With the recent resurgence of an emphasis on complex traits, new approaches and experimental crosses are being developed. Genes modulating the complexities of brain biology and behavioral, as well as gene environment interactions have been particularly difficult to identify. In order to overcome some of these deficiencies, we will develop simple yet accurate statistical methods for complex quantitative trait loci mapping using recently described recombinant inbred intercrosses (RIX). Thus the specific aims are to 1) Develop appropriate statistical analysis tools for the RIX design; 2) Derive appropriate significance thresholds of the test statistics empirically and theoretically; and 3) Develop open source software to implement RIX methods. The approaches we describe in this small project will greatly aid developments in complex trait dissection and should lead to greater precision and more accurate localization of the causative genes in a wide variety of research applications, not the least of which is the role of genes in neurological diseases.
| Huang, Hanwen; Eversley, Chevonne D; Threadgill, David W et al. (2007) Bayesian multiple quantitative trait loci mapping for complex traits using markers of the entire genome. Genetics 176:2529-40 |
| Zou, Fei; Xu, Zongli; Vision, Todd (2006) Assessing the significance of quantitative trait loci in replicable mapping populations. Genetics 174:1063-8 |
| Zou, Fei; Gelfond, Jonathan A L; Airey, David C et al. (2005) Quantitative trait locus analysis using recombinant inbred intercrosses: theoretical and empirical considerations. Genetics 170:1299-311 |
