High-throughput and quantitative assessment of enhancer activity in mammals by CapStarr-seq

Laurent Vanhille, Aurélien Griffon, Muhammad Ahmad Maqbool, Joaquin Zacarias-Cabeza, Lan T.M. Dao, Nicolas Fernandez, Benoit Ballester, Jean Christophe Andrau and Salvatore Spicuglia ()
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Laurent Vanhille: Inserm U1090, Technological Advances for Genomics and Clinics (TAGC)
Aurélien Griffon: Inserm U1090, Technological Advances for Genomics and Clinics (TAGC)
Muhammad Ahmad Maqbool: Institute of Molecular Genetics of Montpellier (IGMM), UMR5535 CNRS
Joaquin Zacarias-Cabeza: Institute of Biomedical Research, University of Birmingham
Lan T.M. Dao: Inserm U1090, Technological Advances for Genomics and Clinics (TAGC)
Nicolas Fernandez: Inserm U1090, Technological Advances for Genomics and Clinics (TAGC)
Benoit Ballester: Inserm U1090, Technological Advances for Genomics and Clinics (TAGC)
Jean Christophe Andrau: Institute of Molecular Genetics of Montpellier (IGMM), UMR5535 CNRS
Salvatore Spicuglia: Inserm U1090, Technological Advances for Genomics and Clinics (TAGC)

Nature Communications, 2015, vol. 6, issue 1, 1-10

Abstract: Abstract Cell-type specific regulation of gene expression requires the activation of promoters by distal genomic elements defined as enhancers. The identification and the characterization of enhancers are challenging in mammals due to their genome complexity. Here we develop CapStarr-Seq, a novel high-throughput strategy to quantitatively assess enhancer activity in mammals. This approach couples capture of regions of interest to previously developed Starr-seq technique. Extensive assessment of CapStarr-seq demonstrates accurate quantification of enhancer activity. Furthermore, we find that enhancer strength is associated with binding complexity of tissue-specific transcription factors and super-enhancers, while additive enhancer activity isolates key genes involved in cell identity and function. The CapStarr-Seq thus provides a fast and cost-effective approach to assess the activity of potential enhancers for a given cell type and will be helpful in decrypting transcription regulation mechanisms.

Date: 2015
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DOI: 10.1038/ncomms7905

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