Cultivated rice (Oryza sativa L.) is one of the staple food for over half of the world’s population. Thus, improvement of cultivated rice is important for the development of the world. It has been shown that abundant elite genes exist in rice landraces in previous studies. A genome-wide association study (GWAS) performed with EMMAX for 12 agronomic traits measured in both Guangzhou and Hangzhou was carried out using 150 accessions of Ting’s core collection selected based on 48 phenotypic traits from 2262 accessions of Ting’s collection, the GWAS included more than 3.8 million SNPs. Within Ting’s core collection, which has a simple population structure, low relatedness, and rapid linkage disequilibrium (LD) decay, we found 32 peaks located closely to previously cloned genes such as Hd1, SD1, Ghd7, GW8, and GL7 or mapped QTL, and these loci might be natural variations in the cloned genes or QTL which influence potentially agronomic traits. Furthermore, we also detected 32 regions where new genes might be located, and some peaks of these new candidate genes such as the signal on chromosome 11 for heading days were even higher than that of Hd1. Detailed annotation of these significant loci were shown in this study. Moreover, according to the estimated LD decay distance of 100 to 350 kb on the 12 chromosomes in this study, we found 13 identical significant regions in the two locations. This research provided important information for further mining these elite genes within Ting’s core collection and using them for rice breeding.

Association analysis based on linkage disequilibrium (LD) is an efficient way to dissect complex traits and to identify gene functions in rice. Although association analysis is an effective way to construct fine maps for quantitative traits, there are a few issues which need to be addressed. In this review, we will first summarize type, structure and LD level of populations used for association analysis of rice, and then discuss the genotyping methods and statistical approaches used for association analysis in rice. Moreover, we will review current shortcomings and benefits of association analysis as well as specific types of future research to overcome these shortcomings. Furthermore, we will analyze the reasons for the underutilization of the results within association analysis in rice breeding.

Sheath blight disease (ShB) is considered to be the second most important disease affecting rice, and the genetic mechanism of ShB resistance in rice is great complicated. Uncovering genetic mechanism of ShB resistance and strong resistant varieties in rice are the premise for ShB resistance improvement. A rice ShB genome-wide association study (GWAS) was performed using approximately five million SNPs within Ting’s core collection. “Early pradifice”, one typical japonica, was determined to be the most resistant variety in both 2016 and 2017. A total of 34 and four significant (p ≤ 1.93 × 10⁻⁸) SNPs were observed in 2016 and 2017, respectively. Moreover, 23 of 34 and two of four gene-based SNPs not reported in previous studies in 2016 and 2017, respectively, were identified as significantly associated with rice ShB resistance. Furthermore, we performed GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses for the genes located at a region within 10 kb of the significant SNPs. Both in 2016 and 2017, we observed that genes were uniquely enriched in the regulation of transcription and RNA processing in the category of “biological process”, plasma membrane, nucleus, integral component of membrane and cell wall in the category of “cellular component”, and ATP binding in the category of “molecular function”. The results of the present study may establish a foundation for further research investigating these elite genes and utilizing the resistant varieties in Ting’s core collection to improve rice ShB resistance.

Aluminum (Al) at high concentrations inhibits root growth, damage root systems, and causes significant reductions in rice yields. Indica and Japonica rice have been cultivated in distinctly different ecological environments with different soil acidity levels; thus, they might have different mechanisms of Al-tolerance. In the present study, transcriptomic analysis in the root apex for Al-tolerance in the seedling stage was carried out within Al-tolerant and -sensitive varieties belonging to different subpopulations (i.e., Indica, Japonica, and mixed). We found that there were significant differences between the gene expression patterns of Indica Al-tolerant and Japonica Al-tolerant varieties, while the gene expression patterns of the Al-tolerant varieties in the mixed subgroup, which was inclined to Japonica, were similar to the Al-tolerant varieties in Japonica. Moreover, after further GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses of the transcriptomic data, we found that eight pathways, i.e., “Terpenoid backbone biosynthesis”, “Ribosome”, “Amino sugar and nucleotide sugar metabolism”, “Plant hormone signal transduction”, “TCA cycle”, “Synthesis and degradation of ketone bodies”, and “Butanoate metabolism” were found uniquely for Indica Al-tolerant varieties, while only one pathway (i.e., “Sulfur metabolism”) was found uniquely for Japonica Al-tolerant varieties. For Al-sensitive varieties, one identical pathway was found, both in Indica and Japonica. Three pathways were found uniquely in “Starch and sucrose metabolism”, “Metabolic pathway”, and “Amino sugar and nucleotide sugar metabolism”.

Aluminum (Al) solubilizes into trivalent ions (Al³⁺) on acidic soils, inhibiting root growth. Since about 13% of global rice cultivation is grown on acidic soils, improving Al tolerance in rice may significantly increase yields. In the present study, metabolome analysis under Al toxicity between the Al-tolerant variety Nipponbare and the Al-sensitive variety H570 were performed. There were 45 and 83 differential metabolites which were specifically detected in Nipponbare and H570 under Al toxicity, respectively. Furthermore, the results showed that 16 lipids out of 45 total metabolites were down-regulated, and 7 phenolic acids as well as 4 alkaloids of 45 metabolites were up-regulated in Nipponbare, while 12 amino acids and their derivatives were specifically detected in H570, of which 11 amino acids increased, including L-homoserine and L-methionine, which are involved in cysteine synthesis, L-ornithine and L-proline, which are associated with putrescine synthesis, and 1-aminocyclopropane-1-carboxylate, which is associated with ethylene synthesis. The contents of cysteine and s-(methyl) glutathione, which were reported to be related to Al detoxification in rice, decreased significantly. Meanwhile, putrescine was accumulated in H570, while there was no significant change in Nipponbare, so we speculated that it might be an intermediate product of Al detoxification in rice. The differential metabolites detected between Al-tolerant and -sensitive rice variants in the present study might play important roles in Al tolerance. These results provide new insights in the mechanisms of Al tolerance in rice.

Rice is sensitive to high temperatures at the seedling stage. In the present study, a combined analysis of transcriptome and metabolome was performed on a heat-resistant accession, DY80, from Dongxiang wild rice and a heat-sensitive variety, R974, under heat stress at the seedling stage. The results of the transcriptome and metabolome analyses were verified through qRT-PCR and ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) analysis. We found that there were 1817 and 561 differentially expressed genes (DEGs) unique in DY80 and R974 under heat stress, respectively. The elite genes for the heat stress involved in Dongxiang wild rice may include upregulated genes in the pathway of unfolded protein binding; downregulated genes in the pathways of chlorophyll biosynthetic process, and cysteine and methionine metabolism; and photosystem I, photosystem II, and unchanged genes in the pathways of the anchored component of the plasma membrane, cell wall biogenesis, and photosynthesis-antenna proteins. Moreover, a total of 301 and 28 metabolites were identified as unique in DY80 and R974 after heat treatment, respectively. Further analyses showed that malic acid, stearic acid, and L-threonine might be causal metabolites, contributing to strong heat resistance in Dongxiang wild rice. These findings provide new insights into the mechanisms of heat resistance in rice.