Transcript Slide 1
Tracing Human Evolution with Genetics SELECTION June 9-17, 2007 SNPs Single Nucleotide Polymorphisms May or may not be in coding regions May or may not cause phenotypic changes Frequency of SNP distribution varies Seq 1 Seq 2 Seq 3 ATCGG ATCCA TGTAT CGATT ATGGG ATGCA TGTAT CGATT ATCGG ATGCA TGAAA CGATT Haplotype Refers to either: Genetic makeup of one set of chromosomes An area of a chromosome defined by a set of associated SNPs Based on statistical analysis and measurement of linkage disequilibrium (LD) Sources of LD Recombination Genetic linkage Random drift Non-random mating Interactions between genes Population structure Important points… Correlation of a SNP and a phenotype is just that – a correlation, not necessarily a cause. Haplotypes often identify genes involved in polygenic traits. No single site controls the phenotype. Quantitative trait loci (QTLs) are genetic areas involved in modulating expression of polygenic traits. Haplotypes and Evolution Recent human evolution is visible in the genome as “selective sweeps”. Selective sweeps are identified based on LD and haplotypes. Articles: Localizing Recent Adaptive Evolution in the Human Genome Convergent adaptation of human lactase persistence in Africa and Europe Lactase Persistence and Pastoralism Positive selective pressure Liquid Protein Subsequent migration and spread of phenotype Northern Europeans to North America Southern migrations through Africa Lactase Persistence Lactose malabsorption Lactose tolerance Lactase Persistence Continued expression of lactasephlorizin hydrolase (LPH) in mammals past weaning Global Distribution of Lactase Persistence Europeans Asian High levels in Scandinavians Decreasing levels further south in Europe Generally low levels in tested populations High in Khazaks African High in Tutsi and Fulani Low in other groups Genetics of Lactase Persistence Northern Europeans SNP identified Enhanced expression of lactase gene Africans Not the same SNP Lactose Tolerance Test Fast for 8-12 hours Ingest 50g lactose Take blood samples for two hours and test for a rise in blood glucose levels Caveats: Fasting? Field conditions: Used finger pricks and strips for monitoring diabetes Evolutionary Medicine Many common medical issues are polygenic Traditionally required a large affected family to identify candidate genes Genome Wide Association (GWA) Articles Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Guilt by association Case A medical researcher is interested in the underlying causes of type II diabetes. Specifically, why do different people have different tendencies to develop diabetes? Obviously current lifestyle will have a major impact, but lifestyle is not a complete explanation. What about genetic history? Is there a way to use tools such as the HapMap or genome-wide association surveys to predict risk for populations and individuals? How might this be useful for helping an American of mixed ancestry understand their risk for developing diabetes? Would it be useful for a Han Chinese person? What are the ethical considerations of collecting and using this kind of information?