Quantitative genetics is the study of the genetic basis underlying phenotypic variation among individuals, with a focus primarily on traits that take a continuous range of values. Some familiar examples include height, weight, and longevity. However, traits that take discrete values (e.g., number of offspring) may also be analyzed within a quantitative genetics framework. “Threshold traits” are a special category of quantitative trait in which phenotypes take discrete, often binary, values (e.g., disease states) but reflect an underlying liability that has a continuous distribution, with different phenotypes produced above or below a certain threshold. Quantitative traits tend to be polygenic (influenced by a large number of genes) and also subject to nongenetic (environmental) influences. Heritability (H2), defined most generally as the proportion of the total phenotypic variation that is attributable to genetic factors (technically known as “broad sense” heritability), measures the relative importance of genes in determining phenotypic variance. “Narrow sense” heritability (h2) is the proportion of total phenotypic variation that is due to additive genetic variance and is of particular interest because of its importance in determining the response of a population to natural or artificial selection. Awareness of the factors underlying variation in quantitative traits is central to an understanding of evolution in natural populations and for predicting responses to selective breeding in agricultural species and disease risk in humans. Quantitative genetic variation has traditionally been studied using statistical analyses to partition components of phenotypic variation, often without knowledge of the genes involved. However, ongoing developments in genomic technology mean that it is increasingly possible to also identify the specific genes that underlie variation in quantitative traits.
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