Design Flow Enhancements for DNA Arrays

1. Design Flow Enhancements for DNA Arrays Andrew B. Kahng1 Ion I. Mandoiu2 Sherief Reda1 Xu Xu1 Alex Zelikovsky3 (1)CSE Department, University of California at San Diego (2) CSE Department, University of Connecticut (3) CS Department, Georgia State University

2. Outline Introduction to DNA microarrays and manufacturing challenges DNA microarray design flow DNA microarray design flow enhancements: Integration of Probe Placement and Embedding Integration of Probe Selection and Physical Design Conclusions and future research directions

3. Introduction to DNA microarrays Uses of DNA arrays Practical experiment using DNA arrays DNA manufacturing process Problems and challenges in DNA manufacturing process

4. DNA Arrays are composed of probes where each probe is a sequence of 25 nucleotides 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

5. Laser activation of fluorescent tags Optical scanning of hybridization intensities DNA Array Hybridization Experiment Tagged RNA fragments flushed over array Images courtesy of Affymetrix.

6. Selectively expose array sites to light Treat substrate with chemically protected linker molecules 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) DNA Array Manufacturing Process

7. Probe Synthesis A  Mask 1 A A A A A A 3×3 array CG AC G AC ACG AG AG C CG Nucleotide Deposition Sequence ACG array probes

8. Probe Synthesis C  Mask 2 A C C A A C A C A C C A 3×3 array CG AC G AC ACG AG AG C CG Nucleotide Deposition Sequence ACG array probes

9. Probe Synthesis G  Mask 3 A Nucleotide DepositionSequence defines the order of nucleotide deposition A Probe Embedding specifies the steps it uses in the nucleotide sequence to get synthesized A C G G C A A C A G C G A C G G C A 3×3 array CG AC G AC ACG AG AG C CG Nucleotide Deposition Sequence ACG array probes

10. 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

11. Unwanted Illumination and Border Cost A  Mask 1 Border Reduction Border = 8  Unwanted illumination  Chip’s yield A A A A A A 3×3 array CG AC G AC ACG AG AG C CG Nucleotide Deposition Sequence ACG array probes

12. Outline Introduction to DNA arrays manufacturing challenges DNA array design flow DNA array design flow enhancements: Integration of Probe Placement and Embedding Integration of Probe Selection and Physical Design Conclusions

13. 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,” WABI02, suggested constructive methods for placement and embedding Kahng et al. “Engineering a Scalable Placement Heuristic for DNA Probe Arrays ,” RECOMB03, suggested scalable placement improvement and embedding techniques

14. Basic DNA Array Design Flow Design of Test Probes Design of Test Probes BIST and DFT Probe Placement Probe Placement Probe Embedding Probe Embedding Physical Design Placement Routing Probe Selection Probe Selection Logic Synthesis Logic Synthesis BIST and DFT Analogy Placement Physical Design Routing DNA Array VLSI Chip

15. 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

16. Key DOF: Probe Embedding (Alignment) T G G G C A T T G G C A T T T G C C C C A Synchronous Embedding As Soon As Possible (ASAP) Embedding Another Embedding G Group T C Deposition Sequence Hypothetical Probe

17. A A G T A A G G G T T T G G G A A Synchronous Embedding ASAP Embedding Embedding Determines Border Conflicts G T C A G T C Deposition Sequence A G T Probes C A A A G G T T T G C G A A

18. Optimal Probe Embedding T Using Dynamic Programming to optimally re-embed a probe A A A T G G G G A A A C T T A A After optimal re-embedding Problem: Optimally embedding a probe with respect to its neighbors T A T G G A A A A A A A C A Before optimal re-embedding Kahng et al. “Border Length Minimization in DNA Array Design,” WABI02

19. Placement Polishing Using Re-Embedding Use optimal re-embedding algorithm to re-embed each probe with respect to its neighbors

20. Placement Objective: Minimize Border 1 2 3 25 A A A A C C A A A A T T A A A A T T A A T T T T G G C C G G C C C C G G G G G G Radix-sorting the probes order reduces discrepancies between adjacent probes 1 2 3 25 Probe 1 Probe 2 Probe 3 Probe 5 Probe 4 Radix-sort the probes in lexicographical order Problem: How to place the 1-D ordering of probes onto the 2-D chip?

21. Placement By Threading A A C A A T A A T A T T G C G C C G G G 1 2 3 25 2 3 Probe 1 Probe 2 5 4 1 Probe 3 Probe 4 Probe 5 Thread on the chip

22. Row-Epitaxial Placement Improvement Row placement = sort + thread + row epitaxial 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

23. Outline Introduction to DNA arrays manufacturing challenges DNA array design flow DNA array design flow enhancements: Integration of Probe Placement and Embedding Integration of Probe Selection and Physical Design Conclusions

24. DNA array design flow enhancements Design of Test Probes Probe Placement Probe Embedding Integration of Probe Placement and Embedding Probe Selection  Initial embeddings influence the placement results  Propose and implement two flows Integration of Probe Selection and Physical Design  Probe pools add additional degrees of freedom Physical Design  Integrate probe selection into physical design  Propose and implement two flows incorporating probe pools DNA Array

25. Integration of Probe Placement and Embedding Integrating placement and probe embedding gives a further reduction in border conflicts. Design of Test Probes Probe Placement Probe Placement Analogous to tighter integration between placement and routing in VLSI physical design Probe Embedding Probe Embedding Probe Selection DNA Array

26. Integration of Probe Placement and Embedding Flow A Flow B 1. As Soon As Possible (ASAP) initial embedding 1. Synchronous initial embedding ASAP initial embedding Row Epitaxial 2. Row placement 2. Row placement Re-embedding 3. Re-embedding using DP 3. Re-embedding using DP Conflicts 6% Chip size

27. Placement + Embedding Runtimes Flow A Flow B 1. As Soon As Possible (ASAP) initial embedding 1. Synchronous initial embedding ASAP initial embedding Row Epitaxial 2. Row placement 2. Row placement Re-embedding 3. Re-embedding using DP 3. Re-embedding using DP CPU (s) Chip size Row Epitaxial Re-embedding

28. Second Enhancement: Probe Pools Design of Test Probes Probe Placement Probe Embedding 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. Probe Pool – Pool Size = 4 Probe Selection Probe 1 Probe 2 Probe 3 Probe 4 Gene Target Sequence Physical Design DNA Array

29. Integrating Probe Selection and Physical Design Flow A Flow B 1. Perform ASAP embedding of all probe candidates 1. Perform ASAP embedding of all probe candidates ASAP initial embedding 2. From each probe pool select the probe that fits in the least number of steps using ASAP 2. Run row placement selecting the probe from the pool that gives the minimum conflict 3. Run row placement using the selected candidates 3. Re-embedding 4. Re-embedding

30. Results (Conflicts) of Probe Pools Chip size = 100 Chip size = 200 Conflicts Conflicts Pool Size Pool Size Chip size = 300 Chip size = 500 Conflicts Conflicts Pool Size Pool Size

31. Comparison of Probe Pools Flows Chip size = 100 Chip size = 200 Conflicts Conflicts Pool Size Pool Size Chip size = 300 Chip size = 500 Conflicts Conflicts Pool Size Pool Size

32. Results (runtime) of Probe Pools Chip size = 100 Chip size = 200 CPU (1000s) CPU (1000s) Pool Size Pool Size Chip size = 300 Chip size = 500 CPU (1000s) CPU (1000s) Pool Size Pool Size

33. 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

34. Open Research Directions Probes P1 P2 P3 P4 P5 T1 T2 Target Sequences T3 T4 Each target sequence should have a unique signature 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.

35. 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 10k× 10k

36. 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

37. Thanks for your attention