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Plant Quantitative Traits

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AbstractIn plants, most of the phenotypic variations are continuously distributed and could be considered as quantitative traits. The complexity of their genetic control is high because the involved genes are numerous, with usually minor effects and very sensitive to environment. The implicated loci are localised by two basic approaches, linkage mapping and association mapping, based on the use of genetic maps and sophisticated statistical analysis. Linkage mapping leads to the identification of small regions of genome but that could contain still several hundred genes. Identification of gene underlying the quantitative trait loci requires positional cloning or direct tests of promising candidates. Association mapping checks directly the relationship between each polymorphism and phenotypic trait variation in wild populations, but physical linkage and population structure are sources of false positives. Finally, validation that an individual gene is responsible for the quantitative trait needs to be performed by using genetic or functional complementation.Key Concepts:Quantitative traits follow continuous, unbroken quasi‐normal distributions whereas qualitative (mendelian) traits are discreetly distributed.Quantitative traits are controlled by several genes, with small additive, dominant or epistatic effects, and in interaction with the environment.A quantitative trait loci (QTL) is defined as an area of genome associated with an effect on a quantitative trait.The combination of alleles at the many genes involved in a quantitative trait leads to constitute the different phenotypes.QTL mapping relies on statistical linkage analysis among quantitative trait and genetic markers using a population that carries combinations of alleles derived from parental lines.Association mapping looks for association between a genetic marker and phenotype in unrelated individuals by exploiting historical recombination events and genetic diversity.Population structure is the presence of hidden subgroups in wild populations that appear because of relatedness and selection with an unequal distribution of alleles.Physical linkage and population structure are sources of linkage disequilibrium and might influence the genome‐wide association (GWA) mapping by creation of false marker‐trait association.Positional cloning of QTL involves the identification of closely linked recombination events requiring analysis of a large number of segregating progeny with molecular markers covering the critical region.Complete genome sequencing has greatly advanced the use of GWA mapping.
Title: Plant Quantitative Traits
Description:
AbstractIn plants, most of the phenotypic variations are continuously distributed and could be considered as quantitative traits.
The complexity of their genetic control is high because the involved genes are numerous, with usually minor effects and very sensitive to environment.
The implicated loci are localised by two basic approaches, linkage mapping and association mapping, based on the use of genetic maps and sophisticated statistical analysis.
Linkage mapping leads to the identification of small regions of genome but that could contain still several hundred genes.
Identification of gene underlying the quantitative trait loci requires positional cloning or direct tests of promising candidates.
Association mapping checks directly the relationship between each polymorphism and phenotypic trait variation in wild populations, but physical linkage and population structure are sources of false positives.
Finally, validation that an individual gene is responsible for the quantitative trait needs to be performed by using genetic or functional complementation.
Key Concepts:Quantitative traits follow continuous, unbroken quasi‐normal distributions whereas qualitative (mendelian) traits are discreetly distributed.
Quantitative traits are controlled by several genes, with small additive, dominant or epistatic effects, and in interaction with the environment.
A quantitative trait loci (QTL) is defined as an area of genome associated with an effect on a quantitative trait.
The combination of alleles at the many genes involved in a quantitative trait leads to constitute the different phenotypes.
QTL mapping relies on statistical linkage analysis among quantitative trait and genetic markers using a population that carries combinations of alleles derived from parental lines.
Association mapping looks for association between a genetic marker and phenotype in unrelated individuals by exploiting historical recombination events and genetic diversity.
Population structure is the presence of hidden subgroups in wild populations that appear because of relatedness and selection with an unequal distribution of alleles.
Physical linkage and population structure are sources of linkage disequilibrium and might influence the genome‐wide association (GWA) mapping by creation of false marker‐trait association.
Positional cloning of QTL involves the identification of closely linked recombination events requiring analysis of a large number of segregating progeny with molecular markers covering the critical region.
Complete genome sequencing has greatly advanced the use of GWA mapping.

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