Optical Mapping as a Method of Whole Genome Analysis

1
Optical Mapping as a Method of Whole Genome
Analysis

• May 4, 2009
• Course 22M151
•   Presented by
• Austin J. Ramme

2
Presentation Outline

• Introduction to Optical Mapping
• Definitions for Understanding
• Modern Optical Mapping Process
• Data Analysis
• Overview
• Steps to Restriction Map Generation
• Applications of Optical Mapping
• Conclusions

3
Optical Mapping (OM) Introduction

• The number of identified polygenetic diseases is
  ever increasing
• Methods to analyze the entire genome will enhance
  current diagnostic and treatment methods for a
  variety of diseases
• Patient-specific genomic analysis has become the
  goal in genetics-based medical research
• Optical mapping(OM) is an automated method of
  ordered restriction map generation with a goal of
  whole genome analysis that avoids the limitations
  inherent to traditional techniques

4
Definitions

• Restriction Enzymes
• Proteins that cleave DNA molecules based on a
  specific base pair sequence (e.g. ATCG)

http//www.belchfire.net/screenshots/Pacman.jpg ht
tp//www.dnavitaminpro.com/wp-content/uploads/2008
/07/dna-horizontal.jpg http//static.rbytes.net/fu
ll_screenshots/z/e/zenwaw-pacman.jpg
5
Definitions

• Restriction Map
• Representation of the cut sites on a given DNA
  molecule to provide spatial information of
  genetic loci
• Optical Mapping
• Process to generate ordered restriction maps from
  single DNA molecules
• Optical Map
• Ordered restriction map of a portion of genomic
  DNA

DNA strand
2
6
Slide Removed for Online Posting
7
Computer Representation of Imaging Data

• Imaged datasets are converted into barcode
  patterns corresponding to the cleaved fragments
• Lengths are determined using an internal ?
  standard and fluorescence intensity values

5
8
Raw Data

• Description
• Image collection containing genomic restriction
  fragments of known length deposited in an ordered
  manner
• Fragments represent randomly sheared genomic DNA
• Each OM imaging study redundantly represents the
  entire genomic region of interest
• Challenges with analyzing individual DNA
  molecules
• Extra cut sites - physical breakage
• Missing cut sites - partial digestion
• Loss of small fragments
• Sizing error
• Chimeric maps- physically overlapped molecules
• Combining multiple OMs gives more accurate
  restriction maps
• Graphing has been used to accomplish this

9
Steps to Restriction Map Generation

1. Calculation of OM Overlaps
2. Overlap Graph Construction
3. Graph Correction Procedure
4. Identification of Islands
5. Contig Construction
6. Construction of Draft Consensus Map
7. Consensus Map Refinement

10
Calculation of Overlaps

• A multitude of OMs are collected per optical
  mapping experiment
• Scoring system used to find overlaps between
  individual optical maps

6

• Scoring system components
• Matching sites are rewarded
• Discordant sites are penalized
• Length similarity is rewarded

11
Overlap Graph Construction

• Overlap Graph G(V,E)
• Literature describes it as a graph, but its
  technically a digraph
• The set of nodes (V) represent individual optical
  maps
• The set of edges (E) represent high quality
  overlaps between pairs of maps
•  Weighting and orienting the edges of the graph
• Edge weights correspond to genomic distances of
  the overlapping map regions
• Orientation based on the sign of distance
  measurements from neighboring map centerpoints
• Goal Heaviest weight path represents the most
  comprehensive genomic restriction map

Optical Mapping Data
OM1
OM2
Graph Construction
OM3
OM4

12
Graph Correction Procedure (1)

• False edges correspond to falsely identified
  overlaps
• Spurious edges
• Connect two nodes forming a cycle which is not
  possible in linear DNA
• Orientation consistent false overlaps (cut edge)
• Edges that connect two unrelated portions of the
  genome

4
4
13
Graph Correction Procedure (2)

• False Nodes ? Chimeric maps
• Consist of two groups of nodes only connected via
  a single node (cut vertex)
• Connect two unrelated portions of the genome

4
14
Identification of Islands

• Islands correspond to genomic regions spanned by
  multiple overlapping optical maps

4
Island 1
Island 2
Island 3
Contig Construction

• For each island, contigs are defined as paths
  from sources to sinks within the overlap graph
  for the island
• The most complete representation of the genomic
  region is represented by the heaviest edge path
  from source to sink

15
Construction of Draft Consensus Map

• Using the determined paths, the nodes and edges
  are used to merge the individual optical maps
  corresponding to each chosen island component
• Each of the individual composite optical maps are
  stored for further analysis

4
16
Consensus Map Refinement (1)

• The draft map may contain errors
• Missing cut sites
• False cut sites
• Hidden Markov Model (HMM) for map refinement
• Compares draft map to many other optical maps
• Statistics used to identify matching, deleted,
  and inserted cut sites

7
Hidden Markov Model
17
Consensus Map Refinement (2)
Sample HMM Path
7

• The corrected consensus map for each island
  pieced back together to form a complete genomic
  restriction map
• Typically takes 13-15 iterations for statistical
  correction of the draft map

18
Applications of Optical Mapping

• Identification of genetic insertions, deletions,
  inversions, and repeats
• Establish genotype-phenotype correlations for
  advancements in diagnosis and treatment of
  genetic disorders
• Reduction of the time needed and the cost to
  sequence entire strands of DNA
• In the future Patient-specific whole genome
  analysis

19
Conclusions

• Optical mapping is a method of restriction map
  generation for whole genome analysis
• Applications range from clinical
  phenotype-genotype correlations to identification
  of polymorphisms in a variety of diseases
• In the future, optical mapping technology will
  help to realize the goal of patient-specific
  whole genomic analysis
• Optical Mapping is a modern application of
  discrete mathematics with potential to change
  medicine

20
References

1. Samad A, Huff EF, Cai W, Schwartz DC. Optical
   mapping A novel, single-molecule approach to
   genomic analysis. Genome Res. 199551-4.
2. Ramme AJ. Personal image collection. .
3. Schwartz DC, Samad A. Optical mapping approaches
   to molecular genomics. Curr Opin Biotechnol.
   1997870-74.
4. Valouev A, Schwartz DC, Zhou S, Waterman MS. An
   algorithm for assembly of ordered restriction
   maps from single DNA molecules. Proc Natl Acad
   Sci U S A. 200610315770-15775.
5. Aston C, Mishra B, Schwartz DC. Optical mapping
   and its potential for large-scale sequencing
   projects. Trends Biotechnol. 199917297-302.
6. Valouev A, Li L, Liu YC, et al. Alignment of
   optical maps. J Comput Biol. 200613442-462.
7. Valouev A, Zhang Y, Schwartz DC, Waterman MS.
   Refinement of optical map assemblies.
   Bioinformatics. 2006221217-1224.

21
Questions?
Further information available from 1.)
Laboratory for Molecular and Computational
Genetics (http//www.lmcg.wisc.edu/) 2.) Opgen
(http//www.opgen.com/)