5Population Genomics- A View ProjectsPopulationGenomicsMicrobialGenomicsPharmacogenomicsFunctionalGenomics
6Population Genomics- definitions The study of forces that determine patterns of DNAvariations in populations (Michel Veuille, European Consortium)Field of genomics that links complex genotypes and phenotypesby comparing the flow of genotypic and phenotypic informationin breeding and natural populations (Andrew Benson, U. Neb)Genomic variation within species permitting the construction ofdetailed linkage maps using polymorphic markers, and throughcrossing experiments between individuals with differentphenotypes, identification of genes responsible for phenotypicvariation (e.g, disease susceptibility, drug toxicity) (Andrew Clark, PSU)
7Questions 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)Questions in Marine Population GeneticsHow 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?
8Continuous populations Dispersal modelsContinuous populationsIsolation-by-distanceDiscrete populationsStepping-stoneIsland model
9FST -approachesNmFSTWright (1951) [The genetical structure of populations. Ann. Eugen. 15: ] noted the following relationship holds when populations reach an equilibrium between genetic driftand migration:where N is the variance effective population size of theaverage population, andm is the average proportion of immigrants in eachpopulationProblem: Useful parameter space is for FST valuesbetween 0.1 and 0.4Nm is a virtual number
10The giant tubeworm, Riftia pachyptila DISTANCE (Km)100010,00020105100Guaymas21°13112East Pacific Rise9Fst. Migration rateGalapagosRiftNWESReject expectations of "island model"Consistent with stepping-stone modelInference: a species with more limited dispersal abilitiesBlack et al Gene flow among vestimentiferan tube worm(Riftia pachyptila) populations from hydrothermal vents of the Eastern Pacific. Marine Biology 120:
11Molecular Toolkit: markers for inferring population structure and gene flow Allozymesmultiple, independent, codominant loci; relatively easy; low costneed to freeze samples; state charactersRFLPsvariation in restriction fragment lengthspolymorphic due to restriction site mutationmtDNArelatively easy; maternally inherited; effectively haploid; non-recombining; modest cost; amenable to genealogical analysislinked loci and psuedoreplicationnuclear DNA sequencesamenable to genealogical analysisdiploid; recombination; start-up time may be considerableAFLPscan get 100s of loci relatively easilydominance; recombination; state characters; mutation models not availableminisatellitesrepeats of bp unitspolymorphic due to unequal crossing over
12Molecular Toolkit: markers for inferring population structure and gene flow DNA microsatellitesRepeat unit 2-3 bp; nuclear; can get dozens of loci relatively easily; method of choice for parentagerecombination; state characters; start-up time is great; issues of homoplasy in geographical studies; mutation must be taken into account in gene flow modelsSingle-Nucleotide Polymorphisms (SNPs)Most simple form and most common source of genetic polymorphism in most genomes.large amount of sequencing effort in nonmodel organismsViolation of analyitcal assmumption of independence among marker lociSequence 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 lociExpressed Sequence Tags (ESTs) (physical marker)Short ( bps) 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
13Molecular Markers:Random Amplified Polymorphic DNA, AP-PCR PCR-based methodTarget Sequence= arbitrary primer (e.g. ggcattactc)High Variability: Probably due to mutations in priming sequencesAmplify regions between priming sites by polymerase chain reactionAnalyze PCR products by agarose gel electrophoresis.Marker is dominant (presence/absence of band).No prior sequence knowledge requiredMany variations on the theme (e.g., RAMP, ISSR)
14Amplified Fragment Length Polymorphism (AFLPs) Polymorphism based on gain or loss of restriction site, or selective basesTechnically demanding and expensiveMany markers generated, mostly dominantMore reliable than RAPD, less so than SSRNo prior sequence knowledge required
15Single-Strand Conformational Polymorphism 1. Amplify Target Sequence2. Denature product with heat and formamideHighly sensitive to DNA sequence: can detect single base changesSimple process but can be difficult to repeat3. Analyze on native (nondenaturing) polyacrylamide gel4. Base sequence determines 3-dimensional conformation
16Denaturing Gradient Gel Electrophoresis 1. Amplify Target Sequence2. 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 differences4. Denaturing gradient gels can be difficult to produce: use perpendicular gradient to identify optimal conditions, move to CDGE: constant denaturant gel electrophoresis
17Cleaved Amplified Polymorphic Sequence (CAPS) 1. Amplify Target Sequence2. Cut with a restriction enzyme that differentiates allelesXFairly simple analysis (cutting can be a hassle)Requires sequence information from several alleles (or luck)Allele 1Allele 23. Alleles can be differentiated by size based on loss or gain of restriction site; May be able to analyze on agarose gel
18Allele Discrimination via Quantitative PCR (Taqman)
21Microsatellites“…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
22Microsatellite Types Dinucleotide Trinucleotide Tetranucleotide Animals - CAPlants - TA, GATrinucleotideGTG, CAG, and AATRelated to disease and cancersTetranucleotideGATA/GACAHighly polymorphic
24Microsatellite Advantages Highly PolymorphicCodominantIn every organism examined to dateVery abundantRandom spacing in the genomeCan find same loci in closely related speciesEasy and reliable scoringHighly sensitiveNeutral markers
25Microsatellite Disadvantages ExpensiveTime consumingSeveral loci are needed to obtain sufficient statistical powerCurrent analyses methods do not distinguish between changes in flanking regions vs. changes within the microsatellite regionsDifferent rates of evolution at different loci
26Mutation MechanismsSlippage in DNA at Replication (Slip-Strand Mispairing, SSM)increases or decreases the repeat by one unitmost supporting evidenceRecombinationUnequal crossing over (UCO)Gene conversion
27Microsatellite Mutations 10-3 to 10-6 events per locus per generation (point mutation 10-9 to 10-10)Varies byrepeat typebase composition of the repeattaxonomic grouplength of the allelemost common - addition or deletion of a single repeatoccasionally 2 to several repeatsstrong evidence that the number of repeats is limited
28Mutation Models Infinite Allele Model (IAM) gain or loss of any number of repeats and always results in an allelic state not present in the populationStepwise Mutation Model (SMM)gain or loss of a single repeatTwo-Phase Model (TPM)gain or loss of X repeatsK-allele Model (KAM)Intermediate step in the IAM (IAM = KAM with infinite K)K possible allelic states
29Creating A Microsatellite-Enriched Library DNA LibraryGenomicDNADNAExtractionDigestionAddLinkersPCR
31Microsatellite Library Screening CloningBlots/HybridizationsPlasmidPrepsIsolated PlasmidsEnzymeDigestCheck Insert SizeDot Blot Hybridizations
32References www.biotech.ufl.edu/WorkshopsCourses/mm_manual.htm Avise, J.C Molecular Markers, Natural History and Evolution. Chapman and Hall, New York pp.Balloux, F. and N. Lugon-Moulin The estimate of population differentiation with microsatellite markers. Molecular Ecology. 11:Goldstein, D.B. and C. Schloterrer (Editors) Microsatellites: Evolution and Applications. Oxford University Press, Oxford, 352 pp.Jarne, P and P.J.L. Lagoda Microsatellites, from molecules to populations and back. Trends in Ecology and Evolution 11(10):Slatkin, M A measure of population subdivision based on microsatellite allele frequencies. Genetics 139:
33Fluorescent Labeling of Microsatellites Acrylamide gel with 5 microsatellite loci and internal size standardSimultaneous analysis of a dozen loci
34Comparing “Genomic” Methods for Population Studies PolymorphismCodominancePrior Seq. KnowledgeDifficultyRepeatabilityDNA QualityDevelopment CostGenotyping Cost/LocusEase of scoringGelRAPD++N+-AgaroseAFLPPolyacryl.Microsats+++YCAPS+(+)*DGGE, SSCPTaqManNone* Depends on cost of restriction enzymes employed
35All 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 lessoften 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:
36Population 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 samplemtDNA, Microsatellites, SNPsUnderstanding current gene flow and mating systems by direct methods (e.g., maternity analysis, paternity analysis)Need high polymorphism, codominance, repeatability, low cost per sampleMicrosatellites, SNPsPharmacogenomics: polymorphism-based approaches for the discoveryand development of new medications; translating polymorphisms into “new genomic medicine”*Need rapid, low-cost, repeatable way to distinguish allelesscreening large numbers of individuals; SNPs and Sequencing*New York Times, Nov. 2002
3853 human mtDNA sequences (16,500 bp) Two main hypotheses for human evolution:“Recent African origin” hypothesis- modern humansoriginated in Africa k years ago, and spread“Multi-regional” hypothesis- modern humans evolved in different parts of the worldMtDNA favored out of Africa hypothesis but lacked statistical support for deep African branchesNeighbor-joining phylogram based on completemtDNA genome sequences (excluding D-loop).1000 bootstrap replicates shown on nodes.Asterisk refers to the MRCA of the youngest cladecontaining both African and non-African individuals.53 human mtDNA sequences (16,500 bp)examined timing of evolutionary eventsmtDNA evolving in a “clocklike” fashionLinkage Disequilibrium not evident3 deepest branches lead exclusively to sub-SaharanNote star-like vs deep branching topology- larger Neor longer genetic history in Africa; bottleneck in non-Affican
39mtDNA mismatch distributions for Africans and non-Africans • Individuals of African origin show a ragged distributionconsistent with constant population size• Individuals of non-African origin show a bell-shaped distributionstrongly suggests a recent population expansionExodus from Africa began 100 million years agoDivergence of Africans and non-Africans occurred52,000 28,000 years agoMismatch distributions of pairwise nucleotidedifferences between a) African and b) non-African
40Human genome mining to produce 507,152 high-confidence SNP candidates as uniform resource for describing nucleotide diversity and regional variationwithin and between human populations
41So 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 genome90% of all human DNA polymorphisms;1SNP in 1000 bp; 1.42 millionSNP Haplotype is a particular pattern of sequential SNPs (or alleles) found on a single chromosomeMicroarrays, mass spectrometry and sequencing are all used to accomplish grouping or blocking of SNPs= haplotypingHaplotype Determination Problem- find all haplotypes given a genome and all identified SNPs (algorithm development)
42Approaches to SNP discovery and Genotyping Many and numerous!(Reviewed Pui-Yan Kwok Annu. Rev. Genomics Hum Genet :SNP discovery can be based on expressed sequence tags (ESTs), genomic restriction fragments,aligned BAC sequences, random shot gun clone sequences, overlapping genomic clone sequencesParallel genotyping of SNPs using generic high-density oligonucleotide tag arraysFan et al. (2000) Genome Research 10: (see Stickney et al 2002 for zebrafish SNP arraying)PCR + single base extension chimeric primers, allele specific (labeled) dideox NTPs and thenhybridized to arrays containing thousands of preselected 20-mer oligonucleotide tagsPolymorphism ratio sequencing: a new approach for SNP discovery and genotypingBlazej et al. (2003) Genome Research 13:Dideoxy-terminator extension ladders generated from a single sample and reference template arelabeled with fluorescent dyes and coinjected into a separation capillary for comparison ofrelative signal intensities.A novel method for SNP detection using a new duplex-specific nuclease from crab hepatopancreasShagin et al. (2002) Genome Research 12:“Duplex Specific Nuclease Preference” - SNP region amplified, template, signal probe, andmatched duplexes are then cleaved by DSN to generate sequence-specific fluorescence
43GenBank has a dbSNPOne year ago: dbSNP had 2,842,021 SNP submissions totalToday, 2003, dbSNP has 6,250,820 submissions for human1,368,805 submissions for mosquito197,414 submissions for mouse2,031 submissions for zebrafishIt is possible to search dbSNP by BLAST comparisons to a target sequence
44The 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 forthe 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.”
45We 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.
46Looked for mismatches; SNPs if Polybayes probability was 0.80Built a set of pairwise sequencealignments by analyzing the over-lapping regions of large insert clonesSNP marker density grouped byoverlapping regionsModeled the marker densitydistribution
47Evaluated degree of fit between observed density distribution and Marker density distributions predicted undercompeting population genetic modelsNo demographic historyPoisson distribution driven by mutation rateDistribution of polymorphic sites profoundly impactedIncreased pop size yields abundance of new lineages with more mutationDecreased pop size raises likelihood of relatedness resulting inover-representation of sequence identityCollapse followed by a phase of recent population recoveryEvaluated degree of fit between observed density distribution andprobability predicted using the log likelihood of the data for a given modelr indicates the per nucleotide, per generation recombination rate
48….followed by a modest recovery Superior fit of the modeled parameters (with or without recombination) suggests asevere, 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.
49separated by blocks of low density (0.5 SNPs per 10kb) History of the inbred laboratory mouseCompared the C57BL/6J Mouse genome sequence with 59 finished segments of the 129/Sv inbred strainDiscovered 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 haplotypeswere shared among common inbred populations.Surveyed wild strains showed that 67% of each of the inbred genomes are derived fromEuropean mice and 33% from Asian mice
50How about other organisms? or new ‘model’ organisms; organisms that exemplify phenomena not well studied in human/worm/mouse?Three-Spined Sticklebacksmorphological evolutionpopulations 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 F2ssee Peichel et al (2001) The genetic architecture of divergence between threespine stickleback species. Nature 414:
51Stickleback genetic map (Woods et al. 2000) 227 polymorphisms1 SNP marker per 4 cMtook ~4 person-yearsnow mapping genetic basis of morphological variations
52Zebrafish Genes Microsatellites First zebrafish SNP map 5 months ago Postlehwait et al A genetic linkage map for zebrafish. Science 264:Woods et al A comparative map of zebrafish genome. Genome Research 10:Geisler et al A radiation hybrid map of the zebrafish genome. Nature Genetics 23:MicrosatellitesShimoda et al Zebrafish genetic map with 2000 microsatellite markers. Genomics 58:First zebrafish SNP map5 months ago2102 SNPs for mutation mappingHundreds of SNPs on single arrayStickney et al Rapid mapping of zebrafish mutationswith SNPs and oligonucleotide microarrays. Genome Res.12:Vertical lines = 25 linkage groupsRed dots correspond to SNPs represented on the olig. microarray
53Population 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 sampleAllozymes, mtDNA, RAPDs, Microsatellites, AFLPs, RFLPs, SNPsUnderstanding current gene flow and mating systems by direct methods (e.g., maternity analysis, paternity analysis)Need high polymorphism, codominance, repeatability, low cost per sampleMicrosatellites, SNPsPharmacogenomics: 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 allelesscreening large numbers of individuals; SNPs and Sequencing*New York Times, Nov. 2002
54Inferring Pairwise Relationships with SNPs (in Your Favorite Metazoan) (Glaubitz, Rhodes, and Dewoody 2003 Molecular Ecology 12: )Problem:Need to determine genetic relationships in populations without known pedigreesMicrosatellites current methods of choice among close kin within a population,but the number of independently segregating microsatellite markers is limitedSNPs may provide large number of segregating loci witha large number of alleles at even frequenciesGoal:To assess known pairwise relationships - via single nucleotide polymorphismswhere already have parallel microsatellite results.Recent advances in microarray technology permit genotyping of large #s of individualsat 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 numbersof microsatellite loci in estimating relationships?
55Glaubitz et alComputer simulations designed to evaluate SNPs abilityto discriminate a variety of (pairwise) relationships likelyto occur in natural populations, comparisons tomicrosatellites from Blouin et al 1996Constructed 5 catagories of relationships types•SNPs segregate independently, ideal genome with 20autosomes, 5 SNPs per chromosome, 10,000 individualsrandom genotypesConstructed an array of pedigreesestimated pairwise relatedness at a single locus (r1)Evaluated the performance of 100 simulated SNPs byestimating misclassification (rate) of relationships
56Microsatellite approaches are still better… illustrates that different pairwise relationships can have different amounts of inherent variance in relatednessthe 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 r100 independently segregating SNPs determinined parent-offspring pairsas well as about 16 or fewer microsatellite loci when both parents are unknownEven 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…
57Conclusion:“SNPs have limited potential for the delineation of genealogical relationships…”Based on 1) assumption of independence among the sampled SNP loci2) that the microsatellites themselves are independent (not linked)My two cents:In the absence of a linkage map, the number of microsatellite or SNP loci scored must beincreased to compensate for the loss of information as a result of nonindependencebetween markersAn alternative to using independently segregating SNPs is to use independentlysegregating haplotypes, with each haplotype defined by a cluster of tightly linkedSNPs. (e.g., Heaton et al 2002 sequenced regions around 32 cattle SNPs; additional183 polymorphic sites; and more haplotypes for better resolution)
58To take full advantage of the “vast” abundance of SNPs in metazoan genomes and their potential automation, we will need analytical methods that accountfor tight genetic linkage (McPeek and Sun 2000) and known recombinationfrequencies….until then, SNP population genomics will likely only be used on model organisms.
59Population Genomics Research Understandings population structure, historic migrations, and gene flow among populations (e.g., Fst, coalescent approaches)Need moderate polymorphism, low cost per sampleAllozymes, mtDNA, RAPDs, Microsatellites, AFLPs, RFLPs, SNPsUnderstanding current gene flow and mating systems by direct methods (e.g., maternity analysis, paternity analysis)Need high polymorphism, codominance, repeatability, low cost per sampleMicrosatellites, allozymesPharmacogenomics: 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 allelesscreening large numbers of individuals; SNPs and Sequencing*New York Times, Nov. 2002
61PharmacogenomicsThe 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 patientCan compare “genotypes” for SNP markers linked to virtually any trait
62Evolving Paradigm for Discovery of Genetic Polymorphisms associated with aberrant drug disposition or effectsObserved phenotype - family studies-inherited basisMore discoveries thru polymorphismsin candidate genes (metabolism; transport;targets of candidate medication
63New Drug Targets Expected from the Human Genome Project Number of Drug Targets12,0005,000–10,00010,0008,0006,0004,0002,000Approx. 500Cumulative Number of Targets Known TodayNew Targets Expected from Human Genome ProjectSource: Drews J. Nat Biotechnol 1996;14.
65Disease Genes Discovered For 1100 genes at least one disease-related mutation has been identified
66Clinical 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
67Functional Classifications Disease genes classed by function and their relative representations
68Some Diseases Involve Polygenic Effects There are a number of classic “genetic diseases” caused by mutations of a single geneHuntington’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, CancerEach 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
69Gene 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.
70Some Examples10% 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.
71Succinylcholine 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.
72Isoniazid 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 drugSome alleles of the NAT2 gene are also associated with succeptibility to various forms of cancer
73Cytochrome 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.
74ACEPatients 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.
75Collect 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.
76Make Genetic ProfilesScan these populations with a large number of SNP markers.Find markers linked to drug response phenotypes.
77Use the ProfilesGenetic 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.
78Major pharmacogenetics approaches in post-genomic era Identifying SNP variations in the genome and populationsStudy of differential gene expressionChips with mRNAs from different tissue types or normal and diseased tissueCan detect expression of a target gene among 50, ,000 transcripts on a microarrayPossibility of simultaneously monitoring expression of every gene in any tissue will be possibleDetecting new metabolic disease pathwaysBased on comparisons with other model organisms
79Micro-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 environmentAnother variable could be normal versus diseased tissuePool the cDNAs
80The 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
81The 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.
82The data can then be analyzed and sorted into tables that show which genes are expressed in response to the stimulus and which are turned offThis 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
83Link 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.
84Diagnostic arrays-Examples of factors showing variability that could be detected on arrays-Provide information of status of SNPs and gene expression profiles
85Pharmacogenomics - The Future Ultimate goal is to personalize drug treatment regimes$Faster clinical trialsLess drug side effectsIdentify how genetic factors interact to affect variation in drug outcomesInactivation or activation by oxidation by cytochrome P450aClearance from bloodstream through kidneyTarget sensitivityToxicityHeterogeneity of disease mechanisms
86Pharmacogenomics - The Future…continued Mutations in coding sequences will probably only play a small role in disease susceptibility between individualsVariations affecting splicing and gene regulation will play a greater roleWe know very little about the the importance that variations in regulatory and intronic sequences have and how they differ between populationsIssues:associating sequence variations with heritable phenotypeshow genotypes affect common diseases, drug responses, and other complex phenotypes
87Booming Population Databases Science News FocusBooming Population DatabasesThe promise is to deliver “personalized” medicine