Summary: Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM‐resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of ‘Maple Arrow’ (partial resistant to SWM) and ‘Hefeng 25’ (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole‐genome encompassing approach and 25 179 single‐nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome‐wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most fatal pests of soybean (Glycine max (L.) Merr.) worldwide and causes huge loss of soybean yield each year. Multiple sources of resistance are urgently needed for effective management of SCN via the development of resistant cultivars. The aim of the present study was to investigate the genetic architecture of resistance to SCN HG Type 0 (race 3) and HG Type 1.2.3.5.7 (race 4) in landraces and released elite soybean cultivars mostly from China. A total of 440 diverse soybean landraces and elite cultivars were screened for resistance to SCN HG Type 0 and HG Type 1.2.3.5.7. Exactly 131 new sources of SCN resistance were identified. Lines were genotyped by SNP markers detected by the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 36,976 SNPs were identified with minor allele frequencies (MAF) > 4 % that were present in 97 % of all the genotypes. Genome-wide association mapping showed that a total of 19 association signals were significantly related to the resistance for the two HG Types. Of the 19 association signals, eight signals overlapped with reported QTL including Rhg1 and Rhg4 genes. Another eight were located in the linked regions encompassing known QTL. Three QTL were found that were not previously reported. The average value of female index (FI) of soybean accessions with resistant alleles was significantly lower than those with susceptible alleles for each peak SNP. Disease resistance proteins with leucine rich regions, cytochrome P450s, protein kinases, zinc finger domain proteins, RING domain proteins, MYB and WRKY transcription activation families were identified. Such proteins may participate in the resistant reaction to SCN and were frequently found in the tightly linked genomic regions of the peak SNPs. GWAS extended understanding of the genetic architecture of SCN resistance in multiple genetic backgrounds. Nineteen association signals were obtained for the resistance to the two Hg Types of SCN. The multiple beneficial alleles from resistant germplasm sources will be useful for the breeding of cultivars with improved resistance to SCN. Analysis of genes near association signals may facilitate the recognition of the causal gene(s) underlying SCN resistances.

Soybean yield is a complex quantitative trait, which is greatly affected by environmental conditions. The main objective of this study is not only to identify specific traits contributing to yield in different latitudes, which can be further used in breeding, but also to identify the outperforming varieties, as this can help to select new lines with these traits. One hundred and seventy-three soybean genotypes were tested in three different ecological environments, including Harbin, Changchun, and Shenyang in China during 2015–2016 cropping seasons. The evaluation on the different agronomic and physiological traits indicated that the soybean varieties with higher plant height, more nodes of main stem, branches, pods, grains, and 100-grain weight, or longer growth periods may have higher yield. Pods, grains and 100-grain weight can be used as direct selection criteria for yield increase, and likewise the other traits such as plant height, nodes of main stem, branches, growth periods indirectly affected yield by affecting the three traits above. The effect of genotype × environment (G × E) interaction on different agronomic traits was significant. The representativeness and discriminability for grains yield per plant was the most significant in Harbin, which could be used to screen varieties with high yield and wider adaptability. Genotype “Suinong 1” was considered stable with higher value of grain yield per plant than other genotypes used in this study. As the yield of certain soybean cultivars may be significantly reduced if they are grown in a region as little as 2°N beyond its normal cultivation latitudes, therefore, the identification and analysis on the stable and widely adaptive soybean genotypes would be very important, and it would provide the significant reference accordance of soybean variety selection for the soybean breeders.