Multiplexed Assays of Variant Effect (MAVE) is a method used to determine sequence-function relationships, identify variants that alter protein structure, stability, or activity, and characterize regulatory elements.Stein, A., Fowler, D. M., Hartmann-Petersen, R. & Lindorff-Larsen, K. Biophysical and Mechanistic Models for Disease-Causing Protein Variants. Trends Biochem Sci 44, 575–588 (2019).Inoue, F. & Ahituv, N. Decoding enhancers using massively parallel reporter assays. Genomics 106, 159–164 (2015).Vanella, R. et al. Understanding activity-stability tradeoffs in biocatalysts by enzyme proximity sequencing. Nat Commun 15, 1807 (2024).Patwardhan, R. P. et al. High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis. Nat Biotechnol 27, 1173–1175 (2009). MAVEs have become important in clinical genetics, particularly for reclassifying variants of uncertain significance (VUSs) in human disease genes. Guidelines on functional evidence, such as data generated by MAVEs, have been increasingly published in the 2020s.ClinGen Variant Classification Guidance - ClinGen | Clinical Genome Resource. https://clinicalgenome.org/tools/clingen-variant-classification-guidance/.Gelman, H. et al. Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation. Genome Med 11, 85 (2019). Beyond this, MAVEs have numerous applications in cancer research, medicine, and Functional genomics, enabling researchers to study both protein-coding and non-coding regions.McEwen, A. E., Tejura, M., Fayer, S., Starita, L. M. & Fowler, D. M. Multiplexed assays of variant effect for clinical variant interpretation. Nat Rev Genet 27, 137–154 (2026). A typical MAVE workflow involves the generation of a library of variants in a gene or regulatory element of interest which is introduced into an experimental model system.Chiasson, M., Dunham, M. J., Rettie, A. E. & Fowler, D. M. Applying Multiplex Assays to Understand Variation in Pharmacogenes. Clin Pharma and Therapeutics 106, 290–294 (2019). Then, the model is subjected to a phenotypic selection and high-throughput DNA sequencing is used to quantify the frequency of each variant before and after selection. The changes in frequency are used to determine the functional score of each variant.Gasperini, M., Starita, L. & Shendure, J. The power of multiplexed functional analysis of genetic variants. Nat Protoc 11, 1782–1787 (2016).
Background The MAVE workflow exists to address the challenge of linking genotypic variants with their corresponding phenotypic outcomes. This correlation poses a challenge when a single gene has a wide range of differences between individuals. While some variants are identifiable as pathogenic based on clinical data, many others are not.Frazer, J. et al. Disease variant prediction with deep generative models of evolutionary data. Nature 599, 91–95 (2021). These unknown variants are termed variants of uncertain significance (VUSs). Often, VUSs arise due to a lack of evidence and a small sample size. Genotype-to-phenotype predictions are not yet reliable enough for the type of causative understanding required to solve VUSs. Historically, researchers have relied on clinical data, rather than genotype-to-phenotype predictors, to determine the pathogenicity of a variant.
However, recent advances in technology have allowed the MAVE workflow to become established. This provides functional data that can be used alongside clinical or familial data to predict variant significance. Along with understanding VUSs, MAVE evidence has been used in determining the effects of cancer mutations, understanding non-coding regulatory elements, and identifying protein weaknesses as drug targets.Dogruluk, T. et al. Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations. Cancer Res 75, 5341–5354 (2015).
Workflow
Select a model system Selecting an appropriate model system for MAVEs requires choosing an experimental model that enables high-throughput, functional screening of genetic variants. A wide variety of models have been used in MAVEs including phage, bacteria, yeast, and human cell lines. To ensure the successful selection of an appropriate model system, the system should accurately reflect the biological processes of the organism of interest and allow for robust, quantitative measurements of variant function.Cevik, S. et al. Matching variants for functional characterization of genetic variants. G3: Genes, Genomes, Genetics 13, jkad227 (2023).
Integrate the variant library into the model system After selecting a model system, a large library of genetic variants is integrated such that each cell expresses a single variant to maintain the link between sequence and phenotype. The variant library is generated by introducing mutations across the target gene, protein, or regulatory element (e.g., promoter, enhancer, splice sites, etc.). The library can be constructed either through random, error-prone PCR-based mutagenesis or synthesized oligo arrays programmes with mutations of interest. The variant library is then introduced into the model system. Common approaches for library introduction include lentiviral transduction or recombinase-based "landing-pad" systems.
Alternatively, variants can be introduced directly into the endogenous genomic locus. Recent advances in CRISPR-Cas9 genome editing have enabled precise modification of target genes while preserving their native context. New editing techniques involve using a modified Cas9 that nicks one DNA strand, attached to an enzyme that chemically converts one base into another, allowing for precise point mutations without making a full double-strand break.Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420–424 (2016).. Prime editing also uses a modified Cas9 that nicks one DNA strand but is attached to reverse transcriptase.Anzalone, A. V. et al. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576, 149–157 (2019). A prime editing guide RNA (pegRNA) directs Cas9 to the correct location but also carries new genetic information to be inserted. This new sequence is then copied into the cell's DNA, allowing precise introduction of specific substitutions, insertions, or deletion.
Apply phenotypic selection of interest with a functional assay Cells expressing the library of interest are assayed for a phenotype of interest, such as drug resistance or reporter activation, to separate the variants based on their function. For example, to find variants associated with drug resistance, cells are grown in the presence of a specific drug and sequenced before drug addiction and at several time points thereafter to determine how common each variant is in the population. A variant that becomes more common over time indicates that it is beneficial for survival and growth in the presence of the drug.Belli, O., Karava, K., Farouni, R. & Platt, R. J. Multimodal scanning of genetic variants with base and prime editing. Nat Biotechnol 43, 1458–1470 (2025).
Sequence cells and compute variant scores After phenotypic selection, cells are sequenced using next-generation sequencing (NGS) methods, such as Illumina and PacBio, to determine the frequency of each variant before and after selection. Enrichment scores are calculated for each variant to determine its impact on function, such that variants that increase in frequency are typically interpreted as beneficial under the assay conditions, whereas variants that decrease are considered detrimental. Computational tools used for variant scoring include Enrich2, DiMSum, and mutscan.Çubuk, H., Jin, X., Phipson, B., Marsh, J. A. & Rubin, A. F. Variant scoring tools for deep mutational scanning. Mol Syst Biol 21, 1293–1305 (2025).
Scientific Principles
Model systems MAVEs can be performed in a variety of experimental model systems, each with its own advantages and limitations. Phage and bacterial systems allow for the creation of very large variant libraries but lack eukaryotic protein folding and post-translational modifications. Yeast provides a eukaryotic context with many conserved cellular processes and human cancer cell lines offer a more physiologically relevant human environment, preserving native protein interactions and modifications. Stem cell-derived specialized cells most closely model specific human tissues, but are technically demanding and less stable.
Phenotypic selection Phenotype selection is a process in the MAVE workflow that is used to select for a desired phenotypic outcome. The proposed disease mechanism is taken into account to ensure the relevance of the resulting functional evidence. Some phenotypic outcomes include an assessment of model system viability. This can include survival, morphology, or competitive survival assays of a model system. Another type of phenotypic selection is drug sensitivity assays, which assess model survival under drug selection. Furthermore, reporter assays are often used to measure protein levels or transcriptional activity. molecular barcodes, as seen in MPRAs, are often utilized.Fowler, D. M. & Fields, S. Deep mutational scanning: a new style of protein science. Nat Methods 11, 801–807 (2014). Finally, proteins produced in these experiments can be purified and assayed. This can be achieved by performing a protein abundance assay, where the total amount of protein present is assessed.Starita, L. M. & Fields, S. Deep Mutational Scanning: A Highly Parallel Method to Measure the Effects of Mutation on Protein Function. Cold Spring Harb Protoc 2015, pdb.top077503 (2015). Alternatively, researchers can examine a protein's functionality by, for example, testing the rate of substrate conversion.Mulvey, B., Lagunas, T. & Dougherty, J. D. Massively Parallel Reporter Assays: Defining Functional Psychiatric Genetic Variants Across Biological Contexts. Biol Psychiatry 89, 76–89 (2021). Due to the varying nature of these phenotypic analyses, researchers can receive different results based on their choice of phenotypic selection methods.
Variant score calculation