Prolonged persistence of mutagenic DNA lesions in somatic cells.

DNA is subject to continual damage, leaving each cell with thousands of individual DNA lesions at any given moment. The efficiency of DNA repair means that most known classes of lesion have a half-life of minutes to hours, but the extent to which DNA damage can persist for longer durations remains unknown. Here, using high-resolution phylogenetic trees from 89 donors, we identified mutations arising from 818 DNA lesions that persisted across multiple cell cycles in normal human stem cells from blood, liver and bronchial epithelium.

Single-cell multi-omics map of human fetal blood in Down syndrome.

Down syndrome predisposes individuals to haematological abnormalities, such as increased number of erythrocytes and leukaemia in a process that is initiated before birth and is not entirely understood. Here, to understand dysregulated haematopoiesis in Down syndrome, we integrated single-cell transcriptomics of over 1.1 million cells with chromatin accessibility and spatial transcriptomics datasets using human fetal liver and bone marrow samples from 3 fetuses with disomy and 15 fetuses with trisomy.

Single-cell and spatial transcriptomics analysis of non-small cell lung cancer.

Lung cancer is the second most frequently diagnosed cancer and the leading cause of cancer-related mortality worldwide. Tumour ecosystems feature diverse immune cell types. Myeloid cells, in particular, are prevalent and have a well-established role in promoting the disease.

Exploiting somatic mutations to decipher human blood production: a natural lineage-tracing strategy.

Lineage tracing using fluorescent proteins, genetic barcodes, and various other strategies has provided critical insights into the dynamics of both fetal and adult hematopoiesis in model organisms. However, these technologies cannot be readily used to study hematopoiesis in human beings. Therefore, there is a critical need to develop strategies to assess cellular dynamics within human hematopoietic tissues in vivo.

SMaSH: a scalable, general marker gene identification framework for single-cell RNA-sequencing.

Background: Single-cell RNA-sequencing is revolutionising the study of cellular and tissue-wide heterogeneity in a large number of biological scenarios, from highly tissue-specific studies of disease to human-wide cell atlases. A central task in single-cell RNA-sequencing analysis design is the calculation of cell type-specific genes in order to study the differential impact of different replicates (e.g.