These authors have contributed equally to this work. SUMMARYSoybean 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 isoflavones are valued in certain medicines, cosmetics, foods and feeds. Selection for high-isoflavone content in seeds along with agronomic traits is a goal of many soybean breeders. The aim of the study was to identify the quantitative trait loci (QTL) underlying seed isoflavone content in soybean among seven environments in China. A cross was made between 'Zhongdou 27', a soybean cultivar with higher mean isoflavone content in the seven environments (daidzein, DZ, 1,865 microg g(-1); genistein, GT, 1,614 microg g(-1); glycitein, GC, 311 microg g(-1) and total isoflavone, TI, 3,791 microg g(-1)) and 'Jiunong 20', a soybean cultivar with lower isoflavone content (DZ, 844 microg g(-1); GT, 1,046 microg g(-1); GC, 193 microg g(-1) and TI, 2,061 microg g(-1)). Through single-seed-descent, 130 F(5)-derived F(6) recombinant inbred lines were advanced. A total of 99 simple-sequence repeat markers were used to construct a genetic linkage map. Seed isoflavone contents were analyzed using high-performance liquid chromatography for multiple years and locations (Harbin in 2005, 2006 and 2007, Hulan in 2006 and 2007, and Suihua in 2006 and 2007). Three QTL were associated with DZ content, four with GT content, three with GC content, and five with TI content. For all QTL detected the beneficial allele was from Zhongdou 27. QTL were located on three (DZ), three (GC), four (GT) and five (TI) molecular linkage groups (LG). A novel QTL was detected with marker Satt144 on LG F that was associated with DZ (0.0014 > P > 0.0001, 5% < R (2) < 11%; 254 < DZ < 552 microg g(-1)), GT (0.0027 > P > 0.0001; 4% < R (2) < 9%; 262 < GT < 391 microg g(-1)), and TI (0.0011 > P > 0.0001; 4% < R (2) < 15%; 195 < TI < 871 microg g(-1)) across the various environments. A previously reported QTL on LG M detected by Satt540 was associated with TI across four environments and TI mean (0.0022 > P > 0.0001; 3% < R (2) < 8%; 182 < TI < 334 microg g(-1)) in China. Because both beneficial alleles were from Zhongdou 27, it was concluded that these two QTL would have the greatest potential value for marker-assisted selection for high-isoflavone content in soybean seed in China.

BackgroundSoybean 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.ResultsA 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.ConclusionsGWAS 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1800-1) contains supplementary material, which is available to authorized users.

Seed weight, measured as mass per seed, is an important yield component of soybean and is generally positively correlated with seed yield (Burton et al, Crop Sci 27:1093, 1987). In previous reports, quantitative trait loci (QTL) associated with seed weight, were identified in single genetic background. The objective of the present study was to identify QTL and epistatic QTL underlying soybean seed weight in three RIL populations (with one common male parent 'Hefeng25') and across three different environments. Overall, 18, 11, and 17 seed weight QTL were identified in HC ('Hefeng25' × 'Conrad'), HM ('Hefeng25' × 'Maple Arrow'), and HB ('Hefeng25' × 'Bayfield') populations, respectively. The amount of phenotypic variation explained by a single QTL underlying seed weight was usually less than 10 %. The environment and background-independent QTL often had higher additive (a) effects. In contrast, the environment or background-dependent QTL were probably due to weak expression of QTL. QTL by environment interaction effects were in the opposite direction of a effects and/or epistasis effects. Four QTL and one QTL could be identified (2.0 < LOD < 9.06) in the HC and HB populations, respectively, across three environments (swHCA2-1, swHCC2-1, swHCD1b-1, swHCA2-2 (linked to Satt233, Satt424, Satt460, Satt428, respectively) and swHBA1-1(Satt449). Seven QTL could be identified in all three RIL populations in at least one location. Two QTL could be identified in the three RIL populations across three environments. These two QTL may have greater potential for use in marker-assisted selection of seed weight in soybean.

At harvest traits such as seed weight are the sum of development and responses to stresses over the growing season and particularly during the reproductive phase of growth. The aim here was to measure quantitative trait loci (QTL) underlying the seed weight from early development to drying post harvest. One hundred forty-three F 5 derived recombinant inbred lines (RILs) developed from the cross of soybean cultivars 'Charleston' and 'Dongnong 594' were used for the analysis of QTL underlying mean 100-seed weight at six different developmental stages. QTL Â Environment interactions (QE) were analyzed by a mixed genetic mode based on 3 years' data. At an experiment-wise threshold of a ¼ 0.05 and by single-point analysis 94 QTL unaffected by QE underlay the mean seed weight at different developmental stages. Sixty-eight QTL affected by QE that also underlay mean seed weight were identified. From the 162 QTL 42 could be located on 12 linkage groups by composite interval mapping (LOD42.0). The numbers, locations and types of the QTL and the genetic effects were different at each developmental stage. On linkage group C2 the distantly linked QTL swC2-1, swC2-2 and swC2-3 each affected mean seed weight throughout the different developmental stages. The DNA markers linked to the QTL possessed potential for use in marker-assisted selection for soybean seed size. The identification of QTL with genetic main effects and QE interaction effects suggested that such interactions might significantly alter seed weight during seed development.