Clonal tracing with somatic epimutations reveals dynamics of blood aging

In this study, we generated comprehensive single-cell multi-omic datasets from bone marrow samples collected from 13 donors spanning a wide age range. We applied the scTAMseq protocol to profile DNA methylation and nuclear mutations obtained from 7 total bone marrow aspirates (donors A.1-A.7) and 6 CD34+-enriched bone marrow samples ((donors B.1-B.5 & X.1). Complementary surface marker expression data were acquired by integrating CITE-seq into the scTAMseq workflow (scTAMseq_prot). Targeted RNA sequencing (scTAMARA_rna) was performed alongside scTAMARA_DNA on one CD34+-enriched sample (X.1). Additionally, a dedicated mitochondrial panel (TAMITO_seq) was employed on a peripheral blood sample from a healthy donor (X.2) to assess mitochondrial heterogeneity and facilitate lineage tracing.

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

5 Datasets 1 Publication

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
EGAD00001015494	This dataset focuses on mitochondrial variant detection using the TAMITO-seq protocol. A pre-designed mitochondrial panel (https://designer.missionbio.com/catalogpanels/Virtual-mtDNA) was spiked into the scTAMseq workflow targeting 200 CpGs and 167 genotyping loci. Data were generated from a peripheral blood sample of a healthy donor, donor X.2, multiplexed with data from another donor.	Illumina NovaSeq 6000	1
EGAD00001015495	This dataset comprises targeted single-cell RNA expression profiles derived from the same CD34+ bone marrow sample (patient X.1) used for scTAMARA_DNA. 120 RNA targets were selected using LASSO regression to capture key transcripts predictive of cell state within the hematopoietic compartment.	Illumina NovaSeq 6000	1
EGAD00001015496	This dataset features single-cell DNA methylation and nuclear genotyping data obtained using the scTAMARA-seq protocol, a combination of SDR-seq and scTAM-seq. The targeted panel, 200 DNA methylation (a subset of the orginal 448 CpG targets) and 167 genotyping targets, were applied to a CD34+ enriched bone marrow sample from patient X.1. The data was generated on the Mission Bio Tapestri platform.	Illumina NovaSeq 6000	2
EGAD00001015497	This dataset contains single-cell surface marker expression profiles generated by integrating the Cite-seq protocol with scTAMseq. Samples were stained with an antibody panel targeting 45 (donor A.6 & A.7) and 56 (donors A.1-A.5, B.1-B.5, and X.2 ) surface proteins to enable robust phenotypic characterization.	Illumina NovaSeq 6000	10
EGAD00001015498	This dataset comprises single-cell DNA methylation and nuclear genotyping profiles of 7 total bone marrow aspirates (donors A.1-A.7) and 5 CD34+-enriched bone marrow samples (donors B.1-B.5) generated using the scTAMseq protocol. Sequencing was performed on the Mission Bio Tapestri platform, targeting a panel of 448 CpGs to assess epigenetic patterns and We also included 147 genomic regions commonly mutated in clonal hematopoiesis and 20 regions targeting chromosome Y. Samples B.1 & B.5, B.2 & B.4 and A.2 & A.5 were, in pairs, multiplexed into single tapestri lanes.	Illumina NovaSeq 6000	9

Publications	Citations
Clonal tracing with somatic epimutations reveals dynamics of blood ageing. Scherer M, Singh I, Braun MM, Szu-Tu C, Sanchez Sanchez P, Lindenhofer D, Jakobsen NA, Körber V, Kardorff M, Nitsch L, Kautz P, Rühle J, Bianchi A, Cozzuto L, Frömel R, Beneyto-Calabuig S, Lareau C, Satpathy AT, Beekman R, Steinmetz LM, Raffel S, Ludwig LS, Vyas P, Rodriguez-Fraticelli A, Velten L. Nature 643: 2025 478-487	13

Publications

Citations

Clonal tracing with somatic epimutations reveals dynamics of blood ageing.
Scherer M, Singh I, Braun MM, Szu-Tu C, Sanchez Sanchez P, Lindenhofer D, Jakobsen NA, Körber V, Kardorff M, Nitsch L, Kautz P, Rühle J, Bianchi A, Cozzuto L, Frömel R, Beneyto-Calabuig S, Lareau C, Satpathy AT, Beekman R, Steinmetz LM, Raffel S, Ludwig LS, Vyas P, Rodriguez-Fraticelli A, Velten L. Nature 643: 2025 478-487