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"Implications of partitioned genetic diversity for linkage disequilibrium mapping in elite UK cereal germplasm". Donal O’Sullivan SGC Meeting, JIC, 6-7.

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Presentation on theme: ""Implications of partitioned genetic diversity for linkage disequilibrium mapping in elite UK cereal germplasm". Donal O’Sullivan SGC Meeting, JIC, 6-7."— Presentation transcript:

1 "Implications of partitioned genetic diversity for linkage disequilibrium mapping in elite UK cereal germplasm". Donal O’Sullivan SGC Meeting, JIC, 6-7 th April 2006

2 Purpose Why use ‘elite’ varieties? Most familiar and obvious material Reasonable levels of diversity present Relevant to current markets Obtainable in quantity Extensive ‘historic series’ of robust field data for most relevant phenotypes To explore the prudent use of ‘populations’ of elite cereal varieties as LD mapping panels

3 Partitioning in 500+ Gediflux Barley varieties

4 Association mapping in wheat: proof of principle Gediflux data set: 499 genotyped varieties. 73 SSAPs, 42 SSRs, 72 NBS 1B1R, pinb haplotypes Historic trial data: 193 varieties with 18 phenotypes (incomplete ) yield +/- treated, hardness (113 lines) Lodging, disease, etc. Use pinb as a candidate with known phenotypic effect Use SSRs for structured association Analyse using “Structure” and “Strat” Use SSAPs for genomic control Analyse trait by trait by logistic regression

5 Mining historic endosperm texture data Historic NL trial data <2001

6 Structured association Structure: burn-in1 million iterations1 million No. populations (K) 8 No. replicate runs2

7 K = 8 cluster 1 vs cluster 5 Proportion of each individual in cluster 1. Proportion of each individual in cluster 5. Gediflux 500+ winter wheat

8 Pedigree of lines with highest ancestry in clusters 1 and 5. Cluster 1Cluster 5

9 Descendants of a cluster 5 founder

10 parents cluster 1cluster 5 progeny cluster 113 1 cluster 5 3 19 odds ratio82 p-value 0.00001 Parentage of lines for clusters 1 and 5. Cluster membership is genetic!

11 Association test using STRAT / structure Pinb and hardness testchi sqp-value Assuming no structure in population 44.44 0 Corrected (run a) 21.89 0 Corrected (run b) 21.42 0

12 STRAT and structure - QC Hardness and 55 SSAP markers, p-values <0.05 TestNo. <0.05 Assuming no pop. structure 14 Adjusted, run a 6 Adjusted, run b 6 Expected 3 May be under correcting.

13 Pedigree relationships between SBCMV resistant varieties 5 5 5 5 5 5 5 3 3 Red = Tested R, Blue = Tested S, Grey = Untested

14 Genomic Control Method: use multilocus genotype data to detect and correct for stratification Premise: admixture operates over the whole genome but LD operates locally at short scales 18 traits 58 SSAP 1044 logistic regression analyses

15 Genomic control: p-values, pinb original GC Dry matter contenttreated1.0001.000 Hagberg numbertreated0.0050.317 Percent leaningtreated0.7330.842 Percent lodgingtreated0.0080.053 Protein contenttreated0.0450.298 Specific weighttreated0.1320.526 Straw lengthtreated0.0530.403 Yieldtreated0.7230.865 Brown rustnot treated0.0080.012 Hagberg numbernot treated0.5830.828 Percent leaningnot treated0.4630.691 Percent lodgingnot treated0.2640.276 Mildewnot treated0.7960.888 Protein contentnot treated0.0010.184 Septoria triticinot treated0.0910.426 Specific weightnot treated0.0800.288 Straw lengthnot treated0.5830.808 Hardness0.0000.000

16 Test markers across all traits No. of tests1044 P-value <0.05 OBS original313 OBS GC34 EXP52 May be overcorrecting Genomic control: QC

17 Conclusions Population structure may be evident e.g. spring-winter/row number divide or less so –Carry out LD mapping within major sub-groups UK winter wheat shows cryptic population structure which groups varieties consistent with known pedigree Genomic control and/or structured association both effective in detecting known associations and reducing false +ves to realistic levels Roll on new phenotype and genotype data!

18 Acknowledgements NIAB –Fiona Leigh –John Law –Ian Mackay –Wayne Powell Gediflux Partners –Barley –Marion Roeder (IPK) –Wheat –Rob Koebner, Simon Orford (JIC) –Martin Ganal (Trait Genetics)


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