The Relative Importance of Modeling Site Pattern Heterogeneity Versus Partition-Wise Heterotachy in Phylogenomic Inference.

Large taxa-rich genome-scale data sets are often necessary for resolving ancient phylogenetic relationships. But accurate phylogenetic inference requires that they are analyzed with realistic models that account for the heterogeneity in substitution patterns amongst the sites, genes and lineages. Two kinds of adjustments are frequently used: models that account for heterogeneity in amino acid frequencies at sites in proteins, and partitioned models that accommodate the heterogeneity in rates (branch lengths) among different proteins in different lineages (protein-wise heterotachy).

Modeling Site Heterogeneity with Posterior Mean Site Frequency Profiles Accelerates Accurate Phylogenomic Estimation.

Proteins have distinct structural and functional constraints at different sites that lead to site-specific preferences for particular amino acid residues as the sequences evolve. Heterogeneity in the amino acid substitution process between sites is not modeled by commonly used empirical amino acid exchange matrices. Such model misspecification can lead to artefacts in phylogenetic estimation such as long-branch attraction.

Split-specific bootstrap measures for quantifying phylogenetic stability and the influence of taxon selection.

Assessing the robustness of an inferred phylogeny is an important element of phylogenetics. This is typically done with measures of stabilities at the internal branches and the variation of the positions of the leaf nodes. The bootstrap support for branches in maximum parsimony, distance and maximum likelihood estimation, or posterior probabilities in Bayesian inference, measure the uncertainty about a branch due to the sampling of the sites from genes or sampling genes from genomes.

An amino acid substitution-selection model adjusts residue fitness to improve phylogenetic estimation.

Standard protein phylogenetic models use fixed rate matrices of amino acid interchange derived from analyses of large databases. Differences between the stationary amino acid frequencies of these rate matrices from those of a data set of interest are typically adjusted for by matrix multiplication that converts the empirical rate matrix to an exchangeability matrix which is then postmultiplied by the amino acid frequencies in the alignment. The result is a time-reversible rate matrix with stationary amino acid frequencies equal to the data set frequencies.

The site-wise log-likelihood score is a good predictor of genes under positive selection.

The strength and direction of selection on the identity of an amino acid residue in a protein is typically measured by the ratio of the rate of non-synonymous substitutions to the rate of synonymous substitutions. In attempting to predict positively selected sites from amino acid alignments, we made the unexpected observation that the site likelihood of an alignment column for a given tree tends to be negatively correlated with the posterior probability that site is in the positive selection class under widely-used codon models. This is likely because positively selected sites tend to be more variable and display more "radical" amino acid changes; both of these features are expected to result in low site log-likelihoods.

Fast statistical tests for detecting heterotachy in protein evolution.

The w statistic introduced by Lockhart et al. (1998. A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages.

PROCOV: maximum likelihood estimation of protein phylogeny under covarion models and site-specific covarion pattern analysis.

Background: The covarion hypothesis of molecular evolution holds that selective pressures on a given amino acid or nucleotide site are dependent on the identity of other sites in the molecule that change throughout time, resulting in changes of evolutionary rates of sites along the branches of a phylogenetic tree. At the sequence level, covarion-like evolution at a site manifests as conservation of nucleotide or amino acid states among some homologs where the states are not conserved in other homologs (or groups of homologs). Covarion-like evolution has been shown to relate to changes in functions at sites in different clades, and, if ignored, can adversely affect the accuracy of phylogenetic inference.

A class frequency mixture model that adjusts for site-specific amino acid frequencies and improves inference of protein phylogeny.

Background: Widely used substitution models for proteins, such as the Jones-Taylor-Thornton (JTT) or Whelan and Goldman (WAG) models, are based on empirical amino acid interchange matrices estimated from databases of protein alignments that incorporate the average amino acid frequencies of the data set under examination (e.g JTT + F). Variation in the evolutionary process between sites is typically modelled by a rates-across-sites distribution such as the gamma (Gamma) distribution.

Topological estimation biases with covarion evolution.

Covarion processes allow changes in evolutionary rates at sites along the branches of a phylogenetic tree. Covarion-like evolution is increasingly recognized as an important mode of protein evolution. Several recent reports suggest that maximum likelihood estimation employing covarion models may support different optimal topologies than estimation using standard rates-across-sites (RAS) models.

Rapid divergence of codon usage patterns within the rice genome.

Background: Synonymous codon usage varies widely between genomes, and also between genes within genomes. Although there is now a large body of data on variations in codon usage, it is still not clear if the observed patterns reflect the effects of positive Darwinian selection acting at the level of translational efficiency or whether these patterns are due simply to the effects of mutational bias. In this study, we have included both intra-genomic and inter-genomic comparisons of codon usage.

Testing for covarion-like evolution in protein sequences.

The covarion hypothesis of molecular evolution proposes that selective pressures on an amino acid or nucleotide site change through time, thus causing changes of evolutionary rate along the edges of a phylogenetic tree. Several kinds of Markov models for the covarion process have been proposed. One model, proposed by Huelsenbeck (2002), has 2 substitution rate classes: the substitution process at a site can switch between a single variable rate, drawn from a discrete gamma distribution, and a zero invariable rate.

Thermal adaptation of the small subunit ribosomal RNA gene: a comparative study.

We carried out a comprehensive survey of small subunit ribosomal RNA sequences from archaeal, bacterial, and eukaryotic lineages in order to understand the general patterns of thermal adaptation in the rRNA genes. Within each lineage, we compared sequences from mesophilic, moderately thermophilic, and hyperthermophilic species. We carried out a more detailed study of the archaea, because of the wide range of growth temperatures within this group.

Cytosine usage modulates the correlation between CDS length and CG content in prokaryotic genomes.

Previous studies have argued that, given the AT-rich nature of stop codons, the length and CG% of coding sequences (CDSs) should be positively correlated. This prediction is generally supported empirically by prokaryotic genomes. However, the correlation is weak for a number of species, with 4 species showing a negative correlation.

On the correlation between genomic G+C content and optimal growth temperature in prokaryotes: data quality and confounding factors.

The correlation between genomic G+C content and optimal growth temperature in prokaryotes has gained renewed interest after Musto et al. [H. Musto, H.

Mutational bias affects protein evolution in flowering plants.

Amino acid sequences from several thousand homologous gene pairs were compared for two plant genomes, Oryza sativa and Arabidopsis thaliana. The Arabidopsis genes all have similar G+C (guanine plus cytosine) contents, whereas their homologs in rice span a wide range of G+C levels. The results show that those rice genes that display increased divergence in their nucleotide composition (specifically, increased G+C content) showed a corresponding, predictable change in the amino acid compositions of the encoded proteins relative to their Arabidopsis homologs.

Evidence for strong selective constraint acting on the nucleotide composition of 16S ribosomal RNA genes.

Previous studies have shown that the guanine plus cytosine (G+C) content of ribosomal RNAs (rRNAs) is highly correlated with bacterial growth temperatures. This correlation is strongest in the double-stranded stem regions of the rRNA, a fact that can be explained by selection for increased structural stability at high growth temperatures. In this study, we examined the single-stranded regions of 16S rRNAs.

The Rapid Identification of Protein Through Its Amino Acid Composition.

This paper described a method for the identification of protein through its composition. The basic idea is as follows: A database for lengths, compositions and molecular weights of all known proteins is easily derived from a protein sequence database and by comparing the composition, length and molecular weight of the protein in question with each array of data in the composition database, proteins with similar length, composition and molecular weight may be found; as such a tentative identification for the said protein may be made. In some cases, it can be perfectly accurate to predict the right protein(s) from the composition database.