Protocol to study the inheritance and propagation of non-genetically encoded states using barcode decay lineage tracing.

Here, we present a protocol to perform barcode decay lineage tracing followed by single-cell transcriptome analysis (BdLT-Seq). We describe steps for BdLT-Seq experimental design, building barcoded episome reporters, performing episome transfection, and barcode retrieval. We then describe procedures for sequencing library construction while providing options for sample multiplexing and data analysis. This BdLT-Seq technique enables the assessment of clonal evolution in a directional manner while preserving isogeneity, thus allowing the comparison of non-genetic molecular features between isogenic cell lineages. For complete details on the use and execution of this protocol, please refer to Shlyakhtina et al. (2023).1.

BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity.

Cell plasticity is a core biological process underlying a myriad of molecular and cellular events taking place throughout organismal development and evolution. It has been postulated that cellular systems thrive to balance the organization of meta-stable states underlying this phenomenon, thereby maintaining a degree of populational homeostasis compatible with an ever-changing environment and, thus, life. Notably, albeit circumstantial evidence has been gathered in favour of the latter conceptual framework, a direct observation of meta-state dynamics and the biological consequences of such a process in generating non-genetic clonal diversity and divergent phenotypic output remains largely unexplored. To fill this void, here we develop a lineage-tracing technology termed Barcode decay Lineage Tracing-Seq. BdLT-Seq is based on episome-encoded molecular identifiers that, supported by the dynamic decay of the tracing information upon cell division, ascribe directionality to a cell lineage tree whilst directly coupling non-genetic molecular features to phenotypes in comparable genomic landscapes. We show that cell transcriptome states are both inherited, and dynamically reshaped following constrained rules encoded within the cell lineage in basal growth conditions, upon oncogene activation and throughout the process of reversible resistance to therapeutic cues thus adjusting phenotypic output leading to intra-clonal non-genetic diversity.

MAT2A as Key Regulator and Therapeutic Target in MLLr Leukemogenesis.

Epigenetic dysregulation plays a pivotal role in mixed-lineage leukemia (MLL) pathogenesis, therefore serving as a suitable therapeutic target. S-adenosylmethionine (SAM) is the universal methyl donor in human cells and is synthesized by methionine adenosyltransferase 2A (MAT2A), which is deregulated in different cancer types. Here, we used our human CRISPR/Cas9-MLL-rearranged (CRISPR/Cas9-MLLr) leukemia model, faithfully mimicking MLLr patients' pathology with indefinite growth potential in vitro, to evaluate the unknown role of MAT2A. Comparable to publicly available patient data, we detected MAT2A to be significantly overexpressed in our CRISPR/Cas9-MLLr model compared to healthy controls. By using non-MLLr and MLLr cell lines and our model, we detected an MLLr-specific enhanced response to PF-9366, a new MAT2A inhibitor, and small interfering (si) RNA-mediated knockdown of MAT2A, by alteration of the proliferation, viability, differentiation, apoptosis, cell cycling, and histone methylation. Moreover, the combinational treatment of PF-9366 with chemotherapy or targeted therapies against the SAM-dependent methyltransferases, disruptor of telomeric silencing 1 like (DOT1L) and protein arginine methyltransferase 5 (PRMT5), revealed even more pronounced effects. In summary, we uncovered MAT2A as a key regulator in MLL leukemogenesis and its inhibition led to significant anti-leukemic effects. Therefore, our study paves the avenue for clinical application of PF-9366 to improve the treatment of poor prognosis MLLr leukemia.

Systematic allelic analysis defines the interplay of key pathways in X chromosome inactivation.

Xist RNA, the master regulator of X chromosome inactivation, acts in cis to induce chromosome-wide silencing. Whilst recent studies have defined candidate silencing factors, their relative contribution to repressing different genes, and their relationship with one another is poorly understood. Here we describe a systematic analysis of Xist-mediated allelic silencing in mouse embryonic stem cell-based models. Using a machine learning approach we identify distance to the Xist locus and prior gene expression levels as key determinants of silencing efficiency. We go on to show that Spen, recruited through the Xist A-repeat, plays a central role, being critical for silencing of all except a subset of weakly expressed genes. Polycomb, recruited through the Xist B/C-repeat, also plays a key role, favouring silencing of genes with pre-existing H3K27me3 chromatin. LBR and the Rbm15/m6A-methyltransferase complex make only minor contributions to gene silencing. Together our results provide a comprehensive model for Xist-mediated chromosome silencing.