水稻轮回选择群体XTBG-HP1表型遗传多样性分析

该研究基于4个陆稻群体及172个水稻品种或杂交组合,构建了水稻多亲本隐性核不育轮回选择群体XTBG-HP1,并经过4次轮回重组,采用16个表型性状对其进行了遗传多样性分析。结果表明:(1)该群体14个数量性状符合正态分布,各表型均存在极端性状个体。(2)数量性状变异系数范围为0.08～0.41,均值为0.20; Shannon-Wiener多样性指数范围为0.72～1.92,均值为1.50。(3)群体在株型与产量构成因子性状方面有显著的相关性,对株型的选择可以实现产量性状的改良。(4)剑叶长、每穗粒总数、千粒重、穗长、粒长、一次枝梗数、有效穗数、剑叶宽、二次枝梗数、抽穗期10个性状可作为群体综合评价指标。(5)剑叶长、二次枝梗数、每穗粒总数3个表型性状具有较高的遗传变异、丰富的遗传多样性及与综合得分F值相关系数较高。综合以上结果发现,后期群体进行基因挖掘、品种改良以及优良育种材料的选育可以基于剑叶长、二次枝梗数及每穗粒总数3个表型性状,同时要充分利用群体株型与产量构成因子性状间的显著相关性。此外,该研究群体中极端单性状或综合得分F值较高的个体,可进一步用于品种选育。

Phenotypic diversity analysis of rice recurrent selection population XTBG-HP1

Genetic diversity is the basis of gene mining, cultivars improvement and breeding, the genetic diversity analysis of recurrent selection population could provide reference and guidance for further population improvement and elite cultivars screening. In this study, we constructed the rice recurrent selection population XTBG-HP1 based on four upland rice populations and 172 rice cultivars or combination, and we evaluated the genetic diversity of the rice population, by using sixteen phenotypic traits after four recurrent combinations. The results were as follows:(1)The fourteen quantitative traits of study population were normal distribution, and there were extreme trait individuals in each phenotype.(2)The coefficient variation of fourteen quantitative traits ranged from 0.08 to 0.41 with a mean of 0.20. Shannon-Wiener diversity index of each trait ranged from 0.72 to 1.92 with a mean of 1.50.(3)There was significant correlation between plant type traits and yield components traits in population, indicating the selection of population plant type could improve population yield traits.(4)The ten traits of flag leaf length, total number of per panicle, 1 000-Grain weight, panicle length, grain length, primary branch number, effective panicle, flag leaf width, the secondary branch number and heading date could be used as indicators for population comprehensive evaluation.(5)The flag leaf length, the secondary branch number and total number of per panicle with high genetic variation, better genetic diversity and high correlation coefficient with composite scores F value. The results of comprehensive experiment analysis showed that the research population has abundant genetic diversities. The late population gene mining, selection of good breeding materials and varieties improvement can be place emphasis on flag leaf length, the secondary branch number, and total number of per panicle, and make the best of the correlation between plant type traits and yield components traits. In addition, individuals with extreme single trait or higher F value in the study population can also be further used for cultivars improvement.