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Genetic Basis of Agronomic Traits Connecting Phenotype to Genotype Yu and Buckler (2006); Zhu et al. (2008) Traditional F2 QTL MappingAssociation Mapping.

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Presentation on theme: "Genetic Basis of Agronomic Traits Connecting Phenotype to Genotype Yu and Buckler (2006); Zhu et al. (2008) Traditional F2 QTL MappingAssociation Mapping."— Presentation transcript:

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2 Genetic Basis of Agronomic Traits

3 Connecting Phenotype to Genotype Yu and Buckler (2006); Zhu et al. (2008) Traditional F2 QTL MappingAssociation Mapping Use recombination events in F2 to narrow trait of interest to a genomic region Rely on co-inheritance of functional polymorphism and DNA variant Correlate molecular with phenotypic variation, rely on many generations of historical recombination, phenotype of interest may be associated with a smaller chromosomal segment

4 Association Mapping Workflow 1. Germplasm 2. Phenotyping 2. Genotyping Genome-wide association mapping Candidate/targeted gene approach 3. Association Testing Choose lines to include in mapping population to capture as much diversity as possible Grow and measure traits in replicated trials Correlate phenotypic variation with genotypic variation

5 Extent of linkage disequilibrium – Informs genotyping strategy – Amount of resolution Degree of population structure – Can lead to false associations Association Mapping Considerations

6 2. Investigate the structure of LD within the association mapping population 4. Test for associations between molecular polymorphisms and variation in key traits 3. Grow and characterize the population for wide variety of traits + genotype Sunflower Association Mapping (SAM) Objectives 1. Population genetics of the sunflower germplasm, select lines for inclusion

7 Core 12 (~50% of allelic diversity) Core 48 (~60% of allelic diversity) Core 96 (~70% of allelic diversity) Core 192 (~80% of allelic diversity) 433 Cultivated Sunflower Lines Core 288 (~90% of allelic diversity) SAM Population Line Selection Mandel et al., TAG 2011

8 SAM Genetic Diversity Mandel et al., PLoS Genetics 2013

9 SAM Genetic Relationships HA X RHA Mandel et al., PLoS Genetics k SNPs

10 Genome-Wide Patterns of F ST Mandel et al., PLoS Genetics 2013 RHA vs. HA 10k SNPs

11 Linkage Group 1 Genome-Wide Patterns of LD Mandel et al., PLoS Genetics k SNPs

12 Linkage Group 10 Genome-Wide Patterns of LD Mandel et al., PLoS Genetics k SNPs

13 Genome-Wide Patterns of LD Mandel et al., PLoS Genetics k SNPs

14 Background Genomic Diversity Substantial SNP genetic variation Population structure RHA vs. HA – Somewhat restricted to linkage groups LD also varies extensively across the genome Phenotypic measurements

15 SAM Field Locations Plant > 20K seeds 288 inbred lines 4 plants per line 2 replicates 3 locations 7,200 plants 15 people

16 Phenotyping: - Flowering time - Plant architecture - Pigmentation - Leaf traits - Dormancy/germination - Wood-related traits - Total biomass - Oil-related traits Genotyping strategies: - 10k SNP Infinium array - GBS approach, ~ 40k SNPs - Seed size/shape SAM Phenotyping/Genotyping - Leaf C and N - Entire SAM re-sequencing

17 Flowering Time SNP associations 10k SNP Array Mandel et al., PLoS Genetics k SNPs

18 Visualizing Associations – LG 10 Recessive apical branching No Branching Branching Mandel et al., PLoS Genetics k SNPs

19 Downy Mildew Black Stem Sunflower Rust Branching/Flowering Elevated LD and Potential Targets of Selection Mandel et al., PLoS Genetics k SNPs

20 Co-Localization of QTL and SNP Associations Days to Flower Total Branching Mandel et al., PLoS Genetics k SNPs

21 Cell-wall Chemistry SNP Associations GBS, Lignin at GA location ~40k SNPs

22 SAM Re-Sequencing Efforts Entire SAM population of 288 lines South Africa ARC, Genome Canada/Quebec, and INRA Illumina Hi-Seq, 1 or 2 samples per lane

23 SAM Re-Sequencing Data Analysis Workflow Adam Bewick and Ben Hsieh Sunflower genome – Version: Nov22k22.scf.split.fasta Read-trimming with prinseq-lite Alignment with BWA Produce VCF files with samtools

24 SAM Re-Sequencing Coverage Adam Bewick 191/288 lines have been run through the pipeline LR, NO-I, O-I, OPV, NO, O

25 SAM Re-Sequencing Next Steps Next step is to assay genetic variation – Structural Variation: CNV – Adam’s talk – SNPs Use data for genome-wide investigations of genetic variation, association mapping, and evolutionary analyses

26 Association Genetics Summary Mapping panel is very diverse LD varies across the genome Association testing and SNPs and genomic regions as candidates Created permanent mapping resource Sequenced genome and 288 re-sequenced lines: GREAT resource!

27 Members of the: Burke Lab Leebens-Mack Lab Rieseberg Lab Raj Ayyampalayam Undergrad Teams Adam Bewick Ben Hsieh John Bowers Mark Chapman Laura Marek Jenny Dechaine Savithri Nambeesan Ed McAssey Steve Knapp Eleni Bachlava Acknowledgments


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