Synteny footprints provide clearer phylogenetic signal than sequence data for prokaryotic classification

Gur Sevillya, Sagi Snir

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Extensive research efforts have been made to reconstruct the Tree of Life, aiming to explain the evolutionary history of life on earth. We expect the advent of next generation sequencing methods to bring us close to solving this challenge. Notwithstanding, with the accumulation of this mass of molecular data, it becomes evident that this solution is more complex and far from reach, especially among prokaryotes. One of the reasons for this is the ability of bacteria to perform horizontal gene transfer (HGT), creating substantial conflicts between different genes histories. Fortunately, evolution has equipped us with several markers with different levels of resolution, among which is synteny - the conservation of gene order along the chromosome. Results: We have performed a comprehensive phylogenomic study via synteny based footprints. We build on the synteny index (SI) concept, defined in a pilot work of ours, and extend it to a systematic phylogenetic method with well defined valid regions of operations. Applying it to the EggNOG repository, divides all species into 39 clusters, agreeing with the conventional taxonomy. We show analytically that the signal of the standard phylogenetic marker, the 16S, is too faint for reliable classification. Conclusions: This work exhibits three separate yet related contributions. In terms of phylogenetics, it demonstrates quantitatively the advantage of the SI-based approach over the standard sequence based marker. Evolutionarily, the tree we produce is unique both in its specificity and broadness. Methodologically, the U-shape approach we developed, from synthetic realm, to real life and back to simulation, is novel and allow us to simulate the exact realistic conditions.

Original languageAmerican English
Pages (from-to)128-137
Number of pages10
JournalMolecular Phylogenetics and Evolution
Volume136
DOIs
StatePublished - Jul 2019

All Science Journal Classification (ASJC) codes

  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology

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