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It has become commonplace to map individual quantitative trait loci (QTL) in experimental organisms; the means (line-crosses and dense maps of markers) and motivation (the close relationship between continuous physiological traits and common, complex diseases) are self-evident. Progress in mapping human QTL has been more gradual, an inevitable consequence of genetic mapping in a natural population setting. The common objective of these studies has been to understand the molecular mechanisms underlying individual QTL. Recent theoretical and practical advances shift this focus to a more comprehensive or genomic perspective on quantitative variation. Fisher's infinitesimal model of adaptive evolution, which satisfied quantitative geneticists for over 50 years, has been modified in the light of data from QTL mapping experiments in plants and animals. The resulting exponential model provides a pleasing empirical fit to the distribution of QTL effect sizes, predicts that a large amount of quantitative variation will be explained by a limited number of genes and suggests a new mathematical framework for linkage mapping. Molecular analysis of QTL suggests that coding variants (e.g. allozymes) underlie a fraction of quantitative variation and that variants that affect gene expression (expression QTL, eQTL) have a substantial role. This is supported by genomic experiments that combine expression profiling with classical genetic mapping approaches to reveal a remarkable wealth of quantitative heritable variation in the transcriptome and that cis-and trans-acting regulatory factors are organized in networks reflecting pleiotropy. It is hoped that these advances will enhance our understanding of the genetic basis of complex inherited diseases.

Original publication




Journal article


Hum Mol Genet

Publication Date



13 Spec No 1


R1 - R7


Animals, Chromosome Mapping, Exons, Genetic Variation, Humans, Introns, Peptidyl-Dipeptidase A, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Rats