DNA%20and%20Gene%20Expression

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DNA and Gene Expression
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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

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DNA Structure
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DNA Replication

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

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Genome

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

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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

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Genetic Code
Amino Acid Codons 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 Phenylalanin
e 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
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Mutations

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

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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 --gt CAC-TAT-GA
• Alanine - aspartic acid - threonine --gt valine -
  isoleucine
• Changing amino acid
• No, small, or large effect on protein production

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Multi-base Mutations

• Some genes can have multiple mutations at
  different locations
• Complicates matters enormously for functionality
  and identification of effects by behavioural
  geneticists

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RNA

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

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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

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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

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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

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Transcription

• Transcription animation

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Translation

• Translation video

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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

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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

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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

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Exons

• Whats left (and spliced back together) after
  introns are removed
• Usually only a few hundred base pairs long

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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

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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

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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

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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

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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

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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

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Classic Approach

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

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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

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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

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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

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Amino Acid Sequence

• SNPs wont 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

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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

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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

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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

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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

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SNPs and Cancer

• SNP changes to genes for proteins regulating rate
  of absorbing, binding, metabolizing, excreting
  precarcinogens or carcinogens
• Small changes can alter an individuals 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.

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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

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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

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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

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Polygenetic Effect

• SNPs dont 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

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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

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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

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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

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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

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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

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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?

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What is a Gene?

• Gene from pangenesis (Darwins mechanism of
  heredity)
• Greek genesis (birth) or genos (origin)
• First coined by Wilhelm Johannsen in 1909

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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

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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-facto
  r binding sites on nearby DNA

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Simplified Extended Dogma
From Seringhaus Gerstein, 2008
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Implications

• Nomenclature
• Gene named and classified by basic function
• Traditional classification systems
• Vertically hierarchical
• Broad functional categories (e.g., genes whose
  products catalyze a hydrolysis reaction) to
  specific functions (e.g., amylase describing
  specific break-down of starch)
• 1950s International Commission on Enzymes
  Classification, Munich Information Center for
  Protein Sequences

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• One gene, one protein, one function
• Straightforward view of subcellular life
• Allowed conception of single protein as
  indivisible unit in larger cellular network
• When mapping genes across species, could assume a
  protein is either fully preserved in organisms or
  entirely absent
• Allowed easy grouping of related proteins in
  different species
• Extended dogma includes regulation, function, and
  conservation

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Current View

• High-throughput experiments
• Probe activity of millions of bases in genome
  simultaneously
• Much more complex than extended dogma

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Creating RNA Transcript

• Genes only small fraction of human genome
• Genome pervasively transcribed (ENCODE Project)
• Non-genic (i.e., genome outside known gene
  boundaries) transcription very widespread (even
  including pseudogenes)
• Function of non-gene transcribed material as yet
  unclear

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Pseudogenes

• DNA sequences
• Similar to functional genes, but contain genetic
  lesions (e.g., truncations, premature stop
  codons) disrupts ability to encode proteins or
  structural RNA
• Long considered fossils of past genes
• Recent estimates 5-20 of human pseudogenes can
  be transcriptionally active (Zheng Gerstein,
  2007)
• Might achieve functionality via fusing with
  mRNAs from nearby functional genes to form
  chimeric RNAs, having RNA transcript that has
  regulatory role, combining with new DNA to
  generate a new gene

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Introns/Exons

• Long understood that eukaryote genes composed of
  short exons separated by long introns
• Introns transcribed to RNA that is spliced out
  before proteins produced
• Now know splicing for a gene-containing locus can
  be done in multiple ways
• Individual exons left out of final product
• Only portions of the sequence in an exon are
  preserved
• Sequences from outside gene can be spliced in
• Result many variants of a single gene

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Example of Current View
From Seringhaus Gerstein, 2008
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Gene Regulation

• Traditional view
• Protein-coding portion of gene and regulatory
  sequence in close proximity on chromosome
• Doesnt apply well to mammalian and other higher
  eukaryote systems
• Gene activity influenced by epigenetic
  modifications (changes to DNA itself or to
  support structures of DNA)
• Genes can be regulated over 50,000 base pairs
  away, beyond adjacent genes
• Looping and folding of DNA brings distant spans
  into close proximity

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DNA Folding
From Seringhaus Gerstein, 2008
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Implications

• Defining gene functionality much more difficult
  now
• Traditionally done by phenotypic effect
• Doesnt capture function on molecular level,
  though
• Also, pathways a gene product engages in within a
  cell significant for understanding functionality

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Classification

• Non-trivial problem in deciding which qualities
  of a gene and its products to use
• Earlier approaches assumed simple hierarchical
  scheme
• No longer so simple
• Recent computer technologies offering solutions

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Direct Acyclic Graphs (DAGs)
Simple hierarchy
DAG hierarchy
In simple hierarchy a gene has only one parent
for each node. In the DAG approach each node can
have multiple parents. Genes can be classified
within multiple groups.
From Seringhaus Gerstein, 2008
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Naming

• Cross-species gene identification difficult
• Naming inconsistent
• Often, traditionally, have different names for
  functionally similar (or same) gene in different
  species
• Recent increases in computing power and genome
  sequencing making homology mapping of similar
  genes across species feasible

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Example Notch Pathway

• Highly conserved among species
• Defective Notch encodes receptor protein in fruit
  flies that produces notched wing shape
• Traditional views of Notch pathway quite limited
• High throughput experiments in humans identifying
  many more proteins involved in pathway
• Hypertext software now makes identifying
  connections easier

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Notch Pathway
Traditional
Current
From Seringhaus Gerstein, 2008