Horizontal Gene Transfer

Horizontal Gene Transfer

Horizontal gene transfer (HGT), the passage of genetic material between genetically distant organisms, is a significant factor in microbial evolution. HGT plays a major role in the emergence of novel human diseases, as well as promoting the spread of antibiotic resistance in bacteria species. HGT puts in question the validity of a single common (tree like) evolutionary history suggesting an alternative evolutionary network. Trivial problems on trees turn to be computationally hard on a network setting. Current methods for HGT analysis are mostly based on intuition or weak signals. As W. Ford Doolittle, possibly the greatest authority on HGT, wrote in his inaugural article for the National Academy of Sciences [1] -”In the near future, even more sophisticated methods should be available, because mathematical research into phylogenetic network reconstruction is presently very active”. During the past recent years, our lab has tackled HGT from various angles of view striving to introduce rigor into the field. Our work is naturally cited  in this excerpt of Doolittle due to its innovative role [2].

Another direction in this context of HGT relies on a theoretical, surprising result we found [9], allowing to use a very faint signal in order to build reliable quartets. The idea, based on probabilistic bounds, uses voting techniques, as a quartets oracle. In a series of following works, we refined this idea to consider the majority of each quartet –  a notion termed the quartet plurality distribution (QPD)[10]. The QPD appeared to be a very strong tool[11], useful in many settings and for purposes such as inferring level and barriers of HGT in a population[14], inferring toxicity of transferred genes[13], and HGT as a source for pseudogenes in bacteria[12].

QPD.png
HGT 1.png
 

  1. W. Ford Doolittle and Eric Bapteste. Inaugural Article: Pattern pluralism and the Tree of Life hypothesis. Proceedings of the National Academy of Sciences, 104(7):2043–2049, 2007.

  2. G. Jin L. Nakhleh, S. Snir and T. Tuller, Maximum Likelihood of Phylogenetic Networks , Bioinformatics, Vol 22, Number 21, November 2006, pages 2604 – 2611. All authors contributed equally.

  3. G. Jin L. Nakhleh, S. Snir and T. Tuller, Inferring Phylogenetic Networks by the Maximum Parsimony Criterion: A Case Study, Molecular Biology and Evolution (MBE) 2007 24(1):324-337; All authors contributed equally. 

  4. G. Jin L. Nakhleh, S. Snir and T. Tuller, Efficient Parsimony-based Methods for Phylogenetic Network Reconstruction , Bioinformatics 2007 23(2):e123-e128; All authors contributed equally. 

  5. S. Snir, “Lateral Transfers: a survey and new developments”. Israel Journal of Ecololgy and Evolution (IJEE). 52(3-4):443-459, 2007

  6. S. Snir and T. Tuller, The NET-HMM Approach: Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models. Journal of Bioinformatics and Computational Biology (JBCB), 2009 Aug;7(4):625-44. Authors contributed equally. 

  7. G. Jin, L. Nakhleh , S. Snir, and T. Tuller. Parsimony Score of Phylogenetic Networks: Hardness Results and a Linear-Time Heuristic. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 6(3): 495-505 (2009). All authors contributed equally

  8. S. Snir and E.N. Trifonov. A Novel Technique for Detecting Putative Horizontal Gene Transfer in the Sequence Space. Journal of Computational Biology (JCB), Volume 17(11): 1417-1430, 2010.

  9. S. Roch and S. Snir, Recovering the tree-like trend of evolution despite extensive lateral genetic transfer: A probabilistic analysis. Journal of Computational Biology (JCB). 20(2): 93-112, 2013

  10. E. Avni, S. Snir. Reconstruction of Real and Simulated Phylogenies Based on Quartet Plurality Inference. BMC Genomics. 2018. 19:4921

  11. E. Avni, S. Snir. A new quartet-based statistical method for comparing sets of gene trees is developed using a generalized Hoeffding inequality. Journal of Computational Biology.

  12. E. Avni, D. Montoya, D. Lopez, R. Modlin, M. Pellegrini*, S. Snir*. A Phylogenomic Study Quantifies Competing Mechanisms for Pseudogenization in Prokaryotes – the Mycobacterium Leprae Case. PLOS ONE. *Joint last author.

  13. E. Avni, S. Snir. Toxic genes present a unique phylogenetic signature. Molecular Phylogenetics and Evolution. Volume 116, November 2017, Pages 141-148.

  14. E. Avni, S. Snir. A New Phylogenomic Approach For Quantifying Horizontal Gene Transfer Trends in Prokaryotes. Submitted.