Yield dissection models to improve yield: A case study in tomato

Yutaka Tsutsumi-Morita, Ep Heuvelink, Sedighehsadat Khaleghi, Daniela Bustos-Korts, Leo F.M. Marcelis, Kim M.C.A. Vermeer, Hannelore Van Dijk, Frank F. Millenaar, George A.K. Van Voorn, Fred A. Van Eeuwijk*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

Abstract

Yield as a complex trait may either be genetically improved directly, by identifying QTLs contributing to yield, or indirectly via improvement of underlying components, where parents contribute complementary alleles to different components. We investigated the utility of two yield dissection models in tomato for identifying promising yield components and corresponding QTLs. In a harvest dissection, marketable yield was the product of number of fruits and individual fruit fresh weight. In a biomass dissection, total yield was the product of fruit fresh-dry weight ratio and total fruit dry weight. Data came from a greenhouse experiment with a population of hybrids formed from four-way RILs. Trade-offs were observed between the component traits in both dissections. Genetic improvements were possible by increasing the number of fruits and the total fruit dry weight to offset losses in fruit fresh weight and fruit fresh-dry weight ratio. Most yield QTLs colocalized with component QTLs, offering options for the construction of high-yielding genotypes. An analysis of QTL allelic effects in relation to parental origin emphasized the complementary role of the parents in the construction of desired genotypes. Multi-QTL models were used for the comparison of yield predictions from yield QTLs and predictions from the products of components following multi-QTL models for those components. Component QTLs underlying dissection models were able to predict yield with the same accuracy as yield QTLs in direct predictions. Harvest and biomass yield dissection models may serve as useful tools for yield improvement in tomato by either or both of combining individual component QTLs and multi-QTL component predictions.

Original languageEnglish
Article numberdiab012
Journalin silico Plants
Volume3
Issue number1
DOIs
Publication statusPublished - 4 Mar 2021

Keywords

  • Complementation
  • four-way RIL
  • indeterminate tomato
  • multi-parent population
  • QTLs
  • yield components
  • yield dissection
  • yield prediction

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