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Kangfu Yu November 17, 2011

An update on the molecular marker development and marker-assisted selection in AAFC bean breeding programs. Kangfu Yu November 17, 2011. Part One: GTM Development. CBB (Common Bacterial Blight) Disease. - Pathogen : Xanthomonas campestris pv. phaseoli and X. fuscans subsp fuscans strains

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Kangfu Yu November 17, 2011

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  1. An update on the molecular marker development and marker-assisted selection in AAFC bean breeding programs Kangfu Yu November 17, 2011

  2. Part One: GTM Development CBB (Common Bacterial Blight) Disease - Pathogen : Xanthomonas campestris pv. phaseoli and X. fuscans subsp fuscans strains - Region: both temperate and tropical production zones - Disease control: resistant varieties, disease-free seed, and crop rotation

  3. Mapping of CBB- QTL B6 B8 - Explain 64% phenotypic variation - Resistant origin from tepary bean - Marker UBC420 - Explain 17% phenotypic variation - Resistant origin from tepary bean - Marker SU91 (Miklas et al., 2006)

  4. Dominant vs. Codiminant Markers • BC420 are SU91 are dominant SCARS • Random markers liked to the QTL • Less efficient for MAS

  5. Objectives • Develop co dominant markers • Candidate gene markers • Test their effectiveness in MAS

  6. Characterizing CBB NILs(near isogenic lines) B6 B8 CBB-2 UBC420 CBB-1 SU91 Complete resistant requires co-dominant genotypes for both CBB-1 and CBB-2 QTLs Donor (resistant): XAN159 Recurrent parent (susceptible):Teebus Recessive epistasis and / or (Vandemark et al., 2008) Marker analysis

  7. BBSS (Resistant) 7DAI 10DAI 14DAI 18DAI bbss (Susceptible) BC420- and SU91-QTL associated to CBB resistance NILs derived from XAP159 x Teebus; Gift from Dr. Philips N. Miklas

  8. Physical map of BC420-QTL locus (Liu et al., 2010)

  9. De novo assembly of BAC sequences Trimmed 454 reads CLC Genomics Workbench (de Bruijun Algorithm) Newbler (OLC Algorithm) Geneious (Greedy Algorithm) Assembled BAC sequence

  10. BAC sequence annotation

  11. BC420 BC420 gene 3 gene 4 gene 9 bbss bbss bbss bbss BBSS BBSS BBSS BBSS Gene-targeted marker development (BC420-QTL locus) gene 10A gene 10B gene 11 Gene 14 gene 15 gene 17 bbss bbss bbss bbss bbss bbss BBSS BBSS BBSS BBSS BBSS BBSS 1kb 500 bp

  12. SU91 bbss BBSS gene 12 gene 3 Gene 11 gene 9B Gene 10 gene 9A bbss bbss bbss bbss bbss bbss BBSS BBSS BBSS BBSS BBSS BBSS Gene-targeted marker development (SU91-QTL locus) 1kb 500 bp

  13. SU91-CG11 accounts for greater phenotypic variations than SU91 Single marker QTL analysis ***, p <0.001

  14. Part Two: Genome-wide association mapping Plant materials (469 genotypes)

  15. CBB rating Note: CBB rating was conducted in 2009 field trial at Harrow, Ontario.

  16. SNP genotyping • Genome-wide distributed SNPs were found from McClean (NDSU) 2007 genetic map (McConnell et al., 2010); • Sequenom iPLEX Gold genotyping platform was used in Genome Quebec; • 132 SNPs were tested and 106 SNPs (80.3%) worked; • Of 106 working SNPs, 12 SNPs were monomorphic and 94 SNPs were polymorphic.

  17. K=1 K=2 K=3 K=4 K=5 K=6 K=7 K=8 K=9 K=10 Andean Mesoamerican Ancestry (%) Population structure estimation • STSTRUCTURE 2.3.3 software was used • Based on 496 genotypes with 75 SNPs • K=2

  18. Population kinship estimation • The K matrix was generated based on 75 SNPs using kinship matrix function in TASSEL software Unrelated genotypes Closely related genotypes

  19. Association analysis • Unified MLM (Mixed Linear Model) method in TASSEL software was used to test association between marker loci and common bacterial blight severity; • Population structure (Q) and relative kinship (K) were taken into account. a n.s., not statistically significant; *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001. bR2_marker was calculated as the proportion of sum square due to marker after accounting for all other effects in model.

  20. Co-localization of DNA markers and CBB-QTLs • The mapping information was extracted from McClean (NDSU) 2007 genetic map; • 15 significant SNP markers were co-localized with or close to previously identified CBB-QTLs; • These markers, if proved to be effective in different backgrounds may help the breeders to facilitate the pyramiding of the QTLs from diverse sources and to attain higher levels of CBB resistance in newly-developed bean cultivars.

  21. Acknowledgements • Funding: • OWBPMB, OCBGA, ORF, AAFC • Collaborators: Navabi, A., Hou, A. Balasubramanian,P • Techanical Assistance: • Shi, C. Rupert, T. Zhang, B. Xie, W.

  22. Thank You

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