A New Method to Reconstruct Recombination Events at a Genomic Scale

Recombination is one of the main forces shaping genome diversity, but the information it generates is often overlooked. A recombination event creates a junction between two parental sequences that may be transmitted to the subsequent generations. Just like mutations, these junctions carry evidence of the shared past of the sequences. We present the IRiS algorithm, which detects past recombination events from extant sequences and specifies the place of each recombination and which are the recombinants sequences. We have validated and calibrated IRiS for the human genome using coalescent simulations replicating standard human demographic history and a variable recombination rate model, and we have fine-tuned IRiS parameters to simultaneously optimize for false discovery rate, sensitivity, and accuracy in placing the recombination events in the sequence. Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity. IRiS analysis of the MS32 region, previously studied using sperm typing, showed good concordance with estimated recombination rates. We also applied IRiS to haplotypes for 18 X-chromosome regions in HapMap Phase 3 populations. Recombination events detected for each individual were recoded as binary allelic states and combined into recotypes. Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS. We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation.Author Summary: Recombination brings together DNA sequences that can be very distantly related, and, thus, quite different from each other. This is often cited as a main hurdle for using recombining regions (that is, most of the genome) to reconstruct sequence phylogeny. We have turned this argument around: chromosomes carrying a similar change in sequence pattern are likely to be descendants of the same recombination event, and thus, related. We have devised an algorithm that detects such changes in sequence patterns and identifies the descendants of a recombination event. After some fine-tuning, we have applied it to sequence data in several human populations and have found that recombination events recapitulate the history of these populations. This opens the possibility of adding recombination to the current allele-based analysis of population structure and history. Our method also provides a tool for the genomic analysis of recombination, both because it pinpoints recombination events rather than just estimating recombination rates, and because, being biased towards more recent events, it can offer a glimpse of the fast evolution of recombination.