2024
Saturation mutagenesis-reinforced functional assays for disease-related genes
Ma K, Huang S, Ng K, Lake N, Joseph S, Xu J, Lek A, Ge L, Woodman K, Koczwara K, Cohen J, Ho V, O'Connor C, Brindley M, Campbell K, Lek M. Saturation mutagenesis-reinforced functional assays for disease-related genes. Cell 2024, 187: 6707-6724.e22. PMID: 39326416, PMCID: PMC11568926, DOI: 10.1016/j.cell.2024.08.047.Peer-Reviewed Original ResearchDisease-related genesDisease-causing genetic variantsGenome-wide resolutionMutation scanning methodsSingle-nucleotide variantsDeep mutational scanning methodFunctional assaysDisease genesComputational predictorsSaturation mutagenesisHuman geneticsGenetic variantsGenesVariantsSmurfAssayMutagenesisLARGE1GeneticsDisease severityHigh-throughput assays to assess variant effects on disease
Ma K, Gauthier L, Cheung F, Huang S, Lek M. High-throughput assays to assess variant effects on disease. Disease Models & Mechanisms 2024, 17: dmm050573. PMID: 38940340, PMCID: PMC11225591, DOI: 10.1242/dmm.050573.Peer-Reviewed Original ResearchConceptsDeep mutational scanningGenetic variantsRare disease diagnosticsRare genetic variantsDisease mechanismsHigh-throughput assaySequencing effortsInvestigation of variantsMutational scanningModel cell lineVariant effectsMolecular toolsCell linesCell survival rateFunctional assaysDrug resistanceDisease diagnosticsDisease-relevant assaysVariantsClinical case reportBiological mechanismsAssayCase reportClinical reportsSurvival rate
2016
Quantifying prion disease penetrance using large population control cohorts
Minikel EV, Vallabh SM, Lek M, Estrada K, Samocha KE, Sathirapongsasuti JF, McLean CY, Tung JY, Yu LP, Gambetti P, Blevins J, Zhang S, Cohen Y, Chen W, Yamada M, Hamaguchi T, Sanjo N, Mizusawa H, Nakamura Y, Kitamoto T, Collins SJ, Boyd A, Will RG, Knight R, Ponto C, Zerr I, Kraus TF, Eigenbrod S, Giese A, Calero M, de Pedro-Cuesta J, Haïk S, Laplanche JL, Bouaziz-Amar E, Brandel JP, Capellari S, Parchi P, Poleggi A, Ladogana A, O’Donnell-Luria A, Karczewski KJ, Marshall JL, Boehnke M, Laakso M, Mohlke KL, Kähler A, Chambert K, McCarroll S, Sullivan PF, Hultman CM, Purcell SM, Sklar P, van der Lee SJ, Rozemuller A, Jansen C, Hofman A, Kraaij R, van Rooij JG, Ikram MA, Uitterlinden AG, van Duijn CM, Consortium E, Daly MJ, MacArthur DG. Quantifying prion disease penetrance using large population control cohorts. Science Translational Medicine 2016, 8: 322ra9. PMID: 26791950, PMCID: PMC4774245, DOI: 10.1126/scitranslmed.aad5169.Peer-Reviewed Original ResearchConceptsPrion protein genePopulation control cohortPrion disease casesHealthy older individualsPrion protein expressionControl cohortLifetime riskTherapeutic suppressionDisease casesTruncating variantsDisease-causing genotypesOlder individualsBenign variantsDisease prevalenceProtein expressionDisease penetranceDiseaseMissense variantsPrion diseasesControl exomesDisease susceptibilityImpact of variantsGenetic variantsRiskPenetrance
2015
Effect of predicted protein-truncating genetic variants on the human transcriptome
Rivas MA, Pirinen M, Conrad DF, Lek M, Tsang EK, Karczewski KJ, Maller JB, Kukurba KR, DeLuca DS, Fromer M, Ferreira PG, Smith KS, Zhang R, Zhao F, Banks E, Poplin R, Ruderfer DM, Purcell SM, Tukiainen T, Minikel EV, Stenson PD, Cooper DN, Huang KH, Sullivan TJ, Nedzel J, Consortium T, Consortium T, Bustamante CD, Li JB, Daly MJ, Guigo R, Donnelly P, Ardlie K, Sammeth M, Dermitzakis ET, McCarthy MI, Montgomery SB, Lappalainen T, MacArthur DG, Segre A, Young T, Gelfand E, Trowbridge C, Ward L, Kheradpour P, Iriarte B, Meng Y, Palmer C, Esko T, Winckler W, Hirschhorn J, Kellis M, Getz G, Shablin A, Li, Zhou Y, Nobel A, Rusyn I, Wright F, Battle A, Mostafavi S, Mele M, Reverter F, Goldmann J, Koller D, Gamazon E, Im H, Konkashbaev A, Nicolae D, Cox N, Flutre T, Wen X, Stephens M, Pritchard J, Tu Z, Zhang B, Huang T, Long Q, Lin L, Yang J, Zhu J, Liu J, Brown A, Mestichelli B, Tidwell D, Lo E, Salvatore M, Shad S, Thomas J, Lonsdale J, Choi R, Karasik E, Ramsey K, Moser M, Foster B, Gillard B, Syron J, Fleming J, Magazine H, Hasz R, Walters G, Bridge J, Miklos M, Sullivan S, Barker L, Traino H, Mosavel M, Siminoff L, Valley D, Rohrer D, Jewel S, Branton P, Sobin L, Barcus M, Qi L, Hariharan P, Wu S, Tabor D, Shive C, Smith A, Buia S, Undale A, Robinson K, Roche N, Valentino K, Britton A, Burges R, Bradbury D, Hambright K, Seleski J, Korzeniewski G, Erickson K, Marcus Y, Tejada J, Taherian M, Lu C, Robles B, Basile M, Mash D, Volpi S, Struewing J, Temple G, Boyer J, Colantuoni D, Little R, Koester S, Carithers L, Moore H, Guan P, Compton C, Sawyer S, Demchok J, Vaught J, Rabiner C, Lockhart N, Friedlander M, Hoen P, Monlong J, Gonzàlez-Porta M, Kurbatova N, Griebel T, Barann M, Wieland T, Greger L, van Iterson M, Almlof J, Ribeca P, Pulyakhina I, Esser D, Giger T, Tikhonov A, Sultan M, Bertier G, Lizano E, Buermans H, Padioleau I, Schwarzmayr T, Karlberg O, Ongen H, Kilpinen H, Beltran S, Gut M, Kahlem K, Amstislavskiy V, Stegle O, Flicek P, Strom T, Lehrach H, Schreiber S, Sudbrak R, Carracedo A, Antonarakis S, Hasler R, Syvanen A, van Ommen G, Brazma A, Meitinger T, Rosenstiel P, Gut I, Estivill X. Effect of predicted protein-truncating genetic variants on the human transcriptome. Science 2015, 348: 666-669. PMID: 25954003, PMCID: PMC4537935, DOI: 10.1126/science.1261877.Peer-Reviewed Original ResearchConceptsGenotype-Tissue ExpressionGenetic variantsProtein-truncating variantsEffects of variantsDosage compensationClass of variantsTranscript decayGene functionTranscriptome dataHuman transcriptomeGenetic variationGEUVADIS projectGene inactivationSplice junctionsGenome interpretationTranscriptome effectsFunctional interpretationClinical genome interpretationFunctional effectsPositional effectsImproved predictive modelVariantsTranscriptomeProfound effectInactivation