SNP microarray analysis for genome-wide detection of crossover regions

There is a great deal of interest in understanding the non-random distribution of recombination events over the human genome, because it has important implications for using linkage disequilibrium (LD) to identify human disease genes. So far, only a few recombination hotspots in the human genome have been characterised and the identification of new crossover hotspots will contribute to a better understanding of the mechanisms that govern their formation and distribution. This study shows that high-density single nucleotide polymorphism (SNP) arrays, together with the presented analysis method, are an appropriate tool for generating a whole-genome recombination pattern and for detecting new crossover regions with enhanced recombination frequency. Based on the genotype data of 16 members of a Caucasian three-generation family, we identified 825 crossover regions. The average recombination frequency of females and males was 0.77 and 0.56 cM/Mb, respectively. We detected 24 crossover regions showing elevated recombination activity, which comprised known hotspots, like the MHC II region, confirming the non-random distribution of recombination events along the genome. Interestingly, 29.2% of the identified crossover hotspot regions overlapped with regions flanked by segmental duplications published by Bailey et al. (Science 297:1003-1007, 2002) suggesting that segmental duplications and crossover hotspot regions are mechanistically linked. By extrapolating the results of the present study, we conclude that it might be feasible, at least in part, to estimate to what extent the block-like pattern of LD exactly relies on the genome-wide crossover pattern using the next generation high-density SNP microarrays.