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Variable Glutamine-Rich Repeats Modulate Transcription Factor Activity.

Gemayel R, Chavali S, Pougach K, Legendre M, Zhu B, Boeynaems S, van der Zande E, Gevaert K, Rousseau F, Schymkowitz J, Babu MM, Verstrepen KJ - Mol. Cell (2015)

Bottom Line: Incremental changes in the number of repeats in the yeast transcriptional regulator Ssn6 (Cyc8) result in systematic, repeat-length-dependent variation in expression of target genes that result in direct phenotypic changes.Quantitative proteomic analysis reveals that the Ssn6 repeats affect its solubility and interactions with Tup1 and other regulators.Thus, Q-rich repeats are dynamic functional domains that modulate a regulator's innate function, with the inherent risk of pathogenic repeat expansions.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Systems Biology, VIB, Gaston Geenslaan 1, 3001 Heverlee, Belgium; Laboratory of Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), Department M2S, KU Leuven, Gaston Geenslaan 1, 3001 Heverlee, Belgium.

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Related in: MedlinePlus

Q-Rich TFs Influence Expression Variation of Targets across Different Timescales(A) Yeast TRN reconstructed based on data from Balaji et al. (2006) and Venters et al. (2011). For the latter, promoter occupancy cutoff of at least 3-fold higher than background was considered. Based on the presence of Q-rich repeats, the TFs and their targets were categorized.(B) Distribution of variation of expression among species and strains, across generations, and among genetically identical cells, of targets regulated by non-repeat containing TFs (NR-TFs) and TFs with Q-rich repeats (Q-rich TFs). The boxes represent the first and third quartile with the median at the black line. The notches correspond to ∼95% confidence interval for the median. The whiskers show data points up to 1.5 times the interquartile range. Statistical significance was assessed using Wilcoxon rank sum test. The effect sizes are represented by the common language effect size (CLES) statistic, describing the probability that a randomly selected target of Q-rich TFs will have higher expression variation than a randomly selected target of NR-TFs.(C) Influence of expression plasticity on gene-expression variability. Distribution of expression plasticity of NR-TF and Q-rich TF targets is shown. The panels represent the median of expression variation across different timescales of targets of NR-TFs and Q-rich TFs in low (bottom 33.3%), medium (middle 33.3%), and high (top 33.3%) expression plasticity bins defined using tertile cuts of the distribution of all genes. p values were estimated using Wilcoxon rank sum test.(D) Proposed model of target gene-expression variability over different time-scales facilitated by Q-rich TFs among genes with high dynamic expression modulation.(E) Enrichment of targets with expression variation across different timescales for each Q-rich TF. Enrichment of targets with expression variation values higher than that of median of all Q-rich TF targets was tested using a permutation test. In each permutation, every target of a Q-rich TF was replaced with a random target from the TRN. The number of random targets with expression variation values equal or higher than the median of Q-rich TF targets was noted for 10,000 iterations. The color intensity in the heatmap represents Z scores, which indicate the distance of the number of real targets to the mean of random expectation in SD units. Statistically significant enrichment is highlighted with a red border. p values were estimated as the ratio of the average number of random targets with expression variation more than or equal to that of Q-rich TF targets over the total number of random samples (10,000).See also Figures S1 and S2 and Tables S1 and S2.
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fig1: Q-Rich TFs Influence Expression Variation of Targets across Different Timescales(A) Yeast TRN reconstructed based on data from Balaji et al. (2006) and Venters et al. (2011). For the latter, promoter occupancy cutoff of at least 3-fold higher than background was considered. Based on the presence of Q-rich repeats, the TFs and their targets were categorized.(B) Distribution of variation of expression among species and strains, across generations, and among genetically identical cells, of targets regulated by non-repeat containing TFs (NR-TFs) and TFs with Q-rich repeats (Q-rich TFs). The boxes represent the first and third quartile with the median at the black line. The notches correspond to ∼95% confidence interval for the median. The whiskers show data points up to 1.5 times the interquartile range. Statistical significance was assessed using Wilcoxon rank sum test. The effect sizes are represented by the common language effect size (CLES) statistic, describing the probability that a randomly selected target of Q-rich TFs will have higher expression variation than a randomly selected target of NR-TFs.(C) Influence of expression plasticity on gene-expression variability. Distribution of expression plasticity of NR-TF and Q-rich TF targets is shown. The panels represent the median of expression variation across different timescales of targets of NR-TFs and Q-rich TFs in low (bottom 33.3%), medium (middle 33.3%), and high (top 33.3%) expression plasticity bins defined using tertile cuts of the distribution of all genes. p values were estimated using Wilcoxon rank sum test.(D) Proposed model of target gene-expression variability over different time-scales facilitated by Q-rich TFs among genes with high dynamic expression modulation.(E) Enrichment of targets with expression variation across different timescales for each Q-rich TF. Enrichment of targets with expression variation values higher than that of median of all Q-rich TF targets was tested using a permutation test. In each permutation, every target of a Q-rich TF was replaced with a random target from the TRN. The number of random targets with expression variation values equal or higher than the median of Q-rich TF targets was noted for 10,000 iterations. The color intensity in the heatmap represents Z scores, which indicate the distance of the number of real targets to the mean of random expectation in SD units. Statistically significant enrichment is highlighted with a red border. p values were estimated as the ratio of the average number of random targets with expression variation more than or equal to that of Q-rich TF targets over the total number of random samples (10,000).See also Figures S1 and S2 and Tables S1 and S2.

Mentions: We scanned the open reading frames of all protein coding genes in genomes that span the eukaryotic diversity (yeast, fruit fly, zebrafish, mouse, human) using Tandem Repeat Finder (Benson, 1999). We find that 14%–20% of eukaryotic genes are enriched in TRs (Table S1). We defined repeats as Q rich if at least 85% of their translated sequence comprised glutamine residues (Table S1). Gene ontology analysis of these Q-rich genes versus all genes with repeats revealed a significant enrichment for regulatory functions such as transcriptional regulation and chromatin modification (Table S2). This is consistent with previous studies investigating the functional enrichment of repeat-containing proteins in various eukaryotic genomes (Faux et al., 2005; Gemayel et al., 2010; Legendre et al., 2007; Young et al., 2000). TRs are often unstable, with even closely related individuals or species showing differences in the number of repeated units in a “homologous” TR. This prompted us to ask whether repeats in transcription factors (TFs) can influence the variability of target gene expression. To address this, we first reconstructed a comprehensive yeast transcriptional regulatory network (TRN) by combining a previously published TRN (Balaji et al., 2006) with the recent genome-wide in vivo binding map of yeast regulatory proteins (Venters et al., 2011) (Figure 1A). We classified the target genes as those regulated by Q-rich TFs and those by non-repeat containing TFs (NR-TFs). We next analyzed gene-expression variation over long, intermediate, or short timescales by examining published datasets on yeast gene-expression variation across species (Tirosh et al., 2006), among strains (Choi and Kim, 2008), across generations (Landry et al., 2007), and between genetically identical cells at an instant (Newman et al., 2006). We find that target genes that are regulated by Q-rich TFs show significantly higher levels of expression divergence, expression variability, mutational variance, and expression noise than targets of NR-TFs (Figure 1B). Importantly, these differences in expression patterns of the targets are not explained by changes in expression patterns of the respective TFs (Figure S1A) or by differences in average transcript levels of targets (Figure S2A). Even if we only consider TFs with low expression variation across multiple time scales, the targets of Q-rich TFs still show higher expression divergence and variability and higher mutational variance than targets of NR-TFs (Figure S1B).


Variable Glutamine-Rich Repeats Modulate Transcription Factor Activity.

Gemayel R, Chavali S, Pougach K, Legendre M, Zhu B, Boeynaems S, van der Zande E, Gevaert K, Rousseau F, Schymkowitz J, Babu MM, Verstrepen KJ - Mol. Cell (2015)

Q-Rich TFs Influence Expression Variation of Targets across Different Timescales(A) Yeast TRN reconstructed based on data from Balaji et al. (2006) and Venters et al. (2011). For the latter, promoter occupancy cutoff of at least 3-fold higher than background was considered. Based on the presence of Q-rich repeats, the TFs and their targets were categorized.(B) Distribution of variation of expression among species and strains, across generations, and among genetically identical cells, of targets regulated by non-repeat containing TFs (NR-TFs) and TFs with Q-rich repeats (Q-rich TFs). The boxes represent the first and third quartile with the median at the black line. The notches correspond to ∼95% confidence interval for the median. The whiskers show data points up to 1.5 times the interquartile range. Statistical significance was assessed using Wilcoxon rank sum test. The effect sizes are represented by the common language effect size (CLES) statistic, describing the probability that a randomly selected target of Q-rich TFs will have higher expression variation than a randomly selected target of NR-TFs.(C) Influence of expression plasticity on gene-expression variability. Distribution of expression plasticity of NR-TF and Q-rich TF targets is shown. The panels represent the median of expression variation across different timescales of targets of NR-TFs and Q-rich TFs in low (bottom 33.3%), medium (middle 33.3%), and high (top 33.3%) expression plasticity bins defined using tertile cuts of the distribution of all genes. p values were estimated using Wilcoxon rank sum test.(D) Proposed model of target gene-expression variability over different time-scales facilitated by Q-rich TFs among genes with high dynamic expression modulation.(E) Enrichment of targets with expression variation across different timescales for each Q-rich TF. Enrichment of targets with expression variation values higher than that of median of all Q-rich TF targets was tested using a permutation test. In each permutation, every target of a Q-rich TF was replaced with a random target from the TRN. The number of random targets with expression variation values equal or higher than the median of Q-rich TF targets was noted for 10,000 iterations. The color intensity in the heatmap represents Z scores, which indicate the distance of the number of real targets to the mean of random expectation in SD units. Statistically significant enrichment is highlighted with a red border. p values were estimated as the ratio of the average number of random targets with expression variation more than or equal to that of Q-rich TF targets over the total number of random samples (10,000).See also Figures S1 and S2 and Tables S1 and S2.
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fig1: Q-Rich TFs Influence Expression Variation of Targets across Different Timescales(A) Yeast TRN reconstructed based on data from Balaji et al. (2006) and Venters et al. (2011). For the latter, promoter occupancy cutoff of at least 3-fold higher than background was considered. Based on the presence of Q-rich repeats, the TFs and their targets were categorized.(B) Distribution of variation of expression among species and strains, across generations, and among genetically identical cells, of targets regulated by non-repeat containing TFs (NR-TFs) and TFs with Q-rich repeats (Q-rich TFs). The boxes represent the first and third quartile with the median at the black line. The notches correspond to ∼95% confidence interval for the median. The whiskers show data points up to 1.5 times the interquartile range. Statistical significance was assessed using Wilcoxon rank sum test. The effect sizes are represented by the common language effect size (CLES) statistic, describing the probability that a randomly selected target of Q-rich TFs will have higher expression variation than a randomly selected target of NR-TFs.(C) Influence of expression plasticity on gene-expression variability. Distribution of expression plasticity of NR-TF and Q-rich TF targets is shown. The panels represent the median of expression variation across different timescales of targets of NR-TFs and Q-rich TFs in low (bottom 33.3%), medium (middle 33.3%), and high (top 33.3%) expression plasticity bins defined using tertile cuts of the distribution of all genes. p values were estimated using Wilcoxon rank sum test.(D) Proposed model of target gene-expression variability over different time-scales facilitated by Q-rich TFs among genes with high dynamic expression modulation.(E) Enrichment of targets with expression variation across different timescales for each Q-rich TF. Enrichment of targets with expression variation values higher than that of median of all Q-rich TF targets was tested using a permutation test. In each permutation, every target of a Q-rich TF was replaced with a random target from the TRN. The number of random targets with expression variation values equal or higher than the median of Q-rich TF targets was noted for 10,000 iterations. The color intensity in the heatmap represents Z scores, which indicate the distance of the number of real targets to the mean of random expectation in SD units. Statistically significant enrichment is highlighted with a red border. p values were estimated as the ratio of the average number of random targets with expression variation more than or equal to that of Q-rich TF targets over the total number of random samples (10,000).See also Figures S1 and S2 and Tables S1 and S2.
Mentions: We scanned the open reading frames of all protein coding genes in genomes that span the eukaryotic diversity (yeast, fruit fly, zebrafish, mouse, human) using Tandem Repeat Finder (Benson, 1999). We find that 14%–20% of eukaryotic genes are enriched in TRs (Table S1). We defined repeats as Q rich if at least 85% of their translated sequence comprised glutamine residues (Table S1). Gene ontology analysis of these Q-rich genes versus all genes with repeats revealed a significant enrichment for regulatory functions such as transcriptional regulation and chromatin modification (Table S2). This is consistent with previous studies investigating the functional enrichment of repeat-containing proteins in various eukaryotic genomes (Faux et al., 2005; Gemayel et al., 2010; Legendre et al., 2007; Young et al., 2000). TRs are often unstable, with even closely related individuals or species showing differences in the number of repeated units in a “homologous” TR. This prompted us to ask whether repeats in transcription factors (TFs) can influence the variability of target gene expression. To address this, we first reconstructed a comprehensive yeast transcriptional regulatory network (TRN) by combining a previously published TRN (Balaji et al., 2006) with the recent genome-wide in vivo binding map of yeast regulatory proteins (Venters et al., 2011) (Figure 1A). We classified the target genes as those regulated by Q-rich TFs and those by non-repeat containing TFs (NR-TFs). We next analyzed gene-expression variation over long, intermediate, or short timescales by examining published datasets on yeast gene-expression variation across species (Tirosh et al., 2006), among strains (Choi and Kim, 2008), across generations (Landry et al., 2007), and between genetically identical cells at an instant (Newman et al., 2006). We find that target genes that are regulated by Q-rich TFs show significantly higher levels of expression divergence, expression variability, mutational variance, and expression noise than targets of NR-TFs (Figure 1B). Importantly, these differences in expression patterns of the targets are not explained by changes in expression patterns of the respective TFs (Figure S1A) or by differences in average transcript levels of targets (Figure S2A). Even if we only consider TFs with low expression variation across multiple time scales, the targets of Q-rich TFs still show higher expression divergence and variability and higher mutational variance than targets of NR-TFs (Figure S1B).

Bottom Line: Incremental changes in the number of repeats in the yeast transcriptional regulator Ssn6 (Cyc8) result in systematic, repeat-length-dependent variation in expression of target genes that result in direct phenotypic changes.Quantitative proteomic analysis reveals that the Ssn6 repeats affect its solubility and interactions with Tup1 and other regulators.Thus, Q-rich repeats are dynamic functional domains that modulate a regulator's innate function, with the inherent risk of pathogenic repeat expansions.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Systems Biology, VIB, Gaston Geenslaan 1, 3001 Heverlee, Belgium; Laboratory of Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), Department M2S, KU Leuven, Gaston Geenslaan 1, 3001 Heverlee, Belgium.

No MeSH data available.


Related in: MedlinePlus