Whole Genome Alignment

1. Whole Genome Alignment MUMmer and Alignment October 2nd, 2007 Adam M Phillippy amp@cs.umd.edu

2. CCGGTAGGCTATTAAACGGGGTGAGGAGCGTTGGCATAGCA CCGGTAGGCTATTAAACGGGGTGAGGAGCGTTGGCATAGCA Goal of WGA • For two genomes, A and B, find a mapping from each position in A to its corresponding position in B 41 bp genome

3. CCGGTAGGATATTAAACGGGGTGAGGAGCGTTGGCATAGCA CCGCTAGGCTATTAAAACCCCGGAGGAG....GGCTGAGCA Not so fast... • Genome A may have insertions, deletions, translocations, inversions, duplications or SNPs with respect to B (sometimes all of the above)

4. Visualization • How can we visualize alignments? • With an identity plot • XY plot • Let x = position in genome A • Let y = %similarity of Ax to corresponding position in B • Plot the identity function • This can reveal islands of conservation, e.g. exons

5. Identity plot example

6. WGA visualization • How can we visualize whole genome alignments? • With an alignment dot plot • N x M matrix • Let i = position in genome A • Let j = position in genome B • Fill cell (i,j) if Ai shows similarity to Bj • A perfect alignment between A and B would completely fill the positive diagonal

7. B A B A Translocation Inversion Insertion http://mummer.sourceforge.net/manual/AlignmentTypes.pdf

9. Global vs. Local • Global pairwise alignment ...AAGCTTGGCTTAGCTGCTAGGGTAGGCTTGGG... ...AAGCTGGGCTTAGTTGCTAG..TAGGCTTTGG... ^ ^ ^^ ^ • Whole genome alignment • Often impossible to represent as a global alignment • We will assume a set of local alignments • This works great for draft sequence

10. global ok global no way Global vs. Local

11. Alignment tools • Whole genome alignment • MUMmer* (nucmer) • Developed, supported and available at TIGR • LAGAN*, AVID • VISTA identity plots • Multiple genome alignment • MGA, MLAGAN*, DIALIGN, MAVID • Multiple alignment • Muscle*, ClustalW* • Local sequence alignment • BLAST*, FASTA, Vmatch *open source

12. MUMmer • Maximal Unique Matcher (MUM) • match • exact match of a minimum length • maximal • cannot be extended in either direction without a mismatch • unique • occurs only once in both sequences (MUM) • occurs only once in a single sequence (MAM) • occurs one or more times in either sequence (MEM)

13. Fee Fi Fo Fum,is it a MAM, MEM or MUM? MUM : maximal unique match MAM : maximal almost-unique match MEM : maximal exact match R Q

14. Seed and extend • How can we make MUMs BIGGER? • Find MUMs using a suffix tree • Cluster MUMs using size, gap and distance parameters • Extend clusters using modified Smith-Waterman algorithm

15. Seed and extend FIND all MUMs CLUSTER consistent MUMs EXTEND alignments R Q

16. atgtgtgtc$ $ c$ t gt 10 9 1 gt c$ c$ gt 8 7 c$ gtc$ c$ gt 5 3 6 c$ gtc$ 4 2 Suffix Tree for atgtgtgtc$ Drawing credit: Art Delcher

17. R m1 m2 m3 A B Q C Clustering cluster length = ∑mi gap distance = C indel factor = |B – A| / B or |B – A|

18. break point = B B A break length = A Extending R score ~70% Q

19. B ^ T T G C A G ^ 1 2 3* 5 6 4 T 1 0 1 2 3 4 5 4 G 2 1 1 1 2 3 A 2 C 3* 2 2 2 1 3 2 T 2 3* 2 3* 3 4 2 G 5 4 3 3 3* 2 Banded alignment 0

20. mummer exact matching nucmer DNA multi-FastA input whole genome alignment promer DNA multi-FastA input whole genome alignment run-mummer1 FastA input global alignment run-mummer3 FastA input w/ draft whole genome alignment exact-tandems FastA input exact tandem repeats NUCmer / PROmer utilities mapview alignment plotter draft sequence mapping mummerplot alignment visualization show-coords alignment summary delta-filter alignment filter show-aligns pairwise alignments System utilities gnuplot xfig MUMmer suite

21. mummer • Primary uses • exact matching (seeding) • dot plotting • Pros • very efficient O(n) time and space • ~17 bytes per bp of reference sequence • E. coli K12 vs. E. coli O157:H7 (~5Mbp each) • 17 seconds using 77 MB RAM • multi-FastA input • Cons • exact matches only

22. nucmer • Primary uses • whole genome alignment and analysis • draft sequence alignment • Pros • multi-FastA inputs • well suited for genome and contig mapping • convenient helper utilities • show-coords, delta-filter, mummerplot • Cons • low sensitivity (w\ default parameters) with respect to BLAST

23. WGA example • Yersina pestis CO92 vs. Yersina pestis KIM • High nucleotide similarity, 99.86% • Two strains of the same species • Extensive genome shuffling • Global alignment will not work • Highly repetitive • Will confuse local alignment (e.g. BLAST)

24. nucmer –maxmatch CO92.fasta KIM.fasta -maxmatch Find maximal exact matches (MEMs) delta-filter –m out.delta > out.filter.m -m Many-to-many mapping -1 One-to-one mapping show-coords -r out.delta.m > out.coords -r Sort alignments by reference position mummerplot --large --fat out.delta.m --large Large plot --fat Nice layout for multi-fasta files --x11 Default, draw using x11 (--postscript, --png) *requires gnuplot COMMANDwhole genome alignment

26. show-coords output • [S1] start of the alignment region in the reference sequence • [E1] end of the alignment region in the reference sequence • [S2] start of the alignment region in the query sequence • [E2] end of the alignment region in the query sequence • [LEN 1] length of the alignment region in the reference sequence • [LEN 2] length of the alignment region in the query sequence • [% IDY] percent identity of the alignment • [% SIM] percent similarity of the alignment • [% STP] percent of stop codons in the alignment • [LEN R] length of the reference sequence • [LEN Q] length of the query sequence • [COV R] percent alignment coverage in the reference sequence • [COV Q] percent alignment coverage in the query sequence • [FRM] reading frame for the reference and query sequence alignments respectively • [TAGS] the reference and query FastA IDs respectively. • All output coordinates and lengths are relative to the forward strand

27. Comparative assembly • Assembly • Orient and place sequencing reads • Using overlaps and mate-pair information • Scaffolding • Order and orient draft contigs • Using mate-pair information and experimental validation • Comparative assembly and scaffolding • Orient and place reads and contigs • Using a reference genome and alignment mapping • e.g. AMOScmp (nucmer)

28. Comparative assembly mate-pairs physical map reference genome homology map

29. Comparative assemblycaveats Finished Un-finished A B A B A B

30. nucmer –maxmatch REF.fasta QRY.fasta -maxmatch Find maximal exact matches (MEMs) REF Reference sequence (genome) QRY Query sequence to be mapped (reads, contigs) delta-filter –q out.delta > out.delta.q -q Best one-to-one mapping for each query show-coords –rcl out.delta.q > out.coords -r Sort alignments by reference -c Display alignment coverage percentage -l Display sequence length COMMANDnucmer read/contig mapping

31. Arachne vs. CA Drosophila virilis Multiple CA contigs (Y) mapping to a single Arachne contig (X) 9kb insertion 5kb translocation

32. Gene reassembly* • nucmer -maxmatch genes.fasta reads.fasta • delta-filter -q out.delta.q • show-coords -THqcl out.delta.q > out.coords • Define matching criteria • %identity, %coverage, max gap size • Assemble matching reads • AMOS, minimus, hawkeye

33. References • Documentation • http://mummer.sourceforge.net • publication listing • http://mummer.sourceforge.net/manual • thorough documentation • http://mummer.sourceforge.net/examples • walkthroughs • Email • mummer-help (at) lists.sourceforge.net • mummer-users (at) lists.sourceforge.net

35. Acknowledgements Art Delcher Steven Salzberg Mihai Pop Mike Schatz Stefan Kurtz