Biology subjects

Sandberg, R.

Publications and source records attributed to Sandberg, R..

31 records · Page 2Linked to original sources

bioRxiv2019

Clonally distinct differentiation trajectories shape CD8+ memory T cell heterogeneity after acute viral infections in humans

CD8+ T cells play essential roles in immunity to viral and bacterial infections, and to guard against malignant cells. The CD8+ T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogenous repertoire of phenotypically and functionally distinct effector and memory cells1, 2. How individual T cell clones contribute to this heterogeneity during an immune response is key to understand immunity but remains largely unknown. Here, we longitudinally tracked CD8+ T cell clones expanding in response to yellow fever virus vaccination at the single cell level in humans. We show that only a fraction of the clones detected in the acute response persists as circulating memory T cells, indicative of clonal selection. Clones persisting in the memory phase displayed biased differentiation trajectories along a gradient of stem cell memory (SCM) towards terminally differentiated effector memory (EMRA) fates. Reactivation of single memory CD8+ T cells revealed that they were poised to recapitulate skewed differentiation trajectories in secondary responses, and this was generalizable across individuals for both yellow fever and influenza virus. Together, we show that the sum of distinct clonal differentiation repertoires results in the multifaceted T cell response to acute viral infections in humans.

immunology↗

bioRxiv2019

Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3

Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states1. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells2,3. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5 unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.

genomics↗

bioRxiv2019

The molecular anatomy of mouse skin during hair growth and rest

Skin homeostasis is orchestrated by dozens of cell types that together direct stem cell renewal, lineage commitment and differentiation. However, a systematic molecular atlas of full-thickness skin is lacking. Here, we used single-cell RNA-sequencing and mRNA-FISH to determine gene-expression identity and spatial location of skin cells during hair growth and rest. We defined 55 cell populations and made striking discoveries about the outer root sheath (ORS) and inner hair follicle layers that together coordinate hair production. The ORS is composed of two distinct cell types, companion layer cells resemble ORS and not inner layer cells, and we identified an asymmetric inner-layer structure with ORS cell identity. Moreover, the inner layers branch from transcriptionally uncommitted progenitors, and each lineage differentiation passes through an intermediate state. Altogether, we generated a comprehensive atlas with molecular and spatial information on epithelial and stromal cells, including fibroblasts, vascular and immune cells, that will spur new discoveries in skin biology.\n\nHIGHLIGHTS- Comprehensive single-cell transcriptome atlas of full-thickness skin\n- Outer root sheath (ORS) is composed of two distinct cell types\n- Companion layer transcriptionally resembles ORS\n- Transcriptional reconstruction of the internal hair follicle (HF) lineages\n- Molecular identification of an asymmetric HF-bulb structure\n- Spatial map of fibroblast subtypes in the skin\n- Online tool. http://kasperlab.org/tools

cell biology↗

bioRxiv2019

Understanding genetic interactions and assessing the utility of the additive and multiplicative models through simulations

Interaction analysis is used to investigate the magnitude of an effect which two risk factors have on disease risk, and on each other. To study interactions, both additive and multiplicative models have been used, although their interpretations are not universally understood. In this study, we set out to investigate the resulting interactions of several risk factors relationships in additive or multiplicative scenarios using simulations, in the context of case-control studies. Our simulation set up showed that independent risk factors approach additive relative risk at low disease prevalence. However, risk factors that contribute to the same chain of events (i.e. have synergy) lead to multiplicative relative risk. Additionally, thresholds on the number of required risk factors for a disease (the multifactorial threshold model) lead to intermediaries between additive and multiplicative risks. We proposed a novel measure of interaction consistent with additive, multiplicative and multifactorial threshold models. Finally, we demonstrate the utility of the simulation strategy and discovered relationships on real data by analyzing and interpreting gene-gene odds ratios from a case-control rheumatoid arthritis study.

genetics↗

bioRxiv2019

Expression reduction of biallelically transcribed X-linked genes during the human female preimplantation development

Our previous single-cell RNA-seq data from human preimplantation embryos showed that female X-chromosome mRNA levels become partly dose compensated during the timespan between zygotic genome activation (ZGA) and implantation. At the same time, XIST RNA is expressed from, and forms clouds in proximity to, both X-chromosome copies and biallelic expression of other X-linked genes persists. We proposed that X-chromosome transcription is transiently lowered on both alleles before X-chromosome inactivation (XCI) takes place. This notion was recently challenged in a reanalysis performed by Moreira de Mello et al, claiming to provide evidence against biallelic expression dampening and that instead proper XCI was responsible for the observed dosage compensation. Here we have addressed this reanalysis and highlighted methodological issues, and we conclude a current lack of evidence against biallelic X-chromosome dampening.

molecular biology↗

bioRxiv2019

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 monoallelic expression resulting from transcriptional bursting and how it compared to the amounts of monoallelic expression of autosomal genes observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain frequent observations of autosomal monoallelic gene expression in cells. Importantly, the burst frequency largely determined the fraction of cells with monoallelic expression, whereas both burst frequency and size contributed to allelic imbalance. Allelic observations deviate from the expected when analysed across heterogeneous groups of cells, suggesting that allelic modelling can provide an unbiased assessment of heterogeneity within cells. Finally, large numbers of cells are required for analyses of allelic imbalance to avoid confounding observations from transcriptional bursting. Altogether, our results shed light on the implications of transcriptional burst kinetics on allelic expression patterns and phenotypic variation between cells.

genomics↗

bioRxiv2019

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects

Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in-depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project.

genomics↗

bioRxiv2019

Transcriptional kinetics of X-chromosome upregulation

Ohnos hypothesis postulates that X-chromosome upregulation rectifies X-dose imbalance relative to autosomal genes, present in two active copies per cell. Here we dissected X-upregulation into kinetics of transcription, inferred from allele-specific single-cell RNA-sequencing (scRNAseq) data from somatic mouse cells. We confirmed increased X-chromosome expression, and remarkably found that the X-chromosome achieved upregulation by elevated burst frequencies. This provides mechanistic insights into X-chromosome upregulation.

molecular biology↗

bioRxiv2019

Cell type composition and circuit organization of neocortical radial clones

SummaryExcitatory neurons arising from a common progenitor establish radially-oriented clonal units in the neocortex which have been proposed to serve as elementary information processing modules. To characterize the cell types and circuit diagram within these clonal units, we performed single-cell RNA-sequencing and multi-cell patch clamp recordings of neurons derived from Nestin-positive progenitors. We found that radial clones do not appear to be fate-restricted, but instead individual clones are composed of a random sampling of the transcriptomic cell types present in a particular cortical area. The effect of lineage on synaptic connectivity depends on the type of connection tested: pairs of clonally related neurons were more likely to be connected vertically, across cortical layers, but not laterally within the same layer, compared to unrelated pairs. We propose that integration of vertical input from related neurons with lateral input from unrelated neurons may represent a developmentally programmed motif for assembling neocortical circuits.

neuroscience↗

bioRxiv2018

Neocortical layer 4 in adult mouse differs in major cell types and circuit organization between primary sensory areas

Layer 4 (L4) of mammalian neocortex plays a crucial role in cortical information processing, yet a complete census of its cell types and connectivity remains elusive. Using whole-cell recordings with morphological recovery, we identified one major excitatory and seven inhibitory types of neurons in L4 of adult mouse visual cortex (V1). Nearly all excitatory neurons were pyramidal and almost all Somatostatin-positive (SOM+) neurons were Martinotti cells. In contrast, in somatosensory cortex (S1), excitatory cells were mostly stellate and SOM+ cells were non-Martinotti. These morphologically distinct SOM+ interneurons correspond to different transcriptomic cell types and are differentially integrated into the local circuit with only S1 cells receiving local excitatory input. Our results challenge the classical view of a canonical microcircuit repeated through the neocortex. Instead we propose that cell-type specific circuit motifs, such as the Martinotti/pyramidal pair, are optionally used across the cortex as building blocks to assemble cortical circuits.

neuroscience↗

bioRxiv2018

NASC-seq monitors RNA synthesis in single cells

Sequencing of newly synthesized RNA can monitor transcriptional dynamics with great sensitivity and high temporal resolution, but is currently restricted to populations of cells. Here, we developed newly synthesized alkylation-dependent single-cell RNA sequencing (NASC-seq), to monitor both newly synthesized and pre-existing RNA in single cells. We validated the method on pre-alkylated exogenous spike-in RNA, and by demonstrating that more newly synthesized RNA was detected for genes with known high mRNA turnover. Importantly, NASC-seq reveals rapidly up- and down-regulated genes during the T-cell activation, and RNA sequenced for induced genes were essentially only newly synthesized. Moreover, the newly synthesized and preexisting transcriptomes after T-cell activation were distinct confirming that we indeed could simultaneously measure gene expression corresponding to two time points in single cells. Altogether, NASC-seq is a powerful tool to investigate transcriptional dynamics and it will enable the precise monitoring of RNA synthesis at flexible time periods during homeostasis, perturbation responses and cellular differentiation.

genomics↗

bioRxiv2018

LCM-seq reveals unique transcriptional adaption mechanisms of resistant neurons in spinal muscular atrophy

Somatic motor neurons are selectively vulnerable in spinal muscular atrophy (SMA), a lethal disease caused by a deficiency of the ubiquitously expressed survival of motor neuron (SMN) protein. However, some brainstem motor neuron groups, including oculomotor and trochlear (ocular), which innervate the muscles around the eyes, are for unknown reasons spared. Here, using laser capture microdissection coupled with RNA sequencing (LCM-seq), we investigate the transcriptional dynamics in discrete neuronal populations in health and SMA to reveal mechanisms of vulnerability and resistance. Using gene correlation network analysis, we reveal a p53-mediated stress response that is intrinsic to all somatic motor neurons independent of their vulnerability, but absent in resistant red nucleus and visceral motor neurons. However, our temporal and spatial differential expression analysis across neuron types clearly demonstrates that the majority of SMA-induced modulations are cell-type specific. Notably, using gene ontology and protein-network analyses we show that ocular motor neurons present unique disease-adaptation mechanisms that could explain their resilience. In particular, ocular motor neurons up-regulate; i) Syt1, Syt5 and Cplx2, which modulate neurotransmitter release; ii) the motor neuron survival factors Chl1 and Lif, iii) Aldh4, that can protect cells from oxidative stress and iv) the caspase inhibitor Pak4. In conclusion, our in-depth longitudinal analysis of gene expression changes in SMA reveal novel cell-type specific changes that present compelling targets for future gene therapy studies aimed towards preserving vulnerable motor neurons.

neuroscience↗

bioRxiv2017

Computational correction of cross-contamination due to exclusion amplification barcode spreading

Recent advances in sequencing technology have considerably increased the throughput and decreased the cost of short-read sequencing by using high-density patterned flow cells. However, high rates of cross-contamination between multiplexed libraries have been observed on data from these machines, likely due to index-switching during exclusion amplification1,2. Here, we demonstrate that a computational correction procedure based on the Sylvester equation removed 80-90% of the false positive expression signal and eliminated spurious clustering. The computational correction procedure can therefore be used to rescue aspects of affected sequence data so that researchers can take advantage of cost-effective sequencing on patterned flow cells.

genomics↗