1. Probe Selection Problems in Gene Sequences

2. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ DNA Microarrays cDNA: PCR from clones Oligonucleotide: design specific probes

3. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ Gene Detection Using Microarrays ….CCCATGGACTCAAG…. ….CCCTGGCGACAGTT…. ….AATCCTACGACGGC…. ….AGCTCTAGGCCCAT…. Each probe  Selected from gene sequences  Same length (20mer~)  Detect one gene

4. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ Probe Selection Uniqueness  Comparing potential probe sequences with the full-length sequences of other genes being monitored Hybridization characteristics  Tm among probes  GC content  Secondary structure  Position of core region  Number of mismatch

5. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ Affymetrix Probe Selection Criteria Single base(As, Ts, Cs, Gs)  Not exceeds 50% of the probe size Length of contiguous As and Ts or Cs and Gs region  Less than 25% of the probe size (G+C)%  Between 40 and 60% of the probe sequence  (G+C)% can be adjusted based on G+C contents of a genome sequence Contiguous repeat  No 15-long repeat anywhere in the entire coding sequence of the whole genome No self-complementary within probe sequence

6. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ Tm Calculation Approximate target DNA concentration  : enthalpy for helix formation  : entropy for helix formation  R : molar gas constant ( )  c : total molar concentration of the annealing oligonucleotides when oligonucleotides are not self-complementary

7. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ General Approach Probe sequence 생성  임의의 서열을 만들어 후보 probe 를 생성한다.  Target gene 서열로부터 후보 probe 를 생성한다.  일반적으로 유전자의 처음부터 sliding window 방식으로 생성 한다. ACGCGTCGCGAGGCCTAGGCC… 후보 probe 시퀀스

8. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ General Approach 후보 probe 서열 중 target sequences 이외의 유전자에 흔히 존재하는 것 들을 삭제한다. (blast 등과 같은 sequence alignment 프로그램을 이용한다 )  cross hybridization 발생 가능성 억제 Target 과 probe 간의 hybridization 이 잘되게 하기 위해 Tm 값을 이용해 후보 probe 서열들을 필터링한다. Sequence 의 2 차원 구조에 따른 필터링을 한다. Intramolecular 구조가 형성될 수 있는 것들을 제거.

9. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ GA Representation Chromosome represents possible probe set. Each position of a chromosome is the starting point of probe sequence in gene sequence. one probe (parameter: probe length c) probe set (size n: number of target genes) 3..... 2 15 90 start position of selected region

10. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ GA Operators Fitness function  Linear combination of sequence match and probe characteristics  Combination rate can be varied with generation  Sequence match between probe and target gene  Perfect match: 1  Mismatch: 0  Considered probe characteristics  Tm  (G+C)%  Self-complementary (by sequence comparison) Population  Population  Parents are selected from roulette-wheel  One-point crossover with Pc, mutation with Pm

11. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ Optimizing Probe Set One probe(spot) is designed to detect one gene. Assumption  Optimal probe set will contain as few oligonucleotide as possible Goal  M probes detect N genes (M is less than or equal to N)  Find M probes which detect N genes

12. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/Example 3 target genes ….CCCATAGGCTCAAG…. ….CCTAGGCGCGCTCA…. ….AGCTCTAGGCCCAT….

13. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ GA Representation Probe sequences are selected from target gene sequences one probe (parameter: probe length c) probe set (size m: number of probes) 3..... 2 15 90 start position of selected region 1..... 8 20 10 gene id

14. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/ Sequence Matching Target, probe Matching result between target c i and probe set  Can be represented as list or vector   fingerprint  Two clones are distinguishable  Find probe set which make all fingerprints different each other.

15. (C) 2003, SNU Biointelligence Lab, http://bi.snu.ac.kr/http://bi.snu.ac.kr/Issues Consider number of mismatch Consider Blast search Design of probe sequences For fitness conditions, probe characteristics can be learned?