lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements

M Grace Gordon; Fumitaka Inoue; Beth Martin; Max Schubach; Vikram Agarwal; Sean Whalen; Shiyun Feng; Jingjing Zhao; Tal Ashuach; Ryan Ziffra; Anat Kreimer; Ilias Georgakopoulos-Soares; Nir Yosef; Chun Jimmie Ye; Katherine S Pollard; Jay Shendure; Martin Kircher; Nadav Ahituv

doi:10.1038/s41596-020-0333-5

lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements

Nat Protoc. 2020 Aug;15(8):2387-2412. doi: 10.1038/s41596-020-0333-5. Epub 2020 Jul 8.

Authors

M Grace Gordon^#^{1

2

3}, Fumitaka Inoue^#^{4

5}, Beth Martin^#⁶, Max Schubach^#^{7

8}, Vikram Agarwal^{6

9}, Sean Whalen¹⁰, Shiyun Feng^{1

2}, Jingjing Zhao^{1

2}, Tal Ashuach¹¹, Ryan Ziffra^{1

2}, Anat Kreimer^{1

2

11}, Ilias Georgakopoulos-Soares^{1

2}, Nir Yosef^{11

12}, Chun Jimmie Ye^{1

2

12

13

14}, Katherine S Pollard^{2

10

12

15}, Jay Shendure^{16

17

18}, Martin Kircher^{19

20}, Nadav Ahituv^{21

22}

Affiliations

¹ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
² Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
³ Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁴ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA. fumitaka.inoue@ucsf.edu.
⁵ Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. fumitaka.inoue@ucsf.edu.
⁶ Department of Genome Sciences, University of Washington, Seattle, WA, USA.
⁷ Berlin Institute of Health (BIH), Berlin, Germany.
⁸ Charité-Universitätsmedizin Berlin, Berlin, Germany.
⁹ Calico Life Sciences LLC, South San Francisco, CA, USA.
¹⁰ Gladstone Institutes, San Francisco, CA, USA.
¹¹ Department of Electrical Engineering and Computer Sciences and Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.
¹² Chan-Zuckerberg Biohub, San Francisco, CA, USA.
¹³ Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
¹⁴ Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, California, USA.
¹⁵ Department of Epidemiology and Biostatistics and Institute of Computational Health Sciences, University of California, San Francisco, San Francisco, CA, USA.
¹⁶ Department of Genome Sciences, University of Washington, Seattle, WA, USA. shendure@uw.edu.
¹⁷ Howard Hughes Medical Institute, Seattle, WA, USA. shendure@uw.edu.
¹⁸ Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA. shendure@uw.edu.
¹⁹ Berlin Institute of Health (BIH), Berlin, Germany. martin.kircher@bihealth.de.
²⁰ Charité-Universitätsmedizin Berlin, Berlin, Germany. martin.kircher@bihealth.de.
²¹ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA. nadav.ahituv@ucsf.edu.
²² Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. nadav.ahituv@ucsf.edu.

^# Contributed equally.

Abstract

Massively parallel reporter assays (MPRAs) can simultaneously measure the function of thousands of candidate regulatory sequences (CRSs) in a quantitative manner. In this method, CRSs are cloned upstream of a minimal promoter and reporter gene, alongside a unique barcode, and introduced into cells. If the CRS is a functional regulatory element, it will lead to the transcription of the barcode sequence, which is measured via RNA sequencing and normalized for cellular integration via DNA sequencing of the barcode. This technology has been used to test thousands of sequences and their variants for regulatory activity, to decipher the regulatory code and its evolution, and to develop genetic switches. Lentivirus-based MPRA (lentiMPRA) produces 'in-genome' readouts and enables the use of this technique in hard-to-transfect cells. Here, we provide a detailed protocol for lentiMPRA, along with a user-friendly Nextflow-based computational pipeline-MPRAflow-for quantifying CRS activity from different MPRA designs. The lentiMPRA protocol takes ~2 months, which includes sequencing turnaround time and data processing with MPRAflow.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Base Sequence
Lentivirus / genetics*
Regulatory Sequences, Nucleic Acid / genetics*
Sequence Analysis, DNA / methods*
Workflow*

Abstract

Publication types

MeSH terms

Grants and funding