions. A closer analysis reveals that, surprisingly, RNA binding sites for Arg, Ile and Tyr "prefer" (exactly as in the actual genetic code) the anticodon(2-3)/codon(1-2) tetramers to their anticodon(1-2)/codon(2-3) counterparts, despite the seemingly perfect symmetry of the latter. However, since in vitro selection of aa-specific RNA aptamers apparently had nothing to do with translation, this striking preference provides a new strong support to the notion of the genetic code emerging before translation, in response to catalytic (and possibly other) needs of ancient RNA life. Consistently with the pre-translation origin of the code, we propose here a new model of tRNA origin by the gradual, Fibonacci process-like, elongation of a tRNA molecule from a primordial coding triplet and 5'DCCA3' quadruplet (D is a base-determinator) to the eventual 76 base-long cloverleaf-shaped molecule. Conclusion Taken together, our findings necessarily imply that primordial tRNAs, tRNA aminoacylating ribozymes, and (later) the translation machinery in general have been co-evolving to ''fit'' the (likely already defined) genetic code, rather than the opposite way around. Coding triplets in this primal pre-translational code were likely similar to the anticodons, with second and third nucleotides being more important than the less specific first one. Later, when the code was expanding in co-evolution with the translation apparatus, the importance of 2-3 nucleotides of coding triplets "transferred" to the 1-2 nucleotides of their complements, thus distinguishing anticodons from codons. This evolutionary primacy of anticodons in genetic coding makes the hypothesis of primal stereo-chemical affinity between amino acids and cognate triplets, the hypothesis of coding coenzyme handles for amino acids, the hypothesis of tRNA-like genomic 3' tags suggesting that tRNAs originated in replication, and the hypothesis of ancient ribozymes-mediated operational code of tRNA aminoacylation not mutually contradicting but rather co-existing in harmony. Reviewers This article was reviewed by Eugene V. Koonin, Wentao Ma (nominated by Juergen Brosius) and Anthony Poole.</p

E.: Mining genetic epidemiology data with bayesian networks i: Bayesian networks and example application (plasma apoe levels

Motivation: The wealth of single nucleotide polymorphism (SNP) data within candidate genes and anticipated across the genome poses enormous analytic problems for studies of genotype-to-phenotype relationships, and modern data mining methods may be particularly well suited to meet the swelling challenges. In this manuscript we introduce the method of Belief (Bayesian) networks to the domain of genotype-to-phenotype analyses and provide an example application. Results: A Belief network is a graphical model of a probabilistic nature that represents a joint multivariate probability distribution and reflects conditional independences between variables. Given the data, optimal network topology can be estimated with the assistance of heuristic search algorithms and scoring criteria. Statistical significance of edge strengths can be evaluated using Bayesian methods and bootstrapping. As an example application, the method of Belief networks was applied to twenty SNPs in the apolipoprotein (apo) E gene and plasma apoE levels in a sample of 702 individuals from Jackson, MS. Plasma apoE level was the primary target variable. These analyses indicate that the edge between SNP 4075, coding for well-known 2 allele, and plasma apoE level was strong. Belief networks can effectively describe complex uncertain processes and can both learn from data and incorporate prior knowledge. Availability: Various alternative and supplemental networks (not shown in text), as well as source code extensions, are available from the authors

Epigenetics and Evolution: Transposons and the Stochastic Epigenetic Modification Model

In addition to genetic variation, epigenetic variation and transposons can greatly affect the evolutionary fitnesses landscape and gene expression. Previously we proposed a mathematical treatment of a general epigenetic variation model that we called Stochastic Epigenetic Modification (SEM) model. In this study we follow up with a special case, the Transposon Silencing Model (TSM), with, once again, emphasis on quantitative treatment. We have investigated the evolutionary effects of epigenetic changes due to transposon (T) insertions; in particular, we have considered a typical gene locus A and postulated that (i) the expression level of gene A depends on the epigenetic state (active or inactive) of a cis- located transposon element T, (ii) stochastic variability in the epigenetic silencing of T occurs only in a short window of opportunity during development, (iii) the epigenetic state is then stable during further development, and (iv) the epigenetic memory is fully reset at each generation. We develop the model using two complementary approaches: a standard analytical population genetics framework (di usion equations) and Monte-Carlo simulations. Both approaches led to similar estimates for the probability of fixation and time of fixation of locus TA with initial frequency P in a randomly mating diploid population of effective size Ne. We have ascertained the e ect that ρ, the probability of transposon Modification during the developmental window, has on the population (species). One of our principal conclusions is that as ρ increases, the pattern of fixation of the combined TA locus goes from &quot;neutral&quot; to &quot;dominant&quot; to &quot;over-dominant&quot;. We observe that, under realistic values of ρ, epigenetic Modifications can provide an e cient mechanism for more rapid fixation of transposons and cis-located gene alleles. The results obtained suggest that epigenetic silencing, even if strictly transient (being reset at each generation), can still have signi cant macro-evolutionary effects. Importantly, this conclusion also holds for the static fitness landscape. To the best of our knowledge, no previous analytical modeling has treated stochastic epigenetic changes during a window of opportunity

Intrinsic Properties of tRNA Molecules as Deciphered via Bayesian Network and Distribution Divergence Analysis

The identity/recognition of tRNAs, in the context of aminoacyl tRNA synthetases (and other molecules), is a complex phenomenon that has major implications ranging from the origins and evolution of translation machinery and genetic code to the evolution and speciation of tRNAs themselves to human mitochondrial diseases to artificial genetic code engineering. Deciphering it via laboratory experiments, however, is difficult and necessarily time- and resource-consuming. In this study, we propose a mathematically rigorous two-pronged in silico approach to identifying and classifying tRNA positions important for tRNA identity/recognition, rooted in machine learning and information-theoretic methodology. We apply Bayesian Network modeling to elucidate the structure of intra-tRNA-molecule relationships, and distribution divergence analysis to identify meaningful inter-molecule differences between various tRNA subclasses. We illustrate the complementary application of these two approaches using tRNA examples across the three domains of life, and identify and discuss important (informative) positions therein. In summary, we deliver to the tRNA research community a novel, comprehensive methodology for identifying the specific elements of interest in various tRNA molecules, which can be followed up by the corresponding experimental work and/or high-resolution position-specific statistical analyses