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Population Genomics Friend or Foe? Tim Shank 4/2/03 [email protected] Woods Hole Oceanographic Institution. Genome Projects. Microbial Genomics. Genome- Genome Interactions. Comparative Genomics. Population Genomics. Genomics Projects. Microbial Genomics. Functional Genomics.

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slide1

Population Genomics

Friend or Foe?

Tim Shank

4/2/03

[email protected]

Woods Hole Oceanographic Institution

slide4

Genome

Projects

Microbial

Genomics

Genome-

Genome

Interactions

Comparative

Genomics

population genomics a view

Population

Genomics

Genomics

Projects

Microbial

Genomics

Functional

Genomics

Pharmaco

genomics

Population Genomics- A View
slide6

Population Genomics- definitions

The study of forces that determine patterns of DNA

variations in populations (Michel Veuille, European Consortium)

Field of genomics that links complex genotypes and phenotypes

by comparing the flow of genotypic and phenotypic information

in breeding and natural populations (Andrew Benson, U. Neb)

Genomic variation within species permitting the construction of

detailed linkage maps using polymorphic markers, and through

crossing experiments between individuals with different

phenotypes, identification of genes responsible for phenotypic

variation (e.g, disease susceptibility, drug toxicity) (Andrew Clark, PSU)

questions in marine population genetics

How do marine larvae disperse between localities that may be isolated?

  • Do topographic and hydrographic features like transform faults and currents disrupt or facilitate gene flow between demes?
  • What role do larval retention and stepping stone habitats play in species maintenance?
  • Does the pattern of colonization and mode of dispersal affect the retention of genetic diversity in marine animals?
Questions in Marine Population Genetics
  • Characterization of genetic relationships of populations important for understanding:
  • • Genetic management of protected or threatened populations (e.g. Jones et al. 2002)
      • Historical migrations and connectivity of populations (e.g. Eizirik et al. 2001)
  • • Kin selection and social behavior (e.g. Morin et al. 1994)
  • • Mating systems (e.g. Engh et al. 2002)
  • • Dispersal, temporal and spatial genetic structure (e.g. Goodisman & Crozier 2001)
dispersal models
Dispersal models
  • Continuous populations
    • Isolation-by-distance
  • Discrete populations
    • Stepping-stone
    • Island model
f st approaches

FST

Nm

FST -approaches

Wright (1951) [The genetical structure of populations. Ann. Eugen. 15:323-354.] noted the following relationship holds when populations reach an equilibrium between genetic drift

and migration:

where N is the variance effective population size of the

average population, and

m is the average proportion of immigrants in each

population

Problem: Useful parameter space is for FST values

between 0.1 and 0.4

Nm is a virtual number

slide10

20

10

5

100

1000

10,000

DISTANCE (Km)

The giant tubeworm, Riftia pachyptila

Guaymas

21°

13

°

11

°

2

°

East Pacific Rise

9

°

Fst. Migration rate

Galapagos

Rift

N

W

E

S

Reject expectations of "island model"

Consistent with stepping-stone model

Inference: a species with more limited dispersal abilities

Black et al. 1994 Gene flow among vestimentiferan tube worm

(Riftia pachyptila) populations from hydrothermal vents of the Eastern Pacific. Marine Biology 120: 33-39.

molecular toolkit markers for inferring population structure and gene flow
Molecular Toolkit: markers for inferring population structure and gene flow
  • Allozymes
    • multiple, independent, codominant loci; relatively easy; low cost
    • need to freeze samples; state characters
  • RFLPs
    • variation in restriction fragment lengths
    • polymorphic due to restriction site mutation
  • mtDNA
    • relatively easy; maternally inherited; effectively haploid; non-recombining; modest cost; amenable to genealogical analysis
    • linked loci and psuedoreplication
  • nuclear DNA sequences
    • amenable to genealogical analysis
    • diploid; recombination; start-up time may be considerable
  • AFLPs
    • can get 100s of loci relatively easily
    • dominance; recombination; state characters; mutation models not available
  • minisatellites
    • repeats of 10-40 bp units
    • polymorphic due to unequal crossing over
molecular toolkit markers for inferring population structure and gene flow12
Molecular Toolkit: markers for inferring population structure and gene flow
  • DNA microsatellites
    • Repeat unit 2-3 bp; nuclear; can get dozens of loci relatively easily; method of choice for parentage
    • recombination; state characters; start-up time is great; issues of homoplasy in geographical studies; mutation must be taken into account in gene flow models
  • Single-Nucleotide Polymorphisms (SNPs)
    • Most simple form and most common source of genetic polymorphism in most genomes.
    • large amount of sequencing effort in nonmodel organisms
    • Violation of analyitcal assmumption of independence among marker loci
  • Sequence Tagged Sites (STSs) (physical marker)
    • A short DNA segment that occurs only once in the genome and whose exact location and order of bases are known. (They can be used as primers for PCR reaction).
    • Very labor intensive; very few loci
  • Expressed Sequence Tags (ESTs) (physical marker)
    • Short (100-300bps) part a cDNA which can be used to fish the rest of the gene out of the chromosome by matching base pairs with part of the gene.
    • large amount of sequencing effort
slide13

Molecular Markers:RandomAmplifiedPolymorphic DNA, AP-PCR

  • PCR-based method

Target Sequence

= arbitrary primer (e.g. ggcattactc)

  • High Variability: Probably due to mutations in priming sequences

Amplify regions between priming sites by polymerase chain reaction

Analyze PCR products by agarose gel electrophoresis.

Marker is dominant (presence/absence of band).

No prior sequence knowledge required

Many variations on the theme (e.g., RAMP, ISSR)

slide14

Amplified Fragment Length Polymorphism (AFLPs)

  • Polymorphism based on gain or loss of restriction site, or selective bases
  • Technically demanding and expensive
  • Many markers generated, mostly dominant
  • More reliable than RAPD, less so than SSR
  • No prior sequence knowledge required
s ingle s trand c onformational p olymorphism
Single-Strand Conformational Polymorphism

1. Amplify Target Sequence

  • Highly sensitive to DNA sequence: can detect single base changes
  • Simple process but can be difficult to repeat

2. Denature product with heat and formamide

3. Analyze on native (nondenaturing) polyacrylamide gel

4. Base sequence determines 3-dimensional conformation

d enaturing g radient g el e lectrophoresis
Denaturing Gradient Gel Electrophoresis

1. Amplify Target Sequence

4. Denaturing gradient gels can be difficult to produce: use perpendicular gradient to identify optimal conditions, move to CDGE: constant denaturant gel electrophoresis

2. Run product on gel with denaturing gradient (parallel or perpendicular to direction gel runs)

3. Product begins denaturing at a certain point, depending on base sequence: greatly retards migration and allows discrimination of alleles based on small sequence differences

c leaved a mplified p olymorphic s equence caps
Cleaved Amplified Polymorphic Sequence (CAPS)

1. Amplify Target Sequence

  • Fairly simple analysis (cutting can be a hassle)
  • Requires sequence information from several alleles (or luck)

2. Cut with a restriction enzyme that differentiates alleles

X

Allele 1

Allele 2

3. Alleles can be differentiated by size based on loss or gain of restriction site; May be able to analyze on agarose gel

microsatellites
Microsatellites

“…reiterated short sequences [of DNA] tandemly arrayed, with variations in copy number accounting for a profusion of distinguishable alleles” - (Avise 1994)

Locations:

- Nuclear DNA

- Chloroplast

microsatellite types
Microsatellite Types
  • Dinucleotide
    • Animals - CA
    • Plants - TA, GA
  • Trinucleotide
      • GTG, CAG, and AAT
      • Related to disease and cancers
  • Tetranucleotide
      • GATA/GACA
      • Highly polymorphic
microsatellite uses
Microsatellite Uses
  • Population Genetics
      • Gene flow
      • Stock Structure
  • Genetic Probes
      • Larvae
      • Gut contents
      • Scat
      • Source populations
  • Pedigree Maps
  • Understanding Diseases
microsatellite advantages
Microsatellite Advantages
  • Highly Polymorphic
  • Codominant
  • In every organism examined to date
  • Very abundant
  • Random spacing in the genome
  • Can find same loci in closely related species
  • Easy and reliable scoring
  • Highly sensitive
  • Neutral markers
microsatellite disadvantages
Microsatellite Disadvantages
  • Expensive
  • Time consuming
  • Several loci are needed to obtain sufficient statistical power
  • Current analyses methods do not distinguish between changes in flanking regions vs. changes within the microsatellite regions
  • Different rates of evolution at different loci
mutation mechanisms
Mutation Mechanisms
  • Slippage in DNA at Replication (Slip-Strand Mispairing, SSM)
      • increases or decreases the repeat by one unit
      • most supporting evidence
  • Recombination
      • Unequal crossing over (UCO)
      • Gene conversion
microsatellite mutations
Microsatellite Mutations
  • 10-3 to 10-6 events per locus per generation (point mutation 10-9 to 10-10)
  • Varies by
    • repeat type
    • base composition of the repeat
    • taxonomic group
    • length of the allele
  • most common - addition or deletion of a single repeat
    • occasionally 2 to several repeats
  • strong evidence that the number of repeats is limited
mutation models
Mutation Models
  • Infinite Allele Model (IAM)
    • gain or loss of any number of repeats and always results in an allelic state not present in the population
  • Stepwise Mutation Model (SMM)
    • gain or loss of a single repeat
  • Two-Phase Model (TPM)
    • gain or loss of X repeats
  • K-allele Model (KAM)
    • Intermediate step in the IAM (IAM = KAM with infinite K)
    • K possible allelic states
creating a microsatellite enriched library

DNA Library

Genomic

DNA

DNA

Extraction

Digestion

Add

Linkers

Creating A Microsatellite-Enriched Library

PCR

enriching microsat library

Hybridize

to Beads

CACA

GTGT

PCR

Microsatellite-Enriched

DNA Library

Enriching Microsat Library
microsatellite library screening

Blots/

Hybridizations

Cloning

Plasmid

Preps

Enzyme

Digest

Isolated Plasmids

Microsatellite Library Screening

Check Insert Size

Dot Blot Hybridizations

references
References

www.biotech.ufl.edu/WorkshopsCourses/mm_manual.htm

Avise, J.C. 1994. Molecular Markers, Natural History and Evolution. Chapman and Hall, New York. 511 pp.

Balloux, F. and N. Lugon-Moulin. 2002. The estimate of population differentiation with microsatellite markers. Molecular Ecology. 11: 155-165.

Goldstein, D.B. and C. Schloterrer (Editors). 1999. Microsatellites: Evolution and Applications. Oxford University Press, Oxford, 352 pp.

Jarne, P and P.J.L. Lagoda. 1996. Microsatellites, from molecules to populations and back. Trends in Ecology and Evolution 11(10): 424-429.

Slatkin, M. 1995. A measure of population subdivision based on microsatellite allele frequencies. Genetics 139: 457-462.

slide33

Fluorescent Labeling of Microsatellites

  • Acrylamide gel with 5 microsatellite loci and internal size standard
  • Simultaneous analysis of a dozen loci
comparing genomic methods for population studies
Comparing “Genomic” Methods for Population Studies

* Depends on cost of restriction enzymes employed

slide35

All population genetic/genomic markers are vulnerable to

violations of assumptions- linkage equilibrium, mendelian inheritance, neutrality.

Linkage Disequilibrium- alleles at different loci are found together more or less

often than expected based on their frequencies (and location in the genome).

Goldstein and Weale 2001 Population genomics: linkage disequilibrium holds the key. Current Biology 11:576-579

population genomics research
Population Genomics Research
  • Understandings population structure, historical migrations, and gene flow among populations (e.g. SNP density distribution, coalescent approaches)
    • Need relatively moderate polymorphism, low cost per sample
    • mtDNA, Microsatellites, SNPs
  • Understanding current gene flow and mating systems by direct methods (e.g., maternity analysis, paternity analysis)
    • Need high polymorphism, codominance, repeatability, low cost per sample
    • Microsatellites, SNPs
  • Pharmacogenomics: polymorphism-based approaches for the discoveryand development of new medications; translating polymorphisms into “new genomic medicine”*
    • Need rapid, low-cost, repeatable way to distinguish alleles
    • screening large numbers of individuals; SNPs and Sequencing

*New York Times, Nov. 2002

slide38

Two main hypotheses for human evolution:

    • “Recent African origin” hypothesis- modern humans

originated in Africa 100 - 200k years ago, and spread

    • “Multi-regional” hypothesis- modern humans evolved in different parts of the world
  • MtDNA favored out of Africa hypothesis but lacked statistical support for deep African branches

Neighbor-joining phylogram based on complete

mtDNA genome sequences (excluding D-loop).

1000 bootstrap replicates shown on nodes.

Asterisk refers to the MRCA of the youngest clade

containing both African and non-African individuals.

  • 53 human mtDNA sequences (16,500 bp)
  • examined timing of evolutionary events
  • mtDNA evolving in a “clocklike” fashion
  • Linkage Disequilibrium not evident
  • 3 deepest branches lead exclusively to sub-Saharan
  • Note star-like vs deep branching topology- larger Ne

or longer genetic history in Africa; bottleneck in non-Affican

slide39

Exodus from Africa began 100 million years ago

Divergence of Africans and non-Africans occurred

52,000  28,000 years ago

mtDNA mismatch distributions for Africans and non-Africans

• Individuals of African origin show a ragged distribution

consistent with constant population size

• Individuals of non-African origin show a bell-shaped distribution

strongly suggests a recent population expansion

Mismatch distributions of pairwise nucleotide

differences between a) African and b) non-African

slide40

Human genome mining to produce 507,152 high-confidence SNP candidates

as uniform resource for describing nucleotide diversity and regional variation

within and between human populations

so what s a snp
So What’s a SNP?
  • A mutation that causes a single base change is known as a Single Nucleotide Polymorphism (SNP)
  • SNPs are the most simple form and most common source of genetic polymorphism in the human genome
    • 90% of all human DNA polymorphisms;1SNP in 1000 bp; 1.42 million
  • SNP Haplotype is a particular pattern of sequential SNPs (or alleles) found on a single chromosome
    • Microarrays, mass spectrometry and sequencing are all used to accomplish grouping or blocking of SNPs= haplotyping
  • Haplotype Determination Problem- find all haplotypes given a genome and all identified SNPs (algorithm development)
slide42

Approaches to SNP discovery and Genotyping

Many and numerous!

(Reviewed Pui-Yan Kwok Annu. Rev. Genomics Hum Genet. 2001. 2:235-258

SNP discovery can be based on expressed sequence tags (ESTs), genomic restriction fragments,

aligned BAC sequences, random shot gun clone sequences, overlapping genomic clone sequences

  • Parallel genotyping of SNPs using generic high-density oligonucleotide tag arrays
  • Fan et al. (2000) Genome Research 10:853-860. (see Stickney et al 2002 for zebrafish SNP arraying)
  • PCR + single base extension chimeric primers, allele specific (labeled) dideox NTPs and then
    • hybridized to arrays containing thousands of preselected 20-mer oligonucleotide tags
  • Polymorphism ratio sequencing: a new approach for SNP discovery and genotyping
  • Blazej et al. (2003) Genome Research 13:287-293.
  • Dideoxy-terminator extension ladders generated from a single sample and reference template are
    • labeled with fluorescent dyes and coinjected into a separation capillary for comparison of
    • relative signal intensities.
  • A novel method for SNP detection using a new duplex-specific nuclease from crab hepatopancreas
  • Shagin et al. (2002) Genome Research 12:1935-1942.
  • “Duplex Specific Nuclease Preference” - SNP region amplified, template, signal probe, and
    • matched duplexes are then cleaved by DSN to generate sequence-specific fluorescence
genbank has a dbsnp
GenBank has a dbSNP

One year ago: dbSNP had 2,842,021 SNP submissions total

Today, 2003, dbSNP has 6,250,820 submissions for human

1,368,805 submissions for mosquito

197,414 submissions for mouse

2,031 submissions for zebrafish

It is possible to search dbSNP by BLAST comparisons to a target sequence

slide44

The SNP Consortium is an alliance of pharmaceutical and computer companies managed by Lincoln Stein at Cold Spring Harbor Lab.

  • “The SNP Consortium Ltd.. is a non-profit foundation organized for
  • the purpose of providing public genomic data. Its mission is to develop up to 300,000 SNPs distributed evenly throughout the human genome and to make the information related to these SNPs available to the public without intellectual property restrictions. The project started in April 1999 and is anticipated to continue until the end of 2001.”
slide45

We describe a map of 1.42 million single nucleotide polymorphisms (SNPs) distributed throughout the human genome, providing an average density on available sequence of one SNP every 1.9 kilobases. These SNPs were primarily discovered by two projects: The SNP Consortium and the analysis of clone overlaps by the International Human Genome Sequencing Consortium. The map integrates all publicly available SNPs with described genes and other genomic features. We estimate that 60,000 SNPs fall within exon (coding and untranslated regions), and 85% of exons are within 5 kb of the nearest SNP. Nucleotide diversity varies greatly across the genome, in a manner broadly consistent with a standard population genetic model of human history. This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.

slide46

Looked for mismatches; SNPs

  • if Polybayes probability was 0.80
  • Built a set of pairwise sequence
  • alignments by analyzing the over-
  • lapping regions of large insert clones
  • SNP marker density grouped by
  • overlapping regions
  • Modeled the marker density
  • distribution
slide47

Marker density distributions predicted under

competing population genetic models

No demographic history

Poisson distribution driven by mutation rate

Distribution of polymorphic sites profoundly impacted

Increased pop size yields abundance of new lineages with more mutation

Decreased pop size raises likelihood of relatedness resulting in

over-representation of sequence identity

Collapse followed by a phase of recent population recovery

Evaluated degree of fit between observed density distribution and

probability predicted using the log likelihood of the data for a given model

r indicates the per nucleotide, per generation recombination rate

slide48

Superior fit of the modeled parameters (with or without recombination) suggests a

severe, 2- to 7 fold, collapse of population size 40,000 years (1600 generations) ago

….followed by a modest recovery

% of successful trials for each model, at each data fraction;

Assessments based on the amount of data required for rejection by X2 test.

Interestingly, data fit between observations and best-fitting models decays with more data.

slide49

History of the inbred laboratory mouse

  • Compared the C57BL/6J Mouse genome sequence with 59 finished segments of the 129/Sv inbred strain
  • Discovered nearly 70,000 SNPs on blocks of high SNP density (40 SNPs per 10kb)
  • separated by blocks of low density (0.5 SNPs per 10kb)
  • Surveyed panels of inbred mouse strains to find that distinct SNP haplotypes
  • were shared among common inbred populations.
  • Surveyed wild strains showed that 67% of each of the inbred genomes are derived from
  • European mice and 33% from Asian mice
slide50

How about other organisms? or new ‘model’ organisms;

organisms that exemplify phenomena not well studied in human/worm/mouse?

Three-Spined Sticklebacks

  • morphological evolution
  • populations isolated after last glaciation, have diverged morphologically and in sequence (CAn microsatellites)
  • strategy: cross benthic and limnetic fish; intercross F1s, follow morphological traits and polymorphisms in F2s
  • see Peichel et al (2001) The genetic architecture of divergence between threespine stickleback species. Nature 414: 901-5.
stickleback genetic map woods et al 2000
Stickleback genetic map(Woods et al. 2000)
  • 227 polymorphisms
  • 1 SNP marker per 4 cM
  • took ~4 person-years
  • now mapping genetic basis of morphological variations
slide52

First zebrafish SNP map

5 months ago

2102 SNPs for mutation mapping

Hundreds of SNPs on single array

Stickney et al. 2002 Rapid mapping of zebrafish mutations

with SNPs and oligonucleotide microarrays. Genome Res.

12: 1929-1934.

Vertical lines = 25 linkage groups

Red dots correspond to SNPs represented on the olig. microarray

Zebrafish

Genes

Postlehwait et al. 1994 A genetic linkage map for zebrafish. Science 264: 699-703.

Woods et al. 2000 A comparative map of zebrafish genome. Genome Research 10: 1903-1914.

Geisler et al. 1999 A radiation hybrid map of the zebrafish genome. Nature Genetics 23: 86-89.

Microsatellites

Shimoda et al. 1999 Zebrafish genetic map with 2000 microsatellite markers. Genomics 58: 219-232.

population genomics research53
Population Genomics Research
  • Understandings population structure, historical migrations, and gene flow among populations (e.g. SNP density distribution, coalescent approaches)
    • Need moderate polymorphism, low cost per sample
    • Allozymes, mtDNA, RAPDs, Microsatellites, AFLPs, RFLPs, SNPs
  • Understanding current gene flow and mating systems by direct methods (e.g., maternity analysis, paternity analysis)
    • Need high polymorphism, codominance, repeatability, low cost per sample
    • Microsatellites, SNPs
  • Pharmacogenomics: polymorphism-based approaches for the discovery and development of new medications; translating polymorphisms into “new genomic medicine”*
    • Need rapid, low-cost, repeatable way to distinguish alleles
    • screening large numbers of individuals; SNPs and Sequencing

*New York Times, Nov. 2002

slide54

Inferring Pairwise Relationships with SNPs (in Your Favorite Metazoan)

(Glaubitz, Rhodes, and Dewoody 2003 Molecular Ecology 12: 1039-1047)

Problem:

Need to determine genetic relationships in populations without known pedigrees

Goal:

To assess known pairwise relationships - via single nucleotide polymorphisms

where already have parallel microsatellite results.

Recent advances in microarray technology permit genotyping of large #s of individuals

at 100s to 1000s of SNP loci (reviewed by Kwok 2001)- this could be big!

Need to know if SNPs equal or exceed the power of practical numbers

of microsatellite loci in estimating relationships?

Microsatellites current methods of choice among close kin within a population,

but the number of independently segregating microsatellite markers is limited

SNPs may provide large number of segregating loci with

a large number of alleles at even frequencies

slide55

Constructed 5 catagories of relationships types

Glaubitz et al. 2003-

Computer simulations designed to evaluate SNPs ability

to discriminate a variety of (pairwise) relationships likely

to occur in natural populations, comparisons to

microsatellites from Blouin et al 1996

•SNPs segregate independently, ideal genome with 20

autosomes, 5 SNPs per chromosome, 10,000 individuals

random genotypes

Constructed an array of pedigrees

estimated pairwise relatedness at a single locus (r1)

Evaluated the performance of 100 simulated SNPs by

estimating misclassification (rate) of relationships

slide56

illustrates that different pairwise relationships can have different amounts of inherent variance in relatedness

  • the parent offspring (PO) and unrelated (U) relationships have 0 inherent variance (share one or no alleles)
  • FS has largest variance; second order relatives can not be distinguished from each other via estimation of r

100 independently segregating SNPs determinined parent-offspring pairs

as well as about 16 or fewer microsatellite loci when both parents are unknown

Even under the optimistic scenario of 100 independent loci, results show little promise for discriminating higher order relationships on the basis of pairwise relatedness.

Microsatellite approaches are still better…

slide57

My two cents:

Based on 1) assumption of independence among the sampled SNP loci

2) that the microsatellites themselves are independent (not linked)

Conclusion:

“SNPs have limited potential for the delineation of genealogical relationships…”

  • In the absence of a linkage map, the number of microsatellite or SNP loci scored must be
  • increased to compensate for the loss of information as a result of nonindependence
  • between markers
  • An alternative to using independently segregating SNPs is to use independently
  • segregating haplotypes, with each haplotype defined by a cluster of tightly linked
  • SNPs. (e.g., Heaton et al 2002 sequenced regions around 32 cattle SNPs; additional
  • 183 polymorphic sites; and more haplotypes for better resolution)
slide58

To take full advantage of the “vast” abundance of SNPs in metazoan genomes

and their potential automation, we will need analytical methods that account

for tight genetic linkage (McPeek and Sun 2000) and known recombination

frequencies….

until then, SNP population genomics will likely only be used on model organisms.

population genomics research59
Population Genomics Research
  • Understandings population structure, historic migrations, and gene flow among populations (e.g., Fst, coalescent approaches)
    • Need moderate polymorphism, low cost per sample
    • Allozymes, mtDNA, RAPDs, Microsatellites, AFLPs, RFLPs, SNPs
  • Understanding current gene flow and mating systems by direct methods (e.g., maternity analysis, paternity analysis)
    • Need high polymorphism, codominance, repeatability, low cost per sample
    • Microsatellites, allozymes
  • Pharmacogenomics: polymorphism-based approaches for the discovery and development of new medications; translating polymorphisms into “new genomic medicine”*
    • Need rapid, low-cost, repeatable way to distinguish alleles
    • screening large numbers of individuals; SNPs and Sequencing

*New York Times, Nov. 2002

pharmacogenomics
Pharmacogenomics
  • The use of DNA sequence information to measure and predict the reaction of individuals to drugs.
  • Pharmacogenetics is the study of this variation at the level of a single gene, while pharmacogenomics studies variation at the genome wide level.
  • Observation that there is great individual variation in response to drugs- genetically determined.
  • It is possible to measure many thousands of SNPs simultaneously in a small blood sample from a patient
  • Can compare “genotypes” for SNP markers linked to virtually any trait
slide62

Evolving Paradigm for Discovery of Genetic Polymorphisms

associated with aberrant drug disposition or effects

More discoveries thru polymorphisms

in candidate genes (metabolism; transport;

targets of candidate medication

Observed phenotype - family studies-

inherited basis

new drug targets expected from the human genome project
New Drug Targets Expected from the Human Genome Project

Number of Drug Targets

12,000

5,000–10,000

10,000

8,000

6,000

4,000

2,000

Approx. 500

0

Cumulative Number of Targets Known Today

New Targets Expected from Human Genome Project

Source: Drews J. Nat Biotechnol 1996;14.

disease genes discovered
Disease Genes Discovered
  • For 1100 genes at least one disease-related mutation has been identified
clinical disorders and gene mutations
Clinical disorders and gene mutations
  • Different mutations in the same gene can give rise to more or less distinct disorders, so total number of diseases for which there are known mutations is ~1500
functional classifications
Functional Classifications
  • Disease genes classed by function and their relative representations
some diseases involve polygenic effects
Some Diseases Involve Polygenic Effects
  • There are a number of classic “genetic diseases” caused by mutations of a single gene
        • Huntington’s, Cystic Fibrosis, Tay-Sachs, PKU, etc.
  • There are also many diseases that are the result of the interactions of many genes:
        • Asthma, Heart disease, Cancer
  • Each of these genes may be considered to be a risk factor for the disease.
  • Groups of SNP markers may be associated with a disease without determining mechanism
slide69

Gene Product- Drug Interaction

  • There are proteins that chemically activate or inactivate drugs.
  • Other proteins can directly enhance or block a drug\'s activity.
  • There are also genes that control side effects.
some examples
Some Examples
  • 10% of African Americans have polymorphic alleles of Glucose-6-phosphate dehydrogenase that lead to haemolyitic anemia when they are given the anti-malarial drug primaquine.
slide71

Succinylcholine Toxicity

  • 0.04% of individuals are homozygous for alleles of psedocholineseterase that are unable to inactivate the muscle relaxant drug succinylcholine, leading to respiratory paralysis.
slide72

Isoniazid Metablolism

  • There are many polymorphic alleles of the N-acetlytransferase (NAT2) gene with reduced (or acclerated) ability to inactivate the drug isoniazid.
    • Some individuals developed peripheral neuropathy in reaction to this drug
    • Some alleles of the NAT2 gene are also associated with succeptibility to various forms of cancer
cytochrome p450
Cytochrome P450
  • ~10% of the Caucasian population is homozygous for alleles of the Cytochrome P450 gene CYP2D6 that do not metabolize the hypertension drug debrisoquine, which can lead to dangerous vascular hypotension.
slide74
ACE
  • Patients homozygous for an allele with a deletion in intron 16 of the gene for angiotensin-converting enzyme (ACE) showed no benefit from the hypertension drug enalapril while other patients benefit.
slide75

Collect Drug Response Data

  • These drug response phenotypes are associated with a set of specific gene alleles.
  • Identify populations of people who show specific responses to a drug.
  • In early clinical trials, it is possible to identify people who react well and react poorly.
slide76

Make Genetic Profiles

  • Scan these populations with a large number of SNP markers.
  • Find markers linked to drug response phenotypes.
use the profiles
Use the Profiles
  • Genetic profiles of new patients can then be used to prescribe drugs more effectively & avoid adverse reactions.
  • Can also speed clinical trials by testing on those who are likely to respond well.
major pharmacogenetics approaches in post genomic era
Major pharmacogenetics approaches in post-genomic era
  • Identifying SNP variations in the genome and populations
  • Study of differential gene expression
    • Chips with mRNAs from different tissue types or normal and diseased tissue
    • Can detect expression of a target gene among 50,000-300,000 transcripts on a microarray
    • Possibility of simultaneously monitoring expression of every gene in any tissue will be possible
  • Detecting new metabolic disease pathways
    • Based on comparisons with other model organisms
slide79

Micro-Array technology to analyze gene expression

The principle behind this is to look at differences in gene expression when variables are changed -

eg. Yeast cells grown in the presence of EtOH- what genes are turned on or off in response to that change in the environment

Another variable could be normal versus diseased tissue

Pool the cDNAs

slide80

The cDNAs are hybridized to microarrays on which every gene that has been cloned is present [the DNA is spotted on the microslides and each spot corresponds to DNA from a different gene]

If a particulatr gene is expressed, then it will be present and labelled in the the cDNA pool. It can then hybridize to the spot of the plate corresponding to that particular gene

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The results from such an experiment look like this where the color of the spot tells you something about that gene expression and drug therapy optimization.

slide82

The data can then be analyzed and sorted into tables that show which genes are expressed in response to the stimulus and which are turned off

This sort of experiment can be done with any collection of RNAs that you want to compare- particularly useful to compare ‘normal’ to mutant/disease state- eg. tells you what genes are turned on in cancerous cells, may give you a clue as to how cancer works

link gene expression to genome sequence
Link Gene Expression to Genome Sequence
  • Identify promoter and 5\' sequence for a group of co-expressed genes.
  • Scan for known transcription factor binding sites.
  • Predict new regulatory sites based on common sequence elements.
diagnostic arrays
Diagnostic arrays

-Examples of factors showing variability that could be detected on arrays

-Provide information of status of SNPs and gene expression profiles

pharmacogenomics the future
Pharmacogenomics - The Future
  • Ultimate goal is to personalize drug treatment regimes
  • $
  • Faster clinical trials
  • $
  • Less drug side effects
  • $
  • Identify how genetic factors interact to affect variation in drug outcomes
    • Inactivation or activation by oxidation by cytochrome P450a
    • Clearance from bloodstream through kidney
    • Target sensitivity
    • Toxicity
    • Heterogeneity of disease mechanisms
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Pharmacogenomics - The Future…continued

  • Mutations in coding sequences will probably only play a small role in disease susceptibility between individuals
  • Variations affecting splicing and gene regulation will play a greater role
  • We know very little about the the importance that variations in regulatory and intronic sequences have and how they differ between populations
  • Issues:
    • associating sequence variations with heritable phenotypes
    • how genotypes affect common diseases, drug responses, and other complex phenotypes
slide87

Booming Population Databases

ScienceNews Focus

The promise is to deliver “personalized” medicine

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