David L. Hyten

Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01

BackgroundA landmark in soybean research, Glyma1.01, the first whole genome sequence of variety Williams 82 (Glycine max L. Merr.) was completed in 2010 and is widely used. However, because the assembly was primarily built based on the linkage maps constructed with a limited number of markers and recombinant inbred lines (RILs), the assembled sequence, especially in some genomic regions with sparse numbers of anchoring markers, needs to be improved. Molecular markers are being used by researchers in the soybean community, however, with the updating of the Glyma1.01 build based on the high-resolution linkage maps resulting from this research, the genome positions of these markers need to be mapped.ResultsTwo high density genetic linkage maps were constructed based on 21,478 single nucleotide polymorphism loci mapped in the Williams 82 x G. soja (Sieb. & Zucc.) PI479752 population with 1083 RILs and 11,922 loci mapped in the Essex x Williams 82 population with 922 RILs. There were 37 regions or single markers where marker order in the two populations was in agreement but was not consistent with the physical position in the Glyma1.01 build. In addition, 28 previously unanchored scaffolds were positioned. Map data were used to identify false joins in the Glyma1.01 assembly and the corresponding scaffolds were broken and reassembled to the new assembly, Wm82.a2.v1. Based upon the plots of the genetic on physical distance of the loci, the euchromatic and heterochromatic regions along each chromosome in the new assembly were delimited. Genomic positions of the commonly used markers contained in BARCSOYSSR_1.0 database and the SoySNP50K BeadChip were updated based upon the Wm82.a2.v1 assembly.ConclusionsThe information will facilitate the study of recombination hot spots in the soybean genome, identification of genes or quantitative trait loci controlling yield, seed quality and resistance to biotic or abiotic stresses as well as other genetic or genomic research.

Soybean Seed Amino Acid Content QTL Detected Using the Uni- versal Soy Linkage Panel 1.0 with 1,536 SNPs

1 Current address: Clemson Pee Dee REC, Advanced Plant Technology Center, 2200 Pocket Road, Florence, SC 29506, USA; 2 University of Tennessee, Department of Plant Sciences, 2431 Joe Johnson Dr., Knoxville, TN 37996, USA; 3 Monsanto, 140 W. Industrial Drive, Harrisburg, SD 57032, USA; 4 University of Arkansas, Department of Crop, Soil, and Environmental Sciences, Fayetteville, AR 72701, USA; 5 Southern Illinois University, Department of Plant, Soil Science and Agricultural Systems, 1205 Lincoln Drive, Carbondale, IL 62901, USA; 6 Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center – West, USDA, ARS, Beltsville, MD 20705, USA; 7 Current address: DuPont Pioneer, 8305 NW 62nd Ave., PO Box 7060, Johnston, IA 50131-7060, USA.

Multi-Population Selective Genotyping to Identify Soybean [Glycine max (L.) Merr.] Seed Protein and Oil QTLs

Plant breeders continually generate ever-higher yielding cultivars, but also want to improve seed constituent value, which is mainly protein and oil, in soybean [Glycine max (L.) Merr.]. Identification of genetic loci governing those two traits would facilitate that effort. Though genome-wide association offers one such approach, selective genotyping of multiple biparental populations offers a complementary alternative, and was evaluated here, using 48 F2:3 populations (n = ∼224 plants) created by mating 48 high protein germplasm accessions to cultivars of similar maturity, but with normal seed protein content. All F2:3 progeny were phenotyped for seed protein and oil, but only 22 high and 22 low extreme progeny in each F2:3 phenotypic distribution were genotyped with a 1536-SNP chip (ca. 450 bimorphic SNPs detected per mating). A significant quantitative trait locus (QTL) on one or more chromosomes was detected for protein in 35 (73%), and for oil in 25 (52%), of the 48 matings, and these QTL exhibited additive effects of ≥ 4 g kg–1 and R2 values of 0.07 or more. These results demonstrated that a multiple-population selective genotyping strategy, when focused on matings between parental phenotype extremes, can be used successfully to identify germplasm accessions possessing large-effect QTL alleles. Such accessions would be of interest to breeders to serve as parental donors of those alleles in cultivar development programs, though 17 of the 48 accessions were not unique in terms of SNP genotype, indicating that diversity among high protein accessions in the germplasm collection is less than what might ordinarily be assumed.

Quantitative Trait Loci (QTL) that Underlie SCN Resistance in Soybean (Glycine max (L.) Merr.) PI438489B by 'Hamilton' Re- combinant Inbred Line (RIL) Population

1 Plant Genomics & Biotechnology Lab, Department of Biological Sciences, Fayetteville State University, Fayetteville, NC, USA; 2 Department of Plant, Soil, and Agricultural Systems, Southern Illinois University, Carbondale, IL, USA; 3 Soybean Genomics and Improvement Lab, 10300 Baltimore Ave, Bldg. 006, Rm. 201, Beltsville, MD 20705; 4 Unite de Recherche En Genomique Vegetale, INRA, Ivry, France; 5 USDA-ARS Midsouth Area, Jackson, TN, USA; 6 Department of Agriculture, Alcorn State University, Alcorn State, MS, USA; 7 Plant Pathology Department and Agronomy Department, Iowa State University, Ames, IA 50011-1010.

Genetic Characterization of the Soybean Nested Association Mapping Population

40 NAM families were developed and 5600 RILs in the families were characterized. The linkage maps for each family and a composite linkage map were constructed. More than a half million high‐confidence SNPs were identified and annotated. Segregation distortion in most families favored alleles from the female parent. The REs in the soybean genome is low.

Genetic Architecture of Soybean Yield and Agronomic Traits

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.

Genome-wide Association Mapping of Qualitatively Inherited Traits in a Germplasm Collection

Genome‐wide association (GWA) is usually aimed at quantitative (but not so much at qualitative) traits. Germplasm collections have extensive data on qualitatively inherited descriptor traits. Positional location of classical genes is lacking in most crop genome sequence maps. Genome‐wide association easily generates high‐resolution genome sequence map positions for classical loci. Genome‐wide association‐based gene positions are attainable even for traits governed by digenic epistasis.

Identifying and exploring significant genomic regions associated with soybean yield, seed fatty acids, protein and oil

Soybean [Glycine max (L.) Merrill] yield and seed fatty acids, protein, and oil content are important traits for which an improved understanding of significant genomic regions would be useful. To accomplish this, a soybean population consisting of 203 F5 derived recombinant inbred lines (RILs) was developed and genotyped with 11,633 polymorphic single nucleotide polymorphisms (SNPs). Each RIL was grown in a single plot at Knoxville, TN in 2010; followed by replicated, multi-location field trials in 2013 and 2014. The data from 2010, 2013, and 2014 were analyzed together in order to detect quantitative trait loci (QTL) for these traits, and 30 total QTLs were detected. Five QTLs are candidates for confirmed status and one QTL is a candidate for positional confirmation. Many of the genes with mutations in close proximity to the fatty acid QTLs are involved in biological processes for fatty acids and/or lipids and could be considered possible candidate genes. Similarly, genes with mutations in genomic regions near yield, protein, and oil QTLs were plentiful and may contribute to the variation observed in these traits. Except for yield and stearic acid, each trait displayed pleiotropic effects with other traits in this study. Notable are the pleiotropic effects for oleic and linolenic acid on chromosomes 9, 13, and 19. Overall, the findings from this research contribute new information to the genetic understanding of soybean yield and seed fatty acids, protein and oil content. This understanding will be useful in making trait improvements.