Aleksandra A. Kolodziejczyk

Accounting for technical noise in single-cell RNA-seq experiments

Single-cell RNA-seq can yield valuable insights about the variability within a population of seemingly homogeneous cells. We developed a quantitative statistical method to distinguish true biological variability from the high levels of technical noise in single-cell experiments. Our approach quantifies the statistical significance of observed cell-to-cell variability in expression strength on a gene-by-gene basis. We validate our approach using two independent data sets from Arabidopsis thaliana and Mus musculus.

The technology and biology of single-cell RNA sequencing.

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications.

Single Cell RNA-Sequencing of Pluripotent States Unlocks Modular Transcriptional Variation

Summary Embryonic stem cell (ESC) culture conditions are important for maintaining long-term self-renewal, and they influence cellular pluripotency state. Here, we report single cell RNA-sequencing of mESCs cultured in three different conditions: serum, 2i, and the alternative ground state a2i. We find that the cellular transcriptomes of cells grown in these conditions are distinct, with 2i being the most similar to blastocyst cells and including a subpopulation resembling the two-cell embryo state. Overall levels of intercellular gene expression heterogeneity are comparable across the three conditions. However, this masks variable expression of pluripotency genes in serum cells and homogeneous expression in 2i and a2i cells. Additionally, genes related to the cell cycle are more variably expressed in the 2i and a2i conditions. Mining of our dataset for correlations in gene expression allowed us to identify additional components of the pluripotency network, including Ptma and Zfp640, illustrating its value as a resource for future discovery.

Single-Cell RNA Sequencing Reveals T Helper Cells Synthesizing Steroids De Novo to Contribute to Immune Homeostasis

Summary T helper 2 (Th2) cells regulate helminth infections, allergic disorders, tumor immunity, and pregnancy by secreting various cytokines. It is likely that there are undiscovered Th2 signaling molecules. Although steroids are known to be immunoregulators, de novo steroid production from immune cells has not been previously characterized. Here, we demonstrate production of the steroid pregnenolone by Th2 cells in vitro and in vivo in a helminth infection model. Single-cell RNA sequencing and quantitative PCR analysis suggest that pregnenolone synthesis in Th2 cells is related to immunosuppression. In support of this, we show that pregnenolone inhibits Th cell proliferation and B cell immunoglobulin class switching. We also show that steroidogenic Th2 cells inhibit Th cell proliferation in a Cyp11a1 enzyme-dependent manner. We propose pregnenolone as a “lymphosteroid,” a steroid produced by lymphocytes. We speculate that this de novo steroid production may be an intrinsic phenomenon of Th2-mediated immune responses to actively restore immune homeostasis.

Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression

Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to facilitate such analyses, separating biological variability from the high level of technical noise that affects scRNA-seq protocols is vital. Here we describe and validate a generative statistical model that accurately quantifies technical noise with the help of external RNA spike-ins. Applying our approach to investigate stochastic allele-specific expression in individual cells, we demonstrate that a large fraction of stochastic allele-specific expression can be explained by technical noise, especially for lowly and moderately expressed genes: we predict that only 17.8% of stochastic allele-specific expression patterns are attributable to biological noise with the remainder due to technical noise.

Single-cell transcriptomic reconstruction reveals cell cycle and multi-lineage differentiation defects in Bcl11a-deficient hematopoietic stem cells

BackgroundHematopoietic stem cells (HSCs) are a rare cell type with the ability of long-term self-renewal and multipotency to reconstitute all blood lineages. HSCs are typically purified from the bone marrow using cell surface markers. Recent studies have identified significant cellular heterogeneities in the HSC compartment with subsets of HSCs displaying lineage bias. We previously discovered that the transcription factor Bcl11a has critical functions in the lymphoid development of the HSC compartment.ResultsIn this report, we employ single-cell transcriptomic analysis to dissect the molecular heterogeneities in HSCs. We profile the transcriptomes of 180 highly purified HSCs (Bcl11a+/+ and Bcl11a−/−). Detailed analysis of the RNA-seq data identifies cell cycle activity as the major source of transcriptomic variation in the HSC compartment, which allows reconstruction of HSC cell cycle progression in silico. Single-cell RNA-seq profiling of Bcl11a−/− HSCs reveals abnormal proliferative phenotypes. Analysis of lineage gene expression suggests that the Bcl11a−/− HSCs are constituted of two distinct myeloerythroid-restricted subpopulations. Remarkably, similar myeloid-restricted cells could also be detected in the wild-type HSC compartment, suggesting selective elimination of lymphoid-competent HSCs after Bcl11a deletion. These defects are experimentally validated in serial transplantation experiments where Bcl11a−/− HSCs are myeloerythroid-restricted and defective in self-renewal.ConclusionsOur study demonstrates the power of single-cell transcriptomics in dissecting cellular process and lineage heterogeneities in stem cell compartments, and further reveals the molecular and cellular defects in the Bcl11a-deficient HSC compartment.

Aging increases cell-to-cell transcriptional variability upon immune stimulation

Single-cell sequencing of mouse immune cells reveals how aging destabilizes a conserved transcriptional activation program. Aging and variability among immune cells How and why the immune system becomes less effective with age are not well understood. Martinez-Jimenez et al. performed single-cell sequencing of CD4+ T cells in old and young mice of two species. In young mice, the gene expression program of early immune activation was tightly regulated and conserved between species. However, as mice aged, the expression of genes involved in pathways responding to immune cell stimulation was not as robust and exhibited increased cell-to-cell variability. Science, this issue p. 1433 Aging is characterized by progressive loss of physiological and cellular functions, but the molecular basis of this decline remains unclear. We explored how aging affects transcriptional dynamics using single-cell RNA sequencing of unstimulated and stimulated naïve and effector memory CD4+ T cells from young and old mice from two divergent species. In young animals, immunological activation drives a conserved transcriptomic switch, resulting in tightly controlled gene expression characterized by a strong up-regulation of a core activation program, coupled with a decrease in cell-to-cell variability. Aging perturbed the activation of this core program and increased expression heterogeneity across populations of cells in both species. These discoveries suggest that increased cell-to-cell transcriptional variability will be a hallmark feature of aging across most, if not all, mammalian tissues.

Establishment of mouse expanded potential stem cells

Mouse embryonic stem cells derived from the epiblast contribute to the somatic lineages and the germline but are excluded from the extra-embryonic tissues that are derived from the trophectoderm and the primitive endoderm upon reintroduction to the blastocyst. Here we report that cultures of expanded potential stem cells can be established from individual eight-cell blastomeres, and by direct conversion of mouse embryonic stem cells and induced pluripotent stem cells. Remarkably, a single expanded potential stem cell can contribute both to the embryo proper and to the trophectoderm lineages in a chimaera assay. Bona fide trophoblast stem cell lines and extra-embryonic endoderm stem cells can be directly derived from expanded potential stem cells in vitro. Molecular analyses of the epigenome and single-cell transcriptome reveal enrichment for blastomere-specific signature and a dynamic DNA methylome in expanded potential stem cells. The generation of mouse expanded potential stem cells highlights the feasibility of establishing expanded potential stem cells for other mammalian species.

Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression

Polycomb repressive complexes (PRCs) are important histone modifiers, which silence gene expression; yet, there exists a subset of PRC-bound genes actively transcribed by RNA polymerase II (RNAPII). It is likely that the role of Polycomb repressive complex is to dampen expression of these PRC-active genes. However, it is unclear how this flipping between chromatin states alters the kinetics of transcription. Here, we integrate histone modifications and RNAPII states derived from bulk ChIP-seq data with single-cell RNA-sequencing data. We find that Polycomb repressive complex-active genes have greater cell-to-cell variation in expression than active genes, and these results are validated by knockout experiments. We also show that PRC-active genes are clustered on chromosomes in both two and three dimensions, and interactions with active enhancers promote a stabilization of gene expression noise. These findings provide new insights into how chromatin regulation modulates stochastic gene expression and transcriptional bursting, with implications for regulation of pluripotency and development.Polycomb repressive complexes modify histones but it is unclear how changes in chromatin states alter kinetics of transcription. Here, the authors use single-cell RNAseq and ChIPseq to find that actively transcribed genes with Polycomb marks have greater cell-to-cell variation in expression.

Single cell transcriptomics of pluripotent stem cells: reprogramming and differentiation.

Single-cell transcriptomics serves as a powerful tool to identify cell states within populations of cells, and to dissect underlying heterogeneity at high resolution. Single-cell transcriptomics on pluripotent stem cells has provided new insights into cellular variation, subpopulation structures and the interplay of cell cycle with pluripotency. The single-cell perspective has helped to better understand gene regulation and regulatory networks during exit from pluripotency, cell-fate determination as well as molecular mechanisms driving cellular reprogramming of somatic cells to induced pluripotent stage. Here we review the recent progress and significant findings from application of single-cell technologies on pluripotent stem cells along with a brief outlook on new combinatorial single-cell approaches that further unravel pluripotent stem cell states.