Single-Cell Profiling Identifies Key Pathways Expressed by iPSCs Cultured in Different Commercial Media

LMNA -Related Dilated Cardiomyopathy: Single-Cell Transcriptomics during Patient-derived iPSC Differentiation Support Cell type and Lineage-specific Dysregulation of Gene Expression and Development for Cardiomyocytes and Epicardium-Derived Cells with Lamin A/C Haploinsufficiency

LMNA -Related Dilated Cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C ( LMNA ) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. Molecular mechanisms of disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms of LMNA -Related DCM using induced pluripotent stem cells derived from a family with a heterozygous LMNA c.357-2A>G splice-site mutation. We differentiated one LMNA mutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (4 Patient and 8 Control) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for Cardiac Progenitors to Cardiomyocytes (CM) and Epicardium-Derived Cells (EPDC). Data integration and comparative analyses of Patient and Control cells found cell type and lineage differentially expressed genes (DEG) with enrichment to support pathway dysregulation. Top DEG and enriched pathways included: 10 ZNF genes and RNA polymerase II transcription in Pluripotent cells (PP); BMP4 and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis, CDH2 and EMT in CM; LMNA and epigenetic regulation and DDIT4 and mTORC1 signaling in EPDC. Top DEG also included: XIST and other X-linked genes, six imprinted genes: SNRPN , PWAR6 , NDN , PEG10 , MEG3 , MEG8 , and enriched gene sets in metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs as proposed in other LMNA disease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model.

A semi-automated pipeline for quantifying drusen-like deposits in human induced pluripotent stem cell-derived retinal pigment epithelium cells

Age-Related Macular Degeneration (AMD) is a highly prevalent form of retinal disease amongst Western communities over 50 years of age. A hallmark of AMD pathogenesis is the accumulation of drusen underneath the retinal pigment epithelium (RPE), a biological process also observable in vitro. The accumulation of drusen has been shown to predict the progression to advanced AMD, making accurate characterisation of drusen in vitro models valuable in disease modelling and drug development. More recently, deposits above the RPE in the subretinal space, called reticular pseudodrusen (RPD) have been recognized as a sub-phenotype of AMD. While in vitro imaging techniques allow for the immunostaining of drusen-like deposits, quantification of these deposits often requires slow, low throughput manual counting of images. This further lends itself to issues including sampling biases, while ignoring critical data parameters including volume and precise localization. To overcome these issues, we developed a semi-automated pipeline for quantifying the presence of drusen-like deposits in vitro, using RPE cultures derived from patient-specific induced pluripotent stem cells (iPSCs). Using high-throughput confocal microscopy, together with three-dimensional reconstruction, we developed an imaging and analysis pipeline that quantifies the number of drusen-like deposits, and accurately and reproducibly provides the location and composition of these deposits. Extending its utility, this pipeline can determine whether the drusen-like deposits locate to the apical or basal surface of RPE cells. Here, we validate the utility of this pipeline in the quantification of drusen-like deposits in six iPSCs lines derived from patients with AMD, following their differentiation into RPE cells. This pipeline provides a valuable tool for the in vitro modelling of AMD and other retinal disease, and is amenable to mid and high throughput screenings.

Human archetypal pluripotent stem cells differentiate into trophoblast stem cells via endogenous BMP5/7 induction without transitioning through naive state

Primary human trophoblast stem cells (TSCs) and TSCs derived from human pluripotent stem cells (hPSCs) can potentially model placental processes in vitro. Yet, the pluripotent states and factors involved in the differentiation of hPSCs to TSCs remain poorly understood. In this study, we demonstrate that the primed pluripotent state can generate TSCs by activating pathways such as Epidermal Growth Factor (EGF) and Wingless-related integration site (WNT), and by suppressing tumor growth factor beta (TGFβ), histone deacetylases (HDAC), and Rho-associated protein kinase (ROCK) signaling pathways, all without the addition of exogenous Bone morphogenetic protein 4 (BMP4)-a condition we refer to as the TS condition. We characterized this process using temporal single-cell RNA sequencing to compare TS conditions with differentiation protocols involving BMP4 activation alone or BMP4 activation in conjunction with WNT inhibition. The TS condition consistently produced a stable, proliferative cell type that closely mimics first-trimester placental cytotrophoblasts, marked by the activation of endogenous retroviral genes and the absence of amnion expression. This was observed across multiple cell lines, including various primed induced pluripotent stem cell (iPSC) and embryonic stem cell (ESC) lines. Primed-derived TSCs can proliferate for over 30 passages and further specify into multinucleated syncytiotrophoblasts and extravillous trophoblast cells. Our research establishes that the differentiation of primed hPSCs to TSC under TS conditions triggers the induction of TMSB4X, BMP5/7, GATA3, and TFAP2A without progressing through a naive state. These findings propose that the primed hPSC state is part of a continuum of potency with the capacity to differentiate into TSCs through multiple routes.

Integration of xeno-free single-cell cloning in CRISPR-mediated DNA editing of human iPSCs improves homogeneity and methodological efficiency of cellular disease modeling

The capability to generate induced pluripotent stem cell (iPSC) lines, in tandem with CRISPR-Cas9 DNA editing, offers great promise to understand the underlying genetic mechanisms of human disease. The low efficiency of available methods for homogeneous expansion of singularized CRISPR-transfected iPSCs necessitates the coculture of transfected cells in mixed populations and/or on feeder layers. Consequently, edited cells must be purified using labor-intensive screening and selection, culminating in inefficient editing. Here, we provide a xeno-free method for single-cell cloning of CRISPRed iPSCs achieving a clonal survival of up to 70% within 7-10 days. This is accomplished through improved viability of the transfected cells, paralleled with provision of an enriched environment for the robust establishment and proliferation of singularized iPSC clones. Enhanced cell survival was accompanied by a high transfection efficiency exceeding 97%, and editing efficiencies of 50%-65% for NHEJ and 10% for HDR, indicative of the method's utility in stem cell disease modeling.

A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omics

Cell annotation is a crucial methodological component to interpreting single cell and spatial omics data. These approaches were developed for single cell analysis but are often biased, manually curated and yet unproven in spatial omics. Here we apply a stemness model for assessing oncogenic states to single cell and spatial omic cancer datasets. This one-class logistic regression machine learning algorithm is used to extract transcriptomic features from non-transformed stem cells to identify dedifferentiated cell states in tumors. We found this method identifies single cell states in metastatic tumor cell populations without the requirement of cell annotation. This machine learning model identified stem-like cell populations not identified in single cell or spatial transcriptomic analysis using existing methods. For the first time, we demonstrate the application of a ML tool across five emerging spatial transcriptomic and proteomic technologies to identify oncogenic stem-like cell types in the tumor microenvironment.

A village in a dish model system for population-scale hiPSC studies

The mechanisms by which DNA alleles contribute to disease risk, drug response, and other human phenotypes are highly context-specific, varying across cell types and different conditions. Human induced pluripotent stem cells are uniquely suited to study these context-dependent effects but cell lines from hundreds or thousands of individuals are required. Village cultures, where multiple induced pluripotent stem lines are cultured and differentiated in a single dish, provide an elegant solution for scaling induced pluripotent stem experiments to the necessary sample sizes required for population-scale studies. Here, we show the utility of village models, demonstrating how cells can be assigned to an induced pluripotent stem line using single-cell sequencing and illustrating that the genetic, epigenetic or induced pluripotent stem line-specific effects explain a large percentage of gene expression variation for many genes. We demonstrate that village methods can effectively detect induced pluripotent stem line-specific effects, including sensitive dynamics of cell states.

Transfer learning enables predictions in network biology

Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recently, transfer learning has revolutionized fields such as natural language understanding1,2 and computer vision3 by leveraging deep learning models pretrained on large-scale general datasets that can then be fine-tuned towards a vast array of downstream tasks with limited task-specific data. Here, we developed a context-aware, attention-based deep learning model, Geneformer, pretrained on a large-scale corpus of about 30 million single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology. During pretraining, Geneformer gained a fundamental understanding of network dynamics, encoding network hierarchy in the attention weights of the model in a completely self-supervised manner. Fine-tuning towards a diverse panel of downstream tasks relevant to chromatin and network dynamics using limited task-specific data demonstrated that Geneformer consistently boosted predictive accuracy. Applied to disease modelling with limited patient data, Geneformer identified candidate therapeutic targets for cardiomyopathy. Overall, Geneformer represents a pretrained deep learning model from which fine-tuning towards a broad range of downstream applications can be pursued to accelerate discovery of key network regulators and candidate therapeutic targets.

Genetic manipulation and targeted protein degradation in mammalian systems: practical considerations, tips and tricks for discovery research

Gaining a mechanistic understanding of the molecular pathways underpinning cellular and organismal physiology invariably relies on the perturbation of an experimental system to infer causality. This can be achieved either by genetic manipulation or by pharmacological treatment. Generally, the former approach is applicable to a wider range of targets, is more precise, and can address more nuanced functional aspects. Despite such apparent advantages, genetic manipulation (i.e., knock-down, knock-out, mutation, and tagging) in mammalian systems can be challenging due to problems with delivery, low rates of homologous recombination, and epigenetic silencing. The advent of CRISPR-Cas9 in combination with the development of robust differentiation protocols that can efficiently generate a variety of different cell types in vitro has accelerated our ability to probe gene function in a more physiological setting. Often, the main obstacle in this path of enquiry is to achieve the desired genetic modification. In this short review, we will focus on gene perturbation in mammalian cells and how editing and differentiation of pluripotent stem cells can complement more traditional approaches. Additionally, we introduce novel targeted protein degradation approaches as an alternative to DNA/RNA-based manipulation. Our aim is to present a broad overview of recent approaches and in vitro systems to study mammalian cell biology. Due to space limitations, we limit ourselves to providing the inexperienced reader with a conceptual framework on how to use these tools, and for more in-depth information, we will provide specific references throughout.

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration

There are currently no treatments for geographic atrophy, the advanced form of age-related macular degeneration. Hence, innovative studies are needed to model this condition and prevent or delay its progression. Induced pluripotent stem cells generated from patients with geographic atrophy and healthy individuals were differentiated to retinal pigment epithelium. Integrating transcriptional profiles of 127,659 retinal pigment epithelium cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identify 445 expression quantitative trait loci in cis that are asssociated with disease status and specific to retinal pigment epithelium subpopulations. Transcriptomics and proteomics approaches identify molecular pathways significantly upregulated in geographic atrophy, including in mitochondrial functions, metabolic pathways and extracellular cellular matrix reorganization. Five significant protein quantitative trait loci that regulate protein expression in the retinal pigment epithelium and in geographic atrophy are identified - two of which share variants with cis- expression quantitative trait loci, including proteins involved in mitochondrial biology and neurodegeneration. Investigation of mitochondrial metabolism confirms mitochondrial dysfunction as a core constitutive difference of the retinal pigment epithelium from patients with geographic atrophy. This study uncovers important differences in retinal pigment epithelium homeostasis associated with geographic atrophy.

Retinal ganglion cell-specific genetic regulation in primary open-angle glaucoma

To assess the transcriptomic profile of disease-specific cell populations, fibroblasts from patients with primary open-angle glaucoma (POAG) were reprogrammed into induced pluripotent stem cells (iPSCs) before being differentiated into retinal organoids and compared with those from healthy individuals. We performed single-cell RNA sequencing of a total of 247,520 cells and identified cluster-specific molecular signatures. Comparing the gene expression profile between cases and controls, we identified novel genetic associations for this blinding disease. Expression quantitative trait mapping identified a total of 4,443 significant loci across all cell types, 312 of which are specific to the retinal ganglion cell subpopulations, which ultimately degenerate in POAG. Transcriptome-wide association analysis identified genes at loci previously associated with POAG, and analysis, conditional on disease status, implicated 97 statistically significant retinal ganglion cell-specific expression quantitative trait loci. This work highlights the power of large-scale iPSC studies to uncover context-specific profiles for a genetically complex disease.

Uncovering the cell fate decision in lysis-lysogeny transition and stem cell development via Markov state modeling

Understanding the behavior of a complex gene regulatory network is a fundamental but challenging task in systems biology. How to reduce the large number of degrees of freedom of a specific network and identify its main biological pathway is the key issue. In this paper, we utilized the transition path theory (TPT) and Markov state modeling (MSM) framework to numerically study two typical cell fate decision processes: the lysis-lysogeny transition and stem cell development. The application of TPT to the lysis-lysogeny decision-making system reveals that the competitions of CI and Cro dimer binding play the major role in determining the cell fates. We also quantified the transition rates from the lysogeny to lysis state under different conditions. The overall computational results are consistent with biological intuitions but with more detailed information. For the stem cell developmental system, we applied the MSM to reduce the original dynamics to a moderate-size Markov chain. Further spectral analysis showed that the reduced system exhibits nine metastable states, which correspond to the refinement of the five known typical cell types in development. We further investigated the dominant transition pathways corresponding to the cell differentiation, reprogramming, and trans-differentiation. A similar approach can be applied to study other biological systems.

Analysis of Clonal Composition in Human iPSC and ESC and Derived 2D and 3D Differentiated Cultures

Human induced pluripotent and embryonic stem cell cultures (hiPSC/hESC) are phenotypically heterogeneous and prone to clonal deviations during subculturing and differentiation. Clonal deviations often emerge unnoticed, but they can change the biology of the cell culture with a negative impact on experimental reproducibility. Here, we describe a computational workflow to profile the bulk clonal composition in a hiPSC/hESC culture that can also be used to infer clonal deviations. This workflow processes data obtained with two versions of the same method. The two versions-epigenetic and transcriptomic-rely on a mechanism of stochastic H3K4me3 deposition during hiPSC/hESC derivation. This mechanism generates a signature of ten or more H3K4me3-enriched clustered protocadherin (PCDH) promoters distinct in every single cell. The aggregate of single-cell signatures provides an identificatory feature in every hiPSC/hESC line. This feature is stably transmitted to the cell progeny of the culture even after differentiation unless there is a clonal deviation event that changes the internal balance of single-cell signatures. H3K4me3 signatures can be profiled by chromatin immunoprecipitation and next-generation sequencing (ChIP-seq). Alternatively, an equivalent PCDH-expression version can be profiled by RNA-seq in PCDH-expressing hiPSC/hESC-derived cells (such as neurons, astrocytes, and cardiomyocytes; and, in long-term cultures, such as cerebral organoids). Notably, our workflow can also distinguish genetically identical hiPSC/hESC lines derived from the same patient or generated in the same editing process. Together, we propose a method to improve data sharing and reproducibility in the hiPSC and hESC fields.

A Multistep Workflow to Evaluate Newly Generated iPSCs and Their Ability to Generate Different Cell Types

Induced pluripotent stem cells (iPSCs) derived from human somatic cells have created new opportunities to generate disease-relevant cells. Thus, as the use of patient-derived stem cells has become more widespread, having a workflow to monitor each line is critical. This ensures iPSCs pass a suite of quality-control measures, promoting reproducibility across experiments and between labs. With this in mind, we established a multistep workflow to assess our newly generated iPSCs. Our workflow tests four benchmarks: cell growth, genomic stability, pluripotency, and the ability to form the three germline layers. We also outline a simple test for assessing cell growth and highlight the need to compare different growth media. Genomic integrity in the human iPSCs is analyzed by G-band karyotyping and a qPCR-based test for the detection of common karyotypic abnormalities. Finally, we confirm that the iPSC lines can differentiate into a given cell type, using a trilineage assay, and later confirm that each iPSC can be differentiated into one cell type of interest, with a focus on the generation of cortical neurons. Taken together, we present a multistep quality-control workflow to evaluate newly generated iPSCs and detail the findings on these lines as they are tested within the workflow.

Balancing serendipity and reproducibility: Pluripotent stem cells as experimental systems for intellectual and developmental disorders

Reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) and their differentiation into neural lineages is a revolutionary experimental system for studying neurological disorders, including intellectual and developmental disabilities (IDDs). However, issues related to variability and reproducibility have hindered translating preclinical findings into drug discovery. Here, we identify areas for improvement by conducting a comprehensive review of 58 research articles that utilized iPSC-derived neural cells to investigate genetically defined IDDs. Based upon these findings, we propose recommendations for best practices that can be adopted by research scientists as well as journal editors.

Culture Variabilities of Human iPSC-Derived Cerebral Organoids Are a Major Issue for the Modelling of Phenotypes Observed in Alzheimer's Disease

Apolipoprotein E (APOE) is the most important susceptibility gene for late onset of Alzheimer's disease (AD), with the presence of APOE-ε4 associated with increased risk of developing AD. Here, we reprogrammed human fibroblasts from individuals with different APOE-ε genotypes into induced pluripotent stem cells (iPSCs), and generated isogenic lines with different APOE profiles. Following characterisation of the newly established iPSC lines, we used an unguided/unpatterning differentiation method to generate six-month-old cerebral organoids from all iPSC lines to assess the suitability of this in vitro system to measure APOE, β amyloid, and Tau phosphorylation levels. We identified variabilities in the organoids' cell composition between cell lines, and between batches of differentiation for each cell line. We observed more homogenous cerebral organoids, and similar levels of APOE, β amyloid, and Tau when using the CRISPR-edited APOE isogenic lines, with the exception of one site of Tau phosphorylation which was higher in the APOE-ε4/ε4 organoids. These data describe that pathological hallmarks of AD are observed in cerebral organoids, and that their variation is mainly independent of the APOE-ε status of the cells, but associated with the high variability of cerebral organoid differentiation. It demonstrates that the cell-line-to-cell-line and batch-to-batch variabilities need to be considered when using cerebral organoids.

Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells

BACKGROUND

The discovery that somatic cells can be reprogrammed to induced pluripotent stem cells (iPSCs) has provided a foundation for in vitro human disease modelling, drug development and population genetics studies. Gene expression plays a critical role in complex disease risk and therapeutic response. However, while the genetic background of reprogrammed cell lines has been shown to strongly influence gene expression, the effect has not been evaluated at the level of individual cells which would provide significant resolution. By integrating single cell RNA-sequencing (scRNA-seq) and population genetics, we apply a framework in which to evaluate cell type-specific effects of genetic variation on gene expression.

RESULTS

Here, we perform scRNA-seq on 64,018 fibroblasts from 79 donors and map expression quantitative trait loci (eQTLs) at the level of individual cell types. We demonstrate that the majority of eQTLs detected in fibroblasts are specific to an individual cell subtype. To address if the allelic effects on gene expression are maintained following cell reprogramming, we generate scRNA-seq data in 19,967 iPSCs from 31 reprogramed donor lines. We again identify highly cell type-specific eQTLs in iPSCs and show that the eQTLs in fibroblasts almost entirely disappear during reprogramming.

CONCLUSIONS

This work provides an atlas of how genetic variation influences gene expression across cell subtypes and provides evidence for patterns of genetic architecture that lead to cell type-specific eQTL effects.

Transcriptomic Profiling of Human Pluripotent Stem Cell-derived Retinal Pigment Epithelium over Time

Human pluripotent stem cell (hPSC)-derived progenies are immature versions of cells, presenting a potential limitation to the accurate modelling of diseases associated with maturity or age. Hence, it is important to characterise how closely cells used in culture resemble their native counterparts. In order to select appropriate time points of retinal pigment epithelium (RPE) cultures that reflect native counterparts, we characterised the transcriptomic profiles of the hPSC-derived RPE cells from 1- and 12-month cultures. We differentiated the human embryonic stem cell line H9 into RPE cells, performed single-cell RNA-sequencing of a total of 16,576 cells to assess the molecular changes of the RPE cells across these two culture time points. Our results indicate the stability of the RPE transcriptomic signature, with no evidence of an epithelial–mesenchymal transition, and with the maturing populations of the RPE observed with time in culture. Assessment of Gene Ontology pathways revealed that as the cultures age, RPE cells upregulate expression of genes involved in metal binding and antioxidant functions. This might reflect an increased ability to handle oxidative stress as cells mature. Comparison with native human RPE data confirms a maturing transcriptional profile of RPE cells in culture. These results suggest that long-term in vitro culture of RPE cells allows the modelling of specific phenotypes observed in native mature tissues. Our work highlights the transcriptional landscape of hPSC-derived RPE cells as they age in culture, which provides a reference for native and patient samples to be benchmarked against.

Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing

The libraries generated by high-throughput single cell RNA-sequencing (scRNA-seq) platforms such as the Chromium from 10× Genomics require considerable amounts of sequencing, typically due to the large number of cells. The ability to use these data to address biological questions is directly impacted by the quality of the sequence data. Here we have compared the performance of the Illumina NextSeq 500 and NovaSeq 6000 against the BGI MGISEQ-2000 platform using identical Single Cell 3′ libraries consisting of over 70 000 cells generated on the 10× Genomics Chromium platform. Our results demonstrate a highly comparable performance between the NovaSeq 6000 and MGISEQ-2000 in sequencing quality, and the detection of genes, cell barcodes, Unique Molecular Identifiers. The performance of the NextSeq 500 was also similarly comparable to the MGISEQ-2000 based on the same metrics. Data generated by both sequencing platforms yielded similar analytical outcomes for general single-cell analysis. The performance of the NextSeq 500 and MGISEQ-2000 were also comparable for the deconvolution of multiplexed cell pools via variant calling, and detection of guide RNA (gRNA) from a pooled CRISPR single-cell screen. Our study provides a benchmark for high-capacity sequencing platforms applied to high-throughput scRNA-seq libraries.

Robust protocol for feeder-free adaptation of cryopreserved human pluripotent stem cells

Human pluripotent stem cells (hPSCs) are conventionally maintained on mouse embryonic fibroblast (MEF) feeder layers. However, downstream applications, such as directed differentiation protocols, are primarily optimized for feeder-free cultures. Therefore, hPSCs must often be adapted to feeder-free conditions. Here we propose a novel feeder-free adaptation protocol using StemFlex medium, which can be directly applied to thawed hPSC lines.The direct feeder-free adaptation protocol using StemFlex culture medium on Geltrex coating led to robust hPSC cultures in approximately 2 weeks. This approach was tested with three human embryonic stem cell (hESC) lines. All lines were confirmed to be pluripotent, expressing POU5F1, SOX2, and NANOG. No chromosomal imbalances were induced by the feeder-free adaptation.StemFlex medium enabled the efficient adaptation of hPSCs to feeder-free conditions directly after thawing. This protocol is easy to implement in laboratories that perform feeder-free cultures, allowing more convenient adaptation and more robust expansion of cryopreserved hPSCs, even in cases when sample quality is low or unknown.