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1.DNA and Gene Expression

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 synthesis of proteins for body

Results in two complete double helixes of DNA

How nucleotides are added in DNA replication (animation)

Maybe 30,000 genes on human genome

Gene range from 1000 to 2 million base pairs

20 amino acids, despite 64 possible combinations from 4 base pairs; duplication

Codons

Various sequences of three base pairs

Each codes for an amino acid (or stop signal)

Amino acids assembled into proteins

Interestingly, only about 2% of genome involved in protein synthesis

Mistakes made in copying DNA

Produces different alleles (called polymorphisms)

Mutations occurring in gametes will be transmitted faithfully unless natural selection intervenes

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, as it shifts the reading of the triplet code

C G A-CTA-TGA --> CAC-TAT-GA

Alanine-aspartic acid-threonine --> valine-isoleucine

Changing amino acid

No, small, or large effect on protein production

Some genes can have multiple mutations at different locations

Complicates matters enormously

Both in terms of functionality and for identification of effects by behavioural geneticists

Ribonucleic acid

Differs from DNA

Single-stranded molecule (generally) and is shorter

Contains ribose, not deoxyribose, making RNA less stable

Complementary nucleotide to adenine is not thymine (as in DNA), but uracil (U)

Various forms: mRNA, tRNA, rRNA, non-coding RNA

Actually, the original genetic code

Still seen in most viruses

But single strand vulnerable to predatory enzymes; double stranded DNA gained selective advantage

RNA degrades quickly, is tissue-, age-, and state-specific

Transcription of gene

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 in cell cytoplasm

mRNA and tRNA

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

Transcription animation

Translation video

Most DNA transcribed into RNA that is not mRNA, so is called non-coding RNA

At least 50% of human genome is responsible for non-coding RNA

Much of this is involved in directly or indirectly regulating protein-coding genes

One type of non-coding RNA

DNA sequencers embedded in protein-coding genes

Transcribed into RNA, but spliced out before RNA leaves nucleus

From 50 to 20,000 base pairs long

About 25% of human genome

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

Whats left (and spliced back together) after introns are removed

Usually only a few hundred base pairs long

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, and thus silence, mRNA

About 500 microRNA identified which regulate expression of over 30% of all coding mRNA

Can be 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

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

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

Gene chips

Surfaces the size of a postage stamp

Hundreds of thousands of DNA sequences

Serve as probes to detect gene expression or single-nucleotide polymorphisms

Fodor's gene chip

Test to identify individuals with a phenotype of interest

Forward genetic screens

Find the genetic basis of a phenotype or trait

Reverse genetic screens

Identify mutant alleles in genes that are already known

Find the possible phenotypes that may derive from specific DNA sequences

Traditionally, with non-humans, expose individuals to mutagens to cause mutations, thereby increasing the 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

A weak effect might be a damaged or abnormal limb, organ, behaviour trait

A strong effect might be the total absence of said limb, organ, behaviour

Map mutants by locating a gene on its chromosome through crossbreeding studies

Statistics on frequency of traits that co-occur are utilized

Now, SNPs (single nucleotide polymorphisms) are used for mapping

Find the effect of a gene sequence on phenotype

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

Gene knockouts

Used in yeast and mice

Individuals engineered to carry genes made inoperative (knocked out)

Gene silencing (gene knockdown)

Uses double stranded RNA to temporarily disrupt gene expression

Produces specific knockout effect without mutating the DNA of interest

Transgenic organisms

Over express normal gene, for example

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

AAGC C TA to AAGC T TA

Two alleles here: C and T

Almost all common SNPs have only two alleles

For a variation to be called an SNP it must occur in at least 1% of the population

SNPs wont necessarily change the amino acid sequence of a protein

Duplicatory nature of codons, might get same amino acid, but have different SNP allele

Synonymous SNPs

Both forms produce same polypeptide sequence

Silent mutation

Non-synonymous SNPs

Different polypeptide sequences are produced

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

SNP in coding region with subtle/harmless protein change

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

SNP in coding region with harmful 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

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

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.

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

Different SNPs may express hyperactive or lazy activator (or something in between)

The carcinogen-making protein

E.g., Hyperactive ones could 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 is caused

Different SNPs could alter individuals risk of lung 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

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

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

Could be applied to why individuals with behaviourally similar forms of schizophrenia can react very differently to the same drug therapy

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

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

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

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

Gene from pangenesis (Darwins mechanism of heredity)

Greek:genesis(birth) orgenos(origin)

First coined by Wilhelm Johannsen in 1909

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

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

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)

In 1950s: International Commission on Enzymes Classification, Munich Information Center for Protein Sequences

One gene, one protein, one function

Straightforward view of subcellular life

Allows conception of single protein as indivisible unit in larger cellular network

When mapping genes across species, can assume a protein is either fully preserved in organisms or entirely absent

Allows easy grouping of related proteins in different species

Extended dogma includes regulation, function, and conservation

High-throughput experiments

Probe activity of millions of bases in genome simultaneously

Much more complex than extended dogma

Genes only small fraction of human genome

Genome pervasively transcribed ( ENCODE Project , 2007)

Non-genic (i.e., genome outside known gene boundaries) transcription very widespread (even including pseudogenes)

Function of non-gene transcribed material as yet unclear

DNA sequences that look similar to functional genes, but contain genetic lesions (e.g., truncations, premature stop codons), disrupting ability to encode proteins or structural RNA

Long considered fossils of past genes

However, recent work estimates that 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

Long understood that eukaryote genes composed of short exons, coding regions of DNA separated by long introns

Introns transcribed to RNA that is spliced out before proteins produced

But, now known that 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 is many variants of a single gene

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, even beyond adjacent genes

Looping and folding of DNA can bring distant spans into close proximity

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

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

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

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