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Lecture 15

HMB265 Lecture 15 & 16.pdf

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Department
Human Biology
Course Code
HMB265H1
Professor
Belinda Chang

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Lecture 15 19.5 Mapping QTL in Populations with Known Pedigrees The genes that control variation in quantitative (or complextraits) are known as qualitativetrait loci QTL have allelic variants that typically make relatively small, quantitative contributions to the phenotype Can visualize the contributions of the alleles at a QTL to thetrait value by looking at the frequency distributions associated with each genotype at a QTL When distributions overlap, cant determine genotype simply by looking at an individuals phenotype (as we can for genes that segregate in Mendelian ratios) QTL mapping has revolutionized our understanding of the inheritance of quantitative traits Fundamental idea behind QTL mapping is that one can identify the location of QTL in the genome usingmarker loci linked to a QTL o Suppose you make a cross between 2 inbred strains P1 with a high trait value andP2 with a low trait value o F1 can be backcrossed to P1 to create a BC1 population in which the alleles at all the genes in the 2 parental genomes will segregate o Marker loci such as SNPs or microsatellites can be scored unambiguously as homozygous P1 or heterozygotes for each BC1 individual o If there is a QTL linked to themarker locus, then the mean trait value for individuals that are homozygous P1 at the marker locus will be different from themean trait value for the heterozygous individuals o Based on such evidence, one can infer that a QTL is locatednear the marker locus The basicmethod For a certainmarker, o If the means for the genotypic classes are very close to the overall mean, there is no QTL affecting the phenotype near that marker o If the means for the genotypic classes are quite different from the overallmean and from each other, there is a QTL affecting fruit weight near thatmarker How different do they need to be before we declare that aQTL is located near a marker? o The statistical analysis involved calculating the probability of observing the data given that there is a QTL near the marker locus and the probability of observing the data given that there is not a QTL near the marker locus o Researchers report the of the odds, or the Lod score If there is a QTL near the marker, then the data were drawn from two underlying distributions (each has its own mean and variance If there is no QTL, then the data were drawn from a single distribution for which the mean and the variance are those of the entire population Lod scores can be calculated for points between the markers o This can be done by using the genotypes of the flankingmarkers to infer the genotypes at points between the markers o The odds equation incorporates this uncertainty when one calculates theLod score at points between the markers The Lod scores can be plotted along the chromosome shows peaks and flats o The null hypothesis is that there is NOT a QTL at a specific position along the chromosome o The greater the Lod score, then the lower the probability under the null hypothesis o Where the Lod score exceeds the threshold value, then we reject the null hypothesis in favour of the alternative hypothesis that a QTL is located at that position QTL mapping can be done with F2 populations and other breeding designs. Advantages: o One gets estimate of the mean trait valued for all 3 QTL genotypes o With these data, one can get estimates of the additive and dominance effects of the QTL What can be learned from QTL mapping? o The number of QTL (genes) affecting a traito The genomic locations of these genes o The size of the effects of each QTL o The mode of gene action for the QTL (dominant vs additive) o Whether one QTL affects the action of another QTL (epistatic interaction) From QTL to gene The resolution of QTL mapping is on the order of 1 to 10 cM, the size of a region that can contain 100 or more genes To go from QTL to a single gene requires additional experiments to fine map a QTL To do this, the researcher creates a set of genetic homozygotes (aka lines), each with a crossover near the QTL o These stocks or lines differ from one another near the QTL, but they are identical to one another (isogenic) throughout therest of their genomes o Lines that are identical throughout their genomes except for a small region of interest are called congenic or nearly isogenic lines. The isolation of QTL in an isogenic background is critical because only the single QTL region differs between the congenic lines Thus, the use of congenic lines eliminates the complications caused by havingmultiple QTL segregate at the same time 19.6 Association Mapping in Random-Mating Populations Association mapping is a method for finding QTL in the genome based on naturally occurring linkage disequilibrium between a marker locus and the QTL in a random mating population o Allows researchers to directly identify the specific genes that control the differences in phenotype among members of a population Association mapping is now routinely used to scan the entire genome for genes contributing to quantitative variation o This type of study is known as a genome-wide association study o Major adv: candidate genes are not required since one is scanning every gene in the genome Other advantages o Since it is performed with random-mating populations, there is no need to make controlled crosses or work with human families with known parent-offspring relationships
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