Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Cell cycle promoter tiling

ABSTRACT: Discover novel transcriptional units upstream of cell cycle genes Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such noncoding transcription are not known. Here we use an ultra-high density array that tiles the promoters of 56 cell cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs--many of which have RT-PCR-validated periodic expression during the cell cycle, show altered expression in human cancers, and are regulated in expression by specific oncogenic stimuli, stem cell differentiation, or DNA damage. 53 samples tiled against respective controls

ORGANISM(S): Homo sapiens

SUBMITTER: Tiffany Hung

PROVIDER: E-GEOD-28631 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters.

Hung Tiffany T Wang Yulei Y Lin Michael F MF Koegel Ashley K AK Kotake Yojiro Y Grant Gavin D GD Horlings Hugo M HM Shah Nilay N Umbricht Christopher C Wang Pei P Wang Yu Y Kong Benjamin B Langerød Anita A Børresen-Dale Anne-Lise AL Kim Seung K SK van de Vijver Marc M Sukumar Saraswati S Whitfield Michael L ML Kellis Manolis M Xiong Yue Y Wong David J DJ Chang Howard Y HY

Nature genetics 20110605 7

Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR-validated periodic expression during the cell cycle, show altered ex ...[more]

PMID: 21642992

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Project description:SUMO modification of proteins (sumoylation) is essential for mitotic progression from yeast to humans, but only a limited number of sumoylated proteins with functions in mitosis have been discovered. Vertebrates express three SUMO paralogs, SUMO-1, SUMO-2 and SUMO-3, but only SUMO-2 and -3 are chromosome-associated in mitosis. In this study, we used chromosome spreads to more precisely define the localization of endogenous SUMO-2 and -3 to the centromere as well as the chromosome protein scaffold. Furthermore, we developed methodologies for the immunopurification of endogenous SUMO-2 and -3 modified proteins from cell extracts. Using LC-MS/MS, we analyzed proteins immunopurified from mitotic chromosome fractions and G0 nuclear fractions. We identified 296 putative sumoylated proteins, with 138 being modified specifically in mitosis. We identified proteins known to localize to the centromere and kinetochore and the chromosome protein scaffold, consistent with SUMO-2/3 localization. Furthermore, we demonstrate that utilizing cell synchronization and fractionation allowed for the discovery of low abundance sumoylated proteins that are not detected in large asynchronous analyses. Our results provide a foundation for further characterization of the roles of sumoylation in regulating diverse aspects of chromosome segregation in mitosis. Thermo .raw files were uploaded to the ProHits (Liu et al, 2010) analytical suite and converted to .mzXML format using ReAdW software. Data were searched using X!Tandem (Craig & Beavis, 2004) against human ORFs (RefSeq v45). Search parameters specified a parent MS tolerance of +/- 15ppm, and an MS/MS tolerance of 0.4 Da, with up to two missed cleavages for trypsin. Oxidation of methionine and tryptophan, ubiquitylation of lysine, and alkylation of cysteine (by NEM) were allowed as variable modifications. Statistical validation of the results was performed using Peptide Prophet and Protein Prophet (Keller et al, 2002; Nesvizhskii et al, 2003) as part of the trans-proteomic pipeline. For each search, the Protein Prophet probability at a 1% false discovery rate was used as a cutoff value to generate SAINT-compatible input files. SAINT parameters were as follows: 5000 iterations, low mode Off (0), minFold 1 and normalization (1) (Choi et al, 2011). SAINT cutoff values of 0.75 were used to generate a high-confidence list of protein identifications.

Dataset Information

Cell cycle promoter tiling

Publications

Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters.

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