Single-cell atlas reveals meningeal leukocyte heterogeneity in the developing mouse brain.

The meninges are important for brain development and pathology. Using single-cell RNA sequencing, we have generated the first comprehensive transcriptional atlas of neonatal mouse meningeal leukocytes under normal conditions and after perinatal brain injury. We identified almost all known leukocyte subtypes and found differences between neonatal and adult border-associated macrophages, thus highlighting that neonatal border-associated macrophages are functionally immature with regards to immune responses compared with their adult counterparts. We also identified novel meningeal microglia-like cell populations that may participate in white matter development. Early after the hypoxic-ischemic insult, neutrophil numbers increased and they exhibited increased granulopoiesis, suggesting that the meninges are an important site of immune cell expansion with implications for the initiation of inflammatory cascades after neonatal brain injury. Our study provides a single-cell resolution view of the importance of meningeal leukocytes at the early stage of development in health and disease.

MutationalPatterns: the one stop shop for the analysis of mutational processes.

BACKGROUND: The collective of somatic mutations in a genome represents a record of mutational processes that have been operative in a cell. These processes can be investigated by extracting relevant mutational patterns from sequencing data. RESULTS: Here, we present the next version of MutationalPatterns, an R/Bioconductor package, which allows in-depth mutational analysis of catalogues of single and double base substitutions as well as small insertions and deletions. Major features of the package include the possibility to perform regional mutation spectra analyses and the possibility to detect strand asymmetry phenomena, such as lesion segregation. On top of this, the package also contains functions to determine how likely it is that a signature can cause damaging mutations (i.e., mutations that affect protein function). This updated package supports stricter signature refitting on known signatures in order to prevent overfitting. Using simulated mutation matrices containing varied signature contributions, we showed that reliable refitting can be achieved even when only 50 mutations are present per signature. Additionally, we incorporated bootstrapped signature refitting to assess the robustness of the signature analyses. Finally, we applied the package on genome mutation data of cell lines in which we deleted specific DNA repair processes and on large cancer datasets, to show how the package can be used to generate novel biological insights. CONCLUSIONS: This novel version of MutationalPatterns allows for more comprehensive analyses and visualization of mutational patterns in order to study the underlying processes. Ultimately, in-depth mutational analyses may contribute to improved biological insights in mechanisms of mutation accumulation as well as aid cancer diagnostics. MutationalPatterns is freely available at http://bioconductor.org/packages/MutationalPatterns .

CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing.

Cell type identification is essential for single-cell RNA sequencing (scRNA-seq) studies, currently transforming the life sciences. CHETAH (CHaracterization of cEll Types Aided by Hierarchical classification) is an accurate cell type identification algorithm that is rapid and selective, including the possibility of intermediate or unassigned categories. Evidence for assignment is based on a classification tree of previously available scRNA-seq reference data and includes a confidence score based on the variance in gene expression per cell type. For cell types represented in the reference data, CHETAH's accuracy is as good as existing methods. Its specificity is superior when cells of an unknown type are encountered, such as malignant cells in tumor samples which it pinpoints as intermediate or unassigned. Although designed for tumor samples in particular, the use of unassigned and intermediate types is also valuable in other exploratory studies. This is exemplified in pancreas datasets where CHETAH highlights cell populations not well represented in the reference dataset, including cells with profiles that lie on a continuum between that of acinar and ductal cell types. Having the possibility of unassigned and intermediate cell types is pivotal for preventing misclassification and can yield important biological information for previously unexplored tissues.

Whole-genome sequencing and mutational analysis of human cord-blood derived stem and progenitor cells.

Mutational signatures have been identified in cancer genomes, providing information about the causes of cancer and treatment vulnerabilities. This protocol describes an assay to determine the genotoxic mechanisms underlying these signatures using cord-blood derived hematopoietic stem and progenitor cells (CB-HSPCs). CB-HSPCs have a low mutation background, enabling sensitive detection of mutations. First, CB-HSPCs are exposed in vitro, sorted, and clonally expanded. This expansion enables whole-genome sequencing to detect the mutation load and respective patterns induced during genotoxic exposure. For complete details on the use and execution of this protocol, please refer to de Kanter et al. (2021).

Elevated Mutational Age in Blood of Children Treated for Cancer Contributes to Therapy-Related Myeloid Neoplasms.

Childhood cancer survivors are confronted with various chronic health conditions like therapy-related malignancies. However, it is unclear how exposure to chemotherapy contributes to the mutation burden and clonal composition of healthy tissues early in life. Here, we studied mutation accumulation in hematopoietic stem and progenitor cells (HSPC) before and after cancer treatment of 24 children. Of these children, 19 developed therapy-related myeloid neoplasms (t-MN). Posttreatment HSPCs had an average mutation burden increase comparable to what treatment-naïve cells accumulate during 16 years of life, with excesses up to 80 years. In most children, these additional mutations were induced by clock-like processes, which are also active during healthy aging. Other patients harbored mutations that could be directly attributed to treatments like platinum-based drugs and thiopurines. Using phylogenetic inference, we demonstrate that most t-MN in children originate after the start of treatment and that leukemic clones become dominant during or directly after chemotherapy exposure. SIGNIFICANCE: Our study shows that chemotherapy increases the mutation burden of normal blood cells in cancer survivors. Only few drugs damage the DNA directly, whereas in most patients, chemotherapy-induced mutations are caused by processes similar to those present during normal aging. This article is highlighted in the In This Issue feature, p. 1825.

Sister chromatid exchanges induced by perturbed replication can form independently of BRCA1, BRCA2 and RAD51.

Sister chromatid exchanges (SCEs) are products of joint DNA molecule resolution, and are considered to form through homologous recombination (HR). Indeed, SCE induction upon irradiation requires the canonical HR factors BRCA1, BRCA2 and RAD51. In contrast, replication-blocking agents, including PARP inhibitors, induce SCEs independently of BRCA1, BRCA2 and RAD51. PARP inhibitor-induced SCEs are enriched at difficult-to-replicate genomic regions, including common fragile sites (CFSs). PARP inhibitor-induced replication lesions are transmitted into mitosis, suggesting that SCEs can originate from mitotic processing of under-replicated DNA. Proteomics analysis reveals mitotic recruitment of DNA polymerase theta (POLQ) to synthetic DNA ends. POLQ inactivation results in reduced SCE numbers and severe chromosome fragmentation upon PARP inhibition in HR-deficient cells. Accordingly, analysis of CFSs in cancer genomes reveals frequent allelic deletions, flanked by signatures of POLQ-mediated repair. Combined, we show PARP inhibition generates under-replicated DNA, which is processed into SCEs during mitosis, independently of canonical HR factors.

Antiviral treatment causes a unique mutational signature in cancers of transplantation recipients.

Genetic instability is a major concern for successful application of stem cells in regenerative medicine. However, the mutational consequences of the most applied stem cell therapy in humans, hematopoietic stem cell transplantation (HSCT), remain unknown. Here we characterized the mutation burden of hematopoietic stem and progenitor cells (HSPCs) of human HSCT recipients and their donors using whole-genome sequencing. We demonstrate that the majority of transplanted HSPCs did not display altered mutation accumulation. However, in some HSCT recipients, we identified multiple HSPCs with an increased mutation burden after transplantation. This increase could be attributed to a unique mutational signature caused by the antiviral drug ganciclovir. Using a machine learning approach, we detected this signature in cancer genomes of individuals who received HSCT or solid organ transplantation earlier in life. Antiviral treatment with nucleoside analogs can cause enhanced mutagenicity in transplant recipients, which may ultimately contribute to therapy-related carcinogenesis.