Quantitative Trait Locus (QTL) Mapping For 100-kernel Weight In Maize Using A Doubled Haploid Population Derived From A Cross Of Nongda333×Nongda335

Kernel weight is one of the important components of maize yield characters, and it is one of the key traits of maize high yield breeding. QTL mapping and cloning of kernel weight are important to elucidate the complex molecular genetic mechanism of yield traits. Meanwhile they are important to exploit the genetic potential of Maize Yield and to improve the efficiency of breeding. After a few years of development, DH(haploid doubled) lines is a good population which can be used to QTL mapping for quantitative traits such as yield. The DH lines of Nongda333×Nongda335 was constructed in Hebei. 190 DH lines were obtained. The DH lines were planted in four environments of Beijing, Hebei, Shandong and Hainan in 2015. The genetic linkage map was constructed and 15 QTL were identified for HKW(100-kernel weight). It has laid the foundation for further fine mapping and positional cloning of HKW. And it also provided a reference for quantitative traits QTL using DH lines. The pecific results were as follows:(1) Nongda 125 was derived from a cross of Nongda333×Nongda335. In 2013, haploid population derived from the cross Nongda 125×HHI69. In 2014, the haploid population was doubled by using APM(amiprophos-methyl). And 190 DH lines were obtained after screening.(2) The DH lines were planted in four environments of Beijing, Hebei, Shandong and Hainan in 2015. QTL were identified for HKW. 6 QTL were identified in Beijing, locating on the chromosome 1, 4, 9, 10. Each of these QTL could explain 7.64%-16.37% of the phenotypic variation of HKW. 5 QTL were identified in Hebei, locating on the chromosome 1, 4, 9. Each of these QTL could explain 7.29%-11.78% of the phenotypic variation of HKW. 5 QTL were identified in Shandong, locating on the chromosome 1, 4, 9, 10. Each of these QTL could explain 7.09%-21.31% of the phenotypic variation of HKW. 8 QTL were identified in Hainan, locating on the chromosome 1, 4, 5, 9, 10. Each of these QTL could explain 5.18%-44.35% of the phenotypic variation of HKW.(3) 15 QTL were identified in Beijing, Hebei, Shandong and Hainan for HKW. 1 QTL for HKW were identified in four environments. It accounted for 6.67% of the total number of QTL for HKW. The QTL was detected in marker of interval umc1916-bnlg181 on chromosome 1. It could explain 10.77%-44.35% of the phenotypic variation of HKW. It was named q HKW1-1. The q HKW1-1 has a great contribution rate for grain weight. The genetic of q HKW1-1 was stability. So q HKW1-1 can be used in fine mapping in the further.(4) 1 QTL for HKW were identified in three environments. They accounted for 6.67% of the total number of QTL for HKW. The QTL was detected in marker of interval bnlg2162-bnlg589 on chromosome 4. It could explain 7.79%-18.75% of the phenotypic variation of HKW. It was named q HKW4.(5) 4 QTL for HKW were identified in two environments. They accounted for 26.67% of the total number of QTL for HKW. 9 QTL for HKW were identified in one environment. They accounted for 60% of the total number of QTL for HKW. And these totalled 86.67%. It showed that environment was an important factor affecting the QTL mapping for quantitative traits.