It & Health 2010 Summary Thomas Nordahl Petersen.

It & Health 2010Summary

Thomas Nordahl Petersen

DNA/RNA

• DNA findes I celle kernen (Eukaryoter)• base paring• T substituted with U in RNA• Reading direction• Reading frame (1,2,3,-1,-2,-3)• 64 codons• DNA -> mRNA• Intron, exon & UTR (non-coding exon)• Intron/Exon splice site

Reading frame andreverse complement

TGCCATGCATAGCCCCTGCCATATCT

Having a piece of DNA like:

Forward strings & reading frames1 : TGCCATGCATAGCCCCTGCCATATCT2 : GCCATGCATAGCCCCTGCCATATCT3 : CCATGCATAGCCCCTGCCATATCT

Reverse complement strings & reading frames-1: TCTATACCGTCCCCGATACGTACCGT-2: CTATACCGTCCCCGATACGTACCGT-3: TATACCGTCCCCGATACGTACCGT

Amino acids

20 naturally occurring amino acids- mRNA -> protein- Reading direction- 4 backbone atoms- Amino acid properties

- Acidic, basic, polar, charged, hydrophibic

- 1 and 3 letter codes

Amino Acids

Amine and carboxyl groups. Sidechain ‘R’ is attached to C-alpha carbon

The amino acids found in Living organisms are L-amino acids

Amino Acids - peptide bond

N-terminal C-terminal

Databases and web-tools

Databases and biological information• Genbank• Uniprot

Web-tools• NCBI Blast• UCSC genome browser• Weblogo

CE

NT

ER

FO

R B

IOLO

GIC

AL

SE

QU

EN

CE

AN

ALY

SIS

Theory of evolution

Charles DarwinCharles Darwin1809-18821809-1882

Phylogenetic tree

Global versus local alignments

Global alignment: align full length of both sequences. (The “Needleman-Wunsch” algorithm).

Local alignment: find best partial alignment of two sequences (the “Smith-Waterman” algorithm).

Global alignment

Seq 1

Seq 2

Local alignment

Pairwise alignment: the solution

”Dynamic programming” (the Needleman-Wunsch algorithm)

Sequence alignment - Blast

Sequence alignment - Blast

Blosum & PAM matrices

• Blosum matrices are the most commonly used substitution matrices.

• Blosum50, Blosum62, blosum80• PAM - Percent Accepted Mutations• PAM-0 is the identity matrix.• PAM-1 diagonal small deviations from 1, off-

diag has small deviations from 0• PAM-250 is PAM-1 multiplied by itself 250

times.

Sequence profiles (1J2J.B)

>1J2J.B mol:aa PROTEIN TRANSPORT NVIFEDEEKSKMLARLLKSSHPEDLRAANKLIKEMVQEDQKRMEK

Log-odds scores

• BLOSUM is a log-likelihood matrix:• Likelihood of observing j given you have i is

– P(j|i) = Pij/Pi

• The prior likelihood of observing j is– Qj , which is simply the frequency

• The log-likelihood score is– Sij = 2log2(P(j|i)/log(Qj) = 2log2(Pij/(QiQj))– Where, Log2(x)=logn(x)/logn(2) – S has been normalized to half bits, therefore the factor 2

BLAST Exercise

Genome browsers - UCSC

Intron - Exon structure

Single Nucleotide polymorphism - SNP

SNPs

Protein 3D-structure

Protein structure

Primary structure: Amino acids sequences

Secondary structure: Helix/Beta sheet

Tertiary structure: Fold, 3D cordinates

Protein structure-helix

helix 3 residues/turn - few, but not uncommon-helix 3.6 residues/turn - by far the most common helixPi-helix 4.1 residues/turn - very rare

Protein structurestrand/sheet

Protein folds

ClassAlpha,beta, alpha+beta and alpha/beta

And last class – none or few SS-elements

ArchitectureOverall shape of a domain

TopologyShare secondary structure connectivity

Protein 3D-structure

Neural NetworksFrom knowledge to information

Protein sequence Biological feature

• A data-driven method to predict a feature, given a set of training data

• In biology input features could be amino acid sequence or nucleotides

• Secondary structure prediction

• Signal peptide prediction

• Surface accessibility

• Propeptide prediction

Use of artificial neural networks

N C

Signalpeptide

Propeptide Mature/active protein

Prediction of biological featuresSurface accessible

Predict surface accessible fromamino acid sequence only.

Logo plots

Information content, how is it calculated - what does it mean.

Logo plots - Information Content

Sequence-logo

Calculate Information Content

I = apalog2pa + log2(4), Maximal value is 2 bits

• Total height at a position is the ‘Information Content’ measured in bits.• Height of letter is the proportional to the frequency of that letter.• A Logo plot is a visualization of a mutiple alignment.

~0.5 each

Completely conserved