Mapping Quantitative Trait Loci

Quantitative trait loci are normal genes in every sense of the word. The somewhat unwieldy term quantitative trait loci highlights the fact that variant forms—or alleles—of QTLs have relatively subtle quantitative effects on phenotypes . QTLs identified in human populations are often referred to as susceptibility genes because humans carrying certain alleles are at greater risk of developing particular diseases. QTLs are often contrasted with Mendelian loci that have pronounced and usually dichotomous effects on phenotypes, but the demarcation between quantitative and qualitative traits is often blurred. QTLs that have particularly large effects—often verging on producing Mendelian segregation patterns (e.g., 1:2:1)—are referred to as major-factor or major-effect QTLs. Their large effects make them the easiest QTLs to map.

If large numbers of genes collectively control variation in a CNS phenotype (neuron number, cell ratios, volume of a region, etc.), then allelic differences at any one locus will be associated with small, possibly undetectable differences in phenotype. This phenomenon is referred to as the infinitesimal model of polygenic action. In contrast, if only a small number of genes control much of the variation and if their alleles exert relatively large effects on the phenotypes, then it will often be possible to map single QTLs. Quantitative genetic analysis of variation in bristle number in Drosophila provides a superb example of what can be achieved by "disassembling" a polygene into its constituent QTLs. Normal allelic variants at the achaete-scute complex and at the scabrous locus each account for 5–10% of the variance in numbers of these sensory organs. In this system, the QTLs controlling natural variation are also known to be vitally important developmental genes that had been identified previously based on mutant phenotypes associated with null alleles.

The ability to map QTLs in the CNS depends critically on the amount of variance explained by allelic differences at single QTLs and the technical precision with which traits can be measured (a signal-to-noise problem). The more accurate and reliable the method of phenotyping, the higher the heritability, and the greater the number of resolvable QTLs.

The introduction of quantitative genetics and QTL mapping in neuroscience is a relatively new phenomenon. Among the traits that have been studied are EEG and evoked response potentials in humans , sensitivity to ischemia in rats, alcohol consumption, tolerance, and withdrawal, behavioral effects of stress , tolerance to various drugs of abuse, and retinal ganglion cell number and brain weight in mice. While the number of neuroscientists examining QTLs is relatively small compared to those mapping QTLs in biology as whole, the recent rapid growth of this field is unmistakable. Virtually every report mentioned above was published within the last four years, and the majority within the last two. In large measure, the reason for this recent surge in neurogenetics is that QTL methods have improved. These methods depend on the polymerase chain reaction (PCR), high-density genetic maps, and sophisticated statistics programs. The application of these methods in the next decade will revolutionize our understanding of normal genetic mechanisms controlling CNS development, susceptibility to disease, and even CNS evolution.