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Understanding Genetic Resistance to Puccinia graminis in Barley and Wheat via eQTL Mapping

This research explores the genetic basis of resistance to Puccinia graminis in barley and wheat through a systems biology approach. By utilizing eQTL mapping and global gene expression profiling, we identify loci regulating gene expression in response to the pathogen. The study leverages a unique experimental population designed for high-throughput genotyping and extensive RNA analysis, paving the way for integrating genetic markers into breeding programs. Our findings will offer insights into disease resistance networks and potential targets for enhancing crop resilience.

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Understanding Genetic Resistance to Puccinia graminis in Barley and Wheat via eQTL Mapping

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  1. Genetical genomics of Puccinia graminis TTKS response: A systems biology approach to rapid development of durable resistance for barley and wheat Roger Wise USDA-ARS / Iowa State University http://wiselab.org/ http://plexdb.org/ http://barleygenome.org/

  2. Gene Expression and QTLs The treatment of transcript accumulation as a Quantitative Trait is called eQTL mapping. Loci that regulate expression of genes or networks can be: -cis-acting QTL -trans-acting QTL

  3. Requirements • Experimental population that harbors genetic variation for resistance to the pathogen • [QSM DH (Q21861 x SM89010)] • Global gene expression profiling platform • (Affymetrix Barley1 GeneChip) • High-throughput genotyping platform • (QSM SFPs detected by Barley1 GeneChip) • Database (BarleyBase/PLEXdb)

  4. Scoring of TTKS on QSM DH mapping population 0; 12 21 3-210; 3+ Brian Steffenson

  5. Barley1 GeneChip22,840 Probe Sets (22,792 + controls) Close et al. 2004, Pl Physiology 134: 960-968

  6. Single feature Polymorphisms (Steptoe and Morex) 22,000 Genes X 11 Oligos X 25nt = 6,325,000 bases [ >4,000 SFPs ] Steptoe Raw Data: Morex Robbie Waugh

  7. Expression Level Polymorphism Contig3660_at Matt Moscou

  8. Experimental Design Dew Chamber QSM DH population (79 lines) Diversity Set (12 lines) Red Trays- Inoculated Blue Trays-Mock-inoculated RNA from each cone of seedlings is hybridized to its own Barley1 GeneChip. Each flat contains up to 98 cones of (6) seedlings randomly arranged among reps and inoc & mock-inoc (Harvested 24 hours after inoculation). [79 DH lines + parents] x 2 inoc. treatments x 2 reps = 340 randomized samples 12 diversity lines x 2 inoc. treatments x 6 reps [= 144 randomized samples]

  9. Data Analysis • Identify subset of genes that show differential expression between TTKS-inoculated and mock-inoculated leaves. • Map the eQTL that regulate the expression of these genes. • Identify regulators by hierarchical analyses. • A locus that regulates one or more significant disease resistance networks is an obvious target for immediate use in breeding.

  10. Expectations • 4,000-8,000 SFP gene markers positioned on the barley population segregating for TTKS resistance; enables QTL mapping of TTKS resistance. • Marker-delineated positions of the eQTL that regulate networks of disease response genes; breeders can incorporate into their germplasm. • Elucidation of gene expression networks responsive to TTKS infection; provides biochemical targets for further analysis. • Genes that possess transcriptional activation elements that allow them to respond more aggressively to TTKS infection; provides key regulators for disease response.

  11. What do we do with all that data? (65 Mb/chip = > 30 GigaBytes)

  12. http://www.plexdb.org

  13. 1000 Barley1 Hybs Uploaded

  14. Knowledge For Tomorrow’s Solutions USDA-ARS/ISU Rico Caldo Matt Moscou Greg Fuerst Nick Lauter Jose Rodriguez Yan Meng Pingsha Hu Liu Xi Dennis Halterman Karin Werner Brent Kronmiller BarleyBase/PLEXdb Julie Dickerson Ethy Cannon Sudhansu Dash Lu Hong Lishuang Shen Dan Nettleton USDA-ARS/UMN Yue Jin Sam Gale Les Szabo Univ. of Minnesota Brian Steffenson Stephanie Dahl

  15. http://barleygenome.org

  16. http://barleycap.org

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