A mixed model based QTL / AM analysis of interactions (G by G, G by E, G by treatment) for plant breeding
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1 Professur Pflanzenzüchtung Professur Pflanzenzüchtung A mixed model based QTL / AM analysis of interactions (G by G, G by E, G by treatment) for plant breeding Jens Léon 4. November 2014, Oulu Workshop Animal models with applications in ecology
2 Professur Pflanzenzüchtung QTL and Association Mapping Goal: genomic locations (map positions) and effects (or variance) of genes underlying quantitative trait variation QTL mapping Using linkage information on a set of known relatives Association mapping Using very fine scale LD to map genes in a set of random individuals from a population
3 Professur Pflanzenzüchtung Outline Introduction on Mixed linear modeling for QTL mapping Case studies on multi parent (NAM, MAGIC) populations Haplotypes, epistatic effects experiment with salt stress tolerance QTL by treatment interaction
4 Professur Pflanzenzüchtung Single Marker analysis (Mixed modeling) QTL mapping methods Interval Mapping (IM) Composite interval mapping (CIM) Same results as Single Marker Analysis With dense marker maps
5 Professur Pflanzenzüchtung Plant Breeding Testing identical genotypes/line/clones using specific experimental designs (replicated Block-, α-design etc.) Often more than one treatment (eg. Control vs. Stress) QTL by treatment interaction (fixed factor) Often in several environments QTL by environment interaction (random factor) Multiple alleles or haplotypes
6 Professur Pflanzenzüchtung Macro Mixed linear model for QTL detection in plant Breeding (SAS 9.2) Y ijk = μ + QTL + T l + B(T l ) + M i + M i * T l + L k (M i ) + ε ijk Y ijk = μ + QTL + M i + M j + M i * M j + L k (M i * M j ) + ε ijk As flexible as the statistical software is Advantages treatment/environment information (fixed or random factor) multi-locus analysis (forward/backward selection) cross validation permutation whole genome marker*marker or treatment by marker interaction shrinkage multi-trait analysis 6
7 Pedigree Analysis & Association Mapping Professur Pflanzenzüchtung Pedigree Analysis: Association Mapping: Pedigree known Low number of Meioses (below or near 100) Power: cmorgan (MBase) Kinship of entries is equal, no population structure pedigree unknown Many meioses (>10 4 ) Power: 10-5 Morgan (kbase) Kinship not equal between entries, population structure
8 Professur Pflanzenzüchtung Association Mapping Q matrix to include the structure into an analysis Identifying several groups in which the members are in Hardy Weinberg equilibrium
9 Professur Pflanzenzüchtung Association Mapping Q matrix to include the structure into an analysis Kinship matrix to include possible genetic relationships between entries in a population Both can be easily included in SAS software
10 Professur Pflanzenzüchtung Case studies Wheat Oilseed rape barley
11 Evolution of hexaploid wheat Professur Pflanzenzüchtung Low agronomic characteristics High genetic diversity Disease resistance Abiotic stress tolerance Fully crossable with modern bread wheat (Lillemo, 2010) 12
12 Development of the synthetic backcrossed population Professur Pflanzenzüchtung Syn86 X Zentos Parents Zentos: F 1 X Zentos German elite winter wheat cultivar Syn86: BC 1 F 1 X Zentos Synthetic hexaploid wheat BC 2 F 1 Z86-population 150 lines BC 2 F 3 2 x selfing 3 x bulk propagation BC 2 F
13 Phenotyping for salt stress tolerance Professur Pflanzenzüchtung Studying effect of salt stress at 3 development stages of wheat: Germination stage Germination test on filter paper (NaCl/Na 2 SO 4) Seedling stage Hydroponics (NaCl/ Na 2 SO 4 ) Maturity stage Field trials in 4 countries in Asia with natural salinization: Uzbekistan, Turkmenistan, Kazakhstan and China Nonsaline Saline 14
14 Genotypic characterization Professur Pflanzenzüchtung Genotyping of testing populations by Illumina GoldenGate 90k SNP-chip at TraitGenetics (Germany) Population Bi-parental population Association panel Population size Kinship Polymorphic markers Average SNP Density 150 related cm 150 unrelated cm 15
15 QTL analysis for Shoot Fresh Weight Professur Pflanzenzüchtung
16 Professur Pflanzenzüchtung Shrinking approach in QTL region Nearby marker should give an similar signature than the QTL itself Walsh lecture on QTL
17 Professur Pflanzenzüchtung Shrinkage of marker effects Algorithm including cross validation and conditional analysis Important for further identification of regions of candidate genes Identification of covariables Epistatic effects or epistatic variance components as all epistatic effects have a trace in additive or dominance genetic variance (V A and V D ) Genomic selection procedures
18 Conditional analysis for Shoot FW Professur Pflanzenzüchtung
19 Professur Pflanzenzüchtung Interaction Gene by Gene Gene by environment Gene by treatment Example: Salt stress tolerance Analyzing each treatment separately Building a Stress index and analyse the index Marker by salt stress interaction
20 Gene by Treatment interaction (Shoot FW) Professur Pflanzenzüchtung
21 Gene by Treatment interaction (Shoot FW) Round 1 Professur Pflanzenzüchtung
22 Gene by Treatment interaction (Shoot FW) Round 2 Professur Pflanzenzüchtung
23 Gene by Treatment interaction (Shoot FW) Round 3 Professur Pflanzenzüchtung
24 QTL analysis and detection of candidate genes Professur Pflanzenzüchtung Gene by Treatment interaction (Shoot FW) R2: 18.7% R2: 9.1% R2: 15.9% 25
25 Professur Chair Pflanzenzüchtung of Plant Breeding Mapping population Association panel Collaborative Cross 2004 MAGIC population Barley Bi-parental population 26
26 recurrent parent Genotype 1 Genotype 2 Genotype 3 Genotype 4 Genotype 5 Genotype 6 Genotype 7 Genotype 8 Genotype 9 Genotype 10 Genotype 11 Genotype 12 Genotype 13 Genotype 14 Genotype 15 Genotype 16 Genotype 17 Genotype 18 Genotype 19 Genotype 20 Genotype 21 BnNAM-DH Pre-BreedYield parents X BnNam DHs 50 DH-Lines per cross 27
27 Erucic acid Pre-BreedYield 28
28 Introduction Material & Methods Results & Discussion Professur Chair Pflanzenzüchtung of Plant Breeding MAGIC-Population in barley Ack. Bavaria Barke Heils Franken Heines Hanna Pflugs Intensiv Ragusa Ack. Danubia Criewener 403 G 0 x x x x A B C D E F G H G 1 x x AB CD EF GH G 2 ABCD x EFGH G 3 x G 4 ABCDEFGH G 5 Doubled Haploid (DH) based on Cavanagh et al
29 Introduction Material & Methods Results & Discussion Professur Chair Pflanzenzüchtung of Plant Breeding Experimental approach 533 MAGIC DH lines Marker data 9k iselect SNP chip Phenotypic data Flowering time QTL Analysis Estimation of epistatic effects 30
30 Introduction Material & Methods Results & Discussion Professur Chair Pflanzenzüchtung of Plant Breeding Genetic approach Marker data (A/C/G/T) Matrix (0/1) Genetic map (R/mpMap) Haplotype approach Chromosome Position Marker Parent 1 DH 1 DH 2 DH 3 DH 4 DH 5 DH 6 DH 7 DH 8 DH 9 DH 10 1H 10.5 SNP H 11.7 SNP H 13.1 SNP H 14.1 SNP H 14.9 SNP H 16.4 SNP H 17.3 SNP H 20.1 SNP H 21.0 SNP H 21.9 SNP H 22.8 SNP
31 Introduction Material & Methods Results & Discussion Professur Chair Pflanzenzüchtung of Plant Breeding Genotypic characterization of MAGIC population Results r² 5117 SNP marker Chromosome 1H-7H cm position in cm (barley consensus map from Comadran et al. 2012) 32
32 Introduction Material & Methods Results & Discussion Professur Chair Pflanzenzüchtung of Plant Breeding Ten epistatic effects determined by haplotype approach Flowering time Epistatic effect SNP 1 SNP 2 position a position a -log 10 (p) AB/ AB/ AB/ B/ HF/ HF/ HH/ HH/ HH/ R/ R/ AD/ AD/ AD/ AB HF AD R HH R HF R AD HH R B HF R Diff Epi-HA-1 5H H NA NA NA NA NA 11.8 Epi-HA-2 2H H NA NA Epi-HA-3 3H H Epi-HA-4 2H H NA Epi-HA-5 1H H NA Epi-HA-6 3H H NA NA 12.5 Epi-HA-7 5H H NA 59.9 NA NA NA NA NA 9.4 Epi-HA-8 5H H NA NA NA 61.2 NA NA NA 53.3 NA NA 73.3 NA NA NA 20.0 Epi-HA-9 3H H NA NA NA NA Epi-HA-10 2H H NA NA NA NA NA 59.9 NA NA NA NA NA
33 Professur Pflanzenzüchtung Epistatic effects haplotype approach flowering time Trevaskis et al., 2007 multi-locus analysis (forward/backward selection) 34
34 Macro for Marker/Trait association Professur Pflanzenzüchtung SAS University Edition (free access). Testing population Phenotypic characterization Genotypic characterization Trait Marker/Trait association Marker QTL detection Validation of cand. genes Breeding process SAS macro (Léon, 2014) 35
35 Professur Pflanzenzüchtung Acknowledgements Data from W. Sannemann Tobias Kox Said Dashani Benedict Oyiga Agim Ballvora
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