AGenome-wide association studies (GWAS) have proven a useful technique for identifying genetic loci responsible for natural variation in rice. With the fast developed next-generation sequencing technology, it is possible for people to carry out GWAS by phenotyping different traits. However, how to make full use of huge data, abandon unnecessary data, and solve the problem of data application effectively seems still an obstacle for many researchers. Taking the case of whole-genome resequencing of Korean authentic rice core set, here we present a general technological path of GWAS including: 1) a schematic view of sequencing-based GWAS in rice; 2) a user-friendly and interactive web application for GWAS in rice by the aid of experience from Arabidopsis; 3) Haplotype and association analysis of candidate genes in a certain mechanism pathway, giving 10 starch synthesis genes as example; and 4) functional validation by Trans- and Mata-Omics analysis.