1. Efficiently Tracking Selection in a Multiparental Population: The Case of Earliness in Wheat
- Author
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Jérôme Enjalbert, Ian Mackay, David Gouache, Gwendal Restoux, Stéphanie Thépot, Isabelle Goldringer, Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), Institut National de la Recherche Agronomique (INRA)-Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Ecologie Systématique et Evolution (ESE), Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Station Expérimentale, ARVALIS - Institut du végétal [Paris], National Institute of Agricultural Botany (NIAB), Arvalis Institut du Vegetal, 'Biologie et Amelioration des Plantes' department of Institut National de la Recherche Agronomique, National Institute of Agricultural Botany, Ministere de l'Enseignement Superieur et de la Recherche, Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Recherche Agronomique (INRA), and AgroParisTech-Institut National de la Recherche Agronomique (INRA)
- Subjects
MPP ,0106 biological sciences ,Linkage disequilibrium ,Genotype ,[SDV]Life Sciences [q-bio] ,Quantitative Trait Loci ,Population ,recombinant population ,Outcrossing ,Investigations ,Biology ,Polymorphism, Single Nucleotide ,01 natural sciences ,Chromosomes, Plant ,Evolution, Molecular ,03 medical and health sciences ,Gene Frequency ,Genetic drift ,Genetics ,experimental evolution ,Selection, Genetic ,Association mapping ,education ,Allele frequency ,Alleles ,Crosses, Genetic ,Triticum ,Selection (genetic algorithm) ,030304 developmental biology ,2. Zero hunger ,0303 health sciences ,education.field_of_study ,Panmixia ,Models, Genetic ,parental contribution ,selection detection ,Genetics, Population ,Phenotype ,multiparental populations ,Multiparent Advanced Generation Inter-Cross (MAGIC) ,QTL detection ,Algorithms ,Genome-Wide Association Study ,010606 plant biology & botany - Abstract
Multiparental populations are innovative tools for fine mapping large numbers of loci. Here we explored the application of a wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population for QTL mapping. This population was created by 12 generations of free recombination among 60 founder lines, following modification of the mating system from strict selfing to strict outcrossing using the ms1b nuclear male sterility gene. Available parents and a subset of 380 SSD lines of the resulting MAGIC population were phenotyped for earliness and genotyped with the 9K i-Select SNP array and additional markers in candidate genes controlling heading date. We demonstrated that 12 generations of strict outcrossing rapidly and drastically reduced linkage disequilibrium to very low levels even at short map distances and also greatly reduced the population structure exhibited among the parents. We developed a Bayesian method, based on allelic frequency, to estimate the contribution of each parent in the evolved population. To detect loci under selection and estimate selective pressure, we also developed a new method comparing shifts in allelic frequency between the initial and the evolved populations due to both selection and genetic drift with expectations under drift only. This evolutionary approach allowed us to identify 26 genomic areas under selection. Using association tests between flowering time and polymorphisms, 6 of these genomic areas appeared to carry flowering time QTL, 1 of which corresponds to Ppd-D1, a major gene involved in the photoperiod sensitivity. Frequency shifts at 4 of 6 areas were consistent with earlier flowering of the evolved population relative to the initial population. The use of this new outcrossing wheat population, mixing numerous initial parental lines through multiple generations of panmixia, is discussed in terms of power to detect genes under selection and association mapping. Furthermore we provide new statistical methods for use in future analyses of multiparental populations.
- Published
- 2014
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