Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome
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Chardon, F
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CNRS, INRA, INA PG, UPS,Stn Genet Vegetale, F-91190 Gif Sur Yvette, FranceCNRS, INRA, INA PG, UPS,Stn Genet Vegetale, F-91190 Gif Sur Yvette, France
Chardon, F
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Virlon, B
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机构:CNRS, INRA, INA PG, UPS,Stn Genet Vegetale, F-91190 Gif Sur Yvette, France
Virlon, B
Moreau, L
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Moreau, L
Falque, M
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Falque, M
Joets, J
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Joets, J
Decousset, L
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Decousset, L
Murigneux, A
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Murigneux, A
Charcosset, A
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机构:CNRS, INRA, INA PG, UPS,Stn Genet Vegetale, F-91190 Gif Sur Yvette, France
Charcosset, A
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[1] CNRS, INRA, INA PG, UPS,Stn Genet Vegetale, F-91190 Gif Sur Yvette, France
Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview Statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in die precision in QTL position estimation, Mien compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections front a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.