Statistical models for the detection of genes controlling quantitative trait loci expression
Many important traits in plant breeding exhibit continuous variation (yield, maturity, biotic and abiotic stress tolerance, etc.). The genetic principles underlying their inheritance are basically the same as those affecting Mendelian or qualitative traits, but since the segregation of the genes concerned could be followed individually, new methods and concepts had to be developed. In this presentation, the task of searching for genes affecting quantitative, or continuous, traits will be considered. The immediate hope is the possibility of identifying specific portions of the genome involved in the variation of these traits (called QTLs) in order to enhance breeding programs. Moreover, the long term hope is finding the location of these genes to characterize and manipulate them to our advantage. Therefore, we will try to discuss the different statistical models used for QTL analysis and the power of different approaches. QTL analysis have been approached using different statistical strategies depending on the number of markers involved in the analysis. Early studies considered the relationship between a marker and a QTL; later, models considered a pair of markers flanking the QTL and studied the association between the QTL and the interval defined by the flanking markers. More recently, statistical methodologies focus their attention to consider the whole linkage group considering all markers of the group as being associated with the QTL. Although any type of classification of statistical approaches is always incomplete and biased, we will try to describe the current statistical models organized according to the number of markers studied and by the basic statistical methodology being employed. The practical implications of the approach will be discussed presenting a study on genotype by environment interactions for 15 traits in almonds investigated during 2-3 years by means of isozymatic markers.
| Main Author: | |
|---|---|
| Format: | Book Chapter biblioteca |
| Language: | English |
| Published: |
International Center for Tropical Agriculture
1995
|
| Subjects: | linear models, genetic markers, genetic variation, genotype environment interaction, modelos lineales, marcadores genéticos, variación genética, interacción genotipo ambiente, |
| Online Access: | https://hdl.handle.net/10568/82010 http://ciat-library.ciat.cgiar.org/Articulos_Ciat/Digital/SB123.E9C.2_An_exchange_of_experiences_from_South_and_South_East_Asia.pdf#page=150 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Many important traits in plant breeding exhibit continuous variation (yield, maturity, biotic and abiotic stress tolerance, etc.). The genetic principles underlying their inheritance are basically the same as those affecting Mendelian or qualitative traits, but since the segregation of the genes concerned could be followed individually, new methods and concepts had to be developed. In this presentation, the task of searching for genes affecting quantitative, or continuous, traits will be considered. The immediate hope is the possibility of identifying specific portions of the genome involved in the variation of these traits (called QTLs) in order to enhance breeding programs. Moreover, the long term hope is finding the location of these genes to characterize and manipulate them to our advantage. Therefore, we will try to discuss the different statistical models used for QTL analysis and the power of different approaches. QTL analysis have been approached using different statistical strategies depending on the number of markers involved in the analysis. Early studies considered the relationship between a marker and a QTL; later, models considered a pair of markers flanking the QTL and studied the association between the QTL and the interval defined by the flanking markers. More recently, statistical methodologies focus their attention to consider the whole linkage group considering all markers of the group as being associated with the QTL. Although any type of classification of statistical approaches is always incomplete and biased, we will try to describe the current statistical models organized according to the number of markers studied and by the basic statistical methodology being employed. The practical implications of the approach will be discussed presenting a study on genotype by environment interactions for 15 traits in almonds investigated during 2-3 years by means of isozymatic markers. |
|---|