Stable tRNA-based phylogenies using only 76 nucleotides

Abstract

tRNAs are among the most ancient, highly conserved sequences on earth, but are often thought to be poor phylogenetic markers because they are short, often subject to horizontal gene transfer, and easily change specificity. Here we use an algorithm now commonly used in microbial ecology, UniFrac, to cluster 175 genomes spanning all three domains of life based on the phylogenetic relationships among their complete tRNA pools. We find that the overall pattern of similarities and differences in the tRNA pools recaptures universal phylogeny to a remarkable extent, and that the resulting tree is similar to the distribution of bootstrapped rRNA trees from the same genomes. In contrast, the trees derived from tRNAs of identical specificity or of individual isoacceptors generally produced trees of lower quality. However, some tRNA isoacceptors were very good predictors of the overall pattern of organismal evolution. These results show that UniFrac can extract meaningful biological patterns from even phylogenies with high level of statistical inaccuracy and horizontal gene transfer, and that, overall, the pattern of tRNA evolution tracks universal phylogeny and provides a background against which we can test hypotheses about the evolution of individual isoacceptors.

FIGURE 1.

Overall tRNA tree-building procedure, including UniFrac clustering. UniFrac measures the fraction of branch length that is not shared between two groups of sequences, so that two identical groups of sequences (A) have a UniFrac score of 0, two completely dissimilar sets of sequences (C) have a UniFrac score of 1, and two related groups of sequences (B) have an intermediate UniFrac score. For a tree with many groups (here, the groups are genomes), the distance between each pair of groups can be calculated separately and summarized in a distance matrix (D). The overall workflow, including UniFrac steps, is shown in E. These analyses were run using the weighted version of the UniFrac algorithm, which corrects for the abundance of each sequence (Lozupone et al. 2007).

FIGURE 2.

Small excerpt from the neighbor-joining phylogenetic tree containing 8847 tRNA sequences. Each tRNA is labeled with its amino acid specificity, its anticodon, and the organism name. This tree containing only 35 tRNAs shows a mixture of several different amino acid specificities and different microbial lineages, reflecting the difficulty of using individual tRNA sequences for phylogeny. Scale bar shows 0.05 substitutions per site.

FIGURE 3.

Weighted UniFrac tree of the tRNA pools in 175 genomes. The clustering recovers the monophyly of the eukaryotes (green), the archaea (blue), and the bacteria (red), along with a large number of genus-level and other taxonomic groupings. Inset shows grouping at the genus level within the actinobacteria.

FIGURE 4.

UniFrac PCoA of global tRNA pools showing clustering within the archaea (blue squares), eukaryotes (green circles), and bacteria (red triangles). The scatterplots show P1 against P2 (A), P3 against P2 (B), P1 against P3 (C), and P1 against P2 plotted with an equal number of genomes from each domain (D); axes are aligned for direct comparison of the same components. This clustering was performed using the weighted UniFrac algorithm as implemented on the UniFrac website (Lozupone et al. 2006).

FIGURE 5.

Distribution of correlation coefficients of distance matrices between the SSU rRNA reference phylogeny and bootstrapped rRNA trees sampled from the same alignment (blue), amino acid specificity clusters (red), isoacceptor clusters (green), and trees constructed from randomly sampled 76 nt rRNA slices (purple). Each element in a matrix corresponds to the branch length traversed when moving from one genome to another genome in the corresponding tree using the shortest possible path (the tip-to-tip distance). The correlation coefficient for the full tRNA pool clustering, 0.67, is shown as a black line.

FIGURE 6.

Concordance of individual tRNA trees with the rRNA tree for the full set of tRNAs for each amino acid (top), and for each isoacceptor family of tRNAs separately (bottom). Y-axis values range from 0 (no correlation with tRNA tree) to 1 (perfect correlation). iMet and eMet refer to initiator methionine and elongator methionine tRNAs separately. In the tRNA graph (bottom), the tRNAs with each amino acid specificity are colored the same way, alternating dark and light by family for clarity.