when many genes and many environmental effects influence trait expression and variation

central limit theorem

under certain conditions, the distribution of the sum of a large number of independent and identically distributed random variables tends to approach a normal distribution, regardless of the original distribution’s shape

sources of phenotypic variance of a complex trait

• P: environmental differences between individuals

  • P₁ and P₂ (both parental lines) are different inbred lines

• F₁: environmental differences between individuals

• F₂: environmental differences and genetic differences between individuals

broad sense heritability

• how much of variability in a standing population is due to genetic differences between individuals

• bounded by 0 and 1

• dimensionless

• standardized parameter

• comparable across traits / species

formula for broad sense heritability

H² = V_g / V_X

monozygotic twins

identical, from same zygote

dizygotic twins

two separate fertilization events, not identical

twin studies

• used to isolate environmental effects (twins have same genetics, no variance)

• H² = r (correlation)

• higher H², higher correlation between genetics and trait

• can’t necessarily expand to represent entire human population (based on small subset, environments may not be completely random)

QTL mapping

• co-segregation of a marker (usually SNPs) with a trait’s phenotypic value helps locate the region of the genome where a gene with influence on the phenotype resides

• begins with crosses of two inbred lines that differ in the trait of interest and they molecular marker genotypes, then backcross F₁ hybrid to one parent

quantitative trait loci (QTL)

genes identified by QTL mapping that are associated with a phenotypic trait

genome-wide association study (GWAS)

relies on population surveys that look for correlation between marker and phenotypic trait values in samples taken from large populations