Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling.

Aged, 80 and over Cell Differentiation Cells, Cultured Clonal Evolution Clone Cells DNA, Mitochondrial / genetics Epigenesis, Genetic Female Genotyping Techniques Hematopoiesis High-Throughput Nucleotide Sequencing / methods Humans Mitochondria / genetics Mutation Neoplasms / genetics Sequence Analysis, DNA Single-Cell Analysis / methods

Journal

Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648

Informations de publication

Date de publication:
04 2021
Historique:
received: 20 01 2020
accepted: 17 07 2020
pubmed: 14 8 2020
medline: 23 4 2021
entrez: 14 8 2020
Statut: ppublish

Résumé

Natural mitochondrial DNA (mtDNA) mutations enable the inference of clonal relationships among cells. mtDNA can be profiled along with measures of cell state, but has not yet been combined with the massively parallel approaches needed to tackle the complexity of human tissue. Here, we introduce a high-throughput, droplet-based mitochondrial single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), a method that combines high-confidence mtDNA mutation calling in thousands of single cells with their concomitant high-quality accessible chromatin profile. This enables the inference of mtDNA heteroplasmy, clonal relationships, cell state and accessible chromatin variation in individual cells. We reveal single-cell variation in heteroplasmy of a pathologic mtDNA variant, which we associate with intra-individual chromatin variability and clonal evolution. We clonally trace thousands of cells from cancers, linking epigenomic variability to subclonal evolution, and infer cellular dynamics of differentiating hematopoietic cells in vitro and in vivo. Taken together, our approach enables the study of cellular population dynamics and clonal properties in vivo.

Identifiants

DOI: 10.1038/s41587-020-0645-6 PMID: 32788668 PMC: PMC7878580
pubmed: 32788668
doi: 10.1038/s41587-020-0645-6
pii: 10.1038/s41587-020-0645-6
pmc: PMC7878580
mid: NIHMS1613366
doi:

Substances chimiques

DNA, Mitochondrial 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

451-461

Subventions

Organisme : NCI NIH HHS
ID : U10 CA180861
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States
Organisme : NHGRI NIH HHS
ID : T32 HG002295
Pays : United States
Organisme : NCI NIH HHS
ID : F31 CA232670
Pays : United States
Organisme : NCI NIH HHS
ID : UG1 CA233338
Pays : United States
Organisme : NCI NIH HHS
ID : T32 CA207021
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA206978
Pays : United States
Organisme : NHLBI NIH HHS
ID : R33 HL120791
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA208756
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK103794
Pays : United States

Commentaires et corrections

Type : ErratumIn

Références

Stewart, J. B. & Chinnery, P. F. The dynamics of mitochondrial DNA heteroplasmy: implications for human health and disease. Nat. Rev. Genet. 16, 530–542 (2015).
pubmed: 26281784 doi: 10.1038/nrg3966
Shoffner, J. M. & Wallace, D. C. Mitochondrial genetics: principles and practice. Am. J. Hum. Genet. 51, 1179–1186 (1992).
pubmed: 1463005 pmcid: 1682908
Elliott, H. R., Samuels, D. C., Eden, J. A., Relton, C. L. & Chinnery, P. F. Pathogenic mitochondrial DNA mutations are common in the general population. Am. J. Hum. Genet. 83, 254–260 (2008).
pubmed: 18674747 pmcid: 2495064 doi: 10.1016/j.ajhg.2008.07.004
Morris, J. et al. Pervasive within-mitochondrion single-nucleotide variant heteroplasmy as revealed by single-mitochondrion sequencing. Cell Rep. 21, 2706–2713 (2017).
pubmed: 29212019 pmcid: 5771502 doi: 10.1016/j.celrep.2017.11.031
Kang, E. et al. Age-related accumulation of somatic mitochondrial DNA mutations in adult-derived human iPSCs. Cell Stem Cell 18, 625–636 (2016).
pubmed: 27151456 doi: 10.1016/j.stem.2016.02.005
Ludwig, L. S. et al. Lineage tracing in humans enabled by mitochondrial mutations and single-cell genomics. Cell 176, 1325–1339.e22 (2019).
pubmed: 30827679 pmcid: 6408267 doi: 10.1016/j.cell.2019.01.022
Xu, J. et al. Single-cell lineage tracing by endogenous mutations enriched in transposase accessible mitochondrial DNA. eLife 8, e45105 (2019).
pubmed: 30958261 pmcid: 6469926 doi: 10.7554/eLife.45105
Lodato, M. A. et al. Somatic mutation in single human neurons tracks developmental and transcriptional history. Science 350, 94–98 (2015).
pubmed: 26430121 pmcid: 4664477 doi: 10.1126/science.aab1785
Lareau, C. A. et al. Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility. Nat. Biotechnol. 37, 916–924 (2019).
pubmed: 31235917 pmcid: 10299900 doi: 10.1038/s41587-019-0147-6
Satpathy, A. T. et al. Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion. Nat. Biotechnol. 37, 925–936 (2019).
pubmed: 31375813 pmcid: 7299161 doi: 10.1038/s41587-019-0206-z
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
pubmed: 24097267 pmcid: 3959825 doi: 10.1038/nmeth.2688
Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).
pubmed: 28846090 pmcid: 5623106 doi: 10.1038/nmeth.4396
Ross, M. G. et al. Characterizing and measuring bias in sequence data. Genome Biol. 14, R51 (2013).
pubmed: 23718773 pmcid: 4053816 doi: 10.1186/gb-2013-14-5-r51
Roadmap Epigenomics Consortium et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).
pmcid: 4530010 doi: 10.1038/nature14248
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).
doi: 10.1038/nature11247
Green, B., Bouchier, C., Fairhead, C., Craig, N. L. & Cormack, B. P. Insertion site preference of Mu, Tn5, and Tn7 transposons. Mob. DNA 3, 3 (2012).
pubmed: 22313799 pmcid: 3292447 doi: 10.1186/1759-8753-3-3
Dames, S. et al. The development of next-generation sequencing assays for the mitochondrial genome and 108 nuclear genes associated with mitochondrial disorders. J. Mol. Diagn. 15, 526–534 (2013).
pubmed: 23665194 doi: 10.1016/j.jmoldx.2013.03.005
Wallace, D. C. & Chalkia, D. Mitochondrial DNA genetics and the heteroplasmy conundrum in evolution and disease. Cold Spring Harb. Perspect. Biol. 5, a021220 (2013).
pubmed: 24186072 pmcid: 3809581 doi: 10.1101/cshperspect.a021220
Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015).
pubmed: 26083756 pmcid: 4685948 doi: 10.1038/nature14590
Lee, J. H. et al. Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nat. Protoc. 10, 442–458 (2015).
pubmed: 25675209 pmcid: 4327781 doi: 10.1038/nprot.2014.191
Wu, S.-P. et al. Increased COUP-TFII expression in adult hearts induces mitochondrial dysfunction resulting in heart failure. Nat. Commun. 6, 8245 (2015).
pubmed: 26356605 doi: 10.1038/ncomms9245
Zunino, R., Schauss, A., Rippstein, P., Andrade-Navarro, M. & McBride, H. M. The SUMO protease SENP5 is required to maintain mitochondrial morphology and function. J. Cell Sci. 120, 1178–1188 (2007).
pubmed: 17341580 doi: 10.1242/jcs.03418
Powell, C. A. et al. TRMT5 mutations cause a defect in post-transcriptional modification of mitochondrial tRNA associated with multiple respiratory-chain deficiencies. Am. J. Hum. Genet. 97, 319–328 (2015).
pubmed: 26189817 pmcid: 4573257 doi: 10.1016/j.ajhg.2015.06.011
Kugeratski, F. G. et al. Hypoxic cancer–associated fibroblasts increase NCBP2-AS2/HIAR to promote endothelial sprouting through enhanced VEGF signaling. Sci. Signal. 12, eaan8247 (2019).
pubmed: 30723174 pmcid: 6794160 doi: 10.1126/scisignal.aan8247
Brusco, J. & Haas, K. Interactions between mitochondria and the transcription factor myocyte enhancer factor 2 (MEF2) regulate neuronal structural and functional plasticity and metaplasticity. J. Physiol. 593, 3471–3481 (2015).
pubmed: 25581818 pmcid: 4560579 doi: 10.1113/jphysiol.2014.282459
Lott, M. T. et al. mtDNA variation and analysis using mitomap and mitomaster. Curr. Protoc. Bioinformatics 44, 1.23.1–26 (2013).
pubmed: 25489354 doi: 10.1002/0471250953.bi0123s44
Bohrson, C. L. et al. Linked-read analysis identifies mutations in single-cell DNA-sequencing data. Nat. Genet. 51, 749–754 (2019).
pubmed: 30886424 pmcid: 6900933 doi: 10.1038/s41588-019-0366-2
Zafar, H., Wang, Y., Nakhleh, L., Navin, N. & Chen, K. Monovar: single-nucleotide variant detection in single cells. Nat. Methods 13, 505–507 (2016).
pubmed: 27088313 pmcid: 4887298 doi: 10.1038/nmeth.3835
Roos-Weil, D. et al. Mutational and cytogenetic analyses of 188 CLL patients with trisomy 12: a retrospective study from the French Innovative Leukemia Organization (FILO) working group. Genes Chromosomes Cancer 57, 533–540 (2018).
pubmed: 30203893 doi: 10.1002/gcc.22650
Izumi, D. et al. TIAM1 promotes chemoresistance and tumor invasiveness in colorectal cancer. Cell Death Dis. 10, 267 (2019).
pubmed: 30890693 pmcid: 6425043 doi: 10.1038/s41419-019-1493-5
Hofbauer, S. W. et al. Tiam1/Rac1 signals contribute to the proliferation and chemoresistance, but not motility, of chronic lymphocytic leukemia cells. Blood 123, 2181–2188 (2014).
pubmed: 24501217 doi: 10.1182/blood-2013-08-523563
Damm, F. et al. Acquired initiating mutations in early hematopoietic cells of CLL patients. Cancer Discov. 4, 1088–1101 (2014).
pubmed: 24920063 doi: 10.1158/2159-8290.CD-14-0104
Kikushige, Y. et al. Self-renewing hematopoietic stem cell is the primary target in pathogenesis of human chronic lymphocytic leukemia. Cancer Cell 20, 246–259 (2011).
pubmed: 21840488 doi: 10.1016/j.ccr.2011.06.029
Alizadeh, A. A. & Majeti, R. Surprise! HSC are aberrant in chronic lymphocytic leukemia. Cancer Cell 20, 135–136 (2011).
pubmed: 21840478 doi: 10.1016/j.ccr.2011.08.001
Lee-Six, H. et al. Population dynamics of normal human blood inferred from somatic mutations. Nature 561, 473–478 (2018).
pubmed: 30185910 pmcid: 6163040 doi: 10.1038/s41586-018-0497-0
Osorio, F. G. et al. Somatic mutations reveal lineage relationships and age-related mutagenesis in human hematopoiesis. Cell Rep. 25, 2308–2316.e4 (2018).
pubmed: 30485801 pmcid: 6289083 doi: 10.1016/j.celrep.2018.11.014
Granja, J. M. et al. Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia. Nat. Biotechnol. 37, 1458–1465 (2019).
pubmed: 31792411 pmcid: 7258684 doi: 10.1038/s41587-019-0332-7
Schep, A. N., Wu, B., Buenrostro, J. D. & Greenleaf, W. J. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data. Nat. Methods 14, 975–978 (2017).
pubmed: 28825706 pmcid: 5623146 doi: 10.1038/nmeth.4401
Buenrostro, J. D. et al. Integrated single-cell analysis maps the continuous regulatory landscape of human hematopoietic differentiation. Cell 173, 1535–1548.e16 (2018).
pubmed: 29706549 pmcid: 5989727 doi: 10.1016/j.cell.2018.03.074
Cusanovich, D. A. et al. A single-cell atlas of in vivo mammalian chromatin accessibility. Cell 174, 1309–1324.e18 (2018).
pubmed: 30078704 pmcid: 6158300 doi: 10.1016/j.cell.2018.06.052
Pliner, H. A. et al. Cicero predicts cis-regulatory DNA interactions from single-cell chromatin accessibility data. Mol. Cell 71, 858–871.e8 (2018).
pubmed: 30078726 pmcid: 6582963 doi: 10.1016/j.molcel.2018.06.044
Choi, J. et al. Haemopedia RNA-seq: a database of gene expression during haematopoiesis in mice and humans. Nucleic Acids Res. 47, D780–D785 (2019).
pubmed: 30395284 doi: 10.1093/nar/gky1020
Jovanovic, M. et al. Immunogenetics. Dynamic profiling of the protein life cycle in response to pathogens. Science 347, 1259038 (2015).
pubmed: 25745177 pmcid: 4506746 doi: 10.1126/science.1259038
Ju, Y. S. et al. Origins and functional consequences of somatic mitochondrial DNA mutations in human cancer. eLife 3, e02935 (2014).
pubmed: 25271376 pmcid: 4371858 doi: 10.7554/eLife.02935
Lareau, C. A., Ludwig, L. S. & Sankaran, V. G. Longitudinal assessment of clonal mosaicism in human hematopoiesis via mitochondrial mutation tracking. Blood Adv. 3, 4161–4165 (2019).
pubmed: 31841597 pmcid: 6929387 doi: 10.1182/bloodadvances.2019001196
Rodriguez-Fraticelli, A. E. et al. Clonal analysis of lineage fate in native haematopoiesis. Nature 553, 212–216 (2018).
pubmed: 29323290 pmcid: 5884107 doi: 10.1038/nature25168
Sun, J. et al. Clonal dynamics of native haematopoiesis. Nature 514, 322–327 (2014).
pubmed: 25296256 pmcid: 4408613 doi: 10.1038/nature13824
Pei, W. et al. Polylox barcoding reveals haematopoietic stem cell fates realized in vivo. Nature 548, 456–460 (2017).
pubmed: 28813413 pmcid: 5905670 doi: 10.1038/nature23653
Biasco, L. et al. In vivo tracking of human hematopoiesis reveals patterns of clonal dynamics during early and steady-state reconstitution phases. Cell Stem Cell 19, 107–119 (2016).
pubmed: 27237736 pmcid: 4942697 doi: 10.1016/j.stem.2016.04.016
Scala, S. et al. Dynamics of genetically engineered hematopoietic stem and progenitor cells after autologous transplantation in humans. Nat. Med. 24, 1683–1690 (2018).
pubmed: 30275570 doi: 10.1038/s41591-018-0195-3
Nam, A. S. et al. Somatic mutations and cell identity linked by genotyping of transcriptomes. Nature 571, 355–360 (2019).
pubmed: 31270458 pmcid: 6782071 doi: 10.1038/s41586-019-1367-0
Walker, M. A. et al. Purifying selection against pathogenic mitochondrial DNA in human T cells. N. Engl. J. Med. https://doi.org/10.1056/NEJMoa2001265 (2020).
Corral-Debrinski, M. et al. Marked changes in mitochondrial DNA deletion levels in Alzheimer brains. Genomics 23, 471–476 (1994).
pubmed: 7835898 doi: 10.1006/geno.1994.1525
Bender, A. et al. High levels of mitochondrial DNA deletions in substantia nigra neurons in aging and Parkinson disease. Nat. Genet. 38, 515–517 (2006).
pubmed: 16604074 doi: 10.1038/ng1769
Lee, S. R. & Han, J. Mitochondrial mutations in cardiac disorders. Adv. Exp. Med. Biol. 982, 81–111 (2017).
pubmed: 28551783 doi: 10.1007/978-3-319-55330-6_5
Triska, P. et al. Landscape of germline and somatic mitochondrial DNA mutations in pediatric malignancies. Cancer Res. 79, 7 (2019).
doi: 10.1158/0008-5472.CAN-18-2220
Sun, N., Youle, R. J. & Finkel, T. The mitochondrial basis of aging. Mol. Cell 61, 654–666 (2016).
pubmed: 26942670 pmcid: 4779179 doi: 10.1016/j.molcel.2016.01.028
Hu, J. et al. Isolation and functional characterization of human erythroblasts at distinct stages: implications for understanding of normal and disordered erythropoiesis in vivo. Blood 121, 3246–3253 (2013).
pubmed: 23422750 pmcid: 3630836 doi: 10.1182/blood-2013-01-476390
Giani, F. C. et al. Targeted application of human genetic variation can improve red blood cell production from stem cells. Cell Stem Cell 18, 73–78 (2016).
pubmed: 26607381 doi: 10.1016/j.stem.2015.09.015
Huang, W., Li, L., Myers, J. R. & Marth, G. T. ART: a next-generation sequencing read simulator. Bioinformatics 28, 593–594 (2012).
pubmed: 22199392 doi: 10.1093/bioinformatics/btr708
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
pubmed: 20110278 pmcid: 2832824 doi: 10.1093/bioinformatics/btq033
Lareau, C. A., Ma, S., Duarte, F. M. & Buenrostro, J. D. Inference and effects of barcode multiplets in droplet-based single-cell assays. Nat. Commun. 11, 866 (2020).
pubmed: 32054859 pmcid: 7018801 doi: 10.1038/s41467-020-14667-5
Lander, E. S. & Waterman, M. S. Genomic mapping by fingerprinting random clones: a mathematical analysis. Genomics 2, 231–239 (1988).
pubmed: 3294162 doi: 10.1016/0888-7543(88)90007-9
Chen, F., Tillberg, P. W. & Boyden, E. S. Optical imaging. Expansion microscopy. Science 347, 543–548 (2015).
pubmed: 25592419 pmcid: 4312537 doi: 10.1126/science.1260088
van Dekken, H., Pinkel, D., Mullikin, J. & Gray, J. W. Enzymatic production of single-stranded DNA as a target for fluorescence in situ hybridization. Chromosoma 97, 1–5 (1988).
pubmed: 3191791 doi: 10.1007/BF00331788
Larsson, C. et al. In situ genotyping individual DNA molecules by target-primed rolling-circle amplification of padlock probes. Nat. Methods 1, 227–232 (2004).
pubmed: 15782198 doi: 10.1038/nmeth723
Schwartz, S., Oren, R. & Ast, G. Detection and removal of biases in the analysis of next-generation sequencing reads. PLoS ONE 6, e16685 (2011).
pubmed: 21304912 pmcid: 3031631 doi: 10.1371/journal.pone.0016685
Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).
pubmed: 21903627 pmcid: 3198575 doi: 10.1093/bioinformatics/btr509
Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at arXiv https://arxiv.org/abs/1207.3907 (2012).
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902.e21 (2019).
pubmed: 31178118 pmcid: 6687398 doi: 10.1016/j.cell.2019.05.031
Becht, E. et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat. Biotechnol. 37, 38–44 (2019).
doi: 10.1038/nbt.4314

Auteurs

Caleb A Lareau (CA)

Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. clareau@broadinstitute.org.
Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. clareau@broadinstitute.org.
Division of Medical Sciences, Harvard Medical School, Boston, MA, USA. clareau@broadinstitute.org.
ORCID: 0000-0003-4179-4807

Leif S Ludwig (LS)

Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. ludwig@broadinstitute.org.
Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. ludwig@broadinstitute.org.
ORCID: 0000-0002-2916-2164

Christoph Muus (C)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
ORCID: 0000-0003-2779-0893

Satyen H Gohil (SH)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Department of Academic Haematology, UCL Cancer Institute, London, UK.

Tongtong Zhao (T)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.

Zachary Chiang (Z)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Division of Medical Sciences, Harvard Medical School, Boston, MA, USA.
Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.

Karin Pelka (K)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Jeffrey M Verboon (JM)

Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Wendy Luo (W)

Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Elena Christian (E)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Division of Medical Sciences, Harvard Medical School, Boston, MA, USA.

Daniel Rosebrock (D)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Gad Getz (G)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Pathology, Harvard Medical School, Boston, MA, USA.
ORCID: 0000-0002-0936-0753

Genevieve M Boland (GM)

Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Fei Chen (F)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
ORCID: 0000-0003-2308-3649

Jason D Buenrostro (JD)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
ORCID: 0000-0001-9958-3987

Nir Hacohen (N)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
ORCID: 0000-0002-2349-2656

Catherine J Wu (CJ)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
ORCID: 0000-0002-3348-5054

Martin J Aryee (MJ)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Pathology, Harvard Medical School, Boston, MA, USA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Aviv Regev (A)

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. aregev@broadinstitute.org.
Howard Hughes Medical Institute, Chevy Chase, MD, USA. aregev@broadinstitute.org.
Department of Biology and Koch Institute, Massachusetts Institute of Technology, Cambridge, MA, USA. aregev@broadinstitute.org.
ORCID: 0000-0003-3293-3158

Vijay G Sankaran (VG)

Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. sankaran@broadinstitute.org.
Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. sankaran@broadinstitute.org.
Harvard Stem Cell Institute, Cambridge, MA, USA. sankaran@broadinstitute.org.
ORCID: 0000-0003-0044-443X

Articles similaires

Comprehensive comparative analysis and development of molecular markers for Lasianthus species based on complete chloroplast genome sequences.

Yue Zhang, Meifang Song, Deying Tang et al.
1.00
Genome, Chloroplast Phylogeny Genetic Markers Base Composition High-Throughput Nucleotide Sequencing

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female

Evaluation of Low-Value Services Across Major Medicare Advantage Insurers and Traditional Medicare.

Ciara Duggan, Adam L Beckman, Ishani Ganguli et al.
1.00
Humans United States Aged Cross-Sectional Studies Medicare Part C

Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Sujet âgé de 80 ans ou plus › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Phénomènes physiologiques cellulaires › Différenciation cellulaire › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Cellules › Cellules cultivées › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Phénomènes génétiques › Évolution clonale › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Cellules › Cellules cultivées › Clones cellulaires › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › ADN › ADN mitochondrial › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Phénomènes génétiques › Régulation de l'expression des gènes › Épigenèse génétique › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Techniques d'investigation › Techniques génétiques › Techniques de génotypage › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Phénomènes physiologiques respiratoires et circulatoires › Phénomènes physiogiques du sang › Hématopoïèse › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Techniques d'investigation › Techniques génétiques › Analyse de séquence › Séquençage nucléotidique à haut débit › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Cellules › Structures cellulaires › Fractions subcellulaires › Mitochondries › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Mutation › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Tumeurs › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Techniques d'investigation › Techniques génétiques › Analyse de séquence › Analyse de séquence d'ADN › Massively parallel single-cell mitochondrial...
questionsmedicales.fr › Techniques d'investigation › Techniques cytologiques › Analyse sur cellule unique › Massively parallel single-cell mitochondrial...