P0564
Development of a Gene-Based Breeding System in Cotton: A New Method Powerful and Efficient for Enhanced Fiber Quality Breeding

Yun-Hua Liu , Texas A&M University, College Station, TX
Yang Xu , Department of Botany & Plant Sciences, University of California - Riverside, Riverside, CA
Meiping Zhang , Department of Soil and Crop Sciences, Texas A&M University, College Station, TX
Sing-Hoi Sze , Department of Computer Science and Engineering and Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX
C. Wayne Smith , Department of Soil and Crop Sciences, Texas A&M University, College Station, TX
Shizhong Xu , Department of Botany & Plant Sciences, University of California - Riverside, Riverside, CA
Hong-Bin Zhang , Department of Soil and Crop Sciences, Texas A&M University, College Station, TX
Continued crop genetic improvement will largely depend on application of new technologies. We previously cloned 474 GFL (Gossypium Fiber Length) genes using the gExpress technology (U.S. Patent Serial No.: 62/298,606). Here we report a gene-based breeding (GBB) method using these GFL genes. GBB designs and breeds superior cultivars based on alleles and expression profiles of the genes controlling the targeted trait. For targeted gene allele selection, we identified 740 SNP/InDels from 226 of the 474 GFL genes that increased or decreased fiber length by 2.1% - 22.6% and 185 genes that gave better-parent heterosis or heterozygous weakness on fiber length by 2.1% - 16.4%. We found the numbers of favorable alleles of these 226 genes were significantly associated with fiber length (r = 0.84, P = 0.00E+00). Using these results we developed a gene allele selection chip that allows designing and breeding superior fiber quality cultivars. Furthermore, we predicted the fiber length with nine genomic selection models using both the GFL SNPs/InDels and the GFL expression profiles. The 226 GFL SNPs/InDels predicted fiber length at a correlation coefficient between predicted and observed fiber length of r = 0.43 – 0.58 (P = 0.00E+00) and the GFL expression profiles predicted fiber length at r = 0.67 – 0.85 (P = 0.00E+00), while none of the randomly-selected gene controls could predict fiber length. These results provide a new line of evidence on the efficiency of the gExpress technology in genome-wide high-throughput gene cloning and an efficient method for enhanced cotton fiber quality breeding.