MOESM1 of Global survey of rice breeders to investigate characteristics and willingness to adopt alternative breeding methods

Additional file 1. Transcript of the actual survey

IRRI MET 2011 2012 phenotype data all files

This archive contains the raw multi-environment (MET) phenotype data used for the MET GS experiments reported in this publication. Each .csv file in the archive contains the data for a particular year, season, and site. See ReadMe file for description of columns

RYT_plotdata_by_GHID_corrected_PUBLIC_ACCESS

contains the raw phenotype data for genotyped individuals for 2009-2012, dry and wet seasons, used in Spindel et al., 2015

binned_subsets_2_14

contains the evenly distributed genotype subsets used in Spindel et al., 201

MET_crfilt_.90_outliers_removed_for_RRBlup

Post-imputation GBS dataset used specifically for GS cross-validation in Spindel et al., 2015. Dataset contains all markers with call rates >= .9 and lines that were included in the GS analysis (i.e., sub-population outliers are removed from this dataset). The data are formatted for use with the R rrBLUP package

Genome-Wide Association Mapping for Yield and Other Agronomic Traits in an Elite Breeding Population of Tropical Rice (<i>Oryza sativa</i>)

<div><p>Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.</p></div

CV experiments.

<p>*AS = all seasons, DS = dry season only, WS = wet season only</p><p>CV experiments.</p