Variation in ubiquitin system genes creates substrate-specific effects on proteasomal protein degradation

  1. Mahlon A Collins
  2. Gemechu Mekonnen
  3. Frank Wolfgang Albert

  • Curated by eLife

    eLife logo

    Evaluation Summary:

    The authors use an elegant experimental design to study genetic variation in the ubiquitin-proteasome degradation system in yeast. They identify a large number of QTLs for naturally occurring variation, and they elucidate the causal variants and likely functional mechanisms of several of these. The paper illustrates an innovative new approach to high-throughput QTL mapping for specific molecular processes and it will be of interest to colleagues aiming to harness natural variation for understanding a range of biological processes.

    (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. Reviewer #1 agreed to share their name with the authors.)

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Precise control of protein degradation is critical for life, yet how natural genetic variation affects this essential process is largely unknown. Here, we developed a statistically powerful mapping approach to characterize how genetic variation affects protein degradation by the ubiquitin-proteasome system (UPS). Using the yeast Saccharomyces cerevisiae , we systematically mapped genetic influences on the N-end rule, a UPS pathway in which protein N-terminal amino acids function as degradation-promoting signals. Across all 20 possible N-terminal amino acids, we identified 149 genomic loci that influence UPS activity, many of which had pathway- or substrate-specific effects. Fine-mapping of four loci identified multiple causal variants in each of four ubiquitin system genes whose products process ( NTA1 ), recognize ( UBR1 and DOA10 ), and ubiquitinate ( UBC6 ) cellular proteins. A cis -acting promoter variant that modulates UPS activity by altering UBR1 expression alters the abundance of 36 proteins without affecting levels of the corresponding mRNA transcripts. Our results reveal a complex genetic basis of variation in UPS activity.

Article activity feed

  1. Version published to 10.7554/elife.79570 on eLife
  2. eLife

    Author Response

    Reviewer #1 (Public Review):

    This well-written paper combines a novel method for assaying ubiquitin-proteasome system (UPS) activity with a yeast genetic cross to study genetic variation in this system. Many loci are mapped, and a few genes and causal polymorphism are identified. A connection between UPS variation and protein abundance is made for one gene, demonstrating that variation in this system may affect phenotypic variation.

    The major strength of the study is the power of yeast genetics which makes it possible to dissect quantitative traits down to the nucleotide level. The weakness is that is not clear whether the observed UBS variation matters on any level, however, the claims are suitable to moderate, and generally supported.

    We agree with the reviewer that understanding how causal variants for ubiquitin-proteasome system (UPS) activity affect other molecular, cellular, and organismal phenotypes is an important area of future research.

    The paper provides a nice example of how it is possible to genetically dissect an "endo-phenotype", and learn some new biology. It also represents a welcome attempt to put the function of a mechanism that is heavily studied in molecular cell biology in a broader context.

    We thank the reviewer for these kind words.

    Reviewer #2 (Public Review):

    In this manuscript, the authors developed an elegant quantitative reporter assay to identify quantitative trait loci that regulates N-end rule pathway, a major quality control mechanism in eukaryotes. By crossing two yeast species with divergent proteostasis activity, they generated a population that showed broad variation in proteostasis activity. By sequencing and mapping the underlying loci, they have identified several genes that regulate N-end rule activity. They then verified them using precise genetic tools, validating the power of their approach.

    Overall, it is a very solid manuscript that would be highly interesting for the quality control field.

    In general, I really liked this manuscript for these reasons:

    • Uses fluorescent timers elegantly to quantitatively measure protein degradation.
    • Validates the approach in depth, showing the readers how the tool works.
    • Uses the power of yeast genetics and bulk segregant analysis to map loci that may have small effects.
    • Validates the mapped loci using precise genetic tools.

    In a field that is dominated by biochemistry, this manuscript will be a fresh breath of air…

    We thank the reviewer for their thoughtful evaluation of our work and these kind words.

    Reviewer #3 (Public Review):

    This manuscript, "Variation in Ubiquitin System Genes Creates Substrate-Specific Effects on Proteasomal Protein Degradation" studies the genetic basis of differences in protein degradation. The authors do so by screening natural genetic variation in two yeast strains, finding several genes and often several variants within each gene that can affect protein degradation efficiency by the Ubiquitin-Proteasome system (UPS). Many of these variants have "substrate-specific effects" meaning they only affect the degradation of specific proteins (those with specific degrons). Also, many variants located within the same genes have conflicting effects, some of which are larger than others and can mask others. Overall, this study reveals a complex genetic basis for protein degradation.

    Strengths: Revealing the genetic basis for any complex trait, such as protein degradation, is a major goal of biology. The results of this paper make a significant step towards the goal of mapping the genes and variants involved in this specific trait. Fine mapping methods are used to home in on the specific variants involved and to measure their effects. This is very nicely done and provides a detailed view of the genetic basis of protein degradation. Further, the GFP/RFP system used to quantify the efficiency of the protein degradation system is a very elegant system. Also, the completeness of the analysis, meaning that all 20 N-degrons were studied, is impressive and leads to very detailed findings. It is interesting that some genetic variants have larger and opposite effects on the degradation of different N-degrons.

    We thank the reviewer for these positive comments.

    Weaknesses: Some of the results discussed in this paper are not surprising. For example, the finding that both large effect and small effect genetic variants contribute to this complex trait is not at all surprising. This is true of many complex traits.

    We agree with the reviewer that the number and patterns of QTLs we observe are perhaps not unexpected given that most traits are genetically complex. However, we also note that our results stand in stark contrast to previous efforts to understand how natural genetic variation affects the UPS, which have focused almost exclusively on large-effect mutations in UPS genes that cause rare Mendelian disorders. We have therefore chosen to retain our discussion of the complex genetic architecture of the UPS.

    The discussion of human disease is also a bit extensive given this study was performed on yeast. It might be more productive to use these findings to understand the UPS better on a mechanistic level. Why does the same genetic variant have opposite effects on the degradation of different degrons, even in cases where those degrons are of the same type?

    Following the reviewer’s suggestion we have removed multiple references to human disease from the introduction. We retained paragraph 3 of the introduction (previously, lines 43-55, pg. 2, para. 2 in the revised manuscript), which discusses disease-causing mutations in UPS genes, because the examples presented highlight two important motivations for our work: (1) individual genetic differences create variation in UPS activity and (2) much of our knowledge of how natural genetic variation affects the UPS comes from these rare, limited examples. However, we have re-written the paragraph to focus on these points and removed descriptions of the clinical manifestations of the disorders mentioned.

    We agree with the reviewer that understanding the mechanistic basis of substrate-specific variant effects on distinct N-degrons is important. However, doing so would require additional experiments that we argue are outside the scope of the current study.

    Overall, this manuscript excels at mapping the genetic basis of variation in the UPS system. It demonstrates a very complex mapping from genotype to phenotype that begs for further mechanistic explanation. These results are important to the UPS field because they may help researchers interrogate this highly conserved essential system. The manuscript is weaker when it comes to the broader conclusions drawn about the relative importance of large vs. small effects variants on complex traits, the amount of heritability explained, and the effects of genetic variation on protein abundance vs transcript abundance. Though in the case of protein vs transcript, I feel the cursory examination of the trends is perhaps at an appropriate level for the study, as it is mainly meant to show these things differ rather than to show exactly how and why they differ.

    We state that the distribution of QTL effect sizes for UPS activity consists of many QTLs with small effects and few QTLs of large effects. While this result is similar to patterns observed for other complex traits, it differs dramatically from the results of previous studies of genetic influences on the UPS, which have been largely confined to large-effect variants. Given these differences, we think it is appropriate and worthwhile to emphasize the complex genetic architecture of UPS activity.

    We agree that estimating the fraction of heritability explained by our QTLs and variants would be valuable. However, as noted in our response to Reviewer 1, the QTL mapping method we used does not permit ready calculation of heritability estimates due to its pooled nature.

    The reviewer is correct in noting that the primary goal of our RNA-seq and proteomics experiments was to provide an initial exploration of the effects of causal variants for UPS activity on global gene expression at the protein and mRNA levels. While a comprehensive dissection of the effects of this and other causal variants is an important area of future work, our results here show broad changes in global gene expression and establish that the causal UBR1 variant affects gene expression at the protein and mRNA levels.

    Reviewer #4 (Public Review):

    Overall the paper is clear and well-written. The experimental design is elegant and powerful, and it's a stimulating read. Most QTL mapping has focused on directly measurable phenotypes such as expression or drug response; I really like this paper's distinctive approach of placing bespoke functional assays for a specific molecular mechanism into the classical QTL framework.

    We thank the reviewer for their thoughtful evaluation of the work and positive comments.

  3. eLife

    Evaluation Summary:

    The authors use an elegant experimental design to study genetic variation in the ubiquitin-proteasome degradation system in yeast. They identify a large number of QTLs for naturally occurring variation, and they elucidate the causal variants and likely functional mechanisms of several of these. The paper illustrates an innovative new approach to high-throughput QTL mapping for specific molecular processes and it will be of interest to colleagues aiming to harness natural variation for understanding a range of biological processes.

    (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. Reviewer #1 agreed to share their name with the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    This well-written paper combines a novel method for assaying ubiquitin-proteasome system (UPS) activity with a yeast genetic cross to study genetic variation in this system. Many loci are mapped, and a few genes and causal polymorphism are identified. A connection between UPS variation and protein abundance is made for one gene, demonstrating that variation in this system may affect phenotypic variation.

    The major strength of the study is the power of yeast genetics which makes it possible to dissect quantitative traits down to the nucleotide level. The weakness is that is not clear whether the observed UBS variation matters on any level, however, the claims are suitable to moderate, and generally supported.

    The paper provides a nice example of how it is possible to genetically dissect an "endo-phenotype", and learn some new biology. It also represents a welcome attempt to put the function of a mechanism that is heavily studied in molecular cell biology in a broader context.

  5. eLife

    Reviewer #2 (Public Review):

    In this manuscript, the authors developed an elegant quantitative reporter assay to identify quantitative trait loci that regulates N-end rule pathway, a major quality control mechanism in eukaryotes. By crossing two yeast species with divergent proteostasis activity, they generated a population that showed broad variation in proteostasis activity. By sequencing and mapping the underlying loci, they have identified several genes that regulate N-end rule activity. They then verified them using precise genetic tools, validating the power of their approach.

    Overall, it is a very solid manuscript that would be highly interesting for the quality control field.

    In general, I really liked this manuscript for these reasons:

    - Uses fluorescent timers elegantly to quantitatively measure protein degradation.

    - Validates the approach in depth, showing the readers how the tool works.

    - Uses the power of yeast genetics and bulk segregant analysis to map loci that may have small effects.

    - Validates the mapped loci using precise genetic tools.

    In a field that is dominated by biochemistry, this manuscript will be a fresh breath of air...

  6. eLife

    Reviewer #3 (Public Review):

    This manuscript, "Variation in Ubiquitin System Genes Creates Substrate-Specific Effects on Proteasomal Protein Degradation" studies the genetic basis of differences in protein degradation. The authors do so by screening natural genetic variation in two yeast strains, finding several genes and often several variants within each gene that can affect protein degradation efficiency by the Ubiquitin-Proteasome system (UPS). Many of these variants have "substrate-specific effects" meaning they only affect the degradation of specific proteins (those with specific degrons). Also, many variants located within the same genes have conflicting effects, some of which are larger than others and can mask others. Overall, this study reveals a complex genetic basis for protein degradation.

    Strengths: Revealing the genetic basis for any complex trait, such as protein degradation, is a major goal of biology. The results of this paper make a significant step towards the goal of mapping the genes and variants involved in this specific trait. Fine mapping methods are used to home in on the specific variants involved and to measure their effects. This is very nicely done and provides a detailed view of the genetic basis of protein degradation. Further, the GFP/RFP system used to quantify the efficiency of the protein degradation system is a very elegant system. Also, the completeness of the analysis, meaning that all 20 N-degrons were studied, is impressive and leads to very detailed findings. It is interesting that some genetic variants have larger and opposite effects on the degradation of different N-degrons.

    Weaknesses: Some of the results discussed in this paper are not surprising. For example, the finding that both large effect and small effect genetic variants contribute to this complex trait is not at all surprising. This is true of many complex traits. The discussion of human disease is also a bit extensive given this study was performed on yeast. It might be more productive to use these findings to understand the UPS better on a mechanistic level. Why does the same genetic variant have opposite effects on the degradation of different degrons, even in cases where those degrons are of the same type?

    Overall, this manuscript excels at mapping the genetic basis of variation in the UPS system. It demonstrates a very complex mapping from genotype to phenotype that begs for further mechanistic explanation. These results are important to the UPS field because they may help researchers interrogate this highly conserved essential system. The manuscript is weaker when it comes to the broader conclusions drawn about the relative importance of large vs. small effects variants on complex traits, the amount of heritability explained, and the effects of genetic variation on protein abundance vs transcript abundance. Though in the case of protein vs transcript, I feel the cursory examination of the trends is perhaps at an appropriate level for the study, as it is mainly meant to show these things differ rather than to show exactly how and why they differ.

  7. eLife

    Reviewer #4 (Public Review):

    Overall the paper is clear and well-written. The experimental design is elegant and powerful, and it's a stimulating read. Most QTL mapping has focused on directly measurable phenotypes such as expression or drug response; I really like this paper's distinctive approach of placing bespoke functional assays for a specific molecular mechanism into the classical QTL framework.

  8. Version published to 10.1101/2021.05.05.442832v2 on bioRxiv
  9. Version published to 10.1101/2021.05.05.442832v1 on bioRxiv