Design Flow Enhancements for DNA Arrays Andrew B. Kahng 1 Ion I. Mandoiu 2 Sherief Reda 1 Xu Xu 1 Alex Zelikovsky 3 (1) CSE Department, University of California at San Diego (2) CSE Department, University of Connecticut (3) CS Department, Georgia State University
Outline Introduction to DNA microarrays and manufacturing challenges DNA microarray design flow enhancements: Integration of Probe Placement and Embedding Integration of Probe Selection and Physical Design Conclusions and future research directions
Introduction to DNA microarrays Uses of DNA arrays Practical experiment using DNA arrays DNA manufacturing process Problems and challenges in DNA manufacturing process
Introduction to DNA Probe Arrays DNA Arrays (Gene Chips) used in wide range of genomic analyses gene expression detection drug discovery mutation detection Diverse fields from health care to environmental sciences DNA Arrays are composed of probes where each probe is a sequence of 25 nucleotides
DNA Array Hybridization Experiment Tagged RNA fragments flushed over array Laser activation of fluorescent tags Optical scanning of hybridization intensities Images courtesy of Affymetrix.
DNA Array Manufacturing Process Treat substrate with chemically protected linker molecules Selectively expose array sites to light Flush chip’s surface with solution of protected A, C, G, T Repeat last two steps until desired probes are synthesized Very Large-Scale Immobilized Polymer Synthesis (VLSIPS)
Probe Synthesis CG AC ACG AG C array probes Nucleotide Deposition Sequence ACG A 3× 3 array A Mask 1 A A A
Probe Synthesis CG AC ACG AG C array probes Nucleotide Deposition Sequence ACG A 3× 3 array C Mask 2 C AC AC A A C
Probe Synthesis CG AC ACG AG C array probes A Nucleotide Deposition Sequence defines the order of nucleotide deposition A Probe Embedding specifies the steps it uses in the nucleotide sequence to get synthesized Nucleotide Deposition Sequence ACG A 3× 3 array G Mask 3 CG AC G AG G AC AG C
VLSIPS Manufacturing Challenges Problem: Diffraction, internal reflection, scattering, internal illumination Occurs at sites near to intentionally exposed sites Lamp Mask Reduce interference Increase yield Reduce cost Design objective: Minimize the border length Array
A 3× 3 array CG AC ACG AG C array probes Border Reduction Unwanted illumination Chip’s yield Nucleotide Deposition Sequence ACG Unwanted Illumination and Border Cost A Mask 1 Border = 8 A A A
Outline Introduction to DNA arrays manufacturing challenges DNA array design flow enhancements: Integration of Probe Placement and Embedding Integration of Probe Selection and Physical Design Conclusions
Previous Work Border minimization was first introduced by Feldman and Pevzner. “Gray Code masks for sequencing by hybridization, ” Genomics, 1994, pp. 233 -235 Work by Hannenhalli et al. gave heuristics for the placement problem by using a TSP formulation. Kahng et al. “Border length minimization in DNA Array Design, ” WABI 02, suggested constructive methods for placement and embedding Kahng et al. “Engineering a Scalable Placement Heuristic for DNA Probe Arrays , ” RECOMB 03, suggested scalable placement improvement and embedding techniques
Basic DNA Array Design Flow Probe Selection Design of Test Probes Probe Placement Logic Synthesis BIST and DFT Analogy Physical Design Placement Physic al Design Probe Embedding Routing DNA Array VLSI Chip
Design Flow Outline Physical Design Probe Embedding Degrees of freedom (DOF) in probe embedding DOF exploitation for border conflict reduction Probe Placement Similar probes should be placed close together Constructive placement Placement improvement operators
Group Key DOF: Probe Embedding (Alignment) T G C A G G T C Deposition Hypothetical Sequence Probe T C C Synchronous As Soon As Possible Embedding (ASAP) Embedding Another Embedding
Deposition Sequence Embedding Determines Border Conflicts G T C A A T A G A T Probes A T G A A G T G G A A Synchronous Embedding ASAP Embedding
Optimal Probe Embedding Problem: Optimally embedding a probe with respect to its neighbors T T A G A T G A Using Dynamic Programming to optimally reembed a probe A G C T G A T T A G A A A A C A After optimal re-embedding Before optimal re-embedding Kahng et al. “Border Length Minimization in DNA Array Design, ” WABI 02
Placement Polishing Using Re-Embedding Use optimal re-embedding algorithm to re-embed each probe with respect to its neighbors
Placement Objective: Minimize Border Radix-sorting the probes order reduces discrepancies between adjacent probes 1 2 3 25 Probe 1 G C A A C A Probe 2 T A T A A Probe 3 A T A A C G G G Probe 5 C G G C G C Probe 4 A A C A T T Radix-sort the probes in lexicographical order Problem: How to place the 1 -D ordering of probes onto the 2 -D chip?
Placement By Threading 1 2 3 25 Probe 1 A A C A Probe 2 A T A A Probe 3 T A T T Probe 4 G C Probe 5 C G G 2 G 1 Thread on the chip 3 4 5
Row-Epitaxial Placement Improvement For each site position (i, j): From within the next k rows, find the best probe to place in (i, j) Move the best probe to (i, j) and lock it in this position Array of size 4 × 4 Row placement = sort + thread + row epitaxial
Outline Introduction to DNA arrays manufacturing challenges DNA array design flow enhancements: Integration of Probe Placement and Embedding Integration of Probe Selection and Physical Design Conclusions
DNA array design flow enhancements Integration of Probe Placement and Embedding Probe Selection Initial embeddings influence the placement results Propose and implement two flows Design of Test Probes Integration of Probe Selection and Physical Design Probe pools additional degrees of freedom Physical Integrate probe selection into physical design Design Propose and implement two flows incorporating probe pools Probe Placement Probe Embedding DNA Array
Integration of Probe Placement and Embedding Probe Selection Design of Test Probes Probe Placement Probe Embedding DNA Array Integrating placement and probe embedding gives a further reduction in border conflicts. Analogous to tighter integration between placement and routing in VLSI physical design
Integration of Probe Placement and Embedding Flow A 1. Synchronous initial embedding 2. Row placement 3. Re-embedding using DP Flow B 1. As Sooninitial embedding ASAP As Possible (ASAP) initial embedding Row Epitaxial 2. Re-embedding Row placement 3. Re-embedding using DP Conflicts 6% Chip size
Placement + Embedding Runtimes Flow A 1. Synchronous initial embedding 2. Row placement 3. Re-embedding using DP Flow B 1. As Sooninitial embedding ASAP As Possible (ASAP) initial embedding Row Epitaxial 2. Re-embedding Row placement 3. Re-embedding using DP CPU (s) Chip size
Second Enhancement: Probe Pools Probe Pool – Pool Size = 4 Probe Selection Probe 1 Design of Test Probes Probe Placement Probe Embedding DNA Array Physical Design Probe 2 Probe 3 Probe 4 Gene Target Sequence Problem: Given a probe pool for every target sequence, select a probe for every target sequence such that the total conflict after placement and alignment is minimum.
Integrating Probe Selection and Physical Design Flow A 1. Perform ASAP embedding of all probe candidates 2. Run row placement selecting the probe from the pool that gives the minimum conflict 3. Re-embedding Flow B 1. Perform ASAP initial embedding of all probe candidates 2. From each probe pool select the probe that fits in the least number of steps using ASAP 3. Run row placement using the selected candidates 4. Re-embedding
Results (Conflicts) of Probe Pools Conflicts Chip size = 100 Chip size = 300 Conflicts Pool Size Chip size = 200 Chip size = 500 Pool Size
Comparison of Probe Pools Flows Conflicts Chip size = 100 Chip size = 300 Conflicts Pool Size Chip size = 200 Chip size = 500 Pool Size
Results (runtime) of Probe Pools CPU (1000 s) Chip size = 100 Chip size = 300 CPU (1000 s) Pool Size Chip size = 200 Chip size = 500 Pool Size
Interpretation and Summary of Experimental Data Initial ASAP embeddings produce a decent reduction in border conflicts. Integration of placement and embedding yield up to 6% improvement Probe pools add an extra 12 -13% improvement Probe pools offer an extra degree of freedom exploited to further reduce border conflicts Total improvement up to 18% compared to results published in the literature
Open Research Directions Probe selection should incorporate ability to uniquely detect target sequences present in sample. This should be done with no ambiguity. Methods similar to Boolean covering and test diagnosis can be used. P 1 P 2 P 3 P 4 P 5 Probes T 1 T 2 Target Sequences T 3 T 4 Each target sequence should have a unique signature
Open Research Directions Insertion of probe test can benefit from test and diagnosis topics for VLSI circuits. Stronger placement operators leading to further reduction in the border cost. Future work also covers next generation chips 10 k × 10 k
Conclusions We presented a DNA design flow benefiting from experiences of the VLSI design flow We introduced feedback loops and integrated a number of steps for further reduction in the border cost and hence unwanted illumination We examined the embedding options and placement on the total border cost We examined the effects of probe selection on both placement and embedding
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