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

Author:

Resende Rafael T1,de Resende Marcos Deon V123,Azevedo Camila F2,Fonseca e Silva Fabyano4,Melo Leonardo C5,Pereira Helton S5,Souza Thiago Lívio P O5,Valdisser Paula Arielle M R6,Brondani Claudio6,Vianello Rosana Pereira6

Affiliation:

1. Department of Forestry

2. Department of Statistics, Universidade Federal de Viçosa, Viçosa, MG 36570-000, Brazil

3. EMBRAPA Florestas, Colombo, PR 83411-000, Brazil

4. Department of Animal Science, Universidade Federal de Viçosa, Viçosa, MG 36570-000, Brazil

5. Common Bean Breeding Program

6. Laboratory of Biotechnology, EMBRAPA Arroz e Feijão, Santo Antônio de Goiás, GO 75375-000, Brazil

Abstract

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.

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology

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