Data from: Genetic architecture of nonadditive inheritance in Arabidopsis thaliana hybrids
| Main Authors: | Seymour, Danelle K., Chae, Eunyoung, Grimm, Dominik G., Martín Pizarro, Carmen, Habring-Müller, Anette, Vasseur, François, Rakitsch, Barbara, Borgwardt, Karsten M., Koenig, Daniel, Weigel, Detlef |
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| Format: | info dataset Journal |
| Terbitan: |
, 2017
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4939426 |
Daftar Isi:
- The ubiquity of nonparental hybrid phenotypes, such as hybrid vigor and hybrid inferiority, has interested biologists for over a century and is of considerable agricultural importance. Although examples of both phenomena have been subject to intense investigation, no general model for the molecular basis of nonadditive genetic variance has emerged, and prediction of hybrid phenotypes from parental information continues to be a challenge. Here we explore the genetics of hybrid phenotype in 435 Arabidopsis thaliana individuals derived from intercrosses of 30 parents in a half diallel mating scheme. We find that nonadditive genetic effects are a major component of genetic variation in this population and that the genetic basis of hybrid phenotype can be mapped using genome-wide association (GWA) techniques. Significant loci together can explain as much as 20% of phenotypic variation in the surveyed population and include examples that have both classical dominant and overdominant effects. One candidate region inherited dominantly in the half diallel contains the gene for the MADS-box transcription factor AGAMOUS-LIKE 50 (AGL50), which we show directly to alter flowering time in the predicted manner. Our study not only illustrates the promise of GWA approaches to dissect the genetic architecture underpinning hybrid performance but also demonstrates the contribution of classical dominance to genetic variance.
- Table S1. Germplasm information.The parental genotypes of each hybrid are listed along with whether the line was included in the final data set (yes=1, no=0). Lines were not included if their manually-fertilized parent did not germinate.TableS1.xlsxTable S2. GCA, SCA, and heritability estimates.Values for plots in Fig 1.TableS2.xlsxTable S3. Summary of significant SNPs detected in GWA analyses.Number of significant SNPs detected for each trait for both within-study and across-study Bonferroni correction.TableS3.xlsxTable S4. Summary of significant SNPs per trait.IDs (chr_position) of all significant SNPs and their significance status in each GWA study.TableS4.xlsxTable S5. Summary of SConES SNPs.Number of associated SNPs detected for each trait.TableS5.xlsxTable S6. Summary of associated SConES SNPs per trait.IDs (chr_position) of all associated SNPs and their significance status in each GWA study.TableS6.xlsxTable S7. Summary of candidate genes.IDs and location of all significant regions, their associated traits, genetic behavior, and candidate causal genes.TableS7.xlsxTable S8. Gene Ontology (GO) enrichment.GO terms significantly associated with the top 1,000 associated SNPs of each trait are listed. Significance was established using a 5% FDR threshold within each trait.TableS8.xlsxTable S9. Genomic control (GC) values.Genomic control values for all GWA analyses. Q-Q plots for GWAs with significant SNPs are shown in SI Appendix, Fig S20.TableS9.xlsx