Molecular Data

1. Molecular Data DNA/RNA Protein Expression Interaction

2. A sequence • A sequence is a linear set of characters (sequence elements) representing nucleotides or amino acids http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

3. Character representation of sequences • DNA or RNA • use 1-letter codes (e.g., A,C,G,T) • protein • use 1-letter codes • can convert to/from 3-letter codes http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

4. The I.U.B. Code proposed by International Union of Biochemistry A, C, G, T, U R = A, G (puRine) Y = C, T (pYrimidine) S = G, C (Strong hydrogen bonds) W = A, T (Weak hydrogen bonds) M = A, C (aMino group) K = G, T (Keto group) B = C, G, T (not A) D = A, G, T (not C) H = A, C, T (not G) V = A, C, G (not T/U) N = A, C, G, T/U (iNdeterminate) X or - are sometimes used

5. DNA code

6. Fasta format >gi|17978494|ref|NM_078467.1| Homo sapiens cyclin-dependent kinase inhibitor AGCTGAGGTGTGAGCAGCTGCCGAAGTCAGTTCCTTGTGGAGCCGGAGCTGGGCGCGGATTCGCCGAGGC ACCGAGGCACTCAGAGGAGGTGAGAGAGCGGCGGCAGACAACAGGGGACCCCGGGCCGGCGGCCCAGAGC CGAGCCAAGCGTGCCCGCGTGTGTCCCTGCGTGTCCGCGAGGATGCGTGTTCGCGGGTGTGTGCTGCGTT CACAGGTGTTTCTGCGGCAGGCGCCATGTCAGAACCGGCTGGGGATGTCCGTCAGAACCCATGCGGCAGC AAGGCCTGCCGCCGCCTCTTCGGCCCAGTGGACAGCGAGCAGCTGAGCCGCGACTGTGATGCGCTAATGG CGGGCTGCATCCAGGAGGCCCGTGAGCGATGGAACTTCGACTTTGTCACCGAGACACCACTGGAGGGTGA CTTCGCCTGGGAGCGTGTGCGGGGCCTTGGCCTGCCCAAGCTCTACCTTCCCACGGGGCCCCGGCGAGGC CGGGATGAGTTGGGAGGAGGCAGGCGGCCTGGCACCTCACCTGCTCTGCTGCAGGGGACAGCAGAGGAAG ACCATGTGGACCTGTCACTGTCTTGTACCCTTGTGCCTCGCTCAGGGGAGCAGGCTGAAGGGTCCCCAGG TGGACCTGGAGACTCTCAGGGTCGAAAACGGCGGCAGACCAGCATGACAGATTTCTACCACTCCAAACGC CGGCTGATCTTCTCCAAGAGGAAGCCCTAATCCGCCCACAGGAAGCCTGCAGTCCTGGAAGCGCGAGGGC CTCAAAGGCCCGCTCTACATCTTCTGCCTTAGTCTCAGTTTGTGTGTCTTAATTATTATTTGTGTTTTAA TTTAAACACCTCCTCATGTACATACCCTGGCCGCCCCCTGCCCCCCAGCCTCTGGCATTAGAATTATTTA AACAAAAACTAGGCGGTTGAATGAGAGGTTCCTAAGAGTGCTGGGCATTTTTATTTTATGAAATACTATT TAAAGCCTCCTCATCCCGTGTTCTCCTTTTCCTCTCTCCCGGAGGTTGGGTGGGCCGGCTTCATGCCAGC TACTTCCTCCTCCCCACTTGTCCGCTGGGTGGTACCCTCTGGAGGGGTGTGGCTCCTTCCCATCGCTGTC ACAGGCGGTTATGAAATTCACCCCCTTTCCTGGACACTCAGACCTGAATTCTTTTTCATTTGAGAAGTAA ACAGATGGCACTTTGAAGGGGCCTCACCGAGTGGGGGCATCATCAAAAACTTTGGAGTCCCCTCACCTCC TCTAAGGTTGGGCAGGGTGACCCTGAAGTGAGCACAGCCTAGGGCTGAGCTGGGGACCTGGTACCCTCCT GGCTCTTGATACCCCCCTCTGTCTTGTGAAGGCAGGGGGAAGGTGGGGTCCTGGAGCAGACCACCCCGCC TGCCCTCATGGCCCCTCTGACCTGCACTGGGGAGCCCGTCTCAGTGTTGAGCCTTTTCCCTCTTTGGCTC CCCTGTACCTTTTGAGGAGCCCCAGCTACCCTTCTTCTCCAGCTGGGCTCTGCAATTCCCCTCTGCTGCT GTCCCTCCCCCTTGTCCTTTCCCTTCAGTACCCTCTCAGCTCCAGGTGGCTCTGAGGTGCCTGTCCCACC CCCACCCCCAGCTCAATGGACTGGAAGGGGAAGGGACACACAAGAAGAAGGGCACCCTAGTTCTACCTCA GGCAGCTCAAGCAGCGACCGCCCCCTCCTCTAGCTGTGGGGGTGAGGGTCCCATGTGGTGGCACAGGCCC CCTTGAGTGGGGTTATCTCTGTGTTAGGGGTATATGATGGGGGAGTAGATCTTTCTAGGAGGGAGACACT GGCCCCTCAAATCGTCCAGCGACCTTCCTCATCCACCCCATCCCTCCCCAGTTCATTGCACTTTGATTAG CAGCGGAACAAGGAGTCAGACATTTTAAGATGGTGGCAGTAGAGGCTATGGACAGGGCATGCCACGTGGG CTCATATGGGGCTGGGAGTAGTTGTCTTTCCTGGCACTAACGTTGAGCCCCTGGAGGCACTGAAGTGCTT AGTGTACTTGGAGTATTGGGGTCTGACCCCAAACACCTTCCAGCTCCTGTAACATACTGGCCTGGACTGT TTTCTCTCGGCTCCCCATGTGTCCTGGTTCCCGTTTCTCCACCTAGACTGTAAACCTCTCGAGGGCAGGG ACCACACCCTGTACTGTTCTGTGTCTTTCACAGCTCCTCCCACAATGCTGAATATACAGCAGGTGCTCAA TAAATGATTCTTAGTGACTTTAAAAAAAAAAAAAAAAAAAA

7. Sequence Content • Mononucleotide frequencies • GC content • Dinucleotide frequencies • CpG islands

8. GC content is non-random Lander et al

9. GC content and expression

10. Determining mononucleotide frequencies • Alphabet: A T C G • Count how many times each nucleotide appears in sequence • Divide (normalize) by total number of nucleotides • fAmononucleotide frequency of A (frequency that A is observed) • pAmononucleotide probability that a nucleotide will be an A http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

11. Determining dinucleotide frequencies • Make 4 x 4 matrix, one element for each ordered pair of nucleotides • Set all elements to zero • Go through sequence linearly, adding one to matrix entry corresponding to the pair of sequence elements observed at that position • Divide by total number of dinucleotides • fAC dinucleotide frequency of AC (frequency that AC is observed out of all dinucleotides) http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

12. Dinucleotide counts Create a 4 x 4 matrix Set all cells to zeros Use a window of size 2 and add 1 to each cell of the matrix when encountering the specified dinucleotide ATTCGACCAGAG

13. Dinucleotide counts ATTCGACCAGAG

14. Observed and expected frequencies http://www.maths.lth.se/bioinformatics/publications/BasicE_2005.pdf

15. Observed and expected frequencies http://www.maths.lth.se/bioinformatics/publications/BasicE_2005.pdf

16. Dinucleotide frequencies in genome http://www.lapcs.univ-lyon1.fr/~piau/mps/Poster-CpG.pdf

17. Sequence features • A sequence feature is a pattern that is observed to occur in more than one sequence and (usually) to be correlated with some function http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

18. Sequence features • promoters • transcription initiation sites • transcription termination sites • polyadenylation sites • ribosome binding sites • protein features http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

19. Consensus sequences • A consensus sequence is a sequence that summarizes or approximates the pattern observed in a group of aligned sequences containing a sequence feature • Consensus sequences are regular expressions http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

20. Occurences • Example: recognition site for a restriction enzyme • EcoRI recognizes GAATTC • AccI recognizes GTMKAC • Basic Algorithm • Start with first character of sequence to be searched • See if enzyme site matches starting at that position • Advance to next character of sequence to be searched • Repeat previous two steps until all positions have been tested http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

21. Statistics of pattern appearance • Goal: Determine the significance of observing a feature (pattern) • Method: Estimate the probability that a pattern would occur randomly in a given sequence. Three different methods • Assume all nucleotides are equally frequent • Use measured frequencies of each nucleotide (mononucleotide frequencies) • Use measured frequencies with which a given nucleotide follows another (dinucleotide frequencies) http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

22. Example 1 • What is the probability of observing the sequence feature ART (A followed by a purine, either A or G, followed by a T)? • Using observed mononucleotide frequencies: • pART = pA (pA + pG) pT • Using equal mononucleotide frequencies • pA = pC = pG = pT = 1/4 • pART = 1/4 * (1/4 + 1/4) * 1/4 = 1/32 http://www.cmu.edu/bio/education/courses/03310/LectureNotes/

23. Example 1: using mononucleotide frequencies • Using equal mononucleotide frequencies • pA = pC = pG = pT = 1/4 • pART = 1/4 * (1/4 + 1/4) * 1/4 = 1/32 • Using observed mononucleotide frequencies: • pART = pA (pA + pG) pT

24. Example 1: using dinucleotide frequencies • pART=pA(p*AAp*AT+p*AGp*GT)

25. Example 2: • What is the probability of observing the sequence feature ARYT (A followed by a purine {either A or G}, followed by a pyrimidine {either C or T}, followed by a T)? • Using equal mononucleotide frequencies • pA = pC = pG = pT = 1/4 • pARYT = 1/4 * (1/4 + 1/4) * (1/4 + 1/4) * 1/4 = 1/64 http://www.cmu.edu/bio/education/courses/03310/LectureNotes/