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Linkage and association mapping of Arabidopsis thaliana flowering time in nature.

Brachi B, Faure N, Horton M, Flahauw E, Vazquez A, Nordborg M, Bergelson J, Cuguen J, Roux F - PLoS Genet. (2010)

Bottom Line: We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters.Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study.Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire Génétique et Evolution des Populations Végétales, Unité Mixte de Recherche CNRS 8016, Université des Sciences et Technologies de Lille 1, Villeneuve d'Ascq, France.

ABSTRACT
Flowering time is a key life-history trait in the plant life cycle. Most studies to unravel the genetics of flowering time in Arabidopsis thaliana have been performed under greenhouse conditions. Here, we describe a study about the genetics of flowering time that differs from previous studies in two important ways: first, we measure flowering time in a more complex and ecologically realistic environment; and, second, we combine the advantages of genome-wide association (GWA) and traditional linkage (QTL) mapping. Our experiments involved phenotyping nearly 20,000 plants over 2 winters under field conditions, including 184 worldwide natural accessions genotyped for 216,509 SNPs and 4,366 RILs derived from 13 independent crosses chosen to maximize genetic and phenotypic diversity. Based on a photothermal time model, the flowering time variation scored in our field experiment was poorly correlated with the flowering time variation previously obtained under greenhouse conditions, reinforcing previous demonstrations of the importance of genotype by environment interactions in A. thaliana and the need to study adaptive variation under natural conditions. The use of 4,366 RILs provides great power for dissecting the genetic architecture of flowering time in A. thaliana under our specific field conditions. We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters. We show that QTL mapping increases our power to distinguish true from false associations in GWA mapping. QTL mapping also permits the identification of false negatives, that is, causative SNPs that are lost when applying GWA methods that control for population structure. Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study. Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock. Furthermore, we identified new genomic regions lacking obvious candidate genes.

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Distribution of the Col-0 additive allelic effect in the 2007–2008 field experiment.Histogram of additive allele estimates for the flowering time for all the 12 RIL families that have Col-0 as a common parental line relative to Col-0.
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pgen-1000940-g004: Distribution of the Col-0 additive allelic effect in the 2007–2008 field experiment.Histogram of additive allele estimates for the flowering time for all the 12 RIL families that have Col-0 as a common parental line relative to Col-0.

Mentions: Given the large population size of each RIL family and the high heritability associated with flowering time, we were able to detect QTLs that account for a small percentage of phenotypic variation within each RIL family. The percentage of phenotypic variation explained by an additive QTL averaged 9.08% and ranged from below 1% (Tsu-0×Col-0, Ct-1×Col-0 and Bay-0×Shahdara) to 45.6% (Cvi-0×Col-0) (Figure 4). In a comparison of the 12 RIL families that have Col-0 as a common parental line, we found that the additive effects of Col-0 alleles range, in absolute values, from 4.19 to 48.09 photothermal units. As expected from the transgressive segregation observed within each RIL family, the distribution of the effects of the Col-0 allele is clearly bimodal, the first mode corresponding to QTLs having negative effects (the Col-0 allele makes plant flower earlier), and the second mode corresponding to QTLs having positive effects (the Col-0 allele makes plant flower later). A less stringent significance level for QTL detection and QTL effects (P = 0.10) did not affect the bimodal distribution of the Col-0 allele effects. Among the 54 additive QTLs detected in these 12 RIL families, 19 have negative effects (∼35.2%) and 35 have positive effects (∼64.8%).


Linkage and association mapping of Arabidopsis thaliana flowering time in nature.

Brachi B, Faure N, Horton M, Flahauw E, Vazquez A, Nordborg M, Bergelson J, Cuguen J, Roux F - PLoS Genet. (2010)

Distribution of the Col-0 additive allelic effect in the 2007–2008 field experiment.Histogram of additive allele estimates for the flowering time for all the 12 RIL families that have Col-0 as a common parental line relative to Col-0.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2865524&req=5

pgen-1000940-g004: Distribution of the Col-0 additive allelic effect in the 2007–2008 field experiment.Histogram of additive allele estimates for the flowering time for all the 12 RIL families that have Col-0 as a common parental line relative to Col-0.
Mentions: Given the large population size of each RIL family and the high heritability associated with flowering time, we were able to detect QTLs that account for a small percentage of phenotypic variation within each RIL family. The percentage of phenotypic variation explained by an additive QTL averaged 9.08% and ranged from below 1% (Tsu-0×Col-0, Ct-1×Col-0 and Bay-0×Shahdara) to 45.6% (Cvi-0×Col-0) (Figure 4). In a comparison of the 12 RIL families that have Col-0 as a common parental line, we found that the additive effects of Col-0 alleles range, in absolute values, from 4.19 to 48.09 photothermal units. As expected from the transgressive segregation observed within each RIL family, the distribution of the effects of the Col-0 allele is clearly bimodal, the first mode corresponding to QTLs having negative effects (the Col-0 allele makes plant flower earlier), and the second mode corresponding to QTLs having positive effects (the Col-0 allele makes plant flower later). A less stringent significance level for QTL detection and QTL effects (P = 0.10) did not affect the bimodal distribution of the Col-0 allele effects. Among the 54 additive QTLs detected in these 12 RIL families, 19 have negative effects (∼35.2%) and 35 have positive effects (∼64.8%).

Bottom Line: We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters.Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study.Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire Génétique et Evolution des Populations Végétales, Unité Mixte de Recherche CNRS 8016, Université des Sciences et Technologies de Lille 1, Villeneuve d'Ascq, France.

ABSTRACT
Flowering time is a key life-history trait in the plant life cycle. Most studies to unravel the genetics of flowering time in Arabidopsis thaliana have been performed under greenhouse conditions. Here, we describe a study about the genetics of flowering time that differs from previous studies in two important ways: first, we measure flowering time in a more complex and ecologically realistic environment; and, second, we combine the advantages of genome-wide association (GWA) and traditional linkage (QTL) mapping. Our experiments involved phenotyping nearly 20,000 plants over 2 winters under field conditions, including 184 worldwide natural accessions genotyped for 216,509 SNPs and 4,366 RILs derived from 13 independent crosses chosen to maximize genetic and phenotypic diversity. Based on a photothermal time model, the flowering time variation scored in our field experiment was poorly correlated with the flowering time variation previously obtained under greenhouse conditions, reinforcing previous demonstrations of the importance of genotype by environment interactions in A. thaliana and the need to study adaptive variation under natural conditions. The use of 4,366 RILs provides great power for dissecting the genetic architecture of flowering time in A. thaliana under our specific field conditions. We describe more than 60 additive QTLs, all with relatively small to medium effects and organized in 5 major clusters. We show that QTL mapping increases our power to distinguish true from false associations in GWA mapping. QTL mapping also permits the identification of false negatives, that is, causative SNPs that are lost when applying GWA methods that control for population structure. Major genes underpinning flowering time in the greenhouse were not associated with flowering time in this study. Instead, we found a prevalence of genes involved in the regulation of the plant circadian clock. Furthermore, we identified new genomic regions lacking obvious candidate genes.

Show MeSH