Multimodal spatiotemporal phenotyping of human retinal organoid development.

Organoids generated from human pluripotent stem cells provide experimental systems to study development and disease, but quantitative measurements across different spatial scales and molecular modalities are lacking. In this study, we generated multiplexed protein maps over a retinal organoid time course and primary adult human retinal tissue. We developed a toolkit to visualize progenitor and neuron location, the spatial arrangements of extracellular and subcellular components and global patterning in each organoid and primary tissue. In addition, we generated a single-cell transcriptome and chromatin accessibility timecourse dataset and inferred a gene regulatory network underlying organoid development. We integrated genomic data with spatially segmented nuclei into a multimodal atlas to explore organoid patterning and retinal ganglion cell (RGC) spatial neighborhoods, highlighting pathways involved in RGC cell death and showing that mosaic genetic perturbations in retinal organoids provide insight into cell fate regulation.

Pyramidal neurons form active, transient, multilayered circuits perturbed by autism-associated mutations at the inception of neocortex.

Cortical circuits are composed predominantly of pyramidal-to-pyramidal neuron connections, yet their assembly during embryonic development is not well understood. We show that mouse embryonic Rbp4-Cre cortical neurons, transcriptomically closest to layer 5 pyramidal neurons, display two phases of circuit assembly in vivo. At E14.5, they form a multi-layered circuit motif, composed of only embryonic near-projecting-type neurons. By E17.5, this transitions to a second motif involving all three embryonic types, analogous to the three adult layer 5 types. In vivo patch clamp recordings and two-photon calcium imaging of embryonic Rbp4-Cre neurons reveal active somas and neurites, tetrodotoxin-sensitive voltage-gated conductances, and functional glutamatergic synapses, from E14.5 onwards. Embryonic Rbp4-Cre neurons strongly express autism-associated genes and perturbing these genes interferes with the switch between the two motifs. Hence, pyramidal neurons form active, transient, multi-layered pyramidal-to-pyramidal circuits at the inception of neocortex, and studying these circuits could yield insights into the etiology of autism.

Full-Length Single-Cell RNA-Sequencing with FLASH-seq.

The single-cell RNA-sequencing (scRNA-seq) field has evolved tremendously since the first paper was published back in 2009 (Tang et al. Nat Methods 6:377-382, 2009). While the first methods analyzed just a handful of cells, the throughput and performance rapidly increased over a very short time span. However, it was not until the introduction of emulsion droplets methods, such as the well-known kits commercialized by 10x Genomics, that the robust and reproducible analysis of thousands of cells became feasible (Zheng et al Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049, 2017). Despite generating data at a speed and a cost per cell that remains unmatched for full-length protocols like Smart-seq (Hagemann-Jensen et al Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol 38:708-714, 2020; Picelli et al Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096-1098, 2013), scRNA-seq in droplets still comes with the drawback of addressing only the terminal portion of the transcripts, thus lacking the required sensitivity for comprehensively analyzing the entire transcriptome.Building upon the existing Smart-seq2/3 workflows (Hagemann-Jensen et al Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol 38:708-714, 2020; Picelli et al Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096-1098, 2013), we developed FLASH-seq (FS), a new full-length scRNA-seq method capable of detecting a significantly higher number of genes than previous versions, requiring limited hands-on time and with a great potential for customization (Hahaut et al. Lightning Fast and Highly Sensitive Full-Length Single-cell sequencing using FLASH-Seq. http://biorxiv.org/lookup/doi/10.1101/2021.07.14.452217. https://doi.org/10.1101/2021.07.14.452217, 2021). Here, we present three variants of the FS protocol.Standard FLASH-seq (FS), which builds upon Smart-seq2 developed in the past, is non-stranded and does not use unique molecular identifiers (UMIs) but still remains the easiest method to measure gene expression in a cell population.FLASH-seq low-amplification (FS-LA) represents the fastest method, which generates sequencing-ready libraries in 4.5 h, without sacrificing performance.FLASH-seq with UMIs (FS-UMI) builds upon the same principle as Smart-seq3 and introduces UMIs for molecule counting and isoform reconstruction. The newly designed template-switching oligonucleotide (TSO) contains a 5-bp spacer, which allows the generation of high-quality data while minimizing the amount of strand-invasion artifacts.

Adenoviral-based vaccine promotes neoantigen-specific CD8+ T cell stemness and tumor rejection.

Upon chronic antigen exposure, CD8+ T cells become exhausted, acquiring a dysfunctional state correlated with the inability to control infection or tumor progression. In contrast, stem-like CD8+ T progenitors maintain the ability to promote and sustain effective immunity. Adenovirus (Ad)-vectored vaccines encoding tumor neoantigens have been shown to eradicate large tumors when combined with anti-programmed cell death protein 1 (αPD-1) in murine models; however, the mechanisms and translational potential have not yet been elucidated. Here, we show that gorilla Ad vaccine targeting tumor neoepitopes enhances responses to αPD-1 therapy by improving immunogenicity and antitumor efficacy. Single-cell RNA sequencing demonstrated that the combination of Ad vaccine and αPD-1 increased the number of murine polyfunctional neoantigen-specific CD8+ T cells over αPD-1 monotherapy, with an accumulation of Tcf1+ stem-like progenitors in draining lymph nodes and effector CD8+ T cells in tumors. Combined T cell receptor (TCR) sequencing analysis highlighted a broader spectrum of neoantigen-specific CD8+ T cells upon vaccination compared to αPD-1 monotherapy. The translational relevance of these data is supported by results obtained in the first 12 patients with metastatic deficient mismatch repair (dMMR) tumors vaccinated with an Ad vaccine encoding shared neoantigens. Expansion and diversification of TCRs were observed in post-treatment biopsies of patients with clinical response, as well as an increase in tumor-infiltrating T cells with an effector memory signature. These findings indicate a promising mechanism to overcome resistance to PD-1 blockade by promoting immunogenicity and broadening the spectrum and magnitude of neoantigen-specific T cells infiltrating tumors.

Fast and highly sensitive full-length single-cell RNA sequencing using FLASH-seq.

We present FLASH-seq (FS), a full-length single-cell RNA sequencing (scRNA-seq) method with increased sensitivity and reduced hands-on time compared to Smart-seq3. The entire FS protocol can be performed in ~4.5 hours, is simple to automate and can be easily miniaturized to decrease resource consumption. The FS protocol can also use unique molecular identifiers (UMIs) for molecule counting while displaying reduced strand-invasion artifacts. FS will be especially useful for characterizing gene expression at high resolution across multiple samples.

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.

Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution.

Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable "developed" state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.

BCG Vaccination in Humans Elicits Trained Immunity via the Hematopoietic Progenitor Compartment.

Induction of trained immunity by Bacille-Calmette-Guérin (BCG) vaccination mediates beneficial heterologous effects, but the mechanisms underlying its persistence and magnitude remain elusive. In this study, we show that BCG vaccination in healthy human volunteers induces a persistent transcriptional program connected to myeloid cell development and function within the hematopoietic stem and progenitor cell (HSPC) compartment in the bone marrow. We identify hepatic nuclear factor (HNF) family members 1a and b as crucial regulators of this transcriptional shift. These findings are corroborated by higher granulocyte numbers in BCG-vaccinated infants, HNF1 SNP variants that correlate with trained immunity, and elevated serum concentrations of the HNF1 target alpha-1 antitrypsin. Additionally, transcriptomic HSPC remodeling was epigenetically conveyed to peripheral CD14+ monocytes, displaying an activated transcriptional signature three months after BCG vaccination. Taken together, transcriptomic, epigenomic, and functional reprogramming of HSPCs and peripheral monocytes is a hallmark of BCG-induced trained immunity in humans.

Single-Cell Transcriptomics Uncovers Zonation of Function in the Mesenchyme during Liver Fibrosis.

Iterative liver injury results in progressive fibrosis disrupting hepatic architecture, regeneration potential, and liver function. Hepatic stellate cells (HSCs) are a major source of pathological matrix during fibrosis and are thought to be a functionally homogeneous population. Here, we use single-cell RNA sequencing to deconvolve the hepatic mesenchyme in healthy and fibrotic mouse liver, revealing spatial zonation of HSCs across the hepatic lobule. Furthermore, we show that HSCs partition into topographically diametric lobule regions, designated portal vein-associated HSCs (PaHSCs) and central vein-associated HSCs (CaHSCs). Importantly we uncover functional zonation, identifying CaHSCs as the dominant pathogenic collagen-producing cells in a mouse model of centrilobular fibrosis. Finally, we identify LPAR1 as a therapeutic target on collagen-producing CaHSCs, demonstrating that blockade of LPAR1 inhibits liver fibrosis in a rodent NASH model. Taken together, our work illustrates the power of single-cell transcriptomics to resolve the key collagen-producing cells driving liver fibrosis with high precision.

Full-Length Single-Cell RNA Sequencing with Smart-seq2.

In the last few years single-cell RNA sequencing (scRNA-seq) has enabled the investigation of cellular heterogeneity at the transcriptional level, the characterization of rare cell types as well as the detailed analysis of the stochastic nature of gene expression. A large number of methods have been developed, varying in their throughput, sensitivity, and scalability. A major distinction is whether they profile only 5'- or 3'-terminal part of the transcripts or allow for the characterization of the entire length of the transcripts. Among the latter, Smart-seq2 is still considered the "gold standard" due to its sensitivity, precision, lower cost, scalability and for being easy to set up on automated platforms. In this chapter I describe how to efficiently generate sequencing-ready libraries, highlight common issues and pitfalls, and offer solutions for generating high-quality data.

Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies.

Single-cell RNA sequencing is at the forefront of high-resolution phenotyping experiments for complex samples. Although this methodology requires specialized equipment and expertise, it is now widely applied in research. However, it is challenging to create broadly applicable experimental designs because each experiment requires the user to make informed decisions about sample preparation, RNA sequencing and data analysis. To facilitate this decision-making process, in this tutorial we summarize current methodological and analytical options, and discuss their suitability for a range of research scenarios. Specifically, we provide information about best practices for the separation of individual cells and provide an overview of current single-cell capture methods at different cellular resolutions and scales. Methods for the preparation of RNA sequencing libraries vary profoundly across applications, and we discuss features important for an informed selection process. An erroneous or biased analysis can lead to misinterpretations or obscure biologically important information. We provide a guide to the major data processing steps and options for meaningful data interpretation. These guidelines will serve as a reference to support users in building a single-cell experimental framework-from sample preparation to data interpretation-that is tailored to the underlying research context.

Two novel colorectal cancer risk loci in the region on chromosome 9q22.32.

Highly penetrant cancer syndromes account for less than 5% of all cases with familial colorectal cancer (CRC), and other genetic contribution explains the majority of the genetic contribution to CRC. A CRC susceptibility locus on chromosome 9q has been suggested. In this study, families where risk of CRC was linked to the region, were used to search for predisposing mutations in all genes in the region. No disease-causing mutation was found. Next, haplotype association studies were performed in the region, comparing Swedish CRC cases (2664) and controls (4782). Two overlapping haplotypes were suggested. One 10-SNP haplotype was indicated in familial CRC (OR 1.4, p = 0.00005) and one 25-SNP haplotype was indicated in sporadic CRC (OR 2.2, p = 0.0000012). The allele frequencies of the 10-SNP and the 25-SNP haplotypes were 13.7% and 2.5% respectively and both included one RNA, RP11-332M4.1 and RP11-l80l4.2, in the non-overlapping regions. The sporadic 25-SNP haplotype could not be studied further, but the familial 10-SNP haplotype was analyzed in 61 additional CRC families, and 6 of them were informative for all markers and had the risk haplotype. Targeted sequencing of the 10-SNP region in the linked families identified one variant in RP11-332M4.1, suggestive to confer the increased CRC risk on this haplotype. Our results support the presence of two loci at 9q22.32, each with one RNA as the putative cause of increased CRC risk. These RNAs could exert their effect through the same, or different, genes/pathways, possibly through the regulation of neighboring genes, such as PTCH1, FANCC, DKFZP434H0512, ERCC6L2 or the processed transcript LINC00046.

PHIP - a novel candidate breast cancer susceptibility locus on 6q14.1.

Most non-BRCA1/2 breast cancer families have no identified genetic cause. We used linkage and haplotype analyses in familial and sporadic breast cancer cases to identify a susceptibility locus on chromosome 6q. Two independent genome-wide linkage analysis studies suggested a 3 Mb locus on chromosome 6q and two unrelated Swedish families with a LOD >2 together seemed to share a haplotype in 6q14.1. We hypothesized that this region harbored a rare high-risk founder allele contributing to breast cancer in these two families. Sequencing of DNA and RNA from the two families did not detect any pathogenic mutations. Finally, 29 SNPs in the region were analyzed in 44,214 cases and 43,532 controls from BCAC, and the original haplotypes in the two families were suggested as low-risk alleles for European and Swedish women specifically. There was also some support for one additional independent moderate-risk allele in Swedish familial samples. The results were consistent with our previous findings in familial breast cancer and supported a breast cancer susceptibility locus at 6q14.1 around the PHIP gene.

STRT-seq-2i: dual-index 5' single cell and nucleus RNA-seq on an addressable microwell array.

Single-cell RNA-seq has become routine for discovering cell types and revealing cellular diversity, but archived human brain samples still pose a challenge to current high-throughput platforms. We present STRT-seq-2i, an addressable 9600-microwell array platform, combining sampling by limiting dilution or FACS, with imaging and high throughput at competitive cost. We applied the platform to fresh single mouse cortical cells and to frozen post-mortem human cortical nuclei, matching the performance of a previous lower-throughput platform while retaining a high degree of flexibility, potentially also for other high-throughput applications.

Defining New Colorectal Cancer Syndromes in a Population-based Cohort of the Disease.

BACKGROUND/AIM: Most known cancer syndromes confer an increased risk of more than one tumour types, and families with more than one colorectal cancer often segregate other cancers as well. The aim of this study was to examine if there is a general increased risk of other cancers in colorectal cancer families, which are defined as having two or more cases of colorectal cancer in close relatives. MATERIALS AND METHODS: The study used a detailed family history of cancer diagnoses in a cohort of more than 3,000 consecutive colorectal cancer cases. A comparison was made between families with sporadic and those with familial colorectal cancer cases. Detailed morphology data were used to find further support for putative syndromes. RESULTS: There were significantly more non-colorectal cancers in the family history of the familial CRC cases (p<0.001), with significantly more gastric cancers (p<0.001), prostate cancers (p<0.001), urinary bladder cancers (p<0.001) and melanomas (p=0.002), leukaemia/lymphomas (p=0.004), gynaecological cancers (p=0.007) and breast cancers (p=0.023). There was also some support for different morphological profiles for four of the five tested syndromes. CONCLUSION: This study found support for a general increased risk of one or more different cancer syndromes involving families with colorectal cancer and other cancers. Further studies will define the different possible syndromes and determine the genetic background.

Single-cell RNA-sequencing: The future of genome biology is now.

Genome-wide single-cell analysis represents the ultimate frontier of genomics research. In particular, single-cell RNA-sequencing (scRNA-seq) studies have been boosted in the last few years by an explosion of new technologies enabling the study of the transcriptomic landscape of thousands of single cells in complex multicellular organisms. More sensitive and automated methods are being continuously developed and promise to deliver better data quality and higher throughput with less hands-on time. The outstanding amount of knowledge that is going to be gained from present and future studies will have a profound impact in many aspects of our society, from the introduction of truly tailored cancer treatments, to a better understanding of antibiotic resistance and host-pathogen interactions; from the discovery of the mechanisms regulating stem cell differentiation to the characterization of the early event of human embryogenesis.

Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes.

Hormone-secreting cells within pancreatic islets of Langerhans play important roles in metabolic homeostasis and disease. However, their transcriptional characterization is still incomplete. Here, we sequenced the transcriptomes of thousands of human islet cells from healthy and type 2 diabetic donors. We could define specific genetic programs for each individual endocrine and exocrine cell type, even for rare δ, γ, ε, and stellate cells, and revealed subpopulations of α, ß, and acinar cells. Intriguingly, δ cells expressed several important receptors, indicating an unrecognized importance of these cells in integrating paracrine and systemic metabolic signals. Genes previously associated with obesity or diabetes were found to correlate with BMI. Finally, comparing healthy and T2D transcriptomes in a cell-type resolved manner uncovered candidates for future functional studies. Altogether, our analyses demonstrate the utility of the generated single-cell gene expression resource.

Exome sequencing in one family with gastric- and rectal cancer.

BACKGROUND: Heritable factors are well known to increase the risk of cancer in families. Known susceptibility genes account for a small proportion of all colorectal cancer cases. The aim of this study was to identify the genetic background in a family suggested to segregate a dominant cancer syndrome with a high risk of rectal- and gastric cancer. We performed whole exome sequencing in three family members, 2 with rectal cancer and 1 with gastric cancer and followed it up in additional family members, other patients and controls. RESULTS: We identified 12 novel non-synonymous single nucleotide variants, which were shared among 5 affected members of this family. The mutations were found in 12 different genes; DZIP1L, PCOLCE2, IGSF10, SUCNR1, OR13C8, EPB41L4B, SEC16A, NOTCH1, TAS2R7, SF3A1, GAL3ST1, and TRIOBP. None of the mutations was suggested as a high penetrant mutation. It was not possible to completely rule out any of the mutations as contributing to disease, although seven were more unlikely than the others. Neither did we rule out the effect of all thousands of intronic, intergenic and synonymous variants shared between the three persons used for exome sequencing. CONCLUSIONS: We propose this family, suggested to segregate dominant disease, could be an example of complex inheritance.

The heterogeneity of human CD127(+) innate lymphoid cells revealed by single-cell RNA sequencing.

Innate lymphoid cells (ILCs) are increasingly appreciated as important participants in homeostasis and inflammation. Substantial plasticity and heterogeneity among ILC populations have been reported. Here we have delineated the heterogeneity of human ILCs through single-cell RNA sequencing of several hundreds of individual tonsil CD127(+) ILCs and natural killer (NK) cells. Unbiased transcriptional clustering revealed four distinct populations, corresponding to ILC1 cells, ILC2 cells, ILC3 cells and NK cells, with their respective transcriptomes recapitulating known as well as unknown transcriptional profiles. The single-cell resolution additionally divulged three transcriptionally and functionally diverse subpopulations of ILC3 cells. Our systematic comparison of single-cell transcriptional variation within and between ILC populations provides new insight into ILC biology during homeostasis, with additional implications for dysregulation of the immune system.

DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control.

Although Burkitt lymphomas and follicular lymphomas both have features of germinal center B cells, they are biologically and clinically quite distinct. Here we performed whole-genome bisulfite, genome and transcriptome sequencing in 13 IG-MYC translocation-positive Burkitt lymphoma, nine BCL2 translocation-positive follicular lymphoma and four normal germinal center B cell samples. Comparison of Burkitt and follicular lymphoma samples showed differential methylation of intragenic regions that strongly correlated with expression of associated genes, for example, genes active in germinal center dark-zone and light-zone B cells. Integrative pathway analyses of regions differentially methylated in Burkitt and follicular lymphomas implicated DNA methylation as cooperating with somatic mutation of sphingosine phosphate signaling, as well as the TCF3-ID3 and SWI/SNF complexes, in a large fraction of Burkitt lymphomas. Taken together, our results demonstrate a tight connection between somatic mutation, DNA methylation and transcriptional control in key B cell pathways deregulated differentially in Burkitt lymphoma and other germinal center B cell lymphomas.