Fraction of Informative Recombinations: A Heuristic Approach to Analyze Recombination Rates

Abstract

In this article we present a new heuristic approach (informative recombinations, InfRec) to analyze recombination density at the sequence level. InfRec is intuitive and easy and combines previously developed methods that (i) resolve genotypes into haplotypes, (ii) estimate the minimum number of recombinations, and (iii) evaluate the fraction of informative recombinations. We tested this approach in its sliding-window version on 117 genes from the SeattleSNPs program, resequenced in 24 AfricanAmericans (AAs) and 23 European-Americans (EAs). We obtained population recombination rate estimates (r obs ) of 0.85 and 0.37 kb À1 in AAs and EAs, respectively. Coalescence simulations indicated that these values account for both the recombinations and the gene conversions in the history of the sample. The intensity of r obs varied considerably along the sequence, revealing the presence of recombination hotspots. Overall, we observed $80% of recombinations in one-third and $50% in only 10% of the sequence. InfRec performance, tested on published simulated and additional experimental data sets, was similar to that of other hotspot detection methods. Fast, intuitive, and visual, InfRec is not constrained by sample size limitations. It facilitates understanding data and provides a simple and flexible tool to analyze recombination intensity along the sequence.

Female-to-Male Breeding Ratio in Modern Humans—an Analysis Based on Historical Recombinations

“…The estimates of r were obtained with the use of InfRec as previously described. 21 The InfRec procedure relies on the existing The X chromosome to the autosomes effective population size ratio, N eX /N eA ¼ d (red line), and the corresponding population recombination rate ratio, r X /r A (blue line), are plotted as a function of the breeding ratio b ¼ N f /N m . Note that the normalized recombination rate ratio, (r X .r A )/(r A .r X ), is equivalent to r X /r A because in humans r X /r A ¼ 1.…”

“…Windows characterized by a very low FNR (< 0.05) and thus effectively noninformative were discarded and were not included in the final estimate (c.f. 21 for details). Each window's sequence coverage is taken into account to express the recombination rate estimates in units of sequence length, usually per Kb.…”

“…33 To estimate r, we used the InfRec method, a heuristic approach described previously. 21 We obtained estimates of r X , r A , and b for three HapMap populations: Yorubans from Nigeria, Western Europeans, and East Asians ( Table 1). Consistent estimates of b were obtained at different sizes of the sliding window (Table S1).…”

“…To evaluate b, we compared the autosomal population recombination rate to that of the X chromosome, estimated in three HapMap population samples 14,15 by the InfRec program. 21 Importantly, our estimates of b do not require the knowledge of a and rely only on independently evaluated, average chromosomal recombination rates estimated from the pedigree studies. 18,19 Using both experimental and simulated data sets, we have previously shown that InfRec is a reliable tool for capturing fluctuations in recombination intensity due to recombination hotspots and is able to reveal overall differences in recombination rates and to faithfully capture quantitative differences between population samples.…”

“…18,19 Using both experimental and simulated data sets, we have previously shown that InfRec is a reliable tool for capturing fluctuations in recombination intensity due to recombination hotspots and is able to reveal overall differences in recombination rates and to faithfully capture quantitative differences between population samples. 21 InfRec estimates rely on the RecMin's R min values, which underestimate the number of historical recombinations. The extent to which InfRec underestimates the intrinsic population recombination rate can be tested through simulation experiments.…”