Dataset Information

Transcription factor binding profiles reveal cyclic expression of human protein-coding genes and non-coding RNAs.

ABSTRACT: Cell cycle is a complex and highly supervised process that must proceed with regulatory precision to achieve successful cellular division. Despite the wide application, microarray time course experiments have several limitations in identifying cell cycle genes. We thus propose a computational model to predict human cell cycle genes based on transcription factor (TF) binding and regulatory motif information in their promoters. We utilize ENCODE ChIP-seq data and motif information as predictors to discriminate cell cycle against non-cell cycle genes. Our results show that both the trans- TF features and the cis- motif features are predictive of cell cycle genes, and a combination of the two types of features can further improve prediction accuracy. We apply our model to a complete list of GENCODE promoters to predict novel cell cycle driving promoters for both protein-coding genes and non-coding RNAs such as lincRNAs. We find that a similar percentage of lincRNAs are cell cycle regulated as protein-coding genes, suggesting the importance of non-coding RNAs in cell cycle division. The model we propose here provides not only a practical tool for identifying novel cell cycle genes with high accuracy, but also new insights on cell cycle regulation by TFs and cis-regulatory elements.

SUBMITTER: Cheng C

PROVIDER: S-EPMC3708869 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transcription factor binding profiles reveal cyclic expression of human protein-coding genes and non-coding RNAs.

Cheng Chao C Ung Matthew M Grant Gavin D GD Whitfield Michael L ML

PLoS computational biology 20130711 7

Cell cycle is a complex and highly supervised process that must proceed with regulatory precision to achieve successful cellular division. Despite the wide application, microarray time course experiments have several limitations in identifying cell cycle genes. We thus propose a computational model to predict human cell cycle genes based on transcription factor (TF) binding and regulatory motif information in their promoters. We utilize ENCODE ChIP-seq data and motif information as predictors to ...[more]

PMID: 23874175

Similar Datasets

Project description:BackgroundAlthough genome-wide association studies (GWAS) have identified hundreds of variants associated with a risk for autoimmune and immune-related disorders (AID), our understanding of the disease mechanisms is still limited. In particular, more than 90% of the risk variants lie in non-coding regions, and almost 10% of these map to long non-coding RNA transcripts (lncRNAs). lncRNAs are known to show more cell-type specificity than protein-coding genes.MethodsWe aimed to characterize lncRNAs and protein-coding genes located in loci associated with nine AIDs which have been well-defined by Immunochip analysis and by transcriptome analysis across seven populations of peripheral blood leukocytes (granulocytes, monocytes, natural killer (NK) cells, B cells, memory T cells, naive CD4(+) and naive CD8(+) T cells) and four populations of cord blood-derived T-helper cells (precursor, primary, and polarized (Th1, Th2) T-helper cells).ResultsWe show that lncRNAs mapping to loci shared between AID are significantly enriched in immune cell types compared to lncRNAs from the whole genome (α <0.005). We were not able to prioritize single cell types relevant for specific diseases, but we observed five different cell types enriched (α <0.005) in five AID (NK cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, and psoriasis; memory T and CD8(+) T cells in juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, and rheumatoid arthritis; Th0 and Th2 cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, and rheumatoid arthritis). Furthermore, we show that co-expression analyses of lncRNAs and protein-coding genes can predict the signaling pathways in which these AID-associated lncRNAs are involved.ConclusionsThe observed enrichment of lncRNA transcripts in AID loci implies lncRNAs play an important role in AID etiology and suggests that lncRNA genes should be studied in more detail to interpret GWAS findings correctly. The co-expression results strongly support a model in which the lncRNA and protein-coding genes function together in the same pathways.

Project description:BACKGROUND: The gene regulation mechanism along the life cycle of the genus Schistosoma is complex. Small non-coding RNAs (sncRNAs) are essential post transcriptional gene regulation elements that affect gene expression and mRNA stability. Preliminary studies indicated that sncRNAs in schistosomal parasites are generated through different pathways, which are developmentally regulated. However, the data of sncRNAs of schistosomal parasites are still fragmental and a complete expression profile of sncRNAs during the parasite development requires a deep investigation. METHODOLOGY/PRINCIPAL FINDINGS: We employed high-throughput genome-wide transcriptome analytic techniques to explore the dynamic expression of microRNAs (miRNAs) and endogenous siRNAs (endo-siRNAs) of Schistosoma japonicum covering the free-living cercarial stage and all stages in the definitive host. This led us to analyze over 70 million clean reads represented both high and low abundance of the small RNA population. Patterns of differential expression of miRNAs and endo-siRNAs were observed. MiRNAs was twice more than endo-siRNAs in cercariae, but gradually decreased along with the development of the parasite. Both small RNA types were presented in equal aboudance in lung-stage schistosomula, while endo-siRNAs accumulated to 6 times more than miRNAs in adult female worms and hepatic eggs. Further, miRNAs were found mainly derived from genes located in the intergenic regions, while endo-siRNAs were mainly generated from transposable elements (TEs). The expression pattern of TE-siRNAs, as well as the pseudogene-derived siRNAs clustered in mRNAs of cytoskeletal proteins, stress proteins, enzymes related to energy metabolism also revealed distinction throughout different developmental stages. Natural antisense transcripts (NATs)-related siRNAs accounted for minor proportion of the endo-siRNAs which were dominantly expressed in cercariae. CONCLUSIONS/SIGNIFICANCE: Our results represented a comprehensive expression profile of sncRNAs in various developmental stages of S. japonicum with high accuracy and coverage. The data would facilitate a deep understanding of the parasite biology and potential discovery of novel targets for the design of anti-parasite drugs.

Dataset Information

Transcription factor binding profiles reveal cyclic expression of human protein-coding genes and non-coding RNAs.

Publications

Transcription factor binding profiles reveal cyclic expression of human protein-coding genes and non-coding RNAs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets