Prediction of crossover recombination using parental genomes


Meiotic recombination is a crucial cellular process, being one of the major drivers of evolution and adaptation of species. In plant breeding, crossing is used to introduce genetic variation among individuals and populations. While different approaches to predict recombination rates for different species have been developed, they fail to estimate the outcome of crossings between two specific accessions. This paper builds on the hypothesis that chromosomal recombination correlates positively to a measure of sequence identity. It presents a model that uses sequence identity, combined with other features derived from a genome alignment (including the number of variants, inversions, absent bases, and CentO sequences) to predict local chromosomal recombination in rice. Model performance is validated in an inter-subspecific indica x japonica cross, using 212 recombinant inbred lines. Across chromosomes, an average correlation of about 0.8 between experimental and prediction rates is achieved. The proposed model, a characterization of the variation of the recombination rates along the chromosomes, can enable breeding programs to increase the chances of creating novel allele combinations and, more generally, to introduce new varieties with a collection of desirable traits. It can be part of a modern panel of tools that breeders can use to reduce costs and execution times of crossing experiments.

PLOS ONE 2023, 18(2), 1-21;
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