1. phylogenetic inferences
Mathematical modelling of evolution of tetranucleotide usage patterns of whole bacterial genomes to improve
phylogenetic inferences
Centre of Bioinformatics and Computational Biology
University of Pretoria
Xiaoyu Yu

2. Background Problem
Phylogenomics: Reconstruction of evolutionary relationships by comparing sequences of whole genomes or portions of genomes.
Prediction of gene function
Establishment and clarification of evolutionary relationships
Gene family evolution
Prediction and retracing lateral gene transfer

3. Background Problem
Multiple algorithms available but falls short individually.
Inconsistency of results between algorithms. No consensus between results

4. Pairwise distance plot

5. Aim and Objectives
Reconcile MSA based and OUP based distances to solve inconsistency

6. Aim and Objectives
Reconcile MSA based and OUP based distances to solve inconsistency
Creating new phylogenomic inferencing method to cover the shortfalls of individual algorithms

7. Aim and Objectives
Reconcile MSA based and OUP based distances to solve inconsistency
Creating new phylogenomic inferencing method to cover the shortfalls of individual algorithms
Determine the biological model for the alignment and annotation method (OUP)

8. Aim and Objectives
Reconcile MSA based and OUP based distances to solve inconsistency
Creating new phylogenomic inferencing method to cover the shortfalls of individual algorithms
Determine the biological model for the alignment and annotation method (OUP)
Develop online web based tool

10. Clustering

11. Cladogram

12. Cladogram NC_009848 1 2 NC_006270 NC_014103 NC_014829 NC_0009641 2
NC_006270
NC_014103
NC_014829
NC_000964
NC_015634
NC_009674
NC_006582
NC_003909
NC_002570
NC_013791

13. Inferencing

14. Inferencing
NC_009848
NC_006270
NC_014103
NC_014829
NC_000964
NC_015634
NC_009674
NC_006582
NC_003909
NC_002570
8.6678
NC_013791

15. Case Studies Bacillus Corynebacteria Enterobacteria Lactobacilli
Mycobacteria
Pseudomonas
Prochlorococcus
Thermatoga

16. Current Limitations
Not all groups of organisms cluster well with current model

17. Current Limitations
Not all groups of organisms cluster well with current model
Parameter still being tested to reconcile the best tree

18. Current Limitations
Not all groups of organisms cluster well with current model
Parameter still being tested to reconcile the best tree
Website under construction

19. What is the driving force of OUP evolution?

20. What is the driving force of OUP evolution?
OUP evolution is driven by adaptation to codon usage
OUP pattern is adjusted to the optimal codon usage with a permanent rate.
Concentrations of tRNAs fluctuate in closely related organisms

21. Conclusion
Driving force of OUP evolution

22. Conclusion Driving force of OUP evolution
Reconciliation of WGS and OUP based distances lead to new phylogenomic inference method

23. Conclusion Driving force of OUP evolution
Reconciliation of WGS and OUP based distances lead to new phylogenomic inference method
A web-based tool is being created for researchers to do phylogenomic studies

24. Acknowledgement University of Pretoria
Centre of Bioinformatics and Computational Biology Staff Members
National Research Foundation grant # 93664