Project description:Eleven genome wide microarrays containing the predicted coding sequences (putative genes) for the ciliated protozoan Tetrahymena thermophila used to study gene expression in conjugation cells (C-0, C-15m, C-2, C-4, C-6, C-8, C-10, C-12, C-14, C-16, C-18). Combined these eleven microarrays with 50 microarrays described in Miao et al (2009) and other 6 microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient, the Spearman correlation coefficient and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast, and the CLR network was found to be the best network, with a Z-score threshold 3.49. Then the TGN was partitioned, and 55 modules were found. In addition, analysis for the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and found evidence indicating that some of these were involved in the same process in Tetrahymena as in human.
Project description:A conserved hallmark of eukaryotic chromatin architecture is the distinctive array of well-positioned nucleosomes downstream of transcription start sites (TSS). Recent studies indicate that trans-acting factors establish this stereotypical array. Here, we present the first genome-wide in vitro and in vivo nucleosome maps for the ciliate Tetrahymena thermophila. In contrast with previous studies in yeast, we find that the stereotypical nucleosome array is preserved in the in vitro reconstituted map, which is governed only by the DNA sequence preferences of nucleosomes. Remarkably, this average in vitro pattern arises from subsets of nucleosomes, rather than the whole array, being present in individual Tetrahymena genes. Variation in GC content contributes to the positioning of these sequence-directed nucleosomes, and affects codon usage and amino acid composition in genes. We propose that these ‘seed’ nucleosomes may aid the AT-rich Tetrahymena genome – which is intrinsically unfavorable for nucleosome formation – in establishing nucleosome arrays in vivo in concert with trans-acting factors, while minimizing changes to the coding sequences they are embedded within.
Project description:In the ciliated protozoan Tetrahymena, an RNAi-mediated feedback loop is important for assembling heterochromatin on the sequences that are removed from the somatic genome by programmed DNA elimination. Because heterochromatin is formed exclusively on the eliminated sequences, some mechanism must inhibit this feedback loop at the boundaries of the eliminated sequences. In this study, we show that the HP1-like protein Coi6p, its interaction partners Coi7p and Lia5p, and the histone demethylase Jmj1p are crucial for confining the production of small RNAs to the eliminated sequences.
Project description:In the ciliated protozoan Tetrahymena, an RNAi-mediated feedback loop is important for assembling heterochromatin on the sequences that are removed from the somatic genome by programmed DNA elimination. Because heterochromatin is formed exclusively on the eliminated sequences, some mechanism must inhibit this feedback loop at the boundaries of the eliminated sequences. In this study, we show that the HP1-like protein Coi6p, its interaction partners Coi7p and Lia5p, and the histone demethylase Jmj1p are crucial for confining the formation of heterochromatin to the eliminated sequences.
Project description:Two genome-wide microarrays containing the predicted coding sequences (putative genes) for the ciliated protozoan Tetrahymena thermophila were used to study gene expression in starved cells (starvation 0 hour and starvation 24 hour). Combining these two microarrays with 50 microarrays described in Miao et al. (2009) and 15 other microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient, the Spearman correlation coefficient and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast, and the CLR network was found to be the best network, with a Z-score threshold 3.49. Then the TGN was partitioned, and 55 modules were found. In addition, analysis for the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and found evidence indicating that some of these were involved in the same process in Tetrahymena as in human.
Project description:Four genome wide microarrays containing the predicted coding sequences (putative genes) for the ciliated protozoan Tetrahymena thermophila used to study gene expression in starved cells (Starvation 0 hour and Starvation 9 hour, each two replicates). Combined these four microarrays with 50 microarrays described in Miao et al (2009, PMID: 19204800; GSE11300) and other 13 microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient, the Spearman correlation coefficient and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast, and the CLR network was found to be the best network, with a Z-score threshold 3.49. Then the TGN was partitioned, and 55 modules were found. In addition, analysis for the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and found evidence indicating that some of these were involved in the same process in Tetrahymena as in human.
Project description:Eleven genome wide microarrays containing the predicted coding sequences (putative genes) for the ciliated protozoan Tetrahymena thermophila used to study gene expression in conjugation cells (C-0, C-15m, C-2, C-4, C-6, C-8, C-10, C-12, C-14, C-16, C-18). Combined these eleven microarrays with 50 microarrays described in Miao et al (2009) and other 6 microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient, the Spearman correlation coefficient and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast, and the CLR network was found to be the best network, with a Z-score threshold 3.49. Then the TGN was partitioned, and 55 modules were found. In addition, analysis for the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and found evidence indicating that some of these were involved in the same process in Tetrahymena as in human. For conjugation, B2086 and CU428 cells that had been starved for 18 hours were resuspended in 10 mM Tris (pH 7.5) at 200,000 cells/ml, mixed, and samples were collected at 15 min, 2, 4, 6, 8, 10, 12, 14, 16, 18 hours after the mixture (referred to as C-0, C-15m, C-2, C-4, C-6, C-8, C-10, C-12, C-14, C-16 and C-18).
Project description:RNA interference (RNAi) and Polycomb repression play evolutionarily conserved and often coordinated roles in transcriptional silencing. Here we show that in the protozoan Tetrahymena thermophila, germ line-specific internally eliminated sequences (IES)—many related to transposable elements (TE)—are transcriptionally activated in mutants deficient in the RNAi-dependent Polycomb repression pathway. Mobilization of recently duplicated TE also dramatically increases in these mutants. Importantly, transcriptional silencing and activation of TE-related sequences are accompanied by switching between noncoding RNA (ncRNA) and mRNA production, which can be affected by co-transcriptional processing as well as RNAi and Polycomb repression. We posit that interplay between RNAi and Polycomb repression is a widespread phenomenon, whose ancestral role is epigenetic silencing of TE.