2023
Efficient reconstruction of cell lineage trees for cell ancestry and cancer
Jang Y, Fasching L, Bae T, Tomasini L, Schreiner J, Szekely A, Fernandez T, Leckman J, Vaccarino F, Abyzov A. Efficient reconstruction of cell lineage trees for cell ancestry and cancer. Nucleic Acids Research 2023, 51: e57-e57. PMID: 37026484, PMCID: PMC10250207, DOI: 10.1093/nar/gkad254.Peer-Reviewed Original ResearchConceptsLineage treesCell ancestryCell lineage treesFirst cell divisionStem cell linesPluripotent stem cell lineLineage reconstructionInduced pluripotent stem cell lineCell divisionCancer progressionLineage representationCell linesMosaic mutationsHuman skin fibroblastsTreesMutationsAncestrySkin fibroblastsMultiple cellsGenomeLineagesZygotesLinesFibroblastsCellsClonally Selected Lines After CRISPR-Cas Editing Are Not Isogenic
Panda A, Suvakov M, Mariani J, Drucker K, Park Y, Jang Y, Kollmeyer T, Sarkar G, Bae T, Kim J, Yoon W, Jenkins R, Vaccarino F, Abyzov A. Clonally Selected Lines After CRISPR-Cas Editing Are Not Isogenic. The CRISPR Journal 2023, 6: 176-182. PMID: 37071670, PMCID: PMC10123805, DOI: 10.1089/crispr.2022.0050.Peer-Reviewed Original ResearchConceptsCopy number alterationsSeparate genomic lociSingle nucleotide mutationsApplication of CRISPRCRISPR-Cas editingOff-target editsScreening of clonesGenomic divergenceWhole-genome sequencingGenomic lociSelection of clonesGenome sequencingNucleotide mutationsTarget editsCultured cellsClonal linesNumber alterationsCell cloningClonesMutationsCloningCRISPR
2022
Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability
Bae T, Fasching L, Wang Y, Shin JH, Suvakov M, Jang Y, Norton S, Dias C, Mariani J, Jourdon A, Wu F, Panda A, Pattni R, Chahine Y, Yeh R, Roberts RC, Huttner A, Kleinman JE, Hyde TM, Straub RE, Walsh CA, Urban A, Leckman J, Weinberger D, Vaccarino F, Abyzov A, Walsh C, Park P, Sestan N, Weinberger D, Moran J, Gage F, Vaccarino F, Gleeson J, Mathern G, Courchesne E, Roy S, Chess A, Akbarian S, Bizzotto S, Coulter M, Dias C, D’Gama A, Ganz J, Hill R, Huang A, Khoshkhoo S, Kim S, Lee A, Lodato M, Maury E, Miller M, Borges-Monroy R, Rodin R, Zhou Z, Bohrson C, Chu C, Cortes-Ciriano I, Dou Y, Galor A, Gulhan D, Kwon M, Luquette J, Sherman M, Viswanadham V, Jones A, Rosenbluh C, Cho S, Langmead B, Thorpe J, Erwin J, Jaffe A, McConnell M, Narurkar R, Paquola A, Shin J, Straub R, Abyzov A, Bae T, Jang Y, Wang Y, Molitor C, Peters M, Linker S, Reed P, Wang M, Urban A, Zhou B, Zhu X, Pattni R, Serres Amero A, Juan D, Lobon I, Marques-Bonet T, Solis Moruno M, Garcia Perez R, Povolotskaya I, Soriano E, Antaki D, Averbuj D, Ball L, Breuss M, Yang X, Chung C, Emery S, Flasch D, Kidd J, Kopera H, Kwan K, Mills R, Moldovan J, Sun C, Zhao X, Zhou W, Frisbie T, Cherskov A, Fasching L, Jourdon A, Pochareddy S, Scuderi S. Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability. Science 2022, 377: 511-517. PMID: 35901164, PMCID: PMC9420557, DOI: 10.1126/science.abm6222.Peer-Reviewed Original ResearchConceptsTranscription factorsSomatic mutationsPutative transcription factorEnhancer-like regionSingle nucleotide mutationsWhole-genome sequencingGene regulationSomatic duplicationGenome sequencingDamaging mutationsBackground mutagenesisMutationsHypermutabilityClonal expansionMotifDiseased brainPotential linkVivo clonal expansionMutagenesisGenesDuplicationSequencingRegulation
2020
SCELLECTOR: ranking amplification bias in single cells using shallow sequencing
Sarangi V, Jourdon A, Bae T, Panda A, Vaccarino F, Abyzov A. SCELLECTOR: ranking amplification bias in single cells using shallow sequencing. BMC Bioinformatics 2020, 21: 521. PMID: 33183232, PMCID: PMC7663899, DOI: 10.1186/s12859-020-03858-y.Peer-Reviewed Original ResearchConceptsMultiple displacement amplificationShallow sequencingSingle-cell platformsSingle-cell sequencingCoverage sequencing dataSingle cellsHuman neuronal cellsMosaic mutationsAmount of DNAAmplification qualityCell sequencingCoverage sequencingHigh-coverage dataSequencing dataHaplotype informationPhi29 polymeraseDNA damageIndividual cellsNeuronal cellsSequencingAmplification biasAllelic imbalancePresence of sitesMutationsFragment length
2017
Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis
Bae T, Tomasini L, Mariani J, Zhou B, Roychowdhury T, Franjic D, Pletikos M, Pattni R, Chen BJ, Venturini E, Riley-Gillis B, Sestan N, Urban AE, Abyzov A, Vaccarino FM. Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science 2017, 359: 550-555. PMID: 29217587, PMCID: PMC6311130, DOI: 10.1126/science.aan8690.Peer-Reviewed Original ResearchConceptsSingle nucleotide variationsMutation rateCancer cell genomeClonal cell populationsCell genomeCell lineagesBackground mutagenesisHuman cellsMutational rateSomatic mosaicismSingle cellsOxidative damageGenomeMutagenesisCell populationsMutation spectrumNeurogenesisCellsHuman fetusesIndividual neuronsLineagesPregastrulationHuman brainBrainMutationsIntersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network
McConnell MJ, Moran JV, Abyzov A, Akbarian S, Bae T, Cortes-Ciriano I, Erwin JA, Fasching L, Flasch DA, Freed D, Ganz J, Jaffe AE, Kwan KY, Kwon M, Lodato MA, Mills RE, Paquola ACM, Rodin RE, Rosenbluh C, Sestan N, Sherman MA, Shin JH, Song S, Straub RE, Thorpe J, Weinberger DR, Urban AE, Zhou B, Gage FH, Lehner T, Senthil G, Walsh CA, Chess A, Courchesne E, Gleeson JG, Kidd JM, Park PJ, Pevsner J, Vaccarino FM, Barton A, Bekiranov S, Bohrson C, Burbulis I, Chronister W, Coppola G, Daily K, D’Gama A, Emery S, Frisbie T, Gao T, Gulyás-Kovács A, Haakenson M, Keil J, Kopera H, Lam M, Lee E, Marques-Bonet T, Mathern G, Moldovan J, Oetjens M, Omberg L, Peters M, Pochareddy S, Pramparo T, Ratan A, Sanavia T, Shi L, Skarica M, Wang J, Wang M, Wang Y, Wierman M, Wolpert M, Woodworth M, Zhao X, Zhou W. Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 2017, 356 PMID: 28450582, PMCID: PMC5558435, DOI: 10.1126/science.aal1641.Peer-Reviewed Original ResearchConceptsSomatic mutationsComplex genetic architectureStructural genomic variantsNeuronal genomeNeuronal transcriptomeGenetic architectureCell divisionCellular metabolismGenomic variantsLong life spanDNA damageComplex neuropsychiatric disorderCellular expansionNeuropsychiatric diseasesNeuropsychiatric disordersProgenitor cellsSomatic mosaicismIndividual neurodevelopmentSmall populationCell proliferationPopulation-based studyMutationsGermline variantsLife spanBrain development