P0199 Genome-wide SNP Development and Validation for Allotetraploid Gossypium

Amanda M. Hulse , Texas A&M University, College Station, TX
Fei Wang , Texas A&M University, College Station, TX
Kevin A. Hoegenauer , Texas A&M University, College Station, TX
David Stelly , Texas A&M University, College Station, TX
Hamid Ashrafi , University of California, Davis, CA
Allen Van Deynze , University of California, Davis, CA
John Z. Yu , USDA-ARS-SPARC, College Station, TX
Z. Jeffrey Chen , The University of Texas at Austin, Austin, TX
Joshua Udall , Brigham Young University, Provo, UT
Don C. Jones , Cotton Incorporated, Cary, NC
Efforts toward development of cotton SNPs have been few and mostly small-scale.  Novel cotton fiber ESTs were developed from normalized non-clonal cDNA libraries of Gossypium species that were sequenced using complementary 454 and Illumina technologies.  A hybrid de novo assembly of G. hirsutum cv. TM-1 read was carried out to construct reference sequence contigs. After differentiating SNPs from A versus D genome-specific polymorphisms (GSPs) by mapping reads to the reference sequences, over 10,000 putative SNP markers were identified for differences among five Upland cotton (G. hirsutum) lines and relative to the other cultivated tetraploid species, G. barbadense, which has far superior fiber length and quality.  Many more SNPs were also identified relative to G. longicalyx, a diploid source of extreme resistance to reniform nematodes.  The Kaspar Assay of Kbiosciences was used to assess a sample of putative SNPs by screening TM-1 (G. hirsutum), 3-79 (G. barbadense), F1 euploid and hypoaneuploid cytogenetic stocks, radiation hybrids and certain 2x and 4x wild species.  We are validating putative SNPs by linkage mapping.  The numbers and positions of SNP assay clusters suggest locus number varies from 1 to 4 or higher.  To contend with the extreme complexity of the cotton genome, we are using cytogenetic stocks, linkage mapping and radiation hybrid mapping as independent assessments of structure. SNP maps will be used to associate valuable complex traits, such as fiber length, disease resistance, improved yield potential and stress tolerance, with specific markers and render them amenable to marker-assisted selection (MAS).