6 results on '"Faulkner GJ"'
Search Results
2. Comparative cofactor screens show the influence of transactivation domains and core promoters on the mechanisms of transcription.
- Author
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Bell CC, Balic JJ, Talarmain L, Gillespie A, Scolamiero L, Lam EYN, Ang CS, Faulkner GJ, Gilan O, and Dawson MA
- Subjects
- Humans, CRISPR-Cas Systems, Transcription, Genetic, Gene Expression Regulation, Promoter Regions, Genetic, Transcription Factors genetics, Transcription Factors metabolism, Transcriptional Activation
- Abstract
Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors used by nine different TFs and core promoters in human cells. Using this dataset, we associate TFs with cofactors, classify cofactors as ubiquitous or specific and discover transcriptional co-dependencies. Through a reductionistic, comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF depends on a unique combination of cofactors, which influences distinct steps in transcription. By contrast, the influence of core promoters appears relatively discrete. Different promoter classes are constrained by either initiation or pause-release, which influences their dynamic range and compatibility with cofactors. Overall, our comparative cofactor screens characterize the interplay between TFs, cofactors and core promoters, identifying general principles by which they influence transcription., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)
- Published
- 2024
- Full Text
- View/download PDF
3. Endogenous retrovirus expression during fruitfly metamorphosis enhances adult viral immunity.
- Author
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Botto JM and Faulkner GJ
- Subjects
- Animals, Metamorphosis, Biological genetics, Drosophila
- Published
- 2022
- Full Text
- View/download PDF
4. Tiny RNAs associated with transcription start sites in animals.
- Author
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Taft RJ, Glazov EA, Cloonan N, Simons C, Stephen S, Faulkner GJ, Lassmann T, Forrest AR, Grimmond SM, Schroder K, Irvine K, Arakawa T, Nakamura M, Kubosaki A, Hayashida K, Kawazu C, Murata M, Nishiyori H, Fukuda S, Kawai J, Daub CO, Hume DA, Suzuki H, Orlando V, Carninci P, Hayashizaki Y, and Mattick JS
- Subjects
- Animals, Chick Embryo, Chickens metabolism, Drosophila genetics, Drosophila metabolism, Humans, Promoter Regions, Genetic, RNA metabolism, Transcription, Genetic, RNA chemistry, Transcription Initiation Site
- Abstract
It has been reported that relatively short RNAs of heterogeneous sizes are derived from sequences near the promoters of eukaryotic genes. In conjunction with the FANTOM4 project, we have identified tiny RNAs with a modal length of 18 nt that map within -60 to +120 nt of transcription start sites (TSSs) in human, chicken and Drosophila. These transcription initiation RNAs (tiRNAs) are derived from sequences on the same strand as the TSS and are preferentially associated with G+C-rich promoters. The 5' ends of tiRNAs show peak density 10-30 nt downstream of TSSs, indicating that they are processed. tiRNAs are generally, although not exclusively, associated with highly expressed transcripts and sites of RNA polymerase II binding. We suggest that tiRNAs may be a general feature of transcription in metazoa and possibly all eukaryotes.
- Published
- 2009
- Full Text
- View/download PDF
5. The regulated retrotransposon transcriptome of mammalian cells.
- Author
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Faulkner GJ, Kimura Y, Daub CO, Wani S, Plessy C, Irvine KM, Schroder K, Cloonan N, Steptoe AL, Lassmann T, Waki K, Hornig N, Arakawa T, Takahashi H, Kawai J, Forrest AR, Suzuki H, Hayashizaki Y, Hume DA, Orlando V, Grimmond SM, and Carninci P
- Subjects
- 3' Untranslated Regions genetics, 3' Untranslated Regions metabolism, Animals, Cells, Cultured, Humans, Mammals genetics, Mice, Promoter Regions, Genetic, RNA, Messenger, RNA, Untranslated metabolism, Gene Expression Profiling, Gene Expression Regulation, Retroelements genetics
- Abstract
Although repetitive elements pervade mammalian genomes, their overall contribution to transcriptional activity is poorly defined. Here, as part of the FANTOM4 project, we report that 6-30% of cap-selected mouse and human RNA transcripts initiate within repetitive elements. Analysis of approximately 250,000 retrotransposon-derived transcription start sites shows that the associated transcripts are generally tissue specific, coincide with gene-dense regions and form pronounced clusters when aligned to full-length retrotransposon sequences. Retrotransposons located immediately 5' of protein-coding loci frequently function as alternative promoters and/or express noncoding RNAs. More than a quarter of RefSeqs possess a retrotransposon in their 3' UTR, with strong evidence for the reduced expression of these transcripts relative to retrotransposon-free transcripts. Finally, a genome-wide screen identifies 23,000 candidate regulatory regions derived from retrotransposons, in addition to more than 2,000 examples of bidirectional transcription. We conclude that retrotransposon transcription has a key influence upon the transcriptional output of the mammalian genome.
- Published
- 2009
- Full Text
- View/download PDF
6. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.
- Author
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Suzuki H, Forrest AR, van Nimwegen E, Daub CO, Balwierz PJ, Irvine KM, Lassmann T, Ravasi T, Hasegawa Y, de Hoon MJ, Katayama S, Schroder K, Carninci P, Tomaru Y, Kanamori-Katayama M, Kubosaki A, Akalin A, Ando Y, Arner E, Asada M, Asahara H, Bailey T, Bajic VB, Bauer D, Beckhouse AG, Bertin N, Björkegren J, Brombacher F, Bulger E, Chalk AM, Chiba J, Cloonan N, Dawe A, Dostie J, Engström PG, Essack M, Faulkner GJ, Fink JL, Fredman D, Fujimori K, Furuno M, Gojobori T, Gough J, Grimmond SM, Gustafsson M, Hashimoto M, Hashimoto T, Hatakeyama M, Heinzel S, Hide W, Hofmann O, Hörnquist M, Huminiecki L, Ikeo K, Imamoto N, Inoue S, Inoue Y, Ishihara R, Iwayanagi T, Jacobsen A, Kaur M, Kawaji H, Kerr MC, Kimura R, Kimura S, Kimura Y, Kitano H, Koga H, Kojima T, Kondo S, Konno T, Krogh A, Kruger A, Kumar A, Lenhard B, Lennartsson A, Lindow M, Lizio M, Macpherson C, Maeda N, Maher CA, Maqungo M, Mar J, Matigian NA, Matsuda H, Mattick JS, Meier S, Miyamoto S, Miyamoto-Sato E, Nakabayashi K, Nakachi Y, Nakano M, Nygaard S, Okayama T, Okazaki Y, Okuda-Yabukami H, Orlando V, Otomo J, Pachkov M, Petrovsky N, Plessy C, Quackenbush J, Radovanovic A, Rehli M, Saito R, Sandelin A, Schmeier S, Schönbach C, Schwartz AS, Semple CA, Sera M, Severin J, Shirahige K, Simons C, St Laurent G, Suzuki M, Suzuki T, Sweet MJ, Taft RJ, Takeda S, Takenaka Y, Tan K, Taylor MS, Teasdale RD, Tegnér J, Teichmann S, Valen E, Wahlestedt C, Waki K, Waterhouse A, Wells CA, Winther O, Wu L, Yamaguchi K, Yanagawa H, Yasuda J, Zavolan M, Hume DA, Arakawa T, Fukuda S, Imamura K, Kai C, Kaiho A, Kawashima T, Kawazu C, Kitazume Y, Kojima M, Miura H, Murakami K, Murata M, Ninomiya N, Nishiyori H, Noma S, Ogawa C, Sano T, Simon C, Tagami M, Takahashi Y, Kawai J, and Hayashizaki Y
- Subjects
- Base Sequence, Cell Line, Gene Expression Profiling, Humans, Leukemia, Myeloid genetics, Leukemia, Myeloid metabolism, Models, Genetic, Molecular Sequence Data, Oligonucleotide Array Sequence Analysis, Promoter Regions, Genetic, RNA, Small Interfering metabolism, Cell Differentiation genetics, Cell Proliferation, Gene Regulatory Networks, Transcription, Genetic
- Abstract
Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.
- Published
- 2009
- Full Text
- View/download PDF
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