Quantitative Genetics

Quantitative traits are described by a frequency distribution Figure 18-3b

Variation in quantitative traits increases in progeny Quantitative Behavior Mendelian Behavior

A norm of reaction is the relation between environment and phenotype Figure 18-6

Crosses are performed to test for heritability Figure 18-11

Selection altered bristle number Figure 18-14

Heritability h2 = genetic variation phenotypic variation Measured using resemblance between relatives h2 = genetic variation phenotypic variation Genetic + environmental + interaction In a moment, I’ll describe approaches that are used to identify those genetic loci that contribute to variation, but of course before you go out and try to identify genetic loci contributing to variation, you want to be sure that such loci exist, i.e., that there is heritable variation in the trait, and this involves measuring the heritability, which is done by measuring the resemblance between relatives. -a bit about heritability, this is the proportion of phenotypic variation that is due to genetic variation. The total phenotypic variation is made up of genetic variation and environmental variation and potentially interaction between the two, so its important to note that heritability depends on a particular environment. It is NOT a fixed value and NOT an answer to the nature/nurture question. The amount of genetic variation may differ between populations, e.g., it will be very low in an inbred population. Similarly, the amount of environmental variation may differ between environments. So say for body size- in the wild you may get lots of environmental variation due to variation in food supply, so the denominator will be high relative to the numerator, and you will get a low heritability, BUT- if you were to bring that same population into the lab, where the environmental conditions are controlled, that would reduce environmental variation, and so reduce the denominator and the heritability would be higher, even if the genetic variation remained constant. But for now, let’s just consider the genetic loci that contribute to continuous variation.

Quantitative Trait Loci (QTL): the specific loci whose allelic differences are responsible for the genetic variation in a quantitative trait (e.g. total sleep time) Note: QTL does not refer to the sum total of all loci that influence a particular trait, only those loci that are functionally polymorphic (with respect to the trait of interest in a given environment) between the parental strains or within the population. In mice, Mutagenesis and engineered KOs can artificially alter any gene, however, “natural” polymorphisms can represent more subtle variations.

QTL Mapping QTL mapping: identification of chromosomal regions containing gene(s) that correlate with measured phenotypes Different methods Single-marker analysis: compares phenotypic means of different marker genotypes Interval mapping: estimates position of QTL between two markers using maximum likelihood (compares null hypothesis of no QTL vs. a QTL between the markers). Composite Interval mapping: IM and multiple regression Multiple QTL models QTL present when LOD score exceeds critical threshold LOD = Log of the Odds = log10 (H1/H0) often for single locus analysis, 3.0 is significant and 2.0 is suggestive depending on sample size, number of markers, and other variables.

Crossing over produces new allelic combinations

An experimental protocol for localizing genes Figure 18-17

Quantitative traits are described by a frequency distribution Figure 18-3b

Only a small percentage of character difference is associated with any one DNA marker Figure 18-18

Mapping by Backcrossing

Generating the Backcross Cast/EiJ x C57BL/6J F1 x Cast/EiJ BC1s Backcross progeny have on average: 75% CE, 25% B6 alleles 50% C/C, 50% C/B genotypes for all loci C57BL/6J (B6) Cast/EiJ (CE)

Mice have 20 chromosomes

Some types of detectable variation RFLPs (Restriction fragment length polymorphisms) VNTRs (Variable nucleotide tandem repeats) = minisatellites Microsatellites SNPs (Single nucleotide polymorphisms)

LOD Scores Null hypothesis: assume no linkage. Alternative hypothesis: assume the disease (or phenotype) and the marker locus are linked.