DNA/RNA Protein Expression Interaction Molecular Data DNA/RNA Protein Expression Interaction
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/
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/
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
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
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
Sequence Content Mononucleotide frequencies Dinucleotide frequencies GC content Dinucleotide frequencies CpG islands
GC content is non-random Lander et al
GC content and expression
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) pAmononucleotide probability that a nucleotide will be an A http://www.cmu.edu/bio/education/courses/03310/LectureNotes/
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/
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
Dinucleotide counts A T C G 1 2 ATTCGACCAGAG
Observed and expected frequencies http://www.maths.lth.se/bioinformatics/publications/BasicE_2005.pdf
Observed and expected frequencies http://www.maths.lth.se/bioinformatics/publications/BasicE_2005.pdf
Dinucleotide frequencies in genome http://www.lapcs.univ-lyon1.fr/~piau/mps/Poster-CpG.pdf
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/
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/
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/
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 http://www.cmu.edu/bio/education/courses/03310/LectureNotes/
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/
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/
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
Example 1: using dinucleotide frequencies pART=pA(p*AAp*AT+p*AGp*GT)
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/