Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data.

By profiling the transcriptomes of individual cells, single-cell RNA sequencing provides unparalleled resolution to study cellular heterogeneity. However, this comes at the cost of high technical noise, including cell-specific biases in capture efficiency and library generation. One strategy for removing these biases is to add a constant amount of spike-in RNA to each cell and to scale the observed expression values so that the coverage of spike-in transcripts is constant across cells. This approach has previously been criticized as its accuracy depends on the precise addition of spike-in RNA to each sample. Here, we perform mixture experiments using two different sets of spike-in RNA to quantify the variance in the amount of spike-in RNA added to each well in a plate-based protocol. We also obtain an upper bound on the variance due to differences in behavior between the two spike-in sets. We demonstrate that both factors are small contributors to the total technical variance and have only minor effects on downstream analyses, such as detection of highly variable genes and clustering. Our results suggest that scaling normalization using spike-in transcripts is reliable enough for routine use in single-cell RNA sequencing data analyses.This work was supported by Cancer Research UK (core funding to JCM, award no. A17197), the University of Cambridge and Hutchison Whampoa Limited. JCM was also supported by core funding from EMBL. LHV was supported by an EMBL Interdisciplinary Postdoctoral fellowship. Work in the G ottgens group was supported by Cancer Research UK, Bloodwise, the National Institute of Diabetes and Digestive and Kidney Diseases, the Leukemia and Lymphoma Society and core infrastructure grants from the Wellcome Trust and the Medical Research Council to the Cambridge Stem Cell Institute

Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation

Background: Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells. Results: We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing. Conclusion: The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity

Mapping Rora expression in resting and activated CD4+ T cells

The transcription factor Rora has been shown to be important for the development of ILC2 and the regulation of ILC3, macrophages and Treg cells. Here we investigate the role of Rora across CD4+ T cells in general, but with an emphasis on Th2 cells, both in vitro as well as in the context of several in vivo type 2 infection models. We dissect the function of Rora using overexpression and a CD4-conditional Rora-knockout mouse, as well as a RORA-reporter mouse. We establish the importance of Rora in CD4+ T cells for controlling lung inflammation induced by Nippostrongylus brasiliensis infection, and have measured the effect on downstream genes using RNA-seq. Using a systematic stimulation screen of CD4+ T cells, coupled with RNA-seq, we identify upstream regulators of Rora, most importantly IL-33 and CCL7. Our data suggest that Rora is a negative regulator of the immune system, possibly through several downstream pathways, and is under control of the local microenvironment

Mapping Rora expression in resting and activated CD4+ T cells.

The transcription factor Rora has been shown to be important for the development of ILC2 and the regulation of ILC3, macrophages and Treg cells. Here we investigate the role of Rora across CD4+ T cells in general, but with an emphasis on Th2 cells, both in vitro as well as in the context of several in vivo type 2 infection models. We dissect the function of Rora using overexpression and a CD4-conditional Rora-knockout mouse, as well as a RORA-reporter mouse. We establish the importance of Rora in CD4+ T cells for controlling lung inflammation induced by Nippostrongylus brasiliensis infection, and have measured the effect on downstream genes using RNA-seq. Using a systematic stimulation screen of CD4+ T cells, coupled with RNA-seq, we identify upstream regulators of Rora, most importantly IL-33 and CCL7. Our data suggest that Rora is a negative regulator of the immune system, possibly through several downstream pathways, and is under control of the local microenvironment

The yeast Cbk1 kinase regulates mRNA localization via the mRNA-binding protein Ssd1

In the absence of Cbk1 phosphorylation Ssd1-associated mRNAs are redirected from sites of polarized cell growth to stress granules and P-bodies

The yeast Batten disease orthologue Btn1 controls endosome–Golgi retrograde transport via SNARE assembly

Btn1 controls endosome–Golgi retrograde sorting by regulating SNARE phosphorylation and assembly

Erratum to: Single cell analysis of CD4+ T cell differentiation reveals three major cell states and progressive acceleration of proliferation.

Background: Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells. Results: We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing. Conclusion: The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity

Cotranslational protein assembly imposes evolutionary constraints on homomeric proteins

Cotranslational protein folding can facilitate rapid formation of functional structures. However, it might also cause premature assembly of protein complexes, if two interacting nascent chains are in close proximity. By analyzing known protein structures, we show that homomeric protein contacts are enriched towards the C-termini of polypeptide chains across diverse proteomes. We hypothesize that this is the result of evolutionary constraints for folding to occur prior to assembly. Using high-throughput imaging of protein homomers in vivo in E. coli and engineered protein constructs with N- and C-terminal oligomerization domains, we show that, indeed, proteins with C-terminal homomeric interface residues consistently assemble more efficiently than those with N-terminal interface residues. Using in vivo, in vitro and in silico experiments, we identify features that govern successful assembly of homomers, which have implications for protein design and expression optimization