Abstract

Inter-individual variation in regulatory circuits controlling gene expression is a powerful source of functional information. The study of associations among genetic variants and gene expression provides important insights about cell circuitry but cannot specify whether and when potential variants dynamically alter their genetic effect during the course of response. Here we develop a computational procedure that captures temporal changes in genetic effects, and apply it to analyze transcription during inhibition of the TOR signaling pathway in segregating yeast cells. We found a high-order coordination of gene modules: sets of genes co-associated with the same genetic variant and sharing a common temporal genetic effect pattern. The temporal genetic effects of some modules represented a single state-transitioning pattern; for example, at 10–30 minutes following stimulation, genetic effects in the phosphate utilization module attained a characteristic transition to a new steady state. In contrast, another module showed an impulse pattern of genetic effects; for example, in the poor nitrogen sources utilization module, a spike up of a genetic effect at 10–20 minutes following stimulation reflected inter-individual variation in the timing (rather than magnitude) of response. Our analysis suggests that the same mechanism typically leads to both inter-individual variation and the temporal genetic effect pattern in a module. Our methodology provides a quantitative genetic approach to studying the molecular mechanisms that shape dynamic changes in transcriptional responses.

Highlights

  • Inherited variation in gene expression is likely to have a major effect on cellular and disease phenotypes, and may allow the underlying DNA polymorphisms to be identified [1]

  • Genetic variation is postulated to play a major role in transcriptional responses to stimulation

  • Our findings suggest that associations of genes with the same genetic variant often occur via the same timing of state transition in genetic effects

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Summary

Introduction

Inherited variation in gene expression is likely to have a major effect on cellular and disease phenotypes, and may allow the underlying DNA polymorphisms (genetic variants) to be identified [1]. Dynamic effect patterns may be described in terms of the shape of changes in genetic effects over time. A linear-like genetic effect pattern (Fig. 1B) reflects a gradual change in the magnitude of genetic effects, whereas in a non-linear genetic effect pattern (Fig. 1C), the level of genetic effect is sustained in some time periods and spikes up or down in others (Fig. 1C). Transcription responses across individuals have been monitored only in two time points (before and after stimulation) and the dynamics of changes in genetic effects over time could not be characterized [4,5,6,7,8,9]

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