Development of an Integrated System to Support Genomics-Based Crop Improvement

Next generation sequencing (NGS) technologies make it easier to generate various “omics” data, and improved bioinformatics algorithms allow collectively interpreting genomes, transcriptomes, regulatory elements and their interactions. Many agriculturally important crops including rice, maize, soybean, tomato, potato, and cotton have been sequenced and many more genomes are under way. With those genome sequences, resequencing or Genotyping-By-Sequencing (GBS) approach allows efficiently collecting sequence information from hundreds of individuals to identify genetic variations in populations. Coupled with high-throughput phenotyping data, the genetic variations in populations will be used to predict direct/indirect association of traits of interest using association mapping. The genetic variation in multi-parental population also will be served to identify minor quantitative trait loci (QTLs) and even predict genomic estimated breeding value (GEBV) to practice precision breeding using genomic selection (GS) approach. We are developing an integrated system in order to support the genomics-based molecular breeding supported by "Next-Generation BioGreen21 Program (PJ011011)" and the objectives are; 1) to construct an integrated genome database including genomes, annotations, transcriptomes, molecular markers, SNP information, 2) to develop an efficient pipeline for variant discovery using NGS data, and 3) to develop a visualization tool for browsing variants and tools for marker development. The conventional molecular breeding is evolving to genomics-assisted molecular breeding and this effort contributes to effectively develop new and better crops.