Theoretical Basis for Separation of Multiple Linked Gene Effects in Mapping Quantitative Trait Loci

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 90; no. 23; pp. 10972 - 10976
• Main Author: Zeng, Zhao-Bang
• Format: Journal Article
• Language: English
• Published: Washington, DC National Academy of Sciences of the United States of America 01.12.1993; National Acad Sciences; National Academy of Sciences
• Subjects: 550400 - Genetics; BASIC BIOLOGICAL SCIENCES; Biological and medical sciences; BIOLOGICAL MARKERS; Chromosome Mapping - methods; CHROMOSOMES; Classical genetics, quantitative genetics, hybrids; Covariance; Fundamental and applied biological sciences. Psychology; Genetic Linkage; GENETIC MAPPING; Genetics; Genetics of eukaryotes. Biological and molecular evolution; Genomes; MAPPING; MATHEMATICS; Methods, theories and miscellaneous; Molecules; Multiple regression; Musical intervals; Phenotypic traits; Quantitative trait loci; REGRESSION ANALYSIS; Regression coefficients; Statistical variance; STATISTICS; Tests; Genetic mapping; Quantitative genetics; Statistical test; Linkage; Gene; Genetic marker; Polygenic; Theory; Quantitative character; Chromosome; Mathematical model
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.90.23.10972

It is now possible to use complete genetic linkage maps to locate major quantitative trait loci (QTLs) on chromosome regions. The current methods of QTL mapping (e.g., interval mapping, which uses a pair or two pairs of flanking markers at a time for mapping) can be subject to the effects of other linked QTLs on a chromosome because the genetic background is not controlled. As a result, mapping of QTLs can be biased, and the resolution of mapping is not very high. Ideally when we test a marker interval for a QTL, we would like our test statistic to be independent of the effects of possible QTLs at other regions of the chromosome so that the effects of QTLs can be separated. This test statistic can be constructed by using a pair of markers to locate the testing position and at the same time using other markers to control the genetic background through a multiple regression analysis. Theory is developed in this paper to explore the idea of a conditional test via multiple regression analysis. Various properties of multiple regression analysis in relation to QTL mapping are examined. Theoretical analysis indicates that it is advantageous to construct such a testing procedure for mapping QTLs and that such a test can potentially increase the precision of QTL mapping substantially.