10.5061/DRYAD.BQ3FN37
Crombie, Timothy A.
University of Florida
Northwestern University
Saber, Sayran
University of Florida
Saxena, Ayush Shekhar
University of Florida
Egan, Robyn
University of Florida
Baer, Charles F.
University of Florida
Data from: Head-to-head comparison of three experimental methods of
quantifying competitive fitness in C. elegans
Dryad
dataset
2018
Caenorhabditis elegans
biosorter
competitive fitness
CellProfiler
large-particle flow cytometer
Holocene
2018-11-07T12:55:25Z
2018-11-07T12:55:25Z
en
https://doi.org/10.1371/journal.pone.0201507
321270 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Organismal fitness is relevant in many contexts in biology. The most
meaningful experimental measure of fitness is competitive fitness, when
two or more entities (e.g., genotypes) are allowed to compete directly. In
theory, competitive fitness is simple to measure: an experimental
population is initiated with the different types in known proportions and
allowed to evolve under experimental conditions to a predefined endpoint.
In practice, there are several obstacles to obtaining robust estimates of
competitive fitness in multicellular organisms, the most pervasive of
which is simply the time it takes to count many individuals of different
types from many replicate populations. Methods by which counting can be
automated in high throughput are desirable, but for automated methods to
be useful, the bias and technical variance associated with the method must
be (a) known, and (b) sufficiently small relative to other sources of bias
and variance to make the effort worthwhile. The nematode Caenorhabditis
elegans is an important model organism, and the fitness effects of
genotype and environmental conditions are often of interest. We report a
comparison of three experimental methods of quantifying competitive
fitness, in which wild-type strains are competed against GFP-marked
competitors under standard laboratory conditions. Population samples were
split into three replicates and counted (1) "by eye" from a
saved image, (2) from the same image using CellProfiler image analysis
software, and (3) with a large particle flow cytometer (a "worm
sorter"). From 720 replicate samples, neither the frequency of
wild-type worms nor the among-sample variance differed significantly
between the three methods. CellProfiler and the worm sorter provide at
least a tenfold increase in sample handling speed with little (if any)
bias or increase in variance.
Suppl Table S2_dataAll count data
North America