Additional file 1: of Stochastic modeling of aging cells reveals how damage accumulation, repair, and cell-division asymmetry affect clonal senescence and population fitness

Figure S1. A-H. Relative representation of the other parameters in the cases where changing the level of inheritance caused a significant (> 5%) fitness difference. Figure S2. A-H. Relative representation of the other parameters in the cases where changing the maximum repair rate caused a significant (> 5%) fitness difference. Figure S3. A-H. Relative representation of the other parameters in the cases where changing the Michaelis constant km for repair caused a significant (> 5%) fitness difference. Figure S4. A-H. Relative representation of the other parameters in the cases where changing the damage accumulation rate caused a significant (> 5%) fitness difference. Table S1. Parameters with fixed mean values. Table S2. Parameters with values selected from a grid of values. (PDF 1035 kb

Table_1_Phenotypic selection during laboratory evolution of yeast populations leads to a genome-wide sustainable chromatin compaction shift.xlsx

In a previous study, we have shown how microbial evolution has resulted in a persistent reduction in expression after repeatedly selecting for the lowest PGAL1-YFP-expressing cells. Applying the ATAC-seq assay on samples collected from this 28-day evolution experiment, here we show how genome-wide chromatin compaction changes during evolution under selection pressure. We found that the chromatin compaction was altered not only on GAL network genes directly impacted by the selection pressure, showing an example of selection-induced non-genetic memory, but also at the whole-genome level. The GAL network genes experienced chromatin compaction accompanying the reduction in PGAL1-YFP reporter expression. Strikingly, the fraction of global genes with differentially compacted chromatin states accounted for about a quarter of the total genome. Moreover, some of the ATAC-seq peaks followed well-defined temporal dynamics. Comparing peak intensity changes on consecutive days, we found most of the differential compaction to occur between days 0 and 3 when the selection pressure was first applied, and between days 7 and 10 when the pressure was lifted. Among the gene sets enriched for the differential compaction events, some had increased chromatin availability once selection pressure was applied and decreased availability after the pressure was lifted (or vice versa). These results intriguingly show that, despite the lack of targeted selection, transcriptional availability of a large fraction of the genome changes in a very diverse manner during evolution, and these changes can occur in a relatively short number of generations.</p

Presentation_1_Phenotypic selection during laboratory evolution of yeast populations leads to a genome-wide sustainable chromatin compaction shift.PDF

In a previous study, we have shown how microbial evolution has resulted in a persistent reduction in expression after repeatedly selecting for the lowest PGAL1-YFP-expressing cells. Applying the ATAC-seq assay on samples collected from this 28-day evolution experiment, here we show how genome-wide chromatin compaction changes during evolution under selection pressure. We found that the chromatin compaction was altered not only on GAL network genes directly impacted by the selection pressure, showing an example of selection-induced non-genetic memory, but also at the whole-genome level. The GAL network genes experienced chromatin compaction accompanying the reduction in PGAL1-YFP reporter expression. Strikingly, the fraction of global genes with differentially compacted chromatin states accounted for about a quarter of the total genome. Moreover, some of the ATAC-seq peaks followed well-defined temporal dynamics. Comparing peak intensity changes on consecutive days, we found most of the differential compaction to occur between days 0 and 3 when the selection pressure was first applied, and between days 7 and 10 when the pressure was lifted. Among the gene sets enriched for the differential compaction events, some had increased chromatin availability once selection pressure was applied and decreased availability after the pressure was lifted (or vice versa). These results intriguingly show that, despite the lack of targeted selection, transcriptional availability of a large fraction of the genome changes in a very diverse manner during evolution, and these changes can occur in a relatively short number of generations.</p

Table_2_Phenotypic selection during laboratory evolution of yeast populations leads to a genome-wide sustainable chromatin compaction shift.xlsx

In a previous study, we have shown how microbial evolution has resulted in a persistent reduction in expression after repeatedly selecting for the lowest PGAL1-YFP-expressing cells. Applying the ATAC-seq assay on samples collected from this 28-day evolution experiment, here we show how genome-wide chromatin compaction changes during evolution under selection pressure. We found that the chromatin compaction was altered not only on GAL network genes directly impacted by the selection pressure, showing an example of selection-induced non-genetic memory, but also at the whole-genome level. The GAL network genes experienced chromatin compaction accompanying the reduction in PGAL1-YFP reporter expression. Strikingly, the fraction of global genes with differentially compacted chromatin states accounted for about a quarter of the total genome. Moreover, some of the ATAC-seq peaks followed well-defined temporal dynamics. Comparing peak intensity changes on consecutive days, we found most of the differential compaction to occur between days 0 and 3 when the selection pressure was first applied, and between days 7 and 10 when the pressure was lifted. Among the gene sets enriched for the differential compaction events, some had increased chromatin availability once selection pressure was applied and decreased availability after the pressure was lifted (or vice versa). These results intriguingly show that, despite the lack of targeted selection, transcriptional availability of a large fraction of the genome changes in a very diverse manner during evolution, and these changes can occur in a relatively short number of generations.</p

Data_Sheet_1_Phenotypic selection during laboratory evolution of yeast populations leads to a genome-wide sustainable chromatin compaction shift.XLSX

In a previous study, we have shown how microbial evolution has resulted in a persistent reduction in expression after repeatedly selecting for the lowest PGAL1-YFP-expressing cells. Applying the ATAC-seq assay on samples collected from this 28-day evolution experiment, here we show how genome-wide chromatin compaction changes during evolution under selection pressure. We found that the chromatin compaction was altered not only on GAL network genes directly impacted by the selection pressure, showing an example of selection-induced non-genetic memory, but also at the whole-genome level. The GAL network genes experienced chromatin compaction accompanying the reduction in PGAL1-YFP reporter expression. Strikingly, the fraction of global genes with differentially compacted chromatin states accounted for about a quarter of the total genome. Moreover, some of the ATAC-seq peaks followed well-defined temporal dynamics. Comparing peak intensity changes on consecutive days, we found most of the differential compaction to occur between days 0 and 3 when the selection pressure was first applied, and between days 7 and 10 when the pressure was lifted. Among the gene sets enriched for the differential compaction events, some had increased chromatin availability once selection pressure was applied and decreased availability after the pressure was lifted (or vice versa). These results intriguingly show that, despite the lack of targeted selection, transcriptional availability of a large fraction of the genome changes in a very diverse manner during evolution, and these changes can occur in a relatively short number of generations.</p

Data_Sheet_2_Phenotypic selection during laboratory evolution of yeast populations leads to a genome-wide sustainable chromatin compaction shift.XLSX

In a previous study, we have shown how microbial evolution has resulted in a persistent reduction in expression after repeatedly selecting for the lowest PGAL1-YFP-expressing cells. Applying the ATAC-seq assay on samples collected from this 28-day evolution experiment, here we show how genome-wide chromatin compaction changes during evolution under selection pressure. We found that the chromatin compaction was altered not only on GAL network genes directly impacted by the selection pressure, showing an example of selection-induced non-genetic memory, but also at the whole-genome level. The GAL network genes experienced chromatin compaction accompanying the reduction in PGAL1-YFP reporter expression. Strikingly, the fraction of global genes with differentially compacted chromatin states accounted for about a quarter of the total genome. Moreover, some of the ATAC-seq peaks followed well-defined temporal dynamics. Comparing peak intensity changes on consecutive days, we found most of the differential compaction to occur between days 0 and 3 when the selection pressure was first applied, and between days 7 and 10 when the pressure was lifted. Among the gene sets enriched for the differential compaction events, some had increased chromatin availability once selection pressure was applied and decreased availability after the pressure was lifted (or vice versa). These results intriguingly show that, despite the lack of targeted selection, transcriptional availability of a large fraction of the genome changes in a very diverse manner during evolution, and these changes can occur in a relatively short number of generations.</p

Additional file 1: of Multi-component gene network design as a survival strategy in diverse environments

Figure S1. Expression level distributions of the strains used in this study in a 2% glucose environment. Center: Expression level distributions of the 16 strains under study. Bottom corners: expression level distributions of the two reference strains: left: the gal80Δ strain (XLUYLmCdd80); right: the WT strain with PTEF-mCherry (XLUYLmC). Glucose catabolite repression and the repression from Gal80p combine to eliminate all expression from the PGAL1-YFP reporter in all strains except the gal80Δ strain. Figure S2. Fitness level measured is invariant to the initial population ratio. Fitness measurements are performed for all 16 strains in Environment D (1% galactose) using different initial fractions: red = 67% (s.d. = 7%), green = 27% (s.d. = 3%), blue = 54% (s.d. = 6%). The results are shown above. Error bars indicate s.e.m. (N = 9). No statistically significant differences were observed (using Student’s t-test with the Benjamini–Hochberg procedure to control false discovery rate at 0.05). Figure S3. Results of the competition experiment in Environment E (0.3% galactose). A. Final expression level distributions of the 16 strains. B. Average PGAL1-YFP expression level of the 16 strains. Expression levels are normalized to the expression level of the reference strain in the same sample. Error bars indicate s.e.m. (N = 9). Stars indicate statistically significant differences from wild-type strain as determined by a two-tailed Student’s t-test (Bonferroni-corrected p-value: ****: p < 0.0001; ***: p < 0.001; **: p < 0.01; *: p < 0.05). C. Average fitness value of the 16 strains, normalized to the average 5 fitness value of the wild-type strain. Error bars indicate s.e.m. (N = 9). Stars indicate statistically significant differences from wild-type strain as determined by a two-tailed Student’s t-test (Bonferroni-corrected p-value: ****: p < 0.0001; ***: p < 0.001; **: p < 0.01; *: p < 0.05). D. Plot of expression vs. fitness for the 16 strains. Solid line is the prediction of the fitted linear model. Error bars indicate s.e.m. (N = 9). E. Average effect of copy number reduction on fitness for the four genes in this environment. Error bars indicate uncertainty calculated from the s.e.m. of the fitness measurements. Figure S4. Results of the competition experiment in Environment F (2% galactose). A. Final expression level distributions of the 16 strains. B. Average PGAL1-YFP expression level of the 16 strains. Expression levels are normalized to the expression level of the reference strain in the same sample. Error bars indicate s.e.m. (N = 9). Stars indicate statistically significant differences from wild-type strain as determined by a twotailed Student’s t-test (Bonferroni-corrected p-value: ****: p < 0.0001; ***: p < 0.001; **: p < 0.01; *: p < 0.05). C. Average fitness value of the 16 strains, normalized to the average fitness 7 value of the wild-type strain. Error bars indicate s.e.m. (N = 9). Stars indicate statistically significant differences from wild-type strain as determined by a two-tailed Student’s t-test (Bonferroni-corrected p-value: ****: p < 0.0001; ***: p < 0.001; **: p < 0.01; *: p < 0.05). D. Plot of expression vs. fitness for the 16 strains. Solid line is the prediction of the fitted linear model; dotted line shows the prediction of the model at 1% galactose. Error bars indicate s.e.m. (N = 9). E. Average effect of copy number reduction on fitness for the four genes in this environment. Error bars indicate uncertainty calculated from the s.e.m. of the fitness measurements. Figure S5. Epistasis analysis. A-F: Left: Overall epistatic deviation of strains with the dosage of more than one gene reduced for environments A through F, respectively. Right: Net epistatic deviation for higher-order interactions for environments A through F, respectively. Error bars indicate uncertainty calculated from the s.e.m. of the fitness measurements. Stars indicate statistically significant epistatic deviation as determined by a two-sided Z-test, with the family-wise error rate controlled using the Holm- Bonferroni procedure: ****: α = 0.0001; ***: α = 0.001; **: α = 0.01; *: α = 0.05. Table S1. Saccharomyces cerevisiae strains used in the study. All strains are built on the W303 genetic background. (PDF 1334 kb

Additional file 1: of A cell size- and cell cycle-aware stochastic model for predicting time-dynamic gene network activity in individual cells

Contains Notes S1 (derivation of the functional form of the GAL network) and S2 (description of phenotypic switching rate characterization), and Tables S1, S2 and S3 (lists of model parameters and their values). (PDF 511 kb