Statistics of trinucleotides in coding sequences and evolution

Plastid thylakoid architecture optimizes photosynthesis in diatoms

Photosynthesis is a unique process that allows independent colonization of the land by plants and of the oceans by phytoplankton. Although the photosynthesis process is well understood in plants, we are still unlocking the mechanisms evolved by phytoplankton to achieve extremely efficient photosynthesis. Here, we combine biochemical, structural and in vivo physiological studies to unravel the structure of the plastid in diatoms, prominent marine eukaryotes. Biochemical and immunolocalization analyses reveal segregation of photosynthetic complexes in the loosely stacked thylakoid membranes typical of diatoms. Separation of photosystems within subdomains minimizes their physical contacts, as required for improved light utilization. Chloroplast 3D reconstruction and in vivo spectroscopy show that these subdomains are interconnected, ensuring fast equilibration of electron carriers for efficient optimum photosynthesis. Thus, diatoms and plants have converged towards a similar functional distribution of the photosystems although via different thylakoid architectures, which likely evolved independently in the land and the ocean.

Phytoplankton and plant plastids have distinct evolutionary origins and membrane organization. Here Flori et al. show that diatom photosynthetic complexes spatially segregate into interconnected subdomains within loose thylakoid stacks enabling fast diffusion of electron carriers and efficient photosynthesis

The structure of selective dinucleotide interactions and periodicities in D melanogaster mtDNA

BACKGROUND

We found a strong selective 3-sites periodicity of deviations from randomness of the dinucleotide (DN) distribution, where both bases of DN were separated by 1, 2, K sites in prokaryotes and mtDNA. Three main aspects are studied. I) the specific 3 K-sites periodic structure of the 16 DN. II) to discard the possibility that the periodicity was produced by the highly nonrandom interactive association of contiguous bases, by studying the interaction of non-contiguous bases, the first one chosen each I sites and the second chosen J sites downstream. III) the difference between this selective periodicity of association (distance to randomness) of the four bases with the described fixed periodicities of base sequences.

RESULTS

I) The 16 pairs presented a consistent periodicity in the strength of association of both bases of the pairs; the most deviated pairs are those where G and C are involved and the least deviated ones are those where A and T are involved. II) we found significant non-random interactions when the first nucleotide is chosen every I sites and the second J sites downstream until I=J=76. III) we showed conclusive differences between these internucleotide association periodicities and sequence periodicities.

CONCLUSIONS

This relational selective periodicity is different from sequence periodicities and indicates that any base strongly interacts with the bases of the residual genome; this interaction and periodicity is highly structured and systematic for every pair of bases. This interaction should be destroyed in few generations by recurrent mutation; it is only compatible with the Synthetic Theory of Evolution and agrees with the Wright's adaptive landscape conception and evolution by shifting balanced adaptive peaks.

Codon-pair usage and genome evolution

The aim of this paper is to demonstrate possible evolutionary constraints that shape codon-pair context. The distributions of numbers of modes (DNM) of codon-pairs in protein coding sequences (CDSs) and the frequency of base triplet pairs in intergenic sequences (IGSs) are analyzed in 110 fully sequenced genomes. We propose that these distributions are in accordance with a gamma distribution. By studying the shape parameter alpha value of gamma distribution a distinct relation between the alpha value and the genome evolution is obtained. For codon-pairs in CDSs, the alpha value increases in the order Archaea, Bacteria, and Eukaryota, and divides the species into three evolutionary groups, Archaea, Bacteria and Eukaryota. For triplet pairs in IGSs, on the other hand, the alpha value classifies the species into two groups, one is Bacteria and the other is Archaea and Eukaryota. The findings suggest that the codon-pair context could be an important determinant for phylogeny of individual species, and indicate the existence of fundamental differences of evolutional constraints imposed on CDSs and IGSs among Archaea, Bacteria, and Eukaryota.

Organisms can essentially be classified according to two codon patterns

We recently classified 23 bacteria into two types based on their complete genomes; "S-type" as represented by Staphylococcus aureus and "E-type" as represented by Escherichia coli. Classification was characterized by concentrations of Arg, Ala or Lys in the amino acid composition calculated from the complete genome. Based on these previous classifications, not only prokaryotic but also eukaryotic genome structures were investigated by amino acid compositions and nucleotide contents. Organisms consisting of 112 bacteria, 15 archaea and 18 eukaryotes were classified into two major groups by cluster analysis using GC contents at the three codon positions calculated from complete genomes. The 145 organisms were classified into "AT-type" and "GC-type" represented by high A or T (low G or C) and high G or C (low A or T) contents, respectively, at every third codon position. Reciprocal changes between G or C and A or T contents at the third codon position occurred almost synchronously in every codon among the organisms. Correlations between amino acid concentrations (Ala, Ile and Lys) and the nucleotide contents at the codon position were obtained in both "AT-type" and "GC-type" organisms, but with different regression coefficients. In certain correlations of amino acid concentrations with GC contents, eukaryotes, archaea and bacteria showed different behaviors; thus these kingdoms evolved differently. All organisms are basically classifiable into two groups having characteristic codon patterns; organisms with low GC and high AT contents at the third codon position and their derivatives, and organisms with an inverse relationship.

Trend of amino acid composition of proteins of different taxa

Archaea, bacteria and eukaryotes represent the main kingdoms of life. Is there any trend for amino acid compositions of proteins found in full genomes of species of different kingdoms? What is the percentage of totally unstructured proteins in various proteomes? We obtained amino acid frequencies for different taxa using 195 known proteomes and all annotated sequences from the Swiss-Prot data base. Investigation of the two data bases (proteomes and Swiss-Prot) shows that the amino acid compositions of proteins differ substantially for different kingdoms of life, and this difference is larger between different proteomes than between different kingdoms of life. Our data demonstrate that there is a surprisingly small selection for the amino acid composition of proteins for higher organisms (eukaryotes) and their viruses in comparison with the "random" frequency following from a uniform usage of codons of the universal genetic code. On the contrary, lower organisms (bacteria and especially archaea) demonstrate an enhanced selection of amino acids. Moreover, according to our estimates, 12%, 3% and 2% of the proteins in eukaryotic, bacterial and archaean proteomes are totally disordered, and long (> 41 residues) disordered segments are found to occur in 16% of arhaean, 20% of eubacterial and 43% of eukaryotic proteins for 19 archaean, 159 bacterial and 17 eukaryotic proteomes, respectively. A correlation between amino acid compositions of proteins of various taxa, show that the highest correlation is observed between eukaryotes and their viruses (the correlation coefficient is 0.98), and bacteria and their viruses (the correlation coefficient is 0.96), while correlation between eukaryotes and archaea is 0.85 only.

Some probabilistic results on the nonrandomness of simple sequence repeats in DNA sequences

Some probabilistic results on simple sequence repeats (SSRs) in DNA sequences are derived and used to quantify the nonrandomness of SSRs as an index of nonrandomness. The applicability of the index of nonrandomness is illustrated using several examples from the literature on selected human diseased genes.

Inferring Parameters Shaping Amino Acid Usage in Prokaryotic Genomes via Bayesian MCMC Methods

Molar content of guanine plus cytosine (G + C) and optimal growth temperature (OGT) are main factors characterizing the frequency distribution of amino acids in prokaryotes. Previous work, using multivariate exploratory methods, has emphasized ascertainment of biological factors underlying variability between genomes, but the strength of each identified factor on amino acid content has not been quantified. We combine the flexibility of the phylogenetic mixed model (PMM) with the power of Bayesian inference via Markov Chain Monte Carlo (MCMC) methods, to obtain a novel evolutionary picture of amino acid usage in prokaryotic genomes. We implement a Bayesian PMM which incorporates the feature that evolutionary history makes observed data interdependent. As in previous studies with PMM, we present a variance partition; however, attention is also given to the posterior distribution of "systematic effects" that may shed light about the relative importance of and relationships between evolutionary forces acting at the genomic level. In particular, we analyzed influences of G + C, OGT, and respiratory metabolism. Estimates of G + C effects were significant for amino acids coded by G + C or molar content of adenine plus thymine (A + T) in first and second bases. OGT had an important effect on 12 amino acids, probably reflecting complex patterns of protein modifications, to cope with varying environments. The effect of respiratory metabolism was less clear, probably due to the already reported association of G + C with aerobic metabolism. A "heritability" parameter was always high and significant, reinforcing the importance of accommodating phylogenetic relationships in these analyses. "Heritable" component correlations displayed a pattern that tended to cluster "pure" G + C (A + T) in first and second codon positions, suggesting an inherited departure from linear regression on G + C.