CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics.

MOTIVATION: Copy number variations (CNVs) are common genetic alterations in tumour cells. The delineation of CNVs holds promise for enhancing our comprehension of cancer progression. Moreover, accurate inference of CNVs from single-cell sequencing data is essential for unravelling intratumoral heterogeneity. However, existing inference methods face limitations in resolution and sensitivity. RESULTS: To address these challenges, we present CopyVAE, a deep learning framework based on a variational autoencoder architecture. Through experiments, we demonstrated that CopyVAE can accurately and reliably detect CNVs from data obtained using single-cell RNA sequencing. CopyVAE surpasses existing methods in terms of sensitivity and specificity. We also discussed CopyVAE's potential to advance our understanding of genetic alterations and their impact on disease advancement. AVAILABILITY AND IMPLEMENTATION: CopyVAE is implemented and freely available under MIT license at https://github.com/kurtsemih/copyVAE.

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.

Intestinal damage is required for the pro-inflammatory differentiation of commensal CBir1-specific T cells.

Commensal-specific clusters of differentiation (CD)4+ T cells are expanded in patients with inflammatory bowel disease (IBD) compared to healthy individuals. How and where commensal-specific CD4+ T cells get activated is yet to be fully understood. We used CBir1 TCR-transgenic CD4+ T cells, specific to a commensal bacterial antigen, and different mouse models of IBD to characterize the dynamics of commensal-specific CD4+ T-cells activation. We found that CBir1 T cells proliferate following intestinal damage and cognate antigen presentation is mediated by CD11c+ cells in the colon-draining mesenteric lymph nodes. Using assay for transposase-accessible chromatin sequencing and flow cytometry, we showed that activated CBir1 T cells preferentially acquire an effector rather than regulatory phenotype, which is plastic over time. Moreover, CBir1 T cells, while insufficient to initiate intestinal inflammation, contributed to worse disease outcomes in the presence of other CD4+ T cells. Our results suggest that the commensal-specific T-cell responses observed in IBD exacerbate rather than initiate disease.

Spatial transcriptomics of B cell and T cell receptors reveals lymphocyte clonal dynamics.

The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.

Long-read whole-genome analysis of human single cells.

Long-read sequencing has dramatically increased our understanding of human genome variation. Here, we demonstrate that long-read technology can give new insights into the genomic architecture of individual cells. Clonally expanded CD8+ T-cells from a human donor were subjected to droplet-based multiple displacement amplification (dMDA) to generate long molecules with reduced bias. PacBio sequencing generated up to 40% genome coverage per single-cell, enabling detection of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, also in regions inaccessible by short reads. 28 somatic SNVs were detected, including one case of mitochondrial heteroplasmy. 5473 high-confidence SVs/cell were discovered, a sixteen-fold increase compared to Illumina-based results from clonally related cells. Single-cell de novo assembly generated a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, our work shows the promise of long-read sequencing toward characterization of the full spectrum of genetic variation in single cells.

Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics.

Functional characterization of the cancer clones can shed light on the evolutionary mechanisms driving cancer's proliferation and relapse mechanisms. Single-cell RNA sequencing data provide grounds for understanding the functional state of cancer as a whole; however, much research remains to identify and reconstruct clonal relationships toward characterizing the changes in functions of individual clones. We present PhylEx that integrates bulk genomics data with co-occurrences of mutations from single-cell RNA sequencing data to reconstruct high-fidelity clonal trees. We evaluate PhylEx on synthetic and well-characterized high-grade serous ovarian cancer cell line datasets. PhylEx outperforms the state-of-the-art methods both when comparing capacity for clonal tree reconstruction and for identifying clones. We analyze high-grade serous ovarian cancer and breast cancer data to show that PhylEx exploits clonal expression profiles beyond what is possible with expression-based clustering methods and clear the way for accurate inference of clonal trees and robust phylo-phenotypic analysis of cancer.

Prostate cancer disease recurrence after radical prostatectomy is associated with HLA type and local cytomegalovirus immunity.

Prostate cancer is a heterogeneous disease with a need for new prognostic biomarkers. Human leukocyte antigen (HLA) genes are highly polymorphic genes central to antigen presentation to T-cells. Two alleles, HLA-A*02:01 and HLA-A*24:02, have been associated with prognosis in patients diagnosed with de novo metastatic prostate cancer. We leveraged the next-generation sequenced cohorts CPC-GENE and TCGA-PRAD to examine HLA alleles, antiviral T-cell receptors and prostate cancer disease recurrence after prostatectomy. Carrying HLA-A*02:01 (111/229; 48% of patients) was independently associated with disease recurrence in patients with low-intermediate risk prostate cancer. HLA-A*11 (carried by 42/441; 10% of patients) was independently associated with rapid disease recurrence in patients with high-risk prostate cancer. Moreover, HLA-A*02:01 carriers in which anti-cytomegalovirus T-cell receptors (CMV-TCR) were identified in tumors (13/144; 10% of all patients in the cohort) had a higher risk of disease recurrence than CMV-TCR-negative patients. These findings suggest that HLA-type and CMV immunity may be valuable biomarkers for prostate cancer progression.

A biliary immune landscape map of primary sclerosing cholangitis reveals a dominant network of neutrophils and tissue-resident T cells.

The human biliary system, a mucosal barrier tissue connecting the liver and intestine, is an organ often affected by serious inflammatory and malignant diseases. Although these diseases are linked to immunological processes, the biliary system represents an unexplored immunological niche. By combining endoscopy-guided sampling of the biliary tree with a high-dimensional analysis approach, comprehensive mapping of the human biliary immunological landscape in patients with primary sclerosing cholangitis (PSC), a severe biliary inflammatory disease, was conducted. Major differences in immune cell composition in bile ducts compared to blood were revealed. Furthermore, biliary inflammation in patients with PSC was characterized by high presence of neutrophils and T cells as compared to control individuals without PSC. The biliary T cells displayed a CD103+CD69+ effector memory phenotype, a combined gut and liver homing profile, and produced interleukin-17 (IL-17) and IL-22. Biliary neutrophil infiltration in PSC associated with CXCL8, possibly produced by resident T cells, and CXCL16 was linked to the enrichment of T cells. This study uncovers the immunological niche of human bile ducts, defines a local immune network between neutrophils and biliary-resident T cells in PSC, and provides a resource for future studies of the immune responses in biliary disorders.

Divergent clonal differentiation trajectories establish CD8+ memory T cell heterogeneity during acute viral infections in humans.

The CD8+ T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogeneous repertoire of effector and memory cells. How individual T cell clones contribute to this heterogeneity throughout immune responses remains largely unknown. In this study, we longitudinally track human CD8+ T cell clones expanding in response to yellow fever virus (YFV) vaccination at the single-cell level. We observed a drop in clonal diversity in blood from the acute to memory phase, suggesting that clonal selection shapes the circulating memory repertoire. Clones in the memory phase display biased differentiation trajectories along a gradient from stem cell to terminally differentiated effector memory fates. In secondary responses, YFV- and influenza-specific CD8+ T cell clones are poised to recapitulate skewed differentiation trajectories. Collectively, we show that the sum of distinct clonal phenotypes results in the multifaceted human T cell response to acute viral infections.

Expansions of adaptive-like NK cells with a tissue-resident phenotype in human lung and blood.

Human adaptive-like "memory" CD56dimCD16+ natural killer (NK) cells in peripheral blood from cytomegalovirus-seropositive individuals have been extensively investigated in recent years and are currently explored as a treatment strategy for hematological cancers. However, treatment of solid tumors remains limited due to insufficient NK cell tumor infiltration, and it is unknown whether large expansions of adaptive-like NK cells that are equipped for tissue residency and tumor homing exist in peripheral tissues. Here, we show that human lung and blood contains adaptive-like CD56brightCD16- NK cells with hallmarks of tissue residency, including expression of CD49a. Expansions of adaptive-like lung tissue-resident NK (trNK) cells were found to be present independently of adaptive-like CD56dimCD16+ NK cells and to be hyperresponsive toward target cells. Together, our data demonstrate that phenotypically, functionally, and developmentally distinct subsets of adaptive-like NK cells exist in human lung and blood. Given their tissue-related character and hyperresponsiveness, human lung adaptive-like trNK cells might represent a suitable alternative for therapies targeting solid tumors.

A heterozygous germline CD100 mutation in a family with primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is a chronic inflammatory liver disease without clear etiology or effective treatment. Genetic factors contribute to PSC pathogenesis, but so far, no causative mutation has been found. We performed whole-exome sequencing in a family with autosomal dominant inheritance of PSC and identified a heterozygous germline missense mutation in SEMA4D, encoding a K849T variant of CD100. The mutation was located in an evolutionarily conserved, unstructured cytosolic region of CD100 affecting downstream signaling. It was found to alter the function of CD100-expressing cells with a bias toward the T cell compartment that caused increased proliferation and impaired interferon-γ (IFN-γ) production after stimulation. Homologous mutation knock-in mice developed similar IFN-γ impairment in T cells and were more prone to develop severe cholangitis when exposed to 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet. Transfer of wild-type T cells to knock-in mice before and during DDC exposure attenuated cholangitis. Taken together, we identified an inherited mutation in the disordered cytosolic region of CD100 resulting in T cell functional defects. Our findings suggest a protective role for T cells in PSC that might be used therapeutically.

Activation of a neural stem cell transcriptional program in parenchymal astrocytes.

Adult neural stem cells, located in discrete brain regions, generate new neurons throughout life. These stem cells are specialized astrocytes, but astrocytes in other brain regions do not generate neurons under physiological conditions. After stroke, however, striatal astrocytes undergo neurogenesis in mice, triggered by decreased Notch signaling. We used single-cell RNA sequencing to characterize neurogenesis by Notch-depleted striatal astrocytes in vivo. Striatal astrocytes were located upstream of neural stem cells in the neuronal lineage. As astrocytes initiated neurogenesis, they became transcriptionally very similar to subventricular zone stem cells, progressing through a near-identical neurogenic program. Surprisingly, in the non-neurogenic cortex, Notch-depleted astrocytes also initiated neurogenesis. Yet, these cortical astrocytes, and many striatal ones, stalled before entering transit-amplifying divisions. Infusion of epidermal growth factor enabled stalled striatal astrocytes to resume neurogenesis. We conclude that parenchymal astrocytes are latent neural stem cells and that targeted interventions can guide them through their neuronal differentiation.

Regenerative medicine aims to help the body replace damaged or worn-out tissues, often by kick-starting its own intrinsic repair mechanisms. However, the brain cannot easily repair itself, and therefore poses a much greater challenge. This is because nerve cells or neurons, which underpin learning, memory, and many other abilities, are also the brain's greatest weakness when it comes to tissue repair. In most parts of the adult brain, neurons are never replaced after they die. This means that damage to brain tissue ­ for example, after a stroke ­ can have severe and long-lasting consequences. Neural stem cells are one type of brain cell that can turn into new neurons if needed, but they are only found in a few parts of the brain and cannot fix damage elsewhere. More recent work in mice has shown that astrocytes, a common type of support cell in the brain that help keep neurons healthy, could also generate new neurons following a stroke. However, the ability was restricted to small numbers of astrocytes in a specific part of the brain. Here, Magnusson et al. set out to determine the molecular mechanisms behind this regenerative process and why it is unique to certain astrocytes. The researchers used a technique called single-cell RNA sequencing to analyze the genetic activity within individual mouse astrocytes that had been exposed to conditions mimicking a stroke. This method revealed which genes are switched on or off, thus generating a profile of gene activity for each astrocyte analyzed. This experiment showed that the profiles of astrocytes that had started to produce neurons were in fact nearly identical to neural stem cells. Even the astrocytes that could not generate neurons took the first few steps towards this genetic state; however, they stalled early in the process. Treating the brains of mice withepidermal growth factor, a powerful molecular signal that stimulates cell growth, kick-started nerve cell production in a subset of these cells ­ showing that at least some of the non-regenerative astrocytes could be stimulated to make neurons if given the right treatment. The results of this study shed new light on how some astrocytes in the brain gain the ability to form new neurons. In the future, this knowledge could help identify a source of replacement cells to regenerate the injured brain.

Cell generation dynamics underlying naive T-cell homeostasis in adult humans.

Thymic involution and proliferation of naive T cells both contribute to shaping the naive T-cell repertoire as humans age, but a clear understanding of the roles of each throughout a human life span has been difficult to determine. By measuring nuclear bomb test-derived 14C in genomic DNA, we determined the turnover rates of CD4+ and CD8+ naive T-cell populations and defined their dynamics in healthy individuals ranging from 20 to 65 years of age. We demonstrate that naive T-cell generation decreases with age because of a combination of declining peripheral division and thymic production during adulthood. Concomitant decline in T-cell loss compensates for decreased generation rates. We investigated putative mechanisms underlying age-related changes in homeostatic regulation of CD4+ naive T-cell turnover, using mass cytometry to profile candidate signaling pathways involved in T-cell activation and proliferation relative to CD31 expression, a marker of thymic proximity for the CD4+ naive T-cell population. We show that basal nuclear factor κB (NF-κB) phosphorylation positively correlated with CD31 expression and thus is decreased in peripherally expanded naive T-cell clones. Functionally, we found that NF-κB signaling was essential for naive T-cell proliferation to the homeostatic growth factor interleukin (IL)-7, and reduced NF-κB phosphorylation in CD4+CD31- naive T cells is linked to reduced homeostatic proliferation potential. Our results reveal an age-related decline in naive T-cell turnover as a putative regulator of naive T-cell diversity and identify a molecular pathway that restricts proliferation of peripherally expanded naive T-cell clones that accumulate with age.

Single-Cell RNA Sequencing of the T Helper Cell Response to House Dust Mites Defines a Distinct Gene Expression Signature in Airway Th2 Cells.

Naive CD4+ T cells differentiate into functionally diverse T helper (Th) cell subsets. Th2 cells play a pathogenic role in asthma, yet a clear picture of their transcriptional profile is lacking. We performed single-cell RNA sequencing (scRNA-seq) of T helper cells from lymph node, lung, and airways in the house dust mite (HDM) model of allergic airway disease. scRNA-seq resolved transcriptional profiles of naive CD4+ T, Th1, Th2, regulatory T (Treg) cells, and a CD4+ T cell population responsive to type I interferons. Th2 cells in the airways were enriched for transcription of many genes, including Cd200r1, Il6, Plac8, and Igfbp7, and their mRNA profile was supported by analysis of chromatin accessibility and flow cytometry. Pathways associated with lipid metabolism were enriched in Th2 cells, and experiments with inhibitors of key metabolic pathways supported roles for glucose and lipid metabolism. These findings provide insight into the differentiation of pathogenic Th2 cells in the context of allergy.

Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing.

Accurate variant calling and genotyping represent major limiting factors for downstream applications of single-cell genomics. Here, we report Conbase for the identification of somatic mutations in single-cell DNA sequencing data. Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions. Comparing the performance of Conbase to three other methods, we find that Conbase performs best in terms of false discovery rate and specificity and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.

Probabilistic count matrix factorization for single cell expression data analysis.

MOTIVATION: The development of high-throughput single-cell sequencing technologies now allows the investigation of the population diversity of cellular transcriptomes. The expression dynamics (gene-to-gene variability) can be quantified more accurately, thanks to the measurement of lowly expressed genes. In addition, the cell-to-cell variability is high, with a low proportion of cells expressing the same genes at the same time/level. Those emerging patterns appear to be very challenging from the statistical point of view, especially to represent a summarized view of single-cell expression data. Principal component analysis (PCA) is a most powerful tool for high dimensional data representation, by searching for latent directions catching the most variability in the data. Unfortunately, classical PCA is based on Euclidean distance and projections that poorly work in presence of over-dispersed count data with dropout events like single-cell expression data. RESULTS: We propose a probabilistic Count Matrix Factorization (pCMF) approach for single-cell expression data analysis that relies on a sparse Gamma-Poisson factor model. This hierarchical model is inferred using a variational EM algorithm. It is able to jointly build a low dimensional representation of cells and genes. We show how this probabilistic framework induces a geometry that is suitable for single-cell data visualization, and produces a compression of the data that is very powerful for clustering purposes. Our method is competed against other standard representation methods like t-SNE, and we illustrate its performance for the representation of single-cell expression data. AVAILABILITY AND IMPLEMENTATION: Our work is implemented in the pCMF R-package (https://github.com/gdurif/pCMF). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High dimensional classification with combined adaptive sparse PLS and logistic regression.

Motivation: The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent over-optimistic predictions. This challenge can be tackled by compression and variable selection, which combined constitute a powerful framework for classification, as well as data visualization and interpretation. However, current proposed combinations lead to unstable and non convergent methods due to inappropriate computational frameworks. We hereby propose a computationally stable and convergent approach for classification in high dimensional based on sparse Partial Least Squares (sparse PLS). Results: We start by proposing a new solution for the sparse PLS problem that is based on proximal operators for the case of univariate responses. Then we develop an adaptive version of the sparse PLS for classification, called logit-SPLS, which combines iterative optimization of logistic regression and sparse PLS to ensure computational convergence and stability. Our results are confirmed on synthetic and experimental data. In particular, we show how crucial convergence and stability can be when cross-validation is involved for calibration purposes. Using gene expression data, we explore the prediction of breast cancer relapse. We also propose a multicategorial version of our method, used to predict cell-types based on single-cell expression data. Availability and implementation: Our approach is implemented in the plsgenomics R-package. Contact: ghislain.durif@inria.fr. Supplementary information: Supplementary data are available at Bioinformatics online.

The Lifespan and Turnover of Microglia in the Human Brain.

The hematopoietic system seeds the CNS with microglial progenitor cells during the fetal period, but the subsequent cell generation dynamics and maintenance of this population have been poorly understood. We report that microglia, unlike most other hematopoietic lineages, renew slowly at a median rate of 28% per year, and some microglia last for more than two decades. Furthermore, we find no evidence for the existence of a substantial population of quiescent long-lived cells, meaning that the microglia population in the human brain is sustained by continuous slow turnover throughout adult life.

Comparison of whole genome amplification techniques for human single cell exome sequencing.

BACKGROUND: Whole genome amplification (WGA) is currently a prerequisite for single cell whole genome or exome sequencing. Depending on the method used the rate of artifact formation, allelic dropout and sequence coverage over the genome may differ significantly. RESULTS: The largest difference between the evaluated protocols was observed when analyzing the target coverage and read depth distribution. These differences also had impact on the downstream variant calling. Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells. DISCUSSION: In this study four commercial kits for WGA (AMPLI1, MALBAC, Repli-G and PicoPlex) were used to amplify human single cells. The WGA products were exome sequenced together with non-amplified bulk samples from the same source. The resulting data was evaluated in terms of genomic coverage, allelic dropout and SNP calling.

Antibody-secreting plasma cells persist for decades in human intestine.

Plasma cells (PCs) produce antibodies that mediate immunity after infection or vaccination. In contrast to PCs in the bone marrow, PCs in the gut have been considered short lived. In this study, we studied PC dynamics in the human small intestine by cell-turnover analysis in organ transplants and by retrospective cell birth dating measuring carbon-14 in genomic DNA. We identified three distinct PC subsets: a CD19+ PC subset was dynamically exchanged, whereas of two CD19- PC subsets, CD45+ PCs exhibited little and CD45- PCs no replacement and had a median age of 11 and 22 yr, respectively. Accumulation of CD45- PCs during ageing and the presence of rotavirus-specific clones entirely within the CD19- PC subsets support selection and maintenance of protective PCs for life in human intestine.