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Supplemental Material for Ramstein et al., 2020

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posted on 2020-03-09, 15:46 authored by Guillaume P. Ramstein, Sara J. Larsson, Jason P. Cook, Jode W. Edwards, Elhan S. Ersoz, Sherry Flint-GarciaSherry Flint-Garcia, Candice A. Gardner, James B. Holland, Aaron J. Lorenz, Michael D. McMullen, Mark J. Millard, Torbert R. Rocheford, Mitchell R. Tuinstra, Peter J. Bradbury, Edward S. Buckler, M. Cinta Romay

Table S1 describes interactions between genotypes and panels. Table S2 describes high-confidence QTL effects in Ames-H and NAM-H, based on GWAS models and BSLMMs. Table S3 shows summary statistics about genomic inbreeding in Ames-H. Table S4 describes the difference in accuracy from Ames×PHZ51 to Ames×B47 for prediction in NAM-H. Table S5 describes prediction accuracy in NAM-H by directional effects of inbreeding in Ames-H. Table S6 describes prediction accuracy from GWAS models. Table S7 presents the significance of variance partition by panel and functional feature. Table S8 describes genomic heritability captured by functional classes in functional enrichment models. Table S9 describes genomic prediction accuracy of functional enrichment models. Figure S1 shows the population clusters in Ames-H, inferred by k-means clustering (k = 4). Figure S2 depicts linkage disequilibrium in Ames-H and NAM-H. Figure S3 shows allele frequency among female parents in Ames-H and NAM-H. Figure S4 shows the significance of marginal additive effects in GWAS in Ames-H and NAM-H. Figure S5 shows the SNP enrichment by bin, for structural and evolutionary features in Ames-H and NAM-H. Figure S6 shows the SNP enrichment by bin, for structural and evolutionary features in Ames-H and NAM-H, while accounting for enrichment by gene proximity.


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Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize

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