Analysis of fine-scale mammalian evolutionary breakpoints provides new insight into their relation to genome organisation

Abstract

Background: The Intergenic Breakage Model, which is the current model of structural genome evolution, considers that evolutionary rearrangement breakages happen with a uniform propensity along the genome but are selected against in genes, their regulatory regions and in-between. However, a growing body of evidence shows that there exists regions along mammalian genomes that present a high susceptibility to breakage. We reconsidered this question taking advantage of a recently published methodology for the precise detection of rearrangement breakpoints based on pairwise genome comparisons.

Results: We applied this methodology between the genome of human and those of five sequenced eutherian mammals which allowed us to delineate evolutionary breakpoint regions along the human genome with a finer resolution (median size 26.6 kb) than obtained before. We investigated the distribution of these breakpoints with respect to genome organisation into domains of different activity. In agreement with the Intergenic Breakage Model, we observed that breakpoints are under-represented in genes. Surprisingly however, the density of breakpoints in small intergenes (1 per Mb) appears significantly higher than in gene deserts (0.1 per Mb).More generally, we found a heterogeneous distribution of breakpoints that follows the organisation of the genome into isochores (breakpoints are more frequent in GC-rich regions). We then discuss the hypothesis that regions with an enhanced susceptibility to breakage correspond to regions of high transcriptional activity and replication initiation.

Conclusion: We propose a model to describe the heterogeneous distribution of evolutionary breakpoints along human chromosomes that combines natural selection and a mutational bias linked to local open chromatin state.

Figure 1

Breakpoint region size distribution. Histogram of BPR sizes (in kb) computed within classes of size 100 kb. (Inset) Same histogram limited to BPRs of size ≤ 100 kb computed in 10 kb classes; the vertical dashed line corresponds to the median BPR size (26.6 kb).

Figure 2

Small intergenes present a high breakpoint density. Intergenic breakpoint density (filled triangle, point up) estimated using model M1 versus intergene size. Mean intergenic breakpoint density (small filled triangle, point down) obtained as the average over 1000 simulated BPR data sets with randomised positions. Data points were obtained by (i) ordering intergenes according to their size, (ii) grouping them into classes of equal number of intergenic breakpoints and (iii) computing intergenic breakpoint density and average intergene size over each class. Vertical bars represent the standard deviations (see Methods); horizontal bars represent the ranges of intergene sizes over each class. The solid line corresponds to an exponential fit of the intergenic breakpoint density curve of equation: d = 0.063 + 0.92 exp(-L/165 kb) Mb^-1.

Figure 3

Breakpoint density is higher in heavy isochors. Intergenic breakpoint density estimated using model M1 versus GC content. Data points were obtained by (i) ordering 50 kb windows according to their GC content, (ii) grouping them into classes of equal number of intergenic breakpoints and (iii) computing intergenic breakpoint density and average GC content over each class. Vertical bars represent the standard deviations (see Methods); horizontal bars represent the ranges of GC content over each class.

Figure 4

Breakpoint density and small intergene coverage decrease with distance to putative replication origins. (a) (open triangle, point up) Intergenic breakpoint density estimated using model M1 of the BPR data set versus the genomic distance to the closest putative origin located in the replication N-domains. (small open triangle, point down) Estimated intergenic breakpoint density in 100 kb windows along replication N-domains versus the distance to the closest ORI assuming that breakpoint density solely depends on the intergene size according to the fit of the breakpoint density versus intergenic size presented in Figure 2. Bars as in Figure 2. (b) Coverage of small intergenes (L ≤ 150 kb) in 50 kb windows along replication N-domains versus the genomic distance to the closest putative replication origin. Small intergene coverage corresponds to the proportion of the sequence covered by a small intergene within the window of interest.

Figure 5

Open chromatin regions present a high breakpoint density. Intergenic breakpoint density estimated using model M1 versus (a) CpG ratio and (b) coverage by DNase I hypersensitive sites. Data points were obtained by (i) ordering 50 kb windows according to their CpG ratio (resp. Dnase I HS sites coverage), (ii) grouping them into classes of equal number of intergenic breakpoints and (iii) computing intergenic breakpoint density and average CpG ratio (resp. Dnase I HS sites coverage) over each class. Vertical bars represent the standard deviations (see Methods); horizontal bars represent the ranges of CpG ratio (resp. Dnase I HS sites coverage) over each class.