Edward N. Trifonov

Translation framing code and frame-monitoring mechanism as suggested by the analysis of mRNA and 16 S rRNA nucleotide sequences.

Protein coding sequences carry an additional message in the form of a universal three-base periodical pattern (G-non-G-N)n, which is expressed as a strong preference for guanines in the first positions of the codons in mRNA and lack of guanines in the second positions. This periodicity appears immediately after the initiation codon and is maintained along the mRNA as far as the termination triplet, where it disappears abruptly. Known cases of ribosome slippage during translation (leaky frameshifts, out-of-frame gene fusion) are analyzed. At the sites of the slippage the G-periodical pattern is found to be interrupted. It reappears downstream from the slippage sites, in a new frame that corresponds to the new translation frame. This suggests that the (G-non-G-N)n pattern in the mRNA may be responsible for monitoring the correct reading frame during translation. Several sites with complementary C-periodical structure are found in the Escherichia coli 16 S rRNA sequence. Only three of them are exposed to various interactions at the surface of the small ribosomal subunit: (517)gcCagCagCegC, (1395)caCacCgcC and (1531)auCacCucC. A model of a frame-monitoring mechanism is suggested based on the weak complementarity of G-periodical mRNA to the C-periodical sites in the ribosomal RNA. The model is strongly supported by the fact that the hypothetical frame-monitoring sites in the 16 S rRNA that are derived from the nucleotide sequence analysis are also the only sites known to be actually involved or implicated in rRNA-mRNA interactions.

The Triplet Code From First Principles

Abstract Temporal order (“chronology”) of appearance of amino acids and their respective codons on evolutionary scene is reconstructed. A consensus chronology of amino acids is built on the basis of 60 different criteria each offering certain temporal order. After several steps of filtering the chronology vectors are averaged resulting in the consensus order: G, A, D, V, P, S, E, (L, T), R, (I, Q, N), H, K, C, F, Y, M, W. It reveals two important features: the amino acids synthesized in imitation experiments of S. Miller appeared first, while the amino acids associated with codon capture events came last. The reconstruction of codon chronology is based on the above consensus temporal order of amino acids, supplemented by the stability and complementarity rules first suggested by M. Eigen and P. Schuster, and on the earlier established processivity rule. At no point in the reconstruction the consensus amino-acid chronology was in conflict with these three rules. The derived genealogy of all 64 codons suggested several important predictions that are confirmed. The reconstruction of the origin and evolutionary history of the triplet code becomes, thus, a powerful research tool for molecular evolution studies, especially in its early stages.

Consensus temporal order of amino acids and evolution of the triplet code

Forty different single-factor criteria and multi-factor hypotheses about chronological order of appearance of amino acids in the early evolution are summarized in consensus ranking. All available knowledge and thoughts about origin and evolution of the genetic code are thus combined in a single list where the amino acids are ranked chronologically. Due to consensus nature of the chronology it has several important properties not visible in individual rankings by any of the initial criteria. Nine amino acids of the Millers imitation of primordial environment are all ranked as topmost (G, A, V, D, E, P, S, L, T). This result does not change even after several criteria related to Millers data are excluded from calculations. The consensus order of appearance of the 20 amino acids on the evolutionary scene also reveals a unique and strikingly simple chronological organization of 64 codons, that could not be figured out from individual criteria: New codons appear in descending order of their thermostability, as complementary pairs, with the complements recruited sequentially from the codon repertoires of the earlier or simultaneously appearing amino acids. These three rules (Thermostability, Complementarity and Processivity) hold strictly as well as leading position of the earliest amino acids according to Miller. The consensus chronology of amino acids, G/A, V/D, P, S, E/L, T, R, N, K, Q, I, C, H, F, M, Y, W, and the derived temporal order for codons may serve, thus, as a justified working model of choice for further studies on the origin and evolution of the genetic code.

CURVATURE: software for the analysis of curved DNA

Software is presented to plot the sequence-dependent spatial trajectory of the DNA double helix and/or distribution of curvature along the DNA molecule. The nearest-neighbor wedge model is implemented to calculate overall DNA path using local helix parameters: helix twist angle, wedge (deflection) angle and direction (of deflection) angle. The procedures described proved to be very convenient as tools for investigation of a relationship between overall DNA curvature and its gel electrophoretic mobility. All parameters of the model had been estimated from experimental data. Using these wedge parameters the program takes, as input, any DNA sequence and calculates the likely degree of curvature at each point along the molecule. This information is displayed both graphically and in the form of simplified representations of curved double helices. The Software, CURVATURE, can thus be used to investigate possible roles of curvature in modulation of gene expression and for location of curved portions of DNA, which may play an important role in sequence-specific protein--DNA interactions.

10-11 bp periodicities in complete genomes reflect protein structure and DNA folding.

MOTIVATION Completely sequenced genomes allow for detection and analysis of the relatively weak periodicities of 10-11 basepairs (bp). Two sources contribute to such signals: correlations in the corresponding protein sequences due to the amphipatic character of alpha-helices and the folding of DNA (nucleosomal patterns, DNA supercoiling). Since the topological state of genomic DNA is of importance for its replication, recombination and transcription, there is an immediate interest to obtain information about the supercoiled state from sequence periodicities. RESULTS We show that correlations within proteins affect mainly the oscillations at distances below 35 bp. The long-ranging correlations up to 100 bp reflect primarily DNA folding. For the yeast genome these oscillations are consistent in detail with the chromatin structure. For eubacteria and archaea the periods deviate significantly from the 10.55 bp value for free DNA. These deviations suggest that while a period of 11 bp in bacteria reflects negative supercoiling, the significantly different period of thermophilic archaea close to 10 bp corresponds to positive supercoiling of thermophilic archaeal genomes. AVAILABILITY Protein sets and C programs for the calculation of correlation functions are available on request from the authors (see http://itb.biologie.hu-berlin.de).

Closed loops of nearly standard size: common basic element of protein structure

By screening the crystal protein structure database for close Cα–Cα contacts, a size distribution of the closed loops is generated. The distribution reveals a maximum at 27±5 residues, the same for eukaryotic and prokaryotic proteins. This is apparently a consequence of polymer statistic properties of protein chain trajectory. That is, closure into the loops depends on the flexibility (persistence length) of the chain. The observed preferential loop size is consistent with the theoretical optimal loop closure size. The mapping of the detected unit‐size loops on the sequences of major typical folds reveals an almost regular compact consecutive arrangement of the loops. Thus, a novel basic element of protein architecture is discovered; structurally diverse closed loops of the particular size.

3-, 10.5-, 200- and 400-base periodicities in genome sequences

The above periodicities are the main hidden oscillating patterns detected so far in the genomic sequences. The 3-base periodicity is characteristic for the protein-coding sequences only. The source of the approximately 10.5-base sequence period is twofold. On the one hand, the sequences coding for alpha-helical coiled-coil regions in proteins have the hidden 3.5 aminoacid repeat which appears as 10.5-base periodicity in the nucleotide sequences. On the other hand, deformability of DNA important for its folding in chromatin is facilitated by periodical positioning of certain dinucleotides along the sequences, with the period close to 10.5 bases. There are some sequence features which are repeated at approximately 400-base distances, nearly periodically. This is due to the general segmented organization of the genomes, which appear to have evolved by fusion of genome segments of nearly standard sizes, close to typical 350 bases for eukaryotes and 440 bases for prokaryotes. Respective half-units (about 200 bases) are also frequently observed.

Interpreting correlations in biosequences

Understanding the complex organization of genomes as well as predicting the location of genes and the possible structure of the gene products are some of the most important problems in current molecular biology. Many statistical techniques are used to address these issues. A central role among them play correlation functions. This paper is based on an analysis of the decay of the entire 4×4 dimensional covariance matrix of DNA sequences. We apply this covariance analysis to human chromosomal regions, yeast DNA, and bacterial genomes and interpret the three most pronounced statistical features – long-range correlations, a period 3, and a period 10–11 – using known biological facts about the structure of genomes. For example, we relate the slowly decaying long-range G+C correlations to dispersed repeats and CpG islands. We show quantitatively that the 3-basepair-periodicity is due to the nonuniformity of the codon usage in protein coding segments. We finally show that periodicities of 10–11 basepairs in yeast DNA originate from an alternation of hydrophobic and hydrophilic amino acids in protein sequences.

Terminators of Transcription with RNA Polymerase from Escherichia coli: What They Look Like and How to Find Them

We present here a compilation of prokaryotic transcription terminator sequences (ref. 1-152). The compilation includes 49 independent terminators, 52 speculated independent terminators, 27 sites shown to function in vivo, and some 20 proven or speculated rho-dependent terminators. In addition to the well-known features of independent terminators (dyad symmetry and T-run), two consensus are found: CGGG(C/G) upstream and TCTG downstream of the termination point. A subset of the collection of sequence has been used to construct a computer algorithm to locate independent terminators by sequence analysis.

What positions nucleosomes? – A model

Here we propose a new determinant for localization of nucleosomes along genomic DNA, in addition to sequence‐dependent features. The new specific class of chromatin scaling signals involves curved DNA. According to the observed positional distribution of DNA curvature, the new synchronizing signal occurs once per four nucleosomes on average. This new factor in nucleosome positioning should substantially influence the efficiency of biological reactions through regulatory factors microscopically and the entire chromatin structure through the 30 nm fiber structure macroscopically. Allocation of the new type of signals is found to be fixed evolutionarily although they could be shifted in accordance with the hierarchy of functional genomic structures.