Evidence map›Paper›PMID 31860654›Full record

ArticlePLoS genetics2019

Crossover interference and sex-specific genetic maps shape identical by descent sharing in close relatives.

Madison Caballero, Daniel N Seidman, Ying Qiao, Jens Sannerud, Thomas D Dyer, Donna M Lehman, Joanne E Curran, Ravindranath Duggirala, John Blangero, Shai Carmi and 1 more

Abstract read
In one paragraph

Article in PLoS genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing 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

56 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Genomes of the Golden Horde elites and their implications for the rulers of the Mongol Empire.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

11 authors.

Madison CaballeroDepartment of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0002-4499-5105
Daniel N SeidmanDepartment of Computational Biology, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0001-9848-9702
Ying QiaoDepartment of Computational Biology, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0002-7175-7129
Jens SannerudDepartment of Computational Biology, Cornell University, Ithaca, New York, United States of America.
Thomas D DyerSouth Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America.ORCID 0000-0002-5809-1190
Donna M LehmanDepartment of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America.ORCID 0000-0001-8547-9927
Joanne E CurranSouth Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America.
Ravindranath DuggiralaSouth Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America.
John BlangeroSouth Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America.ORCID 0000-0001-6250-5723
Shai CarmiBraun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.ORCID 0000-0002-0188-2610
Amy L WilliamsDepartment of Computational Biology, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0003-0737-0533

Funding

PEDIGREE ANALYSIS OF LIPOPROTEIN PHENOTYPESP01HL045522 · NHLBI · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI DYER, THOMAS DAVID · 1991 to 2012
$27.6M
Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD RiskR01HL113323 · NHLBI · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI BLANGERO, JOHN, CURRAN, JOANNE E. · 2012 to 2016
$8.2M
PREDOCTORAL TRAINING IN GENETICS AND DEVELOPMENTT32GM007617 · NIGMS · CORNELL UNIVERSITY ITHACA · PI BARBASH, DANIEL A · 1985 to 2021
$5.5M
NIDDM SUSCEPTIBILITY GENES IN MEXICAN-AMERICANSR01DK047482 · NIDDK · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI LEHMAN, DONNA M · 1993 to 2010
$5.4M
Construction of a Biomedical Research Facility at the U*C06RR020547 · NCRR · UNIV/TEXAS BROWNSVILLE & SOUTHMOST COLL · PI KROUSE, JOHN H · 2010 to 2010
$4.0M
Tri-Institutional Training Program in Computational Biology & MedicineT32GM083937 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHRISTINI, DAVID J. · 2009 to 2018
$3.1M
GENETICS OF GALLBLADDER DISEASE IN MEXICAN AMERICANSR01DK053889 · NIDDK · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI DUGGIRALA, RAVINDRANATH · 1998 to 2011
$2.3M
Scalable methods for the characterization and analysis of families in large genomic datasetsR35GM133805 · NIGMS · CORNELL UNIVERSITY · PI WILLIAMS, AMY LYNNE · 2019 to 2023
$1.6M
NCRR NIH HHS C06 RR020547NHLBI NIH HHS P01 HL045522NHLBI NIH HHS R01 HL113323NIDDK NIH HHS R01 DK047482NIDDK NIH HHS R01 DK053889NIGMS NIH HHS R35 GM133805NIGMS NIH HHS T32 GM007617NIGMS NIH HHS T32 GM083937Wellcome TrustWellcome Trust 076113Wellcome Trust 085475Wellcome Trust 090355
6 · The paper itself

Abstract

Simulations of close relatives and identical by descent (IBD) segments are common in genetic studies, yet most past efforts have utilized sex averaged genetic maps and ignored crossover interference, thus omitting features known to affect the breakpoints of IBD segments. We developed Ped-sim, a method for simulating relatives that can utilize either sex-specific or sex averaged genetic maps and also either a model of crossover interference or the traditional Poisson model for inter-crossover distances. To characterize the impact of previously ignored mechanisms, we simulated data for all four combinations of these factors. We found that modeling crossover interference decreases the standard deviation of pairwise IBD proportions by 10.4% on average in full siblings through second cousins. By contrast, sex-specific maps increase this standard deviation by 4.2% on average, and also impact the number of segments relatives share. Most notably, using sex-specific maps, the number of segments half-siblings share is bimodal; and when combined with interference modeling, the probability that sixth cousins have non-zero IBD sharing ranges from 9.0 to 13.1%, depending on the sexes of the individuals through which they are related. We present new analytical results for the distributions of IBD segments under these models and show they match results from simulations. Finally, we compared IBD sharing rates between simulated and real relatives and find that the combination of sex-specific maps and interference modeling most accurately captures IBD rates in real data. Ped-sim is open source and available from https://github.com/williamslab/ped-sim.

Indexed as

Computer SimulationSex CharacteristicsChromosome MappingFemaleGenetics, PopulationGenetic VariationGenome, HumanHumansMaleModels, GeneticPedigreePoisson Distribution

Identifiers

PMID31860654
PMCPMC6944377

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.