Dataset Information

Association Mapping of Flowering Time QTLs and Insight into Their Contributions to Rapeseed Growth Habits.

ABSTRACT: Plants have developed sophisticated systems to adapt to local conditions during evolution, domestication and natural or artificial selection. The selective pressures of these different growing conditions have caused significant genomic divergence within species. The flowering time trait is the most crucial factor because it helps plants to maintain sustainable development. Controlling flowering at appropriate times can also prevent plants from suffering from adverse growth conditions, such as drought, winter hardness, and disease. Hence, discovering the genome-wide genetic mechanisms that influence flowering time variations and understanding their contributions to adaptation should be a central goal of plant genetics and genomics. A global core collection panel with 448 inbred rapeseed lines was first planted in four independent environments, and their flowering time traits were evaluated. We then performed a genome-wide association mapping of flowering times with a 60 K SNP array for this core collection. With quality control and filtration, 20,342 SNP markers were ultimately used for further analyses. In total, 312 SNPs showed marker-trait associations in all four environments, and they were based on a threshold p-value of 4.06 × 10(-4); the 40 QTLs showed significant association with flowering time variations. To explore flowering time QTLs and genes related to growth habits in rapeseed, selection signals related to divergent habits were screened at the genome-wide level and 117 genomic regions were found. Comparing locations of flowering time QTLs and genes with these selection regions revealed that 20 flowering time QTLs and 224 flowering time genes overlapped with 24 and 81 selected regions, respectively. Based on this study, a number of marker-trait associations and candidate genes for flowering time variations in rapeseed were revealed. Moreover, we also showed that both flowering time QTLs and genes play important roles in rapeseed growth habits. These results will be applied to rapeseed breeding programs, and they will aid in our understanding of the relation between flowering time variations and growth habits in plants.

SUBMITTER: Wang N

PROVIDER: S-EPMC4805649 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Association Mapping of Flowering Time QTLs and Insight into Their Contributions to Rapeseed Growth Habits.

Wang Nian N Chen Biyun B Xu Kun K Gao Guizhen G Li Feng F Qiao Jiangwei J Yan Guixin G Li Jun J Li Hao H Wu Xiaoming X

Frontiers in plant science 20160324

Plants have developed sophisticated systems to adapt to local conditions during evolution, domestication and natural or artificial selection. The selective pressures of these different growing conditions have caused significant genomic divergence within species. The flowering time trait is the most crucial factor because it helps plants to maintain sustainable development. Controlling flowering at appropriate times can also prevent plants from suffering from adverse growth conditions, such as dr ...[more]

PMID: 27047517

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Project description: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.

Project description:BACKGROUND: Seed weight (SW) and silique length (SL) are important determinants of the yield potential in rapeseed (Brassica napus L.). However, the genetic basis of both traits is poorly understood. The main objectives of this study were to dissect the genetic basis of SW and SL in rapeseed through the preliminary mapping of quantitative trait locus (QTL) by linkage analysis and fine mapping of the target major QTL by regional association analysis. RESULTS: Preliminary linkage mapping identified thirteen and nine consensus QTLs for SW and SL, respectively. These QTLs explained 0.7-67.1% and 2.1-54.4% of the phenotypic variance for SW and SL, respectively. Of these QTLs, three pairs of SW and SL QTLs were co-localized and integrated into three unique QTLs. In addition, the significance level and genetic effect of the three co-localized QTLs for both SW and SL showed great variation before and after the conditional analysis. Moreover, the allelic effects of the three QTLs for SW were highly consistent with those for SL. Two of the three co-localized QTLs, uq.A09-1 (mean R(2) = 20.1% and 19.0% for SW and SL, respectively) and uq.A09-3 (mean R(2) = 13.5% and 13.2% for SW and SL, respectively), were detected in all four environments and showed the opposite additive-effect direction. These QTLs were validated and fine mapped (their confidence intervals were narrowed down from 5.3 cM to 1 cM for uq.A09-1 and 13.2 cM to 2.5 cM for uq.A09-3) by regional association analysis with a panel of 576 inbred lines, which has a relatively rapid linkage disequilibrium decay (0.3 Mb) in the target QTL region. CONCLUSIONS: A few QTLs with major effects and several QTLs with moderate effects might contribute to the natural variation of SW and SL in rapeseed. The meta-, conditional and allelic effect analyses suggested that pleiotropy, rather than tight linkage, was the genetic basis of the three pairs of co-localized of SW and SL QTLs. Regional association analysis was an effective and highly efficient strategy for the direct fine mapping of target major QTL identified by preliminary linkage mapping.

Dataset Information

Association Mapping of Flowering Time QTLs and Insight into Their Contributions to Rapeseed Growth Habits.

Publications

Association Mapping of Flowering Time QTLs and Insight into Their Contributions to Rapeseed Growth Habits.

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