Selection of a core set of RILs from Forrest x Williams 82 to develop a framework map in soybean

Genetic Mapping for QTL Associated with Seed Nickel and Molybdenum Accumulation in the Soybean 'Forrest' by 'Williams 82' RIL Population

Understanding the genetic basis of seed Ni and Mo is essential. Since soybean is a major crop in the world and a major source for nutrients, including Ni and Mo, the objective of the current research was to map genetic regions (quantitative trait loci, QTL) linked to Ni and Mo concentrations in soybean seed. A recombinant inbred line (RIL) population was derived from a cross between 'Forrest' and 'Williams 82' (F × W82). A total of 306 lines was used for genotyping using 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted and included the parents and the RIL population. One experiment was conducted in 2018 in North Carolina (NC), and the second experiment was conducted in Illinois in 2020 (IL). Logarithm of the odds (LOD) of ≥2.5 was set as a threshold to report identified QTL using the composite interval mapping (CIM) method. A wide range of Ni and Mo concentrations among RILs was observed. A total of four QTL (qNi-01, qNi-02, and qNi-03 on Chr 2, 8, and 9, respectively, in 2018, and qNi-01 on Chr 20 in 2020) was identified for seed Ni. All these QTL were significantly (LOD threshold > 2.5) associated with seed Ni, with LOD scores ranging between 2.71-3.44, and with phenotypic variance ranging from 4.48-6.97%. A total of three QTL for Mo (qMo-01, qMo-02, and qMo-03 on Chr 1, 3, 17, respectively) was identified in 2018, and four QTL (qMo-01, qMo-02, qMo-03, and qMo-04, on Chr 5, 11, 14, and 16, respectively) were identified in 2020. Some of the current QTL had high LOD and significantly contributed to the phenotypic variance for the trait. For example, in 2018, Mo QTL qMo-01 on Chr 1 had LOD of 7.8, explaining a phenotypic variance of 41.17%, and qMo-03 on Chr 17 had LOD of 5.33, with phenotypic variance explained of 41.49%. In addition, one Mo QTL (qMo-03 on Chr 14) had LOD of 9.77, explaining 51.57% of phenotypic variance related to the trait, and another Mo QTL (qMo-04 on Chr 16) had LOD of 7.62 and explained 49.95% of phenotypic variance. None of the QTL identified here were identified twice across locations/years. Based on a search of the available literature and of SoyBase, the four QTL for Ni, identified on Chr 2, 8, 9, and 20, and the five QTL associated with Mo, identified on Chr 1, 17, 11, 14, and 16, are novel and not previously reported. This research contributes new insights into the genetic mapping of Ni and Mo, and provides valuable QTL and molecular markers that can potentially assist in selecting Ni and Mo levels in soybean seeds.

Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean 'Forrest' by 'Williams 82' Recombinant Inbred Line Population

Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as they contribute to taste and flavor in soy-based food. Therefore, the objectives of this study were to use the 'Forrest' by 'Williams 82' (F × W82) recombinant inbred line (RIL) soybean population (n = 309) to identify quantitative trait loci (QTLs) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTLs that control seed sugar contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTLs. Amongst them, a cluster of four genes involved in the sugars' pathway was collocated within 6 MB of two QTLs that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides.

QTL and Candidate Genes for Seed Tocopherol Content in ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line (RIL) Population of Soybean

Soybean seeds are rich in secondary metabolites which are beneficial for human health, including tocopherols. Tocopherols play an important role in human and animal nutrition thanks to their antioxidant activity. In this study, the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306) was used to map quantitative trait loci (QTL) for seed α-tocopherol, β-tocopherol, δ -tocopherol, γ-tocopherol, and total tocopherol contents in Carbondale, IL over two years. Also, the identification of the candidate genes involved in soybean tocopherols biosynthetic pathway was performed. A total of 32 QTL controlling various seed tocopherol contents have been identified and mapped on Chrs. 1, 2, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, and 20. One major and novel QTL was identified on Chr. 6 with an R² of 27.8, 9.9, and 6.9 for δ-tocopherol, α-tocopherol, and total tocopherol content, respectively. Reverse BLAST analysis of the genes that were identified in Arabidopsis allowed the identification of 37 genes involved in soybean tocopherol pathway, among which 11 were located close to the identified QTLs. The tocopherol cyclase gene (TC) Glyma.06G084100 is located close to the QTLs controlling δ-tocopherol (R² = 27.8), α-tocopherol (R² = 9.96), and total-tocopherol (R² = 6.95). The geranylgeranyl diphosphate reductase (GGDR) Glyma.05G026200 gene is located close to a QTL controlling total tocopherol content in soybean (R² = 4.42). The two methylphytylbenzoquinol methyltransferase (MPBQ-MT) candidate genes Glyma.02G002000 and Glyma.02G143700 are located close to a QTL controlling δ-tocopherol content (R² = 3.57). The two γ-tocopherol methyltransferase (γ-TMT) genes, Glyma.12G014200 and Glyma.12G014300, are located close to QTLs controlling (γ+ß) tocopherol content (R² = 8.86) and total tocopherol (R² = 5.94). The identified tocopherol seed QTLs and candidate genes will be beneficial in breeding programs to develop soybean cultivars with high tocopherol contents.

The Soybean High Density 'Forrest' by 'Williams 82' SNP-Based Genetic Linkage Map Identifies QTL and Candidate Genes for Seed Isoflavone Content

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306); map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020); identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Quantitative Trait Loci Associated with Rotylenchulus reniformis Host Suitability in Soybean

Reniform nematode (Rotylenchulus reniformis) is a yield-limiting pathogen of soybean (Glycine max) in the southeastern region of the United States. A population of 250 recombinant inbred lines (RIL) (F2:8) developed from a cross between reniform nematode resistant soybean cultivar Forrest and susceptible cultivar Williams 82 was utilized to identify regions associated with host suitability. A genetic linkage map was constructed using single-nucleotide polymorphism markers generated by genotyping-by-sequencing. The phenotype was measured in the RIL population and resistance was characterized using normalized and transformed nematode reproduction indices in an optimal univariate cluster analysis. Quantitative trait loci (QTL) analysis using normalized phenotype scores identified two QTLs on each arm of chromosome 18 (rrn-1 and rrn-2). The same QTL analysis performed with log10(x) transformed phenotype data also identified two QTLs: one on chromosome 18 overlapping the same region in the other analysis (rrn-1), and one on chromosome 11 (rrn-3). While rrn-1 and rrn-3 have been reported associated with reduced reproduction of reniform nematode, this is the first report of the rrn-2 region associated with host suitability to reniform nematode. The resistant parent allele at rrn-2 showed an inverse relationship with the resistance phenotype, correlating with an increase in nematode reproduction or host suitability. Several candidate genes within these regions corresponded with host plant defense systems. Interestingly, a characteristic pathogen resistance gene with a leucine-rich repeat was discovered within rrn-2. These genetic markers can be used by soybean breeders in marker-assisted selection to develop lines with resistance to reniform nematode.

Construction of a genetic linkage map in Pyropia yezoensis (Bangiales, Rhodophyta) and QTL analysis of several economic traits of blades

Pyropia yezoensis is an economically important seaweed but its molecular genetics is poorly understood. In the present study, we used a doubled haploid (DH) population that was established in our previous work to construct a genetic linkage map of P. yezoensis and analyze the quantitative trait loci (QTLs) of blades. The DH population was genotyped with fluorescent sequence-related amplified polymorphism (SRAP) markers. A chi-square test identified 301 loci with normal segregation (P ≥ 0.01) and 96 loci (24.18%) with low-level skewed segregation (0.001 ≤ P < 0.01). The genetic map was constructed after a total of 92 loci were assembled into three linkage groups (LGs). The map spanned 557.36 cM covering 93.71% of the estimated genome, with a mean interlocus space of 6.23 cM. Kolmogorov-Smirnov test (α = 5%) showed a uniform distribution of the markers along each LG. On the genetic map, 10 QTLs associated with five economic traits of blades were detected. One QTL was for length, one for width, two for fresh weight, two for specific growth rate of length and four for specific growth rate of fresh weight. These QTLs could explain 2.29–7.87% of the trait variations, indicating that their effects were all minor. The results may serve as a framework for future marker-assisted breeding in P. yezoensis.