Evidence map›Paper›PMID 20126534›Full record

ArticlePLoS genetics2010

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

Pavel P Khil, R Daniel Camerini-Otero

Abstract read
In one paragraph

Article in PLoS genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Meiotic chromosome dynamics and double strand break formation in reptiles.Frontiers in cell and developmental biology · 2022
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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  11. Review
  12. Article
  13. Isolation of meiotic recombinants from mouse sperm.Methods in molecular biology (Clifton, N.J.) · 2011
    Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Pavel P KhilGenetics and Biochemistry Branch, The National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
R Daniel Camerini-Otero

Funding

What determines the location of meiotic crossovers in the mammalian genome?ZIADK052034 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI CAMERINI-OTERO, RAFAEL · 2009 to 2025
$29.8M
Intramural NIH HHS
6 · The paper itself

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.

Indexed as

Computational BiologyCrossing Over, GeneticGenome, HumanComputer SimulationFemaleHumansLinkage DisequilibriumMaleMeiosisModels, GeneticPedigree

Identifiers

PMID20126534
PMCPMC2813264

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.