Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels

Aurelien Beugnot, Tristan Mary-huard,Cyril Bauland,Valerie Combes,Delphine Madur, Bernard Lagardère,Carine Palaffre, Alain Charcosset,Laurence Moreau,Julie B. Fievet

crossref(2022)

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摘要
Abstract Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from intergroup crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibit overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs explains part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrated the interest of admixed panels and our GWAS model to reveal new QTLs involved in group differentiation that were inaccessible in classical factorial hybrid panels with traditional modelling.
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