1. DNA/RNA Protein Expression Interaction
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

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

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 Amino Acid Abbreviation DNA Codons Alanine Ala
GCA, GCC, GCG, GCT
Cysteine
Cys
TGC, TGT
Aspartic Acid
Asp
GAC, GAT
Glutamic Acid
Glu
GAA, GAG
Phenylalanine
Phe
TTC, TTT
Glycine
Gly
GGA, GGC, GGG, GGT
Histidine
His
CAC, CAT
Isoleucine
Ile
ATA, ATC, ATT
Lysine
Lys
AAA, AAG
Leucine
Leu
TTA, TTG, CTA, CTC, CTG, CTT
Methionine
Met
ATG
Asparagine
Asn
AAC, AAT
Proline
Pro
CCA, CCC, CCG, CCT
Glutamine
Gln
CAA, CAG
Arginine
Arg
CGA, CGC, CGG, CGT
Serine
Ser
TCA, TCC, TCG, TCT, AGC, AGT
Threonine
Thr
ACA, ACC, ACG, ACT
Valine
Val
GTA, GTC, GTG, GTT
Tryptophan
Trp
TGG
Tyrosine
Tyr
TAC, TAT
Stop .
TAA, TAG, TGA

6. Fasta format
>gi| |ref|NM_ | 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 Dinucleotide 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

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)

12. Dinucleotide counts A T C G ATTCGACCAGAG 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 A T C G
ATTCGACCAGAG

13. Dinucleotide counts A T C G 1 2
ATTCGACCAGAG

14. Observed and expected frequencies

15. Observed and expected frequencies

16. Dinucleotide frequencies in genome

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

18. Sequence features promoters transcription initiation sites
transcription termination sites
polyadenylation sites
ribosome binding sites
protein features

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

20. Occurences Basic Algorithm
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

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)

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

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