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Construction of a phylogenetic tree of photosynthetic prokaryotes based on average similarities of whole genome sequences.

ABSTRACT: Phylogenetic trees have been constructed for a wide range of organisms using gene sequence information, especially through the identification of orthologous genes that have been vertically inherited. The number of available complete genome sequences is rapidly increasing, and many tools for construction of genome trees based on whole genome sequences have been proposed. However, development of a reasonable method of using complete genome sequences for construction of phylogenetic trees has not been established. We have developed a method for construction of phylogenetic trees based on the average sequence similarities of whole genome sequences. We used this method to examine the phylogeny of 115 photosynthetic prokaryotes, i.e., cyanobacteria, Chlorobi, proteobacteria, Chloroflexi, Firmicutes and nonphotosynthetic organisms including Archaea. Although the bootstrap values for the branching order of phyla were low, probably due to lateral gene transfer and saturated mutation, the obtained tree was largely consistent with the previously reported phylogenetic trees, indicating that this method is a robust alternative to traditional phylogenetic methods.

SUBMITTER: Satoh S

PROVIDER: S-EPMC3724816 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Construction of a phylogenetic tree of photosynthetic prokaryotes based on average similarities of whole genome sequences.

Satoh Soichirou S Mimuro Mamoru M Tanaka Ayumi A

PloS one 20130726 7

Phylogenetic trees have been constructed for a wide range of organisms using gene sequence information, especially through the identification of orthologous genes that have been vertically inherited. The number of available complete genome sequences is rapidly increasing, and many tools for construction of genome trees based on whole genome sequences have been proposed. However, development of a reasonable method of using complete genome sequences for construction of phylogenetic trees has not b ...[more]

PMID: 23922968

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Project description:BackgroundThe efficiencies of the stop codons TAA, TAG, and TGA in protein synthesis termination are not the same. These variations could allow many genes to be regulated. There are many similar nucleotide trimers found on the second and third reading-frames of a gene. They are called premature stop codons (PSC). Like stop codons, the PSC in bacterial genomes are also highly bias in terms of their quantities and qualities on the genes. Phylogenetically related species often share a similar PSC profile. We want to know whether the selective forces that influence the stop codons and the PSC usage biases in a genome are related. We also wish to know how strong these trimers in a genome are related to the natural history of the bacterium. Knowing these relations may provide better knowledge in the phylogeny of bacteriaResultsA 16SrRNA-alignment tree of 19 well-studied α-, β- and γ-Proteobacteria Type species is used as standard reference for bacterial phylogeny. The genomes of sixty-one bacteria, belonging to the α-, β- and γ-Proteobacteria subphyla, are used for this study. The stop codons and PSC are collectively termed "Translation Stop Signals" (TSS). A gene is represented by nine scalars corresponding to the numbers of counts of TAA, TAG, and TGA on each of the three reading-frames of that gene. "Translation Stop Signals Ratio" (TSSR) is the ratio between the TSS counts. Four types of TSSR are investigated. The TSSR-1, TSSR-2 and TSSR-3 are each a 3-scalar series corresponding respectively to the average ratio of TAA: TAG: TGA on the first, second, and third reading-frames of all genes in a genome. The Genomic-TSSR is a 9-scalar series representing the ratio of distribution of all TSS on the three reading-frames of all genes in a genome. Results show that bacteria grouped by their similarities based on TSSR-1, TSSR-2, or TSSR-3 values could only partially resolve the phylogeny of the species. However, grouping bacteria based on thier Genomic-TSSR values resulted in clusters of bacteria identical to those bacterial clusters of the reference tree. Unlike the 16SrRNA method, the Genomic-TSSR tree is also able to separate closely related species/strains at high resolution. Species and strains separated by the Genomic-TSSR grouping method are often in good agreement with those classified by other taxonomic methods. Correspondence analysis of individual genes shows that most genes in a bacterial genome share a similar TSSR value. However, within a chromosome, the Genic-TSSR values of genes near the replication origin region (Ori) are more similar to each other than those genes near the terminus region (Ter).ConclusionThe translation stop signals on the three reading-frames of the genes on a bacterial genome are interrelated, possibly due to frequent off-frame recombination facilitated by translational-associated recombination (TSR). However, TSR may not occur randomly in a bacterial chromosome. Genes near the Ori region are often highly expressed and a bacterium always maintains multiple copies of Ori. Frequent collisions between DNA- polymerase and RNA-polymerase would create many DNA strand-breaks on the genes; whereas DNA strand-break induced homologues-recombination is more likely to take place between genes with similar sequence. Thus, localized recombination could explain why the TSSR of genes near the Ori region are more similar to each other. The quantity and quality of these TSS in a genome strongly reflect the natural history of a bacterium. We propose that the Genomic- TSSR can be used as a subjective biomarker to represent the phyletic status of a bacterium.

Project description:BackgroundThe lancelet Asymmetron inferum (subphylum Cephalochordata) was recently discovered on the ocean floor off the southwest coast of Japan at a depth of 229 m, in an anaerobic and sulfide-rich environment caused by decomposing bodies of the sperm whale Physeter macrocephalus. This deep sulfide-rich habitat of A. inferum is unique among the lancelets. The distinguishing adaptation of this species to such an extraordinary habitat can be considered in a phylogenetic framework. As the first step of reconstruction of the evolutionary processes in this species, we investigated its phylogenetic position based on 11 whole mitochondrial genome sequences including the newly determined ones of the whale-fall lancelet A. inferum and two coral-reef congeners.ResultsOur phylogenetic analyses showed that extant lancelets are clustered into two major clades, the Asymmetron clade and the Epigonichthys + Branchiostoma clade. A. inferum was in the former and placed in the sister group to A. lucayanum complex. The divergence time between A. inferum and A. lucayanum complex was estimated to be 115 Mya using the penalized likelihood (PL) method or 97 Mya using the nonparametric rate smoothing (NPRS) method (the middle Cretaceous). These are far older than the first appearance of large whales (the middle Eocene, 40 Mya). We also discovered that A. inferum mitogenome (mitochondrial genome) has been subjected to large-scale gene rearrangements, one feature of rearrangements being unique among the lancelets and two features shared with A. lucayanum complex.ConclusionOur study supports the monophyly of genus Asymmetron assumed on the basis of the morphological characters. Furthermore, the features of the A. inferum mitogenome expand our knowledge of variation within cephalochordate mitogenomes, adding a new case of transposition and inversion of the trnQ gene. Our divergence time estimation suggests that A. inferum remained a member of the Mesozoic and the early Cenozoic large vertebrate-fall communities before shifting to become a whale-fall specialist.

Project description:Background & objectivesSeveral phylogenetic classification systems have been devised to trace the viral lineages of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, inconsistency in the nomenclature limits uniformity in its epidemiological understanding. This study provides an integration of existing classifications and describes evolutionary trends of the SARS-CoV-2 strains circulating in India.MethodsThe whole genomes of 330 SARS-CoV-2 samples were sequenced using next-generation sequencing (NGS). Phylogenetic and sequence analysis of a total of 3014 Indian SARS-CoV-2 sequences from 20 different States/Union Territories (January to September 2020) from the Global Initiative on Sharing All Influenza Data (GISAID) database was performed to observe the clustering of Nextstrain and Phylogenetic Assignment of Named Global Outbreak LINeages (Pangolin) lineages with the GISAID clades. The identification of mutational sites under selection pressure was performed using Mixed Effects Model of Evolution and Single-Likelihood Ancestor Counting methods available in the Datamonkey server.ResultsTemporal data of the Indian SARS-CoV-2 genomes revealed that except for Uttarakhand, West Bengal and Haryana that showed the circulation of GISAID clade O even after July 2020, the rest of the States showed a complete switch to GR/GH clades. Pangolin lineages B.1.1.8 and B.1.113 identified within GR and GH clades, respectively, were noted to be indigenous evolutions. Sites identified to be under positive selection pressure within these clades were found to occur majorly in the non-structural proteins coded by ORF1a and ORF1b.Interpretation & conclusionsThis study interpreted the geographical and temporal dominance of SARS-CoV-2 strains in India over a period of nine months based on the GISAID classification. An integration of the GISAID, Nextstrain and Pangolin classifications is also provided. The emergence of new lineages B.1.1.8 and B.1.113 was indicative of host-specific evolution of the SARS-CoV-2 strains in India. The hotspot mutations such as those driven by positive selection need to be further characterized.

Dataset Information

Construction of a phylogenetic tree of photosynthetic prokaryotes based on average similarities of whole genome sequences.

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Construction of a phylogenetic tree of photosynthetic prokaryotes based on average similarities of whole genome sequences.

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