Evidence map›Paper›PMID 31515531›Full record

ArticleHeredity2020

The fitness cost of mismatch repair mutators in Saccharomyces cerevisiae: partitioning the mutational load.

Benjamin Galeota-Sprung, Breanna Guindon, Paul Sniegowski

Abstract read
In one paragraph

Article in Heredity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Benjamin Galeota-SprungUniversity of Pennsylvania, Philadelphia, PA, USA. bsprung@gmail.com.
Breanna GuindonUniversity of Pennsylvania, Philadelphia, PA, USA.
Paul SniegowskiUniversity of Pennsylvania, Philadelphia, PA, USA.

Funding

Intramural NASA NNA17BB05A
6 · The paper itself

Abstract

Mutational load is the depression in a population's mean fitness that results from the continual influx of deleterious mutations. Here, we directly estimate the mutational load in a population of haploid Saccharomyces cerevisiae that are deficient for mismatch repair. We partition the load in haploids into two components. To estimate the load due to nonlethal mutations, we measure the competitive fitness of hundreds of randomly selected clones from both mismatch-repair-deficient and -proficient populations. Computation of the mean clone fitness for the mismatch-repair-deficient strain permits an estimation of the nonlethal load, and the histogram of fitness provides an interesting visualization of a loaded population. In a separate experiment, in order to estimate the load due to lethal mutations (i.e. the lethal mutation rate), we manipulate thousands of individual pairs of mother and daughter cells and track their fates. These two approaches yield point estimates for the two contributors to load, and the addition of these estimates is nearly equal to the separately measured short-term competitive fitness deficit for the mismatch-repair-deficient strain. This correspondence suggests that there is no need to invoke direct fitness effects to explain the fitness difference between mismatch-repair-deficient and -proficient strains. Assays in diploids are consistent with deleterious mutations in diploids tending towards recessivity. These results enhance our understanding of mutational load, a central population genetics concept, and we discuss their implications for the evolution of mutation rates.

Indexed as

DNA Mismatch RepairGenetics, PopulationMutationDiploidyGenetic FitnessHaploidyMutation RateSaccharomyces cerevisiae

Identifiers

PMID31515531
PMCPMC6906417

What OpenQuestion holds

Textmetadata
LicenceTDM
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.