1887

Abstract

New insights in evolution are available thanks to next-generation sequencing technologies in recent years. However, due to the network of complex relations between species, caused by the intensive horizontal gene transfer (HGT) between different bacterial species, it is difficult to discover bacterial evolution. This difficulty leads to new research in the field of phylogeny, including the gene-based phylogeny, in contrast to sequence-based phylogeny. In previous articles, we presented evolutionary insights of Synteny Index (SI) study on a large biological dataset. We showed that the SI approach naturally clusters 1133 species into 39 cliques of closely related species. In addition, we presented a model that enables calculation of the number of translocation events between genomes based on their SI distance. Here, these two studies are combined together and lead to new insights. A principal result is the relation between two evolutionary clocks: the well-known sequence-based clock influenced by point mutations, and SI distance clock influenced by translocation events. A surprising linear relation between these two evolutionary clocks rising for closely related species across all genus. In other words, these two different clocks are ticking at the same rate inside the genus level. Conversely, a phase-transition manner discovered between these two clocks across non-closely related species. This may suggest a new genus definition based on an analytic approach, since the phase-transition occurs where each gene, on average, undergoes one translocation event. In addition, rare cases of HGT among highly conserved genes can be detected as outliers from the phase-transition pattern.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2022-02-16
2022-05-18
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References

  1. Randall KH, Michael GJ. Medical Microbiology 1996
    [Google Scholar]
  2. Crow JF. The high spontaneous mutation rate: is it a health risk?. Proc Natl Acad Sci USA 1997; 94:8380–8386 [View Article] [PubMed]
    [Google Scholar]
  3. Pariente N, Sierra S, Airaksinen A. Action of mutagenic agents and antiviral inhibitors on foot-and-mouth disease virus. Virus Res 2005; 107:183–193 [View Article] [PubMed]
    [Google Scholar]
  4. Doolittle WF. Phylogenetic classification and the universal tree. Science 1999; 284:2124–2129 [View Article]
    [Google Scholar]
  5. Grusea S. Measures for the exceptionality of gene order in conserved genomic regions. Adv Appl Math 2010; 45:359–372 [View Article]
    [Google Scholar]
  6. Huang S. The genetic equidistance result of molecular evolution is independent of mutation rates. J Comput Sci Syst Biol 2008; 1:92–102 [View Article]
    [Google Scholar]
  7. Ayala FJ. Molecular clock mirages. Bioessays 1999; 21:71–75 [View Article]
    [Google Scholar]
  8. Drummond AJ, Ho SYW, Phillips MJ, Rambaut A. Relaxed phylogenetics and dating with confidence. PLoS Biol 2006; 4:e88 [View Article] [PubMed]
    [Google Scholar]
  9. Ho SY, Phillips MJ, Cooper A, Drummond AJ. Time dependency of molecular rate estimates and systematic overestimation of recent divergence times. Mol Biol Evol 2005; 22:1561–1568
    [Google Scholar]
  10. Bapteste E, Susko E, Leigh J, MacLeod D, Charlebois R et al. Do orthologous gene phylogenies really support tree-thinking?. BMC Evol Biol 2005; 5:33 [View Article] [PubMed]
    [Google Scholar]
  11. Woese CR. Bacterial evolution. Microbiol Rev 1987; 51:221–271 [View Article] [PubMed]
    [Google Scholar]
  12. Cohen O, Gophna U, Pupko T. The complexity hypothesis revisited: connectivity rather than function constitutes a barrier to horizontal gene transfer. Mol Biol Evol 2011; 28:1481–1489 [View Article] [PubMed]
    [Google Scholar]
  13. Kitahara K, Miyazaki K. Revisiting bacterial phylogeny: Natural and experimental evidence for horizontal gene transfer of 16S rRNA. Mob Genet Elements 2013; 3:e24210 [View Article] [PubMed]
    [Google Scholar]
  14. Kitahara K, Yasutake Y, Miyazaki K. Mutational robustness of 16S ribosomal RNA, shown by experimental horizontal gene transfer in Escherichia coli. Proc Natl Acad Sci U S A 2012; 109:19220–19225 [View Article]
    [Google Scholar]
  15. Tian R-M, Cai L, Zhang W-P, Cao H-L, Qian P-Y. Rare events of intragenus and intraspecies horizontal transfer of the 16S rrna gene. Genome Biol Evol 2015; 7:2310–2320
    [Google Scholar]
  16. Hein J. Reconstructing evolution of sequences subject to recombination using parsimony. Math Biosci 1990; 98:185–200 [View Article] [PubMed]
    [Google Scholar]
  17. Garcia-Vallve S, Romeu A, Palau J. Horizontal gene transfer in bacterial and archaeal complete. Genome Res 2000; 10:1719–1725 [View Article] [PubMed]
    [Google Scholar]
  18. Adato O, Ninyo N, Gophna U, Snir S. Detecting horizontal gene transfer between closely related taxa. PLoS Comput Biol 2015; 11:e1004408 [View Article] [PubMed]
    [Google Scholar]
  19. Baum DA. Species as ranked taxa. Syst Biol 2009; 58:74–86 [View Article]
    [Google Scholar]
  20. Staley JT. The bacterial species dilemma and the genomic–phylogenetic species concept. Philos Trans R Soc Lond B Biol Sci 2006; 361:1899–1909 [View Article]
    [Google Scholar]
  21. Blaxter M, Mann J, Chapman T, Thomas F, Whitton C et al. Defining operational taxonomic units using DNA barcode data. Phil Trans R Soc B 2005; 360:1935–1943 [View Article]
    [Google Scholar]
  22. Rossi-Tamisier M, Benamar S, Raoult D, Fournier P-E. Cautionary tale of using 16S rRNA gene sequence similarity values in identification of human-associated bacterial species. Int J Syst Evol Microbiol 2015; 65:1929–1934 [View Article]
    [Google Scholar]
  23. Moore WEC, Stackebrandt E, Kandler O, Colwell RR, Krichevsky MI et al. Report of the ad hoc committee on reconciliation of approaches to bacterial systematics. Int J Syst Bacteriol 1987; 37:463–464 [View Article]
    [Google Scholar]
  24. Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P et al. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 2007; 57:81–91 [View Article]
    [Google Scholar]
  25. Shifman A, Ninyo N, Gophna U, Snir S. Phylo SI: a new genome wide approach for prokaryotic phylogeny. Nucleic Acids Res 2014; 42:2391–2404 [View Article] [PubMed]
    [Google Scholar]
  26. Powell S, Szklarczyk D, Trachana K, Roth A, Kuhn M et al. eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges. Nucleic Acids Res 2011; 40:D284–9 [View Article] [PubMed]
    [Google Scholar]
  27. Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM et al. Ribosomal:database project: data and tools for high throughput rrna. Nucleic Acids Res 2014; 42:D633–D642
    [Google Scholar]
  28. Sevillya G, Snir S. Synteny footprints provide clearer phylogenetic signal than sequence data for prokayotic classification. Mol Phylo Evol 2018; 136:128–137
    [Google Scholar]
  29. Aric A, Daniel A, Swart PJ. Exploring network structure, dynamics, and function using Network. In Proceedings of the 7th Python in Science Conference Pasadena, USA: 2008
    [Google Scholar]
  30. Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T et al. SciPy 1.0: fundamental algorithms for scientific computing in python. Nat Methods 2020; 17:261–272
    [Google Scholar]
  31. Fabian P, Gael V, Alexandre G, Vincent M, Bertrand T. Scikit-learn: Machine learning in Python. J Mach Learn Res 2011; 12:2825–2830
    [Google Scholar]
  32. Thomas H, Charles R. Evolution of protein molecules. In Mammalian Protein Metabolism New York: Academic Press; 1969
    [Google Scholar]
  33. Sevillya G, Doerr D, Lerner Y, Stoye J, Steel M et al. Horizontal gene transfer phylogenetics: a random walk approach. Mol Biol Evol 2019; 37:1470–1479
    [Google Scholar]
  34. Peabody V GL, Li H, Kao KC. Sexual recombination and increased mutation rate expedite evolution of Escherichia coli in varied fitness landscapes. Nat Commun 2017; 8:2112 [View Article]
    [Google Scholar]
  35. Wolf YI, Makarova KS, Lobkovsky AE, Koonin EV. Two fundamentally different classes of microbial genes. Nat Microbiol 2016; 2:16208 [View Article]
    [Google Scholar]
  36. Hanoch G. The elasticity of scale and the shape of average costs. American Economic Association 1975; 65:492–497
    [Google Scholar]
  37. Irelan JT, Hagemann AT, Selker EU. High frequency repeat-induced point mutation (RIP) is not associated with efficient recombination in neurospora. Genetics 1994; 138:1093–1103 [View Article]
    [Google Scholar]
  38. Yu S, Fearnhead P, Holland BR, Biggs P, Maiden M et al. Estimating the relative roles of recombination and point mutation in the generation of single locus variants in Campylobacter jejuni and Campylobacter coli. J Mol Evol 2012; 74:273–280 [View Article]
    [Google Scholar]
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