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首页> 外文期刊>Oryza >Assessment of polymorphism at molecular level, association studies, multivariate analysis and genetic diversity among recombinant inbred lines of rice (Oryza sativa L.)
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Assessment of polymorphism at molecular level, association studies, multivariate analysis and genetic diversity among recombinant inbred lines of rice (Oryza sativa L.)

机译:分子水平,结合研究,多变量分析和稻米重组近交系中的多元分析和遗传多样性评估(Oryza Sativa L.)

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Five hundred twenty nine microsatellite markers were used to assess polymorphism at molecular level between six rice cultivars, PDKVShriram, Heera, AC38562, Pimpudibasa, Reeta and WAB56-50 having wide variation in yield and related traits. Ninety four(17.76%) microsatellite markers showed polymorphism between these six cultivars. Maximum polymorphism was detected between Reeta and WAB56-50 (34.02%), followed by AC38562 and Pimpudibasa (31.76%), and PDKV Shriram and Heera (27.22%). The recombinant inbred line (RIL) mapping population developed from Reeta and WAB56-50 were used for assessing genetic variability based on the yield and its component traits. The analysis revealed the significant difference among the RILs for all the yield traits. Correlation and path analysis revealed the strong association of grain yield with traits like grain number, thousand grain weight, panicle length and total spikelets per panicle. Further, principal component analysis indicated 58.12% of the total variation explained by first four principal components. Therefore, these RILs could be used for mapping of QTLs associated with yield and its component traits. The polymorphic markers identified in the present study would be usefulfor mapping QTLs associated with yield and its component traits.
机译:使用五百二十九种微卫星标记物来评估六种水稻品种,Pdkvshriram,Heera,AC38562,Pimpudibasa,Reeta和WAB56-50之间的多态性,其产量和相关性状的变化。九十四(17.76%)微卫星标记显示这六种品种之间的多态性。在Reeta和Wab56-50之间检测到最大多态性(34.02%),其次是AC38562和Pimpudibasa(31.76%)和PDKV Shriram和Heera(27.22%)。从Reeta和WAB56-50中产生的重组近交系数(RIL)映射群用于基于产量及其组分特征评估遗传变异性。分析显示所有收益率特征的rils之间的显着差异。相关性和路径分析显示谷物数,粒子重量,千粒重,穗长和总穗根总刺粒产量强的晶粒产量强的强烈关联。此外,主成分分析表明前四个主要成分解释的总变化的58.12%。因此,这些RIL可以用于映射与产量及其组分特征相关的QTL。本研究中鉴定的多态标志物将是用于映射与产量及其组分特征相关的QTL。

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