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Introduction to Bioinformatics 2. Genetics Background Course 341 Department of Computing Imperial College, London © Simon Colton Coursework 1 coursework – worth 20 marks – Work in pairs Retrieving information from a database Using Perl to manipulate that information The Robot Scientist Performs experiments Learns from results – Using machine learning Plans more experiments Saves time and money Team member: – Stephen Muggleton 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 Substructure and Effect (Top Down/Bottom Up) Species Organism Cell Affects the Behaviour of Affects the Function of Nucleus Protein Chromosome Amino Acid DNA strand Gene Base Prescribes Folds into Cells Basic unit of life Different types of cell: – – Cells produced by cells – – Skin, brain, red/white blood Different biological function Cell division (mitosis) 2 daughter cells Eukaryotic cells – Have a nucleus Nucleus and Chromosomes Each cell has nucleus Rod-shaped particles inside – – Different number for species – – – Are chromosomes Which we think of in pairs Human(46),tobacco(48) Goldfish(94),chimp(48) Usually paired up X & Y Chromosomes – – Humans: Male(xy), Female(xx) Birds: Male(xx), Female(xy) 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 DNA Structure Double Helix (Crick & Watson) – – Nitrogenous Base Pairs – – – – – 2 coiled matching strands Backbone of sugar phosphate 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 Differences in DNA DNA differentiates: – – We share DNA with – – Species/race/gender Individuals Primates,mammals Fish, plants, bacteria Genotype – DNA of an individual Genetic constitution Phenotype – Characteristics of the resulting organism Nature and nurture Genes Chunks of DNA sequence – – Large percentage of human genome – Is “junk”: does not code for proteins “Simpler” organisms such as bacteria – – Between 600 and 1200 bases long 32,000 human genes, 100,000 genes in tulips 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 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? 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 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 A=Ala=Alanine Genetic Code 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 Example Synthesis TCGGTGAATCTGTTTGAT Transcribed to: AGCCACUUAGACAAACUA Translated to: SHLDKL Proteins DNA codes for – Amino acids strings – – – – Fold up into complex 3d molecule 3d structures:conformations Between 200 & 400 “residues” Folds are proteins Residue sequences – strings of amino acids Always fold to same conformation Proteins play a part – In almost every biological process Evolution of Genes: Inheritance Evolution of species – But actually, it is the genotype which evolves – – Caused by reproduction and survival of the fittest 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 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 Evolution of Genes: Crossover (Recombination) DNA sections are swapped – From male and female genetic input to offspring DNA Bioinformatics Application #1 Phylogenetic trees Understand our evolution Genes are homologous – By looking at DNA seqs – – If they share a common ancestor 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 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 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 Protein Structure Knowledge Both protein sequence and structure – 1.3+ Million protein sequences known – Found with projects like Human Genome Project 20,000+ protein structures known – Are being determined at an exponential rate 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 Sequence versus Structure 500000 Protein sequence Number 400000 300000 200000 100000 Protein structure 0 85 90 95 Year 00 Database Approaches Slow(er) rate of finding protein structure – Structure is much more conservative than sequence – Still a good idea to pursue the Holy Grail 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 Potential (Big) Payoffs of Protein Structure Prediction Protein function prediction – Rational drug design – Protein interactions and docking 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 Further Reading Human Genome Project at Sanger Centre – Talking glossary of genetic terms – http://www.sanger.ac.uk/HGP/ http://www.genome.gov/glossary.cfm Primer on molecular genetics – http://www.ornl.gov/TechResources/Human_Genome/publicat/primer/toc.html