Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales

Abstract

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

Keywords: adaptation; budding yeast; de novo mutation; drug resistance; pre-existing genetic variation.

Fig. 1.

Evolution of isogenic and heterogeneous populations to RM and HU. (A) Ancestral populations with increasing pre-existing variation from isogenic, two-parent to four-parent populations (top) and timeline of selection experiment for isogenic and four-parent populations (bottom). The timeline of two-parent selection experiment is listed in supplementary table S1, Supplementary Material online. Random subsamples of the initial populations, and of the first, second, fourth, eighth, and the last transfer (T14 for HU and T15 for RM in the isogenic and four-parent populations; T16 for HU and RM in the two-parent populations) were sequenced in bulk. The experimental evolution of 15 two-parent clones was performed only in HU condition. (B) Doubling time in RM (top) and HU (bottom) of the randomly sampled bulk populations after each expansion cycle. Boxplot shows the doubling time of all the populations during the experimental evolution (biological replicates are indicated in parentheses). (C) Doubling time of clonal populations expanded from random, single individuals drawn from the ancestral and endpoint populations (supplementary table S2, Supplementary Material online) in RM (top) and HU (bottom). For each drug, we phenotyped 384 random individuals from both the ancestral and endpoint four-parent populations, as well as 48 and 96 random individuals from each ancestral and endpoint isogenic parental population. The mean doubling time of these individuals were pooled based on their category (e.g., four-parent, two-parent) and time points (e.g., T0, T15) and shown by the boxplots. The details of technical replicates and standard deviation are listed in supplementary table S12, Supplementary Material online. The WA isogenic populations went extinct after T2 in HU. One WE isogenic population in RM was contaminated at T15 and therefore T8 was analyzed instead. *The wide doubling time distribution of two-parent individuals in RM at T16 is due to the coexistence of fast and slow growth individuals with and without driver mutations, see Vázquez-García et al. (2017). Boxplot: center lines = median; boxes = interquartile range (IQR); whiskers = 1.5×IQR; points = outliers beyond 1.5×IQR.

Fig. 2.

De novo mutations in TOR1 and FPR1 drive RM adaptation in isogenic populations. (A) Lines indicate mean doubling time of the bulk population (left y-axis). Bars represent frequency dynamics of de novo driver mutations (right y-axis). Bar colors indicate different driver mutations in FPR1 (light-dark blue) and TOR1 (yellow-brown). (B) Doubling time of random individuals drawn from the ancestral (T0, 48 individuals for each parent), RM evolved (T15, 192 individuals for each parent) populations and genotyped individuals. We divided genotyped individuals into groups based on their driver mutations; no individual carried more than one driver mutation. The number above the boxplot indicates the number of genotyped individuals with confirmed driver mutations by Sanger sequencing. (C) The genome-wide sequencing depth of SA population at T0 and two replicates at T15 evolved in RM, measured by bulk population sequencing. Genomic positions are shown on the x-axis and sequencing depth on the y-axis. Each point indicates the mean sequencing depth of a 10-kb window and the red line indicates median sequencing depth of each chromosome. (D) Design (top) and doubling time (bottom) of a genetic cross experiment. We crossed haploid derived from spores obtained from individuals drawn from the RM evolved (T15) SA populations to generate diploids with known configurations of driver mutation genotypes and chromosome IX copy number. “+” and “–” = TOR1 genotypes, WT and de novo mutated respectively. Blue bar = chromosome IX. Marker shape = chromosome IX copy number, marker color = TOR1 genotype. Of note, there are two distinct clusters of doubling times for the TOR1 WT strains, which is due to the batch effect of two different scanners used to monitor the colony growth (e.g., local variation in humidity within the cabinet). Nevertheless, this did not influence the conclusion that TOR1 was the driver mutation rather than the chrIX copy number changes. Boxplot: center lines, median; boxes, interquartile range (IQR); whiskers, 1.5×IQR. Data points beyond the whiskers are outliers.

Fig. 3.

De novo mutations in TOR1, TOR2, and FPR1 drive RM adaptation in heterogeneous populations. (A) Lines indicate mean doubling time of the bulk population (left y-axis). Bars represent frequency dynamics of de novo driver mutations emerging in four-parent populations adapting to RM (right y-axis). Bar colors indicate different driver mutations in FPR1 (light-dark blue), TOR1 (yellow-red), and TOR2 (green). Top and bottom panels show replicates from F12_1 and F12_2, respectively. (B) Doubling time of random individuals drawn from the ancestral (T0, 384 individuals) and RM evolved (T15, 384 individuals) populations. We divided genotyped individuals into groups based on their driver mutations; no individual carried more than one driver mutation. The number above each boxplot indicates the number of genotyped individuals by Sanger sequencing. Boxplot: center lines, median; boxes, interquartile range (IQR); whiskers, 1.5×IQR. Data points beyond the whiskers are outliers.

Fig. 4.

RNR4 QTL drive adaptation in the four-parent populations in HU. (A) The z-score square underlies QTLs and is derived from allele frequency changes from T0 to early phase of selection (T1–T4). Dashed and solid lines indicate 99% and 95% quantile cut-off, respectively. Strong QTLs are labeled in red and weak ones are in black (coordinates listed in supplementary table S5, Supplementary Material online). We filtered out QTLs that mapped to repetitive regions as well as those detected in YPD control condition (supplementary fig. S9, Supplementary Material online). (B) WE allele frequency changes in chromosome VII in F12_1_HU_2 four-parent population evolved in HU from T0 to T14. The region in the black box contains the RNR4 QTL. (C) Frequency changes (mean) of the four RNR4 alleles from T0 to T14, showing 1:3 segregating pattern (one strong allele vs. three weak alleles). The error bars indicate the standard deviation of the eight replicates. The region highlighted in red indicates the early phase of selection used for QTL mapping. (D) Doubling time of RNR4 reciprocal hemizygotes measured in HU and control experimentally confirmed the RNR4 causative variants. Boxplot: Center lines, median; boxes, interquartile range (IQR); whiskers, 1.5×IQR. Data points beyond the whiskers are outliers.

Fig. 5.

TOR1 and TOR2 allelic variation. (A) TOR1 (top) and TOR2 (bottom) allele frequency changes of the four-parent populations during RM selection. The region highlighted in red indicates the early phase of selection used for QTL mapping. The points and error bars indicate the mean and standard deviation of all the eight replicates. (B) Doubling time (left) and yield (right) of WE/SA hybrid with TOR1 and TOR2 reciprocal hemizygote deletions confirm the causative variants for RM resistance. The doubling time and yield were extracted from the growth curve measured in YPD with RM by Tecan plate reader. (C) CLS of TOR1 and TOR2 reciprocal hemizygotes (WE/SA) in the presence and absence of RM. (D) Characterization of the TORC1 activity by immunoblot of Rps6 phosphorylation in WT parents, hybrid and TOR1, TOR2 reciprocal hemizygotes. Cells were treated with RM (200 ng/ml) for the time indicated (minute). Total lysates were resolved by SDS-PAGE on 10% polyacrylamide gels and analyzed by immunoblot. Actin was used as loading control. The “short,” “interm.,” and “long” panels indicate the exposure time of the membrane to the film. (E) Growth phenotypes of wild type strains and TOR1, TOR2 reciprocal hemizygotes in 18 environments, corresponding to synthetic wine must and single nitrogen source environments at nitrogen limiting concentrations. Heat map shows the fold change in doubling time compared with WE/SA wild type hybrid.

Fig. 6.

Sequence analysis of TOR1, TOR2, and RNR4. The ratio of nonsynonymous and synonymous substitutions (dN/dS) and sequence diversity analysis of (A) TOR1, (B) TOR2, and (C) RNR4. All the plots are based on 60-bp window for each gene. The dN/dS and diversity value was calculated using the sequences from the 1002 Yeast Genomes project. Functional domains are highlighted with different colors. The dashed line shows dN/dS = 1, indicating no selection (neutral). Values above 1 indicate positive selection and below 1 indicate purifying or stabilizing selection. Circle indicates the positions of pre-existing variants of the four parental strains. Star indicates de novo mutations identified in the experimental evolution of the isogenic, two-parent and four-parent populations (supplementary table S7, Supplementary Material online). Gray color represents variants with significant SIFT score, indicating positions of high conservation.

Fig. 7.

Functional characterization of the TOR2 variants. (A) The SA tor2Δ cells are able to grow on synthetic complete (SC) medium although with visible growth defect, but not on YPD. (B) Growth curves of the SA tor2Δ and SA wild type strains growing in SC measured by Tecan plate reader. (C) Immunoblot analysis showed Rps6 phosphorylation in SA wild type and tor2Δ strains. The TORC1 activity is not altered by the TOR2 deletion. All the conditions are similar to the one reported in fig. 5D. (D) Representative plates acquired 4 days after tetrad dissection on SC and YPD for WE/SA wild type and its TOR2 reciprocal hemizygotes. The red circles indicate viable tor2Δ strains. (E) The SA allele frequency on chromosome IX (top) and X (bottom) reveal the regions and candidate genes which compensate for the loss of TOR2. The red box highlights the regions with extremely high (99th percentile) or low (1st percentile) SA allele frequencies in the small spores. The coordinate is based on the WE reference (DBVPG6765, see Yue et al. 2017).