,A panel of single nucleotide polymorphisms (SNPs) for 363 common bean accessions was generated. A genome-wide association study (GWAS) was applied to detect SNPs significantly associated with resistance to Heterodera glycines (HG) also known as the soybean cyst nematode (SCN) in the core collection of common bean, Phaseolus vulgaris. There were 84,416 SNPs identified in 363 common bean accessions.,,

,Soybean aphid (Aphis glycines Matsumura; SA) is a major invasive pest of soybean [Glycine max (L.) Merr.] in northern production regions of North America. Although insecticides are currently the main method for controlling this pest, SA-resistant cultivars are being developed to sustainably manage SA in the future. The viability of SA-resistant cultivars may depend on identifying a diverse set of resistance genes from screening various germplasm sources, including wild soybean (Glycine soja Siebold and Zucc.), the progenitor of cultivated soybean. Data consisted of infestation ratings generated for a total of 337 distinct plant introduction lines of wild soybean that were exposed to avirulent SA biotype 1 for 14 d in 25 separate tests. Individual plants of the test lines were given a common rating by two researchers, based on a rating scale that progressed from 1=0 to 50, 2=51 to 100, 3=101 to 150, 4=151 to 200, 5=201 to 250, and 6 with >250 SA per test plant. Public dissemination of this dataset will allow for further analyses and evaluation of resistance among the test lines.,,

,Phenotypic Data A subset of 264 lines from the National Small Grains Collection global hexaploid winter wheat germplasm collection was evaluated under controlled growth chamber conditions for reaction to the pathogens Parastagonospora nodorum and Pyrenophora tritici-repentis. Both infiltrations and inoculations were performed on plants planted in plastic cones and when seedlings were at the second leaf stage. Plants were infiltrated with the P. nodorum necrotrophic effectors (NEs) SnTox1, SnToxA, SnTox3, SnTox267, and SnTox5; and the P. tritici-repentis NE Ptr ToxB. The scoring system was 0-3, with reaction types of 2 and 3 considered sensitive and 0 to 1 were insensitive. Plants were inoculated with the P. nodorum isolates Sn4, Sn2000, AR2-1, SnIr05H71a, and NOR4 and P. tritici-repentis isolates Pti2, 86-124, DW5, and AR CrossB10. After inoculation, plants were placed in a 100 % humidity growth chamber at 21 °C for 24 hours under constant light, then moved to a controlled growth chamber at 21 °C with a 12 h photoperiod. Plants were scored at 7 days post inoculation. For P. nodorum, plants were scored using a 0 to 5 scale, with 0 being highly resistant and 5 being highly susceptible. For P. tritici-repentis, plants were scored using a 1 to 5 scale, with 1 being highly resistance and 5 being highly susceptible. Three homogeneous replicates (determined by Bartlett’s chi squared analysis) were used to calculate an average value for each trait. This value was used for the rest of the analysis.,Genotypic Data DNA of the winter wheat panel was extracted and genotyped using the Illumina iSelect 90k wheat SNP array. Clustering data was analyzed using GenomeStudio 2.0.5 from Illumina, Inc. SNPs were ordered based on their physical position in the Chinese Spring IWGSC RefSeq v2.0. In TASSEL v5.2, SNP markers were filtered with a minor allele frequency greater than 0.01 and missing data less than 50%. For the remaining markers, missing values were imputed using the LD-KNNi method.,Genome-wide association analysis data Association mapping was conducted using the R package GAPIT v.3. The filtered hapmap file was used for the association mapping, along with the average value for each phenotypic trait. The models GLM, MLM, MLMM, FarmCPU, and Blink were run on the averages for each trait. ** Resources in this dataset:,

,This data is from the manuscript titled: "Genetic variation among 481 diverse soybean accessions, inferred from genomic re-sequencing". SNP calls were obtained from resequencing 481 diverse soybean lines comprising 52 wild (Glycine soja) and 429 cultivated (Glycine max). This dataset contains 6 gzipped VCF (Variant Call Format) files with variant calls for all 481 USB accessions, all G. max accessions, G. soja accessions, accessions sequenced at 15x coverage, accessions sequenced at 40x coverage, and 106 accessions re-sequenced from a previous study (Valliyodan et al. 2016). SNPs were called using the Haplotype caller algorithm from the Genome Analysis Toolkit (GATK) version gatk-2.5-2-gf57256b. A total of 7.8 million SNPs were identified between the 481 re-sequenced accessions. SNPs were assigned IDs using the script "assign_name.awk" available at https://github.com/soybase/SoySNP-Names. SNP effects were predicted using SnpEff 3.0.,Dataset also available at https://soybase.org/data/v2/Glycine/max/diversity/Wm82.gnm2.div.Valliyodan_Brown_2021/,Funding support provided by the United Soybean Board for the large-scale sequencing of soybean genomes (project #1320-532-5615), Bayer (previously Monsanto and Bayer), and Corteva (previously Dow AgroSciences), with in-kind support for analysis from USDA Agricultural Research Service project 5030-21000-069-00-D.,Resources in this dataset:,,

,The soybean aphid (Aphis glycines) is an insect pest of cultivated soybeans (Glycine max). Several genes with resistance to A. glycines (i.e. Rag genes) have been identified in soybean. Virulent strains of soybean aphid are able to overcome the resistance and colonize soybeans having one or more Rag genes. It is important to classify virulent strains of soybean aphids in evaluating soybean lines in order to develop cultivars with durable resistance. The files presented here report the number of soybean aphids on soybean lines that differed in the Rag genes they contained. Two colonies of soybean aphid were tested.,Tests were conducted separately against the two soybean aphid colonies, which were maintained on soybean plants at North Central Agricultural Research Laboratory (NCARL), USDA-ARS, Brookings, South Dakota, USA, largely according to procedures described in Hesler and Tilmon (2018). The first colony was established from a single aphid collected near Volga, South Dakota, USA in 2016 and designated as ‘Volga16’ (Conzemius et al. 2019). It was reared on soybean cultivar ‘LD12R12-15805Ra’ (Rag1+Rag2 pyramid; University of Illinois, Urbana-Champaign, IL, USA).,A second colony designated ‘Accrue’ was derived from a colony originally established from a single first instar isolated from aphids collected at Urbana, IL, USA, and initially reared in Urbana (‘Urbana clone’; Hill et al. 2004). This colony was established as an avirulent soybean aphid colony (Hill et al. 2004). A series of sequential colonies from the initial colony was established, in order, at The Ohio State University, Wooster, OH, USA; Iowa State University, Ames, IA, USA; South Dakota State University, Brookings, SD, USA; and finally, in 2018 at NCARL. Although established as an ostensibly avirulent colony derived from the ‘Urbana clone’ colony, it was unexpectedly virulent against a known resistant accession, LD05R-16137 (containing Rag1), in initial screening tests.,Two separate no-choice tests were run for each soybean aphid colony. Each test consisted of seven soybean lines. Six had one or more Rag genes: 19APH18 (Rag1), 19APH25 (Rag2), 19INC (Rag3), 19APH29 (Rag4), 19APH30 (Rag6), 19APH09Rag12 (a Rag1+Rag2 pyramid); and ‘Titan,’ an aphid-susceptible soybean cultivar (Diers et al. 1999). Two-week-old, unifoliate-stage soybean plants growing in plastic pots (6 cm top diameter, 4 cm bottom diameter, 5.7 cm height) were each infested with 10 apterous adult soybean aphids and covered with a clear plastic, ventilated, cylindrical tube. After 20 days in an environmental chamber, the shoots of test plants were clipped at soil level, placed individually in sealable plastic bags, and stored in a freezer. Plants were removed over the next few days, and the aphids on them were counted. The data are contained in separate files—one for each of two soybean aphid colonies.,

,A field experiment focused on three legumes (soybeans [Glycine max], mothbeans [Vigna aconitifolia], and tepary bean [Phaseolus acutifolius]) was conducted in El Reno, OK over a two year period (2018, 2019). The split-split plot design for the legumes were subject to various row spacing (38cm and 76cm) and irrigation regimes (irrigated and rainfed). Sampling of the plots took place a total of seven times over the two year period. Each of the samplings included an initial triplicate (averaged) hyperspectral readings using a spectroradiometer (350nm to 2500nm; FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA), in-situ measurements (canopy cover [collected with the “Canopeo” app where a ratio of plant to ground pixels were calculated], chlorophyll content [collected with Chlorophyll Content Meter-300, Opti-Sciences, Hudson, NH, USA]), and biomass clipping for various laboratory analytics (dry weight, nitrogen/carbon content, crude protein, neutral detergent fiber, acid detergent fiber, in vitro true digestibility). Locations for sampling (n=334) within the 4m x 3m plots were chosen at random.,

Public information on BRS applications for genetically engineered permits, notifications, and petitions.

,Information on crop genotype- and phenotype-metabolite associations can be of value to trait development as well as to food security and safety. The unique study presented here assessed seed metabolomic and ionomic diversity in a soybean (Glycine max) lineage representing ~35 years of breeding (launch years 1972–2008) and increasing yield potential. Selected varieties included six conventional and three genetically modified (GM) glyphosate-tolerant lines. A metabolomics approach utilizing capillary electrophoresis (CE)-time-of-flight-mass spectrometry (TOF-MS), gas chromatography (GC)-TOF-MS and liquid chromatography (LC)-quadrupole (q)-TOFMS resulted in measurement of a total of 732 annotated peaks. Ionomics through inductively-coupled plasma (ICP)-MS profiled twenty mineral elements. Orthogonal partial least squares-discriminant analysis (OPLS-DA) of the seed data successfully differentiated newer higher-yielding soybean from earlier lower-yielding accessions at both field sites. This result reflected genetic fingerprinting data that demonstrated a similar distinction between the newer and older soybean. Correlation analysis also revealed associations between yield data and specific metabolites. There were no clear metabolic differences between the conventional and GM lines. Overall, observations of metabolic and genetic differences between older and newer soybean varieties provided novel and significant information on the impact of varietal development on biochemical variability. Proposed applications of omics in food and feed safety assessments will need to consider that GM is not a major source of metabolite variability and that trait development in crops will, of necessity, be associated with biochemical variation.,,

These data show grass crop and model species response to toxic chemicals (Arsenic (As)) and humic acids. Experiments were performed by collaboration between the U.S. Geological Survey, Rutgers University, and Rey Juan Carlos University. A series of individual experiments investigated beneficial effects of endophytic bacteria on grass crop growth and resilience to known plant toxicity.

These data show grass crop and model species response to toxic chemicals (Arsenic (As)) and humic acids. Experiments were performed by collaboration between the U.S. Geological Survey, Rutgers University, and Rey Juan Carlos University. A series of individual experiments investigated beneficial effects of endophytic bacteria on grass crop growth and resilience to known plant toxicity.