1. Real-Time Primer Design for DNA Chips Annie Hui CMSC 838 Presentation

2. CMSC 838T – Presentation Use of primers in PCR and Microarrays u PCR (polymerase chain reaction:  to amplify a particular DNA fragment  Use: to test for the presence of nucleotide sequences Ladder: a mixture of fragments of known length Lane 1 : PCR fragment is ~1850 bases long. Lane 2 and 4 : the fragments are ~ 800 bases long. Lane 3 : no product is formed, so the PCR failed. Lane 5 : multiple bands are formed because one of the primers fits on different places. u Test of PCR products:

3. CMSC 838T – Presentation Use of primers in PCR and Microarrays u DNA chips (Microarrays):  to analyse a large number of genes in parallel. u Primers:  20 to 100 bases long  Synthetically manufactured u Automated design of primer  A computational approach  Objective: To find primers that bind well without self-hybridizing  Critique: how accurate? Fixed on chip fluorescence Bound to primer

4. CMSC 838T – Presentation Motivation: This group uses the automated NucliSens extraction system (bioMerieux) to develop their primers here.

5. CMSC 838T – Presentation 1. Select primers from target sequence  two primers P (forward) and Q (reverse) for PCR, one primer for DNA chip (microarray)  Using window size W, number of possible primers with length between m and n within 1 window is: Technique: The computational model

6. CMSC 838T – Presentation Technique: The computational model 2. For each primer pair, or single primer, Quantify 4 hybridization conditions: a. Primer length b. Melting temperature c. GC content d. Secondary structure i. Self annealing ii. Self end annealing iii. Pair annealing iv. Pair end annealing We are starting here

7. CMSC 838T – Presentation Technique: quantifying hybridization conditions a. Primer length len(P)  Affect melting temperature and hybridization b. Melting temperature T m (P)  Temperature at which the bonds between primer and gene sequence break c. CG content CG(P)  G-C pairs are more stable than A-T pairs (because of more H-bonds) What is this measure good for?

8. CMSC 838T – Presentation Technique: quantifying hybridization conditions d. Secondary structure  Study how likely a primer entangles with itself or with another primer  P = {p 1, p 2, …, p n }, Q = {q 1, q 2, …, q m },  Scoring function: l S(p i, q j ) = 2 if {p i, q j } = {A, T} = 4 if {p i, q j } = {C, G} = 0otherwise Example: P:...AGCTTTAGCCATAG Q: TCTTAGGATCGC... score S(p i, q 1 ) = 2+4+2+2+4 = 14 Position i of primer P

9. CMSC 838T – Presentation Technique: quantifying hybridization conditions u Four measures of secondary structure: i. Self annealing, SA(P, P’) P’ = reverse of P P P’ ii. Self end annealing, SEA(P, P’) Like Self annealing k>=0 Only count longest continuous overlaps P P’ iii. Pair annealing, PA(P, Q) P and Q are the forward and reverse primers iv. Pair end annealing, PEA(P, Q) similar to self end annealing

10. CMSC 838T – Presentation u For PCR:  P is forward primer, Q is reverse primer  Ideally, no annealing, length, GC and temp of P equals Q  The optimization is: u For DNA chips (Microarrays):  Q doesn’t exist. No pair annealing to study. Only 5 terms left. Technique: How to apply the model

11. CMSC 838T – Presentation Technique: parallelize SCPCR(p,q) calculation Calculate Len, GC, Temp, SA and SEA in parallel Compute PA and PEA in parallel

12. CMSC 838T – Presentation u Melting temperature and CG content:  Simple adder+divider  Use pipelining  1 st one: O(m)  Subsequent cost: O(1) u Annealing matrix Technique: details ad bd cd a b c d e f ce be ae af bf cf Whole window: AGCGATATA i-th P primer: GCGATA (i+I)-th P primer: CGATAT CG(P i+1 ) = CG(P i ) - 1  H(P i+1 ) =  H(P i ) - H(GC) + H(AT), similar for  S

13. CMSC 838T – Presentation u Complexity for sequential algorithm:  For PCR: l Number of choices of P (window size=W p ): l Number of choices of Q (window size=W q ): l Each distance SCPCR(P,Q): l Total: u Complexity for parallel algorithm:  For PCR: l Distance measure SCPCR(P, Q) = O(1) l Total: O(S*T) Similar but simpler for Microarray Complexity O(S*S*T*T) is a typo in the paper

14. CMSC 838T – Presentation Evaluation u Experimental environment  512 primer pairs, |W p | = |W q | = 16 1. 500MHz Celeron system with integrated hardware accelerator 2. Software implementation u Evaluation results  1920 secs for software implementation  3.41 secs for using hardware accelerator

15. CMSC 838T – Presentation Related Work u Previous approach  DOPRIMER l Same computational model l Differ in the way of doing dynamic programming l Sequential in nature u Other Primer selection softwares  Eg: Primer Premier 5, Primer3, PrimerGen, PrimerDesign  Similarities: l Criteria: Length, Temp range, GC range, GC Clamp, 3’ end stability, uniqueness of 3’ end base, Dimer/hairpins, Degeneracy, Salt concentration, Annealing Oligo Concentration, etc  Differences: l Not a weighed linear sum of all criteria l Need much expert’s supervision, l the numerical criteria are used as a guide only

16. CMSC 838T – Presentation More Related Works u Case study  Burpo did a critical review of PCR primer design algorithms l Subject: saccharomyces cerevisiae deletion strains l Conclusion: u no suitable program for the task of post-design PCR analysis u Especially in the aspect of accurately predicting non-specific hybridization events that impair PCR amplification.

17. CMSC 838T – Presentation Observations u My observations:  Minus side: l Is the computational model too simplistic? l Specifically, is a weighed linear sum justified?  Plus side: l The design of the parallel architecture is neat. l Since primers are about the length of 18-22 bases, current technology certainly can handle it.  When would you need fast primer selection? l Primer walking to connect contigs together quickly l To scan through a large number of sequences for possible primers