Cell Type-specific Changes Research Articles

#3031 Cell free DNA methylation analysis reveals cerebral cell death during hemodialysis

Abstract Background and Aims Patients treated with hemodialysis demonstrate a significant cognitive decline, likely explained by cerebrovascular disease and hypoperfusion. Despite the significant morbidity and mortality associated, no method exists to detect subclinical cerebral injury. This prevents early diagnosis and precludes mitigation strategies. Following cell death, cell free DNA (cfDNA) is released into the peripheral blood. Since DNA methylation is cell-type specific, cfDNA methylation analysis can reveal the cellular origin of cfDNA and cell-type specific changes in cell death. Here, we evaluate if subclinical cerebral ischemia during hemodialysis is detectable through cfDNA methylome analyses. Method Chronic hemodialysis patients with a high cardiovascular risk profile were studied during a single hemodialysis session. Brain tissue oxygenation was measured continuously by near-infrared spectroscopy using two sensors on the forehead. Plasma samples were taken immediately before and after hemodialysis. cfDNA was extracted from the blood plasma and converted into whole genome bisulfite sequencing libraries using tailored protocols. Next, in-solution target enrichment was applied to analyze 4,989 genomic loci, selected for showing specific methylation in one of 15 tissues or cell types. After sequencing, reads were aligned to the hg38 reference genome using BisMark, and deconvoluted using EMeth-Laplace to disclose the relative contribution of the 15 selected tissues or cell types. Results 41 hemodialysis patients participated in the study, with a mean age of 75 ± 8 years (46% male). The median ultrafiltration volume was 2.3 L (IQR 1.6-3.0 L). After targeted bisulfite sequencing and QC-based filtering, 35 patients remained for cfDNA methylation analysis. In 30 patients, cfDNA concentrations were increased following dialysis. Deconvolution analysis revealed a relative increase in granulocyte-derived cfDNA from 36.7% to 55% before versus after dialysis. Consequently, for most other tissues and cell types we observed a relative decrease in their cfDNA contribution. Interestingly, a subset of patients (n = 13) showed an increase in neuron-derived cfDNA from 0% to 0.26%, while no neuron-derived cfDNA was detectable in the remaining 22 patients. Near-infrared spectroscopy showed a significantly reduced cerebral oxygenation in these 13 patients (P < 0.0001) at 2 separate time windows during hemodialysis treatment (at 20-60 and 207-251 minutes into the session) (Fig.). Conclusion In patients with a high cardiovascular risk profile, cfDNA in peripheral blood increased after hemodialysis. cfDNA methylome analyses suggested this to be due to an increased contribution of granulocytes, indicating elevated levels of NETosis. In addition, we observed more neuron-derived cfDNA after dialysis in about 1 in 3 patients. This was most apparent in patients with a reduced brain tissue oxygenation during hemodialysis. Together, these findings suggest that hypoperfusion during hemodialysis can evoke neuronal cell death, detectable through methylome analyses of cfDNA isolated from a minimally invasively obtainable bodily fluid. Follow-up studies are ongoing to assess if this translates to progressive cognitive impairment.

FOXP1 regulates the development of excitatory synaptic inputs onto striatal neurons and induces phenotypic reversal with reinstatement.

Long-range glutamatergic inputs originating from the cortex and thalamus are indispensable for striatal development, providing the foundation for motor and cognitive functions. Despite their significance, transcriptional regulation governing these inputs remains largely unknown. We investigated the role of a transcription factor encoded by a high-risk autism-associated gene, FOXP1, in sculpting glutamatergic inputs onto spiny projection neurons (SPNs) within the striatum. We find a neuron subtype-specific role of FOXP1 in strengthening and maturing glutamatergic inputs onto dopamine receptor 2-expressing SPNs (D2 SPNs). We also find that FOXP1 promotes synaptically driven excitability in these neurons. Using single-nuclei RNA sequencing, we identify candidate genes that mediate these cell-autonomous processes through postnatal FOXP1 function at the post-synapse. Last, we demonstrate that postnatal FOXP1 reinstatement rescues electrophysiological deficits, cell type-specific gene expression changes, and behavioral phenotypes. Together, this study enhances our understanding of striatal circuit development and provides proof of concept for a therapeutic approach for FOXP1 syndrome and other neurodevelopmental disorders.

Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors

Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.

Single-cell insights: pioneering an integrated atlas of chromatin accessibility and transcriptomic landscapes in diabetic cardiomyopathy

BackgroundDiabetic cardiomyopathy (DCM) poses a growing health threat, elevating heart failure risk in diabetic individuals. Understanding DCM is crucial, with fibroblasts and endothelial cells playing pivotal roles in driving myocardial fibrosis and contributing to cardiac dysfunction. Advances in Multimodal single-cell profiling, such as scRNA-seq and scATAC-seq, provide deeper insights into DCM’s unique cell states and molecular landscape for targeted therapeutic interventions.MethodsSingle-cell RNA and ATAC data from 10x Multiome libraries were processed using Cell Ranger ARC v2.0.1. Gene expression and ATAC data underwent Seurat and Signac filtration. Differential gene expression and accessible chromatin regions were identified. Transcription factor activity was estimated with chromVAR, and Cis-coaccessibility networks were calculated using Cicero. Coaccessibility connections were compared to the GeneHancer database. Gene Ontology analysis, biological process scoring, cell-cell communication analysis, and gene-motif correlation was performed to reveal intricate molecular changes. Immunofluorescent staining utilized various antibodies on paraffin-embedded tissues to verify the findings.ResultsThis study integrated scRNA-seq and scATAC-seq data obtained from hearts of WT and DCM mice, elucidating molecular changes at the single-cell level throughout the diabetic cardiomyopathy progression. Robust and accurate clustering analysis of the integrated data revealed altered cell proportions, showcasing decreased endothelial cells and macrophages, coupled with increased fibroblasts and myocardial cells in the DCM group, indicating enhanced fibrosis and endothelial damage. Chromatin accessibility analysis unveiled unique patterns in cell types, with heightened transcriptional activity in myocardial cells. Subpopulation analysis highlighted distinct changes in cardiomyocytes and fibroblasts, emphasizing pathways related to fatty acid metabolism and cardiac contraction. Fibroblast-centered communication analysis identified interactions with endothelial cells, implicating VEGF receptors. Endothelial cell subpopulations exhibited altered gene expressions, emphasizing contraction and growth-related pathways. Candidate regulators, including Tcf21, Arnt, Stat5a, and Stat5b, were identified, suggesting their pivotal roles in DCM development. Immunofluorescence staining validated marker genes of cell subpopulations, confirming PDK4, PPARγ and Tpm1 as markers for metabolic pattern-altered cardiomyocytes, activated fibroblasts and endothelial cells with compromised proliferation.ConclusionOur integrated scRNA-seq and scATAC-seq analysis unveils intricate cell states and molecular alterations in diabetic cardiomyopathy. Identified cell type-specific changes, transcription factors, and marker genes offer valuable insights. The study sheds light on potential therapeutic targets for DCM.

SIRT1 Coordinates Transcriptional Regulation of Neural Activity and Modulates Depression-Like Behaviors in the Nucleus Accumbens

BackgroundMajor depression and anxiety disorders are significant causes of disability and socioeconomic burden. Despite the prevalence and considerable impact of these affective disorders, their pathophysiology remains elusive. Thus, there is an urgent need to develop novel therapeutics for these conditions. We evaluated the role of SIRT1 in regulating dysfunctional processes of reward by using chronic social defeat stress to induce depression- and anxiety-like behaviors. Chronic social defeat stress induces physiological and behavioral changes that recapitulate depression-like symptomatology and alters gene expression programs in the nucleus accumbens, but cell type–specific changes in this critical structure remain largely unknown. MethodsWe examined transcriptional profiles of D1-expressing medium spiny neurons (MSNs) lacking deacetylase activity of SIRT1 by RNA sequencing in a cell type–specific manner using the RiboTag line of mice. We analyzed differentially expressed genes using gene ontology tools including SynGO and EnrichR and further demonstrated functional changes in D1-MSN–specific SIRT1 knockout (KO) mice using electrophysiological and behavioral measurements. ResultsRNA sequencing revealed altered transcriptional profiles of D1-MSNs lacking functional SIRT1 and showed specific changes in synaptic genes including glutamatergic and GABAergic (gamma-aminobutyric acidergic) receptors in D1-MSNs. These molecular changes may be associated with decreased excitatory and increased inhibitory neural activity in Sirt1 KO D1-MSNs, accompanied by morphological changes. Moreover, the D1-MSN–specific Sirt1 KO mice exhibited proresilient changes in anxiety- and depression-like behaviors. ConclusionsSIRT1 coordinates excitatory and inhibitory synaptic genes to regulate the GABAergic output tone of D1-MSNs. These findings reveal a novel signaling pathway that has potential for the development of innovative treatments for affective disorders.

DiffGR: Detecting Differentially Interacting Genomic Regions from Hi-C Contact Maps

Abstract Recent advances in high-throughput chromosome conformation capture (Hi-C) techniques have allowed us to map genome-wide chromatin interactions and uncover higher-order chromatin structures, thereby shedding light on the principles of genome architecture and functions. However, statistical methods for detecting changes in large-scale chromatin organization such as topologically associating domains (TADs) are still lacking. We proposed a new statistical method, DiffGR, for detecting differentially interacting genomic regions at the TAD level between Hi-C contact maps. We utilized the stratum-adjusted correlation coefficient to measure similarity of local TAD regions. We then developed a nonparametric approach to identify statistically significant changes of genomic interacting regions. Through simulation studies, we demonstrated that DiffGR can robustly and effectively discover differential genomic regions under various conditions. Furthermore, we successfully revealed cell type-specific changes in genomic interacting regions in both human and mouse Hi-C datasets, and illustrated that DiffGR yielded consistent and advantageous results compared with state-of-the-art differential TAD detection methods. The DiffGR R package is published under the GNU General Public License (GPL) ≥ 2 license and is publicly available at https://github.com/wmalab/DiffGR.

Abstract 1463: Characterizing inflammation-induced epigenetic and transcriptomic alterations driving NSCLC using lung organoid models

Abstract Chronic inflammation is a major driver of lung cancer and contributes to its pathogenesis by inducing genetic and epigenetic alterations. These, in turn, modulate the microenvironment to facilitate emergence of tumor promoting immune evasive mechanisms. The evolution of epigenetic events and their role, both alone, and in association with lung cancer specific genetic drivers in initiation of lung cancer is not well delineated. Specific pathological subtypes of non-small cell lung cancer (NSCLC) have distinct cells of origin, suggestive of cell type-specific changes in driving their development. We employed lung organoid models with chronic exposure to cigarette smoke condensate (CSC) to elucidate sequential, cell type-specific epigenetic and transcriptomic alterations and their role in co-operating with genetic events to drive development of NSCLC. We examined epigenomic and transcriptomic alterations over a 6-month exposure period by DNA methylation arrays, ATAC-seq, and RNA-seq. We observe that CSC exposure causes distinct morphological changes in organoid structure and composition, accompanied by an increase in proliferative potential. Using flow cytometry and immunofluorescent staining approaches, we demonstrate a chronic inflammation-driven shift in stem cell populations accompanied by reduction in differentiated cell types. Bulk and single-cell RNA sequencing approaches identified distinct temporal changes in transcriptional signatures in CSC exposed organoids suggestive of evolution of an immune evasive and pro-tumorigenic phenotype. Gene set enrichment analysis revealed a downregulation of interferon signaling and upregulation of Myc targets and oxidative phosphorylation pathways in CSC treated organoids. Notably, co-culturing organoids with key immune cell populations, demonstrate the ability of the CSC exposed organoids to modulate shifts in immune cells from a pro- to anti- inflammatory state. In accordance with this shift in immune cell phenotype, CSC treated organoids secreted decreased levels of pro-inflammatory cytokines as measured by multiplex ELISA assays. Genome wide DNA methylation analysis reveal that CSC methylated genes were associated with differentiation and cell fate commitment as well as transcription factor activity. Finally, we demonstrate that introduction of key NSCLC-specific driver events at the 6-month time point sensitize only CSC treated organoids to tumor formation in vivo, leading to the development of distinct genetic driver-specific subtypes of NSCLC. Altogether, our results demonstrate the ability of chronic inflammation to drive key cell type-specific transcriptomic and epigenetic changes leading to the development of distinct subtypes of NSCLC. Our findings will help identify molecular correlates for early detection and aid development of novel therapeutic strategies for disease interception. Citation Format: Na Wang, Kara Lombardo, Raksha Padaki, Ray-Whay Chiu Yen, Malcolm V. Brock, Leslie Cope, Hariharan Easwaran, Stephen B. Baylin, Michelle Vaz. Characterizing inflammation-induced epigenetic and transcriptomic alterations driving NSCLC using lung organoid models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1463.

The impact of ovarian stimulation on the human endometrial microenvironment.

How does ovarian stimulation (OS), which is used to mature multiple oocytes for ART procedures, impact the principal cellular compartments and transcriptome of the human endometrium in the periovulatory and mid-secretory phases? During the mid-secretory window of implantation, OS alters the abundance of endometrial immune cells, whereas during the periovulatory period, OS substantially changes the endometrial transcriptome and impacts both endometrial glandular and immune cells. Pregnancies conceived in an OS cycle are at risk of complications reflective of abnormal placentation and placental function. OS can alter endometrial gene expression and immune cell populations. How OS impacts the glandular, stromal, immune, and vascular compartments of the endometrium, in the periovulatory period as compared to the window of implantation, is unknown. This prospective cohort study carried out between 2020 and 2022 included 25 subjects undergoing OS and 25 subjects in natural menstrual cycles. Endometrial biopsies were performed in the proliferative, periovulatory, and mid-secretory phases. Blood samples were processed to determine serum estradiol and progesterone levels. Both the endometrial transcriptome and the principal cellular compartments of the endometrium, including glands, stroma, immune, and vasculature, were evaluated by examining endometrial dating, differential gene expression, protein expression, cell populations, and the three-dimensional structure in endometrial tissue. Mann-Whitney U tests, unpaired t-tests or one-way ANOVA and pairwise multiple comparison tests were used to statistically evaluate differences. In the periovulatory period, OS induced high levels of differential gene expression, glandular-stromal dyssynchrony, and an increase in both glandular epithelial volume and the frequency of endometrial monocytes/macrophages. In the window of implantation during the mid-secretory phase, OS induced changes in endometrial immune cells, with a greater frequency of B cells and a lower frequency of CD4 effector T cells. The data underlying this article have been uploaded to the Genome Expression Omnibus/National Center for Biotechnology Information with accession number GSE220044. A limited number of subjects were included in this study, although the subjects within each group, natural cycle or OS, were homogenous in their clinical characteristics. The number of subjects utilized was sufficient to identify significant differences; however, with a larger number of subjects and additional power, we may detect additional differences. Another limitation of the study is that proliferative phase biopsies were collected in natural cycles, but not in OS cycles. Given that the OS cycle subjects did not have known endometrial factor infertility, and the comparisons involved subjects who had a similar and robust response to stimulation, the findings are generalizable to women with a normal response to OS. OS substantially altered the periovulatory phase endometrium, with fewer transcriptomic and cell type-specific changes in the mid-secretory phase. Our findings show that after OS, the endometrial microenvironment in the window of implantation possesses many more similarities to that of a natural cycle than does the periovulatory endometrium. Further investigation of the immune compartment and the functional significance of this cellular compartment under OS conditions is warranted. Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases (R01AI148695 to A.M.B. and N.C.D.), Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD109152 to R.A.), and the March of Dimes (5-FY20-209 to R.A.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or March of Dimes. All authors declare no conflict of interest.

ScDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

Beyond Quiescent and Active: Intermediate Microglial Transcriptomic States in a Mouse Model of Down Syndrome.

Research on microglia in Down syndrome (DS) has shown that microglial activation, increased inflammatory gene expression, and oxidative stress occur at different ages in DS brains. However, most studies resulted in simplistic definitions of microglia as quiescent or active, ignoring potential intermediate states. Indeed, recent work on microglial cells in young DS brains indicated that those evolve through different intermediate activation phenotypes before reaching a fully activated state. Here we used single nucleus RNA sequencing, to examine how trisomy affects microglial states in the Ts65Dn mouse model of DS. Despite no substantial changes in the proportion of glial populations, differential expression analysis revealed cell type-specific gene expression changes, most notably in astroglia, microglia, and oligodendroglia. Focusing on microglia, we identified differential expression of genes associated with different microglial states, including disease-associated microglia (DAMs), activated response microglia (ARMs), and human Alzheimer's disease microglia (HAMs), in trisomic microglia. Furthermore, pseudotime analysis reveals a unique reactivity profile in Ts65Dn microglia, with fewer in a homeostatic state and more in an intermediate aberrantly reactive state than in euploid microglia. This comprehensive understanding of microglial transcriptional dynamics sheds light on potential pathogenetic mechanisms but also possible avenues for therapy for neurodevelopmental disorders.

Single-cell RNA sequencing reveals critical modulators of extracellular matrix of penile cavernous cells in erectile dysfunction

Erectile dysfunction (ED) is a common and difficult to treat disease, and has a high incidence rate worldwide. As a marker of vascular disease, ED usually occurs in cardiovascular disease, 2–5 years prior to cardiovascular disease events. The extracellular matrix (ECM) network plays a crucial role in maintaining cardiac homeostasis, not only by providing structural support, but also by promoting force transmission, and by transducing key signals to intracardiac cells. However, the relationship between ECM and ED remains unclear. To help fill this gap, we profiled single-cell RNA-seq (scRNA-seq) to obtain transcriptome maps of 82,554 cavernous single cells from ED and non-ED samples. Cellular composition of cavernous tissues was explored by uniform manifold approximation and projection. Pseudo-time cell trajectory combined with gene enrichment analysis were performed to unveil the molecular pathways of cell fate determination. The relationship between cavernous cells and the ECM, and the changes in related genes were elucidated. The CellChat identified ligand-receptor pairs (e.g., PTN-SDC2, PTN-NCL, and MDK-SDC2) among the major cell types in the cavernous tissue microenvironment. Differential analysis revealed that the cell type-specific transcriptomic changes in ED are related to ECM and extracellular structure organization, external encapsulating structure organization, and regulation of vasculature development. Trajectory analysis predicted the underlying target genes to modulate ECM (e.g., COL3A1, MDK, MMP2, and POSTN). Together, this study highlights potential cell–cell interactions and the main regulatory factors of ECM, and reveals that genes may represent potential marker features of ED progression.

Single cell transcriptome analysis of the THY-Tau22 mouse model of Alzheimer’s disease reveals sex-dependent dysregulations

Alzheimer’s disease (AD) progression and pathology show pronounced sex differences, but the factors driving these remain poorly understood. To gain insights into early AD-associated molecular changes and their sex dependency for tau pathology in the cortex, we performed single-cell RNA-seq in the THY-Tau22 AD mouse model. By examining cell type-specific and cell type-agnostic AD-related gene activity changes and their sex-dimorphism for individual genes, pathways and cellular sub-networks, we identified both statistically significant alterations and interpreted the upstream mechanisms controlling them. Our results confirm several significant sex-dependent alterations in gene activity in the THY-Tau22 model mice compared to controls, with more pronounced alterations in females. Both changes shared across multiple cell types and cell type-specific changes were observed. The differential genes showed significant over-representation of known AD-relevant processes, such as pathways associated with neuronal differentiation, programmed cell death and inflammatory responses. Regulatory network analysis of these genes revealed upstream regulators that modulate many of the downstream targets with sex-dependent changes. Most key regulators have been previously implicated in AD, such as Egr1, Klf4, Chchd2, complement system genes, and myelin-associated glycoproteins. Comparing with similar data from the Tg2576 AD mouse model and human AD patients, we identified multiple genes with consistent, cell type-specific and sex-dependent alterations across all three datasets. These shared changes were particularly evident in the expression of myelin-associated genes such as Mbp and Plp1 in oligodendrocytes. In summary, we observed significant cell type-specific transcriptomic changes in the THY-Tau22 mouse model, with a strong over-representation of known AD-associated genes and processes. These include both sex-neutral and sex-specific patterns, characterized by consistent shifts in upstream master regulators and downstream target genes. Collectively, these findings provide insights into mechanisms influencing sex-specific susceptibility to AD and reveal key regulatory proteins that could be targeted for developing treatments addressing sex-dependent AD pathology.

Cell-type-specific cis-regulatory divergence in gene expression and chromatin accessibility revealed by human-chimpanzee hybrid cells.

Although gene expression divergence has long been postulated to be the primary driver of human evolution, identifying the genes and genetic variants underlying uniquely human traits has proven to be quite challenging. Theory suggests that cell-type-specific cis-regulatory variants may fuel evolutionary adaptation due to the specificity of their effects. These variants can precisely tune the expression of a single gene in a single cell-type, avoiding the potentially deleterious consequences of trans-acting changes and non-cell type-specific changes that can impact many genes and cell types, respectively. It has recently become possible to quantify human-specific cis-acting regulatory divergence by measuring allele-specific expression in human-chimpanzee hybrid cells-the product of fusing induced pluripotent stem (iPS) cells of each species in vitro. However, these cis-regulatory changes have only been explored in a limited number of cell types. Here, we quantify human-chimpanzee cis-regulatory divergence in gene expression and chromatin accessibility across six cell types, enabling the identification of highly cell-type-specific cis-regulatory changes. We find that cell-type-specific genes and regulatory elements evolve faster than those shared across cell types, suggesting an important role for genes with cell-type-specific expression in human evolution. Furthermore, we identify several instances of lineage-specific natural selection that may have played key roles in specific cell types, such as coordinated changes in the cis-regulation of dozens of genes involved in neuronal firing in motor neurons. Finally, using novel metrics and a machine learning model, we identify genetic variants that likely alter chromatin accessibility and transcription factor binding, leading to neuron-specific changes in the expression of the neurodevelopmentally important genes FABP7 and GAD1. Overall, our results demonstrate that integrative analysis of cis-regulatory divergence in chromatin accessibility and gene expression across cell types is a promising approach to identify the specific genes and genetic variants that make us human.

Single-cell transcriptomics reveals that glial cells integrate homeostatic and circadian processes to drive sleep–wake cycles

The sleep–wake cycle is determined by circadian and sleep homeostatic processes. However, the molecular impact of these processes and their interaction in different brain cell populations are unknown. To fill this gap, we profiled the single-cell transcriptome of adult Drosophila brains across the sleep–wake cycle and four circadian times. We show cell type-specific transcriptomic changes, with glia displaying the largest variation. Glia are also among the few cell types whose gene expression correlates with both sleep homeostat and circadian clock. The sleep–wake cycle and sleep drive level affect the expression of clock gene regulators in glia, and disrupting clock genes specifically in glia impairs homeostatic sleep rebound after sleep deprivation. These findings provide a comprehensive view of the effects of sleep homeostatic and circadian processes on distinct cell types in an entire animal brain and reveal glia as an interaction site of these two processes to determine sleep–wake dynamics.

Regional- and cell type-specific changes of the human brain during aging

As individuals age, cognitive decline becomes more prominent, concomitant with an elevated susceptibility to neurodegenerative diseases and dementia. Additionally, symptoms of chronic neuropsychiatric diseases tend to worsen with age. It is crucial to highlight that the aging process does not affect individuals uniformly, and its effects can vary, even within the same person. This review aims to summary the impact of healthy aging on the human brain, focusing on the variations from different brain regions and cell types. Depending on specific brain regions, the brain exhibits thinning, volume reduction, regional shrinkage, disrupted tissue integrity, decreased cell complexity, or iron accumulation during aging. Moreover, the brain cells exhibit morphology and function changes during aging. Neurons undergo changes characterized by reduced dendrites, dendritic spines, and axons with less compact myelin sheaths, leading to a significant loss of synapses. Comparatively, glia often transform into a reactive phenotype.

Single-Cell Histone Modification Profiling with Cell Enrichment Using sortChIC.

Histone post-translational modifications (PTMs) influence the overall structure of the chromatin and gene expression. Over the course of cell differentiation, the distribution of histone modifications is remodeled, resulting in cell type-specific patterns. In the past, their study was limited to abundant cell types that could be purified in necessary numbers. However, studying these cell type-specific dynamic changes in heterogeneous in vivo settings requires sensitive single-cell methods. Current advances in single-cell sequencing methods remove these limitations, allowing the study of nonpurifiable cell types. One complicating factor is that some of the most biologically interesting cell types, including stem and progenitor cells that undergo differentiation, only make up a small fraction of cells in a tissue. This makes whole-tissue analysis rather inefficient. In this chapter, we present a sort-assisted single-cell Chromatin ImmunoCleavage sequencing technique (sortChIC) to map histone PTMs in single cells. This technique combines the mapping of histone PTM location in combination with surface staining-based enrichment, to allow the integration of established strategies for rare cell type enrichment. In general terms, this will enable researchers to quantify local and global chromatin changes in dynamic complex biological systems and can provide additional information on their contribution to lineage and cell-type specification in physiological conditions and disease.

Single Cell RNASeq Analysis of AD and Control Post Mortem Brain Samples

Alzheimer’s disease (AD) is a devastative late life disease, molecularly characterized by biochemical lesions of amyloid β plaques and Tau tangles. the 2nd most frequent one worldwide with no early detection methods/cure. I have applied single cell sequencing and analysed post mortem brain samples (using a Chromium machine) from 2 AD and 2 control frontal cortex samples. All the samples had ethics approval, and the RNA was tested for quality. The samples were obtained from the Edenborough MRC brain bank. Very few genes have been linked to far to AD (mainly through GWAS studies [1]). Overall, I quantified about 24,000 nuclei. Using statistical, bioinformatics and computational analyses I have detected significant differential expression changes in astrocyte, neuronal and microglial marker genes. I also conducted network analyses. The percentage of reads passing filter was slightly low (68%). Overall output was a bit lower than optimal. There was still over 1.6Bn clusters generated though, which is within the specification for an S1 flow-cell, and base call quality (quality control) was excellent: 97% >Q30. The read counts mapping to genome occupancy rate was also fairy low (63-81%). The number of barcodes is as follows: sample 1 (AD, Braak I-II) - 6,223 sample 2 (control) 6,262 sample 3 (AD Braak I-II) 5,332 sample 4 (AD, Braak I-II) 5,332 as well. The data is available for download under the GEO (accession number GSE175814). to assess global and cell-type specific gene expression impacts in Alzheimer’s versus control brain samples, we performed a holistic comparison of matching cell populations in AD and controls with the software cell Harmony. To identify possible gene regulatory network underlying transcriptional regulation in these distinct populations, we further explored prior evidenced transcription factor targets relationships from cell Harmony. Importantly, we observe both common and cell-type specific core transcription factors regulators, with both enriched downstream targets and regulated transcription factors. Upregulated networks in Astrocytes were associated with broad regulation by HIF1A, SOX2, NRF1, and RB1. the proportion of endothelial cells was higher in the Alzheimer’s disease samples than the neurological control samples. results reveal that the cell type-specific transcriptomic changes in Alzheimer’s disease are associated with 4 molecular pathways: angiogenesis in endothelial cells, immune response in endothelial cells and microglia, myelination in oligodendrocytes, and synaptic signalling in astrocytes and neurons. I also compared the results with microarray data from large cohort studies that examined samples from the prefrontal cortex (Alzheimer’s disease: n = 310; Neurological controls: n = 157) or temporal cortex (Alzheimer’s disease: n = 106; Neurological controls: n = 135). Among the DEGs identified in our snRNA-seq analysis, 1,113 and 764 genes were significantly differentially expressed in the microarray data from the prefrontal cortex and temporal cortex, respectively. subcluster analysis of microglia identified 13 subpopulations; VGF signalling was also found as changed. In the future, imaging of post mortem Alzheimer’s patients may verify brain cellular morphology/cell volume of vascular changes in the Alzheimer’s compared to control samples. My study findings [2] may open new venues to our understanding of the disease underlying molecular processes and cellular signaling. Regarding the glial cell changes, our main conclusion is that the glial cells may be reactive in the disease and not causal.

High-capacity sample multiplexing for single cell chromatin accessibility profiling

Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.

Deciphering the Genomic Regulatory Architecture of iPSC Derived Oligodendrocytes from Diverse Ancestries for Alzheimer’s Disease Studies

AbstractBackgroundThe effect of variants associated with Alzheimer’s disease (AD) can be influenced by ancestry, which determines the genomic regulatory architecture (GRA). A global understanding of GRA in the context of AD is imperative to interpret the variability associated with AD risk genes across populations. Most studies up to date have focused on studying GRA in European ancestry, in this study we aimed at determining the GRA in African, Amerindian, and European ancestries. Since GRA is cell specific, we developed a human induced pluripotent cells (hiPSC) based model for oligodendrocytes (OLs), a cell type which has limited studies focused on AD.MethodCells from AD patients or non‐cognitively impaired controls with >90% of either Amerindian, African or European global ancestry were differentiated using a modified multi‐stage protocol that promotes the development and enrichment of oligodendrocytes in neural spheroids. After terminal differentiation, cells were collected and lysed to isolate nuclei for Multiomic profiling of chromatin accessibility and transcriptome using Single Cell ATAC and Single Cell RNA‐seq. Additionally, we examined chromatin interactions using Hi‐C analyses.ResultWe identified oligodendrocyte lineage cells at different stages of development ranging from dividing cells with transcriptional profiles consistent with those of oligodendrocyte precursor cells (OPC) to mature myelinating oligodendrocytes. We compared the oligodendrocytes clusters across ancestries, cases versus controls and APOE genotypes to characterize the genomic landmarks and signatures associated with AD related GWAS loci. Astrocytes and neurons were also derived within our 3D spheroids, allowing us to study ancestry‐related cell type specific changes in GRA.ConclusionOur results provide ancestry‐specific insights into oligodendrocyte chromatin structure and gene regulation in the context of AD. These results offer an integrated view of the GRA of a previously overlooked cell lineage that constitute a large population in the central nervous system and is compromised during AD in terms of abundance and function. This will expand the available functional resources for gene identification studies in African American and Hispanic/Latino studies.

Early life adversity shapes social subordination and cell type-specific transcriptomic patterning in the ventral hippocampus.

Adverse events in early life can modulate the response to additional stressors later in life and increase the risk of developing psychiatric disorders. The underlying molecular mechanisms responsible for these effects remain unclear. Here, we uncover that early life adversity (ELA) in mice leads to social subordination. Using single-cell RNA sequencing (scRNA-seq), we identified cell type-specific changes in the transcriptional state of glutamatergic and GABAergic neurons in the ventral hippocampus of ELA mice after exposure to acute social stress in adulthood. These findings were reflected by an alteration in excitatory and inhibitory synaptic transmission induced by ELA in response to acute social stress. Finally, enhancing the inhibitory network function through transient diazepam treatment during an early developmental sensitive period reversed the ELA-induced social subordination. Collectively, this study significantly advances our understanding of the molecular, physiological, and behavioral alterations induced by ELA, uncovering a previously unknown cell type-specific vulnerability to ELA.