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 cellsGenomeLineagesZygotesLinesFibroblastsCells
2022
Postmortem Human Dura Mater Cells Exhibit Phenotypic, Transcriptomic and Genetic Abnormalities that Impact their Use for Disease Modeling
Argouarch A, Schultz N, Yang A, Jang Y, Garcia K, Cosme C, Corrales C, Nana A, Karydas A, Spina S, Grinberg L, Miller B, Wyss-Coray T, Abyzov A, Goodarzi H, Seeley W, Kao A. Postmortem Human Dura Mater Cells Exhibit Phenotypic, Transcriptomic and Genetic Abnormalities that Impact their Use for Disease Modeling. Stem Cell Reviews And Reports 2022, 18: 3050-3065. PMID: 35809166, PMCID: PMC9622518, DOI: 10.1007/s12015-022-10416-x.Peer-Reviewed Original ResearchConceptsDivergent gene expression profilesDefective DNA damage repairDisease modelingDNA damage repairGene expression profilesSpecific cell typesCell linesDura mater cellsDermal fibroblastsSomatic mutation signaturesPatient-derived cellsNormal biologyDamage repairExpression profilesSlow growth rateDifferentiation protocolsCell typesFibroblast-like cellsMutation signaturesProtein markersHuman dermal fibroblastsExhibit phenotypicNeurodegenerative diseasesDura materFibroblasts
2019
Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2
Zhou B, Ho S, Greer S, Spies N, Bell J, Zhang X, Zhu X, Arthur J, Byeon S, Pattni R, Saha I, Huang Y, Song G, Perrin D, Wong W, Ji H, Abyzov A, Urban A. Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2. Nucleic Acids Research 2019, 47: 3846-3861. PMID: 30864654, PMCID: PMC6486628, DOI: 10.1093/nar/gkz169.Peer-Reviewed Original ResearchConceptsGenome sequenceStructural variantsGenomic structural featuresSomatic genomic rearrangementsFunctional genomics dataAllele-specific expressionEntire chromosome armsIntegrated genome analysisCRISPR/Cas9Cell linesMain cell linesGenome structureEpigenomic characteristicsChromosome armsGenome analysisDNA methylationGenome characteristicsRetrotransposon insertionChromosomal segmentsGenomic rearrangementsGenomic dataRegulatory complexityCell line HepG2Copy numberLoss of heterozygosity
2017
One thousand somatic SNVs per skin fibroblast cell set baseline of mosaic mutational load with patterns that suggest proliferative origin
Abyzov A, Tomasini L, Zhou B, Vasmatzis N, Coppola G, Amenduni M, Pattni R, Wilson M, Gerstein M, Weissman S, Urban AE, Vaccarino FM. One thousand somatic SNVs per skin fibroblast cell set baseline of mosaic mutational load with patterns that suggest proliferative origin. Genome Research 2017, 27: 512-523. PMID: 28235832, PMCID: PMC5378170, DOI: 10.1101/gr.215517.116.Peer-Reviewed Original ResearchConceptsSomatic mosaicismFibroblast cellsSingle-cell whole-genome amplificationAllele frequenciesNumber of SNVsNormal cell proliferationCell proliferationWhole genome amplificationStem cell linesPluripotent stem cell lineHealthy human tissuesDe novo variantsCancer mutationsHigh-resolution analysisMutational loadPCR experimentsSkin fibroblast cellsMutational signaturesHiPSC linesDe novoGenomeNovo variantsFibroblast populationsCell linesSomatic SNVs
2015
Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors
Mitra A, Mukherjee U, Harding T, Jang J, Stessman H, Li Y, Abyzov A, Jen J, Kumar S, Rajkumar V, Van Ness B. Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors. Leukemia 2015, 30: 1094-1102. PMID: 26710886, DOI: 10.1038/leu.2015.361.Peer-Reviewed Original ResearchConceptsSingle cellsIndividual cellsSignificant genetic diversitySingle-cell analysisGene expression profile signaturesSingle-cell levelGenetic diversityTranscriptome analysisDrug responseCellular responsesDrug sensitivityBulk populationInhibitor sensitivitySubclonal architectureProfiling studiesPCR analysisPrediction programsCell linesMyeloma cell linesTumor progressionCellsIntratumor heterogeneityProfile signaturesProteasome inhibitor sensitivitySubclonal level