Type-specific Gene Expression Patterns Research Articles

Establishment of single-cell transcriptional states during seed germination

Germination involves highly dynamic transcriptional programs as the cells of seeds reactivate and express the functions necessary for establishment in the environment. Individual cell types have distinct roles within the embryo, so must therefore have cell type-specific gene expression and gene regulatory networks. We can better understand how the functions of different cell types are established and contribute to the embryo by determining how cell type-specific transcription begins and changes through germination. Here we describe a temporal analysis of the germinating Arabidopsis thaliana embryo at single-cell resolution. We define the highly dynamic cell type-specific patterns of gene expression and how these relate to changing cellular function as germination progresses. Underlying these are unique gene regulatory networks and transcription factor activity. We unexpectedly discover that most embryo cells transition through the same initial transcriptional state early in germination, even though cell identity has already been established during embryogenesis. Cells later transition to cell type-specific gene expression patterns. Furthermore, our analyses support previous findings that the earliest events leading to the induction of seed germination take place in the vasculature. Overall, our study constitutes a general framework with which to characterize Arabidopsis cell transcriptional states through seed germination, allowing investigation of different genotypes and other plant species whose seed strategies may differ.

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC.

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Abstract IA13: Molecular and genomic mechanisms of estrogen signaling and gene regulation in breast cancer

Abstract Transcriptional enhancers function as nucleation sites for the assembly of transcription-regulating complexes across the genome, which act to drive cell type-specific patterns of gene expression. Although many features of active enhancers [e.g., H3K4me1, H3K27ac, enrichment of p300/CBP and Mediator, and production of enhancer RNAs (eRNAs)] have been defined by genomic assays, the roles of these features in estrogen receptor alpha (ERa) enhancer function are not well understood. We are interested in how the molecular underpinnings of ERa enhancer formation and activity control the gene expression programs that drive breast cancer phenotypes and responses to therapeutic agents. We have used a variety of molecular, biochemical, genomic, genetic, and computational approaches to determine the following aspects of ERa enhancers biology in hormone-responsive breast cancer cells: (1) where ERa enhancers are formed across the genome, (2) the kinetics of ERa enhancer formation and disassembly, (3) the influence of genetic variation on ERa enhancer function, (4) the role of the enhancer features noted above in ERa enhancer function, and (5) how protein complexes and small polypeptides serve as coregulators to drive ERa transcriptional activity. Our current focus has been on eRNAs, which are poorly characterized noncoding RNAs that are thought to regulate enhancer function and gene expression. We have identified a ~40 nucleotide functional eRNA regulatory motif (FERM) present in many estrogen-regulated eRNAs that promotes gene expression by increasing ERα recruitment and stimulating p300-catalyzed H3K27 acetylation. In addition, we have been examining how the dose of estrogen impacts the efficiency of enhancer assembly by ERα. Finally, we have been exploring the role of PARP1, a ubiquitous chromatin-associated regulator, and small polypeptides derived from “non-coding” RNAs, control ERa enhancer function. In all cases, we perform analyses to link enhancer function to gene expression outcomes and breast cancer biology. Collectively, our results demonstrate the biological and mechanistic roles of eRNAs in breast cancer. This work is supported by grants from the NIH/NIDDK (DK058110) and CPRIT (RP160319) to W.L.K. Citation Format: W. Lee Kraus. Molecular and genomic mechanisms of estrogen signaling and gene regulation in breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr IA13.

Identifying potential therapeutic targets in lung adenocarcinoma: a multi-omics approach integrating bulk and single-cell RNA sequencing with Mendelian randomization.

Our research aimed to identify new therapeutic targets for Lung adenocarcinoma (LUAD), a major subtype of non-small cell lung cancer known for its low 5-year survival rate of 22%. By employing a comprehensive methodological approach, we analyzed bulk RNA sequencing data from 513 LUAD and 59 non-tumorous tissues, identifying 2,688 differentially expressed genes. Using Mendelian randomization (MR), we identified 74 genes with strong evidence for a causal effect on risk of LUAD. Survival analysis on these genes revealed significant differences in survival rates for 13 of them. Our pathway enrichment analysis highlighted their roles in immune response and cell communication, deepening our understanding. We also utilized single-cell RNA sequencing (scRNA-seq) to uncover cell type-specific gene expression patterns within LUAD, emphasizing the tumor microenvironment's heterogeneity. Pseudotime analysis further assisted in assessing the heterogeneity of tumor cell populations. Additionally, protein-protein interaction (PPI) network analysis was conducted to evaluate the potential druggability of these identified genes. The culmination of our efforts led to the identification of five genes (tier 1) with the most compelling evidence, including SECISBP2L, PRCD, SMAD9, C2orf91, and HSD17B13, and eight genes (tier 2) with convincing evidence for their potential as therapeutic targets.

Single-Cell RNA-Seq Reveals Changes in Cell Subsets in the Cortical Microenvironment during Acute Phase of Ischemic Stroke Rats.

Ischemic stroke, the most common stroke type, has threatened human life and health. Currently, intravenous thrombolysis and endovascular thrombectomy are the mainstream treatment methods, but they may cause cerebral ischemia-reperfusion injury (CIRI), which aggravates brain injury. Consequently, it is worthwhile to start with a study of CIRI mechanism to identify better prevention and treatment methods. Applying single-cell RNA sequencing (scRNA-seq) technology to further understand the biological functions of various cell types in CIRI will facilitate the intervention of CIRI. This study aimed to establish a rat middle cerebral artery occlusion (MCAO) model to simulate cerebral ischemia-reperfusion, perform enzymatic hydrolysis, and suspend cerebral cortex tissue edema. Single-cell transcriptome sequencing was used, combined with cluster analysis, t-distributed stochastic neighbor embedding (t-SNE) visualization, and other bioinformatics methods to distinguish cell subgroups while using gene ontology (GO) function enrichment and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment to reveal the biological function of each cell subgroup. We identified 21 brain clusters with cell type-specific gene expression patterns and cell subpopulations, as well as 42 marker genes representing different cell subpopulations. The number of cells in clusters 0-3 increased significantly in MCAO group compared to that in the sham group, and nine-cell subpopulations exhibited remarkable differences in the number of genes. Subsequently, GO and KEGG analyses were performed on the top 40 differentially expressed genes (DEGs) in the six cell subpopulations with significant differences. These results indicate that biological processes and signaling pathways are involved in different cell subpopulations. ScRNA-seq revealed the diversity of cell differentiation and the unique information of cell subpopulations in the cortex of rats with acute ischemic stroke, providing novel insight into the pathological process and drug discovery in stroke.

69-LB: Sex-Specific Dynamics of GLP-1R and GIPR Expression in the Hypothalamus and the Amygdala of Mice

GIPR:GLP-1R co-agonism improves obesity and cardio-metabolic disease with superior efficacy in both male and female mice compared to mono-agonism. We detected sex-specific differences in metabolic phenotypes, which may point to differing sensitivity for GLP-1R and/or GIPR in areas of the hypothalamus regulating energy balance (ARC, VMH, DMH) and in areas of the amygdala regulating cardiovascular functions. To optimize future therapeutic benefits and minimize side effects from a perspective of sex differences, we investigated whether GLP1R and GIPR expression levels in specific cell populations of the hypothalamus and the amygdala regions are co-determined by sex and diet. Female and male C57Bl6 mice were fed normal chow or 58% high fat diet (HFD) for 21 days (n = 4, total mouse number 16). Spatial transcriptomics by in-situ hybridization method RNAscope™ was combined with immunofluorescence staining for neurons (NeuN), astrocytes (GFAP) and microglia (iba1) to identify cell type specific gene expression patterns of GLP1R and GIPR in female and male brains. In the hypothalamus, both sexes, gene expression of GLP-1R was higher compared to GIPR (ARC, VMH and DMH). In our studies GLP-1R and GIPR were mostly expressed in neurons, marginally in microglia and not observed in astrocytes in both sexes. HFD exposure reduced GLP-1R and GIPR gene expression in males only. In the Amygdala, neuronal GIPR gene expression levels were higher compared to GLP-1R in both sexes. HFD reduced GIPR and GLP-1R gene expression in males only. In females, HFD induced a slight increase of GIPR gene expression specifically in the central and basolateral amygdala. Our results reveal sex-specific dynamics in GLP-1R and GIPR expression patterns in metabolically relevant areas of the hypothalamus and the amygdala induced by HFD exposure. This may imply sex-specific dosing regimens of GIP:GLP-1R co-agonists for future treatments of cardio-metabolic disease Disclosure S. M. Hofmann: None. S. Zhang: None. R. Tom: None. T. D. Müller: Research Support; Novo Nordisk A/S, Speaker's Bureau; Eli Lilly and Company, AstraZeneca, Mercodia AB, Stock/Shareholder; Novo Nordisk A/S, Eli Lilly and Company. M. H. Tschöp: Consultant; Boehringer Ingelheim Pharma GmbH&Co. KG.

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

Cell type specific transcriptomic differences in depression show similar patterns between males and females but implicate distinct cell types and genes

Major depressive disorder (MDD) is a common, heterogenous, and potentially serious psychiatric illness. Diverse brain cell types have been implicated in MDD etiology. Significant sexual differences exist in MDD clinical presentation and outcome, and recent evidence suggests different molecular bases for male and female MDD. We evaluated over 160,000 nuclei from 71 female and male donors, leveraging new and pre-existing single-nucleus RNA-sequencing data from the dorsolateral prefrontal cortex. Cell type specific transcriptome-wide threshold-free MDD-associated gene expression patterns were similar between the sexes, but significant differentially expressed genes (DEGs) diverged. Among 7 broad cell types and 41 clusters evaluated, microglia and parvalbumin interneurons contributed the most DEGs in females, while deep layer excitatory neurons, astrocytes, and oligodendrocyte precursors were the major contributors in males. Further, the Mic1 cluster with 38% of female DEGs and the ExN10_L46 cluster with 53% of male DEGs, stood out in the meta-analysis of both sexes.

Abstract 2111: Identification of molecular markers of pseudomyxoma peritonei using integrative analysis of bulk and single cell RNA-seq data

Abstract Backgrounds: Psuedomyxoma peritonei (PMP) is a rare colon disease, whose symptoms and treatments have been numerously investigated, however, there are insufficient known diagnostic or prognostic markers. Here, we aim to identify molecular markers exhibiting distinct characteristics of PMP. Methods: We analyzed RNA-seq data to identify gene signatures associated with PMP development using 19 fresh frozen tissue samples including 12 PMPs (discovery cohort). For validation, we applied those signatures into an independent cohort containing 34 formalin-fixed paraffin embedded (FFPE) samples including 25 PMPs (validation cohort). We also verified protein expression levels in the signature using immunohistochemical staining (IHC) in other independent cohort in PMP. Additionally, a transcriptomic profiling using single-cell RNA-seq was carried out to confirm the cell type-specific gene expression patterns in a separated patient group with five PMPs. Results: In the discovery cohort of fresh-frozen tissues, unsupervised hierarchical clustering analysis exhibited a distinct gene expression pattern clearly dichotomizing normal and PMP samples. Genes involved in cell movement or immune response were highly expressed in PMPs. Interestingly, we found that PMP disease had a molecular heterogeneity showing epithelial as well as mesenchymal characteristics, in which both CDH1 and CDH2 were significantly elaborated in PMPs. We also estimated protein expression levels of PMP-associated key markers using IHC, in which a significant positive correlation between transcript and protein expressions in CDH1, whereas we could not observe such a significance but a clear tendency toward highly expression of CDH2 in PMPs. However, in a single-cell RNA-seq analysis, we discovered distinct eight cell type-specific clusters including an epithelial cell group, in which CDH1 was highly expressed, and a mesenchymal cell group, in which CDH2 showed a significant higher expression pattern, suggesting that PMP show dual molecular characteristics of epithelial as well as mesenchymal. Conclusion: We explore genetic characteristics and suggest key markers of PMP development. Our findings would be practically utilized for clinical practice in PMP diagnosis or prognosis. Citation Format: Seong-Hwan Park, Hanyong Go, Jae-Yoon Kim, Seon-Young Kim, Jong Lyul Lee, Ye Jin Ha, Seon-Kyu Kim. Identification of molecular markers of pseudomyxoma peritonei using integrative analysis of bulk and single cell RNA-seq data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2111.

TET2 Loss Conspires with MYC to Foster Lymphomagenesis

Programmed DNA methylation patterning serves the generation and maintenance of cell identity, and represents a major barrier against transformation. TET dioxygenases (TET1-3) facilitate DNA demethylation at enhancers, promoting chromatin accessibility and cell type-specific gene expression patterns. Work from our and other labs had shown that TET enzymes settle B lymphocyte identity and warrant antibody-mediated immunity. Due to the prevalence of TET2 mutations in hematological and immune cell tumors, often identified as loss-of-function (LOF) versions, TET2 LOF is considered a cancer driver. Intriguingly, although showing a predisposition for blood cancer, healthy humans carrying TET2 mutations in hematopoietic stem cells can remain cancer-free for decades despite increasing clonal dominance of the affected cells and their offspring, a condition termed clonal hematopoiesis. Furthermore, mice deficient for TET2 only rarely develop tumors. This scenario suggests roles for TET2 LOF as cancer facilitator, rather than driver. In B lymphocytes, the MYC oncoprotein is a potent driver of malignancy. However, therapeutic targeting of MYC is far from reaching the clinic. Thus, establishing functional links between MYC and dependencies imposed by TET2 LOF should provide information on the molecular mechanisms of predisposition, and guide clinical practice and targeted therapy in the future. To address whether TET2 LOF conspires with MYC, we employed the prototypic EμMYC transgenic mouse model, where enforced MYC overexpression early in the B lymphocyte lineage drives lymphomas, but additional hits are required for full transformation. Confirming a tumor suppressor role for TET2, partial or complete loss of the protein accelerated lymphomagenesis, and facilitated specifically the outgrowth of IgM+ lymphomas. The premalignant IgM+ population contained a higher fraction of cells with double strand breaks (EμMYC 2,5% vs. EμMYCTet2+/- or EμMYCTet2-/- 6%) and in the S/G2/M cell cycle phases (EμMYC 15% vs. EμMYCTet2+/- or EμMYCTet2-/- 25%), along with higher spontaneous apoptosis rates (EμMYC 4% vs. EμMYCTet2+/- or EμMYCTet2-/- 7%). Mechanistically, in the context of MYC overexpression, TET2 LOF associates with enhanced JAK/STAT signaling and selective upregulation of the pro-survival BCL2 family protein BCLX. To recapitulate alternative scenarios of TET2 LOF in diffuse large B cell lymphoma (DLBCL), a tumor that originates from germinal center B lymphocytes, we established two preclinical mouse models, (1) either with TET2 LOF in the germline to mimic the scenario of clonal hematopoiesis along with ectopic MYC expression restricted to germinal center B lymphocytes, or (2) using a fully conditional approach where we synchronize ectopic MYC expression and TET2 LOF specifically in germinal center B lymphocytes. In line with the results from the EμMYC model, germline heterozygous Tet2 loss (scenario (1)) sufficed to boost MYC-driven lymphomagenesis, a phenotype that is strongly enhanced by the absence of both Tet2 alleles. Germinal center-specific elimination of Tet2 in scenario (2) also produced lymphomas, however, heterozygous Tet2 loss in germinal center B lymphocytes was not sufficient to unleash MYC-driven lymphomagenesis. Our data from three powerful MYC-driven mouse models suggest (i) that TET2 loss in B lymphocytes nudges MYC-mediated transformation, (ii) that TET2 loss, early on in hematopoietic stem cells, potentiates the transformative potential later on in B lymphocytes, and (iii) that TET2 loss dampens apoptosis during transformation and in established lymphomas, potentially via JAK/STAT signaling and BCLX. Altogether, we provide novel in vivo evidence that TET2 prevents MYC-mediated transformation in B lymphocytes, and our results produced testable dependencies. Beyond MYC-driven blood cancer, TET2 LOF in hematopoietic stem cells predisposes to all-cause mortality in humans. Thus, identifying targetable vulnerabilities of TET2 LOF will serve healthy aging.

Single nucleus transcriptomic analysis of rat nucleus accumbens reveals cell type-specific patterns of gene expression associated with volitional morphine intake

Opioid exposure is known to cause transcriptomic changes in the nucleus accumbens (NAc). However, no studies to date have investigated cell type-specific transcriptomic changes associated with volitional opioid taking. Here, we use single nucleus RNA sequencing (snRNAseq) to comprehensively characterize cell type-specific alterations of the NAc transcriptome in rats self-administering morphine. One cohort of male Brown Norway rats was injected with acute morphine (10 mg/kg, i.p.) or saline. A second cohort of rats was allowed to self-administer intravenous morphine (1.0 mg/kg/infusion) for 10 consecutive days. Each morphine-experienced rat was paired with a yoked saline control rat. snRNAseq libraries were generated from NAc punches and used to identify cell type-specific gene expression changes associated with volitional morphine taking. We identified 1106 differentially expressed genes (DEGs) in the acute morphine group, compared to 2453 DEGs in the morphine self-administration group, across 27 distinct cell clusters. Importantly, we identified 1329 DEGs that were specific to morphine self-administration. DEGs were identified in novel clusters of astrocytes, oligodendrocytes, and D1R- and D2R-expressing medium spiny neurons in the NAc. Cell type-specific DEGs included Rgs9, Celf5, Oprm1, and Pde10a. Upregulation of Rgs9 and Celf5 in D2R-expressing neurons was validated by RNAscope. Approximately 85% of all oligodendrocyte DEGs, nearly all of which were associated with morphine taking, were identified in two subtypes. Bioinformatic analyses identified cell type-specific upstream regulatory mechanisms of the observed transcriptome alterations and downstream signaling pathways, including both novel and previously identified molecular pathways. These findings show that volitional morphine taking is associated with distinct cell type-specific transcriptomic changes in the rat NAc and highlight specific striatal cell populations and novel molecular substrates that could be targeted to reduce compulsive opioid taking.

Single‐cell nucleic acid sequencing reinforces to reveal signal‐ dependent pathways contributing to cellular heterogeneity

Single‐cell nucleic acid sequencing reinforces to reveal signal‐ dependent pathways contributing to cellular heterogeneity

Characterizing cis-regulatory elements using single-cell epigenomics.

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

Single-Cell Transcriptomic Analysis of the Mouse Pancreas: Characteristic Features of Pancreatic Ductal Cells in Chronic Pancreatitis.

Chronic pancreatitis (CP) is a fibroinflammatory disorder of the pancreas. Our understanding of CP pathogenesis is partly limited by the incomplete characterization of pancreatic cell types. Here, we performed single-cell RNA sequencing on 3825 cells from the pancreas of one control mouse and mice with caerulein-induced CP. An analysis of the single-cell transcriptomes revealed 16 unique clusters and cell type-specific gene expression patterns in the mouse pancreas. Sub-clustering of the pancreatic mesenchymal cells from the control mouse revealed four clusters of cells with specific gene expression profiles (combinatorial expressions of Smoc2, Cxcl14, Tnfaip6, and Fn1). We observed that immune cells in the pancreas of the CP mice were abundant and diverse in cellular type. Compared to the control, 547 upregulated genes (including Mmp7, Ttr, Rgs5, Adh1, and Cldn2) and 257 downregulated genes were identified in ductal cells from the CP group. The elevated expression levels of MMP7 and TTR were further verified in the pancreatic ducts of CP patients. This study provides a preliminary description of the single-cell transcriptome profiles of mouse pancreata and accurately demonstrates the characteristics of pancreatic ductal cells in CP. The findings provide insight into novel disease-specific biomarkers and potential therapeutic targets of CP.

Cell type-specific differential expression in Alzheimer’s disease and cancer using spatial transcriptomics

Abstract Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. The detection of genes that are differentially expressed across tissue context for cell types of interest is an essential challenge for dissecting pathological mechanisms. However, changes in cell type composition across space and measurement contamination from other cell types introduce complex statistical challenges. Here, we introduce a statistical method, Generalized Linear Admixture Models for Differential Expression (GLAMDE), that estimates cell type-specific patterns of differential gene expression while accounting for localization of other cell types. By modeling spatial transcriptomics gene expression as an additive mixture, across cell types, of generalized log-linear functions, we provide a unified framework for identifying gene expression changes for a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Our approach enables statistical inference across multiple samples and replicates. We demonstrate, through simulations and validation experiments on Slide-seq and MERFISH data, that our approach accurately identifies cell type-specific differential gene expression with valid uncertainty quantification. Lastly, we apply GLAMDE to characterize spatially-localized tissue changes in the context of disease. In an Alzheimer’s mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. GLAMDE is available within the spacexr R package. D.C. was supported by a Fannie and John Hertz Foundation Fellowship and an NSF Graduate Research Fellowship. This work was supported by an NIH Early Independence Award (DP5, 1DP5OD024583 to F.C.), the NHGRI (R01, R01HG010647 to F.C.), as well as the Burroughs Wellcome Fund, the Searle Scholars Award, and the Merkin Institute to F.C.. R.A.I. was supported by NIH grants R35GM131802 and R01HG005220.

The molecular understanding of super-enhancer dysregulation in cancer.

ABSTRACTAbnormalities in the regulation of gene expression are associated with various pathological conditions. Among the distal regulatory elements in the genome, the activation of target genes by enhancers plays a central role in the formation of cell type–specific gene expression patterns. Super-enhancers are a subclass of enhancers that frequently contain multiple enhancer-like elements and are characterized by dense binding of master transcription factors and Mediator complexes and high signals of active histone marks. Super-enhancers have been studied in detail as important regulatory regions that control cell identity and contribute to the pathogenesis of diverse diseases. In cancer, super-enhancers have multifaceted roles by activating various oncogenes and other cancer-related genes and shaping characteristic gene expression patterns in cancer cells. Alterations in super-enhancer activities in cancer involve multiple mechanisms, including the dysregulation of transcription factors and the super-enhancer–associated genomic abnormalities. The study of super-enhancers could contribute to the identification of effective biomarkers and the development of cancer therapeutics targeting transcriptional addiction. In this review, we summarize the roles of super-enhancers in cancer biology, with a particular focus on hematopoietic malignancies, in which multiple super-enhancer alteration mechanisms have been reported.

Genome-wide expression of the residual lung reacting to experimental Pneumonectomy

BackgroundAcute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq).ResultsHistological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P-value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of “Extrinsic apoptotic signaling pathway” (FDR q = 7.60 × 10− 3) and “Response to insulin” (FDR q = 7.60 × 10− 3) genes, along with an enrichment of genes involved as “Negative regulators of DDX58/IFIH1 signaling” (FDR q = 7.50 × 10− 4) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections.ConclusionThis translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Cellular Complexity of Hemochorial Placenta: Stem Cell Populations, Insights from scRNA-seq, and SARS-CoV-2 Susceptibility.

Purpose of ReviewThe placenta is a transient organ that forms de novo and serves a critical role in supporting fetal growth and development. Placental oxygen, nutrients, and waste are transported through processes that depend on vascular structure and cell type-specific expression and localization of membrane transporters. Understanding how the placenta develops holds great significance for maternal–fetal medicine. The purpose of this review is to examine current information regarding placental progenitor populations.Recent FindingsRecent advancements in single-cell RNA sequencing (scRNA-seq) provide unprecedented depth for the investigation of cell type-specific gene expression patterns in the placenta. Thus far, several mouse placenta scRNA-seq studies have been conducted which produced and analyzed transcriptomes of placental progenitors and cells of the fully developed placenta between embryonic day (E) 7.0 and E12.5. Together with human placenta scRNA-seq data which, in part, has been produced through coordinated research campaigns in the scientific community to understand the potential for SARS-CoV-2 infection, these mammalian studies lend fundamental insight into the cellular and molecular composition of hemochorial placentae found in both mouse and human.SummarySingle-cell placenta research has advanced understanding of tissue-resident stem cells and molecules that are poised to support maternal–fetal communication and nutrient transport. Herein, we provide context for these recent findings by reviewing placental anatomy and cell populations, and discuss recent scRNA-seq mouse placenta findings. Further research is needed to evaluate the utility of placental stem cells in the development of new therapeutic approaches for the treatment of wound healing and disease.

Polycomb Requires Chaperonin Containing TCP-1 Subunit 7 for Maintaining Gene Silencing in Drosophila.

In metazoans, heritable states of cell type-specific gene expression patterns linked with specialization of various cell types constitute transcriptional cellular memory. Evolutionarily conserved Polycomb group (PcG) and trithorax group (trxG) proteins contribute to the transcriptional cellular memory by maintaining heritable patterns of repressed and active expression states, respectively. Although chromatin structure and modifications appear to play a fundamental role in maintenance of repression by PcG, the precise targeting mechanism and the specificity factors that bind PcG complexes to defined regions in chromosomes remain elusive. Here, we report a serendipitous discovery that uncovers an interplay between Polycomb (Pc) and chaperonin containing T-complex protein 1 (TCP-1) subunit 7 (CCT7) of TCP-1 ring complex (TRiC) chaperonin in Drosophila. CCT7 interacts with Pc at chromatin to maintain repressed states of homeotic and non-homeotic targets of PcG, which supports a strong genetic interaction observed between Pc and CCT7 mutants. Depletion of CCT7 results in dissociation of Pc from chromatin and redistribution of an abundant amount of Pc in cytoplasm. We propose that CCT7 is an important modulator of Pc, which helps Pc recruitment at chromatin, and compromising CCT7 can directly influence an evolutionary conserved epigenetic network that supervises the appropriate cellular identities during development and homeostasis of an organism.

Master regulators as order parameters of gene expression states.

Cell type-specific gene expression patterns are represented as memory states of a Hopfield neural network model. It is shown that order parameters of this model can be interpreted as concentrations of master transcription regulators that form concurrent positive feedback loops with a large number of downstream regulated genes. The order parameter free energy then defines an epigenetic landscape in which local minima correspond to stable cell states. The model is applied to gene expression data in the context of hematopoiesis.