1. The Cobweb of life revealed by Genome-Scale estimates of Horizontal Gene Transfer Fan Ge, Li-San Wang, Junhyong Kim Mourya Vardhan

2. Outline Controversy : The extent of HGT affecting the core genealogical history Examination of this controversy by assessing the extent among core orthologous genes A novel statistical method : To asses the extent of HGT based on comparisons of tree topology

3. Introduction Horizontal gene transfer (HGT) refers to the transfer of genes between organisms in a manner other than traditional reproduction. Whole genome analyses of different prokaryotes have been thought to indicate rampant HGTs There is an on going debate over the estimation of HGT frequency and its impact on phylogeny Inference of HGT from tree comparisons should be done under a proper statistical framework

4. Methodology to assess the extent New method to explicitly test for phylogenetic incongruence due to horizontal transfer versus statistical tree errors Used Clusters of Orthologous Groups (COG) from NCBI databases Extracted most reliable COGs Built gene tree for every COG and integrated to construct W-G tree Comparisons of each gene tree with W-G tree to infer significant HGT Augmented this method to pairwise comparisons of gene trees to detect conflicts

6. High-Quality Gene Groups and the W-G Tree COG database is built by redoing sequence comparisons over 43 genomes This resulted in retention of 297 high quality COG entries out of 3852 To approximate the W-G tree, they used median tree estimator The estimate used boot strap values from bootstrap sampling

8. Detection of HGT events By comparison of estimated trees against other gene trees or against trees that represent the history of genomes, we infer HGTs Discrepancy in the trees maybe caused due to HGT or other errors Distance metrics are used to test discrepancies The paper explicitly asks if the discrepancies are caused by HGT events, as an additional precaution.

9. Comparison Metrics Maximum agreement subtree (MAST) - If two trees differ by branches, they share common subtree, the bound on size of the shared subtree can be calculated using MAST Symmetric Difference (SD) - Difference in the trees can be found by this metric

10. Interpretation of HGT events… Case 1: If both MAST and SD are low, trees are most likely not different Case 2: If both the metrics are large, can be either HGT events or errors Case 3: But if they have large SD and low MAST values, it is most likely an HGT event. Case 4: Large MAST and low SD cannot occur due to algorithmic reasons

11. SD and MAST scores for Gene Tree 1 and the W-G tree are 2 and 2, while the scores for Gene Tree 2 and the W-G tree are 8 and 2

12. The Hypothesis Test Hypothesis test Ɣ – difference of the two metrics Computed by generating null distribution by bootstrapping gene trees HGT was inferred when the observed Ɣ was significant with the p-value below the 5% level Simulation studies applied to each COG showed it detecting HGT events as follows, in a COG tree using the 5% significance HGT EventsRates 153.8 270 377.3

13. d s is the SD metric d m is the MAST metric m,n are the no. of branch splits X is the no. of taxa Used PAUP software to calculate

14. HGT Estimation via Comparisons between Each Gene Tree and the W-G Tree Hypothesis Test was applied to each COG Observations showed that the test does not significantly vary with the p- value At 5% level, 33/297 (11.1%) COGs showed putative HGTs These COGs are termed hCOGs

15. The Relationship between Detecting COG entries with HGT and the p-Values

16. HGT Estimation via Comparisons among Gene Trees Problem with comparing the Gene tree and W-G tree is that the results are sensitive to the W-G tree COG entries do not all share the same taxa If its a hCOG, it should test differently for all the comparisons 14,004 pairs of gene trees that contained greater than or equal to six shared taxa were compared At 5% level, 1,764/14,004 (12.6%) pairs were significant

18. Identification of transferred branches in gene trees. For each COG that tested positive for HGT events, transferred branches were found by exhaustive enumeration of possible subtree matches Searched for all combinations of branch prunings to find the ‘‘troublesome’’ branches If there’s only one way to prune to make the trees congruent, it is an HGT event

19. ColorHGT Rates Red>4% Yellow3%–4% Pink2%–3% Blue1%–2% Green1%

20. References 1. Goddard W, Kubicka E, Kubicki G, McMorris FR (1994) The agreement metric for labeled binary trees. Math Biosci 123: 215–226. 2. Robinson DF, Foulds LR (1981) Comparison of phylogenetic trees. Math Biosci 53: 131–147 3. Conover WJ (1999) Practical nonparametric statistics, 3rd ed. New York: Wiley. 584 p. 4. Eisen JA (2000) Horizontal gene transfer among microbial genomes: New insights from complete genome analysis. Curr Opin Genet Dev 10: 606–611

21. Thank You!