| As people deeply aware the serious problem of resources and environments, the hotspot for sustainable development of agriculture based on conserving resources and protecting environments has spread around the world. The objectives and key points for crops genetic improvement are not only to enhance the yield potential, but also to balance the high-yielding, high efficiency, good quality and high resistance.Rice is one of the most important food crops in China. The high-yielding and stability of rice is closely related with food security in our country even in the world. In recent years, through the rice yield is increased by applying excess nitrogen fertilizer, the production costs are also increased year by year and the phenomenon of diminishing utility is serious. Moreover, the application of excessive nitrogen fertilizers in rice cultivation has reduced the efficiency of fertilizer nitrogen use and increased the production cost and environmental pollution. With the increase of nitrogen fertilizer application levels, the nitrogen fertilizer input rates do not rise steadily with the rice yield, but negatively increase with the rice yield. The reduction of nitrogen fertilizer application in fertile soils and increased productivity in sterile soils both require the improvement of the nitrogen use efficiency (NUE), including uptake and utilization efficiency. Therefore, the strategy for exploiting and using of the genotypic potential rice varieties with high NUE would be of economic benefit to farmers and help to reduce environmental contamination.Recently, with the improvements of genomics and bio-statistics analysis software, especially the application of molecular marker technique in genetics and breeding, the association analysis method based on linkage disequilibrium has provided a new access to genetically research quantitative traits in rice and offered a new idea for molecular design breeding in crops. The results from this method and from quantitative trait loci (QTL) can testify and complement each other.To understand the performance of yield and its components to different nitrogen fertilizer levels, a set of recombinant inbred lines (RILs) from a cross of Zhenshan97(indica) and HR5(indica) and a set of Chinese cultivated mini-core germplasm rice were planted in two different growing seasons (rainy season in Shanghai and dry season in Hainan) at three nitrogen fertilizer input levels (i.e. N300,300kg urea/ha, N150,150kg urea/ha and NO,0kg urea/ha) for detection of quantitative trait loci on grain yield and its related components consisting of grain yield per plant (GYPP), panicle number per plant (PNPP), grain number per panicle (GNPP), filled grains per panicle (FGPP), spikelet fertility percentage (SFP) and100-grain weight (HGW). Analysis on genetic components including main effects, epistatic effects of the quantitative trait locus (QTL) and QTL by environment interactions (Q×E) were carried out. The identification of genomic regions associated with yield and its components at different nitrogen levels will be useful to improve nitrogen use efficiency of rice by marker-assisted selection. The main results are as follows:1. A total of57main-effect QTLs for GYPP, PNPP, GNPP, FGPP and HGW were identified from the recombinant inbred line (RIL) population of HR5/ZS97(including188lines) under the three N levels (N300, N150and NO), which distributed at41chromosomal regions. Among them,15,23and19QTLs were identified under the N300, N150and NO, respectively. The contribution rate of a single QTL was small, with the maximum phenotypic variance of13.3%. Under the NO condition, two main-effect QTLs (qGYPP-4b and qGNPP-12) were declared, which explained10.9%and10.2%phenotypic variances, respectively.2. Additionally,30pairs of epistatic effect QTLs controlled yield and its components were detected, except for SFP, which involved in45loci on11choromosomes. Under the N300, N150and NO levels,11,11and8pairs were respectively detected, and most of them were found between two non-main effect QTLs.3. Correlation and path analysis indicated that SFP had the greatest contribution to GYPP at the N300and N150levels with the direct path coefficients of0.809and0.783, and correlation coefficients of0.549**and0.605**, respectively. Under the NO level, although the correlation coefficient of SFP and GYPP was the greatest (R=0.553**), SFP affected GYPP through FGPP, and FGPP contributed the most to GYPP (P=0.816).4. Based on200polymorphic loci in whole genome and the population structure and their kinship, the relationships of nine phenotypic values including PNPP, PL, GNPP, FGPP, SFP, HGW, GYPP, SDW and NCP with polymorphic loci were analyzed by using the mixed linear model (MLM) under two environments (Shanghai in2008and Hainan in 2009) at the three different nitrogen levels. In each experiment,6to26significantly related loci for each trait were detected in whole genome, which distributed on all the12chromosomes. Among these related loci, most of them were located at the known chromosomal regions of mapped QTLs or genes.5. Numerous specially expressed loci/QTLs under the three nitrogen application levels and some co-expression loci/QTLs were declared by the association analysis and QTL mapping. Most of them were identified at one nitrogen application level, indicating that the traits of yield and its components are controlled by different genes under different nitrogen levels. Also, several main-effect QTLs/loci were located at the same regions on chromosomes1,2,3,5,7and10, suggesting that there are some key genes controlling or regulating rice yield and its components. On the whole, the identification of genomic regions associated with yield and its components at different nitrogen levels will be useful to improve NUE of rice by molecular marker-assisted approach. This information together with association results can be applied in breeding programs. |
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