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. 2018 Jul 31;8(8):2841-2854.
doi: 10.1534/g3.118.200493.

Genome-Wide Association and Regional Heritability Mapping of Plant Architecture, Lodging and Productivity in Phaseolus vulgaris

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Genome-Wide Association and Regional Heritability Mapping of Plant Architecture, Lodging and Productivity in Phaseolus vulgaris

Rafael T Resende et al. G3 (Bethesda). .

Abstract

The availability of high-density molecular markers in common bean has allowed to explore the genetic basis of important complex agronomic traits with increased resolution. Genome-Wide Association Studies (GWAS) and Regional Heritability Mapping (RHM) are two analytical approaches for the detection of genetic variants. We carried out GWAS and RHM for plant architecture, lodging and productivity across two important growing environments in Brazil in a germplasm of 188 common bean varieties using DArTseq genotyping strategies. The coefficient of determination of G × E interaction (c2int ) was equal to 17, 21 and 41%, respectively for the traits architecture, lodging, and productivity. Trait heritabilities were estimated at 0.81 (architecture), 0.79 (lodging) and 0.43 (productivity), and total genomic heritability accounted for large proportions (72% to ≈100%) of trait heritability. At the same probability threshold, three marker-trait associations were detected using GWAS, while RHM detected eight QTL encompassing 145 markers along five chromosomes. The proportion of genomic heritability explained by RHM was considerably higher (35.48 to 58.02) than that explained by GWAS (28.39 to 30.37). In general, RHM accounted for larger fractions of the additive genetic variance being captured by markers effects inside the defined regions. Nevertheless, a considerable proportion of the heritability is still missing (∼42% to ∼64%), probably due to LD between markers and genes and/or rare allele variants not sampled. RHM in autogamous species had the potential to identify larger-effect QTL combining allelic variants that could be effectively incorporated into whole-genome prediction models and tracked through breeding generations using marker-assisted selection.

Keywords: Common beans; DArTseq; GWAS QTL; Heritability; RHM QTL.

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Figures

Figure 1
Figure 1
Distribution of 3443 DArT and 3234 SNP markers (6677 total markers) along the 11 chromosomes of common bean (y-axis). The x-axis represents chromosome position in Mb.
Figure 2
Figure 2
Allele pair linkage disequilibrium (r2) across the entire P. vulgaris genome for all genotypes, plotted according to genetic distance in Mb and including both DArT and SNP markers. Decay lines for DArT (dotted line), SNPs (dashed line) and both marker types (solid line) are shown.
Figure 3
Figure 3
Genome-wide distribution of the significant QTL detected in the joint analysis by RHM along the 11 common bean chromosomes (y-axis) subdivided in 1 Mb windows for the three traits (right). Bar legends on the right correspond to regional heritability estimates. Red arrows indicate significant regions according to LRT test.
Figure 4
Figure 4
Manhattan plot of results from GWAS in gray solid circles and RHM in black unfilled circles for the tree traits (plant architecture, lodging and grain productivity). Lines indicate thresholds of genome-wide significance after permutation tests at 5% Bonferroni correction. Gray dotted, GWAS; black dashed, RHM.

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