The impact of recombination on nucleotide substitutions in the human genome

Abstract

Unraveling the evolutionary forces responsible for variations of neutral substitution patterns among taxa or along genomes is a major issue for detecting selection within sequences. Mammalian genomes show large-scale regional variations of GC-content (the isochores), but the substitution processes at the origin of this structure are poorly understood. We analyzed the pattern of neutral substitutions in 1 Gb of primate non-coding regions. We show that the GC-content toward which sequences are evolving is strongly negatively correlated to the distance to telomeres and positively correlated to the rate of crossovers (R2 = 47%). This demonstrates that recombination has a major impact on substitution patterns in human, driving the evolution of GC-content. The evolution of GC-content correlates much more strongly with male than with female crossover rate, which rules out selectionist models for the evolution of isochores. This effect of recombination is most probably a consequence of the neutral process of biased gene conversion (BGC) occurring within recombination hotspots. We show that the predictions of this model fit very well with the observed substitution patterns in the human genome. This model notably explains the positive correlation between substitution rate and recombination rate. Theoretical calculations indicate that variations in population size or density in recombination hotspots can have a very strong impact on the evolution of base composition. Furthermore, recombination hotspots can create strong substitution hotspots. This molecular drive affects both coding and non-coding regions. We therefore conclude that along with mutation, selection and drift, BGC is one of the major factors driving genome evolution. Our results also shed light on variations in the rate of crossover relative to non-crossover events, along chromosomes and according to sex, and also on the conservation of hotspot density between human and chimp.

Figure 1. Correlations between the stationary GC-content (GC*), the current GC content and the crossover rate in human autosomes.

Each dot corresponds to a 1 Mb-long genomic region. (A) GC* vs. current GC-content. The dashed line indicates the slope 1. (B) GC* vs. crossover rate (HAPMAP). Green dots correspond to the predictions of the BGC model (model M1, N = 10,000) (C) Current GC-content vs. crossover rate. Regression lines and Pearson's correlation R² are indicated.

Figure 2. Correlations between the stationary GC-content (GC*), the current GC content and the distance to telomeres in human autosomes.

Each dot corresponds to a 1 Mb-long genomic region. (A) GC* vs. LDT (Log distance to telomere in bp). (B) Current GC-content vs. LDT. Regression lines and Pearson's correlation R² are indicated.

Figure 3. Correlations between substitution rates and the current GC content in human autosomes.

Each dot corresponds to a 1 Mb-long genomic region. Substitution rates: number of substitutions per site in the human lineage since the divergence from chimpanzee. (A) Total substitution rate. (B–D) Base-specific substitution rates: (B) CpG G:C→A:T transition rate. (C) non-CpG S→W and W→W substitution rates. (D) W→S and S→S substitution rates. Regression lines and Pearson's correlation R² are indicated.

Figure 4. Correlations between substitution rates and crossover rate in human autosomes.

Each dot corresponds to a 1 Mb-long genomic region. Substitution rates: number of substitutions per site in the human lineage since the divergence from chimpanzee. (A) Total substitution rate. (B–D) Base-specific substitution rates: (B) CpG G:C→A:T transition rate. (C) non-CpG S→W and W→W substitution rates. (D) W→S and S→S substitution rates. Regression lines and Pearson's correlation R² are indicated.

Figure 5. Predictions of the BGC model and comparison with observed data in human autosomes.

(A) Predicted GC* vs. crossover rate for different parameters of the BGC model (M1 or M2 (see text)) and different effective population sizes (N). (B–D) Correlations between base-specific substitution rates and crossover rates in human autosomes (1 Mb windows). Blue and red dots: observed data. Black dots: predictions of the BGC model (Model M1, N = 10,000).