Evidence map›Paper›PMID 28046117›Full record

ArticlePLoS genetics2017

Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum.

Yuan O Zhu, Gavin Sherlock, Dmitri A Petrov

Abstract read
In one paragraph

Article in PLoS genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

3 authors.

Yuan O ZhuDepartment of Genetics, Stanford University, Stanford, CA, United States of America.
Gavin SherlockDepartment of Genetics, Stanford University, Stanford, CA, United States of America.ORCID http://orcid.org/0000-0002-1692-4983
Dmitri A PetrovDepartment of Biology, Stanford University, Stanford, CA, United States of America.

Funding

Genomics of rapid adaptation in the lab and in the wildR35GM118165 · NIGMS · STANFORD UNIVERSITY · PI Dmitri Petrov · 2016 to 2026
$8.3M
Molecular Characterization of Adaptive EvolutionR01HG003328 · NHGRI · STANFORD UNIVERSITY · PI SHERLOCK, GAVIN J · 2005 to 2015
$4.1M
Genomics of rapid adaptation on seasonal timescales in D. melanogasterR01GM100366 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI SCHMIDT, PAUL · 2012 to 2019
$3.3M
Sequencing yeast lines to measure rates of neutral and deleterious mutationsR01GM097415 · NIGMS · NEW YORK UNIVERSITY · PI PETROV, DMITRI, SIEGAL, MARK L · 2011 to 2014
$2.3M
High-resolution study of adaptation in haploid and diploid populations of yeastR01GM115919 · NIGMS · STANFORD UNIVERSITY · PI PETROV, DMITRI · 2015 to 2015
$312k
NHGRI NIH HHS R01 HG003328NIGMS NIH HHS R01 GM097415NIGMS NIH HHS R01 GM100366NIGMS NIH HHS R01 GM115919NIGMS NIH HHS R35 GM118165
6 · The paper itself

Abstract

The characterization of mutational spectra is usually carried out in one of three ways-by direct observation through mutation accumulation (MA) experiments, through parent-offspring sequencing, or by indirect inference from sequence data. Direct observations of spontaneous mutations with MA experiments are limited, given (i) the rarity of spontaneous mutations, (ii) applicability only to laboratory model species with short generation times, and (iii) the possibility that mutational spectra under lab conditions might be different from those observed in nature. Trio sequencing is an elegant solution, but it is not applicable in all organisms. Indirect inference, usually from divergence data, faces no such technical limitations, but rely upon critical assumptions regarding the strength of natural selection that are likely to be violated. Ideally, new mutational events would be directly observed before the biased filter of selection, and without the technical limitations common to lab experiments. One approach is to identify very young mutations from population sequencing data. Here we do so by leveraging two characteristics common to all new mutations-new mutations are necessarily rare in the population, and absent in the genomes of immediate relatives. From 132 clinical yeast strains, we were able to identify 1,425 putatively new mutations and show that they exhibit extremely low signatures of selection, as well as display a mutational spectrum that is similar to that identified by a large scale MA experiment. We verify that population sequencing data are a potential wealth of information for inferring mutational spectra, and should be considered for analysis where MA experiments are infeasible or especially tedious.

Indexed as

Mutation RatePolymorphism, Single NucleotideGenome, FungalModels, GeneticMutationSaccharomyces cerevisiae

Identifiers

PMID28046117
PMCPMC5207638

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.