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A systematic evaluation of the design and context dependencies of massively parallel reporter assays

Nature Methods volume 17, pages 1083–1091 (2020)Cite this article

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Abstract

Massively parallel reporter assays (MPRAs) functionally screen thousands of sequences for regulatory activity in parallel. To date, there are limited studies that systematically compare differences in MPRA design. Here, we screen a library of 2,440 candidate liver enhancers and controls for regulatory activity in HepG2 cells using nine different MPRA designs. We identify subtle but significant differences that correlate with epigenetic and sequence-level features, as well as differences in dynamic range and reproducibility. We also validate that enhancer activity is largely independent of orientation, at least for our library and designs. Finally, we assemble and test the same enhancers as 192-mers, 354-mers and 678-mers and observe sizable differences. This work provides a framework for the experimental design of high-throughput reporter assays, suggesting that the extended sequence context of tested elements and to a lesser degree the precise assay, influence MPRA results.

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Fig. 1: Nine MPRA strategies and experimental workflow.
Fig. 2: Quantitative comparison of different MPRA strategies.
Fig. 3: Predictive modeling of the ratios and differences between MPRA methods.
Fig. 4: Enhancer activity is largely, but not completely, independent of sequence orientation.
Fig. 5: Including additional sequence context around tested elements leads to differences in the results of MPRAs.
Fig. 6: Predictive modeling of factors dependent on element size.

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Data availability

We developed a fully reproducible MPRA processing pipeline available to process the data into final enhancer activity scores. Raw and processed data have been deposited in the Gene Expression Omnibus at accession number GSE142696.

Code availability

A reproducible processing pipeline for MPRA data is available as a Nextflow-based MPRA processing pipeline named MPRAflow (https://github.com/shendurelab/MPRAflow)44.

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Acknowledgements

We thank S. Kim and other members of the Shendure and Ahituv laboratories for general advice and critical feedback on the manuscript. This work was supported by the National Human Genome Research Institute grants 1UM1HG009408 (N.A. and J.S.), 5R01HG009136 (J.S.), 1R21HG010065 (N.A.), 1R21HG010683 (N.A.) and 5F30HG009479 (J.K.); National Institute of Mental Health grants 1R01MH109907 (N.A.) and 1U01MH116438 (N.A.); NRSA National Institutes of Health fellowship 5T32HL007093 (V.A.); and the Uehara Memorial Foundation (F.I.). J.S. is an investigator of the Howard Hughes Medical Institute.

Author information

Author notes

  1. Jason C. Klein

    Present address: Memorial Sloan Kettering Cancer Center, New York, NY, USA

  2. Fumitaka Inoue

    Present address: Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan

  3. These authors contributed equally: Jason C. Klein, Vikram Agarwal, Fumitaka Inoue, Aidan Keith.

Authors and Affiliations

  1. Department of Genome Sciences, University of Washington, Seattle, WA, USA

    Jason C. Klein, Vikram Agarwal, Aidan Keith, Beth Martin, Martin Kircher & Jay Shendure

  2. Calico Life Sciences LLC, South San Francisco, CA, USA

    Vikram Agarwal

  3. Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA

    Fumitaka Inoue & Nadav Ahituv

  4. Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA

    Fumitaka Inoue & Nadav Ahituv

  5. Berlin Institute of Health (BIH), Berlin, Germany

    Martin Kircher

  6. Charité - Universitätsmedizin Berlin, Berlin, Germany

    Martin Kircher

  7. Howard Hughes Medical Institute, Seattle, WA, USA

    Jay Shendure

  8. Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA

    Jay Shendure

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Contributions

J.K. and A.K. performed all cloning and sequencing for the nine assays and all experimental work for orientation and length sections. J.K. and J.S. conceived the HMPA protocol, and J.K. and A.K. developed and optimized it. A.K. produced schematic figures. M.K. developed the initial MPRA analysis pipeline. V.A. performed the computational analyses and generated all remaining figures and tables. F.I. performed the transfections and lentiviral transductions for the nine assays, carried out luciferase reporter experiments and wrote the associated methods sections. B.M. designed cloning steps and guided the development and testing of the MPRA assays. J.K., V.A., N.A. and J.S. wrote the remainder of the paper. N.A. and J.S. supervised the project.

Corresponding authors

Correspondence to Nadav Ahituv or Jay Shendure.

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Competing interests

V.A. is an employee of Calico Life Sciences LLC.

Additional information

Peer review information Lei Tang was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Supplementary information

Supplementary Information

Supplementary Notes 1–3 and Figs. 1–17.

Reporting Summary

Supplementary Table 1

Genomic coordinates (human genome build hg19) and sequences for all designed elements, both naturally occurring as well as synthetic positive and negative controls, in the experiments testing the nine assays, element orientation and element size.

Supplementary Table 2

Activity scores computed for each element for each of the nine MPRA assays tested as well as HSS_full, HSS_b2, ORI_full and ORI_b2. Provided are averaged activity scores across replicates as well as individual scores for each replicate alongside normalized DNA counts, normalized RNA counts and the number of barcodes per element.

Supplementary Table 3

Summary of 915 features considered in a model trained to predict enhancer activity, with an overview of features considered, feature type (computationally predicted or experimentally derived), data source and number of features in the category.

Supplementary Table 4

Definition of each feature considered in the lasso regression models, with detailed metadata corresponding to the data source of origin, species of origin, sample accession IDs and additional factor-specific information. Also provided are pre-computed tables of the features used during training for the nine MPRA assays as well as the assay testing different size classes.

Supplementary Table 5

Coefficients fit for the full lasso regression models for each of eight MPRA assays shown in Supplementary Fig. 6, differential comparisons shown in Supplementary Figs. 7 and 17, the assay testing different size classes shown in Supplementary Fig. 14 and the corresponding differential pairwise comparisons shown in Supplementary Fig. 15.

Supplementary Table 6

Activity scores computed for each element in the forward (‘F’) and reverse (‘R’) orientations in the orientation assay. Provided are averaged activity scores across replicates as well as individual scores for each replicate alongside normalized DNA counts, normalized RNA counts and the number of barcodes per element.

Supplementary Table 7

Activity scores computed for each element in the short, medium and long elements in the assay testing for different size classes. Provided are averaged activity scores across replicates as well as individual scores for each replicate alongside normalized DNA counts, normalized RNA counts and the number of barcodes per element.

Supplementary Table 8

All primer, adaptor and oligonucleotide sequences utilized throughout the manuscript (excluding HMPA). When applicable, this includes the assay and step for which the primer was used.

Supplementary Table 9

All sequence indexes used for each experiment.

Supplementary Table 10

All primer and adaptor sequences used for HMPA.

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Klein, J.C., Agarwal, V., Inoue, F. et al. A systematic evaluation of the design and context dependencies of massively parallel reporter assays. Nat Methods 17, 1083–1091 (2020). https://doi.org/10.1038/s41592-020-0965-y

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