A Predictive Modeling Approach for Cell Line-specific Long-range Regulatory Interactions

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2015 Sep 5

PMID 26338778

Citations 62

Authors

Sushmita Roy

Alireza Fotuhi Siahpirani

Deborah Chasman

Sara Knaack

Ferhat Ay

Ron Stewart

Michael Wilson

Rupa Sridharan

Affiliations

Soon will be listed here.

Abstract

Long range regulatory interactions among distal enhancers and target genes are important for tissue-specific gene expression. Genome-scale identification of these interactions in a cell line-specific manner, especially using the fewest possible datasets, is a significant challenge. We develop a novel computational approach, Regulatory Interaction Prediction for Promoters and Long-range Enhancers (RIPPLE), that integrates published Chromosome Conformation Capture (3C) data sets with a minimal set of regulatory genomic data sets to predict enhancer-promoter interactions in a cell line-specific manner. Our results suggest that CTCF, RAD21, a general transcription factor (TBP) and activating chromatin marks are important determinants of enhancer-promoter interactions. To predict interactions in a new cell line and to generate genome-wide interaction maps, we develop an ensemble version of RIPPLE and apply it to generate interactions in five human cell lines. Computational validation of these predictions using existing ChIA-PET and Hi-C data sets showed that RIPPLE accurately predicts interactions among enhancers and promoters. Enhancer-promoter interactions tend to be organized into subnetworks representing coordinately regulated sets of genes that are enriched for specific biological processes and cis-regulatory elements. Overall, our work provides a systematic approach to predict and interpret enhancer-promoter interactions in a genome-wide cell-type specific manner using a few experimentally tractable measurements.

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References

Parisi F, Strino F, Nadler B, Kluger Y . Ranking and combining multiple predictors without labeled data. Proc Natl Acad Sci U S A. 2014; 111(4):1253-8. PMC: 3910607. DOI: 10.1073/pnas.1219097111. View

Gerstein M, Kundaje A, Hariharan M, Landt S, Yan K, Cheng C . Architecture of the human regulatory network derived from ENCODE data. Nature. 2012; 489(7414):91-100. PMC: 4154057. DOI: 10.1038/nature11245. View

Schoenfelder S, Furlan-Magaril M, Mifsud B, Tavares-Cadete F, Sugar R, Javierre B . The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements. Genome Res. 2015; 25(4):582-97. PMC: 4381529. DOI: 10.1101/gr.185272.114. View

Hoffman M, Ernst J, Wilder S, Kundaje A, Harris R, Libbrecht M . Integrative annotation of chromatin elements from ENCODE data. Nucleic Acids Res. 2012; 41(2):827-41. PMC: 3553955. DOI: 10.1093/nar/gks1284. View

Rao S, Huntley M, Durand N, Stamenova E, Bochkov I, Robinson J . A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014; 159(7):1665-80. PMC: 5635824. DOI: 10.1016/j.cell.2014.11.021. View

de Laat W, Duboule D . Topology of mammalian developmental enhancers and their regulatory landscapes. Nature. 2013; 502(7472):499-506. DOI: 10.1038/nature12753. View

Jin F, Li Y, Dixon J, Selvaraj S, Ye Z, Lee A . A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature. 2013; 503(7475):290-4. PMC: 3838900. DOI: 10.1038/nature12644. View

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

Ong C, Corces V . Enhancer function: new insights into the regulation of tissue-specific gene expression. Nat Rev Genet. 2011; 12(4):283-93. PMC: 3175006. DOI: 10.1038/nrg2957. View

10.

Calo E, Wysocka J . Modification of enhancer chromatin: what, how, and why?. Mol Cell. 2013; 49(5):825-37. PMC: 3857148. DOI: 10.1016/j.molcel.2013.01.038. View

11.

Misteli T . Higher-order genome organization in human disease. Cold Spring Harb Perspect Biol. 2010; 2(8):a000794. PMC: 2908770. DOI: 10.1101/cshperspect.a000794. View

12.

Imakaev M, Fudenberg G, McCord R, Naumova N, Goloborodko A, Lajoie B . Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat Methods. 2012; 9(10):999-1003. PMC: 3816492. DOI: 10.1038/nmeth.2148. View

13.

Edelman L, Fraser P . Transcription factories: genetic programming in three dimensions. Curr Opin Genet Dev. 2012; 22(2):110-4. DOI: 10.1016/j.gde.2012.01.010. View

14.

Sanyal A, Lajoie B, Jain G, Dekker J . The long-range interaction landscape of gene promoters. Nature. 2012; 489(7414):109-13. PMC: 3555147. DOI: 10.1038/nature11279. View

15.

Thurman R, Rynes E, Humbert R, Vierstra J, Maurano M, Haugen E . The accessible chromatin landscape of the human genome. Nature. 2012; 489(7414):75-82. PMC: 3721348. DOI: 10.1038/nature11232. View

16.

Yip K, Cheng C, Bhardwaj N, Brown J, Leng J, Kundaje A . Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors. Genome Biol. 2012; 13(9):R48. PMC: 3491392. DOI: 10.1186/gb-2012-13-9-r48. View

17.

Corradin O, Saiakhova A, Akhtar-Zaidi B, Myeroff L, Willis J, Cowper-Sal Lari R . Combinatorial effects of multiple enhancer variants in linkage disequilibrium dictate levels of gene expression to confer susceptibility to common traits. Genome Res. 2013; 24(1):1-13. PMC: 3875850. DOI: 10.1101/gr.164079.113. View

18.

Beck D, Oda H, Shen S, Reinberg D . PR-Set7 and H4K20me1: at the crossroads of genome integrity, cell cycle, chromosome condensation, and transcription. Genes Dev. 2012; 26(4):325-37. PMC: 3289880. DOI: 10.1101/gad.177444.111. View

19.

Heidari N, Phanstiel D, He C, Grubert F, Jahanbani F, Kasowski M . Genome-wide map of regulatory interactions in the human genome. Genome Res. 2014; 24(12):1905-17. PMC: 4248309. DOI: 10.1101/gr.176586.114. View

20.

Miele A, Dekker J . Long-range chromosomal interactions and gene regulation. Mol Biosyst. 2008; 4(11):1046-57. PMC: 2653627. DOI: 10.1039/b803580f. View