Dataset Information

Improvement of phylogenetic method to analyze compositional heterogeneity.

ABSTRACT: Phylogenetic analysis is a key way to understand current research in the biological processes and detect theory in evolution of natural selection. The evolutionary relationship between species is generally reflected in the form of phylogenetic trees. Many methods for constructing phylogenetic trees, are based on the optimization criteria. We extract the biological data via modeling features, and then compare these characteristics to study the biological evolution between species.Here, we use maximum likelihood and Bayesian inference method to establish phylogenetic trees; multi-chain Markov chain Monte Carlo sampling method can be used to select optimal phylogenetic tree, resolving local optimum problem. The correlation model of phylogenetic analysis assumes that phylogenetic trees are built on homogeneous data, however there exists a large deviation in the presence of heterogeneous data. We use conscious detection to solve compositional heterogeneity. Our method is evaluated on two sets of experimental data, a group of bacterial 16S ribosomal RNA gene data, and a group of genetic data with five homologous species.Our method can obtain accurate phylogenetic trees on the homologous data, and also detect the compositional heterogeneity of experimental data. We provide an efficient method to enhance the accuracy of generated phylogenetic tree.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC5615240 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Improvement of phylogenetic method to analyze compositional heterogeneity.

Zhang Zehua Z Guo Kecheng K Pan Gaofeng G Tang Jijun J Guo Fei F

BMC systems biology 20170921 Suppl 4

<h4>Background</h4>Phylogenetic analysis is a key way to understand current research in the biological processes and detect theory in evolution of natural selection. The evolutionary relationship between species is generally reflected in the form of phylogenetic trees. Many methods for constructing phylogenetic trees, are based on the optimization criteria. We extract the biological data via modeling features, and then compare these characteristics to study the biological evolution between speci ...[more]

PMID: 28950863

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Project description:BACKGROUND:Mitochondrial genome (mt-genome) data can potentially return artefactual relationships in the higher-level phylogenetic inference of insects due to the biases of accelerated substitution rates and compositional heterogeneity. Previous studies based on mt-genome data alone showed a paraphyly of Cimicomorpha (Insecta, Hemiptera) due to the positions of the families Tingidae and Reduviidae rather than the monophyly that was supported based on morphological characters, morphological and molecular combined data and large scale molecular datasets. Various strategies have been proposed to ameliorate the effects of potential mt-genome biases, including dense taxon sampling, removal of third codon positions or purine-pyrimidine coding and the use of site-heterogeneous models. In this study, we sequenced the mt-genomes of five additional Tingidae species and discussed the compositional and mutational rate heterogeneity in mt-genomes and its effect on the phylogenetic inferences of Cimicomorpha by implementing the bias-reduction strategies mentioned above. RESULTS:Heterogeneity in nucleotide composition and mutational biases were found in mt protein-coding genes, and the third codon exhibited high levels of saturation. Dense taxon sampling of Tingidae and Reduviidae and the other common strategies mentioned above were insufficient to recover the monophyly of the well-established group Cimicomorpha. When the sites with weak phylogenetic signals in the dataset were removed, the remaining dataset of mt-genomes can support the monophyly of Cimicomorpha; this support demonstrates that mt-genomes possess strong phylogenetic signals for the inference of higher-level phylogeny of this group. Comparison of the ratio of the removal of amino acids for each PCG showed that ATP8 has the highest ratio while CO1 has the lowest. This pattern is largely congruent with the evolutionary rate of 13 PCGs that ATP8 represents the highest evolutionary rate, whereas CO1 appears to be the lowest. Notably, the value of Ka/Ks ratios of all PCGs is less than 1, indicating that these genes are likely evolving under purifying selection. CONCLUSIONS:Our results demonstrate that mt-genomes have sites with strong phylogenetic signals for the inference of higher-level phylogeny of Cimicomorpha. Consequently, bioinformatic approaches to removing sites with weak phylogenetic signals in mt-genome without relying on an a priori tree topology would greatly improve this field.

Dataset Information

Improvement of phylogenetic method to analyze compositional heterogeneity.

Publications

Improvement of phylogenetic method to analyze compositional heterogeneity.

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