High-resolution mapping of QTL for fatty acid composition in soybean using specific-locus amplified fragment sequencing.

KEY MESSAGE: We constructed a high-density linkage map comprising 3541 markers developed by specific-locus amplified fragment sequencing, and identified 26 stable QTL including nine novel loci, for fatty acid composition in soybean. Soybean oil quality and stability are mainly determined by the fatty acid composition of the seed. In the present study, we constructed a high-density genetic linkage map using 200 recombinant inbred lines derived from a cross between cultivated soybean varieties Luheidou2 and Nanhuizao, and SNP markers developed by specific-locus amplified fragment sequencing (SLAF-seq). This map comprises 3541 markers on 20 linkage groups and spans a genetic distance of 2534.42 cM, with an average distance of 0.72 cM between adjacent markers. Inclusive composite interval mapping revealed 26 stable QTL for five fatty acids, explaining 0.4-37.0% of the phenotypic variance for individual fatty acids across environments. Of these QTL, nine are novel loci (qLA1, qLNA2_1, qPA4_1, qLA4_1, qPA6_1, qSA12_1, qPA16_1, qOA18_1, and qFA19_1). These stable QTL harbor three fatty acid biosynthesis genes (GmFabG, GmACP, and GmFAD8), and 66 genes encoding lipid-related transcription factors. These stable QTL and tightly linked SNP markers can be used for marker-assisted selection in soybean breeding programs.

Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max.

BACKGROUND: Quantitative trait locus (QTL) mapping is an efficient approach to discover the genetic architecture underlying complex quantitative traits. However, the low density of molecular markers in genetic maps has limited the efficiency and accuracy of QTL mapping. In this study, specific length amplified fragment sequencing (SLAF-seq), a new high-throughput strategy for large-scale SNP discovery and genotyping based on next generation sequencing (NGS), was employed to construct a high-density soybean genetic map using recombinant inbred lines (RILs, Luheidou2×Nanhuizao, F5:8). With this map, the consistent QTLs for isoflavone content across various environments were identified. RESULTS: In total, 23 Gb of data containing 87,604,858 pair-end reads were obtained. The average coverage for each SLAF marker was 11.20-fold for the female parent, 12.51-fold for the male parent, and an average of 3.98-fold for individual RILs. Among the 116,216 high-quality SLAFs obtained, 9,948 were polymorphic. The final map consisted of 5,785 SLAFs on 20 linkage groups (LGs) and spanned 2,255.18 cM in genome size with an average distance of 0.43 cM between adjacent markers. Comparative genomic analysis revealed a relatively high collinearity of 20 LGs with the soybean reference genome. Based on this map, 41 QTLs were identified that contributed to the isoflavone content. The high efficiency and accuracy of this map were evidenced by the discovery of genes encoding isoflavone biosynthetic enzymes within these loci. Moreover, 11 of these 41 QTLs (including six novel loci) were associated with isoflavone content across multiple environments. One of them, qIF20-2, contributed to a majority of isoflavone components across various environments and explained a high amount of phenotypic variance (8.7%-35.3%). This represents a novel major QTL underlying isoflavone content across various environments in soybean. CONCLUSIONS: Herein, we reported a high-density genetic map for soybean. This map exhibited high resolution and accuracy. It will facilitate the identification of genes and QTLs underlying essential agronomic traits in soybean. The novel major QTL for isoflavone content is useful not only for further study on the genetic basis of isoflavone accumulation, but also for marker-assisted selection (MAS) in soybean breeding in the future.

Isoflavone Content of Soybean Cultivars from Maturity Group 0 to VI Grown in Northern and Southern China.

Soybean isoflavone content has long been considered to be a desirable trait to target in selection programs for their contribution to human health and plant defense systems. The objective of this study was to determine isoflavone concentrations of various soybean cultivars from maturity groups 0 to VI grown in various environments and to analyze their relationship to other important seed characters. Forty soybean cultivars were grown in replicated trials at Wuhan and Beijing of China in 2009/2010 and their individual and total isoflavone concentrations were determined by HPLC. Their yield and quality traits were also concurrently analyzed. The isoflavone components had abundant genetic variation in soybean seed, with a range of coefficient variation from 45.01% to 69.61%. Moreover, individual and total isoflavone concentrations were significantly affected by cultivar, maturity group, site and year. Total isoflavone concentration ranged from 551.15 to 7584.07 µg g-1, and averaged 2972.64 µg g-1 across environments and cultivars. There was a similar trend regarding the isoflavone contents, in which a lower isoflavone concentration was generally presented in early rather than late maturing soybean cultivars. In spite of significant cultivar × year × site interactions, cultivars with consistently high or low isoflavone concentrations across environments were identified, indicating that a genetic factor plays the most important role for isoflavone accumulation. The total isoflavone concentration had significant positive correlations with plant height, effective branches, pods per plant, seeds per plant, linoleic acid and linolenic acid, while significant negative correlations with oleic acid and oil content, indicating that isoflavone concentration can be predicted as being associated with other desirable seed characteristics.

Evaluation of the chemical quality traits of soybean seeds, as related to sensory attributes of soymilk.

The soybean seed chemical quality traits (including protein content, oil content, fatty acid composition, isoflavone content, and protein subunits), soymilk chemical character (soluble solid), and soymilk sensory attributes were evaluated among 70 genotypes to determine the correlation between seed chemical quality traits and soymilk sensory attributes. Six sensory parameters (i.e., soymilk aroma, smoothness in the mouth, thickness in the mouth, sweetness, colour and appearance, and overall acceptability) and a seven-point hedonic scale for each parameter were developed. Significant positive correlations were observed between overall acceptability and the other five evaluation parameters, suggesting that overall acceptability is an ideal parameter for evaluating soymilk flavour. The soymilk sensory attributes were significantly positively correlated with the characteristics of the glycinin (11S)/beta-conglycinin (7S) protein ratio, soluble solid, and oil content but negatively correlated with glycitein and protein content. Our results indicated that soymilk sensory attributes could be improved by selecting the desirable seed chemical quality traits in practical soybean breeding programs.