Rapid Genotyping of Soybean Cultivars Using High Throughput Sequencing

Soybean (Glycine max) breeding involves improving commercially grown varieties by introgressing important agronomic traits from poor yielding accessions and/or wild relatives of soybean while minimizing the associated yield drag. Molecular markers associated with these traits are instrumental in increasing the efficiency of producing such crosses and Single Nucleotide Polymorphisms (SNPs) are particularly well suited for this task, owing to high density in the non-genic regions and thus increased likelihood of finding a tightly linked marker to a given trait. A rapid method to develop SNP markers that can differentiate specific loci between any two parents in soybean is thus highly desirable. In this study we investigate such a protocol for developing SNP markers between multiple soybean accessions and the reference Williams 82 genome. To restrict sampling frequency reduced representation libraries (RRLs) of genomic DNA were generated by restriction digestion followed by library construction. We chose to sequence four accessions Dowling (PI 548663), Dwight (PI 597386), Komata (PI200492) and PI 594538A for their agronomic importance as well as Williams 82 as a control

SSR and AFLP based genetic diversity of soybean germplasm differing in photoperiod sensitivity

Forty-four soybean genotypes with different photoperiod response were selected after screening of 1000 soybean accessions under artificial condition and were profiled using 40 SSR and 5 AFLP primer pairs. The average polymorphism information content (PIC) for SSR and AFLP marker systems was 0.507 and 0.120, respectively. Clustering of genotypes was done using UPGMA method for SSR and AFLP and correlation was 0.337 and 0.504, respectively. Mantel's correlation coefficients between Jaccard's similarity coefficient and the cophenetic values were fairly high in both the marker systems (SSR = 0.924; AFLP = 0.958) indicating very good fit for the clustering pattern. UPGMA based cluster analysis classified soybean genotypes into four major groups with fairly moderate bootstrap support. These major clusters corresponded with the photoperiod response and place of origin. The results indicate that the photoperiod insensitive genotypes, 11/2/1939 (EC 325097) and MACS 330 would be better choice for broadening the genetic base of soybean for this trait

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

Soybean BAC-based physical maps provide a useful platform for gene and QTL map-based cloning, EST mapping, marker development, genome sequencing, and comparative genomic research. Soybean physical maps for “Forrest” and “Williams 82” representing the southern and northern US soybean germplasm base, respectively, have been constructed with different fingerprinting methods. These physical maps are complementary for coverage of gaps on the 20 soybean linkage groups. More than 5,000 genetic markers have been anchored onto the Williams 82 physical map, but only a limited number of markers have been anchored to the Forrest physical map. A mapping population of Forrest × Williams 82 made up of 1,025 F8 recombinant inbred lines (RILs) was used to construct a reference genetic map. A framework map with almost 1,000 genetic markers was constructed using a core set of these RILs. The core set of the population was evaluated with the theoretical population using equality, symmetry and representativeness tests. A high-resolution genetic map will allow integration and utilization of the physical maps to target QTL regions of interest, and to place a larger number of markers into a map in a more efficient way using a core set of RILs

Identification of QTL underlying vitamin E contents in soybean seed among multiple environments

Vitamin E (VE) in soybean seed has value for foods, medicines, cosmetics, and animal husbandry. Selection for higher VE contents in seeds along with agronomic traits was an important goal for many soybean breeders. In order to map the loci controlling the VE content, F5-derived F6 recombinant inbred lines (RILs) were advanced through single-seed-descent (SSD) to generate a population including 144 RILs. The population was derived from a cross between ‘OAC Bayfield’, a soybean cultivar with high VE content, and ‘Hefeng 25’, a soybean cultivar with low VE content. A total of 107 polymorphic simple sequence repeat markers were used to construct a genetic linkage map. Seed VE contents were analyzed by high performance liquid chromatography for multiple years and locations (Harbin in 2007 and 2008, Hulan in 2008 and Suihua in 2008). Four QTL associated with α-Toc (on four linkage groups, LGs), eight QTL associated with γ-Toc (on eight LGs), four QTL associated with δ-Toc (on four LGs) and five QTL associated with total VE (on four LGs) were identified. A major QTL was detected by marker Satt376 on linkage group C2 and associated with α-Toc (0.0012 > P > 0.0001, 5.0% < R2 < 17.0%, 25.1 < α-Toc < 30.1 μg g−1), total VE (P < 0.0001, 7.0% < R2 < 10.0%, 118.2 < total VE < 478.3 μg g−1). A second QTL detected by marker Satt286 on LG C2 was associated with γ-Toc (0.0003 > P > 0.0001, 6.0% < R2 < 13.0%, 141.5 < γ-Toc < 342.4 μg g−1) and total VE (P < 0.0001, 2.0% < R2 < 9.0%, 353.9 < total VE < 404.0 μg g−1). Another major QTL was detected by marker Satt266 on LG D1b that was associated with α-Toc (0.0002 > P > 0.0001, 4.0% < R2 < 6.0%, 27.7 < α-Toc < 43.7 μg g−1) and γ-Toc (0.0032 > P > 0.0001, 3.0% < R2 < 10.0%, 69.7 < γ-Toc < 345.7 μg g−1). Since beneficial alleles were all from ‘OAC Bayfield’, it was concluded that these three QTL would have great potential value for marker assisted selection for high VE content

Using Microsatellites to Understand the Physical Distribution of Recombination on Soybean Chromosomes

Soybean is a major crop that is an important source of oil and proteins. A number of genetic linkage maps have been developed in soybean. Specifically, hundreds of simple sequence repeat (SSR) markers have been developed and mapped. Recent sequencing of the soybean genome resulted in the generation of vast amounts of genetic information. The objectives of this investigation were to use SSR markers in developing a connection between genetic and physical maps and to determine the physical distribution of recombination on soybean chromosomes. A total of 2,188 SSRs were used for sequence-based physical localization on soybean chromosomes. Linkage information was used from different maps to create an integrated genetic map. Comparison of the integrated genetic linkage maps and sequence based physical maps revealed that the distal 25% of each chromosome was the most marker-dense, containing an average of 47.4% of the SSR markers and 50.2% of the genes. The proximal 25% of each chromosome contained only 7.4% of the markers and 6.7% of the genes. At the whole genome level, the marker density and gene density showed a high correlation (R2) of 0.64 and 0.83, respectively with the physical distance from the centromere. Recombination followed a similar pattern with comparisons indicating that recombination is high in telomeric regions, though the correlation between crossover frequency and distance from the centromeres is low (R2 = 0.21). Most of the centromeric regions were low in recombination. The crossover frequency for the entire soybean genome was 7.2%, with extremes much higher and lower than average. The number of recombination hotspots varied from 1 to 12 per chromosome. A high correlation of 0.83 between the distribution of SSR markers and genes suggested close association of SSRs with genes. The knowledge of distribution of recombination on chromosomes may be applied in characterizing and targeting genes