1. Finding Mathematics in Genes and Diseases Ming-Ying Leung Department of Mathematical Sciences University of Texas at El Paso (UTEP)

3. Outline: Cytomegalovirus (CMV) Particle DNA and RNA Genome, genes, and diseases Palindromes and replication origins in viral genomes Mathematics for prediction of replication origins

4. DNA and RNA T G C A G A C T G U A C DNA is deoxyribonucleic acid, made up of 4 nucleotide bases Adenine, Cytosine, Guanine, and Thymine. RNA is ribonucleic acid, made up of 4 nucleotide bases Adenine, Cytosine, Guanine, and Uracil. For uniformity of notation, all DNA and RNA data sequences deposited in GenBank are represented as sequences of A, C, G, and T. The bases A and T form a complementary pair, so are C and G.

5. Genes and Genome

6. Genes and Diseases

7. Virus and Eye Diseases CMV Particle CMV Retinitis inflammation of the retina triggered by CMV particles may lead to blindness Genome size ~ 230 kbp

8. Replication Origins and Palindromes High concentration of palindromes exists around replication origins of other herpesviruses Locating clusters of palindromes (above a minimal length) on CMV genome sequence might reveal likely locations of its replication origins.

9. Palindromes in Letter Sequences “A nut for a jar of tuna” “Step on no pets” ANUTFORAAROFTUNAJ remove spaces and capitalize STEPONNOPETS Even Palindrome : Odd Palindrome:

10. DNA Palindromes

11. Association of Palindrome Clusters with Replication Origins

12. Computational Prediction of Replication Origins Palindrome distribution in a random sequence model Criterion for identifying statistically significant palindrome clusters Evaluate prediction accuracy Try to improve…

13. A mathematical model can be used to generate a DNA sequence A DNA molecule is made up of 4 types of bases It can be represented by a letter sequence with alphabet size = 4 Adenosine Cytosine Guanine Thymine Wheel of Bases (WOB) Random Sequence Model G A C T

14. Adenosine Cytosine Guanine Thymine Wheel of Bases (WOB) Random Sequence Model Each type of the bases has its chance (or probability) of being used, depending on the base composition of the DNA molecule. G A C T

15. Adenosine Cytosine Guanine Thymine Wheel of Bases (WOB) Random Sequence Model G A C T Each type of the bases has its chance (or probability) of being used, depending on the base composition of the DNA molecule.

16. Poisson Process Approximation of Palindrome Distribution

17. Use of the Scan Statistic to Identify Clusters of Palindromes

18. Measures of Prediction Accuracy Attempts to improve prediction accuracy by: Adopting the best possible approximation to the scan statistic distribution Taking the lengths of palindromes into consideration when counting palindromes Using a better random sequence model

19. Markov Chain Sequence Models More realistic random sequence model for DNA and RNA It allows neighbor dependence of bases (i.e., the present base will affect the selection of bases for the next base) A Markov chain of nucleotide bases can be generated using four WOBs in a “Sequence Generator (SG)”

20. Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T

21. Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T

22. T Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T

23. T Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T

24. C T Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T

25. C T Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T

26. TT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C

27. TTT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C

28. TTTT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C

29. A TTTT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C

30. A TTTT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C A

31. AA CC G TT G TTTT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C AA

32. TTTT Sequence Generator (SG) Wheels of Bases (WOB) Bases G A C T C AA C AA C G TT G

33. Results Obtained for Markov Sequence Models Probabilities of occurrences of single palindromes Probabilities of occurrences of overlapping palindromes Mean and variance of palindrome counts

34. Related Work in Progress Finding the palindrome distribution on Markov random sequences Investigating other sequence patterns such as close repeats and inversions in relation to replication origins

35. Other Mathematical Topics in Genes and Diseases Optimization Techniques – prediction of molecular structures Differential Equations – molecular dynamics Matrix Theory – analyzing gene expression data Fourier Analysis – proteomics data