Dataset Information

Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected].

ABSTRACT: Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.

SUBMITTER: Vishnoi A

PROVIDER: S-EPMC2994773 | biostudies-other | 2010

REPOSITORIES: biostudies-other

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Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected].

Vishnoi Anchal A Roy Rahul R Prasad Hanumanthappa K HK Bhattacharya Alok A

PloS one 20101130 11

Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequ ...[more]

PMID: 21152403

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Project description:Using genetic data to resolve the evolutionary relationships of species is of major interest in evolutionary and systematic biology. However, reconstructing the sequence of speciation events, the so-called species tree, in closely related and potentially hybridizing species is very challenging. Processes such as incomplete lineage sorting and interspecific gene flow result in local gene genealogies that differ in their topology from the species tree, and analyses of few loci with a single sequence per species are likely to produce conflicting or even misleading results. To study these phenomena on a full phylogenomic scale, we use whole-genome sequence data from 200 individuals of four black-and-white flycatcher species with so far unresolved phylogenetic relationships to infer gene tree topologies and visualize genome-wide patterns of gene tree incongruence. Using phylogenetic analysis in nonoverlapping 10-kb windows, we show that gene tree topologies are extremely diverse and change on a very small physical scale. Moreover, we find strong evidence for gene flow among flycatcher species, with distinct patterns of reduced introgression on the Z chromosome. To resolve species relationships on the background of widespread gene tree incongruence, we used four complementary coalescent-based methods for species tree reconstruction, including complex modeling approaches that incorporate post-divergence gene flow among species. This allowed us to infer the most likely species tree with high confidence. Based on this finding, we show that regions of reduced effective population size, which have been suggested as particularly useful for species tree inference, can produce positively misleading species tree topologies. Our findings disclose the pitfalls of using loci potentially under selection as phylogenetic markers and highlight the potential of modeling approaches to disentangle species relationships in systems with large effective population sizes and post-divergence gene flow.

Project description:Background:Cross-species whole-genome sequence alignment is a critical first step for genome comparative analyses, ranging from the detection of sequence variants to studies of chromosome evolution. Animal genomes are large and complex, and whole-genome alignment is a computationally intense process, requiring expensive high-performance computing systems due to the need to explore extensive local alignments. With hundreds of sequenced animal genomes available from multiple projects, there is an increasing demand for genome comparative analyses. Results:Here, we introduce G-Anchor, a new, fast, and efficient pipeline that uses a strictly limited but highly effective set of local sequence alignments to anchor (or map) an animal genome to another species' reference genome. G-Anchor makes novel use of a databank of highly conserved DNA sequence elements. We demonstrate how these elements may be aligned to a pair of genomes, creating anchors. These anchors enable the rapid mapping of scaffolds from a de novo assembled genome to chromosome assemblies of a reference species. Our results demonstrate that G-Anchor can successfully anchor a vertebrate genome onto a phylogenetically related reference species genome using a desktop or laptop computer within a few hours and with comparable accuracy to that achieved by a highly accurate whole-genome alignment tool such as LASTZ. G-Anchor thus makes whole-genome comparisons accessible to researchers with limited computational resources. Conclusions:G-Anchor is a ready-to-use tool for anchoring a pair of vertebrate genomes. It may be used with large genomes that contain a significant fraction of evolutionally conserved DNA sequences and that are not highly repetitive, polypoid, or excessively fragmented. G-Anchor is not a substitute for whole-genome aligning software but can be used for fast and accurate initial genome comparisons. G-Anchor is freely available and a ready-to-use tool for the pairwise comparison of two genomes.

Project description:BACKGROUND:The past decade has witnessed remarkable progress towards resolution of the Tree of Life. However, despite the increased use of genomic scale datasets, some phylogenetic relationships remain difficult to resolve. Here we employ anchored phylogenomics to capture 107 nuclear loci in 29 species of acanthomorph teleost fishes, with 25 of these species sampled from the recently delimited clade Ovalentaria. Previous studies employing multilocus nuclear exon datasets have not been able to resolve the nodes at the base of the Ovalentaria tree with confidence. Here we test whether a phylogenomic approach will provide better support for these nodes, and if not, why this may be. RESULTS:After using a novel method to account for paralogous loci, we estimated phylogenies with maximum likelihood and species tree methods using DNA sequence alignments of over 80,000 base pairs. Several key relationships within Ovalentaria are well resolved, including 1) the sister taxon relationship between Cichlidae and Pholidichthys, 2) a clade containing blennies, grammas, clingfishes, and jawfishes, and 3) monophyly of Atherinomorpha (topminnows, flyingfishes, and silversides). However, many nodes in the phylogeny associated with the early diversification of Ovalentaria are poorly resolved in several analyses. Through the use of rarefaction curves we show that limited phylogenetic resolution among the earliest nodes in the Ovalentaria phylogeny does not appear to be due to a deficiency of data, as average global node support ceases to increase when only 1/3rd of the sampled loci are used in analyses. Instead this lack of resolution may be driven by model misspecification as a Bayesian mixed model analysis of the amino acid dataset provided good support for parts of the base of the Ovalentaria tree. CONCLUSIONS:Although it does not appear that the limited phylogenetic resolution among the earliest nodes in the Ovalentaria phylogeny is due to a deficiency of data, it may be that both stochastic and systematic error resulting from model misspecification play a role in the poor resolution at the base of the Ovalentaria tree as a Bayesian approach was able to resolve some of the deeper nodes, where the other methods failed.

Dataset Information

Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected].

Publications

Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected].

Similar Datasets

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