Evidence map›Paper›PMID 31425500›Full record

ArticlePLoS genetics2019

An estimator of first coalescent time reveals selection on young variants and large heterogeneity in rare allele ages among human populations.

Alexander Platt, Alyssa Pivirotto, Jared Knoblauch, Jody Hey

Abstract readEvaluation Study
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 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

4 authors.

Alexander PlattCenter for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0003-3783-4781
Alyssa PivirottoCenter for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0002-2409-2574
Jared KnoblauchCenter for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America.
Jody HeyCenter for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0001-5358-6488

Funding

The Population Genetics of DivergenceR01GM078204 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI HEY, EMANUEL · 2007 to 2016
$1.7M
Medical Research Council G9815508Medical Research Council MC_PC_19009NIGMS NIH HHS R01 GM078204
6 · The paper itself

Abstract

Allele age has long been a focus of population genetic research, primarily because it can be an important clue to the fitness effects of an allele. By virtue of their effects on fitness, alleles under directional selection are expected to be younger than neutral alleles of the same frequency. We developed a new coalescent-based estimator of a close proxy for allele age, the time when a copy of an allele first shares common ancestry with other chromosomes in a sample not carrying that allele. The estimator performs well, including for the very rarest of alleles that occur just once in a sample, with a bias that is typically negative. The estimator is mostly insensitive to population demography and to factors that can arise in population genomic pipelines, including the statistical phasing of chromosomes. Applications to 1000 Genomes Data and UK10K genome data confirm predictions that singleton alleles that alter proteins are significantly younger than those that do not, with a greater difference in the larger UK10K dataset, as expected. The 1000 Genomes populations varied markedly in their distributions for singleton allele ages, suggesting that these distributions can be used to inform models of demographic history, including recent events that are only revealed by their impacts on the ages of very rare alleles.

Indexed as

Evolution, MolecularGenome, HumanModels, GeneticSelection, GeneticAllelesBiological Variation, PopulationDatasets as TopicFemaleGene FrequencyGenetic HeterogeneityGenetics, PopulationHumansMaleTime Factors

Identifiers

PMID31425500
PMCPMC6715256

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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.