An intelligent marker-selection system for crop (rice, maize, wheat) genetic breeding Previous GWAS and resequencing analysis of crop germplasm has identified millions SNP markers that can be selected for breeding purposes.
Our Lab is using new generation sequencing platforms including Illumina, PacBio, and comparative-genomics methods to study the crop genomes. We have accomplished several projects and still been working on several new genomes, including:
Genomic selection-assisted breeding mode Compared to molecular marker-assisted breeding (MAB), genomic selection (GS) is a new frontier that uses large numbers of SNP markers to predict breeding values to select candidate lines for hybridization.
Precision nutritional genomics and human health As an adjunct member of the Beijing Human Health and Food Nutrition Innovative Center, we are interested in discovering the relationship between natural genetic variations between different human population and the different efficiency of nutrition intake.
For genetic improvement of crop species, genome-wide association analysis (GWAS) is a rapid way to identify the genes contributing to the variation of important agronomic traits, and the behind principles are population genetics.
Rapid advances in high-throughput genomic technology have enabled biology to enter the era of ‘Big Data’ (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data.