Critical assumptions of classical quantitative genetics and twin studies

Quantitative genetics (QG) analyses variation in traits of humans, other animals, or plants in ways that take account of the genealogical relatedness of the individuals whose traits are observed. This article focuses on "classical" QG where the analysis of variation does not involve data on measurable genetic or environmental entities or factors. Classical QG analysis employs models of genes with simple Mendelian inheritance and direct contributions to the trait (assumption 1). However, the data analysed in QG are of traits, not genes, so it must be possible to analyze the variation without making reference to hypothetical genes. Five other assumptions then warrant new or renewed attention: 2. All other things being equal, similarity in traits for relatives is proportional to the fraction of all the genes that vary in the population which the relatives share, e.g., fraternal or dizygotic twins are half as similar as identical or monozygotic twins. 3. In human twin studies, genotype-environment-interaction variance can either be discounted or be incorporated into the heritability estimates. 4. High heritability of a trait can guide decisions about whether to investigate genetic factors underlying the development of that trait (and analogously for other components of variance). 5. When similarity among a set of close relatives (such as twin pairs) is associated with similarity of (yet-to-be-identified and measured) genes or genetic factors, those factors are the same from one set of relatives to the next. 6. In human twin studies, residual variance is a within-family environmental effect. Allowing for alternatives to these assumptions can change markedly the results or interpretation of classical QG. Lines of further investigation are noted for classical QG, for current QG analyses that incorporate measurable genetic or environmental factors, and for debates in social