A benchmark of computational pipelines for single-cell histone modification data.

BACKGROUND: Single-cell histone post translational modification (scHPTM) assays such as scCUT&Tag or scChIP-seq allow single-cell mapping of diverse epigenomic landscapes within complex tissues and are likely to unlock our understanding of various mechanisms involved in development or diseases. Running scHTPM experiments and analyzing the data produced remains challenging since few consensus guidelines currently exist regarding good practices for experimental design and data analysis pipelines. RESULTS: We perform a computational benchmark to assess the impact of experimental parameters and data analysis pipelines on the ability of the cell representation to recapitulate known biological similarities. We run more than ten thousand experiments to systematically study the impact of coverage and number of cells, of the count matrix construction method, of feature selection and normalization, and of the dimension reduction algorithm used. This allows us to identify key experimental parameters and computational choices to obtain a good representation of single-cell HPTM data. We show in particular that the count matrix construction step has a strong influence on the quality of the representation and that using fixed-size bin counts outperforms annotation-based binning. Dimension reduction methods based on latent semantic indexing outperform others, and feature selection is detrimental, while keeping only high-quality cells has little influence on the final representation as long as enough cells are analyzed. CONCLUSIONS: This benchmark provides a comprehensive study on how experimental parameters and computational choices affect the representation of single-cell HPTM data. We propose a series of recommendations regarding matrix construction, feature and cell selection, and dimensionality reduction algorithms.

Evolution of synchronous female bilateral breast cancers and response to treatment.

Synchronous bilateral breast cancer (sBBC) occurs after both breasts have been affected by the same germline genetics and environmental exposures. Little evidence exists regarding immune infiltration and response to treatment in sBBCs. Here we show that the impact of the subtype of breast cancer on levels of tumor infiltrating lymphocytes (TILs, n = 277) and on pathologic complete response (pCR) rates (n = 140) differed according to the concordant or discordant subtype of breast cancer of the contralateral tumor: luminal breast tumors with a discordant contralateral tumor had higher TIL levels and higher pCR rates than those with a concordant contralateral tumor. Tumor sequencing revealed that left and right tumors (n = 20) were independent regarding somatic mutations, copy number alterations and clonal phylogeny, whereas primary tumor and residual disease were closely related both from the somatic mutation and from the transcriptomic point of view. Our study indicates that tumor-intrinsic characteristics may have a role in the association of tumor immunity and pCR and demonstrates that the characteristics of the contralateral tumor are also associated with immune infiltration and response to treatment.

Multi-modal quantification of pathway activity with MAYA.

Signaling pathways can be activated through various cascades of genes depending on cell identity and biological context. Single-cell atlases now provide the opportunity to inspect such complexity in health and disease. Yet, existing reference tools for pathway scoring resume activity of each pathway to one unique common metric across cell types. Here, we present MAYA, a computational method that enables the automatic detection and scoring of the diverse modes of activation of biological pathways across cell populations. MAYA improves the granularity of pathway analysis by detecting subgroups of genes within reference pathways, each characteristic of a cell population and how it activates a pathway. Using multiple single-cell datasets, we demonstrate the biological relevance of identified modes of activation, the robustness of MAYA to noisy pathway lists and batch effect. MAYA can also predict cell types starting from lists of reference markers in a cluster-free manner. Finally, we show that MAYA reveals common modes of pathway activation in tumor cells across patients, opening the perspective to discover shared therapeutic vulnerabilities.

Epigenomic tumor evolution under the spotlight: the promises of single-cell approaches.

Cancer evolution was long-reduced to a genetic equation. The latest technological and subsequent conceptual advances, catalyzed by single-cell approaches, now begin to reveal the long-suspected part played by epigenomic and transcriptomic mechanisms in cancer evolution. Lie ahead numerous challenges to integrate multi-modal measurements of individual cancer cells over time and space, while aiming for better disease management and the discovery of therapeutic targets and biomarkers.

L'évolution du cancer a longtemps été réduite à une équation génétique. Les dernières avancées technologiques et conceptuelles, catalysées par les approches unicellulaires, commencent maintenant à révéler le rôle longtemps soupçonné des mécanismes épigénomiques et transcriptomiques dans l'évolution du cancer. De nombreux défis nous attendent pour intégrer les mesures multimodales des cellules cancéreuses individuelles dans le temps et l'espace, tout en visant une meilleure gestion de la maladie et la découverte de cibles thérapeutiques et de biomarqueurs.

H3K27me3 conditions chemotolerance in triple-negative breast cancer.

The persistence of cancer cells resistant to therapy remains a major clinical challenge. In triple-negative breast cancer, resistance to chemotherapy results in the highest recurrence risk among breast cancer subtypes. The drug-tolerant state seems largely defined by nongenetic features, but the underlying mechanisms are poorly understood. Here, by monitoring epigenomes, transcriptomes and lineages with single-cell resolution, we show that the repressive histone mark H3K27me3 (trimethylation of histone H3 at lysine 27) regulates cell fate at the onset of chemotherapy. We report that a persister expression program is primed with both H3K4me3 (trimethylation of histone H3 at lysine 4) and H3K27me3 in unchallenged cells, with H3K27me3 being the lock to its transcriptional activation. We further demonstrate that depleting H3K27me3 enhances the potential of cancer cells to tolerate chemotherapy. Conversely, preventing H3K27me3 demethylation simultaneously to chemotherapy inhibits the transition to a drug-tolerant state, and delays tumor recurrence in vivo. Our results highlight how chromatin landscapes shape the potential of cancer cells to respond to initial therapy.

A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression.

Retinoblastoma is the most frequent intraocular malignancy in children, originating from a maturing cone precursor in the developing retina. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using multi-omics data, we demonstrate the existence of two retinoblastoma subtypes. Subtype 1, of earlier onset, includes most of the heritable forms. It harbors few genetic alterations other than the initiating RB1 inactivation and corresponds to differentiated tumors expressing mature cone markers. By contrast, subtype 2 tumors harbor frequent recurrent genetic alterations including MYCN-amplification. They express markers of less differentiated cone together with neuronal/ganglion cell markers with marked inter- and intra-tumor heterogeneity. The cone dedifferentiation in subtype 2 is associated with stemness features including low immune and interferon response, E2F and MYC/MYCN activation and a higher propensity for metastasis. The recognition of these two subtypes, one maintaining a cone-differentiated state, and the other, more aggressive, associated with cone dedifferentiation and expression of neuronal markers, opens up important biological and clinical perspectives for retinoblastomas.

Interactive analysis of single-cell epigenomic landscapes with ChromSCape.

Chromatin modifications orchestrate the dynamic regulation of gene expression during development and in disease. Bulk approaches have characterized the wide repertoire of histone modifications across cell types, detailing their role in shaping cell identity. However, these population-based methods do not capture cell-to-cell heterogeneity of chromatin landscapes, limiting our appreciation of the role of chromatin in dynamic biological processes. Recent technological developments enable the mapping of histone marks at single-cell resolution, opening up perspectives to characterize the heterogeneity of chromatin marks in complex biological systems over time. Yet, existing tools used to analyze bulk histone modifications profiles are not fit for the low coverage and sparsity of single-cell epigenomic datasets. Here, we present ChromSCape, a user-friendly interactive Shiny/R application distributed as a Bioconductor package, that processes single-cell epigenomic data to assist the biological interpretation of chromatin landscapes within cell populations. ChromSCape analyses the distribution of repressive and active histone modifications as well as chromatin accessibility landscapes from single-cell datasets. Using ChromSCape, we deconvolve chromatin landscapes within the tumor micro-environment, identifying distinct H3K27me3 landscapes associated with cell identity and breast tumor subtype.

LifeTime and improving European healthcare through cell-based interceptive medicine.

Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.

CD44 regulates epigenetic plasticity by mediating iron endocytosis.

CD44 is a transmembrane glycoprotein linked to various biological processes reliant on epigenetic plasticity, which include development, inflammation, immune responses, wound healing and cancer progression. Although it is often referred to as a cell surface marker, the functional regulatory roles of CD44 remain elusive. Here we report the discovery that CD44 mediates the endocytosis of iron-bound hyaluronates in tumorigenic cell lines, primary cancer cells and tumours. This glycan-mediated iron endocytosis mechanism is enhanced during epithelial-mesenchymal transitions, in which iron operates as a metal catalyst to demethylate repressive histone marks that govern the expression of mesenchymal genes. CD44 itself is transcriptionally regulated by nuclear iron through a positive feedback loop, which is in contrast to the negative regulation of the transferrin receptor by excess iron. Finally, we show that epigenetic plasticity can be altered by interfering with iron homeostasis using small molecules. This study reveals an alternative iron-uptake mechanism that prevails in the mesenchymal state of cells, which illuminates a central role of iron as a rate-limiting regulator of epigenetic plasticity.

Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis.

BACKGROUND: Many computational methods have been developed recently to analyze single-cell RNA-seq (scRNA-seq) data. Several benchmark studies have compared these methods on their ability for dimensionality reduction, clustering, or differential analysis, often relying on default parameters. Yet, given the biological diversity of scRNA-seq datasets, parameter tuning might be essential for the optimal usage of methods, and determining how to tune parameters remains an unmet need. RESULTS: Here, we propose a benchmark to assess the performance of five methods, systematically varying their tunable parameters, for dimension reduction of scRNA-seq data, a common first step to many downstream applications such as cell type identification or trajectory inference. We run a total of 1.5 million experiments to assess the influence of parameter changes on the performance of each method, and propose two strategies to automatically tune parameters for methods that need it. CONCLUSIONS: We find that principal component analysis (PCA)-based methods like scran and Seurat are competitive with default parameters but do not benefit much from parameter tuning, while more complex models like ZinbWave, DCA, and scVI can reach better performance but after parameter tuning.

High-throughput single-cell ChIP-seq identifies heterogeneity of chromatin states in breast cancer.

Modulation of chromatin structure via histone modification is a major epigenetic mechanism and regulator of gene expression. However, the contribution of chromatin features to tumor heterogeneity and evolution remains unknown. Here we describe a high-throughput droplet microfluidics platform to profile chromatin landscapes of thousands of cells at single-cell resolution. Using patient-derived xenograft models of acquired resistance to chemotherapy and targeted therapy in breast cancer, we found that a subset of cells within untreated drug-sensitive tumors share a common chromatin signature with resistant cells, undetectable using bulk approaches. These cells, and cells from the resistant tumors, have lost chromatin marks-H3K27me3, which is associated with stable transcriptional repression-for genes known to promote resistance to treatment. This single-cell chromatin immunoprecipitation followed by sequencing approach paves the way to study the role of chromatin heterogeneity, not just in cancer but in other diseases and healthy systems, notably during cellular differentiation and development.

Parallel derivation of isogenic human primed and naive induced pluripotent stem cells.

Induced pluripotent stem cells (iPSCs) have considerably impacted human developmental biology and regenerative medicine, notably because they circumvent the use of cells of embryonic origin and offer the potential to generate patient-specific pluripotent stem cells. However, conventional reprogramming protocols produce developmentally advanced, or primed, human iPSCs (hiPSCs), restricting their use to post-implantation human development modeling. Hence, there is a need for hiPSCs resembling preimplantation naive epiblast. Here, we develop a method to generate naive hiPSCs directly from somatic cells, using OKMS overexpression and specific culture conditions, further enabling parallel generation of their isogenic primed counterparts. We benchmark naive hiPSCs against human preimplantation epiblast and reveal remarkable concordance in their transcriptome, dependency on mitochondrial respiration and X-chromosome status. Collectively, our results are essential for the understanding of pluripotency regulation throughout preimplantation development and generate new opportunities for disease modeling and regenerative medicine.

The Smurf transition: new insights on ageing from end-of-life studies in animal models.

PURPOSE OF REVIEW: Over the past 5 years, many articles were published concerning the prediction of high risk of mortality in apparently healthy adults, echoing the first description in 2011 of the Smurf phenotype, a harbinger of natural death in drosophila. RECENT FINDINGS: These recent findings suggest that the end-of-life is molecularly and physiologically highly stereotyped, evolutionarily conserved and predictable. SUMMARY: Taken altogether, these results from independent teams using multiple organisms including humans draw the lines of future directions in ageing research. The ability to identify and study individuals about to die of natural causes with no apparent diseases is a game-changer in this field. In addition, the public health applications are potentially of tremendous impact in our ageing societies and raise important ethical questions.

XACT Noncoding RNA Competes with XIST in the Control of X Chromosome Activity during Human Early Development.

Sex chromosome dosage compensation is essential in most metazoans, but the developmental timing and underlying mechanisms vary significantly, even among placental mammals. Here we identify human-specific mechanisms regulating X chromosome activity in early embryonic development. Single-cell RNA sequencing and imaging revealed co-activation and accumulation of the long noncoding RNAs (lncRNAs) XACT and XIST on active X chromosomes in both early human pre-implantation embryos and naive human embryonic stem cells. In these contexts, the XIST RNA adopts an unusual, highly dispersed organization, which may explain why it does not trigger X chromosome inactivation at this stage. Functional studies in transgenic mouse cells show that XACT influences XIST accumulation in cis. Our findings therefore suggest a mechanism involving antagonistic activity of XIST and XACT in controlling X chromosome activity in early human embryos, and they highlight the contribution of rapidly evolving lncRNAs to species-specific developmental mechanisms.

Ordered chromatin changes and human X chromosome reactivation by cell fusion-mediated pluripotent reprogramming.

Erasure of epigenetic memory is required to convert somatic cells towards pluripotency. Reactivation of the inactive X chromosome (Xi) has been used to model epigenetic reprogramming in mouse, but human studies are hampered by Xi epigenetic instability and difficulties in tracking partially reprogrammed iPSCs. Here we use cell fusion to examine the earliest events in the reprogramming-induced Xi reactivation of human female fibroblasts. We show that a rapid and widespread loss of Xi-associated H3K27me3 and XIST occurs in fused cells and precedes the bi-allelic expression of selected Xi-genes by many heterokaryons (30-50%). After cell division, RNA-FISH and RNA-seq analyses confirm that Xi reactivation remains partial and that induction of human pluripotency-specific XACT transcripts is rare (1%). These data effectively separate pre- and post-mitotic events in reprogramming-induced Xi reactivation and reveal a complex hierarchy of epigenetic changes that are required to reactivate the genes on the human Xi chromosome.

Establishment of X chromosome inactivation and epigenomic features of the inactive X depend on cellular contexts.

X chromosome inactivation (XCI) is an essential epigenetic process that ensures X-linked gene dosage equilibrium between sexes in mammals. XCI is dynamically regulated during development in a manner that is intimately linked to differentiation. Numerous studies, which we review here, have explored the dynamics of X inactivation and reactivation in the context of development, differentiation and diseases, and the phenotypic and molecular link between the inactive status, and the cellular context. Here, we also assess whether XCI is a uniform mechanism in mammals by analyzing epigenetic signatures of the inactive X (Xi) in different species and cellular contexts. It appears that the timing of XCI and the epigenetic signature of the inactive X greatly vary between species. Surprisingly, even within a given species, various Xi configurations are found across cellular states. We discuss possible mechanisms underlying these variations, and how they might influence the fate of the Xi.

Single-cell Visualization of Chromosome Transcriptional Territories by RNA-paint.

We developed a FISH-based method to directly assess chromosome-wide transcriptional activity, thereby enabling the visualization of the actively transcribed fraction of a chromosome at the single-cell level. We applied this method to probe the activity of X-chromosomes and its instability in the context of human embryonic stem cells and cancer cells.