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[Preprint]. 2023 Sep 18:2023.09.18.558197. [Version 1] doi: 10.1101/2023.09.18.558197

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

E Teyssonnière, P Trébulle, J Muenzner, V Loegler, D Ludwig, F Amari, M Mülleder, A Friedrich, J Hou, M Ralser, J Schacherer
PMCID: PMC10541136  PMID: 37781592

Summary

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Highlights

  • At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165).

  • While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscape

  • Wild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populations

  • Loci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover

Full Text Availability

The license terms selected by the author(s) for this preprint version do not permit archiving in PMC. The full text is available from the preprint server.


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