Alternative platelet differentiation pathways initiated by nonhierarchically related hematopoietic stem cells.

Rare multipotent stem cells replenish millions of blood cells per second through a time-consuming process, passing through multiple stages of increasingly lineage-restricted progenitors. Although insults to the blood-forming system highlight the need for more rapid blood replenishment from stem cells, established models of hematopoiesis implicate only one mandatory differentiation pathway for each blood cell lineage. Here, we establish a nonhierarchical relationship between distinct stem cells that replenish all blood cell lineages and stem cells that replenish almost exclusively platelets, a lineage essential for hemostasis and with important roles in both the innate and adaptive immune systems. These distinct stem cells use cellularly, molecularly and functionally separate pathways for the replenishment of molecularly distinct megakaryocyte-restricted progenitors: a slower steady-state multipotent pathway and a fast-track emergency-activated platelet-restricted pathway. These findings provide a framework for enhancing platelet replenishment in settings in which slow recovery of platelets remains a major clinical challenge.

Molecular spikes: a gold standard for single-cell RNA counting.

Single-cell sequencing methods rely on molecule-counting strategies to account for amplification biases, yet no experimental strategy to evaluate counting performance exists. Here, we introduce molecular spikes-RNA spike-ins containing built-in unique molecular identifiers (UMIs) that we use to identify critical experimental and computational conditions for accurate RNA counting in single-cell RNA-sequencing (scRNA-seq). Using molecular spikes, we uncovered impaired RNA counting in methods that were not informative for cellular RNA abundances due to inflated UMI counts. We further leverage molecular spikes to improve estimates of total endogenous RNA amounts in cells, and introduce a strategy to correct experiments with impaired RNA counting. The molecular spikes and the accompanying R package UMIcountR ( https://github.com/cziegenhain/UMIcountR ) will improve the validation of new methods, better estimate and adjust for cellular mRNA amounts and enable more indepth characterization of RNA counting in scRNA-seq.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols.

Evolutionary routes and KRAS dosage define pancreatic cancer phenotypes.

The poor correlation of mutational landscapes with phenotypes limits our understanding of the pathogenesis and metastasis of pancreatic ductal adenocarcinoma (PDAC). Here we show that oncogenic dosage-variation has a critical role in PDAC biology and phenotypic diversification. We find an increase in gene dosage of mutant KRAS in human PDAC precursors, which drives both early tumorigenesis and metastasis and thus rationalizes early PDAC dissemination. To overcome the limitations posed to gene dosage studies by the stromal richness of PDAC, we have developed large cell culture resources of metastatic mouse PDAC. Integration of cell culture genomes, transcriptomes and tumour phenotypes with functional studies and human data reveals additional widespread effects of oncogenic dosage variation on cell morphology and plasticity, histopathology and clinical outcome, with the highest KrasMUT levels underlying aggressive undifferentiated phenotypes. We also identify alternative oncogenic gains (Myc, Yap1 or Nfkb2), which collaborate with heterozygous KrasMUT in driving tumorigenesis, but have lower metastatic potential. Mechanistically, different oncogenic gains and dosages evolve along distinct evolutionary routes, licensed by defined allelic states and/or combinations of hallmark tumour suppressor alterations (Cdkn2a, Trp53, Tgfß-pathway). Thus, evolutionary constraints and contingencies direct oncogenic dosage gain and variation along defined routes to drive the early progression of PDAC and shape its downstream biology. Our study uncovers universal principles of Ras-driven oncogenesis that have potential relevance beyond pancreatic cancer.

Transcriptional bursts explain autosomal random monoallelic expression and affect allelic imbalance.

Transcriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of allelic expression resulting from transcriptional bursting and how it compared to the amount biallelic, monoallelic and allele-biased expression observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain the allelic expression patterns observed in single cells, including the frequent observations of autosomal monoallelic gene expression. Importantly, we identified that the burst frequency largely determined the fraction of cells with monoallelic expression, whereas the burst size had little effect on monoallelic observations. The high consistency between the bursting model predictions and scRNA-seq observations made it possible to assess the heterogeneity of a group of cells as their deviation in allelic observations from the expected. Finally, both burst frequency and size contributed to allelic imbalance observations and reinforced that studies of allelic imbalance can be confounded from the inherent noise in transcriptional bursting. Altogether, we demonstrate that allele-level transcriptional bursting renders widespread, although predictable, amounts of monoallelic and biallelic expression in single cells and cell populations.

Altered social behavior in mice carrying a cortical Foxp2 deletion.

Genetic disruptions of the forkhead box transcription factor FOXP2 in humans cause an autosomal-dominant speech and language disorder. While FOXP2 expression pattern are highly conserved, its role in specific brain areas for mammalian social behaviors remains largely unknown. Here we studied mice carrying a homozygous cortical Foxp2 deletion. The postnatal development and gross morphological architecture of mutant mice was indistinguishable from wildtype (WT) littermates. Unbiased behavioral profiling of adult mice revealed abnormalities in approach behavior towards conspecifics as well as in the reciprocal responses of WT interaction partners. Furthermore mutant mice showed alterations in acoustical parameters of ultrasonic vocalizations, which also differed in function of the social context. Cell type-specific gene expression profiling of cortical pyramidal neurons revealed aberrant regulation of genes involved in social behavior. In particular Foxp2 mutants showed the downregulation of Mint2 (Apba2), a gene involved in approach behavior in mice and autism spectrum disorder in humans. Taken together these data demonstrate that cortical Foxp2 is required for normal social behaviors in mice.

Micropatterning as a tool to identify regulatory triggers and kinetics of actin-mediated endothelial mechanosensing.

Developmental processes, such as angiogenesis, are associated with a constant remodeling of the actin cytoskeleton in response to different mechanical stimuli. The mechanosensitive transcription factors MRTF-A (MKL1) and YAP (also known as YAP1) are important mediators of this challenging adaptation process. However, it is as yet unknown whether both pathways respond in an identical or in a divergent manner to a given microenvironmental guidance cue. Here, we use a micropatterning approach to dissect single aspects of cellular behavior in a spatiotemporally controllable setting. Using the exemplary process of angiogenesis, we show that cell-cell contacts and adhesive surface area are shared regulatory parameters of MRTF and YAP on rigid 2D surfaces. By analyzing MRTF and YAP under laminar flow conditions and during cell migration on dumbbell-shaped microstructures, we demonstrate that they exhibit different translocation kinetics. In conclusion, our work promotes the application of micropatterning techniques as a cell biological tool to study mechanosensitive signaling in the context of angiogenesis.

GATA2/3-TFAP2A/C transcription factor network couples human pluripotent stem cell differentiation to trophectoderm with repression of pluripotency.

To elucidate the molecular basis of BMP4-induced differentiation of human pluripotent stem cells (PSCs) toward progeny with trophectoderm characteristics, we produced transcriptome, epigenome H3K4me3, H3K27me3, and CpG methylation maps of trophoblast progenitors, purified using the surface marker APA. We combined them with the temporally resolved transcriptome of the preprogenitor phase and of single APA+ cells. This revealed a circuit of bivalent TFAP2A, TFAP2C, GATA2, and GATA3 transcription factors, coined collectively the "trophectoderm four" (TEtra), which are also present in human trophectoderm in vivo. At the onset of differentiation, the TEtra factors occupy multiple sites in epigenetically inactive placental genes and in OCT4 Functional manipulation of GATA3 and TFAP2A indicated that they directly couple trophoblast-specific gene induction with suppression of pluripotency. In accordance, knocking down GATA3 in primate embryos resulted in a failure to form trophectoderm. The discovery of the TEtra circuit indicates how trophectoderm commitment is regulated in human embryogenesis.

Chivosazole A Modulates Protein-Protein Interactions of Actin.

Actin is a protein of central importance for many cellular key processes. It is regulated by local interactions with a large number of actin binding proteins (ABPs). Various compounds are known to either increase or decrease the polymerization dynamics of actin. However, no actin binding compound has been developed for clinical applications yet because of selectivity issues. We provide a crystal structure of the natural product chivosazole A (ChivoA) bound to actin and show that-in addition to inhibiting nucleation, polymerization, and severing of F-actin filaments-it selectively modulates binding of ABPs to G-actin: Although unphysiological actin dimers are induced by ChivoA, interaction with gelsolin, profilin, cofilin, and thymosin-ß4 is inhibited. Moreover, ChivoA causes transcriptional effects differing from latrunculin B, an actin binder with a different binding site. Our data show that ChivoA and related compounds could serve as scaffolds for the development of actin binding molecules selectively targeting specific actin functions.

Transcriptional effects of actin-binding compounds: the cytoplasm sets the tone.

Actin has emerged as a versatile regulator of gene transcription. Cytoplasmatic actin regulates mechanosensitive-signaling pathways such as MRTF-SRF and Hippo-YAP/TAZ. In the nucleus, both polymerized and monomeric actin directly interfere with transcription-associated molecular machineries. Natural actin-binding compounds are frequently used tools to study actin-related processes in cell biology. However, their influence on transcriptional regulation and intranuclear actin polymerization is poorly understood to date. Here, we analyze the effects of two representative actin-binding compounds, Miuraenamide A (polymerizing properties) and Latrunculin B (depolymerizing properties), on transcriptional regulation in primary cells. We find that actin stabilizing and destabilizing compounds inversely shift nuclear actin levels without a direct influence on polymerization state and intranuclear aspects of transcriptional regulation. Furthermore, we identify Miuraenamide A as a potent inducer of G-actin-dependent SRF target gene expression. In contrast, the F-actin-regulated Hippo-YAP/TAZ axis remains largely unaffected by compound-induced actin aggregation. This is due to the inability of AMOTp130 to bind to the amorphous actin aggregates resulting from treatment with miuraenamide. We conclude that actin-binding compounds predominantly regulate transcription via their influence on cytoplasmatic G-actin levels, while transcriptional processes relying on intranuclear actin polymerization or functional F-actin networks are not targeted by these compounds at tolerable doses.

powsimR: power analysis for bulk and single cell RNA-seq experiments.

SUMMARY: Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses. AVAILABILITY AND IMPLEMENTATION: The R package and associated tutorial are freely available at https://github.com/bvieth/powsimR. CONTACT: vieth@bio.lmu.de or hellmann@bio.lmu.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tissue-specific RNA Polymerase II promoter-proximal pause release and burst kinetics in a Drosophila embryonic patterning network.

BACKGROUND: Formation of tissue-specific transcriptional programs underlies multicellular development, including dorsoventral (DV) patterning of the Drosophila embryo. This involves interactions between transcriptional enhancers and promoters in a chromatin context, but how the chromatin landscape influences transcription is not fully understood. RESULTS: Here we comprehensively resolve differential transcriptional and chromatin states during Drosophila DV patterning. We find that RNA Polymerase II pausing is established at DV promoters prior to zygotic genome activation (ZGA), that pausing persists irrespective of cell fate, but that release into productive elongation is tightly regulated and accompanied by tissue-specific P-TEFb recruitment. DV enhancers acquire distinct tissue-specific chromatin states through CBP-mediated histone acetylation that predict the transcriptional output of target genes, whereas promoter states are more tissue-invariant. Transcriptome-wide inference of burst kinetics in different cell types revealed that while DV genes are generally characterized by a high burst size, either burst size or frequency can differ between tissues. CONCLUSIONS: The data suggest that pausing is established by pioneer transcription factors prior to ZGA and that release from pausing is imparted by enhancer chromatin state to regulate bursting in a tissue-specific manner in the early embryo. Our results uncover how developmental patterning is orchestrated by tissue-specific bursts of transcription from Pol II primed promoters in response to enhancer regulatory cues.

Clonally heritable gene expression imparts a layer of diversity within cell types.

Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high-coverage single-cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation, which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging, and disease. A record of this paper's transparent peer review process is included in the supplemental information.

Erythroid Differentiation Enhances RNA Mis-Splicing in SF3B1-Mutant Myelodysplastic Syndromes with Ring Sideroblasts.

Myelodysplastic syndromes with ring sideroblasts (MDS-RS) commonly develop from hematopoietic stem cells (HSC) bearing mutations in the splicing factor SF3B1 (SF3B1mt). Direct studies into MDS-RS pathobiology have been limited by a lack of model systems that fully recapitulate erythroid biology and RS development and the inability to isolate viable human RS. Here, we combined successful direct RS isolation from patient samples, high-throughput multiomics analysis of cells encompassing the SF3B1mt stem-erythroid continuum, and functional assays to investigate the impact of SF3B1mt on erythropoiesis and RS accumulation. The isolated RS differentiated, egressed into the blood, escaped traditional nonsense-mediated decay (NMD) mechanisms, and leveraged stress-survival pathways that hinder wild-type hematopoiesis through pathogenic GDF15 overexpression. Importantly, RS constituted a contaminant of magnetically enriched CD34+ cells, skewing bulk transcriptomic data. Mis-splicing in SF3B1mt cells was intensified by erythroid differentiation through accelerated RNA splicing and decreased NMD activity, and SF3B1mt led to truncations in several MDS-implicated genes. Finally, RNA mis-splicing induced an uncoupling of RNA and protein expression, leading to critical abnormalities in proapoptotic p53 pathway genes. Overall, this characterization of erythropoiesis in SF3B1mt RS provides a resource for studying MDS-RS and uncovers insights into the unexpectedly active biology of the "dead-end" RS. SIGNIFICANCE: Ring sideroblast isolation combined with state-of-the-art multiomics identifies survival mechanisms underlying SF3B1-mutant erythropoiesis and establishes an active role for erythroid differentiation and ring sideroblasts themselves in SF3B1-mutant myelodysplastic syndrome pathogenesis.

Compound models and Pearson residuals for normalization of single-cell RNA-seq data without UMIs.

Before downstream analysis can reveal biological signals in single-cell RNA sequencing data, normalization and variance stabilization are required to remove technical noise. Recently, Pearson residuals based on negative binomial models have been suggested as an efficient normalization approach. These methods were developed for UMI-based sequencing protocols, where unique molecular identifiers (UMIs) help to remove PCR amplification noise by keeping track of the original molecules. In contrast, full-length protocols such as Smart-seq2 lack UMIs and retain amplification noise, making negative binomial models inapplicable. Here, we extend Pearson residuals to such read count data by modeling them as a compound process: we assume that the captured RNA molecules follow the negative binomial distribution, but are replicated according to an amplification distribution. Based on this model, we introduce compound Pearson residuals and show that they can be analytically obtained without explicit knowledge of the amplification distribution. Further, we demonstrate that compound Pearson residuals lead to a biologically meaningful gene selection and low-dimensional embeddings of complex Smart-seq2 datasets. Finally, we empirically study amplification distributions across several sequencing protocols, and suggest that they can be described by a broken power law. We show that the resulting compound distribution captures overdispersion and zero-inflation patterns characteristic of read count data. In summary, compound Pearson residuals provide an efficient and effective way to normalize read count data based on simple mechanistic assumptions.

Spatial and single-cell profiling of the metabolome, transcriptome and epigenome of the aging mouse liver.

Tissues within an organism and even cell types within a tissue can age with different velocities. However, it is unclear whether cells of one type experience different aging trajectories within a tissue depending on their spatial location. Here, we used spatial transcriptomics in combination with single-cell ATAC-seq and RNA-seq, lipidomics and functional assays to address how cells in the male murine liver are affected by age-related changes in the microenvironment. Integration of the datasets revealed zonation-specific and age-related changes in metabolic states, the epigenome and transcriptome. The epigenome changed in a zonation-dependent manner and functionally, periportal hepatocytes were characterized by decreased mitochondrial fitness, whereas pericentral hepatocytes accumulated large lipid droplets. Together, we provide evidence that changing microenvironments within a tissue exert strong influences on their resident cells that can shape epigenetic, metabolic and phenotypic outputs.

Scalable single-cell RNA sequencing from full transcripts with Smart-seq3xpress.

Current single-cell RNA sequencing (scRNA-seq) methods with high cellular throughputs sacrifice full-transcript coverage and often sensitivity. Here we describe Smart-seq3xpress, which miniaturizes and streamlines the Smart-seq3 protocol to substantially reduce reagent use and increase cellular throughput. Smart-seq3xpress analysis of peripheral blood mononuclear cells resulted in a granular atlas complete with common and rare cell types. Compared with droplet-based single-cell RNA sequencing that sequences RNA ends, the additional full-transcript coverage revealed cell-type-associated isoform variation.

Transcriptional kinetics and molecular functions of long noncoding RNAs.

An increasing number of long noncoding RNAs (lncRNAs) have experimentally confirmed functions, yet little is known about their transcriptional dynamics and it is challenging to determine their regulatory effects. Here, we used allele-sensitive single-cell RNA sequencing to demonstrate that, compared to messenger RNAs, lncRNAs have twice as long duration between two transcriptional bursts. Additionally, we observed increased cell-to-cell variability in lncRNA expression due to lower frequency bursting producing larger numbers of RNA molecules. Exploiting heterogeneity in asynchronously growing cells, we identified and experimentally validated lncRNAs with cell state-specific functions involved in cell cycle progression and apoptosis. Finally, we identified cis-functioning lncRNAs and showed that knockdown of these lncRNAs modulated the nearby protein-coding gene's transcriptional burst frequency or size. In summary, we identified distinct transcriptional regulation of lncRNAs and demonstrated a role for lncRNAs in the regulation of mRNA transcriptional bursting.

Prime-seq, efficient and powerful bulk RNA sequencing.

Cost-efficient library generation by early barcoding has been central in propelling single-cell RNA sequencing. Here, we optimize and validate prime-seq, an early barcoding bulk RNA-seq method. We show that it performs equivalently to TruSeq, a standard bulk RNA-seq method, but is fourfold more cost-efficient due to almost 50-fold cheaper library costs. We also validate a direct RNA isolation step, show that intronic reads are derived from RNA, and compare cost-efficiencies of available protocols. We conclude that prime-seq is currently one of the best options to set up an early barcoding bulk RNA-seq protocol from which many labs would profit.

Ly6D+Siglec-H+ precursors contribute to conventional dendritic cells via a Zbtb46+Ly6D+ intermediary stage.

Plasmacytoid and conventional dendritic cells (pDC and cDC) are generated from progenitor cells in the bone marrow and commitment to pDCs or cDC subtypes may occur in earlier and later progenitor stages. Cells within the CD11c+MHCII-/loSiglec-H+CCR9lo DC precursor fraction of the mouse bone marrow generate both pDCs and cDCs. Here we investigate the heterogeneity and commitment of subsets in this compartment by single-cell transcriptomics and high-dimensional flow cytometry combined with cell fate analysis: Within the CD11c+MHCII-/loSiglec-H+CCR9lo DC precursor pool cells expressing high levels of Ly6D and lacking expression of transcription factor Zbtb46 contain CCR9loB220hi immediate pDC precursors and CCR9loB220lo (lo-lo) cells which still generate pDCs and cDCs in vitro and in vivo under steady state conditions. cDC-primed cells within the Ly6DhiZbtb46- lo-lo precursors rapidly upregulate Zbtb46 and pass through a Zbtb46+Ly6D+ intermediate stage before acquiring cDC phenotype after cell division. Type I IFN stimulation limits cDC and promotes pDC output from this precursor fraction by arresting cDC-primed cells in the Zbtb46+Ly6D+ stage preventing their expansion and differentiation into cDCs. Modulation of pDC versus cDC output from precursors by external factors may allow for adaptation of DC subset composition at later differentiation stages.