DOI: 10.6084/m9.figshare.20098733.v1
title: Additional file 1 of Assessment of Rice Sheath Blight Resistance Including Associations with Plant Architecture, as Revealed by Genome-Wide Association Studies

description: Additional file 1. Table S1: Percentages of the entire RDP1, and of each subpopulation that were classified as resistant (R), moderately resistant (MR), moderately susceptible (MS), and susceptible (S) based on their field and microchamber disease index (DI) sheath blight (ShB) severity scores. Percentages based on height, heading, tillering, and panicle number are also shown. O. sativa subpopulations are: aus (AUS), indica (IND), temperate japonica (TEJ), tropical japonica (TRJ), aromatic (ARO). Table S2: Pearson correlations across all RDP1 (same as Table 2) and subpopulation panels. Correlation values (r) are blue if significantly positive, red if significantly negative, and black if not significant at α = 0.05. Significance at α = 0.05, α = 0.01, and α = 0.001 are indicated with *, **, and ***, respectively. Sheath blight (ShB) response was evaluated in Arkansas, USA (AR) and Nanning, China (NC) using both field scoring and microchamber disease index (DI). Plant height and days to heading were evaluated in the same AR and NC field plots. Culm habit was rated only in AR. Tiller and panicle number per plant were evaluated in potted plants grown in the greenhouse. Tiller number was counted in young plants at the 5- to 6-week age (mid-tillering stage), panicle number was determined from the same plants grown to maturity. Table S3: List of all the trait associated SNPs identified by the GWA analysis in chromosomal order. The 18 sheath blight (ShB) QTL regions, 15 tiller number (TN) QTL and 14 panicle number (PN) QTL reported in this study are identified in the first three columns, respectively. Table S4: List of the trait-associated SNPs in the QTL regions identified by GWA for ShB (sheath blight), TN (tiller number), and PN (panicle number) selected from the SNPs listed in Table S3. In the QTL column, the yellow highlight identifies the targeted peak SNP within the QTL region reported in Table 3 (ShB-QTL) or Table 4 (TN-QTL, PN-QTL). The starting and ending SNP are in bold to indicate the beginning and end of the QTL region. Table S5: Comparison of the targeted SNP reference allele frequency in the selected RDP1 panel to the reference allele frequencies across the five rice subpopulations for the 4,726 O. sativa accessions included in the RiceVarMap v2.0 database (Zhao et al. 2014). Table S6: A summary of quantitative trait loci (QTL) for sheath blight resistance reported in other GWA and biparental studies that were in the same regions as the ShB GWA-QTL reported in this study. [QTL identified in biparental populations are based on reviews by Jia et al. (2009), Molla et al. (2020) and Srinivasachary et al. (2011).]. Table S7: List of all the significant peak SNPs for ShB identified by the GWA analyses of the RDP1 (present data) and RMC using the ShB-DI LSmeans reported in Jia et al. (2012) and the genotypes for 167 RMC accessions based on 3,200,320 SNPs. The RDP1 GWA-QTL and previously reported SSR markers significantly associated with ShB (Jia et al. 2012) are listed in the first column. The "RMC SNP GWA QTL" column identifies the GWA-QTL based on the SNP genotypes for 167 RMC accessions as reported in this study, and the starting and ending SNPs of the QTL region are highlighted in dark magenta. (RMC is the Rice Minicore association mapping panel). Table S8: Phenotypic and genotypic data for the Rice Diversity Panel 1 (RDP1) accessions used for GWA-mapping that identified 18 QTL for rice sheath blight (ShB) resistance. Phenotypes provided are LSmeans calculated across replications for ShB-scores collected in Arkansas, USA (AR) and Nanning, China (NC) in field plots and using a microchamber disease index (DI) method. Plant height and days to heading (DH) were measured in ShB inoculated field plots. Tiller number (TN) BLUEs were calculated across three replications of greenhouse grown plants 5- to 6-weeks of age at time of tiller counting. Also provided are the Genetics Stocks-Oryza (GSOR) accession numbers and names, originating country, and subpopulation group based on Wang et al. (2018). Three sets of example selections are provided, one based on a combination of AR-field and NC-field performance, a second based on AR-DI and NC-DI scores, and a third based on the number of R alleles estimated in each accession based on QTL-related SNP alleles (Table S4). For estimating the total number of R alleles contained in each RDP1 at the 18 reported ShB-QTL, accessions were estimated to contain the R allele for a QTL when it contained an R-associated allele for one or more peak SNP(s) per QTL, as detailed in columns AM to BG per subpopulation. 'Fail' indicates a failed reaction thus, no SNP genotype was called for a particular accession, 'na' indicates a particular QTL was not applicable to accessions in that subpopulation group. Table S9: Phenotypic gains from selections based on marker-predicted number of R-alleles for each accession and summarized by subpopulation and number of R-alleles. Phenotypes provided are LSmeans calculated across replications for ShB scores collected in Arkansas, USA (AR) and Nanning, China (NC) in field plots and using a microchamber disease index (DI) method. Plant height and days to heading (DH) were measured in ShB inoculated field plots. Tiller number data are BLUEs calculated across three replications of plants whose tillers were counted at 5- to 6-weeks of age, the mid-tillering stage