1Frontier Research Initiative, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo,
108-8639, Japan;
2Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639,
Japan;
3Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi,
Chiba, 277-8568, Japan;
4Department of Molecular Preventive Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku,
Tokyo, 113-8654, Japan;
5Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 4-6-1 Shirokanedai,
Minato-ku, Tokyo, 108-8639, Japan
↵6 These authors contributed equally to this work.
Abstract
We performed a genome-wide analysis of transcriptional start sites (TSSs) in human genes by multifaceted use of a massively
parallel sequencer. By analyzing 800 million sequences that were obtained from various types of transcriptome analyses, we
characterized 140 million TSS tags in 12 human cell types. Despite the large number of TSS clusters (TSCs), the number of
TSCs was observed to decrease sharply with increasing expression levels. Highly expressed TSCs exhibited several characteristic
features: Nucleosome-seq analysis revealed highly ordered nucleosome structures, ChIP-seq analysis detected clear RNA polymerase
II binding signals in their surrounding regions, evaluations of previously sequenced and newly shotgun-sequenced complete
cDNA sequences showed that they encode preferable transcripts for protein translation, and RNA-seq analysis of polysome-incorporated
RNAs yielded direct evidence that those transcripts are actually translated into proteins. We also demonstrate that integrative
interpretation of transcriptome data is essential for the selection of putative alternative promoter TSCs, two of which also
have protein consequences. Furthermore, discriminative chromatin features that separate TSCs at different expression levels
were found for both genic TSCs and intergenic TSCs. The collected integrative information should provide a useful basis for
future biological characterization of TSCs.
[Supplemental material is available for this article. The sequence data from this study have been submitted to the DNA Data
Bank of Japan (https://www.ddbj.nig.ac.jp/index-e.html) under accession numbers listed in the Methods section.]
