High Sensitivity TSS Prediction: Estimates of Locations Where TSS Cannot Occur
High Sensitivity TSS Prediction Estimates of Locations Where TSS Cannot Occur journal.pone.0013934.pdf
High Sensitivity TSS Prediction Estimates of Locations Where TSS Cannot Occur
Bajic, Vladimir B.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Permanent link to this recordhttp://hdl.handle.net/10754/303146
MetadataShow full item record
AbstractBackground Although transcription in mammalian genomes can initiate from various genomic positions (e.g., 3′UTR, coding exons, etc.), most locations on genomes are not prone to transcription initiation. It is of practical and theoretical interest to be able to estimate such collections of non-TSS locations (NTLs). The identification of large portions of NTLs can contribute to better focusing the search for TSS locations and thus contribute to promoter and gene finding. It can help in the assessment of 5′ completeness of expressed sequences, contribute to more successful experimental designs, as well as more accurate gene annotation. Methodology Using comprehensive collections of Cap Analysis of Gene Expression (CAGE) and other transcript data from mouse and human genomes, we developed a methodology that allows us, by performing computational TSS prediction with very high sensitivity, to annotate, with a high accuracy in a strand specific manner, locations of mammalian genomes that are highly unlikely to harbor transcription start sites (TSSs). The properties of the immediate genomic neighborhood of 98,682 accurately determined mouse and 113,814 human TSSs are used to determine features that distinguish genomic transcription initiation locations from those that are not likely to initiate transcription. In our algorithm we utilize various constraining properties of features identified in the upstream and downstream regions around TSSs, as well as statistical analyses of these surrounding regions. Conclusions Our analysis of human chromosomes 4, 21 and 22 estimates ~46%, ~41% and ~27% of these chromosomes, respectively, as being NTLs. This suggests that on average more than 40% of the human genome can be expected to be highly unlikely to initiate transcription. Our method represents the first one that utilizes high-sensitivity TSS prediction to identify, with high accuracy, large portions of mammalian genomes as NTLs. The server with our algorithm implemented is available at http://cbrc.kaust.edu.sa/ddm/
CitationSchaefer U, Kodzius R, Kai C, Kawai J, Carninci P, et al. (2010) High Sensitivity TSS Prediction: Estimates of Locations Where TSS Cannot Occur. PLoS ONE 5: e13934. doi:10.1371/journal.pone.0013934.
PublisherPublic Library of Science (PLoS)
PubMed Central IDPMC2981523
The following license files are associated with this item:
- Dragon gene start finder: an advanced system for finding approximate locations of the start of gene transcriptional units.
- Authors: Bajic VB, Seah SH
- Issue date: 2003 Aug
- GC-compositional strand bias around transcription start sites in plants and fungi.
- Authors: Fujimori S, Washio T, Tomita M
- Issue date: 2005 Feb 28
- GPMiner: an integrated system for mining combinatorial cis-regulatory elements in mammalian gene group.
- Authors: Lee TY, Chang WC, Hsu JB, Chang TH, Shien DM
- Issue date: 2012
- [Analysis, identification and correction of some errors of model refseqs appeared in NCBI Human Gene Database by in silico cloning and experimental verification of novel human genes].
- Authors: Zhang DL, Ji L, Li YD
- Issue date: 2004 May
- MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes.
- Authors: Marinescu VD, Kohane IS, Riva A
- Issue date: 2005 Mar 30