Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing

Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

63 Datasets 9 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001004553	Direct library preparation+ single-cell DNA-sequencing of (i) patient derived triple negative breast cancer xenograft (ii) primary tumour and ascites ovarian cancer cell lines at tumour recurrence.	Illumina HiSeq 2500	980
EGAD00001004719	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1340 samples; filetype=bam	Illumina HiSeq 2500	1340
EGAD00001004720	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2057 samples; filetype=bam	Illumina HiSeq 2500	2057
EGAD00001004721	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1970 samples; filetype=bam	Illumina HiSeq 2500	1970
EGAD00001004722	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2091 samples; filetype=bam	Illumina HiSeq 2500	2091
EGAD00001004723	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1267 samples; filetype=bam	Illumina HiSeq 2500	1267
EGAD00001004724	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 230 samples; filetype=bam	Illumina HiSeq 2500	230
EGAD00001004725	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 232 samples; filetype=bam	Illumina HiSeq 2500	232
EGAD00001004726	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 239 samples; filetype=bam	Illumina HiSeq 2500	239
EGAD00001004727	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 692 samples; filetype=bam	Illumina HiSeq 2500	692
EGAD00001004728	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 612 samples; filetype=bam	Illumina HiSeq 2500	612
EGAD00001004729	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1700 samples; filetype=bam	Illumina HiSeq 2500	1700
EGAD00001004730	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 628 samples; filetype=bam	Illumina HiSeq 2500	628
EGAD00001004731	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 596 samples; filetype=bam	Illumina HiSeq 2500	596
EGAD00001004732	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1735 samples; filetype=bam	Illumina HiSeq 2500	1735
EGAD00001004733	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 585 samples; filetype=bam	NextSeq 550	585
EGAD00001004734	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 766 samples; filetype=bam	NextSeq 550	766
EGAD00001004735	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2055 samples; filetype=bam	Illumina HiSeq 2500	2055
EGAD00001004736	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 620 samples; filetype=bam	Illumina HiSeq 2500	620
EGAD00001004737	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 624 samples; filetype=bam	NextSeq 550	624
EGAD00001004738	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 481 samples; filetype=bam	NextSeq 550	481
EGAD00001004739	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 378 samples; filetype=bam	Illumina HiSeq 2500	378
EGAD00001004740	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 735 samples; filetype=bam	Illumina HiSeq 2500	735
EGAD00001004741	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 718 samples; filetype=bam	Illumina HiSeq 2500	718
EGAD00001004742	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 493 samples; filetype=bam	NextSeq 550	493
EGAD00001004743	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam	Illumina HiSeq 2500	1222
EGAD00001004744	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam	Illumina HiSeq 2500	522
EGAD00001004745	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 488 samples; filetype=bam	Illumina HiSeq 2500	488
EGAD00001004746	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 509 samples; filetype=bam	NextSeq 550	509
EGAD00001004747	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 604 samples; filetype=bam	NextSeq 550	604
EGAD00001004748	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 626 samples; filetype=bam	NextSeq 550	626
EGAD00001004749	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples; filetype=bam	Illumina HiSeq 2500	635
EGAD00001004750	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1522 samples; filetype=bam	HiSeq X Five	1522
EGAD00001004751	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 465 samples; filetype=bam	NextSeq 550	465
EGAD00001004752	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam	Illumina HiSeq 2500	606
EGAD00001004753	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam	NextSeq 550	615
EGAD00001004754	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 636 samples; filetype=bam	NextSeq 550	636
EGAD00001004755	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam	HiSeq X Five	968
EGAD00001004756	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 480 samples; filetype=bam	NextSeq 550	480
EGAD00001004757	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam	NextSeq 550	561
EGAD00001004758	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 844 samples; filetype=bam	HiSeq X Five	844
EGAD00001004759	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam	HiSeq X Five	928
EGAD00001004760	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples	HiSeq X Five	635
EGAD00001004761	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples	HiSeq X Five	1072
EGAD00001004762	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam	HiSeq X Five	1436
EGAD00001004763	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam	HiSeq X Five	589
EGAD00001004764	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam	HiSeq X Five	656
EGAD00001004765	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam	HiSeq X Five	648
EGAD00001004766	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam	HiSeq X Five	375
EGAD00001004767	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam	HiSeq X Five	755
EGAD00001004768	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam	HiSeq X Five	492
EGAD00001004769	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 531 samples; filetype=bam	HiSeq X Five	531
EGAD00001004770	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam	HiSeq X Five	1063
EGAD00001004771	Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam	HiSeq X Five Illumina HiSeq 2500	742
EGAD00001005338	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96146A 1195 samples; filetype=bam	HiSeq X Five	3
EGAD00001005340	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96172B 1694 samples; filetype=bam	HiSeq X Five	3
EGAD00001005345	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96226B 1274 samples; filetype=bam	HiSeq X Five	4
EGAD00001005347	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96193B 2410 samples; filetype=bam	HiSeq X Five	3
EGAD00001005348	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96199A 843 samples; filetype=bam	HiSeq X Five	3
EGAD00001005353	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96199B 1170 samples; filetype=bam	HiSeq X Five	3
EGAD00001005354	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96211C 1397 samples; filetype=bam	HiSeq X Five	3
EGAD00001005355	Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96225C 1034 samples; filetype=bam	HiSeq X Five	2
EGAD00001007756	OV2295-052021 dataset	Illumina HiSeq 2000	1

Publications	Citations
clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers. Campbell KR, Steif A, Laks E, Zahn H, Lai D, McPherson A, Farahani H, Kabeer F, O'Flanagan C, Biele J, Brimhall J, Wang B, Walters P, IMAXT Consortium, Bouchard-Côté A, Aparicio S, Shah SP. Genome Biol 20: 2019 54	55
Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing. Laks E, McPherson A, Zahn H, Lai D, Steif A, Brimhall J, Biele J, Wang B, Masud T, Ting J, Grewal D, Nielsen C, Leung S, Bojilova V, Smith M, Golovko O, Poon S, Eirew P, Kabeer F, Ruiz de Algara T, Lee SR, Taghiyar MJ, Huebner C, Ngo J, Chan T, Vatrt-Watts S, Walters P, Abrar N, Chan S, Wiens M, Martin L, Scott RW, Underhill TM, Chavez E, Steidl C, Da Costa D, Ma Y, Coope RJN, Corbett R, Pleasance S, Moore R, Mungall AJ, Mar C, Cafferty F, Gelmon K, Chia S, CRUK IMAXT Grand Challenge Team, Marra MA, Hansen C, Shah SP, Aparicio S. Cell 179: 2019 1207-1221.e22	107
Single-cell genomic variation induced by mutational processes in cancer. Funnell T, O'Flanagan CH, Williams MJ, McPherson A, McKinney S, Kabeer F, Lee H, Salehi S, Vázquez-García I, Shi H, Leventhal E, Masud T, Eirew P, Yap D, Zhang AW, Lim JLP, Wang B, Brimhall J, Biele J, Ting J, Au V, Van Vliet M, Liu YF, Beatty S, Lai D, Pham J, Grewal D, Abrams D, Havasov E, Leung S, Bojilova V, Moore RA, Rusk N, Uhlitz F, Ceglia N, Weiner AC, Zaikova E, Douglas JM, Zamarin D, Weigelt B, Kim SH, Da Cruz Paula A, Reis-Filho JS, Martin SD, Li Y, Xu H, de Algara TR, Lee SR, Llanos VC, Huntsman DG, McAlpine JN, IMAXT Consortium, Shah SP, Aparicio S. Nature 612: 2022 106-115	36
Computational Methods for Single-cell Multi-omics Integration and Alignment. Stanojevic S, Li Y, Ristivojevic A, Garmire LX. Genomics Proteomics Bioinformatics 20: 2022 836-849	16
Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics. Jun SH, Toosi H, Mold J, Engblom C, Chen X, O'Flanagan C, Hagemann-Jensen M, Sandberg R, Aparicio S, Hartman J, Roth A, Lagergren J. Nat Commun 14: 2023 982	5
Fast intratumor heterogeneity inference from single-cell sequencing data. Kızılkale C, Rashidi Mehrabadi F, Sadeqi Azer E, Pérez-Guijarro E, Marie KL, Lee MP, Day CP, Merlino G, Ergün F, Buluç A, Sahinalp SC, Malikić S. Nat Comput Sci 2: 2022 577-583	3
Joint inference of clonal structure using single-cell genome and transcriptome sequencing data. Bai X, Duren Z, Wan L, Xia LC. NAR Genom Bioinform 6: 2024 lqae017	5
Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes. Kim M, Gorelick AN, Vàzquez-García I, Williams MJ, Salehi S, Shi H, Weiner AC, Ceglia N, Funnell T, Park T, Boscenco S, O'Flanagan CH, Jiang H, Grewal D, Tang C, Rusk N, Gammage PA, McPherson A, Aparicio S, Shah SP, Reznik E. Nat Genet 56: 2024 889-899	1
Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data. Weiner AC, Williams MJ, Shi H, Vázquez-García I, Salehi S, Rusk N, Aparicio S, Shah SP, McPherson A. Nat Commun 15: 2024 8512	2