[Objective]The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 F1 families. [Method]In this study,association analysis was conducted in ...[Objective]The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 F1 families. [Method]In this study,association analysis was conducted in 135 F1 families derived from two maize landraces,and the efficiency of this method was evaluated through simulation. [Result]Association analysis with different kinds of families showed that large population size and robust phenotypic data were required for association mapping. For all the phenotypic traits,the model controlling both population structure and relative kinship (Q+K) performed better than the model controlling relative kinship (K),and similarly to the model controlling population structure (Q). Across 100 simulation runs in QULINE,the average power of QTL detection for the two models were 88. 64% and 83. 64% respectively,and the number of false QTL was reduced from 399 with GLM model to 199 with K model. Our simulation results suggested that these F1 families can be used for association analysis,and the power of the QTL detection was related to the maximum allele frequency (MAF) and the phenotypic variation ( PVE) explained by QTL. [Conclusion]The results from this study suggest that association analysis using the F1 families is an effective approach to study maize landraces for discovering elite genes which we are interested in from these special populations.展开更多
基金Surpported by the Key Program of Department of Education of Sichuan Province,China(12ZB097)
文摘[Objective]The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 F1 families. [Method]In this study,association analysis was conducted in 135 F1 families derived from two maize landraces,and the efficiency of this method was evaluated through simulation. [Result]Association analysis with different kinds of families showed that large population size and robust phenotypic data were required for association mapping. For all the phenotypic traits,the model controlling both population structure and relative kinship (Q+K) performed better than the model controlling relative kinship (K),and similarly to the model controlling population structure (Q). Across 100 simulation runs in QULINE,the average power of QTL detection for the two models were 88. 64% and 83. 64% respectively,and the number of false QTL was reduced from 399 with GLM model to 199 with K model. Our simulation results suggested that these F1 families can be used for association analysis,and the power of the QTL detection was related to the maximum allele frequency (MAF) and the phenotypic variation ( PVE) explained by QTL. [Conclusion]The results from this study suggest that association analysis using the F1 families is an effective approach to study maize landraces for discovering elite genes which we are interested in from these special populations.
基金Supported by the Hi-Tech Research and Development (863) Program of China (2004AA211172), the Program for Changjiang Scholars and Innovative Research Team in University of the Ministry of Education (IRT0432) and the National Natural Science Foundation of China (30070483 and 30270806).
文摘用个人们由交叉开发了的 219 F2,基因标准衬里 TM-1and 在 Gossypium hirsutum L. 的多重主导的标记线 T586,与 19linkage 组一起的一张基因连锁图基于简单顺序重复(SSR ) 被构造标记。与 ourtetraploid backboned 相比分子的遗传图谱从一(TM-1 x Hai 7124 ) x TM-1 BC1 人口, 17 个 the19 连接组被联合并且抛锚到 12 个染色体(亚染色体) 。这些组,在 T586 的四词法标记基因被印射进分子的连锁图。同时,为棉绒百分比的三量的特点 loci 在 A03 连接组和染色体上独立被标注并且印射 6 ……