Development of an Integrated Breeding System for Genomics-Based Crop Improvement

Next generation technology is increasingly popular in agriculture especially in plant breeding area, and it is also suggesting new ways of marker development and trait identification. Many agriculturally important crops including rice, maize, soybean, tomato, potato, and cotton have been sequenced and many more NGS based genomes will be available. With those reference genome sequences, resequencing or reduced representation of genome (GBS, RAD etc.) is becoming a routine strategy to efficiently generate sequence information from hundreds of individuals and identify tremendous amount of sequence based genetic variations. Moreover, coupled with highly accurate phenotyping data, the genetic variations identified will be used to determine direct/indirect association for traits of interest in agriculture. The genetic variation collected from multi-parental population will help to identify even minor quantitative trait loci (QTLs) and predict genomic estimated breeding value (GEBV) to practice precision breeding with genomic selection (GS) approach. NGS in a long run will provide applications to increase the breeding efficiency but there are a few huddles to be addressed; NGS data management, discovery tools and data visualization. We are developing an integrated system in order to support the genomics-based molecular breeding funded by Next-Generation BioGreen21 Program (PJ011011). The objectives of the project 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. It is expected breeder can easily manage genomic data, process NGS sequences and extract information using the integrated breeding system. The plant breeding is evolving to genomics-assisted molecular breeding and the outcomes from the project will contribute to develop new and superior crops efficiently.