The complex relationship between genotype and phenotype can be attributed to individual quantitative trait loci (QTLs). These underling QTLs are often complex in terms of their statistical and biological properties. They could be pleiotropic, linked, linked, developmentally or environmentally plastic, and inter-acting. Statistical methods have been developed to map QTLs and proven to be successful in detecting QTLs of large effects on the phenotype. Yet, these are not vastly adequate, because the application of these methods is limited by the complex nature of QTLs. In this review, we outline recent developments of statistical methods for mapping these complex QTLs within the framework of composite interval mapping. In each section, we discuss the statistical model for dealing with a key topic, followed by computational algorithms. The topics discussed include mapping pleiotropic QTLs for multiple quantitative traits, QTLs linked on the same chromosome, development-dependent QTLs during a growth process, environmentally plastic QTLs causing significant genotype x environment interaction, and epistatic QTLs between which gene effects are not linear. Further considerations for QTL mapping are discussed.
|Original language||English (US)|
|Number of pages||14|
|State||Published - Nov 1 1999|
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