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Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ2) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.

Rice bacterial leaf blight (BB) caused by Xanthomonasoryzae pv. oryzae and bacterial leaf streak (BLS) caused by X. oryzae pv. oryzicola (Xoc) are two important diseases of rice that often outbreak simultaneously and constrain rice production in much of Asia and parts of Africa. Developing resistant cultivars has been the most effective approach to control BB, however, most single resistance genes have limited value in breeding programs because of their narrow-spectrum of resistance to the races of the pathogen. By contrast, there is little progress in breeding varieties resistant to Xoc since BLS resistance in rice was a quantitative trait and so far only a few quantitative resistance loci have been identified. We reported here the development of a high yield elite line, Lu-You-Zhan highly resistant to both BB and BLS by pyramiding Xa23 with a wide-spectrum resistance to BB derived from wild rice and a non-host maize resistance gene, Rxo1, using both marker assisted selection (MAS) and genetic engineering. Our study has provided strong evidence that non-host R genes could be a valuable source of resistance in combating those plant diseases where no single R gene controlling high level of resistance exists and demonstrated that MAS combined with transgenic technologies are an effective strategy to achieve high level of resistance against multiple plant diseases.

Drought tolerance (DT) in rice is known to be controlled by many quantitative trait loci (QTLs) and involved differential expression of large numbers of genes, but linking QTLs with their underlying genes remains the most challenging issue in plant molecular biology. To shed some light on this issue, differential gene expression in response to PEG simulated drought in 3 unique genetic materials (a lowland rice, IR64 and its derived line, PD86 which has 11 introgressed DT QTLs, and a upland rice IRAT109) was investigated using a PCR-based subtractive hybridization strategy. More than 300 unique subtracted cDNA sequences, covering genes of diverse cellular activities and functions, were identified and confirmed by semi-quantitative and quantitative RT-PCR. Detailed bioinformatics analyses of the data revealed two interesting results. First, the levels and mechanisms of DT of the three rice lines were associated with the number and types of differentially expressed genes, suggesting different DT mechanisms in rice are controlled by different sets of genes and different metabolic pathways, and most differentially expressed genes under drought were able to contribute to DT. Second, there appeared a high correspondence in genomic location between DT QTLs and clusters of differentially expressed genes in rice, suggesting some DT QTLs may represent clusters of co-regulated and functionally related genes. Thus, differential gene expression analyses using genetically characterized materials can provide additional insights into the molecular basis of QTLs and convergent evidence to shortlist the candidate genes for target QTLs.

A large set of 254 introgression lines in an elite indica genetic background were evaluated for grain yield (GY) and related traits under the irrigated (control) and drought (stress) conditions in two consecutive years for genetic dissection of adaptive strategies of rice to water stress. A total of 36 quantitative trait loci (QTLs) affecting heading date (HD), plant height (PH), GY and yield components were identified and most QTLs showed pronounced differential expression either qualitatively or quantitatively in response to drought. These QTLs could be grouped into three major types based on their behaviors under control and stress conditions. Type I included 12 QTLs that expressed under both the stress and non-stress conditions. Type II comprised 17 QTLs that expressed under irrigation but not under stress. Type III included seven QTLs that were apparently induced by stress. The observation that the Lemont (japonica) alleles at all HD QTLs except QHd5 resulted in early heading under stress appeared to be responsible for the putative adaptation of Lemont to drought by escaping, whereas the Teqing (indica) alleles at most PH/GY QTLs were consistently associated with increased yield potential and trait stability and thus contributed to DT. Our result that most DT QTLs were non-allelic with QTLs for drought escaping suggests that the two adaptive strategies in the parental lines are under possible negative regulation of two largely non-overlapping genetic systems.

Tremendous efforts have been taken worldwide to develop genome-wide genetic stocks for rice functional genomic (FG) research since the rice genome was completely sequenced. To facilitate FG research of complex polygenic phenotypes in rice, we report the development of over 20,000 introgression lines (ILs) in three elite rice genetic backgrounds for a wide range of complex traits, including resistances/tolerances to many biotic and abiotic stresses, morpho-agronomic traits, physiological traits, etc., by selective introgression. ILs within each genetic background are phenotypically similar to their recurrent parent but each carries one or a few traits introgressed from a known donor. Together, these ILs contain a significant portion of loci affecting the selected complex phenotypes at which allelic diversity exists in the primary gene pool of rice. A forward genetics strategy was proposed and demonstrated with examples on how to use these ILs for large-scale FG research. Complementary to the genome-wide insertional mutants, these ILs opens a new way for highly efficient discovery, candidate gene identification and cloning of important QTLs for specific phenotypes based on convergent evidence from QTL position, expression profiling, functional and molecular diversity analyses of candidate genes, highlights the importance of genetic networks underlying complex phenotypes in rice that may ultimately lead to more complete understanding of the genetic and molecular bases of quantitative trait variation in rice.