Additional file 1 of Genomic regions associated with important seed quality traits in food-grade soybeans
Creators: name: Whiting, Rachel M.
name: Torabi, Sepideh
name: Lukens, Lewis
name: Eskandari, Milad
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: FOS: Biological sciences

description: Additional file 1 : Supplementary Table S1. Mean, standard error (α = 0.05), range, and parental means for soybean seed protein concentration (%, dry weight basis) in two RIL populations, ‘AC X790P’ x ‘S18-R6’ and ‘AC X790P’ x ‘S23-T5’, in five environments: Chatham 2015, Chatham 2016, Merlin 2015, Merlin 2016 and Palmyra 2016. Supplementary Table S2. Mean, standard error (α = 0.05), range, and parental means for soybean seed yield (tonnes ha− 1) in two RIL populations, ‘AC X790P’ x ‘S18-R6’ and ‘AC X790P’ x ‘S23-T5’, in five environments: Chatham 2015, Chatham 2016, Merlin 2015, Merlin 2016 and Palmyra 2016. Supplementary Table S3. Mean, standard error (α = 0.05), range, and parental means for soybean seed weight (100 seed weight in grams) in two RIL populations, ‘AC X790P’ x ‘S18-R6’ and ‘AC X790P’ x ‘S23-T5’, in five environments: Chatham 2015, Chatham 2016, Merlin 2015, Merlin 2016 and Palmyra 2016. Supplementary Table S4. Mean, standard error (α = 0.05), range, and parental means for soybean seed sucrose concentration (%, dry basis) in two RIL populations, ‘AC X790P’ x ‘S18-R6’ and ‘AC X790P’ x ‘S23-T5’, in five environments: Chatham 2015, Chatham 2016, Merlin 2015, Merlin 2016 and Palmyra 2016. Supplementary Table S5. Broad-sense heritability of protein concentration, sucrose concentration, seed weight and seed yield in two RIL populations evaluated in five environments (CHA15, CHA16, MER15, MER16 and PAL16). Supplementary Table S6. Pearson correlation coefficients for seed protein and sucrose concentrations, 100-seed weight, and seed yield in five environments (Chatham 2015, Chatham 2016, Merlin 2015, Merlin 2016, and Palmyra 2016) as well as the combined environment for the recombinant inbred line populations. Supplementary Table S7. Summary of major putative QTL (R2 &gt; 10.0%) associated with soybean seed protein concentration, sucrose concentration and seed weight with potential use in marker-assisted selection, candidate genes, and co-localized QTL in the previous studies. Supplementary Table S8. Major putative QTL (R2 &gt; 10.0%) associated with soybean seed sucrose concentration, yield and seed weight with potential use in marker-assisted selection, identified by multiple QTL mapping (MQM) in RIL populations examined under combined Ontario environments in 2015 and 2016. Supplementary Table S9. Whole-seed (dry basis) calibration values for oil, protein, Moisture and fatty acid components, as provided by Perten Instruments. The coefficient of determination for cross-validation (R2CV) explains the proportion of variance that can be predicted between reference chemistry and predicted values. The minimum and maximum values are the limits of the prediction range. The SECV is the standard error of cross validation, where samples are removed from the validation set and predicted, and the total error for the dataset is calculated. Factors shows the number of factors included in the calibration equation for a given trait. Samples shows the total number of samples used in the calibration. Calibration file dates for each trait are listed.