In the present investigation, experiments were conducted to evaluate F₃ and F₄ populations derived from cross between PAU201 (high-yield) and Palman 579 (iron-rich) indica rice varieties for various physio-morphological traits and minerals (iron and zinc) content. Phenotypic correlation analysis showed no correlation between grain iron and zinc content in F₃ and F₄ population (s). A DNA fingerprint database of 33 PAU201 × Palman 579 derived F₄ plants was prepared using 61 polymorphic SSR markers distributed on the entire genome of rice. The results of NTSYS-pc UPGMA tree cluster analysis and two and three dimensional principal component analysis (PCA) scaling showed scattering of the F₄ population between the two distinct parent genotypes; but more inclined towards Palman 579. The SSR data was used to identify quantitative trait loci (QTL) for grain mineral content and physio-morphological traits. A total of 128 alleles and three new recombinant alleles were identified in F₄ plants population. Composite interval mapping (CIM) analysis by WinQTL cartographer 2.5 revealed a total of six QTLs for mineral content (five for iron and one for zinc) in rice grains on chromosome 5, 6, 7, 9 and sixteen QTLs for various physio-morphological traits on chromosomes 2, 5, 7, 8, 9, 10 and 12. Linkage mapping of QTLs of minerals (iron and zinc) can greatly enhance the efficacy of breeding programs to improve mineral density in rice. The QTLs for minerals identified can successfully employed to improve the target traits through marker assisted selection.

中文翻译：

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谷物矿物质（铁和锌）的QTL连锁图谱以及富矿水稻（Oryza sativa L.）发育的生理形态性状

在本研究中，进行实验，以评估˚F ₃和F _4个从横PAU201（高收率）和八万579之间衍生群体（富铁）籼稻水稻品种的各种生理形态性状和矿物质（铁和锌）内容。表型相关性分析表明，F ₃和F ₄群体中的谷物铁和锌含量没有相关性。33个PAU201×Palman 579衍生的F _4的DNA指纹数据库使用分布在水稻整个基因组上的61个多态性SSR标记来制备植物。NTSYS-pc UPGMA树聚类分析和二维和三维主成分分析（PCA）缩放结果表明，F ₄种群在两个不同的亲本基因型之间散布。但更倾向于Palman579。SSR数据用于识别谷物矿物质含量和生理形态性状的数量性状位点（QTL）。在F _4中总共鉴定了128个等位基因和3个新的重组等位基因植物种群。WinQTL制图师2.5进行的复合区间作图（CIM）分析显示，共有5个，6、7、9、9号染色体上的水稻籽粒中矿物质含量的六个QTL（铁中的五个，锌中的一个）和十六个不同生理形态性状的QTL矿物（铁和锌）的QTL连锁图谱可以大大提高育种程序提高水稻中矿物质密度的效率。鉴定出的矿物的QTL可通过标记辅助选择成功地用于改善目标性状。