1. Experimental Protocol
Differences in mutation accumulation in Schyzosaccharomyces pombe due
to the presence of chromosomal rearrangements
Gustavo Eduardo, Simone Delgado, Ana Paula Marques, Lília Perfeito
Evolution and Genome Structure Group – Instituto Gulbenkian de Ciência, Rua da Quinta Grande, 6, Oeiras, Portugal
Large chromosomal rearrangements are common in natural populations and thought to be involved
in speciation events. In this project, we used experimental evolution to determine how the speed of
evolution and the type of accumulated mutations depend on the ancestral chromosomal structure
and genotype. We utilized two Wild Type strains and a set of genetically engineered
Schizosaccharomyces pombe strains (Avelar, 2012), different solely in the presence of a certain
type of chromosomal variant (one inversion and four translocations), along with respective controls.
These strains were propagated in the laboratory at very low population sizes, in which we expect
natural selection to be less efficient at purging deleterious mutations (Gordo et al, 2011). We then
measured these strains’ changes in fitness throughout this accumulation of deleterious mutations,
comparing the evolutionary trajectories in the different rearrangements to test if the chromosomal
structure affected the speed of evolution.
Our data indicates that different genetic backgrounds accumulate mutations at different rates, even
when natural selection is very weak. Certain chromosomal rearrangements bias the accumulation of
mutations towards beneficial mutations, conferring the strain that carries them an adaptive
advantage.
Results
Conclusions
• The genomic background affects it’s potential evolutionary path, even when minimizing environmental
and natural selection effects.
• Surprisingly, all T4 replicates and some replicates of C2 and C5 presented increases in fitness.
• Is there selection even at low population sizes?
• Could one of the strains be exceptionally prone to high effect beneficial mutations?
Bibliography/Reference
Avelar A; Chromosomal structure: a selectable trait for evolution. Instituto de Tecnologia Química e Biológica, Oeiras,
November 2012
Gordo I, Perfeito L, Sousa A; Fitness Effects of Mutations in Bacteria. J Mol Microbiol Biotechnol 2011;21:20–35
Acknowledgments
Funding for this project was provided by
Different strains accumulate mutations at different speeds
EXPL/BIA-EVF/0129/2013
* - significant change in fitness distributions between both bottleneck numbers
Δ - significant change in fitness average.
*/Δ p-value < 0.05; **/Δ Δ p-value < 0.01; ***/Δ Δ Δ p-value < 0.001
(Statistical significance tested with the Kolmogorov-Smirnov and Mann–Whitney–Wilcoxon tests)
mCherry-marked S. pombe
48 hours later
1st Bottleneck (…)
144th Bottleneck
(B144)
Mutation Accumulation Experiment
Statistical analysis
Fluorescence-activated
cell sorting
(FACS)
Rich medium
(1mg/mL ampicillin)
x12 lines
per strain
Plus controls for each rearrangement. Ex:
Ancestral Strains:
2 Wild Type Karyotypes
5 Chromossomal Rearrangents
Reference
Strain
BD LSRFortessa™
cell analyzer
Competition Assay
Results from fitting an Analysis of Variance Model (ANOVA) comparing ∆W (fitness at
B144 subtracted from fitness at B0) of all lines from different genomic backgrounds.
Red indicates p-value < 0.05, yellow indicates 0.01 > p-value > 0.001 and green indicates 0.001 > p-
value. Bonferroni corrections were applied to all p-values.
SPP26 SPP27 I2 C2 T4 C4 T5 C5 T8 C8 T10 C10
SPP26
SPP27 9,8977E-09
I2 5,36628972 2,1E-06
C2 32,176518 6,227178 50,15595
T4 1,5832E-10 3,29E-15 6,99E-10 0,847641
C4 37,8229896 9,15E-10 1,297978 30,13474 1,89E-14
T5 0,15037645 6,15E-07 24,05454 59,73462 8,47E-14 0,00212
C5 13,4667456 0,000323 62,64657 51,60644 3,47E-06 8,015205 39,11081
T8 9,3140652 6,9E-09 26,31535 42,04811 1,53E-14 0,273657 1,073373 35,86171
C8 62,1447156 2,23E-08 5,511067 35,1945 5,8E-12 25,44505 0,069723 15,66261 6,039258
T10 36,8132622 9,9E-09 11,22059 36,34719 6,96E-12 10,89927 0,370212 21,34037 23,6161 37,01266
C10 57,6936096 5,1E-10 2,290222 31,08003 1,84E-14 32,49946 0,006733 10,21945 1,431345 49,90801 22,89706