Lecture 13- Quantitative genetics Flashcards
what is the quantitative model
way of quantifying complex genetic changes
P = mu + G + E
where mu=population mean, G = genotypic effects, E = environmental effects
what contributes to G
additive variance, dominance variance, epistatic variance in interaction between genes
what contributes to E
pure environmental effects and interactions between genes and environment
how can you mathematically describe heritability
ratio of genetic variance / total phenotypic variance- value between 0 and 1 as phenotypic variance is always higher
3 different ways of looking at heritability
analysis of parent-offspring correlations (correlation between average parent and sibling values for a trait)
sib analysis- based on variation among half- and full-sib groups
twin pairs- taking genetically identical organisms from the same litter
3 issues with heritability estimates
assumptions, such as that 50% of the genome will be shared in siblings, may not be entirely true
genetic change is not accounted for
developmental age can impact traits and their expression
what is deltaP, equation
genetic gain- average change in phenotypic value due to selection
h2 * i * Vp (phenotypic variance) where h is heritability and i is selection intensity
how can breeding value of an individual be estimated
h2 (heritability) and the phenotypic difference between the individual and the population mean
2 issues with using these esitmates in selective breeding, and how they can be fixed
differences between population heritability over time etc- can recalculate h2 periodically, or recalculate the value when combining populations
changing environmental conditions, which can change the estimate of deltaP, can recalculate h2 in different environments or use different breeding populations
selection differential S
can measure total selection acting directly and indirectly on a trait- larger it is, the higher the mean shift
how can genetic correlations be calculated
using a selective index, can plug in multiple traits and assign weights to each depending on their genetic correlation- can then look at a single trait taking into account others
what is QTL mapping
identification of regions which impact a complex trait by identifying the loci which are correlated with it using recombination- ‘quantitative trait locus’
how does QTL work
looking at recombination to map the locations of a specific trait
need large 1k+ sample sizes, due to low recomb rates
can use linear regression to look at correlations between changes at loci and phenotype