Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories
Curation statements for this article:-
Curated by eLife
Evaluation Summary:
This study investigates the effect of copy number variants across all genes in Saccharomyces cerevisiae, and the variation across different genetic backgrounds. Interestingly, apart from universal effects common to most of the genetic backgrounds, the authors also report strain-specific effects related to gene copy number variants.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (eLife)
Abstract
Copy number variation through gene or chromosome amplification provides a route for rapid phenotypic variation and supports the long-term evolution of gene functions. Although the evolutionary importance of copy-number variation is known, little is understood about how genetic background influences its tolerance. Here, we measured fitness costs of over 4000 overexpressed genes in 15 Saccharomyces cerevisiae strains representing different lineages, to explore natural variation in tolerating gene overexpression (OE). Strain-specific effects dominated the fitness costs of gene OE. We report global differences in the consequences of gene OE, independent of the amplified gene, as well as gene-specific effects that were dependent on the genetic background. Natural variation in the response to gene OE could be explained by several models, including strain-specific physiological differences, resource limitations, and regulatory sensitivities. This work provides new insight on how genetic background influences tolerance to gene amplification and the evolutionary trajectories accessible to different backgrounds.
Article activity feed
-
-
Author Response:
Reviewer #1:
How the tolerance of gene overexpression varies across closely related organisms remains poorly understood and this manuscript offers the first systematic functional genomic screen to address this gap. Thus, the approach itself is clearly original and yeast is a great model system for such a study. The data itself would be an important resource for the functional genomics community. The broad picture emerging from this screen is also interesting: a subset of genes is commonly toxic when overexpressed, while many genes are toxic only in specific strains. Importantly, the commonly toxic genes are highly enriched in certain functional classes and often encode for protein complex members. All these make a lot of sense based on what is known about gene dosage sensitivity in baker's yeast.
The more …
Author Response:
Reviewer #1:
How the tolerance of gene overexpression varies across closely related organisms remains poorly understood and this manuscript offers the first systematic functional genomic screen to address this gap. Thus, the approach itself is clearly original and yeast is a great model system for such a study. The data itself would be an important resource for the functional genomics community. The broad picture emerging from this screen is also interesting: a subset of genes is commonly toxic when overexpressed, while many genes are toxic only in specific strains. Importantly, the commonly toxic genes are highly enriched in certain functional classes and often encode for protein complex members. All these make a lot of sense based on what is known about gene dosage sensitivity in baker's yeast.
The more interesting and also riskier part is to identify and understand strain-specific overexpression phenotypes. The authors made great efforts to offer possible explanations for these, however, I had the impression that some further analyses could strengthen the conclusions and yield more insights.
We thank the reviewer for their positive assessment of our work and its importance.
I see four broad issues:
- Statistical analysis: I failed to find data on the reproducibility of the screen and how it varies across strains. Variation in reproducibility may hugely influence some of the conclusions as the number of genes with a significant fitness effect depends on measurement noise (and number of replicates).
We went to great lengths to control all aspects of the experiment and the biological replication. All three biological replicates (two in the case of strain YPS606) are shown in Figure 1B, which demonstrates the high reproducibility. We calculated the average and standard deviation of replicate correlations within each strain; however, analyzing this data is in fact misleading: strains with the fewest deleterious effects are clearly highly reproducible in Figure 1B but often have lower correlation across replicates – this is because the log2 fitness effects are close to zero and thus the correlation is driven by noise. For example, strain Y2209 displayed the lowest correlation across replicates (r = 0.55), but Figure 1B shows very high reproducibility and low fitness effects; incidentally, this strain had above-average number of genes measured at Generation 0 (3,945 genes) and clearly maintains the 2-micron plasmid. Reduced statistical power simply cannot explain the few genes with strong fitness costs in this and other strains.
If we consider only the 7 strains whose average replicate correlation is greater than 0.8 (ranging from 0.80 to 0.89), there is no relationship between mean correlation in their replicates and number of significant genes called (R2 = 0.01). For example, the average correlation in replicates for strain Y12 and YJM1273 is nearly the same (r = 0.795 versus 0.797), yet in Y12 there were 3,060 OE genes of significant effect compared to 1,726 in YJM1273. Thus, while there are always subtle differences in statistical power, our results cannot be explained by this. Instead, our results show that different yeast strains display different sensitivities to Moby 2.0 gene OE. We added a short section on this to the Methods on Page 21.
On a related note, I'm somewhat puzzled by the claim that strains with large median fitness effects do not generally show more OE sensitive genes. Visually, it appears that this relationship is borne out for commonly toxic genes (Fig 3B), although not mentioned or interpreted.
As stated in the manuscript, “While the median fitness cost of deleterious OE genes was not correlated overall with the number of deleterious genes per strain, strains with the most deleterious genes (NCYC3290, YJM1389, and Y12) did show an expanded range of fitness costs, with more genes showing very strong deleterious effects compared to other strains (Figure 2B). The correlation between number of deleterious genes and median fitness cost per strain is low (R2 = 0.08, excluding YPS606 done in duplicate).
- The authors show that the number of deleterious OE genes is strongly correlated with the amount of growth defect caused by expressing the empty Moby 2.0 vector (Figure 4D). This is a pretty strong correlation (r=0.7) and might influence the conclusions drawn from the data. In particular, the strong effect of empty Moby 2.0 should be taken into account when defining strain-specific fitness effects. For example, fitness effects that are present in 2-3 strains might be shared between strains that exhibit a similar cost of empty Moby and therefore need to be interpreted with caution. Previous genetic interaction studies suggest that slow growing mutants tend to show many epistatic interactions with any other mutations (Costanzo et al. 2010). I'm left with the feeling that the strain-specific differences in the number of OE sensitive genes might be a manifestation of this more general phenomenon.
The reviewer raises an important point, one that we have made clearer in the revised manuscript: some strains are simply more sensitive to the library (perhaps due to the DNA burden, the protein burden, and/or the 2-micron replication). These strains are likely stressed during the experiment and may simply be more sensitive to gene OE, in a way that is not specific to the genes being expressed. We added some clarifying statements to the text, on pages 10, 11, 12, and 14-15. Specifically, we now cite that 60% of the deleterious genes meeting our “strain specific” criteria in Y12 were shared with another of the top four strains most sensitive to the empty vector ( DVBPG1373 YJM1592, YPS163, YJM1389, Figure 4D). Thus some of the identified genes may be deleterious if OE in other strains growing in suboptimal or stressful conditions. This is consistent with our aim in the original manuscript and hopefully now clearer with the textual changes in the revision.
- Lack of phylogenetic context: The investigated strains come from several distinct populations with different lifestyles and varying phylogenetic distances. I would have expected some further investigations on how strain-specific OE effects depend on lifestyle or phylogenetic relationship.
We were very interest to see if strains from the same lineage or niche share trends in gene OE sensitivities. However, several analyses did not identify obvious effects. First, we did not find striking similarities for the strain-specific genes identified in strains from the same lineage (this can be seen to some extent from the heat map in Figure 1B). Second, we did not find that strains closely related shared a higher number of genes of similar effect. We would like to return to these questions in future work; thus, for now we have not added the analysis to the current manuscript to maintain focus on the more interesting results.
- The tryptophan depletion story is a nice example of strain-specific difference in physiology. Overall, the presented analyses on tryptophan-enriched genes are highly suggestive, however, it lacks a negative control, that is, other genes that have similar functions but are not enriched in tryptophan.
In the manuscript we state, “Together, these data raised the possibility that DBVPG1373 is sensitive to conditions that deplete tryptophan from the cell.” Our results validated this hypothesis by showing that this strain, but not two others tested, are more sensitive to the OE genes in the absence of tryptophan. It is possible that that strain is more sensitive to any OE gene in this environment. As per the guidance of the editor, we have added a clarification that it is possible that this strain is sensitive to all OE genes in the absence of tryptophan.
-
Evaluation Summary:
This study investigates the effect of copy number variants across all genes in Saccharomyces cerevisiae, and the variation across different genetic backgrounds. Interestingly, apart from universal effects common to most of the genetic backgrounds, the authors also report strain-specific effects related to gene copy number variants.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
-
Reviewer #1 (Public Review):
How the tolerance of gene overexpression varies across closely related organisms remains poorly understood and this manuscript offers the first systematic functional genomic screen to address this gap. Thus, the approach itself is clearly original and yeast is a great model system for such a study. The data itself would be an important resource for the functional genomics community. The broad picture emerging from this screen is also interesting: a subset of genes is commonly toxic when overexpressed, while many genes are toxic only in specific strains. Importantly, the commonly toxic genes are highly enriched in certain functional classes and often encode for protein complex members. All these make a lot of sense based on what is known about gene dosage sensitivity in baker's yeast.
The more interesting and …
Reviewer #1 (Public Review):
How the tolerance of gene overexpression varies across closely related organisms remains poorly understood and this manuscript offers the first systematic functional genomic screen to address this gap. Thus, the approach itself is clearly original and yeast is a great model system for such a study. The data itself would be an important resource for the functional genomics community. The broad picture emerging from this screen is also interesting: a subset of genes is commonly toxic when overexpressed, while many genes are toxic only in specific strains. Importantly, the commonly toxic genes are highly enriched in certain functional classes and often encode for protein complex members. All these make a lot of sense based on what is known about gene dosage sensitivity in baker's yeast.
The more interesting and also riskier part is to identify and understand strain-specific overexpression phenotypes. The authors made great efforts to offer possible explanations for these, however, I had the impression that some further analyses could strengthen the conclusions and yield more insights. I see four broad issues:
Statistical analysis: I failed to find data on the reproducibility of the screen and how it varies across strains. Variation in reproducibility may hugely influence some of the conclusions as the number of genes with a significant fitness effect depends on measurement noise (and number of replicates). On a related note, I'm somewhat puzzled by the claim that strains with large median fitness effects do not generally show more OE sensitive genes. Visually, it appears that this relationship is borne out for commonly toxic genes (Fig 3B), although not mentioned or interpreted.
The authors show that the number of deleterious OE genes is strongly correlated with the amount of growth defect caused by expressing the empty Moby 2.0 vector (Figure 4D). This is a pretty strong correlation (r=0.7) and might influence the conclusions drawn from the data. In particular, the strong effect of empty Moby 2.0 should be taken into account when defining strain-specific fitness effects. For example, fitness effects that are present in 2-3 strains might be shared between strains that exhibit a similar cost of empty Moby and therefore need to be interpreted with caution. Previous genetic interaction studies suggest that slow growing mutants tend to show many epistatic interactions with any other mutations (Costanzo et al. 2010). I'm left with the feeling that the strain-specific differences in the number of OE sensitive genes might be a manifestation of this more general phenomenon.
Lack of phylogenetic context: The investigated strains come from several distinct populations with different lifestyles and varying phylogenetic distances. I would have expected some further investigations on how strain-specific OE effects depend on lifestyle or phylogenetic relationship.
The tryptophan depletion story is a nice example of strain-specific difference in physiology. Overall, the presented analyses on tryptophan-enriched genes are highly suggestive, however, it lacks a negative control, that is, other genes that have similar functions but are not enriched in tryptophan.
-
