Fatty acid synthases are dynamic ensembles of enzymes that can efficiently biosynthesize long hydrocarbon chains. Here we visualize the interaction between the Escherichia coli acyl carrier protein (AcpP) and β-ketoacyl-ACP-synthase I (FabB) using X-ray crystallography, NMR, and MD simulations. We leveraged this structural information to alter lipid profiles in vivo and provide a molecular basis for how protein-protein interactions can regulate the fatty acid profile in E. coli. The E. coli fatty acid synthase (FAS) produces fatty acids through an iterative cycle via the

In diploid species, genetic loci can show additive, dominance, and epistatic effects. To characterize the contributions of these different types of genetic effects to heritable traits, we use a double barcoding system to generate and phenotype a panel of ~200,000 diploid yeast strains that can be partitioned into hundreds of interrelated families. This experiment enables the detection of thousands of epistatic loci, many whose effects vary across families. Here, we show traits are largely specified by a small number of hub loci with major additive and dominance effects, and pervasive epistasis. Genetic background commonly influences both the additive and dominance effects of loci, with multiple modifiers typically involved. The most prominent dominance modifier in our data is the mating locus, which has no effect on its own. Our findings show that the interplay between additivity, dominance, and epistasis underlies a complex genotype-to-phenotype map in diploids.

We used a double barcoding system to generate and phenotype a panel of ~200,000 diploid yeast segregants that can be partitioned into hundreds of interrelated families. This experimental design enabled the detection of thousands of genetic interactions and many loci whose effects vary across families. Traits were largely specified by a small number of hub loci with major additive and dominance effects, and pervasive epistasis. Genetic background commonly influenced both the additive and dominance effects of loci, with multiple modifiers typically involved. The most prominent dominance modifier was the mating locus, which had no effect on its own. Our findings show that the interplay between additivity, dominance, and epistasis underlies a complex genotype-to-phenotype map in diploids.

Mutations often have different effects in genetically distinct individuals. Epistasis between mutations and segregating loci is known to be a major contributor to these background effects, but the architecture of these genetic interactions remains largely unknown. Here, we characterize how segregating loci in a cross of two Saccharomyces cerevisiae strains impact growth following the deletion of the histone deacetylase HOS3. The functions of HOS3 are not well understood and historically its deletion has shown little effect on reference strains. However, we map two loci that genetically interact with HOS3 and each other to produce a broad range of responses to the deletion, including near inviability. Although these interactions explain nearly all of the deletion's expressivity, their penetrance depends on a liability threshold involving at least 11 additional nuclear and mitochondrial loci. Multiple lines of evidence imply the deletion uncovers genetically complex changes in translation and genome stability in the mitochondria, suggesting a novel connection between Hos3-mediated deacetylation and the mitochondria. These results provide a valuable example of the complicated and unexpected mechanisms that can cause background effects in genetically diverse populations, and show how characterization of background effects can provide new insights into gene function. One Sentence SummaryComplex genetics shape a mutation's penetrance and expressivity. Main TextMutations frequently exhibit different effects in genetically distinct individuals (or 'background effects') (1-3). Variable expressivity and incomplete penetrance are two of the most prevalent forms of background effects (4). Variable expressivity occurs when a mutation shows quantitatively different effects among distinct individuals, while incomplete penetrance occurs when a mutation shows an effect in some individuals but not others (4). Variable expressivity and incomplete penetrance are not mutually exclusive; a mutation may only show an effect in certain individuals, but that effect might vary in severity among affected individuals (4). Both variable expressivity and incomplete penetrance can arise due to a variety of reasons, including genetic interactions (or epistasis) between a mutation and segregating loci (4), environmental influences on a mutation (4), and stochastic noise (5).Here, we focus on the contribution of epistasis to expressivity and penetrance. This topic has proven difficult to study, in large part because populations harbor substantial genetic diversity, which can facilitate complex and highly polygenic forms of epistasis with mutations (6-18). These genetic interactions are difficult to map in natural populations (6-18) and it is unclear how well they are modeled by combinations of lab-induced mutations in otherwise isogenic strain backgrounds (19,20). Fortunately, the budding yeast Saccharomyces cerevisiae is a potentially powerful system for studying the expressivity and penetrance of mutations. In this organism, phenotyping of isoge...

Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutation’s expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutation’s expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation.