Limits...
Dissecting dynamic genetic variation that controls temporal gene response in yeast.

Brodt A, Botzman M, David E, Gat-Viks I - PLoS Comput. Biol. (2014)

Bottom Line: 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.Our analysis suggests that the same mechanism typically leads to both inter-individual variation and the temporal genetic effect pattern in a module.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel.

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.

Show MeSH

Related in: MedlinePlus

Temporal genetic effect patterns.Schematic view of gene expression patterns (top) and the relevant temporal genetic effects for these genes (bottom). The cartoons demonstrate a non-dynamic genetic effect pattern (A), a dynamic, linear genetic effect pattern (B), and a dynamic, non-linear genetic effect pattern (C). Top: shown are gene expression levels (y-axis) during a response to stimulation (x-axis). Each curve represents measurements in a different homozygous animal strain (segregants), where brown or black indicates whether the genotype of the associated genetic variant is  or , respectively, in each strain. Bottom: shown are genetic effects (that is, the change in gene expression between the  -carrying and  -carrying strains, y-axis) during a response to stimulation (x-axis). (C) Examples of non-linear genetic effect patterns, which are the focus of this study, including (left to right) a single state-transitioning pattern, which may be followed by a sustained new level of genetic effect, a single-pulse (impulse) pattern, and a multiple-pulse (complex) genetic effect pattern.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4256076&req=5

pcbi-1003984-g001: Temporal genetic effect patterns.Schematic view of gene expression patterns (top) and the relevant temporal genetic effects for these genes (bottom). The cartoons demonstrate a non-dynamic genetic effect pattern (A), a dynamic, linear genetic effect pattern (B), and a dynamic, non-linear genetic effect pattern (C). Top: shown are gene expression levels (y-axis) during a response to stimulation (x-axis). Each curve represents measurements in a different homozygous animal strain (segregants), where brown or black indicates whether the genotype of the associated genetic variant is or , respectively, in each strain. Bottom: shown are genetic effects (that is, the change in gene expression between the -carrying and -carrying strains, y-axis) during a response to stimulation (x-axis). (C) Examples of non-linear genetic effect patterns, which are the focus of this study, including (left to right) a single state-transitioning pattern, which may be followed by a sustained new level of genetic effect, a single-pulse (impulse) pattern, and a multiple-pulse (complex) genetic effect pattern.

Mentions: 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]. The genetic effect of a particular variant on a certain RNA is the quantitative change in gene expression that is associated with changing the variant's genotype (allele). Two recent studies have demonstrated that genetic effects on longitudinal gene expression data might be either stable – where the genetic effect is similar at all time points (a non-dynamic effect pattern; Fig. 1A) – or flexible, changing the magnitude of effect during time points (a dynamic effect pattern; Fig. 1B,C) [2], [3].


Dissecting dynamic genetic variation that controls temporal gene response in yeast.

Brodt A, Botzman M, David E, Gat-Viks I - PLoS Comput. Biol. (2014)

Temporal genetic effect patterns.Schematic view of gene expression patterns (top) and the relevant temporal genetic effects for these genes (bottom). The cartoons demonstrate a non-dynamic genetic effect pattern (A), a dynamic, linear genetic effect pattern (B), and a dynamic, non-linear genetic effect pattern (C). Top: shown are gene expression levels (y-axis) during a response to stimulation (x-axis). Each curve represents measurements in a different homozygous animal strain (segregants), where brown or black indicates whether the genotype of the associated genetic variant is  or , respectively, in each strain. Bottom: shown are genetic effects (that is, the change in gene expression between the  -carrying and  -carrying strains, y-axis) during a response to stimulation (x-axis). (C) Examples of non-linear genetic effect patterns, which are the focus of this study, including (left to right) a single state-transitioning pattern, which may be followed by a sustained new level of genetic effect, a single-pulse (impulse) pattern, and a multiple-pulse (complex) genetic effect pattern.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256076&req=5

pcbi-1003984-g001: Temporal genetic effect patterns.Schematic view of gene expression patterns (top) and the relevant temporal genetic effects for these genes (bottom). The cartoons demonstrate a non-dynamic genetic effect pattern (A), a dynamic, linear genetic effect pattern (B), and a dynamic, non-linear genetic effect pattern (C). Top: shown are gene expression levels (y-axis) during a response to stimulation (x-axis). Each curve represents measurements in a different homozygous animal strain (segregants), where brown or black indicates whether the genotype of the associated genetic variant is or , respectively, in each strain. Bottom: shown are genetic effects (that is, the change in gene expression between the -carrying and -carrying strains, y-axis) during a response to stimulation (x-axis). (C) Examples of non-linear genetic effect patterns, which are the focus of this study, including (left to right) a single state-transitioning pattern, which may be followed by a sustained new level of genetic effect, a single-pulse (impulse) pattern, and a multiple-pulse (complex) genetic effect pattern.
Mentions: 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]. The genetic effect of a particular variant on a certain RNA is the quantitative change in gene expression that is associated with changing the variant's genotype (allele). Two recent studies have demonstrated that genetic effects on longitudinal gene expression data might be either stable – where the genetic effect is similar at all time points (a non-dynamic effect pattern; Fig. 1A) – or flexible, changing the magnitude of effect during time points (a dynamic effect pattern; Fig. 1B,C) [2], [3].

Bottom Line: 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.Our analysis suggests that the same mechanism typically leads to both inter-individual variation and the temporal genetic effect pattern in a module.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel.

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.

Show MeSH
Related in: MedlinePlus