1. Some new sequencing technologies

2. Molecular Inversion Probes

3. Illumina Genotype Arrays

4. Single Molecule Array for Genotyping—Solexa

5. Nanopore Sequencing http://www.mcb.harvard.edu/branton/index.htm

6. Pyrosequencing on a chip Mostafa Ronaghi, Stanford Genome Technologies Center 454 Life Sciences

7. Polony Sequencing

8. Technologies available today Illumina  550,000 SNP array: $300-500 in bulk 454  200 bp reads, 100 Mbp total sequence in 1 run, $8K  500bp reads in much higher throughput coming soon Solexa  1Gbp of sequence coming in paired 35 bp reads  1 day, approx $10K / run

9. Short read sequencing protocol Random, high-coverage clone library (Cov G = 7 – 10x) Low-coverage of clone by reads (Cov R = 1 – 2x)

10. Short read sequencing protocol

11. Ordering clones into clone contigs

12. Contig assembly

14. Assembly quality SequenceCoverage Contig N50 (Kb) Base quality (Q) Misassemblie s (#/Mb) Small indels (#/Mb) D. Melanogaster (118 Mb) 94.2%160.238.42.51.6 Human chr21 (34 Mb) 97.5%79.035.61.92.3 Human chr11 (131 Mb) 96.3%57.434.42.81.9 Human chr1 (223 Mb) 96.2%63.034.43.02.0 Read length = 200 bp, Error rate = 1%, Net coverage = 20.0x

15. Multiple Sequence Alignment

16. Evolution at the DNA level …ACGGTGCAGTTACCA… …AC----CAGTCCACCA… Mutation SEQUENCE EDITS REARRANGEMENTS Deletion Inversion Translocation Duplication

17. Evolutionary Rates OK X X Still OK? next generation

19. Genome Evolution – Macro Events Inversions Deletions Duplications

20. Synteny maps Comparison of human and mouse

21. Synteny maps

22. Orthology, Paralogy, Inparalogs, Outparalogs

23. Synteny maps

25. Building synteny maps Recommended local aligners BLASTZ  Most accurate, especially for genes  Chains local alignments WU-BLAST  Good tradeoff of efficiency/sensitivity  Best command-line options BLAT  Fast, less sensitive  Good for comparing very similar sequences finding rough homology map

26. Index-based local alignment Dictionary: All words of length k (~10) Alignment initiated between words of alignment score  T (typically T = k) Alignment: Ungapped extensions until score below statistical threshold Output: All local alignments with score > statistical threshold …… query DB query scan Question: Using an idea from overlap detection, better way to find all local alignments between two genomes?

27. Local Alignments

28. After chaining

29. Chaining local alignments 1.Find local alignments 2.Chain -O(NlogN) L.I.S. 3.Restricted DP

30. Progressive Alignment When evolutionary tree is known:  Align closest first, in the order of the tree  In each step, align two sequences x, y, or profiles p x, p y, to generate a new alignment with associated profile p result Weighted version:  Tree edges have weights, proportional to the divergence in that edge  New profile is a weighted average of two old profiles x w y z Example Profile: (A, C, G, T, -) p x = (0.8, 0.2, 0, 0, 0) p y = (0.6, 0, 0, 0, 0.4) s(p x, p y ) = 0.8*0.6*s(A, A) + 0.2*0.6*s(C, A) + 0.8*0.4*s(A, -) + 0.2*0.4*s(C, -) Result: p xy = (0.7, 0.1, 0, 0, 0.2) s(p x, -) = 0.8*1.0*s(A, -) + 0.2*1.0*s(C, -) Result: p x- = (0.4, 0.1, 0, 0, 0.5)

31. Threaded Blockset Aligner Human–Cow HMR – CD Restricted Area Profile Alignment

32. Reconstructing the Ancestral Mammalian Genome Human: C Baboon: C Cat: C Dog: G C C or G G