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Comparative genomics and genome alignment �

Conservation detected by genome alignment �

Conservation of ZFPM1 among human, mouse, rat, and mouse. The large introns have several highly conserved regions. Those with conserved GATA-1 binding sites and high regulatory potential (predicted CRMs) are indicated.

http://genome.cshlp.org/content/15/1/184.full

Mulan phylogenetic tree (A) and sequence conservation profile (B) for the GATA3 gene locus from human, rat, mouse, chicken, frog, and three fish genomes.

Ovcharenko I et al. Genome Res. 2005;15:184-194

©2005 by Cold Spring Harbor Laboratory Press

What is comparative genomics?�

•  Methods for characterizing DNA sequences using multiple genomes�

•  Examples of problems that benefit from a comparative approach: �•  Gene prediction �•  Gene regulation �•  Understanding evolutionary relationships

between species according to their genome architecture�

Comparing Genomes: Global Alignment of Long DNA Sequences�

Motivation �

•  Genomic sequences are very long �

•  Aligning genomic regions is useful for revealing conserved elements�•  Want to compare regions > 1,000,000-long �

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Alignment Uses�

•  Whole genome alignment�•  Synteny analysis �•  Polymorphism detection �•  Sequence mapping �

•  Multiple genome alignment�•  Identify conserved sequence, e.g. functional elements

(annotation)�•  Polymorphism detection �

Alignment methods�

•  Local alignment methods (BLAST-like): �•  Do not provide the global picture�•  Weakly conserved local regions can be missed�

•  Global alignment methods (e.g. Needleman-Wunsch):�•  Assume two regions are globally alignable�•  Slow, memory intensive algorithms that cannot

be run on long genomic segments�

Alignment of long genomic regions�

•  Input: two long genomic sequences that are homologous �

Main Idea�

Genomic regions of interest contain islands of similarity, such as genes�

�1.  Find local alignments/anchors�2.  Chain an optimal subset of them�3.  Refine/complete the alignment �

�Systems that use this idea to various degrees: �MUMmer, GLASS, DIALIGN, AVID, LAGAN, TBA �

Saving cells in DP�

1.  Find local alignments�

2.  Chain �

3.  Restricted DP�

Chaining of Local Alignments�

Each local alignment has a weight ��FIND the chain with highest total weight �

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A Graph Structure�

•  Build Directed Acyclic Graph (DAG): �•  Nodes: local alignments (xa,ya),(xb,yb) & score�•  Directed edges: local alignments that can be chained�

•  edge ( (xa, ya), (xb, yb) ), ( (xc, yc), xd, yd) ) if: �"xa < xb < xc < xd�"ya < yb < yc < yd�

Each local alignment �is a node vi with �alignment score si�

A Dynamic Programming Algorithm�

Initialization: �"Find each node va s.t. there is no edge (u,va)�"Set score of V(a) to be sa�

Iteration: "�"For each vi, optimal path ending in vi has total score: �

�

V(i) = maxedges j incident on i ( si + V(j) ) �Termination: �

"Optimal global chain: �" j = argmax ( V(j) ); trace chain from vj�

�Complexity: quadratic�

Multiple Genome Alignment �

•  Given a pairwise alignment method it is possible to convert it into a progressive MSA method.�

•  Examples: �Lagan --> Mlagan, Avid --> Mavid�•  In Mavid progressive alignment is performed by inferring

ancestor sequences and aligning them.�•  Mlagan performs an optional step of iterative refinement �•  Both methods use anchors from the pairwise comparisons

to avoid making the sort of errors that progressive aligners can make.�

MLAGAN vs. ClustalW� Sidetrack: visualization �

•  How can we visualize 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�

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B

A

B

A

Translocation � Inversion � Insertion �

http://mummer.sourceforge.net/manual/AlignmentTypes.pdf

Glocal Alignment Problem�Find least cost transformation of one sequence into another using new operations �

•  Sequence edits�

•  Inversions �

•  Translocations�

•  Duplications�

�

Implemented in Shuffle-Lagan �

Whole genome alignment �

figure from the mummer manual