A quantitative trait is one that has measurable phenotypic variation owing to genetic and/or environmental influences. This variation can consist of discrete values, such as the number of separate tumours in the intestine of a cancer-prone mouse, or can be continuous, such as measurements of height, weight and blood pressure. Sometimes a threshold must be crossed for the quantitative trait to be expressed; this is common among complex diseases.
A QTL is a genetic locus, the alleles of which affect this variation. Generally, quantitative traits are multifactorial and are influenced by several polymorphic genes and environmental conditions, so one or many QTLs can influence a trait or a phenotype. It is important to remember that phenotypic variation can also be caused by environmental factors that are independent of genotype or through gene-environment interactions. Sometimes a cluster of closely linked polymorphic genes is responsible for the quantitative variation of a trait. These are difficult to separate by recombination events and therefore might be detected as one QTL. However, if distinct QTLs can be separated by genetic or functional means, each should be considered to be a separate QTL.
Two classic examples of quantitative traits are height and weight — loci that modulate these traits are therefore called QTLs. These traits can also be influenced by loci that have large discrete effects (often called mendelian loci
); for example, genes that cause dwarfism also affect height but in a qualitative ‘all-or-none’ way. Moreover, the same locus might be considered to be both a QTL and a Mendelian locus depending on the alleles that are examined: some alleles might cause quantitative effects whereas others might cause all-or-none effects. modifier loci
that modulate the effects of a Mendelian locus can also be described as QTLs. For example, Mtap1a
, which is a modifier of the mouse gene tubby (Tub
), is considered to be a QTL6,10,11
. This modifier alters the hearing of tub/tub
mice, as detected by the auditory brainstem response (ABR) threshold. In an F2
population, the ABR measurements are distributed continuously and therefore this modifier qualifies as a QTL6,10,11
The distinction between Mendelian loci and QTLs is artificial, as the same mapping techniques can be applied to both. In fact, the classification of genetic (and allelic) effects should be considered as a continuum. At one end of the spectrum is the dichotomous Mendelian trait with only two detectable and distinct phenotypes, which are governed by a single gene. At the other end are traits, such as growth, which are likely to be affected by many genes that each contribute a small portion to the overall phenotype. Between these two extremes are traits that are regulated by more than one genetic locus (and are possibly also influenced by environmental factors), which show several intermediate phenotypes. Generally, the more loci that are involved in determining a quantitative trait, the more difficult it is to map and identify all of the causative QTLs. When more than one QTL affects a particular trait, each might have a different effect size and the effects of individual QTLs will vary from strong to weak. The size and nature of these effects can also be influenced by the genetic background (the total genotype of the individual) and interactions between QTLs are common.