Evolutionary distances in the twilight zone -- a rational kernel approach

Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets.Comment: to appear in PLoS ON

Diversity of 23S rRNA Genes within Individual Prokaryotic Genomes

The concept of ribosomal constraints on rRNA genes is deduced primarily based on the comparison of consensus rRNA sequences between closely related species, but recent advances in whole-genome sequencing allow evaluation of this concept within organisms with multiple rRNA operons. was the only species in which intragenomic diversity >3% was observed among 4 paralogous 23S rRNA genes.These findings indicate tight ribosomal constraints on individual 23S rRNA genes within a genome. Although classification using primary 23S rRNA sequences could be erroneous, significant diversity among paralogous 23S rRNA genes was observed only once in the 184 species analyzed, indicating little overall impact on the mainstream of 23S rRNA gene-based prokaryotic taxonomy