The power of multiplexed functional analysis of genetic variants
Open accessAbstract
New technologies have recently enabled saturation mutagenesis and functional analysis of nearly all possible variants of regulatory elements or proteins of interest in single experiments. Here we discuss the past, present, and future of such multiplexed (functional) assays for variant effects (MAVEs). MAVEs provide detailed insight into sequence-function relationships, and they may prove critical for the prospective clinical interpretation of genetic variants.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A clear strength of MPRAs is their ability to simultaneously test large numbers of sequences for regulatory activity via a relatively straightforward, widely accessible toolkit.
“A clear strength of MPRAs is their ability to simultaneously test large numbers of sequences for regulatory activity via a relatively straightforward, widely accessible toolkit (i.e. oligonucleotide synthesis, molecular biology, cell culture, and sequencing)175.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [175]
The Abstract says massively parallel reporter assays map regulatory sequence–function relationships and can assess hundreds to thousands of variants in one experiment. The Construction of a variant library and Sequencing to count variant frequency sections describe oligonucleotide libraries and sequencing, but the paper does not establish that the toolkit is relatively straightforward or widely accessible; it describes library construction as challenging. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works
Genome engineering using the CRISPR-Cas9 system
Ran, F. A., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A., & Zhang, F. (2013) · Nature Protocols · doi:10.1038/nprot.2013.143 · Cited by 11,133 · see citing works
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587 · see citing works
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210 · see citing works
Shrestha, S., & Offer, S. M. (2016) · Medical Epigenetics · doi:10.1159/000444713 · Cited by 8,949 · see citing works
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062 · see citing works
In Vivo Gene Delivery and Stable Transduction of Nondividing Cells by a Lentiviral Vector
Naldini, L., Blömer, U., Gallay, P., Ory, D., Mulligan, R., Gage, F. H., Verma, I. M., & Trono, D. (1996) · Science · doi:10.1126/science.272.5259.263 · Cited by 4,903 · see citing works
Next-generation DNA sequencing
Shendure, J., & Ji, H. (2008) · Nature Biotechnology · doi:10.1038/nbt1486 · Cited by 4,509 · see citing works
Self-citationSmith, G. P. (1985) · Science · doi:10.1126/science.4001944 · Cited by 4,143 · see citing works
ClinVar: public archive of interpretations of clinically relevant variants
Landrum, M. J., Lee, J. M., Benson, M., Brown, G., Chao, C., Chitipiralla, S., Gu, B., Hart, J., Hoffman, D., Hoover, J., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1222 · Cited by 2,758 · see citing works
The NHGRI GWAS Catalog, a curated resource of SNP-trait associations
Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., Klemm, A., Flicek, P., Manolio, T., Hindorff, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1229 · Cited by 2,707 · see citing works
Rapid generation of functional human IgG antibodies derived from Fab-on-phage display libraries
Jostock, T., Vanhove, M., Brepoels, E., van Gool, R., Daukandt, M., Wehnert, A., van Hegelsom, R., Dransfield, D., Sexton, D., Devlin, M., et al. (2004) · Journal of Immunological Methods · doi:10.1016/j.jim.2004.03.014 · Cited by 2,562 · see citing works
ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing
Green, R. C., Berg, J. S., Grody, W. W., Kalia, S. S., Korf, B. R., Martin, C. L., McGuire, A. L., Nussbaum, R. L., O’Daniel, J. M., Ormond, K. E., et al. (2013) · Genetics in Medicine · doi:10.1038/gim.2013.73 · Cited by 2,544 · see citing works
RNA-programmed genome editing in human cells
Jinek, M., East, A., Cheng, A., Lin, S., Ma, E., & Doudna, J. (2013) · eLife · doi:10.7554/elife.00471 · Cited by 2,098 · see citing works
Yeast surface display for screening combinatorial polypeptide libraries
Boder, E. T., & Wittrup, K. D. (1997) · Nature Biotechnology · doi:10.1038/nbt0697-553 · Cited by 1,774 · see citing works
High-Resolution Epitope Mapping of hGH-Receptor Interactions by Alanine-Scanning Mutagenesis
Cunningham, B. C., & Wells, J. A. (1989) · Science · doi:10.1126/science.2471267 · Cited by 1,361 · see citing works
Deep mutational scanning: a new style of protein science
Fowler, D. M., & Fields, S. (2014) · Nature Methods · doi:10.1038/nmeth.3027 · Cited by 1,287 · see citing works
The human splicing code reveals new insights into the genetic determinants of disease
Xiong, H. Y., Alipanahi, B., Lee, L. J., Bretschneider, H., Merico, D., Yuen, R. K. C., Hua, Y., Gueroussov, S., Najafabadi, H. S., Hughes, T., et al. (2014) · Science · doi:10.1126/science.1254806 · Cited by 1,225 · see citing works
BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis
Canver, M. C., Smith, E. C., Sher, F., Pinello, L., Sanjana, N. E., Shalem, O., Chen, D. D., Schupp, P. G., Vinjamur, D. S., Garcia, S. P., et al. (2015) · Nature · doi:10.1038/nature15521 · Cited by 886 · see citing works
Melnikov, A., Murugan, A., Zhang, X., Tesileanu, T., Wang, L., Rogov, P., Feizi, S., Gnirke, A., Callan, C. G., Kinney, J. B., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2137 · Cited by 711 · see citing works
Local fitness landscape of the green fluorescent protein
Sarkisyan, K. S., Bolotin, D. A., Meer, M. V., Usmanova, D. R., Mishin, A. S., Sharonov, G. V., Ivankov, D. N., Bozhanova, N. G., Baranov, M. S., Soylemez, O., et al. (2016) · Nature · doi:10.1038/nature17995 · Cited by 591 · see citing works
Massively parallel functional dissection of mammalian enhancers in vivo
Patwardhan, R. P., Hiatt, J. B., Witten, D. M., Kim, M. J., Smith, R. P., May, D., Lee, C., Andrie, J. M., Lee, S.-I., Cooper, G. M., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2136 · Cited by 536 · see citing works
Self-citationHigh-resolution mapping of protein sequence-function relationships
Fowler, D. M., Araya, C. L., Fleishman, S. J., Kellogg, E. H., Stephany, J. J., Baker, D., & Fields, S. (2010) · Nature Methods · doi:10.1038/nmeth.1492 · Cited by 516 · see citing works
Tewhey, R., Kotliar, D., Park, D. S., Liu, B., Winnicki, S., Reilly, S. K., Andersen, K. G., Mikkelsen, T. S., Lander, E. S., Schaffner, S. F., et al. (2016) · Cell · doi:10.1016/j.cell.2016.04.027 · Cited by 480 · see citing works
The spatial architecture of protein function and adaptation
McLaughlin, R. N., Poelwijk, F. J., Raman, A., Gosal, W. S., & Ranganathan, R. (2012) · Nature · doi:10.1038/nature11500 · Cited by 462 · see citing works
Sharon, E., Kalma, Y., Sharp, A., Raveh-Sadka, T., Levo, M., Zeevi, D., Keren, L., Yakhini, Z., Weinberger, A., & Segal, E. (2012) · Nature Biotechnology · doi:10.1038/nbt.2205 · Cited by 457 · see citing works
Fine Structure Genetic Analysis of a β-Globin Promoter
Myers, R., Tilly, K., & Maniatis, T. (1986) · Science · doi:10.1126/science.3457470 · Cited by 437 · see citing works
High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis
Patwardhan, R. P., Lee, C., Litvin, O., Young, D. L., Pe'er, D., & Shendure, J. (2009) · Nature Biotechnology · doi:10.1038/nbt.1589 · Cited by 377 · see citing works
Self-citationWhitehead, T. A., Chevalier, A. A., Song, Y., Dreyfus, C., Fleishman, S. J., de Mattos, C., Myers, C., Kamisetty, H., Blair, P. J., Wilson, I. A., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2214 · Cited by 364 · see citing works
Saturation editing of genomic regions by multiplex homology-directed repair
Findlay, G. M., Boyle, E. A., Hause, R. J., Klein, J. C., & Shendure, J. (2014) · Nature · doi:10.1038/nature13695 · Cited by 362 · see citing works
Self-citationExperimental illumination of a fitness landscape
Hietpas, R. T., Jensen, J. D., & Bolon, D. N. A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016024108 · Cited by 336 · see citing works
Kinney, J. B., Murugan, A., Callan, C. G., & Cox, E. C. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1004290107 · Cited by 334 · see citing works
Systematic Functional Dissection of Common Genetic Variation Affecting Red Blood Cell Traits
Ulirsch, J. C., Nandakumar, S. K., Wang, L., Giani, F. C., Zhang, X., Rogov, P., Melnikov, A., McDonel, P., Do, R., Mikkelsen, T. S., et al. (2016) · Cell · doi:10.1016/j.cell.2016.04.048 · Cited by 328 · see citing works
THE MECHANISM OF CONSERVATIVE SITE-SPECIFIC RECOMBINATION
Craig, N. L. (1988) · Annual Review of Genetics · doi:10.1146/annurev.ge.22.120188.000453 · Cited by 314 · see citing works
Massively Parallel Functional Analysis of BRCA1 RING Domain Variants
Starita, L. M., Young, D. L., Islam, M. M., Kitzman, J. O., Gullingsrud, J., Hause, R. J., Fowler, D. M., Parvin, J. D., Shendure, J., & Fields, S. (2015) · Genetics · doi:10.1534/genetics.115.175802 · Cited by 300 · see citing works
Self-citationEvolvability as a Function of Purifying Selection in TEM-1 β-Lactamase
Stiffler, M. A., Hekstra, D. R., & Ranganathan, R. (2015) · Cell · doi:10.1016/j.cell.2015.01.035 · Cited by 284 · see citing works
Decoding enhancers using massively parallel reporter assays
Inoue, F., & Ahituv, N. (2015) · Genomics · doi:10.1016/j.ygeno.2015.06.005 · Cited by 272 · see citing works
Learning the Sequence Determinants of Alternative Splicing from Millions of Random Sequences
Rosenberg, A. B., Patwardhan, R. P., Shendure, J., & Seelig, G. (2015) · Cell · doi:10.1016/j.cell.2015.09.054 · Cited by 254 · see citing works
Self-citationDeciphering the rules by which 5′-UTR sequences affect protein expression in yeast
Dvir, S., Velten, L., Sharon, E., Zeevi, D., Carey, L. B., Weinberger, A., & Segal, E. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222534110 · Cited by 246 · see citing works
Complex effects of nucleotide variants in a mammalian cis -regulatory element
Kwasnieski, J. C., Mogno, I., Myers, C. A., Corbo, J. C., & Cohen, B. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1210678109 · Cited by 233 · see citing works
Analyses of the Effects of All Ubiquitin Point Mutants on Yeast Growth Rate
Roscoe, B. P., Thayer, K. M., Zeldovich, K. B., Fushman, D., & Bolon, D. N. A. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.01.032 · Cited by 229 · see citing works
Adeno-associated virus vector integration.
Deyle, D. R., & Russell, D. W. (2009) · PubMed · Cited by 206 · see citing works
Quantitative evaluation of all hexamers as exonic splicing elementsPreprint
Ke, S., Shang, S., Kalachikov, S. M., Morozova, I., Yu, L., Russo, J. J., Ju, J., & Chasin, L. A. (2011) · Genome Research · doi:10.1101/gr.119628.110 · Cited by 204 · see citing works
The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin
Thyagarajan, B., & Bloom, J. D. (2014) · eLife · doi:10.7554/elife.03300 · Cited by 199 · see citing works
White, M. A., Myers, C. A., Corbo, J. C., & Cohen, B. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1307449110 · Cited by 195 · see citing works
An Experimentally Determined Evolutionary Model Dramatically Improves Phylogenetic Fit
Bloom, J. D. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu173 · Cited by 194 · see citing works
Strategies and Applications of in Vitro Mutagenesis
Botstein, D., & Shortle, D. (1985) · Science · doi:10.1126/science.2994214 · Cited by 194 · see citing works
Pervasive degeneracy and epistasis in a protein-protein interface
Podgornaia, A., & Laub, M. T. (2015) · Science · doi:10.1126/science.1257360 · Cited by 186 · see citing works
Activity-enhancing mutations in an E3 ubiquitin ligase identified by high-throughput mutagenesis
Starita, L. M., Pruneda, J. N., Lo, R. S., Fowler, D. M., Kim, H. J., Hiatt, J. B., Shendure, J., Brzovic, P. S., Fields, S., & Klevit, R. E. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1303309110 · Cited by 183 · see citing works
Self-citationLarge-scale filament formation inhibits the activity of CTP synthetase
Barry, R. M., Bitbol, A., Lorestani, A., Charles, E. J., Habrian, C. H., Hansen, J. M., Li, H., Baldwin, E. P., Wingreen, N. S., Kollman, J. M., et al. (2014) · eLife · doi:10.7554/elife.03638 · Cited by 180 · see citing works
Site-specific recombination: developments and applications
Sauer, B. (1994) · Current Opinion in Biotechnology · doi:10.1016/0958-1669(94)90068-x · Cited by 179 · see citing works
Comprehensive mutational scanning of a kinase in vivo reveals substrate-dependent fitness landscapes
Melnikov, A., Rogov, P., Wang, L., Gnirke, A., & Mikkelsen, T. S. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku511 · Cited by 177 · see citing works
Majithia, A. R., Flannick, J. A., Shahinian, P., Guo, M. H., Bray, M., Fontanillas, P., Gabriel, S., NHGRI JHS/FHS Allelic Spectrum Project, Rosen, E. D., Altshuler, D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1410428111 · Cited by 171 · see citing works
A Statistical Analysis of Random Mutagenesis Methods Used for Directed Protein Evolution
Wong, T. S., Roccatano, D., Zacharias, M., & Schwaneberg, U. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.10.082 · Cited by 157 · see citing works
Massively parallel single-amino-acid mutagenesis
Kitzman, J. O., Starita, L. M., Lo, R. S., Fields, S., & Shendure, J. (2015) · Nature Methods · doi:10.1038/nmeth.3223 · Cited by 154 · see citing works
Self-citationPál, G., Kouadio, J.-L. K., Artis, D. R., Kossiakoff, A. A., & Sidhu, S. S. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m603826200 · Cited by 154 · see citing works
Parallel, tag-directed assembly of locally derived short sequence reads
Hiatt, J. B., Patwardhan, R. P., Turner, E. H., Lee, C., & Shendure, J. (2010) · Nature Methods · doi:10.1038/nmeth.1416 · Cited by 149 · see citing works
Self-citationMaxwell, K. N., Hart, S. N., Vijai, J., Schrader, K. A., Slavin, T. P., Thomas, T., Wubbenhorst, B. S., Ravichandran, V., Moore, R. M., Hu, C., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.02.024 · Cited by 129 · see citing works
Mutational Robustness of Ribosomal Protein Genes
Lind, P. A., Berg, O. G., & Andersson, D. I. (2010) · Science · doi:10.1126/science.1194617 · Cited by 127 · see citing works
Software for the analysis and visualization of deep mutational scanning data
Bloom, J. D. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0590-4 · Cited by 122 · see citing works
PFunkel: Efficient, Expansive, User-Defined Mutagenesis
Firnberg, E., & Ostermeier, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0052031 · Cited by 121 · see citing works
Enrich: software for analysis of protein function by enrichment and depletion of variants
Fowler, D. M., Araya, C. L., Gerard, W., & Fields, S. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr577 · Cited by 121 · see citing works
Production of complex nucleic acid libraries using highly parallel in situ oligonucleotide synthesis
Cleary, M. A., Kilian, K. A., Wang, Y., Bradshaw, J., Cavet, G., Ge, W., Kulkarni, A., Paddison, P. J., Chang, K., Sheth, N. U., et al. (2004) · Nature Methods · doi:10.1038/nmeth724 · Cited by 108 · see citing works
Vockley, C. M., Guo, C., Majoros, W. H., Nodzenski, M., Scholtens, D. M., Hayes, M. G., Lowe, W. L., & Reddy, T. E. (2015) · Genome Research · doi:10.1101/gr.190090.115 · Cited by 99 · see citing works
Deng, Z., Huang, W.-Z., Bakkalbasi, E., Brown, N., Adamski, C., Rice, K., Muzny, D., Gibbs, R., & Palzkill, T. (2012) · Journal of Molecular Biology · doi:10.1016/j.jmb.2012.09.014 · Cited by 92 · see citing works
Site-Specific Amino Acid Preferences Are Mostly Conserved in Two Closely Related Protein Homologs
Doud, M. B., Ashenberg, O., & Bloom, J. D. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv167 · Cited by 89 · see citing works
Computational Design of a Protein-Based Enzyme Inhibitor
Procko, E., Hedman, R., Hamilton, K., Seetharaman, J., Fleishman, S. J., Su, M., Aramini, J. M., Kornhaber, G. J., Hunt, J. F., Tong, L., et al. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.06.035 · Cited by 88 · see citing works
Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing
Adkar, B. V., Tripathi, A., Sahoo, A., Pahuja, K. B., Goswami, D., Chakrabarti, P., Swarnkar, M. K., Gokhale, R. S., & Varadarajan, R. (2012) · Structure · doi:10.1016/j.str.2011.11.021 · Cited by 87 · see citing works
Jain, P. C., & Varadarajan, R. (2013) · Analytical Biochemistry · doi:10.1016/j.ab.2013.12.002 · Cited by 87 · see citing works
In Vitro Selection for Catalytic Activity with Ribosome Display
Amstutz, P., Pelletier, J. N., Guggisberg, A., Jermutus, L., Cesaro-Tadic, S., Zahnd, C., & Plückthun, A. (2002) · Journal of the American Chemical Society · doi:10.1021/ja025870q · Cited by 82 · see citing works
Systematic Dissection of the Sequence Determinants of Gene 3’ End Mediated Expression Control
Shalem, O., Sharon, E., Lubliner, S., Regev, I., Lotan-Pompan, M., Yakhini, Z., & Segal, E. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005147 · Cited by 69 · see citing works
Forsyth, C. M., Juan, V., Akamatsu, Y., DuBridge, R. B., Doan, M., Ivanov, A. V., Ma, Z., Polakoff, D., Razo, J., Wilson, K., et al. (2013) · mAbs · doi:10.4161/mabs.24979 · Cited by 68 · see citing works
Blarcom, T. J. V., Rossi, A., Foletti, D. L., Sundar, P. D., Pitts, S. J., Bee, C., Witt, J. M., Melton, Z., Hasa-Moreno, A., Shaughnessy, L., et al. (2014) · Journal of Molecular Biology · doi:10.1016/j.jmb.2014.09.020 · Cited by 67 · see citing works
White, M. A. (2015) · Genomics · doi:10.1016/j.ygeno.2015.06.003 · Cited by 66 · see citing works
High-throughput Analysis of in vivo Protein Stability
Kim, I., Miller, C. R., Young, D. L., & Fields, S. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o113.031708 · Cited by 65 · see citing works
Doolan, K., & Colby, D. W. (2014) · Journal of Molecular Biology · doi:10.1016/j.jmb.2014.10.024 · Cited by 51 · see citing works
A Statistical Guide to the Design of Deep Mutational Scanning Experiments
Matuszewski, S., Hildebrandt, M. E., Ghenu, A., Jensen, J. D., & Bank, C. (2016) · Genetics · doi:10.1534/genetics.116.190462 · Cited by 49 · see citing works
Birnbaum, R. Y., Patwardhan, R., Kim, M. J., Findlay, G. M., Martin, B., Zhao, J.-J., Bell, R. J. A., Smith, R. P., Ku, A., Shendure, J., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004592 · Cited by 42 · see citing works
Self-citationHolmqvist, E., Reimegård, J., & Wagner, E. G. H. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt267 · Cited by 32 · see citing works
Melamed, D., Young, D. L., Miller, C. R., & Fields, S. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1004918 · Cited by 30 · see citing works
Comprehensive Analysis of the SUL1 Promoter of Saccharomyces cerevisiae
Rich, M. S., Payen, C., Rubin, A. F., Ong, G. T., Sánchez, M., Yachie, N., Dunham, M. J., & Fields, S. (2016) · Genetics · doi:10.1534/genetics.116.188037 · Cited by 28 · see citing works
Gajula, K. S., Huwe, P. J., Mo, C. Y., Crawford, D., Stivers, J. T., Radhakrishnan, R., & Kohli, R. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku689 · Cited by 19 · see citing works
Shin, H., Cho, Y., Choe, D., Jeong, Y., Cho, S., Kim, S. C., & Cho, B. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097817 · Cited by 12 · see citing works
MPAthic: Quantitative Modeling of Sequence-Function Relationships for massively parallel assaysPreprint
Ireland, W. T., & Kinney, J. B. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/054676 · Cited by 8 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [51]Ireland WT & Kinney JB Sort-Seq Tools: sequence-function relationship modeling for massively parallel assays Preprint at http://biorxiv.org/content/early/2016/05/21/054676 (2016).
Cited by
Sorted by citations
Accurate classification of BRCA1 variants with saturation genome editing
Findlay, G. M., Daza, R. M., Martin, B., Zhang, M. D., Leith, A. P., Gasperini, M., Janizek, J. D., Huang, X., Starita, L. M., & Shendure, J. (2018) · Nature · doi:10.1038/s41586-018-0461-z · Cited by 843 · see citing works
Self-citationMutation effects predicted from sequence co-variation
Hopf, T. A., Ingraham, J. B., Poelwijk, F. J., Schärfe, C. P. I., Springer, M., Sander, C., & Marks, D. S. (2017) · Nature Biotechnology · doi:10.1038/nbt.3769 · Cited by 775 · see citing works
Deep generative models of genetic variation capture the effects of mutations
Riesselman, A. J., Ingraham, J. B., & Marks, D. S. (2018) · Nature Methods · doi:10.1038/s41592-018-0138-4 · Cited by 601 · see citing works
Multiplex assessment of protein variant abundance by massively parallel sequencing
Matreyek, K. A., Starita, L. M., Stephany, J. J., Martin, B., Chiasson, M. A., Gray, V. E., Kircher, M., Khechaduri, A., Dines, J. N., Hause, R. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0122-z · Cited by 436 · see citing works
Self-citationTowards a comprehensive catalogue of validated and target-linked human enhancers
Gasperini, M., Tome, J. M., & Shendure, J. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-019-0209-0 · Cited by 396 · see citing works
Self-citationVariant interpretation: functional assays to the rescue
Starita, L. M., Ahituv, N., Dunham, M. J., Kitzman, J. O., Roth, F. P., Seelig, G., Shendure, J., & Fowler, D. M. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.07.014 · Cited by 381 · see citing works
Self-citationMultiplexed Engineering and Analysis of Combinatorial Enhancer Activity in Single Cells
Xie, S., Duan, J., Li, B., Zhou, P., & Hon, G. C. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.03.007 · Cited by 334 · see citing works
Esposito, D., Weile, J., Shendure, J., Starita, L. M., Papenfuss, A. T., Roth, F. P., Fowler, D. M., & Rubin, A. F. (2019) · Genome biology · doi:10.1186/s13059-019-1845-6 · Cited by 248 · see citing works
Self-citationPharmacogenomics of CYP2C9: Functional and Clinical Considerations
Daly, A. K., Rettie, A. E., Fowler, D. M., & Miners, J. O. (2017) · Journal of Personalized Medicine · doi:10.3390/jpm8010001 · Cited by 228 · see citing works
Durrant, M. G., Fanton, A., Tycko, J., Hinks, M. M., Chandrasekaran, S. S., Perry, N. T., Schaepe, J. M., Du, P. P., Lotfy, P., Bassik, M. C., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01494-w · Cited by 212 · see citing works
Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data
Gray, V. E., Hause, R. J., Luebeck, J., Shendure, J., & Fowler, D. M. (2017) · Cell Systems · doi:10.1016/j.cels.2017.11.003 · Cited by 205 · see citing works
Self-citationGEMME: A Simple and Fast Global Epistatic Model Predicting Mutational Effects
Laine, É., Karami, Y., & Carbone, A. (2019) · Molecular Biology and Evolution · doi:10.1093/molbev/msz179 · Cited by 197 · see citing works
Inferring protein 3D structure from deep mutation scans
Rollins, N. J., Brock, K. P., Poelwijk, F. J., Stiffler, M. A., Gauthier, N. P., Sander, C., & Marks, D. S. (2019) · Nature Genetics · doi:10.1038/s41588-019-0432-9 · Cited by 163 · see citing works
A platform for functional assessment of large variant libraries in mammalian cells
Matreyek, K. A., Stephany, J. J., & Fowler, D. M. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx183 · Cited by 140 · see citing works
An improved platform for functional assessment of large protein libraries in mammalian cells
Matreyek, K. A., Stephany, J. J., Chiasson, M. A., Hasle, N., & Fowler, D. M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz910 · Cited by 122 · see citing works
Multiplexed gene synthesis in emulsions for exploring protein functional landscapes
Plesa, C., Sidore, A. M., Lubock, N. B., Zhang, D., & Kosuri, S. (2018) · Science · doi:10.1126/science.aao5167 · Cited by 124 · see citing works
An Atlas of Variant Effects to understand the genome at nucleotide resolution
Fowler, D. M., Adams, D. J., Gloyn, A. L., Hahn, W. C., Marks, D. S., Muffley, L. A., Neal, J. T., Roth, F. P., Rubin, A. F., Starita, L. M., et al. (2023) · Genome biology · doi:10.1186/s13059-023-02986-x · Cited by 109 · see citing works
Self-citationFayer, S., Horton, C., Dines, J. N., Rubin, A. F., Richardson, M. E., McGoldrick, K., Hernandez, F., Pesaran, T. F., Karam, R., Shirts, B. H., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.11.001 · Cited by 112 · see citing works
Self-citationWill variants of uncertain significance still exist in 2030?
Fowler, D. M., & Rehm, H. L. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.11.005 · Cited by 106 · see citing works
Rohlhill, J., Sandoval, N. R., & Papoutsakis, E. T. (2017) · ACS Synthetic Biology · doi:10.1021/acssynbio.7b00114 · Cited by 96 · see citing works
Chiasson, M. A., Rollins, N. J., Stephany, J. J., Sitko, K. A., Matreyek, K. A., Verby, M., Sun, S., Roth, F. P., DeSloover, D., Marks, D. S., et al. (2020) · eLife · doi:10.7554/elife.58026 · Cited by 91 · see citing works
Manrubia, S., Cuesta, J. A., Aguirre, J., Ahnert, S. E., Altenberg, L., Cano, A. V., Catalán, P., Diaz-Uriarte, R., Elena, S. F., García-Martín, J. A., et al. (2021) · Physics of Life Reviews · doi:10.1016/j.plrev.2021.03.004 · Cited by 88 · see citing works
Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations
Funk, J. S., Klimovich, M., Drangenstein, D., Pielhoop, O., Hunold, P., Borowek, A., Noeparast, M., Pavlakis, E., Neumann, M. M., Balourdas, D.-I., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02039-4 · Cited by 92 · see citing works
On behalf of the Brotman Baty Institute Mutational Scanning Working Group, Gelman, H., Dines, J. N., Berg, J., Berger, A. H., Brnich, S., Hisama, F. M., James, R. G., Rubin, A. F., Shendure, J., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0698-7 · Cited by 81 · see citing works
Self-citationScalable Functional Assays for the Interpretation of Human Genetic Variation
Tabet, D. R., Parikh, V. N., Mali, P., Roth, F. P., & Claussnitzer, M. (2022) · Annual Review of Genetics · doi:10.1146/annurev-genet-072920-032107 · Cited by 83 · see citing works
Ravenscroft, G., Clayton, J. S., Faiz, F., Sivadorai, P., Milnes, D., Cincotta, R., Moon, P., Kamien, B., Edwards, M. J., Delatycki, M. B., et al. (2020) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2020-106901 · Cited by 74 · see citing works
Combinatorial mutagenesis en masse optimizes the genome editing activities of SpCas9
Choi, G. C. G., Zhou, P., Yuen, C. T. L., Chan, B. K. C., Xu, F., Bao, S., Chu, H. Y., Thean, D., Tan, K., Wong, K. H., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0473-0 · Cited by 61 · see citing works
Leveraging massively parallel reporter assays for evolutionary questions
Romero, I. G., & Lea, A. J. (2023) · Genome biology · doi:10.1186/s13059-023-02856-6 · Cited by 62 · see citing works
Findlay, G. M. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab219 · Cited by 55 · see citing works
Synthetic regulatory reconstitution reveals principles of mammalian Hox cluster regulation
Pinglay, S., Bulajić, M., Rahe, D. P., Huang, E., Brosh, R., Mamrak, N., King, B. R., German, S. V., Cadley, J. A., Rieber, L., et al. (2022) · Science · doi:10.1126/science.abk2820 · Cited by 53 · see citing works
Mycobacterium abscessus pathogenesis identified by phenogenomic analyses
Boeck, L., Burbaud, S., Skwark, M. J., Pearson, W. H., Sangen, J., Wüest, A., Marshall, E. K. P., Weimann, A., Everall, I., Bryant, J. M., et al. (2022) · Nature Microbiology · doi:10.1038/s41564-022-01204-x · Cited by 51 · see citing works
Toward a More Precise Future for Oncology
Murciano-Goroff, Y. R., Taylor, B. S., Hyman, D. M., & Schram, A. M. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.03.014 · Cited by 48 · see citing works
High-resolution functional mapping of RAD51C by saturation genome editing
Olvera-León, R., Zhang, F., Offord, V., Zhao, Y., Tan, H. K., Gupta, P., Pal, T., Robles-Espinoza, C. D., Arriaga-González, F. G., Matsuyama, L. S. A. S., et al. (2024) · Cell · doi:10.1016/j.cell.2024.08.039 · Cited by 44 · see citing works
Aditham, A. K., Markin, C. J., Mokhtari, D. A., DelRosso, N. V., & Fordyce, P. M. (2020) · Cell Systems · doi:10.1016/j.cels.2020.11.012 · Cited by 45 · see citing works
Matreyek, K. A., Stephany, J. J., Ahler, E., & Fowler, D. M. (2021) · Genome Medicine · doi:10.1186/s13073-021-00984-x · Cited by 48 · see citing works
High-throughput evaluation of T7 promoter variants using biased randomization and DNA barcoding
Komura, R., Aoki, W., Motone, K., Satomura, A., & Ueda, M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0196905 · Cited by 45 · see citing works
The impact of hereditary cancer gene panels on clinical care and lessons learnedPreprint
Okur, V., & Chung, W. K. (2017) · Molecular Case Studies · doi:10.1101/mcs.a002154 · Cited by 45 · see citing works
Next Generation Sequencing Mitochondrial DNA Analysis in Autism Spectrum Disorder
Patowary, A., Nesbitt, R., Archer, M., Bernier, R., & Brkanac, Z. (2017) · Autism Research · doi:10.1002/aur.1792 · Cited by 44 · see citing works
Zhang, L., Sarangi, V., Moon, I., Yu, J., Liu, D., Devarajan, S., Reid, J. M., Kalari, K. R., Wang, L., & Weinshilboum, R. M. (2020) · Clinical and Translational Science · doi:10.1111/cts.12758 · Cited by 42 · see citing works
Characterizing variants of unknown significance in rhodopsin: A functional genomics approach
Wan, A., Place, E., Pierce, E. A., & Comander, J. (2019) · Human Mutation · doi:10.1002/humu.23762 · Cited by 41 · see citing works
Multiplexed assays of variant effect for clinical variant interpretation
McEwen, A. E., Tejura, M., Fayer, S., Starita, L. M., & Fowler, D. M. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00870-x · Cited by 41 · see citing works
Self-citationDropSynth 2.0: high-fidelity multiplexed gene synthesis in emulsions
Sidore, A. M., Plesa, C., Samson, J., Lubock, N. B., & Kosuri, S. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa600 · Cited by 38 · see citing works
HAP1, a new revolutionary cell model for gene editing using CRISPR-Cas9
Llargués‐Sistac, G., Bonjoch, L., & Castellvı́-Bel, S. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1111488 · Cited by 36 · see citing works
Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification
Ryu, J., Barkal, S., Yu, T., Jankowiak, M., Zhou, Y., Francoeur, M., Phan, Q. V., Li, Z., Tognon, M., Brown, L., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01726-6 · Cited by 33 · see citing works
Multimodal scanning of genetic variants with base and prime editing
Belli, O., Karava, K., Farouni, R., & Platt, R. J. (2024) · Nature Biotechnology · doi:10.1038/s41587-024-02439-1 · Cited by 33 · see citing works
Deep mutational scanning of proteins in mammalian cells
Maes, S., Deploey, N., Peelman, F., & Eyckerman, S. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100641 · Cited by 36 · see citing works
Integrating Functional Analysis in the Next-Generation Sequencing Diagnostic Pipeline of RASopathies
Leung, G. K. C., Luk, H., Tang, V. H. M., Gao, W., Mak, C. C. Y., Yu, M. H. C., Wong, W. L., Chu, Y. W. Y., Yang, W., Wong, W. H. S., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-20894-0 · Cited by 30 · see citing works
Decoding molecular mechanisms for loss-of-function variants in the human proteomePreprint
Cagiada, M., Jonsson, N., & Lindorff-Larsen, K. (2025) · bioRxiv · doi:10.1101/2024.05.21.595203 · Cited by 32 · see citing works
Differential strengths of molecular determinants guide environment specific mutational fates
Dandage, R., Pandey, R., Jayaraj, G. G., Rai, M., Berger, D., & Chakraborty, K. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007419 · Cited by 26 · see citing works
Measuring Pharmacogene Variant Function at Scale Using Multiplexed Assays
Geck, R. C., Boyle, G. E., Amorosi, C. J., Fowler, D. M., & Dunham, M. J. (2021) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-032221-085807 · Cited by 26 · see citing works
Rong, S., Neil, C. R., Welch, A., Duan, C., Maguire, S., Meremikwu, I. C., Meyerson, M., Evans, B. J., & Fairbrother, W. G. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2218308120 · Cited by 24 · see citing works
Classifying disease-associated variants using measures of protein activity and stability
Jepsen, M. M., Fowler, D. M., Hartmann‐Petersen, R., Stein, A., & Lindorff‐Larsen, K. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819132-3.00005-1 · Cited by 25 · see citing works
High-throughput screening of human genetic variants by pooled prime editing
Herger, M., Kajba, C. M., Buckley, M., Cunha, A., Strom, M., & Findlay, G. M. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100814 · Cited by 25 · see citing works
Overcoming the design, build, test bottleneck for synthesis of nonrepetitive protein-RNA cassettes
Katz, N., Tripto, E., Granik, N., Goldberg, S., Atar, O., Zohar Yakhini, B., Orenstein, Y., & Amit, R. (2021) · Nature Communications · doi:10.1038/s41467-021-21578-6 · Cited by 24 · see citing works
Estimating contribution of rare non‐coding variants to neuropsychiatric disorders
Takata, A. (2018) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12774 · Cited by 24 · see citing works
Deep generative models of genetic variation capture mutation effectsPreprint
Riesselman, A. J., Ingraham, J., & Marks, D. S. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/235655 · Cited by 23 · see citing works
Sahu, S., Sullivan, T. L., Mitrophanov, A. Y., Galloux, M., Nousome, D., Southon, E. A., Caylor, D., Mishra, A. P., Evans, C. N., Clapp, M. E., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010940 · Cited by 22 · see citing works
Levchenko, А., Nurgaliev, T., Kanapin, A. A., Samsonova, A. A., & Gainetdinov, R. R. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e03990 · Cited by 20 · see citing works
Parallel genetics of regulatory sequences using scalable genome editing in vivo
Froehlich, J. J., Uyar, B., Herzog, M., Theil, K., Glažar, P., Akalin, A., & Rajewsky, N. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108988 · Cited by 17 · see citing works
Parmar, J., Laing, N., Kennerson, M., & Ravenscroft, G. (2024) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2024-333436 · Cited by 17 · see citing works
Modern methods for laboratory diversification of biomolecules
Bratulić, S., & Badran, A. H. (2017) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2017.10.010 · Cited by 18 · see citing works
Accurate prediction of functional effect of single amino acid variants with deep learning
Derbel, H., Zhao, Z., & Liu, Q. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.11.017 · Cited by 17 · see citing works
van Karnebeek, C., O’Donnell‐Luria, A., Baynam, G. S., Baudot, A., Groza, T., Jans, J. J. M., Lassmann, T., Letinturier, M. C. V., Montgomery, S. B., Robinson, P. N., et al. (2024) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-024-03361-0 · Cited by 17 · see citing works
The Impact of Genetic Variants on PTEN Molecular Functions and Cellular PhenotypesPreprint
Hasle, N., Matreyek, K. A., & Fowler, D. M. (2019) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a036228 · Cited by 17 · see citing works
Alignment-based Protein Mutational Landscape Prediction: Doing More with Less
Abakarova, M., Marquet, C., Rera, M., Rost, B., & Laine, E. (2023) · Genome Biology and Evolution · doi:10.1093/gbe/evad201 · Cited by 14 · see citing works
Minimum information and guidelines for reporting a multiplexed assay of variant effect
Claussnitzer, M., Parikh, V. N., Wagner, A. H., Arbesfeld, J. A., Bult, C. J., Firth, H. V., Muffley, L. A., Ba, A. N. N., Riehle, K. P., Roth, F. P., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03223-9 · Cited by 17 · see citing works
Topological deep learning based deep mutational scanning
Chen, J.-H., Woldring, D. R., Huang, F.-Q., Huang, X., & Wei, G.-S. (2023) · Comput. Biol. Medicine · doi:10.1016/j.compbiomed.2023.107258 · Cited by 19 · see citing works
Wu, H., Lin, J., Tang, X., Marenne, G., Zou, W., Schutz, S., Masson, E., Génin, E., Fichou, Y., Gac, G. L., et al. (2024) · Human Genomics · doi:10.1186/s40246-024-00586-9 · Cited by 13 · see citing works
A combination of transcription factors mediates inducible interchromosomal contacts
Kim, S., Dunham, M. J., & Shendure, J. (2019) · eLife · doi:10.7554/elife.42499 · Cited by 15 · see citing works
Self-citationToward Robust Functional Neuroimaging Genetics of Cognition
Uddén, J., Hultén, A., Bendtz, K., Mineroff, Z., Kucera, K. S., Vino, A., Fedorenko, E. G., Peter Hagoort, A., & Fisher, S. E. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.0888-19.2019 · Cited by 16 · see citing works
Gilbert, M. A., Keefer-Jacques, E., Jadhav, T., Antfolk, D., Ming, Q., Valente, N., Shaw, G. T.-W., Sottolano, C. J., Matwijec, G., Luca, V. C., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.06.011 · Cited by 15 · see citing works
Predicting mutant outcome by combining deep mutational scanning and machine learning
Sarfati, H., Naftaly, S., Papo, N., & Keasar, C. (2021) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.26184 · Cited by 16 · see citing works
GPT-4 Performance, Nondeterminism, and Drift in Genetic Literature Review
Aronson, S., Machini, K., Shin, J., Sriraman, P., Hamill, S., Henricks, E. R., Mailly, C. J., Nottage, A. J., Amr, S. S., Oates, M., et al. (2024) · NEJM AI · doi:10.1056/aics2400245 · Cited by 14 · see citing works
Understanding genetic variants in context
Sinnott-Armstrong, N., Fields, S., Roth, F. P., Starita, L. M., Trapnell, C., Villén, J., Fowler, D. M., & Queitsch, C. (2024) · eLife · doi:10.7554/elife.88231 · Cited by 14 · see citing works
Self-citationPharmacogenomic Testing in the Clinical Laboratory: Historical Progress and Future Opportunities
Moyer, A. M., & Black, J. L. (2025) · Annals of Laboratory Medicine · doi:10.3343/alm.2024.0652 · Cited by 13 · see citing works
Childhood rare lung disease in the 21st century: “‐omics” technology advances accelerating discovery
Vece, T. J., Wambach, J., & Hagood, J. S. (2020) · Pediatric Pulmonology · doi:10.1002/ppul.24809 · Cited by 13 · see citing works
Genomic Newborn Screening for Pediatric Cancer Predisposition Syndromes: A Holistic Approach
Linga, B. G., Mohammed, S. G. A. A., Farrell, T. J., Rifai, H. A., Al-Dewik, N. I. E., & Qoronfleh, M. W. (2024) · Cancers · doi:10.3390/cancers16112017 · Cited by 12 · see citing works
popDMS infers mutation effects from deep mutational scanning data
Hong, Z., Shimagaki, K. S., & Barton, J. P. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae499 · Cited by 12 · see citing works
Artificial intelligence in the lab: ask not what your computer can do for you
de Ridder, D. (2018) · Microbial Biotechnology · doi:10.1111/1751-7915.13317 · Cited by 10 · see citing works
Efficient epistasis inference via higher-order covariance matrix factorization
Shimagaki, K. S., & Barton, J. P. (2025) · Genetics · doi:10.1093/genetics/iyaf118 · Cited by 10 · see citing works
Limits to detecting epistasis in the fitness landscape of HIV
Biswas, A., Haldane, A., & Levy, R. M. (2022) · PLoS ONE · doi:10.1371/journal.pone.0262314 · Cited by 10 · see citing works
3D protein structure from genetic epistasis experimentsPreprint
Rollins, N. J., Brock, K. P., Poelwijk, F. J., Stiffler, M. A., Gauthier, N. P., Sander, C., & Marks, D. S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/320721 · Cited by 10 · see citing works
Pakpahan, I., Sihombing, M., Liu, H., Wang, M., Su, Z., & Fang, M. (2026) · GigaScience · doi:10.1093/gigascience/giag004 · Cited by 10 · see citing works
Quantitative determination of SLC2A1 variant functional effects in GLUT1 deficiency syndrome
Tayebi, N., León-Ricardo, B. X., McCall, K., Mehinovic, E., Engelstad, K., Huynh, V., Turner, T. N., Weisenberg, J., Thio, L. L., Hruz, P. W., et al. (2023) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51767 · Cited by 9 · see citing works
Shah, B. P., Abou‐Sleiman, P. M., Donald, J. M., Moeller, I. H., & Kleyn, P. (2023) · Expert Review of Endocrinology & Metabolism · doi:10.1080/17446651.2023.2179985 · Cited by 9 · see citing works
Classification of GBA1 variants and their impact on Parkinson’s disease: an in silico score analysis
Lanore, A., Tesson, C., Basset, A., Lejeune, F., Cogan, G., Mangone, G., Sambin, S., Bertille, N., Anheim, M., Arnulf, I., et al. (2025) · npj Parkinson s Disease · doi:10.1038/s41531-025-01060-6 · Cited by 9 · see citing works
Wang, Y., Masson, E., Wang, Q.-W., Génin, E., Gac, G. L., Fichou, Y., Cooper, D. N., Liao, Z., Férec, C., Zou, W., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.07.013 · Cited by 8 · see citing works
Pal, T., Christopher, J., Astiazarán-Symonds, E., Foulkes, W. D., James, P., Klugman, S. D., Kurian, A. W., Mak, J. S., Monteiro, A. N., Robson, M. E., et al. (2026) · Genetics in Medicine · doi:10.1016/j.gim.2025.101659 · Cited by 8 · see citing works
The evolving landscape of pharmacogenomics: Current achievements and future directions
Lauschke, V. M., & Ingelman‐Sundberg, M. (2026) · Pharmacological Reviews · doi:10.1016/j.pharmr.2026.100122 · Cited by 12 · see citing works
A call to action for deciphering genetic variants in human pluripotent stem cells for cell therapy
Benvenisty, N., Draper, J. S., Gokhale, P. J., Healy, L. E., Hewitt, Z., Hursh, D. A., Hodgson, A., Ludwig, T. E., Mah, N., McClelland, S. E., et al. (2025) · Cell stem cell · doi:10.1016/j.stem.2025.03.003 · Cited by 8 · see citing works
Accelerating structure‐function mapping using the ViVa webtool to mine natural variation
Hamm, M. O., Moss, B. L., Leydon, A. R., Gala, H., Lanctot, A., Ramos, R., Klaeser, H., Lemmex, A. C., Zahler, M. L., Nemhauser, J. L., et al. (2019) · Plant Direct · doi:10.1002/pld3.147 · Cited by 8 · see citing works
Label-free simultaneous sensor for multi-components detection based on G-Quadruplex DNA structure
Zeng, Y., Zhang, D., Qi, P., & Zheng, L. (2018) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2018.03.039 · Cited by 8 · see citing works
Fasano, C., Signorile, M. L., Marco, K. D., Forte, G., Disciglio, V., Sanese, P., Grossi, V., & Simone, C. (2024) · Cells · doi:10.3390/cells13161314 · Cited by 7 · see citing works
High-throughput assays to assess variant effects on disease
Ma, K., Gauthier, L. O., Cheung, F., Huang, S., & Lek, M. (2024) · Disease Models & Mechanisms · doi:10.1242/dmm.050573 · Cited by 7 · see citing works
Decoding molecular mechanisms for loss-of-function variants in the human proteomePreprint
Cagiada, M., Jonsson, N., & Lindorff‐Larsen, K. (2025) · eLife · doi:10.7554/elife.108160.1 · Cited by 7 · see citing works
Li, B., Jin, B., Capra, J. A., & Bush, W. S. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122220-112147 · Cited by 5 · see citing works
Out of the dark: the emerging roles of lncRNAs in pain
Habib, A. M., Cox, J. J., & Okorokov, A. L. (2024) · Trends in Genetics · doi:10.1016/j.tig.2024.04.009 · Cited by 6 · see citing works
Interface-guided phenotyping of coding variants in the transcription factor RUNX1
Öztürk, K., Panwala, R., Sheen, J., Ford, K. M., Jayne, N. D., Portell, A. J., Zhang, D., Hütter, S., Haferlach, T., Ideker, T. E., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114436 · Cited by 7 · see citing works
Concerted Genetic Function in Blood Traits
Kim-Hellmuth, S., & Lappalainen, T. (2016) · Cell · doi:10.1016/j.cell.2016.10.055 · Cited by 5 · see citing works
- Authors
- Gasperini, M., Starita, L., & Shendure, J.
- Affiliations
- University of Washington (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Shendure, Jay
- Venue
- Nature Protocols
- Published
- 2016-09-01
- Volume
- 11
- Issue
- 10
- Pages
- 1782-1787
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- PMC
- PMC6690347
- OpenAlex
- W2512645103
- Cited by
- 160
- References
- 84
- Citations by year
- 2026: 12 · 2025: 19 · 2024: 28 · 2023: 17 · 2022: 10 · 2021: 15 · 2020: 13 · 2019: 17 · 2018: 15 · 2017: 13 · 2016: 1
- FWCI
- 12.39
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Protocols (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Howard Hughes Medical Institute
- National Human Genome Research Institute (DP1HG007811, UM1HG009408)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- genetic variants, variant effect prediction, saturation mutagenesis, regulatory elements, protein variants, sequence-function relationships, functional genomics
- MeSH terms
- Animals, Genotype, Humans, Models, Molecular, Phenotype, Proteins, Genetic Variation, Mutagenesis, Genomics, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review