Embryonic stem cells co-express Oct4 and Oct1, a related protein with similar DNA-binding specificity. To study the role of Oct1 in ESC pluripotency and transcriptional control, we constructed germline and inducible-conditional Oct1-deficient ESC lines. ESCs lacking Oct1 show normal appearance, self-renewal and growth but manifest defects upon differentiation. They fail to form beating cardiomyocytes, generate neurons poorly, form small, poorly differentiated teratomas, and cannot generate chimeric mice. Upon RA-mediated differentiation, Oct1-deficient cells induce lineage-appropriate developmentally poised genes poorly while lineage-inappropriate genes, including extra-embryonic genes, are aberrantly expressed. In ESCs, Oct1 co-occupies a specific set of targets with Oct4, but does not occupy differentially expressed developmental targets. Instead, Oct1 occupies these targets as cells differentiate and Oct4 declines. These results identify a dynamic interplay between Oct1 and Oct4, in particular during the critical window immediately after loss of pluripotency when cells make the earliest developmental fate decisions.

Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs.

Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we use seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in five disease-relevant immune cell lines, based on a set of features related to regulatory potential. Trait/disease-associated variants are enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 have at least one variant meeting one or both of these criteria, 5 of which are further supported by genetic fine-mapping. Our work provides a comprehensive strategy to characterize genetic variation at important disease-associated loci, and aids in the effort to identify trait causal genetic variants.

We introduce macromolecular crowding quantitatively into the model for kinetics of gene regulation in Escherichia coli. We analyse and compute the specific-site searching time for 180 known transcription factors (TFs) regulating 1300 operons. The time is between 160 s (e.g. for SoxS Mw = 12.91 kDa) and 1550 s (e.g. for PepA6 of Mw = 329.28 kDa). Diffusion coefficients for one-dimensional sliding are between for large proteins up to for small monomers or dimers. Three-dimensional diffusion coefficients in the cytoplasm are 2 orders of magnitude larger than 1D sliding coefficients, nevertheless the sliding enhances the binding rates of TF to specific sites by 1-2 orders of magnitude. The latter effect is due to ubiquitous non-specific binding. We compare the model to experimental data for LacI repressor and find that non-specific binding of the protein to DNA is activation- and not diffusion-limited. We show that the target location rate by LacI repressor is optimized with respect to microscopic rate constant for association to non-specific sites on DNA. We analyse the effect of oligomerization of TFs and DNA looping effects on searching kinetics. We show that optimal searching strategy depends on TF abundance.

The term "transcriptional network" refers to the mechanism(s) that underlies coordinated expression of genes, typically involving transcription factors (TFs) binding to the promoters of multiple genes, and individual genes controlled by multiple TFs. A multitude of studies in the last two decades have aimed to map and characterize transcriptional networks in the yeast Saccharomyces cerevisiae. We review the methodologies and accomplishments of these studies, as well as challenges we now face. For most yeast TFs, data have been collected on their sequence preferences, in vivo promoter occupancy, and gene expression profiles in deletion mutants. These systematic studies have led to the identification of new regulators of numerous cellular functions and shed light on the overall organization of yeast gene regulation. However, many yeast TFs appear to be inactive under standard laboratory growth conditions, and many of the available data were collected using techniques that have since been improved. Perhaps as a consequence, comprehensive and accurate mapping among TF sequence preferences, promoter binding, and gene expression remains an open challenge. We propose that the time is ripe for renewed systematic efforts toward a complete mapping of yeast transcriptional regulatory mechanisms.

Mammalian transcriptomes contain thousands of long noncoding RNAs (lncRNAs). Some lncRNAs originate from intragenic enhancers which, when active, behave as alternative promoters producing transcripts that are processed using the canonical signals of their host gene. We have followed up this observation by analyzing intergenic lncRNAs to determine the extent to which they might also originate from intergenic enhancers.

No abstract available

Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.

During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone-marrow-derived hematopoietic progenitors that migrate through the bloodstream. The current understanding of the nature of thymic immigrants is largely based on data from pre-clinical models. Here, we employed single-cell RNA sequencing (scRNA-seq) to examine the immature postnatal thymocyte population in humans. Integration of bone marrow and peripheral blood precursor datasets identified two putative thymus seeding progenitors that varied in expression of CD7; CD10; and the homing receptors CCR7, CCR9, and ITGB7. Whereas both precursors supported T cell development, only one contributed to intrathymic dendritic cell (DC) differentiation, predominantly of plasmacytoid dendritic cells. Trajectory inference delineated the transcriptional dynamics underlying early human T lineage development, enabling prediction of transcription factor (TF) modules that drive stage-specific steps of human T cell development. This comprehensive dataset defines the expression signature of immature human thymocytes and provides a resource for the further study of human thymopoiesis.

Long-term hematopoietic stem cells (LT-HSCs) maintain hematopoietic output throughout an animal's lifespan. However, with age, the balance is disrupted, and LT-HSCs produce a myeloid-biased output, resulting in poor immune responses to infectious challenge and the development of myeloid leukemias. Here, we show that young and aged LT-HSCs respond differently to inflammatory stress, such that aged LT-HSCs produce a cell-intrinsic, myeloid-biased expression program. Using single-cell RNA sequencing (scRNA-seq), we identify a myeloid-biased subset within the LT-HSC population (mLT-HSCs) that is prevalent among aged LT-HSCs. We identify CD61 as a marker of mLT-HSCs and show that CD61-high LT-HSCs are uniquely primed to respond to acute inflammatory challenge. We predict that several transcription factors regulate the mLT-HSCs gene program and show that Klf5, Ikzf1, and Stat3 play an important role in age-related inflammatory myeloid bias. We have therefore identified and isolated an LT-HSC subset that regulates myeloid versus lymphoid balance under inflammatory challenge and with age.

Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. We apply the method to reconstruct the landscape of reprogramming from 315,000 single-cell RNA sequencing (scRNA-seq) profiles, collected at half-day intervals across 18 days. The results reveal a wider range of developmental programs than previously characterized. Cells gradually adopt either a terminal stromal state or a mesenchymal-to-epithelial transition state. The latter gives rise to populations related to pluripotent, extra-embryonic, and neural cells, with each harboring multiple finer subpopulations. The analysis predicts transcription factors and paracrine signals that affect fates and experiments validate that the TF Obox6 and the cytokine GDF9 enhance reprogramming efficiency. Our approach sheds light on the process and outcome of reprogramming and provides a framework applicable to diverse temporal processes in biology.

Both intrinsic cell state changes and variations in the composition of stem cell populations have been implicated as contributors to aging. We used single-cell RNA-seq to dissect variability in hematopoietic stem cell (HSC) and hematopoietic progenitor cell populations from young and old mice from two strains. We found that cell cycle dominates the variability within each population and that there is a lower frequency of cells in the G1 phase among old compared with young long-term HSCs, suggesting that they traverse through G1 faster. Moreover, transcriptional changes in HSCs during aging are inversely related to those upon HSC differentiation, such that old short-term (ST) HSCs resemble young long-term (LT-HSCs), suggesting that they exist in a less differentiated state. Our results indicate both compositional changes and intrinsic, population-wide changes with age and are consistent with a model where a relationship between cell cycle progression and self-renewal versus differentiation of HSCs is affected by aging and may contribute to the functional decline of old HSCs.

Nucleosomes regulate many DNA-dependent processes by controlling the accessibility of DNA, and DNA sequences such as the poly-dA:dT element are known to affect nucleosome binding. We demonstrate that poly-dA:dT tracts form an asymmetric barrier to nucleosome movement in vivo, mediated by ATP-dependent chromatin remodelers. We theorize that nucleosome transit over poly-A elements is more energetically favourable in one direction, leading to an asymmetric arrangement of nucleosomes around these sequences. We demonstrate that different arrangements of poly-A and poly-T tracts result in very different outcomes for nucleosome occupancy in yeast, mouse, and human, and show that yeast takes advantage of this phenomenon in its promoter architecture.

The expression of co-inhibitory receptors, such as CTLA-4 and PD-1, on effector T cells is a key mechanism for ensuring immune homeostasis. Dysregulated expression of co-inhibitory receptors on CD4+ T cells promotes autoimmunity, whereas sustained overexpression on CD8+ T cells promotes T cell dysfunction or exhaustion, leading to impaired ability to clear chronic viral infections and diseases such as cancer1,2. Here, using RNA and protein expression profiling at single-cell resolution in mouse cells, we identify a module of co-inhibitory receptors that includes not only several known co-inhibitory receptors (PD-1, TIM-3, LAG-3 and TIGIT) but also many new surface receptors. We functionally validated two new co-inhibitory receptors, activated protein C receptor (PROCR) and podoplanin (PDPN). The module of co-inhibitory receptors is co-expressed in both CD4+ and CD8+ T cells and is part of a larger co-inhibitory gene program that is shared by non-responsive T cells in several physiological contexts and is driven by the immunoregulatory cytokine IL-27. Computational analysis identified the transcription factors PRDM1 and c-MAF as cooperative regulators of the co-inhibitory module, and this was validated experimentally. This molecular circuit underlies the co-expression of co-inhibitory receptors in T cells and identifies regulators of T cell function with the potential to control autoimmunity and tumour immunity.

Variation in chromatin organization across single cells can help shed important light on the mechanisms controlling gene expression, but scale, noise, and sparsity pose significant challenges for interpretation of single cell chromatin data. Here, we develop BROCKMAN (Brockman Representation Of Chromatin by K-mers in Mark-Associated Nucleotides), an approach to infer variation in transcription factor (TF) activity across samples through unsupervised analysis of the variation in DNA sequences associated with an epigenomic mark.