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Genetic crossovers are predicted accurately by the computed human recombination map.

Khil PP, Camerini-Otero RD - PLoS Genet. (2010)

Bottom Line: This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers.To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees.An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations.

View Article: PubMed Central - PubMed

Affiliation: Genetics and Biochemistry Branch, The National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.

ABSTRACT
Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers.

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Related in: MedlinePlus

The population averaged map is much closer to the distribution of meiotic crossovers than the CEU map.We calculated and plotted cumulative recombination frequency graphs for CEPH (A) and Hutterite (B) crossovers and the cumulative recombination frequency graphs for crossovers re-distributed according to the population-averaged or CEU maps.
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pgen-1000831-g003: The population averaged map is much closer to the distribution of meiotic crossovers than the CEU map.We calculated and plotted cumulative recombination frequency graphs for CEPH (A) and Hutterite (B) crossovers and the cumulative recombination frequency graphs for crossovers re-distributed according to the population-averaged or CEU maps.

Mentions: Compared to the analysis presented on Figure 1 where all of the hotspots were combined, the cumulative recombination frequency graphs reflect the relative activity of hotspots of different strengths. To better estimate how close the computed recombination rate maps are to the observed distribution of crossovers we compared the observed cumulative recombination frequency graphs with those obtained by computer simulation (Figure 3, Figure S11). Here we again clearly see that the crossover distribution both in CEPH and Hutterite datasets resembles the population-averaged map better than the CEU map. We must note, however, that the observed distribution of crossovers is not identical to that of either the CEU or the population-averaged map. For most subsets of crossovers hotspots predict more crossover intervals than expected from the population-averaged map. This suggests that the population-averaged map slightly underestimates the strength of hotspots and the peak rate inside them. For the CEU map we see exactly the opposite effect — hotspots predict less crossovers than expected. This means that the CEU map tends to overestimate the strength of some hotspots and that the actual distribution of crossovers is less concentrated in hotspots compared to what would be expected from the CEU map.


Genetic crossovers are predicted accurately by the computed human recombination map.

Khil PP, Camerini-Otero RD - PLoS Genet. (2010)

The population averaged map is much closer to the distribution of meiotic crossovers than the CEU map.We calculated and plotted cumulative recombination frequency graphs for CEPH (A) and Hutterite (B) crossovers and the cumulative recombination frequency graphs for crossovers re-distributed according to the population-averaged or CEU maps.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2813264&req=5

pgen-1000831-g003: The population averaged map is much closer to the distribution of meiotic crossovers than the CEU map.We calculated and plotted cumulative recombination frequency graphs for CEPH (A) and Hutterite (B) crossovers and the cumulative recombination frequency graphs for crossovers re-distributed according to the population-averaged or CEU maps.
Mentions: Compared to the analysis presented on Figure 1 where all of the hotspots were combined, the cumulative recombination frequency graphs reflect the relative activity of hotspots of different strengths. To better estimate how close the computed recombination rate maps are to the observed distribution of crossovers we compared the observed cumulative recombination frequency graphs with those obtained by computer simulation (Figure 3, Figure S11). Here we again clearly see that the crossover distribution both in CEPH and Hutterite datasets resembles the population-averaged map better than the CEU map. We must note, however, that the observed distribution of crossovers is not identical to that of either the CEU or the population-averaged map. For most subsets of crossovers hotspots predict more crossover intervals than expected from the population-averaged map. This suggests that the population-averaged map slightly underestimates the strength of hotspots and the peak rate inside them. For the CEU map we see exactly the opposite effect — hotspots predict less crossovers than expected. This means that the CEU map tends to overestimate the strength of some hotspots and that the actual distribution of crossovers is less concentrated in hotspots compared to what would be expected from the CEU map.

Bottom Line: This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers.To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees.An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations.

View Article: PubMed Central - PubMed

Affiliation: Genetics and Biochemistry Branch, The National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.

ABSTRACT
Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers.

Show MeSH
Related in: MedlinePlus