Whole-genome versus per-chromosome targeted recombination: Simulations and predicted gains in maize with an integer programming model.

Abstract

Per-chromosome targeted recombination, with one to two recombinations at specific marker intervals on each chromosome, doubles the predicted genetic gains in biparental populations. We developed an integer programing model to identify where a fixed number of targeted recombinations should occur across the whole genome, without restrictions on the number of targeted recombinations on each chromosome. We compared whole-genome and per-chromosome targeted recombination in 392 biparental maize (Zea mays L.) populations and in simulation experiments. For yield, moisture, test weight, and a simulated trait controlled by 2000 quantitative trait loci (QTL), predicted gains were 8%-9% larger with 10 targeted recombinations across the entire genome than with one targeted recombination on each of the 10 chromosomes. With whole-genome targeted recombination, the number of recombinations on a given chromosome was correlated (r=0.76-0.91) with the chromosome size (in cM). Simulation results suggested that previous results on gains from targeted recombination relative to nontargeted recombination were too optimistic by around 20%. Because the underlying QTL are unknown, studies on targeted recombination have relied on genomewide marker effects as proxies for QTL information. The simulation results indicated a 25% (for 10 recombinations) to 33% (for 20 recombinations) reduction in response due to the use of genomewide marker effects as proxies for QTL information. Overall, the results indicated that the integer programming model we developed is useful for increasing both the predicted and true gains from targeted recombination, but the predicted gains are likely to overestimate the true gains.