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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.

No MeSH data available.


Related in: MedlinePlus

Whole-Genome Transcriptomics Reveal that Variation in the SSN6 TR2 Region Influences the Expression of Target Genes(A) Expression profiles for genes (rows) in different SSN6 TR2 variants (columns) in carbon-starved (left) or glucose-rich medium (right) measured by RNA-seq. The data are represented as relative to the expression levels in the WT (TR2-63), and similar colors indicate similar changes in expression relative to the WT strain. Enriched biological processes (Gene Ontology [GO] categories) of the target genes are shown (p < 0.05). Genes highlighted with arrows are key genes involved in alternative carbon transport and catabolism. The SUC2 gene that encodes the major sucrose-hydrolyzing enzyme is also highlighted. See also Figure S4 and Table S4.(B) Many genes showing SSN6 repeat-dependent variation in expression are known targets of Ssn6. The figure represents a functional network of all genes whose expression is affected by SSN6 TR2 variation, with edge colors representing different types of interactions.(C) Venn diagrams showing the overlap between genes whose expression is SSN6 TR2-dependent, genes with Ssn6-bound promoters (enrichment of 1.5-fold over background) (Venters et al., 2011) and genes showing de-repression upon TUP1 depletion from the nucleus (Wong and Struhl, 2011). The overlapping p values between our RNA-seq dataset and the other datasets were estimated by a chi-square test with Yates’ correction.(D) SSN6 TR2 variation confers environment-dependent changes in fitness. The correlation between fitness and SSN6 TR2 number was assessed by a linear regression test. Data points represent mean ± SD, n = 3.
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fig3: Whole-Genome Transcriptomics Reveal that Variation in the SSN6 TR2 Region Influences the Expression of Target Genes(A) Expression profiles for genes (rows) in different SSN6 TR2 variants (columns) in carbon-starved (left) or glucose-rich medium (right) measured by RNA-seq. The data are represented as relative to the expression levels in the WT (TR2-63), and similar colors indicate similar changes in expression relative to the WT strain. Enriched biological processes (Gene Ontology [GO] categories) of the target genes are shown (p < 0.05). Genes highlighted with arrows are key genes involved in alternative carbon transport and catabolism. The SUC2 gene that encodes the major sucrose-hydrolyzing enzyme is also highlighted. See also Figure S4 and Table S4.(B) Many genes showing SSN6 repeat-dependent variation in expression are known targets of Ssn6. The figure represents a functional network of all genes whose expression is affected by SSN6 TR2 variation, with edge colors representing different types of interactions.(C) Venn diagrams showing the overlap between genes whose expression is SSN6 TR2-dependent, genes with Ssn6-bound promoters (enrichment of 1.5-fold over background) (Venters et al., 2011) and genes showing de-repression upon TUP1 depletion from the nucleus (Wong and Struhl, 2011). The overlapping p values between our RNA-seq dataset and the other datasets were estimated by a chi-square test with Yates’ correction.(D) SSN6 TR2 variation confers environment-dependent changes in fitness. The correlation between fitness and SSN6 TR2 number was assessed by a linear regression test. Data points represent mean ± SD, n = 3.

Mentions: To investigate the direct consequences of SSN6 repeat variation, we created a series of variants of the SSN6 TR1 and TR2 regions in the reference yeast strain Sigma1278b (Figure 2D). These variants included natural repeat lengths, as well as extremely short and long forms. This set of mutants allowed us to explore the outcomes of natural variability, as well as complete loss or long expansions of Q-rich repeats in Ssn6 controlled by its native promoter, in an otherwise isogenic background. As TR2 shows higher variability within the natural strains, we chose nine TR2 variants (natural variations: TR2-33, TR2-55, TR2-63; short variants: TR2-0, TR2-14, TR2-20, TR2-27; long variants: TR2-90, TR2-105) to investigate the influence of Q-rich repeats on gene-expression regulation. Using RNA sequencing, we profiled the transcriptome of the SSN6 TR2 variants in glucose-rich medium and during carbon starvation. As many as 153 genes showed significant changes in expression (log2 fold-change cutoff of 0.8 and false discovery rate (FDR) p < 0.01) in either the SSN6 TR2 deletion (TR2-0) or expansion (TR2-105) variant compared with the WT strain (TR2-63) in either culture conditions (Table S4). To further discriminate between noise and targets whose regulation is directly influenced by SSN6 TR2 number variation, we computed the autocorrelation function, which detects non-randomness in data, considering the SSN6 TR2 number as a series. By selecting SSN6 target genes that showed an autocorrelation coefficient ≥0.2 and the same expression trend in at least two consecutive repeat variants, we identified 89 targets whose regulation was TR2 length dependent (Figure 3A).


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)

Whole-Genome Transcriptomics Reveal that Variation in the SSN6 TR2 Region Influences the Expression of Target Genes(A) Expression profiles for genes (rows) in different SSN6 TR2 variants (columns) in carbon-starved (left) or glucose-rich medium (right) measured by RNA-seq. The data are represented as relative to the expression levels in the WT (TR2-63), and similar colors indicate similar changes in expression relative to the WT strain. Enriched biological processes (Gene Ontology [GO] categories) of the target genes are shown (p < 0.05). Genes highlighted with arrows are key genes involved in alternative carbon transport and catabolism. The SUC2 gene that encodes the major sucrose-hydrolyzing enzyme is also highlighted. See also Figure S4 and Table S4.(B) Many genes showing SSN6 repeat-dependent variation in expression are known targets of Ssn6. The figure represents a functional network of all genes whose expression is affected by SSN6 TR2 variation, with edge colors representing different types of interactions.(C) Venn diagrams showing the overlap between genes whose expression is SSN6 TR2-dependent, genes with Ssn6-bound promoters (enrichment of 1.5-fold over background) (Venters et al., 2011) and genes showing de-repression upon TUP1 depletion from the nucleus (Wong and Struhl, 2011). The overlapping p values between our RNA-seq dataset and the other datasets were estimated by a chi-square test with Yates’ correction.(D) SSN6 TR2 variation confers environment-dependent changes in fitness. The correlation between fitness and SSN6 TR2 number was assessed by a linear regression test. Data points represent mean ± SD, n = 3.
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fig3: Whole-Genome Transcriptomics Reveal that Variation in the SSN6 TR2 Region Influences the Expression of Target Genes(A) Expression profiles for genes (rows) in different SSN6 TR2 variants (columns) in carbon-starved (left) or glucose-rich medium (right) measured by RNA-seq. The data are represented as relative to the expression levels in the WT (TR2-63), and similar colors indicate similar changes in expression relative to the WT strain. Enriched biological processes (Gene Ontology [GO] categories) of the target genes are shown (p < 0.05). Genes highlighted with arrows are key genes involved in alternative carbon transport and catabolism. The SUC2 gene that encodes the major sucrose-hydrolyzing enzyme is also highlighted. See also Figure S4 and Table S4.(B) Many genes showing SSN6 repeat-dependent variation in expression are known targets of Ssn6. The figure represents a functional network of all genes whose expression is affected by SSN6 TR2 variation, with edge colors representing different types of interactions.(C) Venn diagrams showing the overlap between genes whose expression is SSN6 TR2-dependent, genes with Ssn6-bound promoters (enrichment of 1.5-fold over background) (Venters et al., 2011) and genes showing de-repression upon TUP1 depletion from the nucleus (Wong and Struhl, 2011). The overlapping p values between our RNA-seq dataset and the other datasets were estimated by a chi-square test with Yates’ correction.(D) SSN6 TR2 variation confers environment-dependent changes in fitness. The correlation between fitness and SSN6 TR2 number was assessed by a linear regression test. Data points represent mean ± SD, n = 3.
Mentions: To investigate the direct consequences of SSN6 repeat variation, we created a series of variants of the SSN6 TR1 and TR2 regions in the reference yeast strain Sigma1278b (Figure 2D). These variants included natural repeat lengths, as well as extremely short and long forms. This set of mutants allowed us to explore the outcomes of natural variability, as well as complete loss or long expansions of Q-rich repeats in Ssn6 controlled by its native promoter, in an otherwise isogenic background. As TR2 shows higher variability within the natural strains, we chose nine TR2 variants (natural variations: TR2-33, TR2-55, TR2-63; short variants: TR2-0, TR2-14, TR2-20, TR2-27; long variants: TR2-90, TR2-105) to investigate the influence of Q-rich repeats on gene-expression regulation. Using RNA sequencing, we profiled the transcriptome of the SSN6 TR2 variants in glucose-rich medium and during carbon starvation. As many as 153 genes showed significant changes in expression (log2 fold-change cutoff of 0.8 and false discovery rate (FDR) p < 0.01) in either the SSN6 TR2 deletion (TR2-0) or expansion (TR2-105) variant compared with the WT strain (TR2-63) in either culture conditions (Table S4). To further discriminate between noise and targets whose regulation is directly influenced by SSN6 TR2 number variation, we computed the autocorrelation function, which detects non-randomness in data, considering the SSN6 TR2 number as a series. By selecting SSN6 target genes that showed an autocorrelation coefficient ≥0.2 and the same expression trend in at least two consecutive repeat variants, we identified 89 targets whose regulation was TR2 length dependent (Figure 3A).

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