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With the improvement of living standards, people pay more attention to grain quality of rice, so how to maintain the current yield potential and to further improve quality of rice is one of the main objectives in rice breeding. In this study, a high-quality indica restorer line Ce258 and traditional indica rice variety Zhongguangxiang 1 were used as the recurrent parents, to cross with the donor parent, IR75862, a japonica waxy breeding line, producing two BC1F7 backcross introgression line populations. QTLs and their genetic background and environment interactions for yield-related traits–second branch number (SBN), spikelet number per panicle (SNP), filled grains number per panicle (FGN), 1000-grain weight (TGW) and panicle weight (PW); grain type traits–grain length (GL), width (GW) and thickness (GT) and milling quality traits–brown rice percentage (BR), milled rice percentage (MR) and head rice percentage (HR); micro-element concentrations of Fe, Zn, Cd, Hg and Pb were identified and analyzed in the two environments, Nanning of Guangxi and Sanya of Hainan, using above two introgression line populations. The main results were obtained and described as follows:1. Significant differences were found in FGN, TGW, GL, GW, HR, concentrations of Fe, Zn and Cd between Ce258 and IR75862. Similarly, significant differences were also found in FGN, SNP, TGW, PW, MR and concentrations of Fe and Zn between Zhongguangxiang 1 and IR75862. Most yield- and grain type-related traits had no significant relations with the three milling quality traits (BR, MR and HR).2. A total of 98 and 90 main-effect QTLs was identified for yield- and grain type-related traits as well as milling quality and five micro-element concentrations in Nanning and Sanya environments from the introgression line populations of Ce258/IR75862 and Zhongguangxiang 1/IR75862, respectively, which distributed all over 12 chromosomes.3. Among nine QTLs affecting HR detected from the two mapping populations across the two environments, seven showed significantly environment interactions. However, no any common QTL for the concentrations of the five micro-element was detected from Zhongguangxiang 1/IR75862 in the two environments, whereas only two common QTLs for Zn concentration were mapped in Ce258/IR75862 population. It was indicated that as compared with yield- and grain type-related traits, QTLs affecting HR and concentrations of mirco-elements had stronger environmental interaction effects.4. The average introgression frequency of IR75862 into Ce258 genetic background was 5%, two and half times as high as that into Zhongguangxiang 1 background. Similarly, number of QTLs shared by the two backgrounds in the same environment accounted for 5.3% of total QTLs affecting all tested traits, indicating genetic background had obvious effects on introgression of donor alleles and QTL detection. The common QTL among different backgrounds probably had similar additive effect or varied with background in effect size.5. Many QTLs affecting grain number and grain weight were mapped in the same or neighboring regions with opposite gene effect. However, some QTLs affecting the two kinds of traits seemed genetically independent, such as those locating in the regions of RM262~RM475 on chromosome 2, RM509~RM430 on chromosome 5, RM587~RM510 on chromosome 6 and RM566~RM242 on chromosome 9, which only affected grain number but had no any effect on grain weight; on the contrary, those locating in the regions of RM478~RM134 on chromosome 7 and RM519~RM235 on chromosome 12, which were only associated with grain weight but independent of grain number. Therefore, it is possible to further improve rice yield potential via marker-assisted selection or pyramiding against above the two kinds of loci on the basis of present structures of grain number and grain weight of rice.6. Most QTLs affecting BR, MR and HR were identified in different regions on chromosomes with those for branch and grain number as well as grain weight, suggesting milling quality traits inherited independently with the traits of branch number, grain number and grain weight. So optimal deployment of grain yield and milling quality will be made by recombination of the QTLs for those traits.7. QTLs affecting different micro-elements were located in the same or neighboring regions with same direction of gene effect, indicating tightly linkage or pleiotropism probably control these traits. It is suggested that improvement of Fe and Zn in the grains will accompany increase of those poisonous element content such as Cd, Hg and Pb. In the present study, qFe2、qZn2a and qZn6a which affected Fe and Zn with independence with the other heavy metal elements could be valuable in biofortification breeding in rice.
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