Evidence map›Paper›PMID 30753705›Full record

ArticleMolecular biology and evolution2019

Signals of Variation in Human Mutation Rate at Multiple Levels of Sequence Context.

Rachael C Aikens, Kelsey E Johnson, Benjamin F Voight

Abstract readComparative Study
In one paragraph

Article in Molecular biology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
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  3. "Evolution of the mutation spectrum across a mammalian phylogeny".bioRxiv : the preprint server for biology · 2023
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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

3 authors.

Rachael C AikensProgram in Biomedical Informatics, Stanford University School of Medicine, Stanford University, Stanford, CA.
Kelsey E JohnsonGenetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Benjamin F VoightDepartment of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.

Funding

PREDOCTORAL TRAINING PROGRAM IN GENETICST32GM008216 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI EPSTEIN, DOUGLAS J · 1987 to 2023
$8.3M
Algorithms to identify non-coding mutational burden and disease-relevant pathwaysR01DK101478 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI VOIGHT, BENJAMIN FRANKLIN · 2014 to 2018
$2.9M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
NIDDK NIH HHS R01 DK101478NIGMS NIH HHS T32 GM008216NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

Our understanding of the human mutation rate helps us build evolutionary models and interpret patterns of genetic variation observed in human populations. Recent work indicates that the frequencies of specific polymorphism types have been elevated in Europe, and that many more, subtler signatures of global polymorphism variation may yet remain unidentified. Here, we present an analysis of the 1000 Genomes Project supported by analysis in the Simons Genome Diversity Panel, suggesting additional putative signatures of mutation rate variation across populations and the extent to which they are shaped by local sequence context. First, we compiled a list of the most significantly variable polymorphism types in a cross-continental statistical test. Clustering polymorphisms together, we observe three sets that showed distinct shared patterns of relative enrichment among ancestral populations, and we characterize each one of these putative "signatures" of polymorphism variation. For three of these signatures, we found that a single flanking base pair of sequence context was sufficient to determine the majority of enrichment or depletion of a polymorphism type. However, local genetic context up to 2-3 bp away contributes additional variability and may help to interpret a previously noted enrichment of certain polymorphism types in some East Asian groups. Moreover, considering broader local genetic context highlights patterns of polymorphism variation, which were not captured by previous approaches. Building our understanding of mutation rate in this way can help us to construct more accurate evolutionary models and better understand the mechanisms that underlie genetic change.

Indexed as

Genome, HumanMutation RatePolymorphism, GeneticGene FrequencyHumansmutation ratesequence context modelsstatistical genetics

Identifiers

PMID30753705
PMCPMC6501879

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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.