Rice salt tolerance at the germination stage directly affects the germination rate and seedling establishment of rice directly seeded in saline soils, which in turn affects yield. In this study, we determined the relative germination potential (RGP) and relative germination index (RGI) under 200 mM salt stress and control conditions using 295 japonica rice accessions. Statistical analysis showed extensive phenotypic variations under salt stress conditions. Twenty-one varieties with an RGP ≥ 80% and an RGI ≥ 80% were screened. Based on genotypic data including, 788,396 single-nucleotide polymorphisms (SNPs), 40 quantitative trait loci (QTL) were localized on rice chromosomes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12, which were shown to be significantly associated with rice salt tolerance at the germination stage, including 20 for RGP and 20 for RGI, using genome-wide association analysis. Six QTL with ≥ 3 consecutive significant SNP loci and localized in the same LD interval were selected for further analysis. Four rice genes (LOC_Os01g04920, LOC_Os10g38350, LOC_Os10g38470, and LOC_Os10g38489) were selected as important candidates for salt tolerance based on haplotype analysis and functional annotation. The findings could facilitate the development of valuable rice varieties for direct seeding in salinized soil and improve japonica rice salt tolerance at the germination stage through molecular breeding.

Improving rice yield is one of the most important food issues internationally. It is an undeniable goal of rice breeding, and the effective panicle number (EPN) is a key factor determining rice yield. Increasing the EPN in rice is a major way to increase rice yield. Currently, the main quantitative trait locus (QTL) for EPN in rice is limited, and there is also limited research on the gene for EPN in rice. Therefore, the excavation and analysis of major genes related to EPN in rice is of great significance for molecular breeding and yield improvement. This study used japonica rice varieties Dongfu 114 and Longyang 11 to construct an F₅ population consisting of 309 individual plants. Two extreme phenotypic pools were constructed by identifying the EPN of the population, and QTL-seq analysis was performed to obtain three main effective QTL intervals for EPN. This analysis also helped to screen out 34 candidate genes. Then, EPN time expression pattern analysis was performed on these 34 genes to screen out six candidate genes with higher expression levels. Using a 3K database to perform haplotype analysis on these six genes, we selected haplotypes with significant differences in EPN. Finally, five candidate genes related to EPN were obtained.

Nitrogen (N) is one of the essential nutrients for the growth and development of crops. The adequate application of N not only increases the yield of crops but also improves the quality of agricultural products, but the excessive application of N can cause many adverse effects on ecology and the environment. In this study, genome-wide association analysis (GWAS) was performed under low- and high-N conditions based on 788,396 SNPs and phenotypic traits relevant to N uptake and utilization (N content and N accumulation). A total of 75 QTLs were obtained using GWAS, which contained 811 genes. Of 811 genes, 281 genes showed different haplotypes, and 40 genes had significant phenotypic differences among different haplotypes. Of these 40 genes, 5 differentially expressed genes (Os01g0159250, Os02g0618200, Os02g0618400, Os02g0630300, and Os06g0619000) were finally identified as the more valuable candidate genes based on the transcriptome data sequenced from Longjing31 (low-N-tolerant variety) and Songjing 10 (low-N-sensitive variety) under low- and high-N treatments. These new findings enrich the genetic resources for N uptake and utilization in rice, as well as lay a theoretical foundation for improving the efficiency of N uptake and utilization in rice.