Next we used the SCHEMA-based method [8] to investigate whether or not this breakpoint distribution exhibits evidence of purifying selection acting on recombinants with disrupted protein folding. This analysis indicated that breakpoints observable in natural viruses tend to occur in regions within env that were predicted to have a significantly lower impact on protein folding than randomly placed breakpoints (p,1.0610 24 for gp120 and p = 8.9610 23 for gp41, see Protocol S1). To investigate whether accounting for variations in the functionality of recombinants might reconcile the natural and experimental breakpoint distributions, we first approximated the combined effects of mechanistic recombination rate variation ( Figure 2B ) and selection for fully functional recombinants ( Figure 3 ) on the distribution of breakpoints in cell culture. Selection ''corrected'' recombination rate estimates were then used to determine the distribution of 133 expected breakpoints. The resulting distribution was used to evaluate the probability of clustering of breakpoints (green graph in Figure 5A ). Only regions 1, 4, 5 and 6 remained areas of significant clustering (light-green boxes at the bottom of Figure 5A ), a pattern very close to that found in HIV recombinants sampled from nature, with the exception of region 4 for which there was substantially less evidence of recombination within natural recombinants than was expected based on our empirical model. Indeed, when compared to the Recombinants 115A/126D, 115A/89D, 120A/89D, and 126D/120A were described previously [33] . The number (n) of individual recombinants for which the position of the breakpoint has been mapped is given on the right of each graph. A map of gp120 and gp41 domains is given as a frame of reference at the top of the figure. (B) top graph: pooled distribution of recombination breakpoints across env, obtained as described in Materials and Methods. Bottom graph: the height of the black plot at any particular position represents the probability (determined by a permutation test with 10,000 iterations) that recombination breakpoint distributions are not more clustered than would be expected by chance within a 50 nucleotides window centred on that position. Assuming that breakpoints are randomly distributed, the dark and light grey regions represent degrees of breakpoint clustering expected due to chance in 95% and 99% of the examined windows, respectively. Whereas peaks emerging above the grey regions represent possible recombination hot-spots, troughs dipping below the grey regions represent possible recombination cold-spots. The paleblue shaded areas numbered from 1 to 6 correspond to breakpoint clusters, or hot regions, as defined in the text. doi:10.1371/journal.ppat.1000418.g002