Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway

Kemble, Harry; Eisenhauer, Catherine; Couce, Alejandro; Chapron, Audrey; Magnan, Mélanie; Gautier, Grégory; Nagard, Hervé Le; Nghe, Philippe; Tenaillon, Olivier

doi:10.1126/sciadv.abb2236

Cited by 33 publications

(42 citation statements)

References 64 publications

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“…The most restrictive assumption in the present work is that of first-order kinetics. Networks with only first-order kinetics clearly fail to capture some biologically important phenomena, such as sign epistasis ( Weinreich et al, 2005 ; Chou et al, 2014 ; Ewald et al, 2017 ; Kemble et al, 2020 ). I discuss possible ways to relax this assumption below.…”

Section: Discussionmentioning

confidence: 99%

Emergence and propagation of epistasis in metabolic networks

Kryazhimskiy

2021

eLife

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Epistasis is often used to probe functional relationships between genes, and it plays an important role in evolution. However, we lack theory to understand how functional relationships at the molecular level translate into epistasis at the level of whole-organism phenotypes, such as fitness. Here, I derive two rules for how epistasis between mutations with small effects propagates from lower- to higher-level phenotypes in a hierarchical metabolic network with first-order kinetics and how such epistasis depends on topology. Most importantly, weak epistasis at a lower level may be distorted as it propagates to higher levels. Computational analyses show that epistasis in more realistic models likely follows similar, albeit more complex, patterns. These results suggest that pairwise inter-gene epistasis should be common and it should generically depend on the genetic background and environment. Furthermore, the epistasis coefficients measured for high-level phenotypes may not be sufficient to fully infer the underlying functional relationships.

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Section: Discussionmentioning

confidence: 99%

Emergence and propagation of epistasis in metabolic networks

Kryazhimskiy

2021

eLife

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“…Further, many measurable phenotypes are related in complex ways ( Geiler-Samerotte et al, 2020 ). Mapping their contribution to fitness requires a complete understanding of how genetic changes lead to molecular changes and how these percolate to higher functional levels and ultimately influence fitness ( Kemble et al, 2020 ). This might be possible to do in some cases where the phenotype to fitness mapping is simple (e.g.…”

Section: Introductionmentioning

confidence: 99%

Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation

Kinsler

Geiler-Samerotte

Petrov

2020

eLife

103

208

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Building a genotype-phenotype-fitness map of adaptation is a central goal in evolutionary biology. It is difficult even when adaptive mutations are known because it is hard to enumerate which phenotypes make these mutations adaptive. We address this problem by first quantifying how the fitness of hundreds of adaptive yeast mutants responds to subtle environmental shifts. We then model the number of phenotypes these mutations collectively influence by decomposing these patterns of fitness variation. We find that a small number of inferred phenotypes can predict fitness of the adaptive mutations near their original glucose-limited evolution condition. Importantly, inferred phenotypes that matter little to fitness at or near the evolution condition can matter strongly in distant environments. This suggests that adaptive mutations are locally modular—affecting a small number of phenotypes that matter to fitness in the environment where they evolved—yet globally pleiotropic—affecting additional phenotypes that may reduce or improve fitness in new environments.

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“…Epistasis represents an alternative aspect of genetic aetiology for complex diseases [56] , [57] , [58] , [59] but interpretation of the results with different types of interactions [60] , [61] , [62] , [63] , [64] may be more challenging than for main effects. In biology however, proteins or genes function dependently on many other activities in most cases.…”

Section: Discussionmentioning

confidence: 99%

Epistatic evidence for gender-dependant slow neurotransmission signalling in substance use disorders: PPP1R12B versus PPP1R1B

et al. 2020

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Background Slow neurotransmission including DARPP-32 signalling is implicated in substance use disorders (SUDs) by experimental systems but not yet in the human aetiology. PPP1R12B , encoding another protein in the DARPP-32 family, hasn't been studied in the brain. Methods Brain-regional gene activity was assessed in three different animal models of SUDs for mRNA level alterations. Genetic associations were assessed by meta-analysis of pre-existing dbGaP GWAS datasets for main effects and epistasis with known genetic risks, followed by cell type-specific pathway delineation. Parkinson's disease (PD) was included as a dopamine-related disease control for SUDs. Findings In animal models of SUDs, environmentally-altered PPP1R12B expression sex-dependently involves motivation-related brain regions. In humans with polysubstance abuse, meta-analysis of pre-existing datasets revealed that PPP1R12B and PPP1R1B , although expressed in dopamine vs. dopamine-recipient neurons, exerted similar interactions with known genetic risks such as ACTR1B and DRD2 in men but with ADH1B, HGFAC and DRD3 in women. These interactions reached genome-wide significances ( P meta <10 −20 ) for SUDs but not for PD (disease selectivity: P = 4.8 × 10 −142 , OR = 6.7 for PPP1R12B; P = 8.0 × 10 −8 , OR = 2.1 for PPP1R1B ). CADM2 was the common risk in the molecular signalling regardless of gender and cell type. Interpretation Gender-dependant slow neurotransmission may convey both genetic and environmental vulnerabilities selectively to SUDs. Funding Grants from National Institute on Drug Abuse (NIDA) and National Institute on Alcohol Abuse and Alcoholism (NIAAA) of U.S.A. and National Natural Science Foundation of China (NSFC).

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Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway

Cited by 33 publications

References 64 publications

Emergence and propagation of epistasis in metabolic networks

Emergence and propagation of epistasis in metabolic networks

Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation

Epistatic evidence for gender-dependant slow neurotransmission signalling in substance use disorders: PPP1R12B versus PPP1R1B

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