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Phenotypic variation in diverse organism-level traits have been studied in Caenorhabditis elegans wild strains, but differences in gene expression and the underlying variation in regulatory mechanisms are largely unknown. Here, we use natural variation in gene expression to connect genetic variants to differences in organismal- level traits, including drug and toxicant responses. We performed transcriptomic analysis on 207 genetically distinct C. elegans wild strains to study natural regulatory variation of gene expression. Using this massive dataset, we performed genome-wide association mappings to investigate the genetic basis underlying gene expression variation and revealed complex genetic architectures. We found a large collection of hotspots enriched for expression quantitative trait loci across the genome. We further used mediation analysis to understand how gene expression variation could underlie organism-level phenotypic variation for a variety of complex traits. These results reveal the natural diversity in gene expression and possible regulatory mechanisms in this keystone model organism, highlighting the promise of gene expression variation in shaping phenotypic diversity.
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Quantitative Control for Stoichiometric Protein Synthesis
Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production.
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- Award ID(s):
- 1844668
- PAR ID:
- 10315171
- Date Published:
- Journal Name:
- Annual Review of Microbiology
- Volume:
- 75
- Issue:
- 1
- ISSN:
- 0066-4227
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1146/annurev-micro-041921-012646
