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A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins.

ABSTRACT: Because of the limited effectiveness of prevailing phylogenetic methods when applied to highly divergent protein sequences, the phylogenetic analysis problem remains challenging. Here, we propose a sequence-based evolutionary distance algorithm termed sequence distance (SD), which innovatively incorporates site-to-site correlation within protein sequences into the distance estimation. In protein superfamilies, SD can effectively distinguish evolutionary relationships both within and between protein families, producing phylogenetic trees that closely align with those based on structural information, even with sequence identity less than 20%. SD is highly correlated with the similarity of the protein structure, and can calculate evolutionary distances for thousands of protein pairs within seconds using a single CPU, which is significantly faster than most protein structure prediction methods that demand high computational resources and long run times. The development of SD will significantly advance phylogenetics, providing researchers with a more accurate and reliable tool for exploring evolutionary relationships.

SUBMITTER: Cao W

PROVIDER: S-EPMC10662474 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins.

Cao Wei W Wu Lu-Yun LY Xia Xia-Yu XY Chen Xiang X Wang Zhi-Xin ZX Pan Xian-Ming XM

Scientific reports 20231120 1

Because of the limited effectiveness of prevailing phylogenetic methods when applied to highly divergent protein sequences, the phylogenetic analysis problem remains challenging. Here, we propose a sequence-based evolutionary distance algorithm termed sequence distance (SD), which innovatively incorporates site-to-site correlation within protein sequences into the distance estimation. In protein superfamilies, SD can effectively distinguish evolutionary relationships both within and between prot ...[more]

PMID: 37985846

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Project description:Leishmaniasis is a debilitating infectious disease that has a variety of clinical forms. In China, visceral leishmaniasis (VL) is the most common symptom, and L. donovani and/or L. infantum are the likely pathogens. In this study, multilocus sequence typing (MLST) of five enzyme-coding genes (fh, g6pdh, icd, mpi, pgd) and two conserved genes (hsp70, lack) was used to investigate the phylogenetic relationships of Chinese Leishmania strains. Concatenated alignment of the nucleotide sequences of the seven genes was analyzed and phylogenetic trees were constructed using neighbor-joining and maximum parsimony models. A set of additional sequences from 25 strains (24 strains belong to the L. donovani complex and one strain belongs to L. gerbilli) were retrieved from GenBank to infer the molecular evolutionary history of Leishmania from China and other endemic areas worldwide. Phylogenetic analyses consolidated Chinese Leishmania into four groups: (i) one clade A population comprised 13 isolates from different foci in China, which were pathogenic to humans and canines. This population was subdivided into two subclades, clade A1 and clade A2, which comprised sister organisms to the remaining members of the worldwide L. donovani complex; (ii) a population in clade B consisted of one reference strain of L. turanica and five Chinese strains from Xinjiang; (iii) clade C (SELF-7 and EJNI-154) formed a population that was closely related to clade B, and both isolates were identified as L. gerbilli; and (iv) the final group, clade D, included Sauroleishmania (LIZRD and KXG-E) and was distinct from the other strains. We hypothesize that the phylogeny of Chinese Leishmania is associated with the geographical origins rather than with the clinical forms (VL or CL) of leishmaniasis. To conclude, this study provides further molecular information on Chinese Leishmania isolates and the Chinese isolates appear to have a more complex evolutionary history than previously thought.

Dataset Information

A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins.

Publications

A sequence-based evolutionary distance method for Phylogenetic analysis of highly divergent proteins.

Similar Datasets

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