Limits...
The influence of recombination on human genetic diversity.

Spencer CC, Deloukas P, Hunt S, Mullikin J, Myers S, Silverman B, Donnelly P, Bentley D, McVean G - PLoS Genet. (2006)

Bottom Line: In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale.Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition.To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of Oxford, Oxford, United Kingdom.

ABSTRACT
In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale. Despite considerable debate, it is not clear whether these factors are causally linked or, if they are, whether this is driven by the repeated action of adaptive evolution or molecular processes such as double-strand break formation and mismatch repair. We introduce three innovations to the analysis of recombination and diversity: fine-scale genetic maps estimated from genotype experiments that identify recombination hotspots at the kilobase scale, analysis of an entire human chromosome, and the use of wavelet techniques to identify correlations acting at different scales. We show that recombination influences genetic diversity only at the level of recombination hotspots. Hotspots are also associated with local increases in GC content and the relative frequency of GC-increasing mutations but have no effect on substitution rates. Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition. To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations. However, that hotspots have no influence on substitution rates suggests that they are too ephemeral on an evolutionary time scale to have a strong influence on broader scale patterns of base composition and long-term molecular evolution.

Show MeSH

Related in: MedlinePlus

Power Spectra and Pairwise Correlations of Detail Wavelet CoefficientsDiagonal plots show the power spectrum of the wavelet decomposition of each factor on the long (red) and short (blue) arms of Chromosome 20. Off-diagonal plots show the rank correlation coefficient between pairs of detail wavelet coefficients at each scale on the long (top right) and short (bottom left) arms. Red crosses indicate significant correlations (p-value < 0.01; Kendall's rank correlation). Scale is shown in kilobases.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC1575889&req=5

pgen-0020148-g002: Power Spectra and Pairwise Correlations of Detail Wavelet CoefficientsDiagonal plots show the power spectrum of the wavelet decomposition of each factor on the long (red) and short (blue) arms of Chromosome 20. Off-diagonal plots show the rank correlation coefficient between pairs of detail wavelet coefficients at each scale on the long (top right) and short (bottom left) arms. Red crosses indicate significant correlations (p-value < 0.01; Kendall's rank correlation). Scale is shown in kilobases.

Mentions: A useful feature of the wavelet decomposition is that the variance in the original signal is proportional to the sum over all levels of the sum of squares of the detail coefficients at that level. Consequently, the proportions of the total variance explained by heterogeneity at different scales, known as the power spectrum of a signal, can be used to characterise the signal's distribution. Before focusing specifically on recombination and diversity, we first explored the power spectra and pairwise correlations between wavelet coefficients at each scale for all factors (Figure 2). Power spectra for each of the measured features are shown along the diagonal in Figure 2, for the short arm (blue) and the long arm (red). Broadly, we observe three different patterns. For diversity, divergence, and read depth, the greatest source of heterogeneity is at the finest scale (2 kb), and successively broader scales show successively weaker contribution. For GC content, we find a bimodal distribution, with peaks at both very fine scales (2 to 8 kb) and very broad scales (8 to 32 Mb). For recombination and, to a lesser extent, gene content, we find the greatest contribution to heterogeneity is made by intermediate scales; approximately 8 kb in the case of recombination.


The influence of recombination on human genetic diversity.

Spencer CC, Deloukas P, Hunt S, Mullikin J, Myers S, Silverman B, Donnelly P, Bentley D, McVean G - PLoS Genet. (2006)

Power Spectra and Pairwise Correlations of Detail Wavelet CoefficientsDiagonal plots show the power spectrum of the wavelet decomposition of each factor on the long (red) and short (blue) arms of Chromosome 20. Off-diagonal plots show the rank correlation coefficient between pairs of detail wavelet coefficients at each scale on the long (top right) and short (bottom left) arms. Red crosses indicate significant correlations (p-value < 0.01; Kendall's rank correlation). Scale is shown in kilobases.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1575889&req=5

pgen-0020148-g002: Power Spectra and Pairwise Correlations of Detail Wavelet CoefficientsDiagonal plots show the power spectrum of the wavelet decomposition of each factor on the long (red) and short (blue) arms of Chromosome 20. Off-diagonal plots show the rank correlation coefficient between pairs of detail wavelet coefficients at each scale on the long (top right) and short (bottom left) arms. Red crosses indicate significant correlations (p-value < 0.01; Kendall's rank correlation). Scale is shown in kilobases.
Mentions: A useful feature of the wavelet decomposition is that the variance in the original signal is proportional to the sum over all levels of the sum of squares of the detail coefficients at that level. Consequently, the proportions of the total variance explained by heterogeneity at different scales, known as the power spectrum of a signal, can be used to characterise the signal's distribution. Before focusing specifically on recombination and diversity, we first explored the power spectra and pairwise correlations between wavelet coefficients at each scale for all factors (Figure 2). Power spectra for each of the measured features are shown along the diagonal in Figure 2, for the short arm (blue) and the long arm (red). Broadly, we observe three different patterns. For diversity, divergence, and read depth, the greatest source of heterogeneity is at the finest scale (2 kb), and successively broader scales show successively weaker contribution. For GC content, we find a bimodal distribution, with peaks at both very fine scales (2 to 8 kb) and very broad scales (8 to 32 Mb). For recombination and, to a lesser extent, gene content, we find the greatest contribution to heterogeneity is made by intermediate scales; approximately 8 kb in the case of recombination.

Bottom Line: In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale.Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition.To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of Oxford, Oxford, United Kingdom.

ABSTRACT
In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale. Despite considerable debate, it is not clear whether these factors are causally linked or, if they are, whether this is driven by the repeated action of adaptive evolution or molecular processes such as double-strand break formation and mismatch repair. We introduce three innovations to the analysis of recombination and diversity: fine-scale genetic maps estimated from genotype experiments that identify recombination hotspots at the kilobase scale, analysis of an entire human chromosome, and the use of wavelet techniques to identify correlations acting at different scales. We show that recombination influences genetic diversity only at the level of recombination hotspots. Hotspots are also associated with local increases in GC content and the relative frequency of GC-increasing mutations but have no effect on substitution rates. Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition. To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations. However, that hotspots have no influence on substitution rates suggests that they are too ephemeral on an evolutionary time scale to have a strong influence on broader scale patterns of base composition and long-term molecular evolution.

Show MeSH
Related in: MedlinePlus