Abstract
Recombination is the exchange of genetic material between homologous chromosomes via physical crossovers. High-throughput sequencing approaches detect crossovers genome wide to produce recombination rate maps but are difficult to scale as they require large numbers of recombinants individually sequenced. We present a simple and scalable pooled-sequencing approach to experimentally infer near chromosome-wide recombination rates by taking advantage of non-Mendelian allele frequency generated from a fitness differential at a locus under selection. As more crossovers decouple the selected locus from distal loci, the distorted allele frequency attenuates distally toward Mendelian and can be used to estimate the genetic distance. Here, we use marker selection to generate distorted allele frequency and theoretically derive the mathematical relationships between allele frequency attenuation, genetic distance, and recombination rate in marker-selected pools. We implemented nonlinear curve-fitting methods that robustly estimate the allele frequency decay from batch sequencing of pooled individuals and derive chromosome-wide genetic distance and recombination rates. Empirically, we show that marker-selected pools closely recapitulate genetic distances inferred from scoring recombinants. Using this method, we generated novel recombination rate maps of three wild-derived strains of Drosophila melanogaster, which strongly correlate with previous measurements. Moreover, we show that this approach can be extended to estimate chromosome-wide crossover interference with reciprocal marker selection and discuss how it can be applied in the absence of visible markers. Altogether, we find that our method is a simple and cost-effective approach to generate chromosome-wide recombination rate maps requiring only one or two libraries.