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Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits.

ABSTRACT: Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect size genes could cumulatively play a substantial role in pathway function. Here, we determine the number, strength, and identity of all non-essential test genes that affect two quantitative galactose-responsive traits in addition to re-analyzing two previously screened quantitative traits. We find that over a quarter of assayed genes have a detectable, quantitative effect on phenotype. Despite their ubiquity, these genes are enriched in core cellular processes in a trait-specific manner. In a simulated population with 50% frequency of all-or-none alleles, we show that small effect size alleles are capable of contributing more to trait variation than alleles in a canonical, large effect size pathway. In total, by demonstrating that the genes effecting quantitative traits can be highly distributed and interconnected, this work challenges the concept of pathways as modular and independent.

SUBMITTER: Hua B

PROVIDER: S-EPMC6319666 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits.

Hua Bo B Springer Michael M

Cell systems 20181201 6

Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect size genes could cumulatively play a substantial role in pathway function. Here, we determine the number, strength, and identity of all non-essential test genes that affect two quantitative galactose-responsive traits in addition to re-analyzing two previously screened quantitative traits. We find ...[more]

PMID: 30579728

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Project description:BackgroundDetection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations.ResultsLarge QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait.ConclusionsOur results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs.

Dataset Information

Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits.

Publications

Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits.

Similar Datasets

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