Scientia Agricultura Sinica ›› 2014, Vol. 47 ›› Issue (14): 2699-2714.doi: 10.3864/j.issn.0578-1752.2014.14.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS •     Next Articles

Heterosis loci and QTL of Super Hybrid Rice Liangyoupeijiu Yield by Using Molecular Marker

 XIN  Ye-Yun-1, 2 , YUAN  Long-Ping-1, 2   

  1. 1、State Key Laboratory of Hybrid Rice, Changsha 410125/Wuhan 430072;
    2、China National Hybrid Rice R&D Center, Changsha 410125
  • Received:2014-01-14 Online:2014-07-15 Published:2014-04-08

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Abstract: 【Objective】 The heterosis loci and QTLs of yield and yield components were detected by using a RILsBCF1 population derived from a cross between Pei’ai 64S and 9311. The relationship was explored between the genetic variance of these two parental lines and yield heterosis in the resulted hybrid for predicting hybrid heterosis.【Method】Based on a population of 219 recombinant inbred lines (RILs) of F8 generation produced by single seed descendant method from the Pei’ai 64S×9311 cross, a RILsBCF1 population was generated by backcrossing of RILs to Pei’ai 64S. With a total of 151 polymorphic SSR markers, a linkage map was constructed spanning 1 617.7 cM across the whole genome with an average marker interval of 10.93 cM. The correlation between genetic distances and F1 trait performance of RILsBCF1 and their prediction in yield and yield component traits were conducted respectively by using molecular marker analysis, one-way ANOVA with different freedoms, and composite interval mapping using mix linear model in SAS, together with heterosis prediction and QTL mapping. 【Result】The RILsBCF1 used in the study showed significant diversity with high segregation in multiple traits, and their average performance was significantly higher than that of RILs F8. In this RILsBCF1 population, 74 heterosis positive loci and effect-increasing loci were identified by two-group method and three-group method in yield and yield component traits, respectively. Compared with two-group method, three-group method could get more positive loci or effect-increasing loci to a certain degree and raise efficiency of predicting correlationship between genetic distances of both positive loci and effect-increasing loci and F1 traits’ performances. The result of the effect-increasing loci detecting was the same in both two-group and three-group methods. Six heterosis loci were detected at the same regions for three traits (Sterile lemma per panicle, Grains per panicle and Pencentage seed setting), overlapped with three yield effect-increasing loci clustered on chromosome 7. Based on the relationship between marker-effect values of yield effect-increasing loci using the three-group method and F1 trait performance, four multiple regression prediction models were constructed using a stepwise procedure. A total of 28 markers with heterozygous genotypes were identified to significantly increase the correlation coefficient between the genetic distances and the F1 trait performance from 0.335 to 0.617. Three QTLs for yield heterosis and three QTLs for grain per panicle heterosis were mapped using this RILsBCF1 population. The mapped loci of QTL QGpp7 for grain per panicle heterosis and QHy7 for yield heterosis matched the effect-increasing loci identified by the methods of two-group and three group analyses. 【Conclusion】The approaches of screening more positive loci or effect-increasing loci and specific markers which influent heterosis can increase the correlation coefficient between the genetic distances and the F1 traits performances, and thus can be applied more efficiently in predicting the yield heterosis of rice hybrids with genetic distance of molecular markers. The yield QTL QHy7 located on chromosome 7 with a yield increase contribution of 7.48% can be used for yield heterosis prediction and in hybrid rice breeding. A heading stage QTL located between RM293-RM468 on chromosome 3 with the contribution of 14.9% can be used for rareripe high yield rice breeding.

Key words: super-yielding hybrid rice , yield component trait heterosis , heterosis prediction , QTL mapping

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