"Clonal heterogeneity influences the fate of new adaptive mutations"
Ignacio Vázquez-García, Francisco Salinas, Jing Li, Andrej Fischer, Benjamin Barré, Johan Hallin, Anders Bergström, Elisa Alonso-Pérez, Jonas Warringer, Ville Mustonen, Gianni Liti
This IPython notebook is provided for reproduction of Figure 5 of the paper. It can be viewed by copying its URL to nbviewer and it can be run by opening it in binder.
In [1]:
# Load external dependencies
from setup import *
# Load internal dependencies
import config,plot,utils
%load_ext autoreload
%autoreload 2
%matplotlib inline
In [2]:
# Load data
loh_length_df = pd.read_csv(dir_data+'seq/loh/homozygosity_length.csv')
loh_length_df = loh_length_df.set_index("50kb_bin_center")
loh_length_df = loh_length_df.reindex(columns=['HU','RM','YPD'])
loh_length_df.head()
Out[2]:
In [3]:
# Read csv file containing the competition assay data
loh_fluctuation_df = pd.read_csv(dir_data+'fluctuation/fluctuation_assay_rates.csv')
loh_fluctuation_df = loh_fluctuation_df.sort_values('background', ascending=False)
loh_fluctuation_df = loh_fluctuation_df.groupby(['background','environment'],sort=False)[['mean_LOH_rate','lower_LOH_rate','upper_LOH_rate']].mean()
loh_fluctuation_df = loh_fluctuation_df.ix[['WA/WA','NA/NA','WA/NA']].unstack('background')
loh_fluctuation_df = loh_fluctuation_df.ix[['HU','RM','YPD']]
loh_fluctuation_df
Out[3]:
In [4]:
fig = plt.figure(figsize=(4,6))
grid = gridspec.GridSpec(nrows=3, ncols=2, height_ratios=[15, 7, 5], hspace=0.7, wspace=0.3)
gs = {}
gs['length'] = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=grid[0,0])
gs['fluctuation'] = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=grid[0,1])
gs[('loh','WAxNA_F12_1_HU_3')] = gridspec.GridSpecFromSubplotSpec(7, 1, subplot_spec=grid[1:2,:], hspace=0)
gs[('loh','WAxNA_F12_2_RM_1')] = gridspec.GridSpecFromSubplotSpec(5, 1, subplot_spec=grid[2:3,:], hspace=0)
### Left panel ###
ax = plt.subplot(gs['length'][:])
ax.text(-0.185, 1.055, 'A', transform=ax.transAxes,
fontsize=9, fontweight='bold', va='top', ha='right')
data = loh_length_df.rename(columns=config.selection['short_label'])
kwargs = {
'color': [config.selection['color'][e] for e in loh_length_df.columns]
}
plot.loh_length(data, ax, **kwargs)
### Right panel ###
ax = plt.subplot(gs['fluctuation'][:])
ax.text(-0.2, 1.05, 'B', transform=ax.transAxes,
fontsize=9, fontweight='bold', va='top', ha='right')
data = loh_fluctuation_df['mean_LOH_rate']
kwargs = {
'yerr': loh_fluctuation_df[['lower_LOH_rate','upper_LOH_rate']].T.values,
'color': [config.background['color'][b] for b in loh_fluctuation_df['mean_LOH_rate'].columns]
}
plot.loh_fluctuation(data, ax, **kwargs)
# Axes limits
for ax in fig.get_axes():
ax.xaxis.label.set_size(6)
ax.yaxis.label.set_size(6)
ax.tick_params(axis='both', which='major', size=3, labelsize=6)
ax.tick_params(axis='both', which='minor', size=2, labelsize=4)
plot.save_figure(dir_paper+'figures/figure5/figure5')
plt.show()
Fig. 5: Pervasive genome instability. (A) The length distribution of homozygous segments, in bins corresponding to 50-kb increments, shows an excess of long homozygosity tracts above 300 kb in hydroxyurea and rapamycin (KS-test, $P<0.01$). Ancestral haploid isolates are used to compare a set of in silico diploid genomes to evolved diploid isolates. Only unrelated isolate backgrounds were included. (B) Background- and environment-dependent rates of loss-of-heterozygosity were measured in a fluctuation assay by loss of the URA3 marker. 5-FOA+ colonies indicate loss of the marker. LOH rates were elevated in hydroxyurea compared to the control environment and manifested background-dependent effects between the parents and their hybrid. The mean frequency of 5-FOA+ colony-forming units (CFU) is shown. Error bars indicate the standard error of the mean. (C) Whole-genome sequences of evolved clones sampled from WAxNA F12 populations after 32 days in hydroxyurea (top) or rapamycin (bottom). Chromosomes are shown on the $x$-axis; clone isolates are listed on the left, colored by lineage (see Fig. S4). The consensus shows the majority genotype across isolates with sequence identity greater than 80%. Individual cells with a shared background genotype carry de novo SNVs and indels (circles), mis-segregations with loss-of-heterozygosity (solid segments) and copy-number changes (hatched segments). Driver and passenger mutations are listed along the top (drivers are in boldface). In hydroxyurea, each isolate carries a shared RNR2 heterozygous mutation and private regions with LOH. Chromosome II has undergone extensive LOH in isolates C5 and C6, which have 13% faster growth rate compared to C1-C4 (Fig. 2D, center panel). In rapamycin, FPR1 mutant clone C1 is haploid and is related to the diploid clone C3. Both have lost the remaining FPR1 wild-type copy either by a localized LOH event (C3) or meiosis (C1). An extended version of the figure with all sequenced isolates can be found in Fig. S6.