Poster # 126

Ahmad H. Sallam¹, Matthew Haas², Yadong Huang², Yanhong Dong¹, Zenith Tandukar², Gary Muehlbauer^{2, 3}, Kevin P. Smith², and Brian J. Steffenson¹
1. University of Minnesota, Department of Plant Pathology, Saint Paul, MN, USA 2. University of Minnesota, Department of Agronomy and Plant Genetics, Saint Paul, MN, USA 3. University of Minnesota, Department of Plant and Microbial Biology, Saint Paul, MN, USA

Brian Steffenson

University of Minnesota, Department of Plant Pathology, Saint Paul, MN, USA

Consensus maps are the product of integrating molecular marker information from several linkage maps and different molecular marker types. One of the goals of this study was the construction of a new barley consensus map that integrates SNP, SSR, RFLP, AFLP, and morphological markers with the purpose of developing a greater understanding of the genetic architecture of loci associated with Fusarium head blight (FHB) resistance and deoxynivalenol (DON) accumulation. Eight barley maps including six mapping populations and two previously developed consensus maps were used to construct the new consensus map. The linear programming theory implemented in the LPmerge package in R was used to integrate and order markers in these eight maps. A total of 4,788 markers on seven barley chromosomes covered about 1,299 cM. Marker positions on the consensus map were compared with the positions on other maps to confirm marker order. The average correlation of marker positions on the consensus map compared with the other eight maps is more than 0.95, indicating robust integration of these different marker types while preserving their relative order. The consensus map was used to consolidate mapping data for QTL associated with FHB resistance and DON accumulation from 13 bi- or tri-parental mapping populations and two genomewide association mapping panels. Based on this consensus map, we positioned 96 QTL associated with FHB resistance and 57 associated with DON accumulation across the barley genome. Most of the QTL explained a low percentage (<10%) of the variation for the traits and were often found significant in only one or a few environments in multi-year/multi-location field trials. Moreover, many of the major-effect FHB/DON QTL mapped to chromosomal positions coincident with various agro-morphological traits (e.g., heading date, height, spike density and spike angle). The large number of QTL with small effects that are not associated with agro-morphological traits suggests that genomic selection and rigorous phenotypic selection are appropriate approaches to improve disease resistance.