1 Lecture 43 – Quantitative genetics I. Multifactorial traits – eg

Lecture 43 – Quantitative genetics
I. Multifactorial traits –
eg. Human height
- hundreds of genes influence height
- quantitative traits can be measured
A. Variance provides a measure of variation
- total variance (Vp) includes both
genetic and environmental factors
V P = VG + V
- may be able to separate genetic from environmental factors (eg. dandelion)
B. Heritability provides an estimate of the genetic contribution to a trait
- heritability = H2 = VG/VP
- H2 = 0 means genetics does not contribute
- H2 = 1 means trait is entirely genetic
- can estimate by studies, including of twins
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II. How can we get at the loci responsible for quantitative traits?
A. QTL mapping
- cross small “p” X large “l”
- cross F1’s X large “l”
- weight F2 fruit and genotype across genome
“p/l” vs “l/l”
- does weight differ?
- For most genotypes, the answer is no but for
a few it is yes (these are loci that contribute to
the trait, in this case fruit size)
- identified 28 loci responsible for fruit
size
B. How can we study QTLs in humans?
1. First a definition: linkage equilibrium = occurrence of a specific comination of
alleles in cis at two or more loci at a frequency equal to the frequency of the
respective allele in the population
- eg. consider two linked loci, A and a each have a frequency of 50%, D
and d have frequency of 10% and 90%, respectively
- haplotype = group of alleles in cis at closely linked loci, inherited as unit
2. Association mapping – look for linkage disequilibrium between polymorphisms and
phenotype
- mutation arose on some chromosome, linked to
polymorphisms
- generations of recombination randomized
polymorphisms except for the most closely linked
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