|CABRERA, ANTONIO - The Ohio State University|
|GUTTIERI, MARY - University Of Nebraska|
|SMITH, NATHAN - Bhn Research, Bhn Seed|
|SOUZA, EDWARD - Bayer Cropscience|
|HUA, DUC - The Ohio State University|
|GRIFFEY, CARL - Virginia Polytechnic Institution & State University|
|BARNETT, MARLA - Limagrain Cereal Seeds|
|MURPHY, PAUL - North Carolina State University|
|OHM, HERB - Purdue University|
|UPHAUS, JIM - Pioneer Hi-Bred International|
|SORRELLS, MARK - Cornell University|
|HEFFNER, E - Dupont Pioneer Hi-Bred|
|VAN SANFORD, DAVID - University Of Kentucky|
|SNELLER, CLAY - The Ohio State University|
Submitted to: Journal of Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/7/2015
Publication Date: 11/1/2015
Publication URL: http://handle.nal.usda.gov/10113/4470284
Citation: Cabrera, A., Guttieri, M., Smith, N., Souza, E., Sturbaum-Abud, A.K., Hua, D., Griffey, C., Barnett, M., Murphy, P., Ohm, H., Uphaus, J., Sorrells, M., Heffner, E., Brown Guedira, G.L., Van Sanford, D., Sneller, C. 2015. Identification of milling and baking quality QTL in multiple soft wheat mapping populations. Journal of Theoretical and Applied Genetics. 128(11):2227-2242. doi: 10.1007/s00122-015-2580-3.
Interpretive Summary: Soft wheat is grown in the northeastern U.S. and is used primarily for baking diverse end products including pastries, cookies, and crackers. Hard wheat, grown in the Great Plains, is used almost exclusively for bread making. For both hard and soft wheat, milling and baking quality has been shown to be genetically inherited, however, due to the different end product flour requirements, the desired quality parameters differ for hard and soft wheat. Because milling and baking quality describes a complex set of traits, genetic mapping for quality identifies multiple sites across the genome with small effects on quality. Additionally, most published studies for genetic mapping of milling and baking quality have been performed using hard wheat. We studied inheritance of quality parameters to genetically map quality traits in soft wheat using multiple populations and diverse types of genetic markers. We identified two genetic regions on chromosomes 1B and 2B providing consistently significant effects on quality among the different populations used and allowing us to specify markers that can be applied to select milling and baking quality in soft wheat. Markers to select for the favorable traits on these chromosomes will be useful for breeders making selections for good quality when developing new wheat lines. Furthermore, the influence of these two regions on quality parameters allows for further investigation to uncover the genes and biochemical pathways influencing milling and baking quality.
Technical Abstract: Wheat derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL/1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify Quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 72 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.