Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet

Epistasis is defined as interactions between alleles of two or more genetic loci. Detection of epistatic interactions is the key to understand the genetic architecture and gene networks underlying complex traits. Here, we examined the extent of epistasis for seven quantitative traits with an associa...

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Bibliographic Details
Published in:Theoretical and applied genetics 2011-06, Vol.123 (1), p.109-118
Main Authors: Würschum, Tobias, Maurer, Hans Peter, Schulz, Britta, Möhring, Jens, Reif, Jochen Christoph
Format: Article
Language:English
Subjects:
Agricultural production
Agriculture
alleles
Beta vulgaris
Beta vulgaris - genetics
Biochemistry
Biological and medical sciences
Biomedical and Life Sciences
Biotechnology
Botanical research
Breeding
Chromosome Mapping
Classical genetics, quantitative genetics, hybrids
Crosses, Genetic
epistasis
Epistasis, Genetic
Estimates
Fundamental and applied biological sciences. Psychology
Gene expression
Gene loci
Genetic aspects
Genetic Association Studies - methods
Genetics of eukaryotes. Biological and molecular evolution
Genome-wide association studies
Genomes
Genotype
kinship
Life Sciences
loci
Methods, theories and miscellaneous
Models, Genetic
Original Paper
Phenotype
Physiology
Plant Biochemistry
Plant Breeding/Biotechnology
Plant Genetics and Genomics
Potassium
Pteridophyta, spermatophyta
Quantitative Trait Loci
quantitative traits
Sugar beet
variance
Vegetals
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Summary:Epistasis is defined as interactions between alleles of two or more genetic loci. Detection of epistatic interactions is the key to understand the genetic architecture and gene networks underlying complex traits. Here, we examined the extent of epistasis for seven quantitative traits with an association mapping approach in a large population of elite sugar beet lines. We found that correction for population stratification is required and that in terms of reducing the false-positive rate the mixed model approach including the kinship matrix performed best. In genome-wide scans, we detected both main effects and epistatic QTL. For physiological traits, the detected digenic and higher-order epistasis explained a considerable proportion of the genotypic variance. We illustrate that the identified epistatic interactions define comprehensive genetic networks, which may serve as starting points towards a systems-oriented approach to understand the regulation of complex traits.
ISSN:0040-5752
1432-2242
DOI:10.1007/s00122-011-1570-3