This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Plomin, R. Articles by Gora-Maslak, G. Search for Related Content PubMed Articles by Plomin, R. Articles by Gora-Maslak, G. Social Bookmarking                   What's this?

Quantitative trait loci and psychopharmacology: response to commentaries

Center for Developmental and Health Genetics, Pennsylvania State University, University Park, PA 16802, USA

Gerald E. McClearn

Center for Developmental and Health Genetics, Pennsylvania State University, University Park, PA 16802, USA

Grazyna Gora-Maslak

Center for Developmental and Health Genetics, Pennsylvania State University, University Park, PA 16802, USA

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 F₁ 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.

Journal of Psychopharmacology, Vol. 5, No. 1, 23-28 (1991)
DOI: 10.1177/026988119100500106


CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?