1. Introduction to Bioinformatics 2. Genetics Background Course 341 Department of Computing Imperial College, London © Simon Colton

2. Coursework 1 coursework – worth 20 marks – Work in pairs Retrieving information from a database Using Perl to manipulate that information

3. The Robot Scientist Performs experiments Learns from results – Using machine learning Plans more experiments Saves time and money Team member: – Stephen Muggleton

4. Biological Nomenclature Need to know the meaning of: – Species, organism, cell, nucleus, chromosome, DNA – Genome, gene, base, residue, protein, amino acid – Transcription, translation, messenger RNA – Codons, genetic code, evolution, mutation, crossover – Polymer, genotype, phenotype, conformation – Inheritance, homology, phylogenetic trees

5. Substructure and Effect (Top Down/Bottom Up) Species Organism Cell Nucleus Chromosome DNA strand Gene Base Protein Amino Acid Folds into Affects the Function of Affects the Behaviour of Prescribes

6. Cells Basic unit of life Different types of cell: – Skin, brain, red/white blood – Different biological function Cells produced by cells – Cell division (mitosis) – 2 daughter cells Eukaryotic cells – Have a nucleus

7. Nucleus and Chromosomes Each cell has nucleus Rod-shaped particles inside – Are chromosomes – Which we think of in pairs Different number for species – Human(46),tobacco(48) – Goldfish(94),chimp(48) – Usually paired up X & Y Chromosomes – Humans: Male(xy), Female(xx) – Birds: Male(xx), Female(xy)

8. DNA Strands Chromosomes are same in every cell of organism – Supercoiled DNA (Deoxyribonucleic acid) Take a human, take one cell – Determine the structure of all chromosonal DNA – You’ve just read the human genome (for 1 person) – Human genome project 13 years, 3.2 billion chemicals (bases) in human genome Other genomes being/been decoded: – Pufferfish, fruit fly, mouse, chicken, yeast, bacteria

9. DNA Structure Double Helix (Crick & Watson) – 2 coiled matching strands – Backbone of sugar phosphate pairs Nitrogenous Base Pairs – Roughly 20 atoms in a base – Adenine  Thymine [A,T] – Cytosine  Guanine [C,G] – Weak bonds (can be broken) – Form long chains called polymers Read the sequence on 1 strand – GATTCATCATGGATCATACTAAC

10. Differences in DNA 2% tiny Roughly 4% Share Material DNA differentiates: – Species/race/gender – Individuals We share DNA with – Primates,mammals – Fish, plants, bacteria Genotype – DNA of an individual Genetic constitution Phenotype – Characteristics of the resulting organism Nature and nurture

11. Genes Chunks of DNA sequence – Between 600 and 1200 bases long – 32,000 human genes, 100,000 genes in tulips Large percentage of human genome – Is “junk”: does not code for proteins “Simpler” organisms such as bacteria – Are much more evolved (have hardly any junk) – Viruses have overlapping genes (zipped/compressed) Often the active part of a gene is spit into exons – Seperated by introns

12. The Synthesis of Proteins Instructions for generating Amino Acid sequences – (i) DNA double helix is unzipped – (ii) One strand is transcribed to messenger RNA – (iii) RNA acts as a template ribosomes translate the RNA into the sequence of amino acids Amino acid sequences fold into a 3d molecule Gene expression – Every cell has every gene in it (has all chromosomes) – Which ones produce proteins (are expressed) & when?

13. Transcription Take one strand of DNA Write out the counterparts to each base – G becomes C (and vice versa) – A becomes T (and vice versa) Change Thymine [T] to Uracil [U] You have transcribed DNA into messenger RNA Example: Start: GGATGCCAATG Intermediate: CCTACGGTTAC Transcribed: CCUACGGUUAC

14. Genetic Code How the translation occurs Think of this as a function: – Input: triples of three base letters (Codons) – Output: amino acid – Example: ACC becomes threonine (T) Gene sequences end with: – TAA, TAG or TGA

15. Genetic Code A=Ala=Alanine C=Cys=Cysteine D=Asp=Aspartic acid E=Glu=Glutamic acid F=Phe=Phenylalanine G=Gly=Glycine H=His=Histidine I=Ile=Isoleucine K=Lys=Lysine L=Leu=Leucine M=Met=Methionine N=Asn=Asparagine P=Pro=Proline Q=Gln=Glutamine R=Arg=Arginine S=Ser=Serine T=Thr=Threonine V=Val=Valine W=Trp=Tryptophan Y=Tyr=Tyrosine

16. Example Synthesis TCGGTGAATCTGTTTGAT Transcribed to: AGCCACUUAGACAAACUA Translated to: SHLDKL

17. Proteins DNA codes for – strings of amino acids Amino acids strings – Fold up into complex 3d molecule – 3d structures:conformations – Between 200 & 400 “residues” – Folds are proteins Residue sequences – Always fold to same conformation Proteins play a part – In almost every biological process

18. Evolution of Genes: Inheritance Evolution of species – Caused by reproduction and survival of the fittest But actually, it is the genotype which evolves – Organism has to live with it (or die before reproduction) – Three mechanisms: inheritance, mutation and crossover Inheritance: properties from parents – Embryo has cells with 23 pairs of chromosomes – Each pair: 1 chromosome from father, 1 from mother – Most important factor in offspring’s genetic makeup

19. Evolution of Genes: Mutation Genes alter (slightly) during reproduction – Caused by errors, from radiation, from toxicity – 3 possibilities: deletion, insertion, alteration Deletion: ACGTTGACTC  ACGTGACTC Insertion: ACGTTGACTC  AGCGTTGACTC Substitution: ACGTTGACTC  ACGATGACTT Mutations are almost always deleterious – A single change has a massive effect on translation – Causes a different protein conformation

20. Evolution of Genes: Crossover (Recombination) DNA sections are swapped – From male and female genetic input to offspring DNA

21. Bioinformatics Application #1 Phylogenetic trees Understand our evolution Genes are homologous – If they share a common ancestor By looking at DNA seqs – For particular genes – See who evolved from who Example: – Mammoth most related to African or Indian Elephants? LUCA: – Last Universal Common Ancestor – Roughly 4 billion years ago

22. Genetic Disorders Disorders have fuelled much genetics research – Remember that genes have evolved to function Not to malfunction Different types of genetic problems Downs syndrome: three chromosome 21s Cystic fibrosis: – Single base-pair mutation disables a protein – Restricts the flow of ions into certain lung cells – Lung is less able to expel fluids

23. Bioinformatics Application #2 Predicting Protein Structure Proteins fold to set up an active site – Small, but highly effective (sub)structure – Active site(s) determine the activity of the protein Remember that translation is a function – Always same structure given same set of codons – Is there a set of rules governing how proteins fold? – No one has found one yet – “Holy Grail” of bioinformatics

24. Protein Structure Knowledge Both protein sequence and structure – Are being determined at an exponential rate 1.3+ Million protein sequences known – Found with projects like Human Genome Project 20,000+ protein structures known – Found using techniques like X-ray crystallography Takes between 1 month and 3 years – To determine the structure of a protein – Process is getting quicker

25. Sequence versus Structure 00959085 0 100000 200000 300000 400000 500000 Year Number Protein sequence Protein structure

26. Database Approaches Slow(er) rate of finding protein structure – Still a good idea to pursue the Holy Grail Structure is much more conservative than sequence – 1.3m genes, but only 2,000 – 10,000 different conformations First approach to sequence prediction: – Store [sequence,structure] pairs in a database – Find ways to score similarity of residue sequences – Given a new sequence, find closest matches A good match will possibly mean similar protein shape E.g., sequence identity > 35% will give a good match – Rest of the first half of the course about these issues

27. Potential (Big) Payoffs of Protein Structure Prediction Protein function prediction – Protein interactions and docking Rational drug design – Inhibit or stimulate protein activity with a drug Systems biology – Putting it all together: “E-cell” and “E-organism” – In-silico modelling of biological entities and process

28. Further Reading Human Genome Project at Sanger Centre – http://www.sanger.ac.uk/HGP/ Talking glossary of genetic terms – http://www.genome.gov/glossary.cfm Primer on molecular genetics – http://www.ornl.gov/TechResources/Human_Genome/publicat/primer/toc.html http://www.ornl.gov/TechResources/Human_Genome/publicat/primer/toc.html