Cited by 226Genomics and Chromatin DynamicsCRISPR and Genetic EngineeringGene Regulatory Network Analysis

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

Open access
Klein, Jason C., Agarwal, Vikram, Inoue, Fumitaka, Keith, Aidan, Martin, Beth, Kircher, Martin, Ahituv, Nadav, Shendure, Jay·2020·Nature Methods

Published version of a preprint

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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Crossref · 10.1038/s41592-020-0965-y

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  • The strength of the regularization was controlled by a single λ parameter, which was optimized using tenfold crossvalidation for each training set.

    “The strength of the regularization was controlled by a single λ parameter, which was optimized using tenfold crossvalidation for each training set using the cv.glmnet function of the glmnet library in R.”

    From Effective gene expression prediction from sequence by integrating long-range interactions (2021) · cites this paper as [45]

    The Online Methods, under “Model training” (page unavailable), says that a single λ parameter was optimized using tenfold cross-validation. It specifies optimization on the entire dataset, not for each training set, and does not identify the cv.glmnet function or glmnet library named in the citing sentence. (LLM, conf=0.88)

    Experimental — accuracy not yet measured
  • Activity-CNN added ETS and AP-1 sites underlying higher enhancer activity, in agreement with previous MPRA studies in the liver.

    “whereas the activity-CNN added ETS and AP-1 sites underlying higher enhancer activity, in agreement with previous MPRA studies in the liver60.”

    From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [60]

    In Results (‘Different MPRA designs yield different results’; page unavailable), ETS-related features are more predictive of episomal activity. In Results (‘Appending sequence context leads to differences in the results of MPRAs’; page unavailable), predicted binding of JUN and FOS, components of AP-1, helps explain activity differences between enhancer lengths in HepG2 assays. The paper does not establish that adding both ETS and AP-1 sites raises enhancer activity; it cautions that correlated features limit causal interpretation. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • The 12K library included 795 shuffled regions as negative control and 360 positive controls that previously showed activity in HepG2 and have mouse orthologous regions accessible in mouse liver.

    “Moreover, we included 795 shuffled regions as a negative control, and 360 positive controls that previously showed activity in HepG2, and for which a mouse orthologous region can be found that is also accessible in the mouse liver.”

    From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [60]

    The Results section (“Implementation and testing of nine MPRA strategies”; page unavailable) describes positive controls previously shown to have enhancer activity in HepG2, supporting that part of the claim. But it describes a 2,440-sequence library with 204 controls, not a 12K library with 795 shuffled negative controls and 360 positive controls. The cited passage does not establish the claimed mouse-ortholog or mouse-liver accessibility criteria. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • The zonation-CNN added Tbx3 and Tcf7l1 motifs as crucial sequence features to hepatocyte enhancers, while the activity-CNN added ETS and AP-1 sites underlying higher enhancer activity, in agreement with previous MPRA studies in the liver.

    “The zonation-CNN added Tbx3 and Tcf7l1 motifs as crucial sequence features to the hepatocyte enhancers; while the activity-CNN added ETS and AP-1 sites underlying higher enhancer activity, in agreement with previous MPRA studies in the liver17.”

    From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [17]

    In the Results sections on MPRA design and sequence context (page not available), the paper reports that ETS-variant factors predict episomal assay activity and that predicted binding of Jun and FOS, components of AP-1, helps explain activity differences between enhancer lengths in HepG2 experiments. It does not report zonation-CNN or activity-CNN adding motifs, or identify Tbx3 and Tcf7l1 as crucial hepatocyte-enhancer features. The reported associations therefore support only part of the claimed agreement with prior MPRA work. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Massively Parallel Reporter Assays have been established to directly test and identify active enhancers.

    “new experimental approaches, such as Massively Parallel Reporter Assays (MPRAs), have been established to directly test and identify active enhancers14–18.”

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1 of the 51 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. [43]Li H Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv [q-bio.GN] (2013).

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Authors
Klein, J. C., Agarwal, V., Inoue, F., Keith, A., Martin, B., Kircher, M., Ahituv, N., & Shendure, J.
Affiliations
  • Memorial Sloan Kettering Cancer Center (US)
  • University of Washington (US)
  • University of California, San Francisco (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Ahituv, Nadav
  • Shendure, Jay
Venue
Nature Methods
Published
2020-10-12
Volume
17
Issue
11
Pages
1083-1091
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
OpenAlex
W3092421956
Cited by
226
References
51
Citations by year
2026: 34 · 2025: 46 · 2024: 38 · 2023: 35 · 2022: 32 · 2021: 27 · 2020: 10 · 2019: 4
FWCI
8.44
Type
journal article
Language
en
Open access
Locations
  • Nature Methods (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (1UM1HG009408, 5R01HG009136, 5F30HG009479, 1R21HG010065)
  • Howard Hughes Medical Institute
  • U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (5T32HL007093)
  • Uehara Memorial Foundation
  • U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (1R01MH109907, 1U01MH116438)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
massively parallel reporter assay, assay design, enhancer activity, HepG2 cells, sequence context, dynamic range, reproducibility, epigenetic features
MeSH terms
Enhancer Elements, Genetic, Humans, Regulatory Sequences, Nucleic Acid, Transcription Factors, Reproducibility of Results, Gene Library, Sequence Analysis, DNA, Genes, Reporter, Hep G2 Cells, High-Throughput Nucleotide Sequencing

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