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DNA and Gene Expression

DNA and Gene Expression. Dexoyribonucleic Acid (DNA). Two phosphoric acid sugar strands held apart by pairs of four bases Adenine (A), thymine (T), guanine (G), cytosine (C) A pairs with T, G pairs with C Self replicating molecule Directs protein synthesis. DNA Structure.

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DNA and Gene Expression

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  1. DNA and Gene Expression

  2. Dexoyribonucleic Acid (DNA) • Two phosphoric acid sugar strands held apart by pairs of four bases • Adenine (A), thymine (T), guanine (G), cytosine (C) • A pairs with T, G pairs with C • Self replicating molecule • Directs protein synthesis

  3. DNA Structure <static.howstuffworks.com/gif/dna-2.jpg> <static.howstuffworks.com/gif/dna-base-pairings.gif>

  4. DNA Replication • Results in two complete double helixes of DNA • How nucleotides are added in DNA replication (animation)

  5. Genome • Maybe 30,000 genes on human genome • Gene range from 1000 to 2 million base pairs

  6. Protein Synthesis • 20 amino acids, despite 64 possible combinations from 4 base pairs; duplication • Codons • Sequences of three base pairs • Each codes for an amino acid (or “stop” signal) • Amino acids assembled into proteins • Only about 2% of genome involved in protein synthesis

  7. Genetic Code Amino AcidCodons Alanine CGA, CGG, CGT, CGC Arginine GCA, GCG, GCT, GCC, TCT, TCC Aaparagine TTA, TTG Aspartic acid CTA, CTG Cysteine ACA, ACG Glutamic acid CTT, CTC Glutamine GTT, GTC Glycine CCA, CCG, CCT, CCC Histidine GTA, GTG Isoleucine TAA, TAG, TAT Leucine ATT, AAC, GAA, GAG, GAT, GAC Lysine TTT, TTC Methionine TAC Phenylalanine AAA, AAG Proline GGA, GGG, GGT, GGC Serine AGA, AGG, AGT, AGC, TAC, TCG Threonine TGA, TGG, TGT, TGC Tryptophan ACC Tyrosine ATA, ATG Valine CAA, CAG, CAT, CAC (Stop signals) ATT, ATC, ACT

  8. Mutations • Mistakes made in copying DNA • Produces different alleles (called polymorphisms) • Mutations in gametes are transmitted faithfully unless natural selection intervenes

  9. Single-Base Mutations • Can either change or remove a base from a codon • Changing one base for another • Generally less likely to have an affect • Removal of base • More problematic; shifts the reading of the triplet code • CGA-CTA-TGA --> CAC-TAT-GA… • Alanine - aspartic acid - threonine --> valine - isoleucine… • Changing amino acid • No, small, or large effect on protein production

  10. Multi-base Mutations • Some genes can have multiple mutations at different locations • Complicates matters enormously for functionality and identification of effects by behavioural geneticists

  11. RNA • Ribonucleic acid • Differs from DNA • Single-stranded molecule (generally); shorter • Ribose, not deoxyribose; RNA is less stable • Adenine’s complementary nucleotide is uracil (U), not thymine • Various forms: mRNA, tRNA, rRNA, non-coding RNA

  12. RNA • The original genetic code • Still seen in most viruses • Single strand vulnerable to predatory enzymes; double stranded DNA gained selective advantage • RNA degrades quickly, is tissue-, age-, and state-specific

  13. Gene Expression • Transcription • Production of mRNA in nucleus from DNA template • Translation • Assembly of amino acids into peptide chains on basis of information encoded in mRNA • Occurs in ribosomes • mRNA and tRNA

  14. mRNA • mRNA exists only for a few minutes • Amount of protein produced depends on amount of mRNA available for translation • Protein production regulation • mRNA carries information about a protein sequence to the ribosomes • About 100 amino acids added to protein per second • Proteins 100-1000 amino acids long

  15. Transcription • Transcription animation

  16. Translation • Translation video

  17. Non-Coding RNA • Most DNA transcribed into RNA that is not mRNA: non-coding RNA • At least 50% of human genome is responsible for non-coding RNA • Mostly involved in directly or indirectly regulating protein-coding genes

  18. Introns • DNA sequencers embedded in protein-coding genes • Transcribed into RNA, but spliced out before RNA leaves nucleus; non-coding • From 50 to 20,000 base pairs long • About 25% of human genome

  19. Introns • Used to be called “junk” DNA • Not the case at all • Introns can regulate transcription of genes in which they reside • In some cases can also regulate other genes

  20. Exons • What’s left (and spliced back together) after introns are removed • Usually only a few hundred base pairs long

  21. MicroRNA • Another class of non-coding RNA • Usually only 21 base pairs long • DNA coding for them is about 80 base pairs • Especially important for regulation of genes involved in primate nervous system • Bind to (i.e., “silences”) mRNA • About 500 microRNA identified; regulate expression of over 30% of all coding mRNA

  22. Gene Regulation • Short-term or long-term • Responsive to both environmental factors and expression of other genes • i.e., genes can turn each other on and off

  23. Polymorphisms • Genome is about 3 billion base pairs • Millions of base pairs differ among individuals • However, about 2 million base pairs differ among at least 1 percent of the population • These are the DNA polymorphisms useful for behavioural geneticists

  24. Detecting Polymorphisms • Genetic markers • Traditionally, single genes were identified by their phenotypic protein outcome • DNA markers • Based on the actual polymorphisms in the DNA • Millions of DNA base sequences are polymorphic and can be used in genome-wide DNA studies • Identify single-gene disorders

  25. DNA Microarrays • Gene chips • Surfaces the size of a postage stamp • Hundreds of thousands of DNA sequences • Serve as probes to detect gene expression or single base mutations • Fodor's gene chip <http://learn.genetics.utah.edu /units/biotech/microarray/> <http://www.bio.davidson.edu/ Courses/genomics/chip/chipreal.html>

  26. Genetic Screens • Expose non-humans to mutagens to cause mutations, increases frequency of unusual alleles • Basic screens look for a phenotype of interest in the mutated population • Enhancer/suppressor screens used when an allele of a gene leads to a weak mutant phenotype • E.g., weak effect: damaged or abnormal limb, organ, behaviour trait • E.g., strong effect: total absence of limb, organ, behaviour

  27. Classic Approach • Map mutants by locating a gene on its chromosome through crossbreeding studies • Statistics on frequency of traits that co-occur are utilized

  28. More Recently • Produce disruption in DNA, then look for effect on whole organism • Random or directed deletions, insertions, and point mutations produce a mutagenized population • Screen population for specific change at the gene of interest

  29. Directed Deletions and Point Mutations • Gene knockouts • Individuals engineered to carry genes made inoperative (“knocked out”) • Gene silencing (“gene knockdown”) • Uses double stranded RNA to temporarily disrupt gene expression • Produces specific effect without mutating the DNA of interest • Transgenic organisms • E.g., over express normal gene

  30. Single Nucleotide Polymorphisms • SNPs • A variation in DNA sequence when a single nucleotide (A, T, C, G) in the genome differs between individuals or between paired chromosomes of an individual • AAGCCTA to AAGCTTA • Two alleles here: C and T • Almost all common SNPs have only two alleles • For a variation to be called a SNP it must occur in at least 1% of the population

  31. Amino Acid Sequence • SNPs won’t necessarily change the amino acid sequence of a protein • Duplication of codons • Synonymous SNPs • Both forms produce same polypeptide sequence • “Silent mutation” • Non-synonymous SNPs • Different polypeptide sequences are produced

  32. Coding Regions • SNPs can exist in both protein coding and non-coding regions of genome • Even non-protein coding region SNPs can have effects • Gene splicing • Transcription factor binding • Sequencing of non-coding RNA

  33. Example • SNP in coding region with subtle effect • Change the GAU codon to GAG • Changes amino acid from aspartic acid to glutamic acid • Similar chemical properties, but glutamic acid is a bit bigger • This change to a protein is unlikely to be crucial to its function

  34. Example • SNP in coding region with large effect • Sickle-cell anemia • Changes one nucleotide base in coding region of hemoglobin beta gene • Glutamic acid replaced by valine • Hemoglobin molecule no longer carrying oxygen as efficiently due to drastic change in protein shape

  35. Latent Effects • SNP in coding region only switching gene on under certain conditions • Under normal conditions, gene is switched off (is latent) • Can activate under specific environmental conditions • E.g., exposure to precarcinogens or carcinogens

  36. SNPs and Cancer • SNP changes to genes for proteins regulating rate of absorbing, binding, metabolizing, excreting precarcinogens or carcinogens • Small changes can alter an individual’s risk for cancer • SNP does no harm itself under normal circumstances, only having an effect when person is exposed to a particular environmental agent • E.g., Two people with different SNPs could both smoke, but only one develops cancer, responds to therapy, etc.

  37. Smoking and Susceptibility • Precarcinogens from tobacco enter lungs • Lodge in fat-soluable areas of cells • Bind to proteins converting precarcinogens to carcinogens • Reactive molecules quickly eliminated • Detoxifying proteins make carcinogens water-soluable • Excreted in urine before (hopefully) damaging cell

  38. SNP Variability • Different SNPs may express hyperactive or lazy activator (or something in between) • The carcinogen-making protein • E.g., Hyperactive: “grab” and convert more precarcinogens than usual or do it more rapidly • E.g., Influence effectiveness of detoxifying enzymes • If more carcinogens build up in lungs, more damage to cells’ DNA • Different SNPs could alter individuals’ risk of lung cancer

  39. Bladder Cancer • Workers in dye industry exposed to arylamines • Have increased risk of bladder cancer • SNPs may be involved • In liver, an acetylator enzymes acts on arylamines, deactivating them for excretion • SNPs produce several different slow forms of acetylator enzyme, keeping arylamines in liver for longer • More are converted to precarcinogens, increasing risk for cancer

  40. Polygenetic Effect • SNPs don’t entirely explain this • Not all individuals with slow acetylators exposed to arylamines are at increased risk of bladder cancer • About half of North American population has slow acetylators • Only 1 in 500 develop bladder cancer • Other yet undiscovered genes and proteins involved

  41. Drug Therapies • SNPs could also explain different patient reactions to the same drug treatment • Many proteins interact with a drug • Transportation through body, absorption into tissues, metabolism into more active or toxic by-products, excretion • Having SNPs in one or more of the proteins involved may alter the time the body is exposed to the active form of the drug • E.g., individuals with behaviourally similar forms of schizophrenia can react very differently to the same drug therapy

  42. SNPs and Gene Mapping • SNPs are very common variations throughout the genome • Relatively easy to measure • Very stable across generations • Useful as gene markers • Contribute to understanding of complex gene interactions in behaviours and behavioural disorders

  43. By Association • If SNP located close to gene of interest • If gene passed from parent to child, SNP is likely passed too • Can infer that when same SNP found in a group of individuals’ genomes that associated gene is also present

  44. Sequencing SNPs • Sequence the genome of large numbers of people • Compare base sequences to discover SNPs • Goal is to generate a single map of human genome containing all possible SNPs

  45. SNP Profile • Each individual has his or her own pattern of SNPs • “SNP profile” • By studying SNP profiles in populations correlations will emerge between specific SNP profiles and specific behaviour traits • E.g., specific responses to cancer treatments

  46. Sidebar • If you could have your genome scanned, would you want to know your genetic predispositions? • What if you were predisposed to an incurable disorder? • Complex interactions. Cognitive dissonance. • Probabilities and risk factors. Are people inherently good at these? • Support systems?

  47. What is a Gene? • “Gene” from “pangenesis” (Darwin’s mechanism of heredity) • Greek: genesis (“birth”) or genos (“origin”) • First coined by Wilhelm Johannsen in 1909

  48. Central Dogma • One gene, one protein • Information travels from DNA through RNA to protein • Gene = DNA region expressed as mRNA, then translated into polypeptide • View held through 1960s

  49. Extended Dogma • Transcribed mRNA produces single polypeptide chain (folds into functional protein) • This molecule performs discrete, discernible cellular function • Gene regulated by promoter and transcription-factor binding sites on nearby DNA

  50. Simplified Extended Dogma From: Seringhaus & Gerstein, 2008

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