GoT-Splice protocol for multi-omics profiling of gene expression, cell-surface proteins, mutational status, and RNA splicing in human cells.

Studying RNA splicing factor mutations is challenging due to difficulties in distinguishing wild-type and mutant cells within complex human tissues and inaccuracies associated with reconstructing splicing signals from short-read sequencing data. Here, we present Genotyping of Transcriptomes (GoT)-Splice, a protocol that overcomes these limitations by combining GoT with enhanced long-read single-cell transcriptome and cell-surface proteomics profiling. We describe steps for long-read library preparation and analysis, followed by cDNA re-amplification, enrichment of mutation of interest, sample indexing, and GoT library preparation. For complete details on the use and execution of this protocol, please refer to Cortés-López et al.1.

Metformin reduces the clonal fitness of Dnmt3aR878H hematopoietic stem and progenitor cells by reversing their aberrant metabolic and epigenetic state.

Clonal hematopoiesis (CH) arises when a hematopoietic stem cell (HSC) acquires a mutation that confers a competitive advantage over wild-type (WT) HSCs, resulting in its clonal expansion. Individuals with CH are at an increased risk of developing hematologic neoplasms and a range of age-related inflammatory illnesses1-3. Therapeutic interventions that suppress the expansion of mutant HSCs have the potential to prevent these CH-related illnesses; however, such interventions have not yet been identified. The most common CH driver mutations are in the DNA methyltransferase 3 alpha (DNMT3A) gene with arginine 882 (R882) being a mutation hotspot. Here we show that murine hematopoietic stem and progenitor cells (HSPCs) carrying the Dnmt3aR878H/+ mutation, which is equivalent to human DNMT3AR882H/+, have increased mitochondrial respiration compared with WT cells and are dependent on this metabolic reprogramming for their competitive advantage. Importantly, treatment with metformin, an oral anti-diabetic drug with inhibitory activity against complex I in the electron transport chain (ETC), reduced the fitness of Dnmt3aR878H/+ HSCs. Through a multi-omics approach, we discovered that metformin acts by enhancing the methylation potential in Dnmt3aR878H/+ HSPCs and reversing their aberrant DNA CpG methylation and histone H3K27 trimethylation (H3K27me3) profiles. Metformin also reduced the fitness of human DNMT3AR882H HSPCs generated by prime editing. Our findings provide preclinical rationale for investigating metformin as a preventive intervention against illnesses associated with DNMT3AR882 mutation-driven CH in humans.

Decoding Cancer Evolution: Integrating Genetic and Non-Genetic Insights.

The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution.

Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths.

RNA splicing factors are recurrently mutated in clonal blood disorders, but the impact of dysregulated splicing in hematopoiesis remains unclear. To overcome technical limitations, we integrated genotyping of transcriptomes (GoT) with long-read single-cell transcriptomics and proteogenomics for single-cell profiling of transcriptomes, surface proteins, somatic mutations, and RNA splicing (GoT-Splice). We applied GoT-Splice to hematopoietic progenitors from myelodysplastic syndrome (MDS) patients with mutations in the core splicing factor SF3B1. SF3B1mut cells were enriched in the megakaryocytic-erythroid lineage, with expansion of SF3B1mut erythroid progenitor cells. We uncovered distinct cryptic 3' splice site usage in different progenitor populations and stage-specific aberrant splicing during erythroid differentiation. Profiling SF3B1-mutated clonal hematopoiesis samples revealed that erythroid bias and cell-type-specific cryptic 3' splice site usage in SF3B1mut cells precede overt MDS. Collectively, GoT-Splice defines the cell-type-specific impact of somatic mutations on RNA splicing, from early clonal outgrowths to overt neoplasia, directly in human samples.

Single-cell multi-omics of human clonal hematopoiesis reveals that DNMT3A R882 mutations perturb early progenitor states through selective hypomethylation.

Somatic mutations in cancer genes have been detected in clonal expansions across healthy human tissue, including in clonal hematopoiesis. However, because mutated and wild-type cells are admixed, we have limited ability to link genotypes with phenotypes. To overcome this limitation, we leveraged multi-modality single-cell sequencing, capturing genotype, transcriptomes and methylomes in progenitors from individuals with DNMT3A R882 mutated clonal hematopoiesis. DNMT3A mutations result in myeloid over lymphoid bias, and an expansion of immature myeloid progenitors primed toward megakaryocytic-erythroid fate, with dysregulated expression of lineage and leukemia stem cell markers. Mutated DNMT3A leads to preferential hypomethylation of polycomb repressive complex 2 targets and a specific CpG flanking motif. Notably, the hypomethylation motif is enriched in binding motifs of key hematopoietic transcription factors, serving as a potential mechanistic link between DNMT3A mutations and aberrant transcriptional phenotypes. Thus, single-cell multi-omics paves the road to defining the downstream consequences of mutations that drive clonal mosaicism.

Single cell biology-a Keystone Symposia report.

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.

Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states.

Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.

Smart-RRBS for single-cell methylome and transcriptome analysis.

The integration of DNA methylation and transcriptional state within single cells is of broad interest. Several single-cell dual- and multi-omics approaches have been reported that enable further investigation into cellular heterogeneity, including the discovery and in-depth study of rare cell populations. Such analyses will continue to provide important mechanistic insights into the regulatory consequences of epigenetic modifications. We recently reported a new method for profiling the DNA methylome and transcriptome from the same single cells in a cancer research study. Here, we present details of the protocol and provide guidance on its utility. Our Smart-RRBS (reduced representation bisulfite sequencing) protocol combines Smart-seq2 and RRBS and entails physically separating mRNA from the genomic DNA. It generates paired epigenetic promoter and RNA-expression measurements for ~24% of protein-coding genes in a typical single cell. It also works for micro-dissected tissue samples comprising hundreds of cells. The protocol, excluding flow sorting of cells and sequencing, takes ~3 d to process up to 192 samples manually. It requires basic molecular biology expertise and laboratory equipment, including a PCR workstation with UV sterilization, a DNA fluorometer and a microfluidic electrophoresis system.

Pre-introduction introgression contributes to parallel differentiation and contrasting hybridization outcomes between invasive and native marine mussels.

Non-native species experience novel selection pressures in introduced environments and may interbreed with native lineages. Species introductions therefore provide opportunities to investigate repeated patterns of adaptation and introgression across replicated contact zones. Here, we investigate genetic parallelism between multiple introduced populations of the invasive marine mussel, Mytilus galloprovincialis, in the absence (South Africa and California) and presence of hybridization with a native congener (Mytilus planulatus in Batemans Bay and Sydney Harbour, Australia). Repeatability in post-introduction differentiation from native-range populations varied between genetically distinct Atlantic and Mediterranean lineages, with Atlantic-derived introductions displaying high differentiation (maxFST  > 0.4) and parallelism at outlier loci. Identification of long noncoding RNA transcripts (lncRNA) additionally allowed us to clarify that parallel responses are largely limited to protein-coding loci, with lncRNAs likely evolving under evolutionary constraints. Comparisons of independent hybrid zones revealed differential introgression most strongly in Batemans Bay, with an excess of M. galloprovincialis ancestry and resistance to introgression at loci differentiating parental lineages (M. planulatus and Atlantic M. galloprovincialis). Additionally, contigs putatively introgressed with divergent alleles from a closely related species, Mytilus edulis, showed stronger introgression asymmetries compared with genome-wide trends and also diverged in parallel in both Atlantic-derived introductions. These results suggest that divergent demographic histories experienced by introduced lineages, including pre-introduction introgression, influence contemporary admixture dynamics. Our findings build on previous investigations reporting contributions of historical introgression to intrinsic reproductive architectures shared between marine lineages and illustrate that interspecific introgression history can shape differentiation between colonizing populations and their hybridization with native congeners.

Deep conservation of the enhancer regulatory code in animals.

Interactions of transcription factors (TFs) with DNA regulatory sequences, known as enhancers, specify cell identity during animal development. Unlike TFs, the origin and evolution of enhancers has been difficult to trace. We drove zebrafish and mouse developmental transcription using enhancers from an evolutionarily distant marine sponge. Some of these sponge enhancers are located in highly conserved microsyntenic regions, including an Islet enhancer in the Islet-Scaper region. We found that Islet enhancers in humans and mice share a suite of TF binding motifs with sponges, and that they drive gene expression patterns similar to those of sponge and endogenous Islet enhancers in zebrafish. Our results suggest the existence of an ancient and conserved, yet flexible, genomic regulatory syntax that has been repeatedly co-opted into cell type-specific gene regulatory networks across the animal kingdom.

Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring.

In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care.

DNA methylation disruption reshapes the hematopoietic differentiation landscape.

Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A) are frequently observed in hematological malignancies1-3 and clonal hematopoiesis4,5. Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A-mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif.

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia.

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.

De Novo Plant Transcriptome Assembly and Annotation Using Illumina RNA-Seq Reads.

The ability to identify and quantify transcribed sequences from a multitude of organisms using high-throughput RNA sequencing has revolutionized our understanding of genetics and plant biology. However, a number of computational tools used in these analyses still require a reference genome sequence, something that is seldom available for non-model organisms. Computational tools employing de Bruijn graphs to reconstruct full-length transcripts from short sequence reads allow for de novo transcriptome assembly. Here we provide detailed methods for generating and annotating de novo transcriptome assembly from plant RNA-seq data.

Corrupted coordination of epigenetic modifications leads to diverging chromatin states and transcriptional heterogeneity in CLL.

Cancer evolution is fueled by epigenetic as well as genetic diversity. In chronic lymphocytic leukemia (CLL), intra-tumoral DNA methylation (DNAme) heterogeneity empowers evolution. Here, to comprehensively study the epigenetic dimension of cancer evolution, we integrate DNAme analysis with histone modification mapping and single cell analyses of RNA expression and DNAme in 22 primary CLL and 13 healthy donor B lymphocyte samples. Our data reveal corrupted coherence across different layers of the CLL epigenome. This manifests in decreased mutual information across epigenetic modifications and gene expression attributed to cell-to-cell heterogeneity. Disrupted epigenetic-transcriptional coordination in CLL is also reflected in the dysregulation of the transcriptional output as a function of the combinatorial chromatin states, including incomplete Polycomb-mediated gene silencing. Notably, we observe unexpected co-mapping of typically mutually exclusive activating and repressing histone modifications, suggestive of intra-tumoral epigenetic diversity. Thus, CLL epigenetic diversification leads to decreased coordination across layers of epigenetic information, likely reflecting an admixture of cells with diverging cellular identities.

Early metazoan cell type diversity and the evolution of multicellular gene regulation.

A hallmark of metazoan evolution is the emergence of genomic mechanisms that implement cell-type-specific functions. However, the evolution of metazoan cell types and their underlying gene regulatory programmes remains largely uncharacterized. Here, we use whole-organism single-cell RNA sequencing to map cell-type-specific transcription in Porifera (sponges), Ctenophora (comb jellies) and Placozoa species. We describe the repertoires of cell types in these non-bilaterian animals, uncovering diverse instances of previously unknown molecular signatures, such as multiple types of peptidergic cells in Placozoa. Analysis of the regulatory programmes of these cell types reveals variable levels of complexity. In placozoans and poriferans, sequence motifs in the promoters are predictive of cell-type-specific programmes. By contrast, the generation of a higher diversity of cell types in ctenophores is associated with lower specificity of promoter sequences and the existence of distal regulatory elements. Our findings demonstrate that metazoan cell types can be defined by networks of transcription factors and proximal promoters, and indicate that further genome regulatory complexity may be required for more diverse cell type repertoires.

Sex Determination in Ceratopteris richardii Is Accompanied by Transcriptome Changes That Drive Epigenetic Reprogramming of the Young Gametophyte.

The fern Ceratopteris richardii is an important model for studies of sex determination and gamete differentiation in homosporous plants. Here we use RNA-seq to de novo assemble a transcriptome and identify genes differentially expressed in young gametophytes as their sex is determined by the presence or absence of the male-inducing pheromone called antheridiogen. Of the 1,163 consensus differentially expressed genes identified, the vast majority (1,030) are up-regulated in gametophytes treated with antheridiogen. GO term enrichment analyses of these DEGs reveals that a large number of genes involved in epigenetic reprogramming of the gametophyte genome are up-regulated by the pheromone. Additional hormone response and development genes are also up-regulated by the pheromone. This C. richardii gametophyte transcriptome and gene expression dataset will prove useful for studies focusing on sex determination and differentiation in plants.

Long non-coding regulatory RNAs in sponges and insights into the origin of animal multicellularity.

How animals evolved from a single-celled ancestor over 700 million years ago is poorly understood. Recent transcriptomic and chromatin analyses in the sponge Amphimedon queenslandica, a morphologically-simple representative of one of the oldest animal phyletic lineages, have shed light on what innovations in the genome and its regulation underlie the emergence of animal multicellularity. Comparisons of the regulatory genome of this sponge with those of more complex bilaterian model species and even simpler unicellular relatives have revealed that fundamental changes in genome regulatory complexity accompanied the evolution of animal multicellularity. Here, we review and discuss the results of these recent investigations by specifically focusing on the contribution of long non-coding RNAs to the evolution of the animal regulatory genome.

Sponge Long Non-Coding RNAs Are Expressed in Specific Cell Types and Conserved Networks.

Although developmental regulation by long non-coding RNAs (lncRNAs) appears to be a widespread feature amongst animals, the origin and level of evolutionary conservation of this mode of regulation remain unclear. We have previously demonstrated that the sponge Amphimedon queenslandica-a morphologically-simple animal-developmentally expresses an array of lncRNAs in manner akin to more complex bilaterians (insects + vertebrates). Here, we first show that Amphimedon lncRNAs are expressed in specific cell types in larvae, juveniles and adults. Thus, as in bilaterians, sponge developmental regulation involves the dynamic, cell type- and context-specific regulation of specific lncRNAs. Second, by comparing gene co-expression networks between Amphimedon queenslandica and Sycon ciliatum-a distantly-related calcisponge-we identify several putative co-expression modules that appear to be shared in sponges; these network-embedded sponge lncRNAs have no discernable sequence similarity. Together, these results suggest sponge lncRNAs are developmentally regulated and operate in conserved gene regulatory networks, as appears to be the case in more complex bilaterians.

Landscape of histone modifications in a sponge reveals the origin of animal cis-regulatory complexity.

Combinatorial patterns of histone modifications regulate developmental and cell type-specific gene expression and underpin animal complexity, but it is unclear when this regulatory system evolved. By analysing histone modifications in a morphologically-simple, early branching animal, the sponge Amphimedonqueenslandica, we show that the regulatory landscape used by complex bilaterians was already in place at the dawn of animal multicellularity. This includes distal enhancers, repressive chromatin and transcriptional units marked by H3K4me3 that vary with levels of developmental regulation. Strikingly, Amphimedon enhancers are enriched in metazoan-specific microsyntenic units, suggesting that their genomic location is extremely ancient and likely to place constraints on the evolution of surrounding genes. These results suggest that the regulatory foundation for spatiotemporal gene expression evolved prior to the divergence of sponges and eumetazoans, and was necessary for the evolution of animal multicellularity.