Supplemental Material for Bajgain, Zhang, and Anderson, 2019
datasetposted on 29.05.2019 by Prabin Bajgain, Xiaofei Zhang, James A. Anderson
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Table S1: No. of SNPs distributed across the IWG genome (21 chromosomes). Physical length of the chromosomes are shown in base pairs (based on v2.1 reference genome). The no. of QTL detected in each chromosome is correlated with a) no. of SNPs in the respective chromosome, and b) the length of the respective chromosome.
Table S2: Output from the program STRUCTURE for K=1 to K= 10, summarized by Structure Harvester.
Table S3: Complete table of significant SNPs detected in the study. In the manuscript, we have only displayed common QTL in Table 2, which is the truncated version of this table.
Table S4: Several attributes of SNPs that were significantly associated with the yield and yield component traits in this study. There are 11 columns in this sheet, which are (from left to right): trait the SNP is associated with, SNP name, chromosome the SNP is positioned in, physical position of the SNP, estimate of the allelic effect from GWAS, percentage of phenotypic variation explained by the SNP (R2), major SNP allele, minor SNP allele, minor allele frequency, favorable allele, and if the favorable allele is major or minor.
Table S5: Frequencies of favorable alleles belonging to the significant SNPs detected in this study compared with that from the first cycle of IWG breeding and the University of Minnesota (UMN_C1). Note that significant SNPs detected in this study does not mean they were also significantly associated with these traits in UMN_C1.
Table S6: Comparison of QTL detected by Zhang et al (2017) and our study. Some of this data is displayed in Figure 5.