ABSTRACT
Soybean mosaic virus (SMV) is detrimental to soybean (Glycine max) breeding, seed quality, and yield worldwide. Improving the basic resistance of host plants is the most effective and economical method to reduce damage from SMV. Therefore, it is necessary to identify and clone novel SMV resistance genes. Here, we report the characterization of two soybean cultivars, DN50 and XQD, with different levels of resistance to SMV. Compared with XQD, DN50 exhibits enhanced resistance to the SMV strain SC7. By combining bulked-segregant analysis (BSA)-seq and fine-mapping, we identified a novel resistance locus, R SMV -11, spanning an approximately 207-kb region on chromosome 11 and containing 25 annotated genes in the reference Williams 82 genome. Of these genes, we identified eleven with non-synonymous single-nucleotide polymorphisms (SNPs) or insertion-deletion mutations (InDels) in their coding regions between two parents. One gene, GmMATE68 (Glyma.11G028900), harbored a frameshift mutation. GmMATE68 encodes a multidrug and toxic compound extrusion (MATE) transporter that is expressed in all soybean tissues and is induced by SC7. Given that MATE transporter families have been reported to be linked with plant disease resistance, we suggest that GmMATE68 is responsible for SC7 resistance in DN50. Our results reveal a novel SMV-resistance locus, improving understanding of the genetics of soybean disease resistance and providing a potential new tool for marker-assisted selection breeding in soybean.
ABSTRACT
Plant height is an important target for soybean breeding. It is a typical quantitative trait controlled by multiple genes and is susceptible to environmental influences. Here, we carried out phenotypic analysis of 156 recombinant inbred lines derived from "Dongnong L13" and "Henong 60" in nine environments at four locations over 6 years using interval mapping and inclusive composite interval mapping methods. We performed quantitative trait locus (QTL) analysis by applying pre-built simple-sequence repeat maps. We detected 48 QTLs, including nine significant QTLs detected by multiple methods and in multiple environments. Meanwhile, genotyping of all lines using the SoySNP660k BeadChip produced 54,836 non-redundant single-nucleotide polymorphism (SNP) genotypes. We used five multi-locus genome-wide association analysis methods to locate 10 quantitative trait nucleotides (QTNs), four of which overlap with previously located QTLs. Five candidate genes related to plant height are predicted to lie within 200 kb of these four QTNs. We identified 19 homologous genes in Arabidopsis, two of which may be associated with plant height. These findings further our understanding of the multi-gene regulatory network and genetic determinants of soybean plant height, which will be important for breeding high-yielding soybean.
ABSTRACT
Pod number is an important factor that influences yield in soybean. Here, we used two associated recombinant inbred line (RIL) soybean populations, RIL3613 (containing 134 lines derived from Dongnong L13 × Heihe 36) and RIL6013 (composed of 156 individuals from Dongnong L13 × Henong 60), to identify quantitative trait loci (QTLs) regulating the vertical distribution and quantity of seeds and seed pods. The numbers of pods were quantified in the upper, middle, and lower sections of the plant, as well as in the plants as a whole, and QTLs regulating these spatial traits were mapped using an inclusive complete interval mapping method. A total of 21 and 26 QTLs controlling pod-number-related traits were detected in RIL3613 and RIL6013, respectively, which explained 1.25-11.6698% and 0.0001-7.91% of the phenotypic variation. A total of 34 QTLs were verified by comparison with previous research, were identified in both populations, or were found to regulate multiple traits, indicating their authenticity. These results enhance our understanding of the vertical distribution of pod-number-related traits and support molecular breeding for seed yield.
