Rice (Oryza sativa L.) is seriously impacted by global soil salinization. To determine the quantitative trait loci (QTLs) related to salt tolerance in rice roots, F 2:3 and BC 1 F 2:3 populations derived from a cross between the cv. Dongnong 425 of high quality and yield and the salt-tolerant cv. Changbai 10, were studied at different development stages. Two genetic linkage maps of F 2:3 and BC 1 F 2:3 populations were constructed. A 66 mM NaCl solution was used to irrigate the field and to analyze the dynamic QTL of some rice root traits. Using unconditional and conditional QTL mapping methods, 30 unconditional QTLs and 16 conditional QTLs related to the 6 root traits were detected on the 9 rice chromosomes during different developmental stages. Fourteen pairs of unconditional and conditional QTLs were detected at the identical developmental stage in the identical population. A number of QTLs were detected at different developmental stages, however, many did not appear at the last stage. Remarkably, qRKC1 appeared continuously at multiple stages in both the populations suggesting its key role in regulating the salt tolerance of rice roots.

As the major source of edible protein and oil, the global demand for soybean (Glycine max (L.) Merr.) is increasing. Plant height is closely related to yield; therefore, understanding the genetic basis of plant height will help to improve soybean plant type and increase seed yield. In this study, quantitative trait loci (QTLs) and nucleotides (QTNs) for soybean plant height were detected by linkage analysis and association analysis. A high-density map containing 2225 bin markers was constructed by using 108 342 SNPs of a recombinant inbred line population (named RIL3613) of 120 lines for linkage analysis. In total, 39 QTLs were detected, including 16 QTLs that were repeatedly detected in multiple environments. Association analysis was performed by using 63 306 SNPs from a germplasm population of 455 natural soybean accessions. In total, 62 QTNs were detected, and 26 QTNs were repeatedly detected by multiple methods. Fourteen QTNs were distributed in the intervals of six multiple-environment QTLs by comparing the results of association analysis and linkage analysis. With pathway analysis, six candidate genes were identified as being associated with plant height. These results contribute to analysis of the genetic basis of plant height and will promote marker-assisted selection for breeding ideal plant shape.

Although the main stem node number of soybean [Glycine max (L.) Merr. ] is an important yield-related trait, there have been limited studies on the effect of plant density on the identification of quantitative trait loci (QTL) for main stem node number (MSNN). To address this issue, here, 144 four-way recombinant inbred lines (FW-RILs) derived from Kenfeng 14, Kenfeng 15, Heinong 48, and Kenfeng 19 were used to identify QTL for MSNN with densities of 2.2 × 105 (D1) and 3 × 105 (D2) plants/ha in five environments by linkage and association studies. As a result, the linkage and association studies identified 40 and 28 QTL in D1 and D2, respectively, indicating the difference in QTL in various densities. Among these QTL, five were common in the two densities; 36 were singly identified for response to density; 12 were repeatedly identified by both response to density and phenotype of two densities. Thirty-one were repeatedly detected across various methods, densities, and environments in the linkage and association studies. Among the 24 common QTL in the linkage and association studies, 15 explained a phenotypic variation of more than 10%. Finally, Glyma.06G094400, Glyma.06G147600, Glyma.19G160800.1, and Glyma.19G161100 were predicted to be associated with MSNN. These findings will help to elucidate the genetic basis of MSNN and improve molecular assistant selection in high-yield soybean breeding.