1. Genomic Rearrangements CS 374 – Algorithms in Biology Fall 2006 Nandhini N S

2. Motivation One of the keys to evolution. Detecting dynamics between members of the same family. An interesting combinatorial problem!! Everybody loves Central Limit theorem (or a variant).

3. Terminology Possible rearrangements Reversals Translocations Fission Fusion. Most Parsimonious scenario. Genomic Distance. Synteny Blocks

4. Describing the problem Basically a reversal distance problem. Given permutations π & σ (permutations implying genes), find a series of reversals such that π.ρ 1.ρ 2.ρ 3 …..ρ n = σ and n (genomic distance) is minimum. “The most parsimonious scenario”.

7. Putting it all together Local Alignments. Synteny Blocks. Breakpoint Graph. Rearrangement Scenario.

8. From Local Alignments to Synteny Blocks Non-Trivial Issue!!  False orthologs.  Micro-rearrangements.  Sequence similarities in non-coding regions.

9. Human and Mouse Synteny Blocks

10. Grimm Synteny algorithm Form an anchor Graph whose vertex set is the set of anchors. Obtaining the Anchor Graph. (Use BLAST/ BLAST like techniques).

11. Grimm Synteny algorithm, contd. Connect vertices in the anchor graph by an edge if the distance between them is smaller than the gap size G.

12. Determine the connected components of the anchor graph. Each small component is called a cluster. Grimm Synteny algorithm, contd.

13. Delete ‘small’ clusters (shorter than the minimum cluster size C in length). Grimm Synteny algorithm, contd.

14. Determine cluster order and signs for each genome. Output the strips in the resulting cluster order as synteny blocks. Grimm Synteny algorithm, contd.

15. From Synteny Blocks to the breakpoint graph

16. From Breakpoint Graph to Rearrangement Scenarios b(π)–c(π)+h(π) <= d(π) <= b(π)–c(π)+h(π)+1 “Efficient sorting of genomic permutations by translocation, inversion and block interchange ”

17. Reconstructing contiguous regions of an ancestral genome.

19. Reconstructing regions of an ancestral genome Segmenting genomes based on pair wise alignments. Nets -> Orthology Blocks -> Conserved Segments.

20. Nets to Orthology Blocks to Conserved Segments First determine alignments Then the orthology blocks And then come the conserved segments.

21. Methodology Predicting contiguous ancestral regions (CARs) from modern alignments. Identification of small inversions Properties of breakpoints. Inferring CARs.

22. Consider..

24. Sundry Details - Small Inversions.  For ambiguous cases, go with human data (the best documented till now).

25. A Sanity Check Define a genome; and follow it through its evolution!! Imagine a genome π with n elements, that evolves through a series of rearrangements. Works! 90.8% of adjacencies predicted in the Boreoeutherian ancestor are correct!

26. More realism!!!! Employed a realistic evolutionary tree with branch lengths based on substitution frequencies. Rearrangements –  90% Inversions.  5% Translocations.  3.75% Fusions.  1.25% Fissions. Modeled length of block with γ distribution, with shape and scale parameters α =.7 and θ = 500.γ distribution

27. Comparison with other reconstructions

28. Details More data needed. Looking for better sequenced outgroups. Require improvements in handling large duplications and deletions. Modeling gene conversion, expansion, contraction of short tandem repeats caused by strand slippage. Eventually; nucleotide resolution.

29. Inferring CARs

30. Thank you