Quantitative trait loci and psychopharmacology: response to commentaries
- PMID: 22282118
- DOI: 10.1177/026988119100500106
Quantitative trait loci and psychopharmacology: response to commentaries
Abstract
The theme of our article was that a merger is needed between quantitative genetic and molecular genetic approaches in order to detect genes associated with psychopharmacological processes even when the genes account for small amounts of variance, so-called quantitative trait loci (QTL). The recombinant inbred (RI) QTL approach using the BXD RI series was discussed as a promising approach.The commentaries by Crabbe and by McGuffin and Buckland make several excellent points to which we have little to add. Goldman and Katz, on the other hand, disagree with some of our arguments and for this reason much of the limited space of our response to the commentaries is directed towards the commentary by Goldman and Katz. We focus on three general issues that they raise: the relationship between quantitative genetics and molecular genetics (single genes vs multiple genes), reverse genetics (anonymous markers) vs forward genetics (candidate genes) and heterogeneity (narrow vs broad assessment). Our response to Goldman and Katz is that these are false dichotomies-we do not need to choose sides between major- and multiple- gene approaches, reverse and forward genetics, or narrow and broad assessment. Rather than choosing sides, we should encourage the deployment of multiple research strategies in order to maximize the probability of identifying genes that affect behavior. A major strength of the RI QTL approach is that it can identify both major- and multiple-gene effects, it employs both reverse and forward genetics, and it can be applied to both narrow and broad assessment (and its multivariate extension is ideally suited to understanding the genetic interrelationships among different levels of assessment).After discussing these general issues raised by Goldman and Katz, we address two specific issues raised in the commentaries: multivariate analysis of multiple markers and the use of F(1) crosses between RI strains to increase power. We end by mentioning the establishment of an RI QTL collaborative registry which aims to facilitate RI QTL analyses.
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