Characterization Of Transcriptome Research Articles

017 Epigenetic and transcriptomic characterization of skin homing CLA+ CD4+ T-cells in atopic dermatitis and psoriasis

017 Epigenetic and transcriptomic characterization of skin homing CLA+ CD4+ T-cells in atopic dermatitis and psoriasis

Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3

We developed an automated high-throughput Smart-seq3 (HT Smart-seq3) workflow that integrates best practices and an optimized protocol to enhance efficiency, scalability, and method reproducibility. This workflow consistently produces high-quality data with high cell capture efficiency and gene detection sensitivity. In a rigorous comparison with the 10X platform using human primary CD4 + T-cells, HT Smart-seq3 demonstrated higher cell capture efficiency, greater gene detection sensitivity, and lower dropout rates. Additionally, when sufficiently scaled, HT Smart-seq3 achieved a comparable resolution of cellular heterogeneity to 10X. Notably, through T-cell receptor (TCR) reconstruction, HT Smart-seq3 identified a greater number of productive alpha and beta chain pairs without the need for additional primer design to amplify full-length V(D)J segments, enabling more comprehensive TCR profiling across a broader range of species. Taken together, HT Smart-seq3 overcomes key technical challenges, offering distinct advantages that position it as a promising solution for the characterization of single-cell transcriptomes and immune repertoires, particularly well-suited for low-input, low-RNA content samples.

Dyna-vivo-seq unveils cellular RNA dynamics during acute kidney injury via in vivo metabolic RNA labeling-based scRNA-seq

A fundamental objective of genomics is to track variations in gene expression program. While metabolic RNA labeling-based single-cell RNA sequencing offers insights into temporal biological processes, its limited applicability only to in vitro models challenges the study of in vivo gene expression dynamics. Herein, we introduce Dyna-vivo-seq, a strategy that enables time-resolved dynamic transcription profiling in vivo at the single-cell level by examining new and old RNAs. The new RNAs can offer an additional dimension to reveal cellular heterogeneity. Leveraging new RNAs, we discern two distinct high and low metabolic labeling populations among proximal tubular (PT) cells. Furthermore, we identify 90 rapidly responding transcription factors during the acute kidney injury in female mice, highlighting that high metabolic labeling PT cells exhibit heightened susceptibility to injury. Dyna-vivo-seq provides a powerful tool for the characterization of dynamic transcriptome at the single-cell level in living organism and holds great promise for biomedical applications.

Leveraging homologous recombination deficiency for sarcoma : Unravelling homologous recombination repair deficiency and therapeutic opportunities in soft tissue and bone sarcoma.

Homologous recombination deficiency (HRD) in tumors correlates with poor prognosis and metastases development. Determining HRD is of major clinical relevance as it can be treated with PARP inhibitors (PARPi). HRD remains poorly investigated in sarcoma, arare and heterogeneous cancer of mesenchymal origin. We aimed (i)to investigate predictive biomarkers of HRD in several independent sarcoma cohorts using across-functional strategy by combining genomic, transcriptomic and phenotypic approaches and (ii)to evaluate the therapeutic potential of PARPi and DNA damage response (DDR)-based therapies ex vivo. We performed acomprehensive genomic and transcriptomic characterization of sarcoma using datasets from The Cancer Genome Atlas (TCGA) and Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and our own bone and soft tissue sarcoma cohorts. We evaluated PARP1/2 and WEE1 inhibition ex vivo in patient-derived sarcoma cell models as monotherapy and in combination with chemotherapeutic agents to identify synergistic effects. Firstly, we identified genomic traits of HRD in asubset of sarcomas associated with molecular alterations in homologous recombination repair (HRR) pathway genes and high chromosomal instability. Secondly, we identified and validated distinct SARC-HRD transcriptional signatures that predicted sensitivity to PARPi. Finally, we showed functional defects in HRR in sarcoma cells that were associated with functional dependency towards PARPi and WEE1i and support the clinical use of RAD51 as apredictive biomarker for PARPi sensitivity. We provide apersonalized oncological approach to potentially improve the treatment of sarcoma patients. We encourage the evaluation of gene expression signatures to enhance the identification of patients who might benefit from DDR-based therapies.

TLR8 agonist selgantolimod regulates Kupffer cell differentiation status and impairs HBV entry into hepatocytes via an IL-6-dependent mechanism

ObjectiveAchieving HBV cure will require novel combination therapies of direct-acting antivirals and immunomodulatory agents. In this context, the toll-like receptor 8 (TLR8) agonist selgantolimod (SLGN) has been investigated in preclinical...

HistoSPACE: Histology-inspired spatial transcriptome prediction and characterization engine

Spatial transcriptomics (ST) enables the visualization of gene expression within the context of tissue morphology. This emerging discipline has the potential to serve as a foundation for developing tools to design precision medicines. However, due to the higher costs and expertise required for such experiments, its translation into a regular clinical practice might be challenging. Despite implementing modern deep learning to enhance information obtained from histological images using AI, efforts have been constrained by limitations in the diversity of information. In this paper, we developed a model, HistoSPACE, that explores the diversity of histological images available with ST data to extract molecular insights from tissue images. Further, our approach allows us to link the predicted expression with disease pathology. Our proposed study built an image encoder derived from a universal image autoencoder. This image encoder was connected to convolution blocks to build the final model. It was further fine-tuned with the help of ST-Data. The number of model parameters is small and requires lesser system memory and relatively lesser training time. Making it lightweight in comparison to traditional histological models. Our developed model demonstrates significant efficiency compared to contemporary algorithms, revealing a correlation of 0.56 in leave-one-out cross-validation. Finally, its robustness was validated through an independent dataset, showing similar prediction with predefined disease pathology. Our code is available at https://github.com/samrat-lab/HistoSPACE.

The first chicken oocyte nucleus whole transcriptomic profile defines the spectrum of maternal mRNA and non-coding RNA genes transcribed by the lampbrush chromosomes.

Lampbrush chromosomes, with their unusually high rate of nascent RNA synthesis, provide a valuable model for studying mechanisms of global transcriptome up-regulation. Here, we obtained a whole-genomic profile of transcription along the entire length of all lampbrush chromosomes in the chicken karyotype. With nuclear RNA-seq, we obtained information about a wider set of transcripts, including long non-coding RNAs retained in the nucleus and stable intronic sequence RNAs. For a number of protein-coding genes, we visualized their nascent transcripts on the lateral loops of lampbrush chromosomes by RNA-FISH. The set of genes transcribed on the lampbrush chromosomes is required for basic cellular processes and is characterized by a broad expression pattern. We also present the first high-throughput transcriptome characterization of miRNAs and piRNAs in chicken oocytes at the lampbrush chromosome stage. Major targets of predicted piRNAs include CR1 and long terminal repeat (LTR) containing retrotransposable elements. Transcription of tandem repeat arrays was demonstrated by alignment against the whole telomere-to-telomere chromosome assemblies. We show that transcription of telomere-derived RNAs is initiated at adjacent LTR elements. We conclude that hypertranscription on the lateral loops of giant lampbrush chromosomes is required for synthesizing large amounts of transferred to the embryo maternal RNA for thousands of genes.

Physiological and transcriptomic characterization of cold acclimation in endodormant grapevine under different temperature regimes.

It is essential for the survival of grapevines in cool climate viticultural regions where vines properly acclimate in late fall and early winter and develop freezing tolerance. Climate change-associated abnormities in temperature during the dormant season, including oscillations between prolonged warmth in late fall and extreme cold in midwinter, impact cold acclimation and threaten the sustainability of the grape and wine industry. We conducted two experiments in controlled environment to investigate the impacts of different temperature regimes on cold acclimation ability in endodormant grapevine buds through a combination of freezing tolerance-based physiological and RNA-seq-based transcriptomic monitoring. Results show that exposure to a constant temperature, whether warm (22 and 11°C), moderate (7°C), or cool (4 and 2°C) was insufficient for triggering cold acclimation and increasing freezing tolerance in dormant buds. However, when the same buds were exposed to temperature cycling (7±5°C), acclimation occurred, and freezing tolerance was increased by 5°C. We characterized the transcriptomic response of endodormant buds to high and low temperatures and temperature cycling and identified new potential roles for the ethylene pathway, starch and sugar metabolism, phenylpropanoid regulation, and protein metabolism in the genetic control of endodormancy maintenance. Despite clear evidence of temperature-responsive transcription in endodormant buds, our current understanding of the genetic control of cold acclimation remains a challenge when generalizing across grapevine tissues and phenological stages.

Clustering-independent estimation of cell abundances in bulk tissues using single-cell RNA-seq data

Single-cell RNA sequencing has transformed the study of biological tissues by enabling transcriptomic characterizations of their constituent cell states. Computational methods for gene expression deconvolution use this information to infer the cell composition of related tissues profiled at the bulk level. However, current deconvolution methods are restricted to discrete cell types and have limited power to make inferences aboutcontinuous cellular processes such as cell differentiation or immune cell activation. We present ConDecon, a clustering-independent method for inferring the likelihood for each cell in a single-cell dataset to be present in a bulk tissue. ConDecon represents an improvement in phenotypic resolution and functionality with respect to regression-based methods. Using ConDecon, we discover the implication of neurodegenerative microglia inflammatory pathways in the mesenchymal transformation of pediatric ependymoma and characterize their spatial trajectories of activation. The generality of this approach enables the deconvolution of other data modalities, such as bulk ATAC-seq data.

Effects of oxycodone on placental lineages: Evidence from the transcriptome profile of mouse trophoblast giant cells

Pregnant women are often prescribed or abuse opioid drugs. The placenta is likely the key to understanding how opioids cause adverse pregnancy outcomes. Maternal oxycodone (OXY) exposure of pregnant mice leads to disturbances in the layer of invasive parietal trophoblast giant cells (pTGC) that forms the interface between the placenta and uterus. These cells are analogous to extravillous trophoblasts of the human placenta. They are crucial to coordinating the metabolic needs of the conceptus with those of the mother and are primary participants in the placenta-brain axis. Their large nuclear size, however, has precluded both single-cell (sc) and single-nucleus (sn) RNA-seq analyses beyond embryonic day (E) 8.5. Here, we compared the transcriptomes of placentas from pregnant mice exposed to OXY with unexposed controls at E12.5, with particular emphasis on the pTGC. The nonfluidic Parse snRNA-seq approach permitted characterization of the nuclear transcriptomes of all the major placental cell lineages and their presumed progenitors at E12.5. OXY exposure had a negligible effect on components of the placental labyrinth, including the two syncytial cell layers, but caused transcriptomic changes consistent with metabolic stress throughout the spongiotrophoblast. Most notably, there was loss of the majority of pTGC, whose normal gene expression is consistent with elevated energy demand relating to biosynthesis of multiple secretory products, especially hormones, and endoduplication of DNA. This unusual sensitivity of pTGC presumably puts the pregnancy and future health of the offspring at particular risk to OXY exposure.

Spatial transcriptomics of meningeal inflammation reveals inflammatory gene signatures in adjacent brain parenchyma.

While modern high efficacy disease modifying therapies have revolutionized the treatment of relapsing-remitting multiple sclerosis, they are less effective at controlling progressive forms of the disease. Meningeal inflammation is a recognized risk factor for cortical gray matter pathology which can result in disabling symptoms such as cognitive impairment and depression, but the mechanisms linking meningeal inflammation and gray matter pathology remain unclear. Here, we performed magnetic resonance imaging (MRI)-guided spatial transcriptomics in a mouse model of autoimmune meningeal inflammation to characterize the transcriptional signature in areas of meningeal inflammation and the underlying brain parenchyma. We found broadly increased activity of inflammatory signaling pathways at sites of meningeal inflammation, but only a subset of these pathways active in the adjacent brain parenchyma. Subclustering of regions adjacent to meningeal inflammation revealed the subset of immune programs induced in brain parenchyma, notably complement signaling and antigen processing/presentation. Trajectory gene and gene set modeling analysis confirmed variable penetration of immune signatures originating from meningeal inflammation into the adjacent brain tissue. This work contributes a valuable data resource to the field, provides the first detailed spatial transcriptomic characterization in a model of meningeal inflammation, and highlights several candidate pathways in the pathogenesis of gray matter pathology.

Spatial transcriptomics of meningeal inflammation reveals inflammatory gene signatures in adjacent brain parenchyma

While modern high efficacy disease modifying therapies have revolutionized the treatment of relapsing-remitting multiple sclerosis, they are less effective at controlling progressive forms of the disease. Meningeal inflammation is a recognized risk factor for cortical gray matter pathology which can result in disabling symptoms such as cognitive impairment and depression, but the mechanisms linking meningeal inflammation and gray matter pathology remain unclear. Here, we performed magnetic resonance imaging (MRI)-guided spatial transcriptomics in a mouse model of autoimmune meningeal inflammation to characterize the transcriptional signature in areas of meningeal inflammation and the underlying brain parenchyma. We found broadly increased activity of inflammatory signaling pathways at sites of meningeal inflammation, but only a subset of these pathways active in the adjacent brain parenchyma. Subclustering of regions adjacent to meningeal inflammation revealed the subset of immune programs induced in brain parenchyma, notably complement signaling and antigen processing/presentation. Trajectory gene and gene set modeling analysis confirmed variable penetration of immune signatures originating from meningeal inflammation into the adjacent brain tissue. This work contributes a valuable data resource to the field, provides the first detailed spatial transcriptomic characterization in a model of meningeal inflammation, and highlights several candidate pathways in the pathogenesis of gray matter pathology.

Over-expression of SiADCL1 in Arabidopsis modulates folate and amino acid metabolism to impact on flowering time

Foxtail millet is a C4 crop rich in folate (FA). This study explores the roles of the 4-amino-4-deoxychorismate lyase (ADCL) – a member of the transaminase IV group of enzymes – in FA metabolism and conferred phenotypes. Phylogenetic comparisons identified diversity in the transaminase IV/ADCL gene family in the foxtail millet genome which was associated with genomic duplications. Molecular docking studies suggested that SiADCL1 bound most strongly to aminodeoxychorismate (ADC) and most likely had the highest catalytic activities. SiADCL1 which was highly expressed in roots, peduncles and flag leaves. Over-expression of SiADCL1 in Arabidopsis significantly increased total FA content (1.14–1.84 fold) and this was linked to a delayed flowering time. Metabolomic and transcriptomic characterization of the derived over-expression lines, found that FA promotes the change of methylation-related genes, ethylene synthesis, amino acid metabolism and flowering-related genes. This study revealed a potential gene coexpression network linked with FA and targeted key genes that could be exploited in foxtail millet breeding programs.

Assembly of glioblastoma tumoroids and cerebral organoids: a 3D in vitro model for tumor cell invasion.

Glioblastoma (GBM) has a fatal prognosis because of its aggressive and invasive characteristics. Understanding the mechanism of invasion necessitates an elucidation of the relationship between tumor cells and the tumor microenvironment. However, there has been a scarcity of suitable models to investigate this. In this study, we established a glioblastoma-cerebral organoid assembloid (GCOA) model by co-culturing patient-derived GBM tumoroids and human cerebral organoids. Tumor cells from the tumoroids infiltrated the cerebral organoids, mimicking the invasive nature of the parental tumors. Using time-lapse imaging, various invasion patterns of cancer cells within cerebral organoids resembling a normal tissue milieu were monitored. Both single- and collective-cell invasion was captured in real-time. We also confirmed the formation of an intercellular tumor network and tumor-normal-cell interactions. Furthermore, the transcriptomic characterization of GCOAs revealed distinct features of invasive tumor cells. Overall, this study established the GCOA as a three-dimensional (3D) in vitro assembloid model to investigate invasion mechanisms and interactions between tumor cells and their microenvironment.

A comprehensive transcriptome characterization of individual nuclear receptor pathways in the human small intestine

Nuclear receptors (NRs) are widely expressed transcription factors that bind small, lipophilic compounds and regulate diverse biological processes. In the small intestine, NRs are known to act as sensors that control transcriptional responses to endogenous and exogenous signals, yet their downstream effects have not been characterized extensively. Here, we investigate the activation of six different NRs individually in human intestinal organoids using small molecules agonists. We observe changes in key enterocyte functions such as lipid, glucose, and amino acid absorption, the regulation of electrolyte balance, and drug metabolism. Our findings reinforce PXR, LXR, FXR, and PPARα as regulators of lipid absorption. Furthermore, known hepatic effects of AHR and VDR activation were recapitulated in the human small intestine. Finally, we identify unique target genes for intestinal PXR activation (ERG28, TMEM97, and TM7SF2), LXR activation (RAB6B), and VDR activation (CA12). This study provides an unbiased and comprehensive transcriptomic description of individual NR pathways in the human small intestine. By gaining a deeper understanding of the effects of individual NRs, we might better harness their pharmacological and therapeutic potential.

Deciphering Acclimation to Sublethal Combined and Sequential Abiotic Stresses in Arabidopsis thaliana.

Plants are frequently exposed to environmental challenges. Responses to sub-lethal abiotic stress combinations are complex and often distinct from responses to individual stresses and remain poorly understood. Investigating traits and molecular factors mediating acclimation to stress combinations is essential for the development of climate change-resilient field crops. Here, we studied the morphological, physiological, and molecular responses of Arabidopsis thaliana to i) co-occurring high temperature and drought and ii) flooding followed by drought, both of which have increased in frequency due to climate change, and the individual component stresses: high temperature, drought and flooding. A set of 15 physiological and morphological traits were assessed during single and combined stresses. By combining these comprehensive trait analyses with transcriptome characterization, we established the generally additive negative effects of simultaneous or sequential stresses on plant morphology and physiology compared to the corresponding individual stresses. Although drought had a mild effect on various growth, morphological and physiological traits in both stress combinations, a unique transcriptome signature emerged upon combination with high temperature simultaneously or flooding sequentially. Molecular processes identified as important for multi-stress resilience included plastid-nucleus communication, ABA signaling and photo-acclimation. Based on the RNA-seq data, a set of 39 genes was identified as potential multi-stress response regulators. Mutants were tested to validate the contribution of these genes to plant survival and phenotypic acclimation under combined stress. We confirmed the involvement of several genes in regulating phenotypic acclimation traits. Among the identified factors were EARLY FLOWERING 6 (ELF6) and ARABIDOPSIS TÓXICOS EN LEVADURA 80 (ATL80), with substantial effects on plant growth, leaf development and plant survival (wilting) during high-temperature drought and post-submergence drought, respectively.

Deciphering the biodegradation of thiamethoxam by Phanerochaete chrysosporium with natural siderite: Synergistic mechanisms, transcriptomics characterization, and molecular simulation

Fungi play vital roles in the fate of organic pollutants, particularly when interacting with minerals in aquatic and soil environments. Mechanisms by which fungi may mitigate pollutions in fungus-mineral interactions are still unclear. Inspired by biogeochemical cycling, we constructed a range of co-culture systems to investigate synergistic effects of the white-rot fungus Phanerochaete chrysosporium and the iron-bearing mineral siderite on thiamethoxam (THX) transformation, a common neonicotinoid pesticide. Co-culturing with siderite significantly enhanced THX transformation during the initial 10 days with a dose effect, achieving 86 % removal within 25 days. Fungi could affect siderite’s dissolution, transformation, and precipitation through their biological activities. These interactions triggered physiological adaptation and resilience in fungi. Siderite could enhance the activity of fungal ligninolytic enzymes and cytochrome P450, facilitating biotransformation. Genes expression related to growth, energy metabolism, and oxidative stress response upregulated, enhancing fungal resilience to THX. The primary THX degradation pathways included nitro-reduction, C-N cleavage, and de-chlorination. Molecular dynamics simulations provided insights into catalytic mechanisms of enzyme-THX interactions. Together, siderite could act as natural enhancers that endowed fungi to resist physical and chemical stresses in environments, providing insights into contaminants attenuation, fungal biomineralization, and the coevolution of the Earth's lithosphere and biosphere.

Full-length transcriptome characterization and analysis of Carrizo Citrange and molecular insights into pathogen defense.

Citrus huanglongbing (HLB) is a major challenge that impacts the flourishing of the citrus industry. Therefore, analyzing the genomic information of HLB-resistant or tolerant citrus resources is crucial for breeding HLB-resistant citrus varieties. The Carrizo citrange, a hybrid of Citrus sinensis and Poncirus trifoliata, plays a pivotal role in citrus cultivation. However, its genetic explorations are difficult due to the absence of a reference genome or full-length transcriptome. In order to enhance our understanding of the genetic information of citrange, we conducted a full-length transcriptomic sequencing of multiple tissues from the Carrizo citrange using the PacBio Sequel II platform. Moreover, we performed gene ontology (GO) annotation, gene functional annotation, simple sequence repeats (SSR) types analysis, as well as identification of lncRNAs, alternative splicing events, and analysis of pathogen defense-related genes. Results showed that a total of 43,452 isoforms were generated, with 43,307 of them being annotated. GO annotation indicated the involvement of these isoforms in various biological processes, cellular components, and molecular functions. The coding sequence length of the isoforms ranged from 1,000 to 4,000 base pairs (bp). Moreover, we have discovered 54 varieties of transcription factors and regulators, along with 16 classifications of genes associated with resistance. Among all types of SSRs, trimer type SSRs were the most abundant. 130 lncRNAs were predicted to be highly reliable in the isoforms of the Carrizo citrange, with alternative splicing events identified, and the most frequent being retained intron. The analysis of gene family expansion and contraction revealed a significant increase in pathogen defense-related genes within the Carrizo citrange. The results of this study will be of great value for future investigations into gene function in citrange and for expanding the genetic pool for breeding citrus varieties resistant or tolerant to HLB.

Real-time and programmable transcriptome sequencing with PROFIT-seq

The high diversity and complexity of the eukaryotic transcriptome make it difficult to effectively detect specific transcripts of interest. Current targeted RNA sequencing methods often require complex pre-sequencing enrichment steps, which can compromise the comprehensive characterization of the entire transcriptome. Here we describe programmable full-length isoform transcriptome sequencing (PROFIT-seq), a method that enriches target transcripts while maintaining unbiased quantification of the whole transcriptome. PROFIT-seq employs combinatorial reverse transcription to capture polyadenylated, non-polyadenylated and circular RNAs, coupled with a programmable control system that selectively enriches target transcripts during sequencing. This approach achieves over 3-fold increase in effective data yield and reduces the time required for detecting specific pathogens or key mutations by 75%. We applied PROFIT-seq to study colorectal polyp development, revealing the intricate relationship between host immune responses and bacterial infection. PROFIT-seq offers a powerful tool for accurate and efficient sequencing of target transcripts while preserving overall transcriptome quantification, with broad applications in clinical diagnostics and targeted enrichment scenarios.

Molecular mechanisms underlying glucose-dependent insulinotropic polypeptide secretion in human duodenal organoids.

Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone secreted by enteroendocrine K cells in the proximal small intestine. This study aimed to explore the function of human K cells at the molecular and cellular levels. CRISPR-Cas9 homology-directed repair was used to insert transgenes encoding a yellow fluorescent protein (Venus) or an Epac-based cAMP sensor (Epac-S-H187) in the GIP locus in human duodenal-derived organoids. Fluorescently labelled K cells were purified by FACS for RNA-seq and peptidomic analysis. GIP reporter organoids were employed for GIP secretion assays, live-cell imaging of Ca2+ using Fura-2 and cAMP using Epac-S-H187, and basic electrophysiological characterisation. The G protein-coupled receptor genes GPR142 and CASR were knocked out to evaluate roles in amino acid sensing. RNA-seq of human duodenal K cells revealed enrichment of several G protein-coupled receptors involved in nutrient sensing, including FFAR1, GPBAR1, GPR119, CASR and GPR142. Glucose induced action potential firing and cytosolic Ca2+ elevation and caused a 1.8-fold increase in GIP secretion, which was inhibited by the sodium glucose co-transporter 1/2 (SGLT1/2) blocker sotagliflozin. Activation of the long-chain fatty acid receptor free fatty acid receptor 1 (FFAR1) induced a 2.7-fold increase in GIP secretion, while tryptophan and phenylalanine stimulated secretion by 2.8- and 2.1-fold, respectively. While CASR knockout blunted intracellular Ca2+ responses, a CASR/GPR142 double knockout was needed to reduce GIP secretory responses to aromatic amino acids. The newly generated human organoid K cell model enables transcriptomic and functional characterisation of nutrient-sensing pathways involved in human GIP secretion. Both calcium-sensing receptor (CASR) and G protein-coupled receptor 142 (GPR142) contribute to protein-stimulated GIP secretion. This model will be further used to identify potential targets for modulation of native GIP secretion in diabetes and obesity.