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Updated: May 5, 2026

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A theoretical model for quantitatively inherited traits influenced by nuclear-cytoplasmic interactions
W D Beavis1, E Pollak, K J Frey
1Pioneer Hi-bred International, 79072, Plainview, TX, USA.
Summary
Cytoplasmic genes influence crop traits like yield through non-Mendelian inheritance. A new model incorporating maternal inheritance helps understand genetic contributions to quantitative traits.
Area of Science:
- Genetics
- Plant Breeding
- Molecular Biology
Background:
- Cytoplasmic genes in chloroplasts and mitochondria affect crop quantitative traits (biomass, yield).
- These genes exhibit non-Mendelian, often maternal, inheritance, unlike nuclear genes.
- Photosynthesis and respiration, key physiological processes, are regulated by both cytoplasmic and nuclear genes.
Purpose of the Study:
- To develop a genetic model for crop individuals considering both nuclear and cytoplasmic inheritance.
- To derive genetic variances and covariances for populations with mixed inheritance patterns.
- To explore the utility of reciprocal mating designs for estimating genetic variance components.
Main Methods:
- Modeled genotypic value using maternal inheritance of cytoplasmic genomes and Mendelian inheritance of nuclear genomes.
- Derived genetic variances and covariances for a random-mating population based on the model.
- Investigated reciprocal mating designs for estimating variance components.
Main Results:
- A model was established to integrate maternal cytoplasmic inheritance with Mendelian nuclear inheritance.
- The model allows for the derivation of genetic variances and covariances.
- Reciprocal mating designs show potential for estimating variance components.
Conclusions:
- The developed model provides a framework for understanding the genetic basis of quantitative traits influenced by cytoplasmic factors.
- This approach is crucial for crop improvement strategies, particularly in understanding maternal effects on yield and biomass.
- Further investigation into reciprocal crosses can refine the estimation of genetic contributions from different genomes.
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