Predicting Promoter Activities of Primary Human DNA Sequences

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2011 Apr 14

PMID 21486745

Citations 5

Authors

Takuma Irie

Sung-Joon Park

Riu Yamashita

Masahide Seki

Tetsushi Yada

Sumio Sugano

Kenta Nakai

Yutaka Suzuki

Affiliations

Soon will be listed here.

Abstract

We developed a computer program that can predict the intrinsic promoter activities of primary human DNA sequences. We observed promoter activity using a quantitative luciferase assay and generated a prediction model using multiple linear regression. Our program achieved a prediction accuracy correlation coefficient of 0.87 between the predicted and observed promoter activities. We evaluated the prediction accuracy of the program using massive sequencing analysis of transcriptional start sites in vivo. We found that it is still difficult to predict transcript levels in a strictly quantitative manner in vivo; however, it was possible to select active promoters in a given cell from the other silent promoters. Using this program, we analyzed the transcriptional landscape of the entire human genome. We demonstrate that many human genomic regions have potential promoter activity, and the expression of some previously uncharacterized putatively non-protein-coding transcripts can be explained by our prediction model. Furthermore, we found that nucleosomes occasionally formed open chromatin structures with RNA polymerase II recruitment where the program predicted significant promoter activities, although no transcripts were observed.

Citing Articles

A new computational method to predict transcriptional activity of a DNA sequence from diverse datasets of massively parallel reporter assays.

Liu Y, Irie T, Yada T, Suzuki Y Nucleic Acids Res. 2017; 45(13):e124.

PMID: 28531296 PMC: 5737609. DOI: 10.1093/nar/gkx396.

Prediction of fine-tuned promoter activity from DNA sequence.

Siwo G, Rider A, Tan A, Pinapati R, Emrich S, Chawla N F1000Res. 2016; 5:158.

PMID: 27347373 PMC: 4916984. DOI: 10.12688/f1000research.7485.1.

Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

Tsai Z, Shiu S, Tsai H PLoS Comput Biol. 2015; 11(8):e1004418.

PMID: 26291518 PMC: 4546298. DOI: 10.1371/journal.pcbi.1004418.

Computational promoter modeling identifies the modes of transcriptional regulation in hematopoietic stem cells.

Park S, Umemoto T, Saito-Adachi M, Shiratsuchi Y, Yamato M, Nakai K PLoS One. 2014; 9(4):e93853.

PMID: 24710559 PMC: 3977923. DOI: 10.1371/journal.pone.0093853.

Inferring gene expression from ribosomal promoter sequences, a crowdsourcing approach.

Meyer P, Siwo G, Zeevi D, Sharon E, Norel R, Segal E Genome Res. 2013; 23(11):1928-37.

PMID: 23950146 PMC: 3814892. DOI: 10.1101/gr.157420.113.

References

Lieberman-Aiden E, van Berkum N, Williams L, Imakaev M, Ragoczy T, Telling A . Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science. 2009; 326(5950):289-93. PMC: 2858594. DOI: 10.1126/science.1181369. View

Gray N, Wickens M . Control of translation initiation in animals. Annu Rev Cell Dev Biol. 1999; 14:399-458. DOI: 10.1146/annurev.cellbio.14.1.399. View

Park P . ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet. 2009; 10(10):669-80. PMC: 3191340. DOI: 10.1038/nrg2641. View

Carninci P, Kasukawa T, Katayama S, Gough J, Frith M, Maeda N . The transcriptional landscape of the mammalian genome. Science. 2005; 309(5740):1559-63. DOI: 10.1126/science.1112014. View

Suzuki Y, Sugano S . Construction of a full-length enriched and a 5'-end enriched cDNA library using the oligo-capping method. Methods Mol Biol. 2003; 221:73-91. DOI: 10.1385/1-59259-359-3:73. View

Kel A, Gossling E, Reuter I, Cheremushkin E, Kel-Margoulis O, Wingender E . MATCH: A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Res. 2003; 31(13):3576-9. PMC: 169193. DOI: 10.1093/nar/gkg585. View

Down T, Hubbard T . Computational detection and location of transcription start sites in mammalian genomic DNA. Genome Res. 2002; 12(3):458-61. PMC: 155284. DOI: 10.1101/gr.216102. View

Imanishi T, Itoh T, Suzuki Y, ODonovan C, Fukuchi S, Koyanagi K . Integrative annotation of 21,037 human genes validated by full-length cDNA clones. PLoS Biol. 2004; 2(6):e162. PMC: 393292. DOI: 10.1371/journal.pbio.0020162. View

Das D, Nahle Z, Zhang M . Adaptively inferring human transcriptional subnetworks. Mol Syst Biol. 2006; 2:2006.0029. PMC: 1681499. DOI: 10.1038/msb4100067. View

10.

Beer M, Tavazoie S . Predicting gene expression from sequence. Cell. 2004; 117(2):185-98. DOI: 10.1016/s0092-8674(04)00304-6. View

11.

Farnham P . Insights from genomic profiling of transcription factors. Nat Rev Genet. 2009; 10(9):605-16. PMC: 2846386. DOI: 10.1038/nrg2636. View

12.

Tsuchihara K, Suzuki Y, Wakaguri H, Irie T, Tanimoto K, Hashimoto S . Massive transcriptional start site analysis of human genes in hypoxia cells. Nucleic Acids Res. 2009; 37(7):2249-63. PMC: 2673422. DOI: 10.1093/nar/gkp066. View

13.

Simonis M, Klous P, Splinter E, Moshkin Y, Willemsen R, de Wit E . Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture-on-chip (4C). Nat Genet. 2006; 38(11):1348-54. DOI: 10.1038/ng1896. View

14.

Gilmour D . Promoter proximal pausing on genes in metazoans. Chromosoma. 2008; 118(1):1-10. DOI: 10.1007/s00412-008-0182-4. View

15.

Sultan M, Schulz M, Richard H, Magen A, Klingenhoff A, Scherf M . A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science. 2008; 321(5891):956-60. DOI: 10.1126/science.1160342. View

16.

Birney E, Stamatoyannopoulos J, Dutta A, Guigo R, Gingeras T, Margulies E . Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature. 2007; 447(7146):799-816. PMC: 2212820. DOI: 10.1038/nature05874. View

17.

Levine M, Tjian R . Transcription regulation and animal diversity. Nature. 2003; 424(6945):147-51. DOI: 10.1038/nature01763. View

18.

Veitia R . A sigmoidal transcriptional response: cooperativity, synergy and dosage effects. Biol Rev Camb Philos Soc. 2003; 78(1):149-70. DOI: 10.1017/s1464793102006036. View

19.

Das D, Pellegrini M, Gray J . A primer on regression methods for decoding cis-regulatory logic. PLoS Comput Biol. 2009; 5(1):e1000269. PMC: 2607548. DOI: 10.1371/journal.pcbi.1000269. View

20.

Suzuki Y, Tsunoda T, Sese J, Taira H, Hata H, Ota T . Identification and characterization of the potential promoter regions of 1031 kinds of human genes. Genome Res. 2001; 11(5):677-84. PMC: 311086. DOI: 10.1101/gr.gr-1640r. View