The archaea monophyly issue: A phylogeny of translational elongation factor G(2) sequences inferred from an optimized selection of alignment positions

Accounting for alignment uncertainty in phylogenomics

Uncertainty in multiple sequence alignments has a large impact on phylogenetic analyses. Little has been done to evaluate the quality of individual positions in protein sequence alignments, which directly impact the accuracy of phylogenetic trees. Here we describe ZORRO, a probabilistic masking program that accounts for alignment uncertainty by assigning confidence scores to each alignment position. Using the BALIBASE database and in simulation studies, we demonstrate that masking by ZORRO significantly reduces the alignment uncertainty and improves the tree accuracy.

Analysis of the fusA2 locus encoding EFG2 in Mycobacterium smegmatis

The translation elongation factor G (EFG) is encoded by the fusA gene. Several bacteria possess a second fusA-like locus, fusA2 which encodes EFG2. A comparison of EFG and EFG2 from various bacteria reveals that EFG2 preserves domain organization and maintains significant sequence homology with EFG, suggesting that EFG2 may function as an elongation factor. However, with the single exception of a recent study on Thermus thermophilus EFG2, this class of EFG-like factors has not been investigated. Here, we have characterized EFG2 (MSMEG_6535) from Mycobacterium smegmatis. Expression of EFG2 was detected in stationary phase cultures of M. smegmatis (Msm). Our in vitro studies show that while MsmEFG2 binds guanine nucleotides, it lacks the ribosome-dependent GTPase activity characteristic of EFGs. Furthermore, unlike MsmEFG (MSMEG_1400), MsmEFG2 failed to rescue an E. coli strain harboring a temperature-sensitive allele of EFG, for its growth at the non-permissive temperature. Subsequent experiments showed that the fusA2 gene could be disrupted in M. smegmatis mc(2)155 with Kan(R) marker. The M. smegmatis fusA2::kan strain was viable and showed growth kinetics similar to that of the parent strain (wild-type for fusA2). However, in the growth competition assays, the disruption of fusA2 was found to confer a fitness disadvantage to M. smegmatis, raising the possibility that EFG2 is of some physiological relevance to mycobacteria.

Evolution of elongation factor G and the origins of mitochondrial and chloroplast forms

Protein synthesis elongation factor G (EF-G) is an essential protein with central roles in both the elongation and ribosome recycling phases of protein synthesis. Although EF-G evolution is predicted to be conservative, recent reports suggest otherwise. We have characterized EF-G in terms of its molecular phylogeny, genomic context, and patterns of amino acid substitution. We find that most bacteria carry a single "canonical" EF-G, which is phylogenetically conservative and encoded in an str operon. However, we also find a number of EF-G paralogs. These include a pair of EF-Gs that are mostly found together and in an eclectic subset of bacteria, specifically δ-proteobacteria, spirochaetes, and planctomycetes (the "spd" bacteria). These spdEFGs have also given rise to the mitochondrial factors mtEFG1 and mtEFG2, which probably arrived in eukaryotes before the eukaryotic last common ancestor. Meanwhile, chloroplasts apparently use an α-proteobacterial-derived EF-G rather than the expected cyanobacterial form. The long-term comaintenance of the spd/mtEFGs may be related to their subfunctionalization for translocation and ribosome recycling. Consistent with this, patterns of sequence conservation and site-specific evolutionary rate shifts suggest that the faster evolving spd/mtEFG2 has lost translocation function, but surprisingly, the protein also shows little conservation of sites related to recycling activity. On the other hand, spd/mtEFG1, although more slowly evolving, shows signs of substantial remodeling. This is particularly extensive in the GTPase domain, including a highly conserved three amino acid insertion in switch I. We suggest that subfunctionalization of the spd/mtEFGs is not a simple case of specialization for subsets of original activities. Rather, the duplication allows the release of one paralog from the selective constraints imposed by dual functionality, thus allowing it to become more highly specialized. Thus, the potential for fine tuning afforded by subfunctionalization may explain the maintenance of EF-G paralogs.

Mega-phylogeny approach for comparative biology: an alternative to supertree and supermatrix approaches

Background

Biology has increasingly recognized the necessity to build and utilize larger phylogenies to address broad evolutionary questions. Large phylogenies have facilitated the discovery of differential rates of molecular evolution between trees and herbs. They have helped us understand the diversification patterns of mammals as well as the patterns of seed evolution. In addition to these broad evolutionary questions there is increasing awareness of the importance of large phylogenies for addressing conservation issues such as biodiversity hotspots and response to global change. Two major classes of methods have been employed to accomplish the large tree-building task: supertrees and supermatrices. Although these methods are continually being developed, they have yet to be made fully accessible to comparative biologists making extremely large trees rare.

Results

Here we describe and demonstrate a modified supermatrix method termed mega-phylogeny that uses databased sequences as well as taxonomic hierarchies to make extremely large trees with denser matrices than supermatrices. The two major challenges facing large-scale supermatrix phylogenetics are assembling large data matrices from databases and reconstructing trees from those datasets. The mega-phylogeny approach addresses the former as the latter is accomplished by employing recently developed methods that have greatly reduced the run time of large phylogeny construction. We present an algorithm that requires relatively little human intervention. The implemented algorithm is demonstrated with a dataset and phylogeny for Asterales (within Campanulidae) containing 4954 species and 12,033 sites and an rbcL matrix for green plants (Viridiplantae) with 13,533 species and 1,401 sites.

Conclusion

By examining much larger phylogenies, patterns emerge that were otherwise unseen. The phylogeny of Viridiplantae successfully reconstructs major relationships of vascular plants that previously required many more genes. These demonstrations underscore the importance of using large phylogenies to uncover important evolutionary patterns and we present a fast and simple method for constructing these phylogenies.

Multiple sequence alignment: in pursuit of homologous DNA positions

DNA sequence alignment is a prerequisite to virtually all comparative genomic analyses, including the identification of conserved sequence motifs, estimation of evolutionary divergence between sequences, and inference of historical relationships among genes and species. While it is mere common sense that inaccuracies in multiple sequence alignments can have detrimental effects on downstream analyses, it is important to know the extent to which the inferences drawn from these alignments are robust to errors and biases inherent in all sequence alignments. A survey of investigations into strengths and weaknesses of sequence alignments reveals, as expected, that alignment quality is generally poor for two distantly related sequences and can often be improved by adding additional sequences as stepping stones between distantly related species. Errors in sequence alignment are also found to have a significant negative effect on subsequent inference of sequence divergence, phylogenetic trees, and conserved motifs. However, our understanding of alignment biases remains rudimentary, and sequence alignment procedures continue to be used somewhat like benign formatting operations to make sequences equal in length. Because of the central role these alignments now play in our endeavors to establish the tree of life and to identify important parts of genomes through evolutionary functional genomics, we see a need for increased community effort to investigate influences of alignment bias on the accuracy of large-scale comparative genomics.

Alignment and Topological Accuracy of the Direct Optimization approach via POY and Traditional Phylogenetics via ClustalW + PAUP*

Direct optimization frameworks for simultaneously estimating alignments and phylogenies have recently been developed. One such method, implemented in the program POY, is becoming more common for analyses of variable length sequences (e.g., analyses using ribosomal genes) and for combined evidence analyses (morphology + multiple genes). Simulation of sequences containing insertion and deletion events was performed in order to directly compare a widely used method of multiple sequence alignment (ClustalW) and subsequent parsimony analysis in PAUP* with direct optimization via POY. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (clocklike, non-clocklike, and ultrametric). Alignment accuracy scores for the implied alignments from POY and the multiple sequence alignments from ClustalW were calculated and compared. In almost all cases (99.95%), ClustalW produced more accurate alignments than POY-implied alignments, judged by the proportion of correctly identified homologous sites. Topological accuracy (distance to the true tree) for POY topologies and topologies generated under parsimony in PAUP* from the ClustalW alignments were also compared. In 44.94% of the cases, Clustal alignment tree reconstructions via PAUP* were more accurate than POY, whereas in 16.71% of the cases POY reconstructions were more topologically accurate (38.38% of the time they were equally accurate). Comparisons between POY hypothesized alignments and the true alignments indicated that, on average, as alignment error increased, topological accuracy decreased.

Multiple sequence alignment accuracy and phylogenetic inference

Phylogenies are often thought to be more dependent upon the specifics of the sequence alignment rather than on the method of reconstruction. Simulation of sequences containing insertion and deletion events was performed in order to determine the role that alignment accuracy plays during phylogenetic inference. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (ultrametric equal branch length, ultrametric random branch length, nonultrametric random branch length). Comparisons between hypothesized alignments and true alignments enabled determination of two measures of alignment accuracy, that of the total data set and that of individual branches. In general, our results indicate that as alignment error increases, topological accuracy decreases. This trend was much more pronounced for data sets derived from more pectinate topologies. In contrast, for balanced, ultrametric, equal branch length tree shapes, alignment inaccuracy had little average effect on tree reconstruction. These conclusions are based on average trends of many analyses under different conditions, and any one specific analysis, independent of the alignment accuracy, may recover very accurate or inaccurate topologies. Maximum likelihood and Bayesian, in general, outperformed neighbor joining and maximum parsimony in terms of tree reconstruction accuracy. Results also indicated that as the length of the branch and of the neighboring branches increase, alignment accuracy decreases, and the length of the neighboring branches is the major factor in topological accuracy. Thus, multiple-sequence alignment can be an important factor in downstream effects on topological reconstruction.

RibAlign: a software tool and database for eubacterial phylogeny based on concatenated ribosomal protein subunits

Background

Until today, analysis of 16S ribosomal RNA (rRNA) sequences has been the de-facto gold standard for the assessment of phylogenetic relationships among prokaryotes. However, the branching order of the individual phlya is not well-resolved in 16S rRNA-based trees. In search of an improvement, new phylogenetic methods have been developed alongside with the growing availability of complete genome sequences. Unfortunately, only a few genes in prokaryotic genomes qualify as universal phylogenetic markers and almost all of them have a lower information content than the 16S rRNA gene. Therefore, emphasis has been placed on methods that are based on multiple genes or even entire genomes. The concatenation of ribosomal protein sequences is one method which has been ascribed an improved resolution. Since there is neither a comprehensive database for ribosomal protein sequences nor a tool that assists in sequence retrieval and generation of respective input files for phylogenetic reconstruction programs, RibAlign has been developed to fill this gap.

Results

RibAlign serves two purposes: First, it provides a fast and scalable database that has been specifically adapted to eubacterial ribosomal protein sequences and second, it provides sophisticated import and export capabilities. This includes semi-automatic extraction of ribosomal protein sequences from whole-genome GenBank and FASTA files as well as exporting aligned, concatenated and filtered sequence files that can directly be used in conjunction with the PHYLIP and MrBayes phylogenetic reconstruction programs.

Conclusion

Up to now, phylogeny based on concatenated ribosomal protein sequences is hampered by the limited set of sequenced genomes and high computational requirements. However, hundreds of full and draft genome sequencing projects are on the way, and advances in cluster-computing and algorithms make phylogenetic reconstructions feasible even with large alignments of concatenated marker genes. RibAlign is a first step in this direction and may be particularly interesting to scientists involved in whole genome sequencing of representatives of new or sparsely studied eubacterial phyla. RibAlign is available at

Multiple sequence alignment accuracy and evolutionary distance estimation

BACKGROUND

Sequence alignment is a common tool in bioinformatics and comparative genomics. It is generally assumed that multiple sequence alignment yields better results than pair wise sequence alignment, but this assumption has rarely been tested, and never with the control provided by simulation analysis. This study used sequence simulation to examine the gain in accuracy of adding a third sequence to a pair wise alignment, particularly concentrating on how the phylogenetic position of the additional sequence relative to the first pair changes the accuracy of the initial pair's alignment as well as their estimated evolutionary distance.

RESULTS

The maximal gain in alignment accuracy was found not when the third sequence is directly intermediate between the initial two sequences, but rather when it perfectly subdivides the branch leading from the root of the tree to one of the original sequences (making it half as close to one sequence as the other). Evolutionary distance estimation in the multiple alignment framework, however, is largely unrelated to alignment accuracy and rather is dependent on the position of the third sequence; the closer the branch leading to the third sequence is to the root of the tree, the larger the estimated distance between the first two sequences.

CONCLUSION

The bias in distance estimation appears to be a direct result of the standard greedy progressive algorithm used by many multiple alignment methods. These results have implications for choosing new taxa and genomes to sequence when resources are limited.

Evolutionary distance estimation and fidelity of pair wise sequence alignment

BACKGROUND

Evolutionary distances are a critical measure in comparative genomics and molecular evolutionary biology. A simulation study was used to examine the effect of alignment accuracy of DNA sequences on evolutionary distance estimation.

RESULTS

Under the studied conditions, distance estimation was relatively unaffected by alignment error (50% or more of the sites incorrectly aligned) as long as 50% or more of the sites were identical among the sequences (observed P-distance < 0.5). Beyond this threshold, the alignment procedure artificially inflates the apparent sequence identity, skewing distance estimates, and creating alignments that are essentially indistinguishable from random data. This general result was independent of substitution model, sequence length, and insertion and deletion size and rate.

CONCLUSION

Examination of the estimated sequence identity may yield some guidance as to the accuracy of the alignment. Inaccurate alignments are expected to have large effects on analyses dependent on site specificity, but analyses that depend on evolutionary distance may be somewhat robust to alignment error as long as fewer than half of the sites have diverged.

A genomic timescale of prokaryote evolution: insights into the origin of methanogenesis, phototrophy, and the colonization of land

Background

The timescale of prokaryote evolution has been difficult to reconstruct because of a limited fossil record and complexities associated with molecular clocks and deep divergences. However, the relatively large number of genome sequences currently available has provided a better opportunity to control for potential biases such as horizontal gene transfer and rate differences among lineages. We assembled a data set of sequences from 32 proteins (~7600 amino acids) common to 72 species and estimated phylogenetic relationships and divergence times with a local clock method.

Results

Our phylogenetic results support most of the currently recognized higher-level groupings of prokaryotes. Of particular interest is a well-supported group of three major lineages of eubacteria (Actinobacteria, Deinococcus, and Cyanobacteria) that we call Terrabacteria and associate with an early colonization of land. Divergence time estimates for the major groups of eubacteria are between 2.5–3.2 billion years ago (Ga) while those for archaebacteria are mostly between 3.1–4.1 Ga. The time estimates suggest a Hadean origin of life (prior to 4.1 Ga), an early origin of methanogenesis (3.8–4.1 Ga), an origin of anaerobic methanotrophy after 3.1 Ga, an origin of phototrophy prior to 3.2 Ga, an early colonization of land 2.8–3.1 Ga, and an origin of aerobic methanotrophy 2.5–2.8 Ga.

Conclusions

Our early time estimates for methanogenesis support the consideration of methane, in addition to carbon dioxide, as a greenhouse gas responsible for the early warming of the Earths' surface. Our divergence times for the origin of anaerobic methanotrophy are compatible with highly depleted carbon isotopic values found in rocks dated 2.8–2.6 Ga. An early origin of phototrophy is consistent with the earliest bacterial mats and structures identified as stromatolites, but a 2.6 Ga origin of cyanobacteria suggests that those Archean structures, if biologically produced, were made by anoxygenic photosynthesizers. The resistance to desiccation of Terrabacteria and their elaboration of photoprotective compounds suggests that the common ancestor of this group inhabited land. If true, then oxygenic photosynthesis may owe its origin to terrestrial adaptations.

The origin and evolution of model organisms

The phylogeny and timescale of life are becoming better understood as the analysis of genomic data from model organisms continues to grow. As a result, discoveries are being made about the early history of life and the origin and development of complex multicellular life. This emerging comparative framework and the emphasis on historical patterns is helping to bridge barriers among organism-based research communities.

Genomics and early cellular evolution. The origin of the DNA world

The sequencing of several genomes from each of the three domains of life (Archaea, Bacteria and Eukarya) has provided a huge amount of data that can be used to gain insight about early cellular evolution. Some features of the universal tree of life based on rRNA polygenies have been confirmed, such as the division of the cellular living world into three domains. The monophyly of each domain is supported by comparative genomics. However, the hyperthermophilic nature of the 'last universal common ancestor' (LUCA) is not confirmed. Comparative genomics has revealed that gene transfers have been (and still are) very frequent in genome evolution. Nevertheless, a core of informational genes appears more resistant to transfer, testifying for a close relationship between archaeal and eukaryal informational processes. This observation can be explained either by a common unique history between Archaea and Eukarya or by an atypical evolution of these systems in Bacteria. At the moment, comparative genomics still does not allow to choose between a simple LUCA, possibly with an RNA genome, or a complex LUCA, with a DNA genome and informational mechanisms similar to those of Archaea and Eukarya. Further comparative studies on informational mechanisms in the three domains should help to resolve this critical question. The role of viruses in the origin and evolution of DNA genomes also appears an area worth of active investigations. I suggest here that DNA and DNA replication mechanisms appeared first in the virus world before being transferred into cellular organisms.