• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Turkey pumphrey 2
 

Turkey pumphrey 2

on

  • 156 views

 

Statistics

Views

Total Views
156
Views on SlideShare
156
Embed Views
0

Actions

Likes
0
Downloads
4
Comments
0

0 Embeds 0

No embeds

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Turkey pumphrey 2 Turkey pumphrey 2 Presentation Transcript

    • Utilization of Genetic Resources in Breeding for Stripe Rust Resistance Mike Pumphrey Peter Bulli Xianming Chen 2nd International Wheat Stripe Rust Symposium April 29, 2014 m.pumphrey@wsu.edu
    • Thoughts about improving stripe rust resistance, from a breeding program with very good resources (germplasm access, greenhouses, equipment, land, genotyping, human), in an area with recurrent and severe epidemics Context
    • Several effective seedling and ~3 APR genes, in each variety, is best when considering farmers, the environment, and epidemiology of rusts “Complex resistance” My Opinion
    • The primary and secondary genepools are sufficient for stripe rust resistance gene discovery My Next Opinion
    • Using complex resistance 1. Identify defined resistance loci, then develop/use diagnostic markers for all segregating genes (APR and seedling) 2. Genomic predictions for APR, if elite germplasm has enough, and breed for seedling resistance gene combinations 3. Trans/cis-genics (plus or minus strategy 1 and 2) Develop germplasm, then develop SUPERIOR varieties with a combination of seedling and adult plant resistance
    • Utilization of Genetic Resources in Breeding for Stripe Rust Resistance 1. USDA-ARS National Small Grains Germplasm Collection. Elite advanced lines and varieties from North America and other regions. -$25M USD project -USDA-ARS and WSU -association/bi-parental mapping 2. Global tetraploid germplasm -two Monsanto Beachell-Borlaug Projects and other collaborations
    • Data and Germplasm http://triticeaetoolbox.org/wheat/ http://www.ars-grin.gov/npgs/acc/acc_queries.html
    • Phenotyping • 3 routine locations – Pullman, Central Ferry, and Mt. Vernon, plus UC Davis • 2-3 years data per study • Infection type (0-9) and severity (%) are recorded at seedling and adult stage • Greenhouse seedling tests with defined races
    • Panel Entries Phenotyping Genotyping NSGC Core 5000 Seedling: (WA) PSTv14, 18, 37, 40, 51 9K SNP NSGC Core 5000 Field: Spring-CA, WA(2) Winter-KS, WA (2) 9K SNP T-CAP Triticeae CAP Grant 730 Breeding line 1393 Cultivar 1623 Landrace 1372 No classification 5118 Total North America South America North Africa Southern Africa West Africa Central America East Africa Australia Northern Europe West Asia South Asia Southeast Asia East Asia Central Asia Northern Eurasia Southern Europe Western Europe Eastern Europe Central Europe Central Africa
    • Panel Entrie s Phenotyping Genotyping Winter Yr diversity 384 Seedling and field-WA (2) 90K SNP Spring Hard elite 256 Seedling and field-MN, WA (3) , E. Africa (4) 90K SNP Eastern SRW elite 384 Field: NC, WA (3) 9K SNP Spring PNW Elite 427 Seedling and field-WA (2) 9K SNP Small NAM 384 Field: CA 9K SNP Spring Lr diversity 384 Seedling and field- WA (2) 90K SNP T-CAP Triticeae CAP Grant
    • Panel Entries Phenotyping Genotyping Emmer (tetraploid) wheat 196 Seedling and field-WA (2) 9K SNP Ethiopian landraces/ cultivars 300 Seedling and field-WA (3), Ethiopia (3) 90K SNP Wild tetraploids 200 Seedling and field-WA (3) 90K SNP Ethiopian durum 200 Seedling and field-WA(2) 90K SNP Elite Durum 300 Seedling and field-WA(2) 9K SNP Other Projects
    • Origin Cluster, kinship, and structure analyses of 1000 spring wheat core accessions T-CAPWardcluster(W) Kinship matrix (K) Q 4 Q 5 Q 6 Q 7 America Asia Africa Europe Structure (Q)
    • Spring panel Winter panel Pullman Mt. Vernon Across location Pullman Mt. Vernon Across location 0-9 0-100% 0-9 0-100% 0-9 0-100% 0-9 0-100% 0-9 0-100% 0-9 0-100% Pop mean 4.08 45.27 4.48 49.57 4.28 47.42 5.07 52.45 4.88 54.92 4.97 53.66 Range low 0 0 0 0 0 0 2 2 1 0 1 0 Range high 9 100 9 100 9 100 9 100 9 100 9 100 2.87**** 379**** 3.94**** 677**** 3.37**** 510**** 3.64**** 640**** 4.40**** 620**** 4.09**** 622**** 0.03NS 306**** 0.96**** 312**** -- -- 0.11* 398**** 0.14* 161**** -- -- -- -- -- -- 0.00 336**** -- -- -- -- 0.18**** 297**** 2.03 1.00 1.10 1.00 2.20* 0.00 1.01 1.00 1.53 1.03 1.21 1.00 0.76 0.70 0.85 0.85 0.88 0.85 0.86 0.75 0.77 0.88 0.88 0.89 Model describing the data: Yijk = µ + gi + yj + gyij + lk(j) + eijk Summary of reactions from field study, and covariance estimates from random model T-CAP
    • MajorSNP Associatedmarkers Positionrange Chrom. chrom Pos KeptwhenremovingIT0,1,2 IT2_2011_UCD_ZEW_transf IT2_2012_UCD_ZEW_transf IT_fill_MTV2012_transf IT_flower_MTV2013_transf IT_flower_PLM2012_transf IT_head_PLM2011_transf SEV2_2011_UCD_Zew_transf SEV2_2012_UCD_Zew_transf SEV_fill_MTV2012_transf SEV_flower_MTV2013_transf SEV_flower_PLM2012_transf SEV_head_PLM2011_transf PST37 PST40 PSTV14 PSTV4 IT.ALL.BLUE IT.MTV.BLUE IT.PLM.BLUE IT.UCD.BLUE SEV.ALL.BLUE SEV.MTV.BLUE SEV.PLM.BLUE SEV.UCD.BLUE DH_2011_UCD DH_2012_UCD hd.PLM.2011 hd.PLM.2012 ht.MTV.2011 ht.MTV.2013 ht.PLM.2011 ht.PLM.2013 PH_2011_UCD PH_2012_UCD Pseudo_Black_chaff_UCD_2012 Pubescence_Glume_UCD_2012 Waxiness fl.PLM.2012 glume.MTV.2011 glume.PLM.2011 glume.PLM.2013 ped.PLM.2011 Leaf_errectness_UCD_2012 IWA6441 39 11A 39 0 0.2 0 0 0.3 0.6 0 0 0 0 0.1 0.4 0.2 0.2 0.6 0.4 0 0 0.5 0 0 0 0.2 0 0 1 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 1 IWA5194 58 11A 58 0 0 0.1 0.8 0 0.2 0.1 0.1 0.2 0.3 0 0.1 0.9 0.1 0.4 0.4 0.1 0.2 0.1 0 0 0.2 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 IWA5174 88.1 11A 88.1 0 0 0.1 0.2 0 0.6 0 0 0 0.1 0.1 0.3 0.9 0.8 0.9 0.6 0 0.1 0.2 0 0 0 0.1 0 0 1 0 0 1 0 0 0 0 0 1 1 0 0 1 1 1 1 0 IWA1225 120.3 11A 120.3 0.4 0 0.1 0 0 0 0.1 0 0 0 0 0 0.3 0.6 0 0.6 0 0.1 0 0.2 0 0 0 0.1 1 0 1 0 0 0 1 0 0 0 1 1 1 1 0 1 0 1 0 IWA672 148.1 11A 148.1YES 0 0 0 0 0.1 0.2 0 0.1 0 0.1 0.1 0.3 0.4 0.1 0.2 0.1 0 0 0.2 0 0 0 0.1 0 0 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 1 IWA2035 173.7 11A 173.7 0.5 0.4 0.1 0 0 0 0.3 0.3 0 0 0 0 0.7 0.7 1.0 0.3 0 0 0 0.2 0 0 0 0.3 1 1 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 1 0 IWA962 35.5 21B 35.5 0.2 0.3 0 0 0.2 0 0 0.1 0 0 0.3 0 0.9 0.1 1.0 0.2 0 0 0.1 0 0 0 0 0 0 0 1 0 0 0 1 1 1 1 0 1 0 0 1 1 1 1 0 IWA6758 51.9 21B 51.9 0.4 0 0 0 0.1 0.1 0.1 0 0 0 0.1 0 0.1 0.2 0.6 0 0 0 0.1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0 1 1 1 0 0 IWA3307 57.6 21B 57.6 0 0 0 0 0.2 0 0 0.1 0.1 0 0.4 0 0.3 0.6 0.6 0.6 0 0 0.1 0 0 0 0 0 1 0 1 1 1 1 1 0 1 1 1 0 0 1 1 0 0 0 1 IWA1825 IWA5847, IWA3043 107.4-109.5 21B 109.3 0.1 0 0.2 0 0 0 0 0 0.1 0 0.1 0 0.8 0.5 0.2 0.1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 IWA3892 IWA846 123.4-123.6 21B 123.4YES 0 0 0 0 0 0 0 0 0 0 0 0 0.7 0 0.8 0.2 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 0 1 1 0 1 0 0 1 IWA2077 141.2 21B 141.2 0.3 0.1 0 0 0 0 0.2 0 0 0 0.1 0.1 0.2 0.2 0.2 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 1 1 0 1 0 1 1 0 0 IWA422 IWA423 9.9 42A 9.9YES 0.1 0 0 0 0 0 0.1 0 0 0 0 0 0.3 0.9 0 0.1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 IWA5272 IWA5273 96.2 42A 96.2 0 0 0 0.2 0 0 0.1 0 0 0.1 0.1 0 0.6 0.5 0.4 0.6 0 0.1 0 0 0 0 0 0 1 1 1 0 1 0 1 0 1 0 1 1 0 0 1 1 1 0 1 IWA200 160.2 42A 160.2 0 0 0 0.1 0 0.1 0 0 0 0 0 0.2 0.8 0.3 0.2 0.2 0 0.1 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0 1 1 0 1 1 1 0 0 IWA905 112.3 52B 112.3 0.2 0.2 0 0 0.1 0 0.3 0 0 0 0.4 0.1 0.5 0.3 0.9 0.8 0 0 0 0.1 0 0 0.1 0 1 1 1 1 0 0 0 1 0 0 1 1 0 0 0 0 0 0 1 IWA586 IWA587 147.3 52B 147.3 0 0.1 0 0.3 0 0.2 0.1 0.1 0 0.1 0.1 0.1 0.3 0.1 0.3 0.7 0 0 0 0 0.1 0.1 0.1 0 1 0 1 0 0 0 0 1 0 0 0 1 0 1 0 1 1 0 0 IWA226 163.4 52B 163.4 0 0 0 0.1 0.1 0.7 0 0 0 0 0.2 0.3 0.2 0 0 0 0 0 0.5 0 0 0 0.2 0 1 0 1 0 1 0 1 0 1 0 1 0 0 1 0 0 0 0 1 IWA692 260.6 52B 260.6 0 0.2 0.3 0.5 0 0 0.1 0.1 0.5 0.4 0.4 0 0.5 0.1 0.6 0.7 0 0.3 0 0 0.1 0.4 0 0.1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 IWA5969 13.2 73A 13.2 0.1 0 0 0 0.2 0.4 0.2 0.1 0 0.1 0 0 0 0.1 0.6 0.2 0 0 0.3 0 0 0 0 0.2 0 0 0 0 0 1 0 0 1 1 1 0 0 0 1 0 1 0 1 IWA2049 27.5 73A 27.5 0.2 0 0 0 0 0.1 0.1 0.1 0 0 0 0 0.8 0.3 0.4 1.0 0 0 0 0.1 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 1 0 1 1 1 0 0 1 IWA1996 35 73A 35 0 0 0 0.7 0 0.1 0 0 0 0.3 0 0.1 0.7 0.1 0 0.1 0 0.2 0 0 0 0.1 0 0 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 IWA6877 IWA5039 58.4-59.4 73A 59.4YES 0.2 0 0 0 0.2 0 0.4 0.1 0.1 0.2 0.3 0.1 0.1 0 0.1 0.3 0 0 0.1 0.1 0.2 0.2 0.1 0.3 1 0 1 0 1 1 1 1 0 1 0 1 1 0 1 1 0 1 0 IWA8215 70.4 73A 70.4 0 0.2 0.1 0.4 0 0 0 0.1 0.1 0.5 0.1 0.2 0.7 0.9 0.4 0 0 0.1 0 0 0.1 0.2 0.1 0 1 1 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 IWA7011 75.2 73A 75.2 0.3 0.1 0 0.2 0 0 0.5 0.2 0.1 0.4 0 0.1 0.7 0.7 0 0.2 0 0.1 0 0.3 0 0.2 0 0.5 1 0 0 1 0 0 0 1 0 1 0 1 0 1 0 0 1 1 1 IWA2332 102.9 73A 102.9 0 0.3 0 0.2 0 0 0 0.2 0 0 0 0 0.5 0.5 0.6 0.9 0 0.1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 1 0 0 1 0 1 0 0 1 0 IWA4796 1.9 83B 1.9 0.1 0 0.1 0.1 0 0 0.7 0.1 0.1 0.1 0 0 0.2 0.8 0 0.1 0 0 0 0 0 0.1 0 0.5 0 1 1 0 0 0 0 0 1 0 0 1 0 1 1 1 1 0 1 IWA5202 3.9 83B 3.9YES 0 0.1 0 0.1 0 0 0.4 0.5 0.1 0.1 0 0 0.9 0.1 0.1 0.5 0 0 0 0 0.1 0.1 0 0.6 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 1 1 0 0 IWA6632 57.4 83B 57.4YES 0.2 0 0 0.2 0 0 0.5 0.4 0.2 0.2 0 0 0.7 0.3 0.8 1.0 0 0 0 0.1 0.1 0.2 0 0.4 1 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 1 0 1 IWA377 IWA2622 73.8 83B 73.8 0 0 0 0.2 0.2 0.3 0 0 0 0.7 0.2 0.1 0.5 0.8 0.2 0.2 0.1 0.1 0.3 0 0.1 0.2 0.2 0 0 0 0 0 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 IWA8480 77.5 83B 77.5 0 0 0 0.1 0.3 0.1 0 0 0 0.1 0 0.1 0.8 0.5 0.7 0.8 0.1 0.1 0.2 0 0 0 0.1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 IWA5890 84.5 83B 84.5 0 0.4 0 0 0 0 0 0.1 0 0 0.1 0 0.5 0.8 0.3 0.2 0 0 0 0.1 0 0 0 0.1 0 0 1 1 1 1 0 1 1 0 1 1 0 0 1 0 1 0 1 IWA6221 95.5 83B 95.5 0 0 0 0.3 0 0 0.1 0 0 0.1 0.1 0 0.7 0.6 0.5 0.1 0 0 0 0 0 0 0 0 1 1 1 0 1 1 1 1 1 1 1 0 0 1 1 0 0 0 1 IWA6100 IWA4251 35.2-36.6 104A 35.2 0 0 0 0.1 0 0.1 0.1 0.1 0 0.1 0.1 0 0.4 0.1 0.5 0.6 0 0 0 0 0 0 0 0.1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 IWA1570 IWA5687, IWA3489, IWA3490, IWA5036, IWA8, IWA7203 66.6-69.3 104A 68.1 0 0.1 0 0 0 0 0 0 0 0 0 0 0.2 0.1 0.5 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 0 1 1 0 1 0 1 0 0 0 0 0 1 IWA2170 IWA7765, IWA1066, IWA6690 164.3-167.3 104A 167.3YES 0 0 0 0 0.2 0 0 0 0 0 0.2 0 0.5 0.8 0.1 0.3 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 0 1 0 0 0 1 1 0 0 0 1 1 IWA1034 181.7 104A 181.7YES 0 0 0 0.1 0 0 0 0 0 0.1 0 0 0.4 0.2 0.3 0.2 0 0 0 0 0 0 0 0 0 1 1 1 0 1 1 1 0 0 1 1 0 1 0 1 1 0 1 IWA2745 IWA1923, IWA1910, IWA3846, IWA4330, IWA6898, IWA7437 64.5-65.8 114B 65.8 0 0 0.1 0 0 0 0 0 0 0 0.1 0.1 0.2 0 0 0 0 0 0 0 0 0 0.1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 IWA4347 IWA2398, IWA1007, IWA3736, IWA4347, IWA4348, IWA1006 67.9-68.7 114B 68.3YES 0 0 0 0.1 0 0 0 0 0 0 0 0 0.6 0.3 0.3 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 1 0 0 1 0 0 0 IWA6461 85.2 114B 85.2 0 0.1 0.3 0 0.3 0 0.1 0 0.2 0 0.3 0.2 0.2 0.8 0.2 0.1 0 0 0.1 0 0 0 0.2 0 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 IWA6277 20.6 124D 20.6 0 0 0 0 0 0.2 0 0 0 0 0 0.2 0.9 0.6 0.6 0 0 0 0.1 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 1 IWA5375 IWA5766 26.9 124D 26.9 0 0 0 0 0 0.1 0 0 0 0 0 0 0.8 0.1 0.6 0 0 0 0 0 0 0 0 0 1 1 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 IWA2144 IWA2143, IWA2146 4.9 135A 4.9 0.1 0 0 0 0 0 0 0 0.1 0 0.1 0 1.0 0.7 0.1 0.6 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 0 1 0 1 1 1 IWA1486 IWA4648 119.3 135A 119.3 0 0.1 0.1 0 0 0 0.2 0.1 0.1 0.1 0 0 0 0.1 0.1 0.1 0 0 0 0 0 0.1 0 0.1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 IWA6988 189.2 135A 189.2 0 0 0 0.3 0 0.1 0 0 0.1 0.1 0 0.2 0.2 0.9 0 0.7 0 0.1 0 0 0 0 0 0 1 0 1 1 1 0 1 0 1 0 1 1 1 0 1 1 1 1 0 IWA2646 194.9 135A 194.9 0 0 0 0.2 0 0 0 0 0 0.1 0 0.1 0 0.3 0.1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 IWA868 0 145B 0YES 0 0.2 0 0.1 0.1 0 0.1 0.1 0.2 0.2 0 0 0.7 0.8 0.2 0.6 0 0 0 0 0 0.2 0 0.1 0 0 1 1 0 0 0 1 1 1 1 0 0 0 1 0 0 0 0 IWA7227 68.3 145B 68.3 0.2 0 0.1 0.1 0 0 0.5 0 0 0 0 0 0 0.6 0 0.1 0 0.1 0 0.1 0 0 0 0.1 1 1 0 0 0 1 0 0 0 0 1 0 1 0 1 1 1 1 1 IWA3633 85.9 145B 85.9YES 0 0 0 0 0 0.3 0 0 0 0 0 0 0.5 0.1 0.7 0.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 1 0 0 IWA4280 IWA8069 115.3-119.9 145B 119.9YES 0.1 0.1 0 0.1 0 0 0 0.2 0.1 0.1 0 0 0 0 0 0.9 0 0 0 0.2 0 0.1 0 0.1 1 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 IWA4824 75.5 186A 75.5 0 0.1 0.5 0 0 0 0 0 0.4 0 0 0 0 0 0.3 0 0 0.1 0 0 0 0.1 0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 1 1 0 0 0 1 IWA3066 217.7 186A 217.7 0 0 0.1 0 0 0.1 0 0 0 0 0 0 0.9 0.1 0.2 0 0 0.1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 IWA8134 37.9 196B 37.9 0 0.1 0 0.1 0 0.5 0 0.2 0 0 0 0 0 0.2 0.1 1.0 0 0 0.2 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 0 0 1 0 1 1 0 0 IWA2888 38.5 196B 38.5 0.1 0 0 0.8 0 0.2 0.1 0 0 0.1 0 0 0.1 0.4 0 0.5 0 0.1 0 0.1 0 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1 0 1 1 1 1 0 1 IWA7625 IWA2419, IWA1655, IWA2417, IWA2420, IWA4823, IWA4825, IWA4827 50.7-50.8 196B 50.8 0 0 0.3 0 0 0 0 0 0.2 0 0 0 0 0 0.3 0 0 0.1 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 1 1 0 0 1 1 IWA3796 81.3 196B 81.3 0.1 0 0 0 0 0.1 0.1 0 0 0.1 0 0 0 0 0.1 0.7 0 0 0.1 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 0 1 1 1 0 1 0 0 0 IWA6770 84.5 196B 84.5 0 0.1 0 0.1 0 0 0 0 0 0 0 0 0.2 0.1 0.1 0.1 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 1 1 0 1 1 0 0 0 1 0 IWA3289 87.8 196B 87.8 0 0.1 0 0.1 0 0 0 0 0 0 0 0 0.2 0.1 0.1 0.1 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 1 1 0 1 1 0 0 0 1 0 IWA6660 91 196B 91 0 0 0.1 0 0.2 0.2 0 0 0.1 0 0.1 0.1 0.7 0 0.6 0.6 0 0 0.2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 1 IWA7257 112.3 196B 112.3YES 0 0 0 0 0 0 0 0 0 0 0 0 0.4 0.4 0.8 0.2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 1 1 0 1 IWA7816 68.6 216D2 68.6 0 0 0 0 0 0.4 0 0 0 0.1 0 0.1 1.0 0.5 1.0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 1 1 0 1 1 0 0 1 0 0 IWA167 73.2 216D2 73.2YES 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.1 0.1 0.2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 0 1 1 0 0 0 0 1 IWA7306 6.2 237A 6.2 0.1 0 0 0.4 0 0.5 0 0 0 0 0 0 0.5 0.7 0.5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 IWA7121 49.9 237A 49.9 0 0 0 0.1 0.2 0.8 0.1 0 0 0 0.4 0.4 0.9 0.3 0.7 0.8 0 0 0.3 0 0 0 0.3 0 0 1 1 1 1 0 1 1 0 0 1 0 1 1 1 0 1 0 0 IWA7549 105.5 237A 105.5 0 0 0.1 0.2 0 0 0 0 0 0.1 0 0.1 0.2 0.1 0.1 0.2 0 0.1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 1 1 1 1 0 IWA1108 IWA6143, IWA8233 40.6-42.8 247B 40.6 0.9 0 0 0 0 0 0.5 0 0.1 0 0 0 0.1 0.5 0 0 0 0 0 0.4 0 0 0 0.4 1 1 0 0 0 1 1 1 1 0 0 0 1 0 0 0 0 1 0 IWA615 107.4 247B 107.4 0.2 0 0 0.1 0 0 0.5 0 0 0 0.1 0.3 0.1 0 0 0.4 0 0 0 0.1 0 0 0.1 0.1 0 0 0 1 1 0 0 0 1 0 1 1 1 1 1 1 0 0 1 IWA917 Unknown 284BS Unknown 0 0 0 0.1 0 0 0.1 0 0 0.1 0.1 0.1 0.6 0.8 0.2 0.1 0 0 0 0 0 0 0.1 0 1 1 0 1 0 0 0 0 1 1 1 1 1 0 1 1 0 0 1 IWA1135 Unknown 284BS Unknown 0 0 0 0.1 0 0 0 0 0 0.1 0.1 0.1 0.7 0.6 0.2 0.3 0 0 0 0 0 0 0.1 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 1 0 0 0 1 IWA3090 Unknown 287AL Unknown 0.1 0.4 0 0 0.1 0 0.9 0.2 0 0 0.2 0.1 1.0 0.3 0.8 0.7 0 0 0 0.1 0.1 0 0.2 0.5 1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 1 IWA6629 Unknown 287AL Unknown 0.1 0.4 0 0 0 0 0.6 0.1 0 0 0.1 0 0.7 0.4 0.8 0.5 0 0 0 0.1 0 0 0.1 0.3 1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 1 IWA481 Unknown 285AS Unknown 0.2 0 0 0.1 0 0 0 0 0.1 0.1 0.1 0 0.8 1.0 0 0.7 0 0 0 0 0 0.1 0 0 1 1 1 1 1 0 1 1 0 0 0 0 1 1 1 0 1 1 1 IWA2142 Unknown 285AS Unknown 0.2 0 0 0.1 0 0.1 0 0 0.1 0.1 0.2 0 0.8 1.0 0 0.7 0 0 0 0 0 0.1 0 0 0 1 1 1 1 0 1 1 0 0 0 0 1 0 1 0 1 1 1 IWA2791 Unknown 285BL Unknown 0 0.1 0 0 0 0.5 0 0 0 0 0 0.2 0.7 0.1 0.7 0.2 0 0 0.1 0 0 0 0.1 0 1 1 0 0 0 0 0 1 0 0 1 1 0 0 1 1 1 1 0 GWAS “hits” from 1000 spring wheat core accessions phenotyped in 6 env + 4 races as seedling T-CAP IT-ENV SEV-ENV IT-RACE IT-LOC SEV-LOC Phenological and Morphological Traits
    • SNP Chrom IWA137 Unknown IWA148 Unknown IWA627 Unknown IWA3084 Unknown IWA6460 Unknown Genomic regions associated with field resistance to stripe rust in Spring wheat core (1000) T-CAP IWA6441 IWA5194 1A 36.15 68.15 IWA422 (9.58) IWA4213 (51.52) 2A Yr17 Yr32 Yr1 IWA3413 IWA4719 5A Yr34/Yr48 77.19 120.88 IWA4637 7A 82.34 3B IWA5202 3.87 Yr4 Yr30 4B IWA3874 Yr50 IWA4347 68.33 63.97 5B IWA7815 121.78 Yr40 Yr47 6B IWA7098 IWA7257 112.30 147.90 Yr35 Yr36 7B IWA3416 IWA1108 164.88 Yr52 Yr39 40.62 1D IWA7154 67.29 2D IWA5750 139.65 6D IWA4592 126.26 4D Lr67/Yr46IWA5375
    • T-CAP Locus Chrom Pos (cM) MAF Pullman, WA Mount Vernon, WA P-value FDR P-value FDR IWA5505 1AL 134.80 0.49 **** ** **** **** IWA108 4AS 19.91 0.10 **** * -- -- IWA5452 4AS 69.77 0.07 **** ** -- -- IWA3774 4AS 131.65 0.20 **** ** **** ** IWA1067 4AL 166.59 0.42 *** NS **** * IWA1835 4AL 197.23 0.31 **** NS **** ** IWA5002 5AL 187.00 0.19 *** NS **** * IWA5915 1BL 97.13 0.34 **** ** **** **** IWA1810 5BS (Yr47?) 39.37 0.05 **** *** -- -- IWA7372 5BS? 63.66 0.09 **** * NS NS IWA7815 5BL 121.78 0.16 -- -- **** **** IWA4711 2DS 11.20 0.18 **** * -- -- Ppd Group 2 -- 0.43 **** *** **** *** IWA62 -- -- 0.07 **** ** **** **** IWA2265 -- -- 0.11 **** NS **** ** IWA3401 -- -- 0.10 **** * **** *** IWA8279 -- -- 0.05 **** * -- -- Winter wheat panel GWAS summary for 2012 and 2013 field stripe rust data
    • 0 1 2 3 Expected –log10(p) Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group X -log10(p) 12345 2B 7D 7B X Observed–log10(p) 012345 PSTV-14 Race Virulence formula: Yr1, Yr6, Yr7, Yr8, Yr9, Yr17, Yr27, Yr43, Yr44, YrTri, YrExp2, YrTye Locus Chrom Pos(cM) 0.1 FDR Mapped Yr gene IWA7815 5BL 121.78 1.86E-26 -- PSTV-40 Race Virulence formula: Yr3, Yr6, Yr7, Yr8, Yr9, Yr10, Yr24, Yr27, Yr32, Yr43, Yr44, YrTri, YrExp2 Locus Chrom Pos(cM) 0.1 FDR Mapped Yr gene IWA8601 2BL 149.36 2.00E-2 Yr5 and Yr53 IWA6 7BL 58.27 2.51E-2 IWA118 7DS 0 2.00E-2 IWA7 -- -- 2.00E-2 -- IWA2356 -- -- 1.14E-2 -- IWA3389 -- -- 2.00E-2 -- Spring panel GWAS for seedling reaction to stripe rust races T-CAP
    • Yr52 (YrPI183527) 1.0 3.9 1.1 0.7 1.2 Xgpw1144 Xgwm577 5.9 Xwmc276 4.4 Xbarc32 5.7 Xwmc273 0.8 Xwgp5668 Xcfa2040 1.5 Xwgp5271 Xwgp5175 Xwgp5258 1.1 Xbarc182 7BL 7BL-14 (0.14) 7BL-1 (0.40) 7BL-9 (0.45) 7BL-5 (0.69) 7BL-10 (0.78) 7BL-6 (0.84) 7BL-3 (0.86) 7BL-7 (0.63) Yr52 2.4 9.9 0.4 4.0 1.3 5.6 2.7 1.4 3.3 1.8 7.7 5.5 Yr5STS7/8 Yr5 Xbarc349 Yr44 Xgwm501 Xwmc441 Yr53 (YrPI480148) XLRRrev/NLRRrev350 Ptokin2/Xa1NBS-F234 (STS2F/1R219) Ptokin1/NLRR-INV1800 Xwmc149 Yr43 Xwgp109 2BL Yr53 APR resistance from PI 183527 and seedling resistance from PI 480148 Ren et al. 2012 TAG 125:847-857 Xu et al. 2013 TAG 126:523-533
    • Yr59 in PI 178759 Zhou et al. 2014 TAG 127:935-945
    • Yr62 & a QTL in PI 192252 Lu et al. 2014 TAG DOI: 10.1007/s00122-014-2312-0
    • Concerns •Many opportunities… not enough well developed tools •How do we prioritize resistance loci? Fitness costs, interactions, durability, linkage relationships, etc.? •What genes are we missing (or false positives)? Masking, power, MAF, marker density and bias? •How do we identify lines that have each resistance locus, for sure?- Haplotypes, not single markers Developing Nested Association Mapping population with ~200 accessions in Avocet S background, and other populations for seedling R genes
    • Acknowledgements Stripe rust collaborators Arron Carter Steven Xu Jorge Dubcovsky Roberto Tuberosa Bekele Abeyo Bedada Girma Kim Campbell Shiaoman Chao Deven See Gina Brown-Guedira Mike Bonman