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Measuring Selection Coefficients Below 10−3: Method, Questions, and Prospects

Overview of attention for article published in Genetics, January 2012
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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129 Mendeley
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Article details
Title
Measuring Selection Coefficients Below 10−3: Method, Questions, and Prospects
Published in
Genetics, January 2012
DOI 10.1534/genetics.111.133454
Pubmed ID
Authors
Abstract

Measuring fitness with precision is a key issue in evolutionary biology, particularly in studying mutations of small effects. It is usually thought that sampling error and drift prevent precise measurement of very small fitness effects. We circumvented these limits by using a new combined approach to measuring and analyzing fitness. We estimated the mutational fitness effect (MFE) of three independent mini-Tn10 transposon insertion mutations by conducting competition experiments in large populations of Escherichia coli under controlled laboratory conditions. Using flow cytometry to assess genotype frequencies from very large samples alleviated the problem of sampling error, while the effect of drift was controlled by using large populations and massive replication of fitness measures. Furthermore, with a set of four competition experiments between ancestral and mutant genotypes, we were able to decompose fitness measures into four estimated parameters that account for fitness effects of our fluorescent marker (α), the mutation (β), epistasis between the mutation and the marker (γ), and departure from transitivity (τ). Our method allowed us to estimate mean selection coefficients to a precision of 2 × 10(-4). We also found small, but significant, epistatic interactions between the allelic effects of mutations and markers and confirmed that fitness effects were transitive in most cases. Unexpectedly, we also detected variation in measures of s that were significantly bigger than expected due to drift alone, indicating the existence of cryptic variation, even in fully controlled experiments. Overall our results indicate that selection coefficients are best understood as being distributed, representing a limit on the precision with which selection can be measured, even under controlled laboratory conditions.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 2%
United Kingdom 2 2%
Portugal 1 <1%
Israel 1 <1%
Greece 1 <1%
Switzerland 1 <1%
Belgium 1 <1%
Unknown 120 93%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 35 27%
Researcher 30 23%
Student > Master 11 9%
Student > Postgraduate 9 7%
Student > Bachelor 8 6%
Other 21 16%
Unknown 15 12%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 76 59%
Biochemistry, Genetics and Molecular Biology 19 15%
Immunology and Microbiology 5 4%
Physics and Astronomy 3 2%
Medicine and Dentistry 3 2%
Other 7 5%
Unknown 16 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 October 2025.
All research outputs
#11,885,876
of 34,357,901 outputs
Outputs from Genetics
#4,378
of 9,089 outputs
Outputs of similar age
#96,909
of 304,632 outputs
Outputs of similar age from Genetics
#25
of 55 outputs
Altmetric has tracked 34,357,901 research outputs across all sources so far. This one has received more attention than most of these and is in the 64th percentile.
So far Altmetric has tracked 9,089 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 304,632 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.