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Prediction of crossover recombination using parental genomes
Mauricio Peñuela1, Camila Riccio-Rengifo1, Jorge Finke1
1Facultad de Ingeniería y Ciencias, Pontificia Universidad Javeriana, Cali, Colombia.
Plos One
|February 16, 2023
Summary
Predicting plant recombination rates is now more accurate. A new model uses sequence identity to estimate chromosomal recombination, aiding plant breeding and the development of new varieties.
Area of Science:
- Genetics
- Plant Breeding
- Genomics
Background:
- Meiotic recombination drives evolution and adaptation.
- Plant breeding utilizes crossing to introduce genetic variation.
- Existing methods struggle to predict recombination between specific plant accessions.
Purpose of the Study:
- To develop a predictive model for local chromosomal recombination rates in rice.
- To test the hypothesis that chromosomal recombination correlates with sequence identity.
Main Methods:
- Developed a model using sequence identity and genome alignment features (variants, inversions, absent bases, CentO sequences).
- Validated the model using an indica x japonica rice cross with 212 recombinant inbred lines.
Main Results:
- Achieved an average correlation of approximately 0.8 between predicted and experimental recombination rates across chromosomes.
- Demonstrated the model's ability to characterize recombination rate variation along chromosomes.
Conclusions:
- The proposed model accurately predicts local chromosomal recombination in rice.
- This tool can enhance breeding programs by facilitating the creation of novel allele combinations and desirable traits.
- The model offers a way to reduce costs and time in plant crossing experiments.
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