The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR

We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health.

Type: Cancer Genomics
Archiver: EGA European Genome-Phenome Archive

3 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
EGAD00001004086	We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health. This dataset contains all the data available for this study on 2018-04-19.	HiSeq X Ten Illumina HiSeq 2500	207
EGAD00001006595	This dataset contains 160 single-cell derived blood colonies from two neonates and 6 adults. It also contains 18 samples that were used as matched normals to call mutations in NanoSeq data (dataset EGAD00001006459).	HiSeq X Ten Illumina NovaSeq 6000	13
EGAD00001008107	A lymphocyte suffers many threats to its genome, including programmed mutation during differentiation, antigen-driven proliferation and residency in diverse microenvironments. After developing protocols for single-cell lymphocyte expansions, we sequenced whole genomes from 717 normal naive and memory B and T lymphocytes and hematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells – the extra mutations were mostly acquired during differentiation, with burdens higher in memory than naive lymphocytes, although T cells also had a higher rate of mutation accumulation throughout life. Off-target effects of immunological diversification accounted for most of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every one on-target IGV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than stem cells, with ~15% of deletions being attributable to off-target RAG activity. Mutational processes associated with ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory lymphocytes. The mutation burden and signatures of normal B lymphocytes were broadly comparable to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.	HiSeq X Ten	717

Publications	Citations
Diverse mutational landscapes in human lymphocytes. Machado HE, Mitchell E, Øbro NF, Kübler K, Davies M, Leongamornlert D, Cull A, Maura F, Sanders MA, Cagan ATJ, McDonald C, Belmonte M, Shepherd MS, Vieira Braga FA, Osborne RJ, Mahbubani K, Martincorena I, Laurenti E, Green AR, Getz G, Polak P, Saeb-Parsy K, Hodson DJ, Kent DG, Campbell PJ. Nature 608: 2022 724-732	19