{"id":26407,"date":"2025-07-21T15:37:09","date_gmt":"2025-07-21T15:37:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/26407\/"},"modified":"2025-07-21T15:37:09","modified_gmt":"2025-07-21T15:37:09","slug":"multiplexed-assays-of-variant-effect-for-clinical-variant-interpretation","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/26407\/","title":{"rendered":"Multiplexed assays of variant effect for clinical variant interpretation"},"content":{"rendered":"

Chen, E. et al. Rates and classification of variants of uncertain significance in hereditary disease genetic testing. JAMA Netw. Open 6, e2339571 (2023).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Rehm, H. L. et al. The landscape of reported VUS in multi-gene panel and genomic testing: time for a change. Genet. Med. 25, 100947 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

LaDuca, H. et al. A clinical guide to hereditary cancer panel testing: evaluation of gene-specific cancer associations and sensitivity of genetic testing criteria in a cohort of 165,000 high-risk patients. Genet. Med. 22, 407\u2013415 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ndugga-Kabuye, M. K. & Issaka, R. B. Inequities in multi-gene hereditary cancer testing: lower diagnostic yield and higher VUS rate in individuals who identify as Hispanic, African or Asian and Pacific Islander as compared to European. Fam. Cancer 18, 465\u2013469 (2019).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Roberts, M. E. et al. Ancestry-specific hereditary cancer panel yields: moving toward more personalized risk assessment. J. Genet. Couns. 29, 598\u2013606 (2020).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kwon, D. H.-M., Borno, H. T., Cheng, H. H., Zhou, A. Y. & Small, E. J. Ethnic disparities among men with prostate cancer undergoing germline testing. Urol. Oncol. 38, 80.e1\u201380.e7 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405\u2013424 (2015). This paper established the now widely adopted five-tier classification system (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign) and a standardized evidence-based framework for interpreting sequence variants in Mendelian disorders, promoting consistency and reliability in clinical genetic testing.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Fowler, D. M. et al. An atlas of variant effects to understand the genome at nucleotide resolution. Genome Biol. 24, 147 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gelman, H. et al. Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation. Genome Med. 11, 85 (2019). This paper provides consensus recommendations to ensure rigorous generation, reporting and clinical integration of multiplexed functional assay data, enabling these data sets to be reliably incorporated as evidence within the ACMG\/AMP variant interpretation framework.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Brnich, S. E. et al. Recommendations for application of the functional evidence PS3\/BS3 criterion using the ACMG\/AMP sequence variant interpretation framework. Genome Med. 12, 3 (2019). This paper provides a structured, evidence-based framework for evaluating and applying functional assay data (PS3\/BS3 criteria) in clinical variant interpretation, addressing previous ambiguity and inconsistency in the use of functional evidence.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Criteria Specification Registry. https:\/\/cspec.genome.network\/cspec\/ui\/svi\/<\/a>.<\/p>\n

Findlay, G. M. Linking genome variants to disease: scalable approaches to test the functional impact of human mutations. Hum. Mol. Genet. 30, R187\u2013R197 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Weile, J. & Roth, F. P. Multiplexed assays of variant effects contribute to a growing genotype\u2013phenotype atlas. Hum. Genet. 137, 665\u2013678 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Tabet, D., Parikh, V., Mali, P., Roth, F. P. & Claussnitzer, M. Scalable functional assays for the interpretation of human genetic variation. Annu. Rev. Genet. 56, 441\u2013465 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Geck, R. C., Boyle, G., Amorosi, C. J., Fowler, D. M. & Dunham, M. J. Measuring pharmacogene variant function at scale using multiplexed assays. Annu. Rev. Pharmacol. Toxicol. 62, 531\u2013550 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Fowler, D. M. et al. High-resolution mapping of protein sequence\u2013function relationships. Nat. Methods 7, 741\u2013746 (2010).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ernst, A. et al. Coevolution of PDZ domain\u2013ligand interactions analyzed by high-throughput phage display and deep sequencing. Mol. Biosyst. 6, 1782\u20131790 (2010).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Starita, L. M. et al. Activity-enhancing mutations in an E3 ubiquitin ligase identified by high-throughput mutagenesis. Proc. Natl Acad. Sci. USA 110, E1263\u2013E1272 (2013).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Adkar, B. V. et al. Protein model discrimination using mutational sensitivity derived from deep sequencing. Structure 20, 371\u2013381 (2012).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Jacquier, H. et al. Capturing the mutational landscape of the beta-lactamase TEM-1. Proc. Natl Acad. Sci. USA 110, 13067\u201313072 (2013).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Firnberg, E., Labonte, J. W., Gray, J. J. & Ostermeier, M. A comprehensive, high-resolution map of a gene\u2019s fitness landscape. Mol. Biol. Evol. 31, 1581\u20131592 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hietpas, R. T., Jensen, J. D. & Bolon, D. N. A. Experimental illumination of a fitness landscape. Proc. Natl Acad. Sci. USA 108, 7896\u20137901 (2011).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Dutta, S. et al. Determinants of BH3 binding specificity for Mcl-1 versus Bcl-xL. J. Mol. Biol. 398, 747\u2013762 (2010).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Traxlmayr, M. W. et al. Construction of a stability landscape of the CH3 domain of human IgG1 by combining directed evolution with high throughput sequencing. J. Mol. Biol. 423, 397\u2013412 (2012).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Bloom, J. D. An experimentally determined evolutionary model dramatically improves phylogenetic fit. Mol. Biol. Evol. 31, 1956\u20131978 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Melnikov, A. et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat. Biotechnol. 30, 271\u2013277 (2012).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Wagenaar, T. R. et al. Resistance to vemurafenib resulting from a novel mutation in the BRAFV600E kinase domain. Pigment Cell Melanoma Res. 27, 124\u2013133 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chan, K. K. et al. Engineering human ACE2 to optimize binding to the spike protein of SARS coronavirus 2. Science 369, 1261\u20131265 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Weile, J. et al. A framework for exhaustively mapping functional missense variants. Mol. Syst. Biol. 13, 957 (2017). This study integrated deep mutational scanning with yeast-complementation assays to systematically assess the impact of every possible missense variant in six human genes within a single experimental framework.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kotler, E. et al. A systematic p53 mutation library links differential functional impact to cancer mutation pattern and evolutionary conservation. Mol. Cell 71, 178\u2013190.e8 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Giacomelli, A. O. et al. Mutational processes shape the landscape of TP53 mutations in human cancer. Nat. Genet. 50, 1381\u20131387 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Matreyek, K. A. et al. Multiplex assessment of protein variant abundance by massively parallel sequencing. Nat. Genet. 50, 874\u2013882 (2018). This study was the first use of variant abundance by massively parallel sequencing, a generalizable, high-throughput method that directly quantifies the intracellular abundance of thousands of protein variants in parallel using massively parallel sequencing.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mighell, T. L., Evans-Dutson, S. & O\u2019Roak, B. J. A saturation mutagenesis approach to understanding PTEN lipid phosphatase activity and genotype\u2013phenotype relationships. Am. J. Hum. Genet. 102, 943\u2013955 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816\u2013821 (2012).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Cong, L. et al. Multiplex genome engineering using CRISPR\/Cas systems. Science 339, 819\u2013823 (2013).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Hsu, P. D., Lander, E. S. & Zhang, F. Development and applications of CRISPR\u2013Cas9 for genome engineering. Cell 157, 1262\u20131278 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Findlay, G. M., Boyle, E. A., Hause, R. J., Klein, J. C. & Shendure, J. Saturation editing of genomic regions by multiplex homology-directed repair. Nature 513, 120\u2013123 (2014). This paper introduces saturation genome editing, CRISPR\u2013Cas9-mediated double-stranded breaks coupled with multiplex homology-directed repair using a complex library of donor plasmid DNAs, enabling the introduction of all possible single-nucleotide variants or small sequence changes directly into endogenous loci of human cells.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

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\u2013424 (2016).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Anzalone, A. V. et al. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576, 149\u2013157 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gasperini, M., Starita, L. & Shendure, J. The power of multiplexed functional analysis of genetic variants. Nat. Protoc. 11, 1782\u20131787 (2016).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Patwardhan, R. P. et al. High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis. Nat. Biotechnol. 27, 1173\u20131175 (2009).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ozturk, K. et al. Interface-guided phenotyping of coding variants in the transcription factor RUNX1. Cell Rep. 43, 114436 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ursu, O. et al. Massively parallel phenotyping of coding variants in cancer with Perturb-seq. Nat. Biotechnol. 40, 896\u2013905 (2022). This study demonstrates a scalable, single-cell Perturb-seq approach to functionally characterize hundreds of cancer-associated coding variants in TP53 and KRAS, revealing a continuum of phenotypic effect that cannot be predicted solely by variant frequency, thereby enabling more precise functional annotation of variants at scale.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Xu, H. et al. Single cell sequencing as a general variant interpretation assay. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2023.12.12.571130<\/a> (2023).<\/p>\n

Hasle, N. et al. High-throughput, microscope-based sorting to dissect cellular heterogeneity. Mol. Syst. Biol. 16, e9442 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Yang, F. et al. Identifying pathogenicity of human variants via paralog-based yeast complementation. PLoS Genet. 13, e1006779 (2017).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Yeh, C.-L. C., Jiang, P. & Dunham, M. J. High-throughput approaches to functional characterization of genetic variation in yeast. Curr. Opin. Genet. Dev. 76, 101979 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kato, S. et al. Understanding the function\u2013structure and function\u2013mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis. Proc. Natl Acad. Sci. USA 100, 8424\u20138429 (2003). This paper presented the first study to generate a comprehensive, high-resolution functional map of all possible missense mutations in a human disease gene (TP53).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Monteiro, A. N., August, A. & Hanafusa, H. Evidence for a transcriptional activation function of BRCA1 C-terminal region. Proc. Natl Acad. Sci. USA 93, 13595\u201313599 (1996).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Monteiro, A. N., August, A. & Hanafusa, H. Common BRCA1 variants and transcriptional activation. Am. J. Hum. Genet. 61, 761\u2013762 (1997).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Vallon-Christersson, J. et al. Functional analysis of BRCA1 C-terminal missense mutations identified in breast and ovarian cancer families. Hum. Mol. Genet. 10, 353\u2013360 (2001).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Richards, C. S. et al. ACMG recommendations for standards for interpretation and reporting of sequence variations: revisions 2007. Genet. Med. 10, 294\u2013300 (2008).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kazazian, H. H., Boehm, C. D. & Seltzer, W. K. ACMG recommendations for standards for interpretation of sequence variations. Genet. Med. 2, 302\u2013303 (2000).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Olivier, M., Hollstein, M. & Hainaut, P. TP53 mutations in human cancers: origins, consequences, and clinical use. Cold Spring Harb. Perspect. Biol. 2, a001008 (2010).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Soussi, T., Kato, S., Levy, P. P. & Ishioka, C. Reassessment of the TP53 mutation database in human disease by data mining with a library of TP53 missense mutations. Hum. Mutat. 25, 6\u201317 (2005).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Iacopetta, B. et al. Functional categories of TP53 mutation in colorectal cancer: results of an international collaborative study. Ann. Oncol. 17, 842\u2013847 (2006).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Fortuno, C. et al. Specifications of the ACMG\/AMP variant interpretation guidelines for germline TP53 variants. Hum. Mutat. 42, 223\u2013236 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

McLaughlin, R. N. Jr, Poelwijk, F. J., Raman, A., Gosal, W. S. & Ranganathan, R. The spatial architecture of protein function and adaptation. Nature 491, 138\u2013142 (2012).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gajula, K. S. et al. High-throughput mutagenesis reveals functional determinants for DNA targeting by activation-induced deaminase. Nucleic Acids Res. 42, 9964\u20139975 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Doolan, K. M. & Colby, D. W. Conformation-dependent epitopes recognized by prion protein antibodies probed using mutational scanning and deep sequencing. J. Mol. Biol. 427, 328\u2013340 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Starita, L. M. et al. Massively parallel functional analysis of BRCA1 RING domain variants. Genetics 200, 413\u2013422 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Majithia, A. R. et al. Prospective functional classification of all possible missense variants in PPARG. Nat. Genet. 48, 1570\u20131575 (2016).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Starita, L. M. et al. Variant interpretation: functional assays to the rescue. Am. J. Hum. Genet. 101, 315\u2013325 (2017).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kachroo, A. H. et al. Systematic humanization of yeast genes reveals conserved functions and genetic modularity. Science 348, 921\u2013925 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

van Loggerenberg, W. et al. Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation. Am. J. Hum. Genet. 110, 1769\u20131786 (2023).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Lo, R. S. et al. The functional impact of 1,570 individual amino acid substitutions in human OTC. Am. J. Hum. Genet. 110, 863\u2013879 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Weile, J. et al. Shifting landscapes of human MTHFR missense-variant effects. Am. J. Hum. Genet. 108, 1283\u20131300 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ollodart, A. R. et al. Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae. Genetics 218, iyab058 (2021).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Sun, S. et al. A proactive genotype-to-patient-phenotype map for cystathionine beta-synthase. Genome Med. 12, 13 (2020).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Silverstein, R. A. et al. A systematic genotype\u2013phenotype map for missense variants in the human intellectual disability-associated gene GDI1. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2021.10.06.463360<\/a> (2021).<\/p>\n

Gersing, S. et al. A comprehensive map of human glucokinase variant activity. Genome Biol. 24, 97 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Jia, X. et al. Massively parallel functional testing of MSH2 missense variants conferring Lynch syndrome risk. Am. J. Hum. Genet. 108, 163\u2013175 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Sung, A. Y. et al. Systematic analysis of NDUFAF6 in complex I assembly and mitochondrial disease. Nat. Metab. 6, 1128\u20131142 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Findlay, G. M. et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature 562, 217\u2013222 (2018). This study demonstrated that saturation genome editing enables high-throughput, accurate functional assessment of nearly all possible single-nucleotide variants in key exons of BRCA1 (BRCT and RING domains), providing immediate and clinically actionable data for the classification of variants of uncertain significance.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Radford, E. J. et al. Saturation genome editing of DDX3X clarifies pathogenicity of germline and somatic variation. Nat. Commun. 14, 7702 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Buckley, M. et al. Saturation genome editing maps the functional spectrum of pathogenic VHL alleles. Nat. Genet. 56, 1446\u20131455 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Olvera-Le\u00f3n, R. et al. High-resolution functional mapping of RAD51C by saturation genome editing. Cell 187, 5719\u20135734.e19 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Waters, A. J. et al. Saturation genome editing of BAP1 functionally classifies somatic and germline variants. Nat. Genet. 56, 1434\u20131445 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Blomen, V. A. et al. Gene essentiality and synthetic lethality in haploid human cells. Science 350, 1092\u20131096 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Meitlis, I. et al. Multiplexed functional assessment of genetic variants in CARD11. Am. J. Hum. Genet. 107, 1029\u20131043 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Sahu, S. et al. Saturation genome editing of 11 codons and exon 13 of BRCA2 coupled with chemotherapeutic drug response accurately determines pathogenicity of variants. PLoS Genet. 19, e1010940 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Huang, H. et al. Saturation genome editing-based functional evaluation and clinical classification of BRCA2 single nucleotide variants. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2023.12.14.571597<\/a> (2023).<\/p>\n

Funk, J. S. et al. Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations. Nat. Genet. 57, 140\u2013153 (2025).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Yue, P., Li, Z. & Moult, J. Loss of protein structure stability as a major causative factor in monogenic disease. J. Mol. Biol. 353, 459\u2013473 (2005).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Redler, R. L., Das, J., Diaz, J. R. & Dokholyan, N. V. Protein destabilization as a common factor in diverse inherited disorders. J. Mol. Evol. 82, 11\u201316 (2016).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Amorosi, C. J. et al. Massively parallel characterization of CYP2C9 variant enzyme activity and abundance. Am. J. Hum. Genet. 108, 1735\u20131751 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Boyle, G. E. et al. Deep mutational scanning of CYP2C19 in human cells reveals a substrate specificity-abundance tradeoff. Genetics 228, iyae156 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chiasson, M. A. et al. Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact. eLife 9, e58026 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Suiter, C. C. et al. Massively parallel variant characterization identifies NUDT15 alleles associated with thiopurine toxicity. Proc. Natl Acad. Sci. USA 117, 5394\u20135401 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Clausen, L. et al. A mutational atlas for Parkin proteostasis. Nat. Commun. 15, 1541 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Muhammad, A. et al. High-throughput functional mapping of variants in an arrhythmia gene, KCNE1, reveals novel biology. Genome Med. 16, 73 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

O\u2019Neill, M. J. et al. Multiplexed assays of variant effect and automated patch clamping improve KCNH2-LQTS variant classification and cardiac event risk stratification. Circulation 150, 1869\u20131881 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kozek, K. A. et al. High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KV11.1. Heart Rhythm 17, 2180\u20132189 (2020).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gr\u00f8nb\u00e6k-Thygesen, M. et al. Deep mutational scanning reveals a correlation between degradation and toxicity of thousands of aspartoacylase variants. Nat. Commun. 15, 4026 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Yee, S. W. et al. The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics. Mol. Cell 84, 1932\u20131947.e10 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Popp, N. A. et al. Multiplex, multimodal mapping of variant effects in secreted proteins. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2024.04.01.587474<\/a> (2024).<\/p>\n

Tavtigian, S. V. et al. Modeling the ACMG\/AMP variant classification guidelines as a Bayesian classification framework. Genet. Med. 20, 1054\u20131060 (2018). This paper translated the ACMG\/AMP variant classification guidelines into a quantitative Bayesian framework by assigning odds of pathogenicity to each evidence strength level (supporting, moderate, strong and very strong) and modelling the combination of evidence as multiplicative updates to a prior probability of pathogenicity.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Fayer, S. et al. Closing the gap: systematic integration of multiplexed functional data resolves variants of uncertain significance in BRCA1, TP53, and PTEN. Am. J. Hum. Genet. 108, 2248\u20132258 (2021). This paper systematically integrated multiplexed assays of variant effect evidence to resolve variants of uncertain significance in clinically actionable genes, BRCA1, TP53 and PTEN, using a diagnostic laboratory cohort and demonstrated that 49% of such variants in BRCA1, 69% in TP53 and 15% in PTEN could be reclassified.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mester, J. L. et al. Gene-specific criteria for PTEN variant curation: recommendations from the ClinGen PTEN expert panel. Hum. Mutat. 39, 1581\u20131592 (2018).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Scott, A. et al. Saturation-scale functional evidence supports clinical variant interpretation in Lynch syndrome. Genome Biol. 23, 266 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Miller, D. T. et al. ACMG SF v3.2 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet. Med. 25, 100866 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Adamovich, A. I. et al. The functional impact of BRCA1 BRCT domain variants using multiplexed DNA double-strand break repair assays. Am. J. Hum. Genet. 109, 618\u2013630 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Floyd, B. J. et al. Proactive variant effect mapping aids diagnosis in pediatric cardiac arrest. Circ. Genom. Precis. Med. 16, e003792 (2023).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Boettcher, S. et al. A dominant-negative effect drives selection of TP53 missense mutations in myeloid malignancies. Science 365, 599\u2013604 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Zheng, H. et al. Proactive functional classification of all possible missense single-nucleotide variants in KCNQ4. Genome Res. 32, 1573\u20131584 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Glazer, A. M. et al. Deep mutational scan of an SCN5A voltage sensor. Circ. Genom. Precis. Med. 13, e002786 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Rubin, A. F. et al. MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays. Genome Biol. 26, 13 (2025). This study provides a centralized, publicly accessible repository for multiplexed assays of variant effect data.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

IGVF Consortium. Deciphering the impact of genomic variation on function. Nature 633, 47\u201357 (2024). This paper established a comprehensive framework and resource for systematically mapping the functional consequences of human genomic variation across hundreds of cell types and states, integrating single-cell mapping, high-throughput genomic perturbations and predictive modelling to link both coding and non-coding variants to molecular and cellular phenotypes.<\/p>\n

CAS<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Claussnitzer, M. et al. Minimum information and guidelines for reporting a multiplexed assay of variant effect. Genome Biol. 25, 100 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Zhang, F. & Lupski, J. R. Non-coding genetic variants in human disease. Hum. Mol. Genet. 24, R102\u2013R110 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

French, J. D. & Edwards, S. L. The role of noncoding variants in heritable disease. Trends Genet. 36, 880\u2013891 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mattioli, K. et al. High-throughput functional analysis of lncRNA core promoters elucidates rules governing tissue specificity. Genome Res. 29, 344\u2013355 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Patwardhan, R. P. et al. Massively parallel functional dissection of mammalian enhancers in vivo. Nat. Biotechnol. 30, 265\u2013270 (2012).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kheradpour, P. et al. Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay. Genome Res. 23, 800\u2013811 (2013).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Zhao, W. et al. Massively parallel functional annotation of 3\u2032 untranslated regions. Nat. Biotechnol. 32, 387\u2013391 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Birnbaum, R. Y. et al. Systematic dissection of coding exons at single nucleotide resolution supports an additional role in cell-specific transcriptional regulation. PLoS Genet. 10, e1004592 (2014).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kwasnieski, J. C., Fiore, C., Chaudhari, H. G. & Cohen, B. A. High-throughput functional testing of ENCODE segmentation predictions. Genome Res. 24, 1595\u20131602 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Wong, M. S., Kinney, J. B. & Krainer, A. R. Quantitative activity profile and context dependence of all human 5\u2032 splice sites. Mol. Cell 71, 1012\u20131026.e3 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Doni Jayavelu, N., Jajodia, A., Mishra, A. & Hawkins, R. D. Candidate silencer elements for the human and mouse genomes. Nat. Commun. 11, 1061 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Oikonomou, P., Goodarzi, H. & Tavazoie, S. Systematic identification of regulatory elements in conserved 3\u2032 UTRs of human transcripts. Cell Rep. 7, 281\u2013292 (2014).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Sample, P. J. et al. Human 5\u2032 UTR design and variant effect prediction from a massively parallel translation assay. Nat. Biotechnol. 37, 803\u2013809 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mueller, W. F., Larsen, L. S. Z., Garibaldi, A., Hatfield, G. W. & Hertel, K. J. The silent sway of splicing by synonymous substitutions. J. Biol. Chem. 290, 27700\u201327711 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Julien, P., Mi\u00f1ana, B., Baeza-Centurion, P., Valc\u00e1rcel, J. & Lehner, B. The complete local genotype\u2013phenotype landscape for the alternative splicing of a human exon. Nat. Commun. 7, 11558 (2016).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ke, S. et al. Saturation mutagenesis reveals manifold determinants of exon definition. Genome Res. 28, 11\u201324 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chong, R. et al. A multiplexed assay for exon recognition reveals that an unappreciated fraction of rare genetic variants cause large-effect splicing disruptions. Mol. Cell 73, 183\u2013194.e8 (2019).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Rosenberg, A. B., Patwardhan, R. P., Shendure, J. & Seelig, G. Learning the sequence determinants of alternative splicing from millions of random sequences. Cell 163, 698\u2013711 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Braun, S. et al. Decoding a cancer-relevant splicing decision in the RON proto-oncogene using high-throughput mutagenesis. Nat. Commun. 9, 3315 (2018).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Safra, M., Nir, R., Farouq, D., Vainberg Slutskin, I. & Schwartz, S. TRUB1 is the predominant pseudouridine synthase acting on mammalian mRNA via a predictable and conserved code. Genome Res. 27, 393\u2013406 (2017).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Liu, X. et al. Learning cis-regulatory principles of ADAR-based RNA editing from CRISPR-mediated mutagenesis. Nat. Commun. 12, 2165 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Shukla, C. J. et al. High-throughput identification of RNA nuclear enrichment sequences. EMBO J. 37, e98452 (2018).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

McQuerry, J. A. et al. Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients. Sci. Rep. 12, 7576 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Rhine, C. L. et al. Massively parallel reporter assays discover de novo exonic splicing mutants in paralogs of autism genes. PLoS Genet. 18, e1009884 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kircher, M. et al. Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution. Nat. Commun. 10, 3583 (2019). This study demonstrated that saturation mutagenesis combined with massively parallel reporter assays enables single base-pair resolution functional mapping of disease-associated regulatory elements.<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ellingford, J. M. et al. Recommendations for clinical interpretation of variants found in non-coding regions of the genome. Genome Med. 14, 73 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Li, M. M. et al. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J. Mol. Diagn. 19, 4\u201323 (2017).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Horak, P. et al. Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC). Genet. Med. 24, 986\u2013998 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Johnson, A. et al. Clinical use of precision oncology decision support. JCO Precis. Oncol. 2017, 1\u201312 (2017).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Dogruluk, T. et al. Identification of variant-specific functions of PIK3CA by rapid phenotyping of rare mutations. Cancer Res. 75, 5341\u20135354 (2015).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Narayan, P. et al. FDA approval summary: alpelisib plus fulvestrant for patients with HR-positive, HER2-negative, PIK3CA-mutated, advanced or metastatic breast cancer. Clin. Cancer Res. 27, 1842\u20131849 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

de Bruijn, I. et al. Analysis and visualization of longitudinal genomic and clinical data from the AACR Project GENIE Biopharma Collaborative in cBioPortal. Cancer Res. 83, 3861\u20133867 (2023).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Bridgford, J. L. et al. Novel drivers and modifiers of MPL-dependent oncogenic transformation identified by deep mutational scanning. Blood 135, 287\u2013292 (2020).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Estevam, G. O. et al. Conserved regulatory motifs in the juxtamembrane domain and kinase N-lobe revealed through deep mutational scanning of the MET receptor tyrosine kinase domain. eLife 12, RP91619 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Bandaru, P. et al. Deconstruction of the Ras switching cycle through saturation mutagenesis. eLife 6, e27810 (2017).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Cantor, A. J., Shah, N. H. & Kuriyan, J. Deep mutational analysis reveals functional trade-offs in the sequences of EGFR autophosphorylation sites. Proc. Natl Acad. Sci. USA 115, E7303\u2013E7312 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Belli, O., Karava, K., Farouni, R. & Platt, R. J. Multimodal scanning of genetic variants with base and prime editing. Nat. Biotechnol. https:\/\/doi.org\/10.1038\/s41587-024-02439-1<\/a> (2024).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kohsaka, S. et al. A method of high-throughput functional evaluation of EGFR gene variants of unknown significance in cancer. Sci. Transl. Med. 9, eaan6566 (2017).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kim, Y., Oh, H.-C., Lee, S. & Kim, H. H. Saturation profiling of drug-resistant genetic variants using prime editing. Nat. Biotechnol. https:\/\/doi.org\/10.1038\/s41587-024-02465-z<\/a> (2024).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chardon, F. M. et al. A multiplex, prime editing framework for identifying drug resistance variants at scale. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2023.07.27.550902<\/a> (2023).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Ma, L. et al. CRISPR\u2013Cas9-mediated saturated mutagenesis screen predicts clinical drug resistance with improved accuracy. Proc. Natl Acad. Sci. USA 114, 11751\u201311756 (2017).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Chakraborty, S. et al. Profiling of drug resistance in Src kinase at scale uncovers a regulatory network coupling autoinhibition and catalytic domain dynamics. Cell Chem. Biol. 31, 207\u2013220.e11 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Awad, M. M. et al. Acquired resistance to KRASG12C inhibition in cancer. N. Engl. J. Med. 384, 2382\u20132393 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Persky, N. S. et al. Defining the landscape of ATP-competitive inhibitor resistance residues in protein kinases. Nat. Struct. Mol. Biol. 27, 92\u2013104 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kim, J. et al. A framework for individualized splice-switching oligonucleotide therapy. Nature 619, 828\u2013836 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

McKee, A. G. et al. General trends in the effects of VX-661 and VX-445 on the plasma membrane expression of clinical CFTR variants. Cell Chem. Biol. 30, 632\u2013642.e5 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Howard, C. J. et al. High resolution deep mutational scanning of the melanocortin-4 receptor enables target characterization for drug discovery. eLife 13, RP104725 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mathy, C. J. P. et al. A complete allosteric map of a GTPase switch in its native cellular network. Cell Syst. 14, 237\u2013246.e7 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Tack, D. S. et al. The genotype\u2013phenotype landscape of an allosteric protein. Mol. Syst. Biol. 17, e10179 (2021).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Faure, A. J. et al. Mapping the energetic and allosteric landscapes of protein binding domains. Nature 604, 175\u2013183 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Leander, M., Yuan, Y., Meger, A., Cui, Q. & Raman, S. Functional plasticity and evolutionary adaptation of allosteric regulation. Proc. Natl Acad. Sci. USA 117, 25445\u201325454 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Weng, C., Faure, A. J., Escobedo, A. & Lehner, B. The energetic and allosteric landscape for KRAS inhibition. Nature 626, 643\u2013652 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mason, D. M. et al. High-throughput antibody engineering in mammalian cells by CRISPR\/Cas9-mediated homology-directed mutagenesis. Nucleic Acids Res. 46, 7436\u20137449 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Wollacott, A. M. et al. Structural prediction of antibody\u2013APRIL complexes by computational docking constrained by antigen saturation mutagenesis library data. J. Mol. Recognit. 32, e2778 (2019).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Koenig, P., Sanowar, S., Lee, C. V. & Fuh, G. Tuning the specificity of a Two-in-One Fab against three angiogenic antigens by fully utilizing the information of deep mutational scanning. MAbs 9, 959\u2013967 (2017).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Renn, A., Fu, Y., Hu, X., Hall, M. D. & Simeonov, A. Fruitful neutralizing antibody pipeline brings hope to defeat SARS-CoV-2. Trends Pharmacol. Sci. 41, 815\u2013829 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Mengist, H. M. et al. Mutations of SARS-CoV-2 spike protein: implications on immune evasion and vaccine-induced immunity. Semin. Immunol. 55, 101533 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Starr, T. N. et al. Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding. Cell 182, 1295\u20131310.e20 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Starr, T. N. et al. Prospective mapping of viral mutations that escape antibodies used to treat COVID-19. Science 371, 850\u2013854 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Starr, T. N., Greaney, A. J., Dingens, A. S. & Bloom, J. D. Complete map of SARS-CoV-2 RBD mutations that escape the monoclonal antibody LY-CoV555 and its cocktail with LY-CoV016. Cell Rep. Med. 2, 100255 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Greaney, A. J. et al. Mapping mutations to the SARS-CoV-2 RBD that escape binding by different classes of antibodies. Nat. Commun. 12, 4196 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Greaney, A. J., Starr, T. N. & Bloom, J. D. An antibody-escape estimator for mutations to the SARS-CoV-2 receptor-binding domain. Virus Evol. 8, veac021 (2022).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Dadonaite, B. et al. Spike deep mutational scanning helps predict success of SARS-CoV-2 clades. Nature 631, 617\u2013626 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Li, Y., Arcos, S., Sabsay, K. R., Te Velthuis, A. J. W. & Lauring, A. S. Deep mutational scanning reveals the functional constraints and evolutionary potential of the influenza A virus PB1 protein. J. Virol. 97, e0132923 (2023).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kikawa, C. et al. The effect of single mutations in Zika virus envelope on escape from broadly neutralizing antibodies. J. Virol. 97, e0141423 (2023).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Radford, C. E. et al. Mapping the neutralizing specificity of human anti-HIV serum by deep mutational scanning. Cell Host Microbe 31, 1200\u20131215.e9 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Lei, R. et al. Mutational fitness landscape of human influenza H3N2 neuraminidase. Cell Rep. 42, 111951 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Soh, Y. S., Moncla, L. H., Eguia, R., Bedford, T. & Bloom, J. D. Comprehensive mapping of adaptation of the avian influenza polymerase protein PB2 to humans. eLife 8, e45079 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Dadonaite, B. et al. Deep mutational scanning of H5 hemagglutinin to inform influenza virus surveillance. PLoS Biol. 22, e3002916 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Larsen, B. B. et al. Functional and antigenic landscape of the Nipah virus receptor-binding protein. Cell 188, 2480\u20132494.e22 (2025).<\/p>\n

PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Carr, C. R. et al. Deep mutational scanning reveals functional constraints and antibody-escape potential of Lassa virus glycoprotein complex. Immunity 57, 2061\u20132076.e11 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Martin-Rufino, J. D. et al. Massively parallel base editing to map variant effects in human hematopoiesis. Cell 186, 2456\u20132474.e24 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Schmidt, R. et al. Base-editing mutagenesis maps alleles to tune human T cell functions. Nature 625, 805\u2013812 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Walsh, Z. H. et al. Mapping variant effects on anti-tumor hallmarks of primary human T cells with base-editing screens. Nat. Biotechnol. https:\/\/doi.org\/10.1038\/s41587-024-02235-x<\/a> (2024).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Richter, M. F. et al. Phage-assisted evolution of an adenine base editor with improved Cas domain compatibility and activity. Nat. Biotechnol. 38, 883\u2013891 (2020).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Nishimasu, H. et al. Engineered CRISPR\u2013Cas9 nuclease with expanded targeting space. Science 361, 1259\u20131262 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Thuronyi, B. W. et al. Continuous evolution of base editors with expanded target compatibility and improved activity. Nat. Biotechnol. 37, 1070\u20131079 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kim, M. Y. et al. Genetic inactivation of CD33 in hematopoietic stem cells to enable CAR T cell immunotherapy for acute myeloid leukemia. Cell 173, 1439\u20131453.e19 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Cheng, J. et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science 381, eadg7492 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Frazer, J. et al. Disease variant prediction with deep generative models of evolutionary data. Nature 599, 91\u201395 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Orenbuch, R. et al. Proteome-wide model for human disease genetics. Preprint at medRxiv https:\/\/doi.org\/10.1101\/2023.11.27.23299062<\/a> (2025).<\/p>\n

Schneider, K., Zelley, K., Nichols, K. E., Schwartz Levine, A. & Garber, J. GeneReviews (Univ. Washington, 1993).<\/p>\n

Sondka, Z. et al. COSMIC: a curated database of somatic variants and clinical data for cancer. Nucleic Acids Res. 52, D1210\u2013D1217 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Critical Assessment of Genome Interpretation Consortium. CAGI, the critical assessment of genome interpretation, establishes progress and prospects for computational genetic variant interpretation methods. Genome Biol. 25, 53 (2024).<\/p>\n


\n Google Scholar<\/a>\u00a0\n <\/p>\n

Livesey, B. J. & Marsh, J. A. Using deep mutational scanning to benchmark variant effect predictors and identify disease mutations. Mol. Syst. Biol. 16, e9380 (2020). This study demonstrated that deep mutational scanning provides an independent, quantitative benchmark for evaluating computational variant effect predictors, revealing that experimental deep mutational scanning data often outperform current computational methods in identifying pathogenic missense mutations.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Notin, P. et al. ProteinGym: large-scale benchmarks for protein design and fitness prediction. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2023.12.07.570727<\/a> (2023).<\/p>\n

Avsec, \u017d. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat. Methods 18, 1196\u20131203 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gray, V. E., Hause, R. J., Luebeck, J., Shendure, J. & Fowler, D. M. Quantitative missense variant effect prediction using large-scale mutagenesis data. Cell Syst. 6, 116\u2013124.e3 (2018).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Jagota, M. et al. Cross-protein transfer learning substantially improves disease variant prediction. Genome Biol. 24, 182 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Lafita, A. et al. Fine-tuning protein language models with deep mutational scanning improves variant effect prediction. Preprint at https:\/\/doi.org\/10.48550\/arXiv.2405.06729<\/a> (2024).<\/p>\n

Dieckhaus, H., Brocidiacono, M., Randolph, N. Z. & Kuhlman, B. Transfer learning to leverage larger datasets for improved prediction of protein stability changes. Proc. Natl Acad. Sci. USA 121, e2314853121 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Tsuboyama, K. et al. Mega-scale experimental analysis of protein folding stability in biology and design. Nature 620, 434\u2013444 (2023).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Dawood, M. et al. Using multiplexed functional data to reduce variant classification inequities in underrepresented populations. Genome Med. 16, 143 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kuang, D. et al. MaveRegistry: a collaboration platform for multiplexed assays of variant effect. Bioinformatics 37, 3382\u20133383 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Beltran, A., Jiang, X., Shen, Y. & Lehner, B. Site-saturation mutagenesis of 500 human protein domains. Nature 637, 885\u2013894 (2025).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Kreimer, A. et al. Massively parallel reporter perturbation assays uncover temporal regulatory architecture during neural differentiation. Nat. Commun. 13, 1504 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Capauto, D. et al. Characterization of enhancer activity in early human neurodevelopment using massively parallel reporter assay (MPRA) and forebrain organoids. Sci. Rep. 14, 3936 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Deng, C. et al. Massively parallel characterization of regulatory elements in the developing human cortex. Science 384, eadh0559 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Allen, S. et al. Workshop report: the clinical application of data from multiplex assays of variant effect (MAVEs), 12 July 2023. Eur. J. Hum. Genet. 32, 593\u2013600 (2024).<\/p>\n

PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Villani, R. M. et al. Consultation informs strategies for improving the use of functional evidence in variant classification.\u00a0Am. J. Hum. Genet. 112, 1489\u20131495 (2025).\u00a0<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Park, M. S. et al. Insights on improving accessibility and usability of functional data to unlock their potential for variant interpretation. Am. J. Hum. Genet. 112, 1468\u20131478 (2025). This paper surveys genetics professionals actively engaged in clinical variant interpretation, with both quantitative and qualitative analyses performed on the responses to assess current practices, barriers and needs related to the use of high-throughput functional assay data for variant classification.<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Clark, K. A. et al. Comprehensive evaluation and efficient classification of BRCA1 RING domain missense substitutions. Am. J. Hum. Genet. 109, 1153\u20131174 (2022).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gebbia, M. et al. A missense variant effect map for the human tumor-suppressor protein CHK2. Am. J. Hum. Genet. 111, 2675\u20132692 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Shepherdson, J. L. et al. Mutational scanning of CRX classifies clinical variants and reveals biochemical properties of the transcriptional effector domain. Genome Res. 34, 1540\u20131552 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Gilbert, M. A. et al. Functional characterization of 2,832 JAG1 variants supports reclassification for Alagille syndrome and improves guidance for clinical variant interpretation. Am. J. Hum. Genet. 111, 1656\u20131672 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

McDonnell, A. F. et al. Deep mutational scanning quantifies DNA binding and predicts clinical outcomes of PAX6 variants. Mol. Syst. Biol. 20, 825\u2013844 (2024).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n PubMed Central<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Wan, A., Place, E., Pierce, E. A. & Comander, J. Characterizing variants of unknown significance in rhodopsin: a functional genomics approach. Hum. Mutat. 40, 1127\u20131144 (2019).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n

Fortuno, C. et al. An updated quantitative model to classify missense variants in the TP53 gene: a novel multifactorial strategy. Hum. Mutat. 42, 1351\u20131361 (2021).<\/p>\n

CAS<\/a>\u00a0
\n PubMed<\/a>\u00a0
\n
\n Google Scholar<\/a>\u00a0\n <\/p>\n","protected":false},"excerpt":{"rendered":"Chen, E. et al. Rates and classification of variants of uncertain significance in hereditary disease genetic testing. JAMA…\n","protected":false},"author":2,"featured_media":26408,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[50],"tags":[2342,13114,258,23090,8869,23091,13113,257,200,3870,5714,79],"class_list":["post-26407","post","type-post","status-publish","format-standard","has-post-thumbnail","category-genetics","tag-agriculture","tag-animal-genetics-and-genomics","tag-biomedicine","tag-cancer-genetics","tag-cancer-research","tag-functional-genomics","tag-gene-function","tag-general","tag-genetics","tag-human-genetics","tag-medical-genetics","tag-science"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/26407","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=26407"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/26407\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/26408"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=26407"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=26407"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=26407"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}