In recent years, with the rapid development of sequencing technology, a massive quantity of genomic data has been accumulated, thus laying a solid foundation for mining excellent genes at whole genome-wide, constructing new breeding strategies, and developing genome-targeted breeding by design platform. In the past decade, the team at the Zhejiang University College of Agriculture and Biotechnology led by Prof. HU Yan, Assoc. Prof. FANG Lei, Dr. SI Zhanfeng and Prof. ZHANG Tianzhen has been committed to cotton precision breeding. They have successfully developed a cotton whole-genome selectionbreeding by design platform that features high throughput, precision, efficiency, and cost-effectiveness.
On the basis of the released high-quality data, the team worked in collaboration with MolBreeding Biotechnology Co. Ltd. and developed a liquid single nucleotide polymorphism (SNP) chip named "ZJU Cotton SNP40K" through genotyping by targeted sequencing. The SNP set for the chip was selected from nearly 1,000 cotton accessions. After rigorous selection, the final array included 40,071 core SNPs evenly distributed across 26 chromosomes and 11,099 SNPs were within genic regions. Experiments revealed that this chip could be successfully applied to the construction of genetic map, QTL mapping and so on.
The team also constructed a comprehensive cotton multi-omics database-COTTONOMICS. It is an easily accessible web database that integrates 32.5 TB of omics data including seven assembled genomes, resequencing data from 1,180 allotetraploid cotton accessions and RNA-sequencing (RNA-seq), small RNA-sequencing (smRNA-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), DNase hypersensitive sites sequencing (DNase-seq), Bisulfite sequencing (BS-seq) and so on. COTTONOMICS allows users to employ various search scenarios and retrieve information concerning the cotton genomes, genomic variation (SNPs, InDels and STRs), gene expression, smRNA expression, epigenetic regulation and whole-genome associated loci of important agricultural traits. The user-friendly web interface offers a variety of modules for storing, retrieving, analyzing and visualizing cotton multi-omics data for diverse purposes, thereby enabling users to carry out population genetics research more conveniently and identify potential genes with important breeding value more efficiently.
