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Parent Selection – Usefulness and Prediction of Hybrid Performance

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Diagnostics in Plant Breeding

Abstract

Efficiency of breeding programs depends on choice of optimal parental combinations. The ability to identify parental combinations that will result in greater genetic variance of progeny would help to maximize genetic gain from selection in plant breeding programs. Substantial efforts have been invested to study the possible correlations between various predictors based on parental information with population mean \( ({\mu_m}) \) and genetic variance of segregating population \( \left( {\Delta {\sigma_{g(m) }}} \right) \). With the development of DNA-based markers, it became possible to determine genetic distances \( (G{\overset{\lower0.0em\hbox{$\smash{\scriptscriptstyle\frown}$}}{D}}) \) among parental lines. However, prediction \( \Delta {\sigma_{g(m) }} G{\overset{\lower0.0em\hbox{$\smash{\scriptscriptstyle\frown}$}}{D}} \) based on DNA marker data remains a challenging issue. In view of the weakness of traditional marker-assisted selection in prediction potential \( \Delta {\sigma_{g(m) }}, \) the use of genomic selection (GS) is considered as promising approach. Rather than seeking to identify individual markers significantly associated with a quantitative trait, GS could use all marker data as predictors of parental line performance and contributes to accurate predictions of the usefulness of parental combinations.

The ability to predict hybrid performance (HP) of breeding lines based on molecular-based genetic data would greatly enhance the efficiency of hybrid breeding programs. Therefore, the relationship between genetic distance \( G{\overset{\lower0.0em\hbox{$\smash{\scriptscriptstyle\frown}$}}{D}} \) and HP was intensively studied by many authors, predominantly by allogamous crop breeders. Prediction of HP without having to produce and assess hundreds of single-cross hybrids would reduce the time and effort required to identify promising combinations. Earlier studies indicated that the success of predicting HP based on \( G{\overset{\lower0.0em\hbox{$\smash{\scriptscriptstyle\frown}$}}{D}} \) of parental information was not encouraging and at best inconsistent. However, recent marker-based prediction approaches based on expression profiling and those based on multiple linear regressions gave results often superior or at least similar to phenotypic and pedigree data approaches.

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Acknowledgements

This book chapter was prepared while Dr. Adel Abdel-Ghani was a visiting Fulbright Postdoctoral Fellow and during the sabbatical leave granted to Dr. Adel Abdel-Ghani from Mu’tah University, Jordan during the academic year 2011–2012 at Iowa State University, Ames, USA.

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  1. Department of Plant Production, Faculty of Agriculture, Mu’tah University, 7, Karak, Jordan

    Adel H. Abdel-Ghani

  2. Department of Agronomy, Iowa State University, 1211 Agronomy Hall, Ames, IA, USA

    T. Lübberstedt

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Correspondence to Adel H. Abdel-Ghani .

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  1. Dept. Agronomy, Iowa State University, Agronomy Hall 1204, Ames, 50011, Iowa, USA

    Thomas Lübberstedt

  2. ICRISAT, Centre of Excellence in Genomics (CEG), Patancheru, 502 324, Andra Pradesh, India

    Rajeev K. Varshney

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Abdel-Ghani, A.H., Lübberstedt, T. (2013). Parent Selection – Usefulness and Prediction of Hybrid Performance. In: Lübberstedt, T., Varshney, R. (eds) Diagnostics in Plant Breeding. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5687-8_17

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