期刊
GENOME RESEARCH
卷 19, 期 4, 页码 644-656出版社
COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.085449.108
关键词
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资金
- NHGRI NIH HHS [R01 HG004065, R01 HG 004065] Funding Source: Medline
- NIGMS NIH HHS [P50GM081883, P50 GM081883] Funding Source: Medline
The recent arrival of large-scale cap analysis of gene expression (CAGE) data sets in mammals provides a wealth of quantitative information on coding and noncoding RNA polymerase II transcription start sites (TSS). Genome-wide CAGE studies reveal that a large fraction of TSS exhibit peaks where the vast majority of associated tags map to a particular location (similar to 45%), whereas other active regions contain a broader distribution of initiation events. The presence of a strong single peak suggests that transcription at these locations may be mediated by position-specific sequence features. We therefore propose a new model for single-peaked TSS based solely on known transcription factors (TFs) and their respective regions of positional enrichment. This probabilistic model leads to near-perfect classification results in cross-validation (auROC = 0.98), and performance in genomic scans demonstrates that TSS prediction with both high accuracy and spatial resolution is achievable for a specific but large subgroup of mammalian promoters. The interpretable model structure suggests a DNA code in which canonical sequence features such as TATA-box, Initiator, and GC content do play a significant role, but many additional TFs show distinct spatial biases with respect to TSS location and are important contributors to the accurate prediction of single-peak transcription initiation sites. The model structure also reveals that CAGEtag clusters distal fromannotated gene starts have distinct characteristics compared to those close to gene 59-ends. Using this high-resolution single-peakmodel, we predict TSS for similar to 70% of mammalian microRNAs based on currently available data.
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