Recent genomic research on plant populations has revealed abundant structural variations (SVs) of > 50 bp within and among genotypes of major crop species, but the application of SVs as a unique type of molecular marker in genetic research and breeding remains limited. In this study, we used a panel of 305 rice accessions from the 3000 Rice Genome Project to compare 26,000 + SVs (> 90% deletions and translocations) and 180,000 + high-quality SNPs in predicting the field performance of 20 traits using nine commonly used genomic selection models. We demonstrated that SVs had slightly lower prediction accuracies (PA) across 20 different traits than SNPs, but saved 53.8%–77.8% of computation time to achieve reasonably high PA. The major advantage of SVs as valuable markers in obtaining reliable genomic estimated breeding values (GEBVs) in GS experiments resulted primarily from their greater phenotypic effects on high heritability traits. Our results suggested that P_0.01 was an appropriate threshold for marker filtering of both SVs and SNPs to achieve high PA in genomic selection experiments. A dataset containing all identified SVs from this study has been deposited at the China National Center for Bioinformation under BioProject: PRJCA038102, a publicly accessible molecular marker resource, enabling broad applications in rice research including gene/QTL discovery, allelic mining, and genomic selection experiments.

Single nucleotide polymorphism (SNP) genotyping arrays provide an optimal high-throughput platform for genetic research and molecular breeding programs in both animals and plants. In this study, a high-quality and custom-designed Rice3K56 SNP array was developed with the resequencing data of 3024 rice accessions worldwide, which was then tested extensively in 192 representative rice samples. Printed on the GeneTitan chips of Affymetrix Axiom each containing 56,606 SNP markers, the Rice3K56 array has a high genotyping reliability (99.6%), high and uniform genome coverage (an average of 6.7-kb between adjacent SNPs), abundant polymorphic information and easy automation, compared with previously developed rice SNP arrays. When applied in rice varietal differentiation, population diversity analysis, gene mapping of 13 complex traits by a genome-wide association study analysis (GWAS), and genome selection experiments in a recombinant inbred line and a multi-parent advanced generation inter-cross populations, these properties of the Rice3K56 array were well demonstrated for its power and great potential to be a highly efficient tool for rice genetic research and genomic breeding.