Canola Diseases Focus Session Prepared for a major sclerotinia outbreak?

Transcription

1 Canola Diseases Focus Session Prepared for a major sclerotinia outbreak?

2 Agriculture and Agriculture et Agri-Food Canada Agroalimentaire Canada Best models for sclerotinia risk assessment in canola Sclerotinia check list used in Canada Experience with sclerotia depots Sclerotinia risk App for the smartphone Sclerotinia research in Canada Lone Buchwaldt Agriculture and Agri-Food Canada Saskatoon Research and Development Centre Saskatchewan, Canada Lone Buchwaldt AAFC, Saskatoon, Saskatchewan, Canada Perth, Australia 2017

3 Sclerotinia forecasting

4 Sclerotinia incidence in canola Courtesy Saskatchewan Ministry of Agriculture High Sclerotinia incidence is related to wet weather in the growing season A well-timed fungicide application can control sclerotinia However, the decision to spray is made before symptoms can be seen

5 A check-list for sclerotinia risk assessment is promoted in Canada Sclerotinia risk factors Years since last canola crop Sclerotinia in last host crop (*) Crop density Rain in the last two weeks Weather forecast (*) Sclerotia germination (*) Early to full flower Time to decision whether to spray Weather condition in the remainder of the growing season dry - wet - dry wet - dry - dry dry - dry - wet Deciding on fungicide application is similar to buying mutual funds Growers make a decision based on the best information available at the time, and accept that certain risk factors (*) have a degree of uncertainty They realise that weather conditions in the remainder of the growing season can affect both disease severity and yield - in either direction Taken together the size of the economical return is not guaranteed, but the decisions was the best possible at the time of the decision

6 We made the sclerotinia check-list interactive and placed it on the web It was originally developed in Sweden (Twengstrom et al, 1998) A fungicide application is recommended at 40 points or higher Link to the interactive check-list:

7 We seek to provide data on sclerotia germination with the help of sclerotia depots 200 depots are produced each year as follows Sclerotia are collected from commercial canola fields 10,000 sclerotia 7-15 mm long are selected 50 sclerotia are inserted in nylon mesh Pockets sealed with heat Depots with 50 sclerotia each, ready for overwintering Overwintering of depots in the field

8 Sclerotia germination is tested under controlled conditions Depots are placed in soil, watered to field capacity and kept at low day light Apothecia forms after 4-5 weeks Depots show 50-75% sclerotia germination

9 Volunteers place depots in canola fields and submit sclerotia germination using smartphones Volunteers are private or public extension staff and canola growers Google cloud is used for data storage We access the data daily and produce a map of % sclerotia germination

10 Thoughts about sclerotia depots ADVANTAGE A depot provides a fixed point for observing apothecia instead of searching in the field PROBLEM Resource demanding for AAFC Low resolution of 10 km because isolated rain events are common SOLUTION Growers and extension staff could produce sclerotia depots for their own use COMPROMISE Sclerotia germination will not be shared on a public web site

11 We are developing a Sclerotinia risk App for smartphones Sclero App Provides real-time rainfall data by pointing to a map Provides the likelihood of rain in the 3-day weather forecast ~ 700 weather stations A canola growth stage key shows when to begin risk assessment The App has the interactive sclerotinia check-list Has a link to apothecia development in sclerotia depots

12 The App will have an 3D interactive graph of yield, seed sales price and cost of fungicide application Growers can point to the graph and select the numbers that are specific to the actual canola field

13 We plan to determining the effect of crop rotation on sclerotinia severity using Canadian data Data is needed from ~1000 canola fields over 3-5 years: Sclerotinia severity at harvest +/- fungicide application Canola variety Sclerotinia severity in the last host crop 10 year crop history Soil type

14 We plan to utilize precision technology to measure yield in sprayed versus unsprayed canola This allow calculation of the economic threshold for fungicide application under Canadian conditions. Heat map of yield from a combine with precision technology. A threshold from Europe is 7.5 bushels /acre = 15% sclerotinia infected stems

15 The sclerotinia stem test Identification of resistant B. napus germplasm

16 Lesion length The sclerotinia stem test Method S. sclerotiorum mycelium is grown on nutrient agar Plants are inoculated at full flower by attaching mycelium plugs to the stem with Parafilm Lesion length and stem firmness are recorded at weekly intervals Five traits are used for data analysis: Lesion length 7 dai Lesion length 14 dai Lesion length 21 dai AUDPC (Y i + Y (i+1) ) / 2 (t (i+1) ti) where Y i is the disease rating at time ti % soft + collapsed lesions AUDPC Days after inoculation

17 Resistant and susceptible phenotypes The stem test differentiated the resistant Chinese variety Zhongyou 821 and the susceptible Canadian variety Westar Naturally infected canola plants Resistant Susceptible 17

18 The stem test was adopted by industry 9 public and private collaborators in AB, SK, MB 33 field tests over 5 growing seasons 45H29 - susceptible control 45S52 - best partially resistant line at the time The stem test was able to differentiate the two line each year. The Western Canada Rapeseed/Canola Recommending Committee (WCC/RRC) decided that lines with a claim of sclerotinia resistance should provide stem test data Results available in a report on Canola Council of Canada s web site

19 AUDPC % soft + collapsed lesions Identification of sclerotinia resistance in B. napus germplasm 125 AUDPC % soft + collapsed lesions ZY SRS1632 Tanto PAK54 PAK93 K22 DC China E-Europe W-Europe Pakistan Japan South Korea 0 Accessions select for breeding and research: Zhongyou China K22 - Japan PAK54 - Pakistan PAK93 - Pakistan DC21 - South Korea Tanto - France SRS Poland

20 Characterisation of the Canadian sclerotinia population

21 Genotyping of the Canadian S. sclerotiorum population Method 168 commercial canola fields in AB, SK, MB 130 isolates 47 microsatellite markers Result 17 sub-populations identified One isolate selected from each subpopulation Chromosome SSR name Repeat motif Number of alleles PIC 1 AAFC_2b (AG) AAFC_2d (GAAAG) AAFC_5e (TACA) AAFC_22a (CTT) AAFC_22C (TCTTCA) AAFC_22e (ACCT) AAFC_22f (GT) AAFC_23b (TTG)9(GTG) AAFC_24c (AG)9(GT) AAFC_24e (AAAAGC) ssr_5-2 (GT) ssr_20-3 (GT)7GG(GT) ssr_9-2 (CA)9(CT) AAFC_3c (AGAT) ssr_ 7-2 (GA) ssr_17-3 (TTA) ssr_114-4 (AGAT)14(AAGC) AAFC_7b (ACATA)6(TATT) ssr_12-2 (CA) ssr_5-3 [(GT)2GAT]3(GT)14GAT(GT)5[GAT(GT)4]3(GAT) ssr_7-3 GT AAFC_9b (AATGAA) AAFC_9d (GATATT) AAFC_21a (GGTAGT) AAFC_21d (CAGA)9&(CAGG) AAFC_21e (CAA) ssr_36-4 CA6(CGCA)2CAT ssr_110-4 (TATG) AAFC_6f (TGT) na 9 AAFC_11a (CTCCTT) AAFC_27b (AGTTG) ssr_119-4 (GTAT)6 and (TACA) ssr_ 6-2* (TTTTTC)2(TTTTTG)2(TTTTTC) AAFC_20b (TCT) AAFC_20d (TG) ssr_8-3 CA AAFC_33d (GTAG) AAFC_12a (GTAT) AAFC_12b (CATC) AAFC_26b (TCCATT) AAFC_25b (TTATAT) AAFC_25d (TACAA) AAFC_25e (GTAT) AAFC_15e (AAATA) R AAFC_4d (ATTAT) AAFC_18a (AC) na ssr_55-4 TACA

22 17 sub-populations of S. sclerotiorum identified in Western Canada 1 2 SK3 SK11 AB29 SK12 AB5 AB30 AB17 SK50 AB13 AB21 SK MB16 MB20 MB44 46 alleles were polymorphic (2-35 per SSR). MB43 MB15 SK46 5 SK13 SK45 ach isolate a unique haplotype. AB1 6 AB3 SK37 AB10 MB31 est of MCG: only 1% of isolates are compatible 7 SK32 with one or two othe MB17 SK29 olates. 8 SK23 9 SK38 MB1 AB27 AB16 AB6 MB36 SK6 AB12 SK16 AB9 AB23 MB18 MB24 MB27 SK55 SK5 SK8 MB29 MB5 MB58 MB52 MB13 MB48 MB39 MB25 SK26 SK2 SK52 SK9 MB38 MB19 SK53 MB6 MB26 SK4 MB22 MB51 SK33 AB31 MB10 MB3 MB49 MB59 MB61 MB55 10 MB56 MB32 MB21 MB12 MB40 SK20 MB45 12 AB15 SK35 11 MB2 AB25 AB7 SK15 AB4 SK10 MB11 MB23 MB57 SK48 SK51 SK34 13 AB22 MB50 MB46 MB41 SK36 MB7 Each isolate is a unique haplotype SK41 SK30 MB8 SK24 AB26 14 MB4 MB60 AB18 AB19 AB20 SK1 MB33 MB9 SK27 MB54 SK47 SK7 15 SK14 SK56 AB8 6 from Manitoba. SK49 16 AB2 MB30 17 MB SK Coefficient MB35 One isolate from each sub-population was selected for pathogenicity testing 5 from Alberta, 6 from Saskatchewan and

23 AB7 321 AB3 MB35 MB57 SK35 SK44 MB21 SK23 MB52 MB61 SK14 MB51 SK38 SK45 AB19 AB29 Stem lesion length, mm 250 Stem lesion length of B. napus accessions inoculated with 17 S. sclerotiorum isolates 200 Topas Tanto DC21 K PAK93 PAK

24 Identifying molecular markers linked to sclerotinia resistance

25 Molecular markers linked to sclerotinia resistance Method QTL mapping using 9 bi-parental doubled haploid populations Genotyping: 6K B. napus SNP chip microsatellite markers (AAFC) QTL data combined in a meta-analysis ( BioMacator ) Chromosome and genomic block Contributing parent Number of hits* max R 2 max LOD QTLsize (cm) Additive effect A1 U ZY to 15.0 C3 U ZY821 Bao to 5.0 C1 U ZY to 5.4 A3 F ZY821 PAK to 11.0 C1 F ZY821 PAK to 14.0 A1 F ZY821 Digger to 11.1 A6 C ZY to 16.8 A10 R PAK to 17.4 A7 I/X ZY821 PAK93 Digger to 27.6 C2 X ZY821 PAK to 24.4 C6 E ZY821 PAK93 Bao to 16.5 A5 J ZY821 PAK93 Digger to 25.5 C9 W ZY to 6.6 A6 A PAK to 7.1 A9 A ZY821 PAK54 Digger to 20.6 *The number of times one of the disease traits was significant unpublished

26 Transfer of sclerotinia resistance to canola Method 1) Cross elite canola line N x resistant line PAK54 2) Backcross F 1 to N ) Select F 1 plants having molecular markers linked to sclerotinia resistance 4) Develop hundreds of doubled haploid lines DH from these F 1 5) Use the stem test to select resistant DH lines 6) Identify DH lines that have other desirable traits

27 Identification of candidate defense genes underlying the molecular markers

28 -log (P-value) -log (P-value) Genome wide association study (GWAS) Method 180 B. napus accessions Phenotyped using the stem test Genotyped using 6K SNP chip (Illumna) microsatellite markers (SSR) Kinship analysis (Structure) QTL analysis (Tassel) Result: 114 SNP and 34 SSR were associated with sclerotinia resistance a) Genome A A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 b) Genome C C1 C2 C3 C4 C5 C6 C7 C8 C9 Manhattan plot of SSR markers associated with sclerotinia resistance

29 A7 sr1075bnm sr12235 Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sn12256 sr4047a Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sr0282r sn12242a Bn-A07-p Bn-A07-p sr6549a Bn-A07-p sn8353b sn12940bnp sr7660rb Bn-A10-p Bn-A07-p Bn-A09-p sr12111np sr11576a Bn-A10-p sn12131c Bn-A10-p sr11457 Bn-A10-p Bn-A02-p Bn-A10-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A10-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A10-p Bn-A07-p Bn-A01-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sn0658 Bn-A07-p Bn-A07-p sr11457a Bn-A07-p sr12111anp Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p ss2367a Bn-A07-p Bn-A07-p Bn-C7-p Bn-A07-p sn0582a Bn-A07-p Bn-A06-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sr8905a Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sn2065anp sr10557a Bn-A07-p sn2555ra sn2318r sr9226a sr9226c Bn-A07-p sn2195a Bn-A07-p Bn-C7-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A02-p sr12173bnp Bn-A02-p Bn-A02-p sr12294i Bn-A02-p Bn-A02-p Bn-A02-p sr12236a sr12387b Bn-A02-p Bn-A09-p sn9539bnp Bn-A07-p Bn-A02-p sr7223 sn12119a Bn-A07-p Bn-C6-p sn4641anp Bn-C6-p Bn-C6-p sn12461ia BnOMT Bn-A07-p Bn-A07-p Bn-A06-p ss2269a Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-C6-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-C6-p Bn-C6-p Bn-C6-p Bn-A07-p Bn-C6-p Bn-C6-p sr6014a Bn-C6-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-C6-p Bn-A07-p Bn-A07-p sr6275a snrh59 sr12236anm sr9539bnm Bn-C4-p Bn-C6-p Bn-C6-p Bn-A07-p Bn-A09-p Bn-C6-p Bn-C6-p Bn-C6-p Bn-C6-p Bn-A07-p Bn-C6-p Bn-A07-p Bn-C6-p Bn-A07-p Bn-A07-p Bn-C6-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-C6-p Bn-C6-p Bn-A07-p Bn-S00722-p17303 Bn-A07-p Bn-C6-p Bn-A07-p Bn-C6-p Bn-C6-p Bn-A07-p Bn-C6-p34871 ss2141b sn13026bnp Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p cM Candidate defense genes underlying resistance QTL on A7 IX A7 B. napus Bn-A07-p sn0582a Bn-A07-p Bn-A06-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sr8905a Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p sn2065anp sr10557a Bn-A07-p sn2555ra sn2318r sr9226a sr9226c Bn-A07-p sn2195a Bn-A07-p Bn-C7-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A07-p Bn-A02-p sr12173bnp Bn-A02-p Bn-A02-p sr12294i Bn-A02-p Bn-A02-p Bn-A02-p sr12236a sr12387b Bn-A02-p Bn-A09-p sn9539bnp Bn-A07-p B. rapa Bra Bra Lectin Bra Bra Bra Bra Bra BrID10283 BrID90043 Bra OMT Bra OMT Bra OMT BrID10281 Bra Bra Bra Lectin Bra Lectin Bra Bra Lectin Bra NBS-LRR Bra NBS-LRR Bra NBS-LRR BRMS005 BrID10923 Bra Lectin Bra Lectin Bra Bra Bra Bra BrID10485 Resources sequenced genomes of B. napus, B. rapa and B. oleracea Annotated genes in Abrabidopsis Br Gene ID position At gene ID Functional annotation Bra AT5G Leucine-rich receptor-like protein kinase family protein Bra AT1G O-methyltransferase family protein Bra AT1G O-methyltransferase family protein Bra AT1G O-methyltransferase family protein Bra Leucine-rich repeat transmembrane AT2G protein kinase protein Bra Leucine-rich repeat transmembrane AT4G protein kinase protein Bra Leucine-rich repeat protein kinase AT5G family protein Bra Disease resistance protein (CC-NBS- AT5G LRR class) family Bra Disease resistance protein (CC-NBS- AT5G LRR class) family Bra Disease resistance protein (CC-NBS- AT5G LRR class) family Bra Leucine-rich repeat protein kinase AT2G family protein Bra Leucine-rich repeat protein kinase AT2G family protein Bra Disease resistance-responsive AT1G (dirigent-like protein) family protein

30 Method mrna extracted from inoculated, un-inoculated, resistant and susceptible stem tissue 6, 12, 24, 48 and 72 hpi Transcription to cdna Hybridization to a 15,000 B. napus gene array Gene expression study Genes exclusively up-regulated in inoculated resistant stem tissue PGIP Stem tissue collected around lesions on ZY821 and Westar Zhao, J., Buchwaldt, L., Rimmer, S.R., Sharpe, A., McGregor, L.., Bekkaoui, D., and Hegedus, D., Patterns of differential gene expression in Brassica napus cultivars infected with Sclerotinia sclerotiorum. Mol. Plant Path. 10:

31 Gene used for transformation Function in host resistance Reduction in sclerotinia relative to the untransformed line DH12075 Hevein (lectin-like) Pathogen recognition. Proteins that bind Lectin carbohydrates especially from foreign sources such as chitin. Grouped by the substrate they bind (concanavalin) Concanavalin: α-d-mannosyl and α-d-glucosyl Lectin (curculin) Curculin: unknown substrate O-methyl transferase (OMT) Annexin Adds CH3- to indol-glucosinolates 0.7 Cytoplasmic calcium-binding protein, involved in polysaccharide transport. Response to stress and relocates to plasma membrane when cytosolic Ca 2+ increases. Involved in trafficking and organization of vesicles, exocytosis, endocytosis, calcium ion channel formation WRKY33 Regulation of gene transcription PGIP Effect of inserting a single candidate defense gene in canola on the sclerotinia phenotype Inhibitor of fungal polygalacturonase No effect

32 Agriculture and Agri-Food Canada Agriculture et Agroalimentaire Canada Acknowledgements Scientists Dwayne Hegedus Isobel Parkin Sally Vail Post Docs Edis Dzanaovic Fuyou Fu Harsh Garg Neha Gujaria-Verma Sanjaya Gyawali Krishna Puri Technicians Jennifer Adam Diney Bekkaoui Jonathan Durkin Myrtle Harrington Erin Higgins Kyla Horner Jackie Nettleton Vicky Roslinsky Funding Canadian Government Canola Council of Canada Saskatchewan Canola Development Council Saskatchewan Ministry of Agriculture Industry Consortium: Bayer, Dow, DL Seeds, KWS, Rapool Ring