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STARR-seq and UMI-STARR-seq: Assessing Enhancer Activities for Genome-Wide-, High-, and Low-Complexity Candidate

Christoph Neumayr1, Michaela Pagani1, Alexander Stark1,2

  • 1Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria.

Current Protocols in Molecular Biology
|September 11, 2019
PubMed
Summary
This summary is machine-generated.

STARR-seq directly measures enhancer activity for millions of DNA sequences, aiding in understanding gene regulation and genetic variants. This method enables genome-wide enhancer mapping in human cells.

Keywords:
MPRASTARR-seqUMI-STARR-seqcis-regulatory elementenhancerfunctional genomicsgene expressiongene regulationmassively parallel reporter assaytranscriptional regulation

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Area of Science:

  • Genomics
  • Molecular Biology
  • Epigenetics

Background:

  • Understanding gene regulation requires identifying transcriptional enhancers and quantifying their activity.
  • Assessing how genomic variants impact enhancer function is crucial for human health.
  • Genome-wide enhancer activity maps are essential for deciphering regulatory information.

Purpose of the Study:

  • To describe the methodology for creating and performing STARR-seq (Self-Transcribing Activated Regulatory Region sequencing) screens in human cells.
  • To enable the direct and quantitative assessment of enhancer activity for millions of DNA sequences in parallel.
  • To introduce UMI-STARR-seq for accurate reporter mRNA quantification in low-complexity libraries.

Main Methods:

  • Cloning candidate sequences downstream of a core promoter in a reporter gene's transcription unit.
  • Performing STARR-seq screens in mammalian cells to quantify reporter mRNA levels via deep sequencing.
  • Utilizing unique molecular identifiers (UMIs) in UMI-STARR-seq for enhanced accuracy.

Main Results:

  • STARR-seq allows parallel, quantitative assessment of millions of candidate enhancer sequences.
  • The protocol facilitates the creation of focused and genome-wide human STARR-seq libraries.
  • UMI-STARR-seq improves the accuracy of reporter mRNA counting, especially for complex libraries.

Conclusions:

  • STARR-seq is a powerful tool for genome-wide enhancer activity mapping and functional variant analysis.
  • The described protocols enable efficient and scalable screening of enhancer function in human cells.
  • UMI-STARR-seq enhances the reliability of STARR-seq for diverse library complexities.