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Abstract

Crossovers (COs) that form between homologous chromosomes during meiosis allow for novel combinations of
alleles in progeny and can therefore generate trait variation that did not exist in the parental generation. The
frequency and spatial location of COs are not only important for generating the raw material for evolution, but also
contribute to our ability to perform quantitative trait locus (QTL) mapping for phenotypic traits. Understanding the
mechanisms that govern CO formation will inform our current views of its importance for evolution and also
provide potential targets for facilitating plant breeding. Engineering changes in the frequency and distribution of
COs can improve QTL mapping of important agricultural traits and an also allow for more efficient trait
introgression by reducing the number of linked loci. Here we describe improvements in the ability to precisely
locate crossover events and perform QTL mapping using low-coverage whole-genome sequencing of individuals
in mapping populations. We developed a method for preparing libraries for next-generation sequencing at about a
tenth of the cost of established protocols and then used a refined Hidden Markov Model approach to reconstruct
the recombinant genomes of hundreds of F2 individuals generated from the Col-0 and Ws-2 accessions of
Arabidopsis thaliana. We resolved most CO breakpoints to within 2 kb and detected a 25-kb QTL interval for
flowering time on Chromosome 5 that includes the MAF2-5 gene cluster, which has previously been shown to
contribute to flowering time variation in natural populations. We conclude that this approach is efficient for
studying genetic factors affecting the crossover landscape and allows for the simultaneous (fine-) mapping of
quantitative traits.