| High-oil corn was a new type of high value-added corn by artificial cultivation in the 20th century with its comprehensive kernel nutritional quality traits and higher value. At present, grain yield determined by ear-kernel characters was still a main limitation in the large scale utilization of high-oil corn hybrids. Previous researches about QTL mapping for grain yield and its components have been conducted with IHO and BHO high-oil corn germplasms. In this study, 284 and 265 F2:3 family lines were respectively developed from two crosses between the same high-oil corn inbred GY220 with ASK germplasms and two normal corn inbreds, 8984 and 8622. The field experiments were conducted under two different environments, Luoyang in spring and Xuchang in summer. SSR markers were used to construct high-density genetic maps. Using composite interval mapping (CIM) method, QTL mapping was conducted under the two environments individually and conbined. The eight ear-kernel characters included grain weight (GW), grain weight per plant (GWP), 100 grain weight (100GW), ear length (EL), kernel number per row (RKN), ear diameter (ED), row number per ear (ERN) and kernel rate (KR). The interactions among detected QTL were identified using multiple interval mapping (MIM) method according to the result of CIM method. Conditional QTL mapping and joint QTL analysis among main ear-kernel characters and grain weight with two kernel nutritional quality characters were done using CIM method of multiple traits analysis. Our objectives were to reveal the molecular genetic mechanism of grain yield components. These results will do great help in fine mapping QTL associated with ear-kernel characters and their map-based cloning, and in marker-assisted selection in high-oil maize breeding. The main results were as follows:1. For the two connected F2:3 populations (P1F2:3 and P2F2:3 ), 185 and 173 pairs of SSR markers were selected respectively to construct the maize genetic linkage maps. The genetic distance was 2111.7 cM and 2298.5 cM, with an average of 11.41 cM and 13.29 cM , respectively. Only 83 pairs of markers were in common between the two connected populations.2. 91 QTL were detected for 8 ear-kernel characters using the two F2:3 populations analyed under two environments individually and combined. 52 and 39 QTL were detected in P1F2:3 population and P2F2:3 population. Contribution of single QTL to phenotypic variation varied from 4.8% to 17.0% and from 4.2% to 48.4%, repectively. In P1F2:3 population, only one QTL was detected under two different environments and in combined analysis. Nine QTL were detected under one environment and in combined analysis. In P2F2:3 population, five QTL were detected under one environment and combination analysis. Most interactions among detected QTL were small, except for ED (umc2256～umc2118 and umc2118～umc1746) in Luoyang in P1F2:3 population and KR (qKR2-4-1 and bnlg1194～umc1304) in combined analysis and 100GW (qx100GW2-1-1and bnlg1792～umc1666) in Xuchang in P2F2:3 population. Major QTL for 100GW (ql100GW1-3-1/q100GW1-3-2, qx100GW1-6-1/q100GW1-6-1 and qx100GW2-1-1/q100GW2-1-1), EL (qlEL2-10-1/qEL2-10-1), ERN (qxERN1-3-2/ qERN1-3-2 and qlERN2-5-2/ qERN2-5-1) and KR (qlKR1-7-1/qxKR1-7-1/qKR1-7-1) with higher contributions and stability could be used as the main objective QTL in further studies and in MAS. Some QTL controlling several ear-kernel characters located at the same marker loci or in the same marker confidence intervals on chromosome 3, 7, 10 in P1F2:3 population and 1, 5 7 in P2F2:3 population, which showed hot regions. Partially dominance and over dominance played the most part role in the genetics of ear-kernel traits.3. No common marker interval associated with the same trait was detected in both populations, but some QTL associated with 100GW, ED and ERN were detected in adjacent marker intervals. q100GW1-1-2 (umc2237～phi039) and ql100GW2-1-1 (umc2237～bnlg1643), qxERN1-5-2 (bnlg1879～umc1162) and qlERN2-5-1 (bnlg1879～umc1389) were located below the same marker umc2237 and bnlg1879, repectively. They might be common QTL associated with 100GW and ERN, repectively. qxED1-1-1 (umc2237～phi039) and qED2-1-1(umc1395～umc2237)were associated with the same marker umc2237.4. GW and GWP were positively correlated with other ear-kernel characters significantly in phenotype, except for KR under the two populations, while 100GW and RKN were negatively correlated significantly. Therefore, it was very important to coordinate different ear kernel traits for the improvement of grain yield in high-oil corn, especially between 100GW and RKN. The results of multiple traits joint analysis among 100GW, RKN and ERN showed that two major QTL (q100GW1-3-2 and q100GW2-1-1) detected in single trait ananysis were also detected. Moreover, the QTL on chromosome 1, 3, 5, 6, 7 and 8 controlling 100GW and RKN or ERN showed pleiotropy or tight linkage.5. 100GW and kernel oil concentration were negatively correlated significantly in phenotype, except in Xuchang in P1F2:3 pupulation..Multiple trait joint analysis for 100GW with kernel oil concentration and 100GW with kernel protein concentration showed that the QTL on chromosome 1, 3, 5, 6, 7, 8 and 10 controlling 100GW and kernel oil concentration or kernel protein concentration showed pleiotropy or tight linkage. Excluding the influence of oil and starch concentration on 100GW, conditional QTL analysis showed that their 100GW was obviously affected by oil and starch concentration. But q100GW2-1-1 and q100GW1-6-1 were less affected by oil concentration. These two major QTL were also detected in multiple trait joint analysis for 100GW with oil concentration and in previous studies. Positive selection for these two QTL through MAS could increase grain weight, while oil concentration might be less influenced. Thus, the negative correlation between grain weight oil concentration could be reduced, and the problem of phenotypic selection could be overcome in some degree.
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