Search

Secretion levels required of industrial Chinese hamster ovary (CHO) cell lines can challenge endoplasmic reticulum (ER) homeostasis, and ER stress caused by accumulation of misfolded proteins can be a bottleneck in biomanufacturing. The unfolded protein response (UPR) is initiated to restore homeostasis in response to ER stress, and optimization of the UPR can improve CHO cell production of therapeutic proteins. We compared the fed-batch growth, production characteristics, and transcriptomic response of an immunoglobulin G1 (IgG1) producer to its parental, non-producing host cell line. We conducted differential gene expression analysis using high throughput RNA sequencing (RNASeq) and quantitative polymerase chain reaction (qPCR) to study the ER stress response of each cell line during fed-batch culture. The UPR was activated in the IgG1 producer compared to the host cell line and our analysis of differential expression profiles indicated transient upregulation of ATF6α target mRNAs in the IgG1 producer, suggesting two upstream regulators of the ATF6 arm of the UPR, ATF6β and WFS1, are rational engineering targets. Although both ATF6β and WFS1 have been reported to negatively regulate ATF6α, this study shows knockdown of either target elicits different effects in an IgG1-producing CHO cell line. Stable knockdown of ATF6β decreased cell growth without decreasing titer; however, knockdown of WFS1 decreased titer without affecting growth. Relative expression measured by qPCR indicated no direct relationship between ATF6β and WFS1 expression, but upregulation of WFS1 in one pool was correlated with decreased growth and upregulation of ER chaperone mRNAs. While knockdown of WFS1 had negative impacts on UPR activation and product mRNA expression, knockdown of ATF6β improved the UPR specifically later in fed-batch leading to increased overall productivity. [ABSTRACT FROM AUTHOR]

Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients. [ABSTRACT FROM AUTHOR]

Genetic variations in the ovine ovulation rate, which are associated with the FecB mutation, provide useful models by which to explore the mechanisms regulating the development of mammalian antral follicles. In order to study the effects of the FecB mutation on cumulus cell differentiation, preovulatory follicles were aspirated and cumulus cells were isolated from three FecB genotypes (homozygous, heterozygous and wild type) of Small Tail Han (STH) sheep superstimulated with FSH. Transcriptome information from tens of thousands of cumulus cells was determined with the 10 × Genomics single-cell RNA-seq technology. Under the superovulation treatment, the observed number of preovulatory follicles in the ovaries of FecB carriers was still significantly higher than that in the wild-type (P < 0.05). The expression patterns of cumulus cells differed between FecB carriers and wild-type ewes. The screened cumulus cells could also be further divided into different cell clusters, and the differentiation states and fates of each group of cumulus cells also remained different, which supports the notion that heterogeneity in gene expression is prevalent in single cells. The oxidative phosphorylation pathway was significantly enriched in differentially expressed genes among the cell differentiation branch nodes of cumulus cells and among the differentially expressed genes of cumulus cells from the three genotypes. Combined with the important role of oxidative phosphorylation in the maturation of COCs, we suggest that the oxidative phosphorylation pathway of cumulus cells plays a crucial role in the differentiation process of cumulus cells and the mutation effect of the FecB gene. [ABSTRACT FROM AUTHOR]

It has been found that progression from leukoplakia to head and neck squamous cell carcinoma (HNSCC) is a long-term process that may involve changes in the multicellular ecosystem. We acquired scRNA-seq samples information from gene expression omnibus and UCSC Xena database. The BEAM function was used to construct the pseudotime trajectory and analyze the differentially expressed genes in different branches. We used the ssGSEA method to explore the correlation between each cell subgroup and survival time, and obtained the cell subgroup related to prognosis. During the progression from leukoplakia to HNSCC, we found several prognostic cell subgroups, such as AURKB + epithelial cells, SFRP1 + fibroblasts, SLC7A8 + macrophages, FCER1A + CD1C + dendritic cells, and TRGC2 + NK/T cells. All cell subgroups had two different fates, one tending to cell proliferation, migration, and enhancement of angiogenesis capacity, and the other tending to inflammatory immune response, leukocyte chemotaxis, and T cell activation. Tumor-promoting genes such as CD163 and CD209 were highly expressed in the myeloid cells, and depletion marker genes such as TIGIT, LAG3 were highly expressed in NK/T cells. Our study may provide a reference for the molecular mechanism of HNSCC and theoretical basis for the development of new therapeutic strategies. [ABSTRACT FROM AUTHOR]

Natural killer (NK) cells play essential roles in the tumor development, diagnosis, and prognosis of tumors. In this study, we aimed to establish a reliable signature based on marker genes in NK cells, thus providing a new perspective for assessing immunotherapy and the prognosis of patients with gastric cancer (GC). We analyzed a total of 1560 samples retrieved from the public database. We performed a comprehensive analysis of single-cell RNA-sequencing (scRNA-seq) data of gastric cancer and identified 377 marker genes for NK cells. By performing Cox regression analysis, we established a 12-gene NK cell-associated signature (NKCAS) for the Cancer Genome Atlas (TCGA) cohort, that assigned GC patients into a low-risk group (LRG) or a high-risk group (HRG). In the TCGA cohort, the areas under curve (AUC) value were 0.73, 0.81, and 0.80 at 1, 3, and 5 years. External validation of the predictive ability for the signature was then validated in the Gene Expression Omnibus (GEO) cohorts (GSE84437). The expression levels of signature genes were measured and validated in GC cell lines by real-time PCR. Moreover, NKCAS was identified as an independent prognostic factor by multivariate analysis. We combined this with a variety of clinicopathological characteristics (age, M stage, and tumor grade) to construct a nomogram to predict the survival outcomes of patients. Moreover, the LRG showed higher immune cell infiltration, especially CD8+ T cells and NK cells. The risk score was negatively associated with inflammatory activities. Importantly, analysis of the independent immunotherapy cohort showed that the LRG had a better prognosis and immunotherapy response when compared with the HRG. The identification of NK cell marker genes in this study suggests potential therapeutic targets. Additionally, the developed predictive signatures and nomograms may aid in the clinical management of GC. [ABSTRACT FROM AUTHOR]

Fetal growth restriction (FGR) is associated with aberrant placentation and accounts for a significant proportion of perinatal deaths. microRNAs have been shown to be dysregulated in FGR. The purpose of this study was to determine microRNA-regulated molecular pathways altered using a caloric restricted mouse model of FGR. Pregnant mice were subjected to a 50% caloric restricted diet beginning at E9. At E18.5, RNA sequencing of placental tissue was performed to identify differences in gene expression between caloric restricted and control placentas. Significant differences in gene expression between caloric restricted and control placentas were observed in 228 of the 1546 (14.7%) microRNAs. Functional analysis of microRNA–mRNA interactions demonstrated enrichment of several biological pathways with oxidative stress, apoptosis, and autophagy pathways upregulated and angiogenesis and signal transduction pathways downregulated. Ingenuity pathway analysis also suggested that ID1 signaling, a pathway integral for trophoblast differentiation, is also dysregulated in caloric restricted placentas. Thus, a maternal caloric restriction mouse model of FGR results in aberrant microRNA-regulated molecular pathways associated with angiogenesis, oxidative stress, signal transduction, apoptosis, and cell differentiation. As several of these pathways are dysregulated in human FGR, our findings suggest that this model may provide an excellent means to study placental microRNA derangements seen in FGR. [ABSTRACT FROM AUTHOR]

Long interspersed nuclear elements (LINE-1s/L1s) are a group of retrotransposons that can copy themselves within a genome. In humans, it is the most successful transposon in nucleotide content. L1 expression is generally mild in normal human tissues, but the activity has been shown to increase significantly in many cancers. Few studies have examined L1 expression at single-cell resolution, thus it is undetermined whether L1 reactivation occurs solely in malignant cells within tumors. One of the cancer types with frequent L1 activity is high-grade serous ovarian carcinoma (HGSOC). Here, we identified locus-specific L1 expression with 3′ single-cell RNA sequencing in pre- and post-chemotherapy HGSOC sample pairs from 11 patients, and in fallopian tube samples from five healthy women. Although L1 expression quantification with the chosen technique was challenging due to the repetitive nature of the element, we found evidence of L1 expression primarily in cancer cells, but also in other cell types, e.g. cancer-associated fibroblasts. The expression levels were similar in samples taken before and after neoadjuvant chemotherapy, indicating that L1 transcriptional activity was unaffected by clinical platinum-taxane treatment. Furthermore, L1 activity was negatively associated with the expression of MYC target genes, a finding that supports earlier literature of MYC being an L1 suppressor. [ABSTRACT FROM AUTHOR]

Asynchronously cycling cells pose a challenge to the accurate characterization of phase-specific gene expression. Current strategies, including RNAseq, survey the steady state gene expression across the cell cycle and are inherently limited by their inability to resolve dynamic gene regulatory networks. Single cell RNAseq (scRNAseq) can identify different cell cycle transcriptomes if enough cycling cells are present, however some cells are not amenable to scRNAseq. Therefore, we merged two powerful strategies, the CDT1 and GMNN degrons used in Fluorescent Ubiquitination-based Cell Cycle Indicator (FUCCI) cell cycle sensors and the ribosomal protein epitope tagging used in RiboTrap/Tag technologies to isolate cell cycle phase-specific mRNA for sequencing. The resulting cell cycle dependent, tagged ribosomal proteins (ccTaggedRP) were differentially expressed during the cell cycle, had similar subcellular locations as endogenous ribosomal proteins, incorporated into ribosomes and polysomes, and facilitated the recovery of cell cycle phase-specific RNA for sequencing. ccTaggedRP has broad applications to investigate phase-specific gene expression in complex cell populations. [ABSTRACT FROM AUTHOR]

Immunotherapy has emerged as a promising modality for addressing advanced or conventionally drug-resistant malignancies. When it comes to lung adenocarcinoma (LUAD), T cells have demonstrated significant influence on both antitumor activity and the tumor microenvironment. However, their specific contributions remain largely unexplored. This investigation aimed to delineate molecular subtypes and prognostic indicators founded on T cell marker genes, thereby shedding light on the significance of T cells in LUAD prognosis and precision treatment. The cellular phenotypes were identified by scrutinizing the single-cell data obtained from the GEO repository. Subsequently, T cell marker genes derived from single-cell sequencing analyses were integrated with differentially expressed genes from the TCGA repository to pinpoint T cell-associated genes. Utilizing Cox analysis, molecular subtypes and prognostic signatures were established and subsequently verified using the GEO dataset. The ensuing molecular and immunological distinctions, along with therapy sensitivity between the two sub-cohorts, were examined via the ESTIMATE, CIBERSORT, and ssGSEA methodologies. Compartmentalization, somatic mutation, nomogram development, chemotherapy sensitivity prediction, and potential drug prediction analyses were also conducted according to the risk signature. Additionally, real-time qPCR and the HPA database corroborated the mRNA and protein expression patterns of signature genes in LUAD tissues. In summary, this research yielded an innovative T cell marker gene-based signature with remarkable potential to prognosis and anticipate immunotherapeutic outcomes in LUAD patients. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNAs) are linked to cancer, but it's still not clear what role they play in prostatic cancer. Through high-throughput sequencing, the goal of this study was to compare how circRNAs are expressed at different stages of prostate cancer. 12 patients attending the Department of Urology at the Second Affiliated Hospital of Nanchang University between June 2020 and October 2021 were used for RNA sequencing, and 14 patients were used for real-time fluorescent quantitative PCR (qRT-PCR). The expression profiles of prostate cancer circRNAs were constructed by sequencing with the help of next-generation high-throughput sequencing technology, and the differentially expressed circRNAs were analyzed by targeting microRNA (miRNA) loci and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the genes from which circRNAs originated. Finally, the expression of target circRNAs in two prostate tissues was verified by qRT-PCR. Following high-throughput sequencing, 13,047 circRNAs were identified, and 605 circRNAs with significant differential expression were identified, of which 361 circRNAs were up-regulated, and 244 circRNAs were down-regulated. Analysis of circRNA-originated genes using GO and the KEGG enrichment analysis showed that circRNA host genes can regulate and influence multiple signaling pathways in prostate cancer with important biological functions. And the circRNA–miRNA network was constructed. The highest number of differentially expressed circRNA-binding miRNAs were: hsa_circ_000 7582 (52), hsa_circ_000 6198 (37), hsa_circ_000 6759 (28), hsa_circ_000 5675 (25), and hsa_circ_000 2172 (22). Moreover, we further screened out the circRNA (hsa_circ_0005692) that was significantly differentially expressed and common to all groups and verified by qRT-PCR that the expression of the target circRNA (hsa_circ_0005692) was significantly downregulated in prostate cancer compared with benign prostatic hyperplasia (BPH) tissues. [ABSTRACT FROM AUTHOR]

Abiotic stresses are a significant constraint to plant production globally. Identifying stress-related genes can aid in the development of stress-tolerant elite genotypes and facilitate trait and crop manipulation. The primary aim of this study was to conduct whole transcriptome analyses of the salt-tolerant faba bean genotype, Hassawi-2, under different durations of salt stress (6 h, 12 h, 24 h, 48 h, and 72 h) at the early vegetative stage, to better understand the molecular basis of salt tolerance. After de novo assembly, a total of 140,308 unigenes were obtained. The up-regulated differentially expressed genes (DEGs) were 2380, 2863, 3057, 3484, and 4820 at 6 h, 12 h, 24 h, 48 h, and 72 h of salt stress, respectively. Meanwhile, 1974, 3436, 2371, 3502, and 5958 genes were downregulated at 6 h, 12 h, 24 h, 48 h, and 72 h of salt stress, respectively. These DEGs encoded various regulatory and functional proteins, including kinases, plant hormone proteins, transcriptional factors (TFs) basic helix-loop-helix (bHLH), Myeloblastosis (MYB), and (WRKY), heat shock proteins (HSPs), late embryogenesis abundant (LEA) proteins, dehydrin, antioxidant enzymes, and aquaporin proteins. This suggests that the faba bean genome possesses an abundance of salinity resistance genes, which trigger different adaptive mechanisms under salt stress. Some selected DEGs validated the RNA sequencing results, thus confirming similar gene expression levels. This study represents the first transcriptome analysis of faba bean leaves subjected to salinity stress offering valuable insights into the mechanisms governing salt tolerance in faba bean during the vegetative stage. This comprehensive investigation enhances our understanding of precise gene regulatory mechanisms and holds promise for the development of novel salt-tolerant faba bean salt-tolerant cultivars. [ABSTRACT FROM AUTHOR]

T cells are important in the pathogenesis of acute kidney injury (AKI), and TCR+CD4-CD8- (double negative-DN) are T cells that have regulatory properties. However, there is limited information on DN T cells compared to traditional CD4+ and CD8+ cells. To elucidate the molecular signature and spatial dynamics of DN T cells during AKI, we performed single-cell RNA sequencing (scRNA-seq) on sorted murine DN, CD4+, and CD8+ cells combined with spatial transcriptomic profiling of normal and post AKI mouse kidneys. scRNA-seq revealed distinct transcriptional profiles for DN, CD4+, and CD8+ T cells of mouse kidneys with enrichment of Kcnq5, Klrb1c, Fcer1g, and Klre1 expression in DN T cells compared to CD4+ and CD8+ T cells in normal kidney tissue. We validated the expression of these four genes in mouse kidney DN, CD4+ and CD8+ T cells using RT-PCR and Kcnq5, Klrb1, and Fcer1g genes with the NIH human kidney precision medicine project (KPMP). Spatial transcriptomics in normal and ischemic mouse kidney tissue showed a localized cluster of T cells in the outer medulla expressing DN T cell genes including Fcer1g. These results provide a template for future studies in DN T as well as CD4+ and CD8+ cells in normal and diseased kidneys. [ABSTRACT FROM AUTHOR]

Reduction in visceral adipose tissue (VAT) mass reduces body weight and metabolic disease risk in obese patients. However surgical removal of VAT is highly invasive and thus not clinically feasible. We developed an injectable ice slurry for selective reduction of adipose tissue through cryolipolysis. The aim of this study was to investigate safety, feasibility and mechanism of ice slurry-induced cryolipolysis of VAT. Perigonadal VAT in diet-induced obese mice and rats was subjected to slurry or sham treatment. Body weight and blood chemistry were monitored for 56 days post-treatment. Histological analysis and molecular studies were performed to elucidate mechanisms of fat reduction. Treatment of VAT was well tolerated in all animals. Slurry induced adipocyte cell death via selective cryolipolysis; significant weight loss was noted at day 21 post-treatment. RNA sequencing from treated VAT samples showed increased expression of genes involved in inflammation, immune response, collagen biosynthesis and wound healing, and decreased expression of adipokines. This study demonstrates that slurry treatment is safe and effective in inducing cryolipolysis of VAT and subsequent weight loss in mice. Ice slurry is promising as a minimally-invasive treatment to reduce visceral adipose tissue. [ABSTRACT FROM AUTHOR]

Senescent cells are predicted to occur and increase in animal tissues with aging. However, senescent cells in the tissues of aged animals remain to be identified. We refer to the marker genes to identify senescent cells in tissues as "age-associated genes". In this study, we searched for age-associated genes to identify senescent cells in the livers of aged animals. We performed single-cell RNA sequencing (scRNA-seq) to screen candidates for age-associated genes using young and aged rat primary hepatocytes. To remove animal species specificity, gene expression analyses in mouse livers were performed, confirming age-associated increases in the mRNA expression levels of Glipr1, Clec12a, and Phlda3. Moreover, the mRNA expression levels of Glipr1 and Phlda3 were increased by stress-induced premature senescence using doxorubicin in primary hepatocytes and livers of young mice. Transcriptome data of aged rat hepatocytes suggested that Glipr1, Clec12a, and Phlda3 were expressed in almost identical cells. Fluorescence in situ hybridization (FISH) confirmed the presence of cells with abundant Glipr1, Clec12a, and Phlda3 mRNA in 27-month-old mouse primary hepatocytes, which are considered to be senescent cells. This study is the first to identify Glipr1, Clec12a, and Phlda3 as age-associated genes in the mouse liver. [ABSTRACT FROM AUTHOR]

Cancer treatment is still challenging because the disease is often caused by multiple mutations. Although genomic studies have identified many oncogenes and tumor suppressor genes, gene sets involved in tumorigenesis remain poorly understood. Xenopus, a genus of aquatic frogs, is a useful model to identify gene sets because it can be genetically and experimentally analyzed. Here, we analyzed gene expression in tumor tissues of three individuals in Xenopus tropicalis and identified 55 differentially expressed genes (DEGs). Gene ontology (GO) analysis showed that the upregulated genes in the tumor tissues were enriched in GO terms related to the extracellular matrix and collagen fibril organization. Hierarchical clustering showed that the gene expression patterns of tumor tissues in X. tropicalis were comparable to those of human connective, soft, and subcutaneous tissue-derived cancers. Additionally, pathway analysis revealed that these DEGs were associated with multiple pathways, including the extracellular matrix, collagen fibril organization, MET signaling, and keratan sulfate. We also found that the expression tendency of some DEGs that have not been well analyzed in the cancer field clearly determines the prognosis of human cancer patients. This study provides a remarkable reference for future experimental work on X. tropicalis to identify gene sets involved in human cancer. [ABSTRACT FROM AUTHOR]

Brain disorders are leading causes of disability worldwide. Gene expression studies provide promising opportunities to better understand their etiology but it is critical that expression is studied on a cell-type level. Cell-type specific association studies can be performed with bulk expression data using statistical methods that capitalize on cell-type proportions estimated with the help of a reference panel. To create a fine-grained reference panel for the human prefrontal cortex, we performed an integrated analysis of the seven largest single nucleus RNA-seq studies. Our panel included 17 cell-types that were robustly detected across all studies, subregions of the prefrontal cortex, and sex and age groups. To estimate the cell-type proportions, we used an empirical Bayes estimator that substantially outperformed three estimators recommended previously after a comprehensive evaluation of methods to estimate cell-type proportions from brain transcriptome data. This is important as being able to precisely estimate the cell-type proportions may avoid unreliable results in downstream analyses particularly for the multiple cell-types that had low abundances. Transcriptome-wide association studies performed with permuted bulk expression data showed that it is possible to perform transcriptome-wide association studies for even the rarest cell-types without an increased risk of false positives. [ABSTRACT FROM AUTHOR]

The apicomplexan parasite Theileria annulata is transmitted by Hyalomma ticks and causes an acute lymphoproliferative disease that is invariably lethal in exotic cattle breeds. The unique ability of the schizont stage of T. annulata to transform infected leukocytes to a cancer-like phenotype and the simplicity of culturing and passaging T. annulata-transformed cells in vitro have been explored for live vaccine development by attenuating the transformed cells using lengthy serial propagation in vitro. The empirical in vivo evaluation of attenuation required for each batch of long-term cultured cells is a major constraint since it is resource intensive and raises ethical issues regarding animal welfare. As yet, the molecular mechanisms underlying attenuation are not well understood. Characteristic changes in gene expression brought about by attenuation are likely to aid in the identification of novel biomarkers for attenuation. We set out to undertake a comparative transcriptome analysis of attenuated (passage 296) and virulent (passage 26) bovine leukocytes infected with a Tunisian strain of T. annulata termed Beja. RNA-seq was used to analyse gene expression profiles and the relative expression levels of selected genes were verified by real-time quantitative PCR (RT-qPCR) analysis. Among the 3538 T. annulata genes analysed, 214 were significantly differentially expressed, of which 149 genes were up-regulated and 65 down-regulated. Functional annotation of differentially expressed T. annulata genes revealed four broad categories of metabolic pathways: carbon metabolism, oxidative phosphorylation, protein processing in the endoplasmic reticulum and biosynthesis of secondary metabolites. It is interesting to note that of the top 40 genes that showed altered expression, 13 were predicted to contain a signal peptide and/or at least one transmembrane domain, suggesting possible involvement in host-parasite interaction. Of the 16,514 bovine transcripts, 284 and 277 showed up-regulated and down-regulated expression, respectively. These were assigned to functional categories relevant to cell surface, tissue morphogenesis and regulation of cell adhesion, regulation of leucocyte, lymphocyte and cell activation. The genetic alterations acquired during attenuation that we have catalogued herein, as well as the accompanying in silico functional characterization, do not only improve understanding of the attenuation process, but can also be exploited by studies aimed at identifying attenuation biomarkers across different cell lines focusing on some host and parasite genes that have been highlighted in this study, such as bovine genes (CD69, ZNF618, LPAR3, and APOL3) and parasite genes such as TA03875. [ABSTRACT FROM AUTHOR]

Members of the NOX/DUOX family of NADPH oxidases are responsible for regulated ROS production in diverse cells and tissues. Detection of NOX/DUOX proteins at the protein level remains an important challenge in the field. Here we report the development and characterization of a novel anti-NOX5 monoclonal antibody, which recognizes the human NOX5 protein in both Western blot, immunocytochemistry, and histochemistry applications. With the help of the antibody we could successfully detect both heterologously and endogenously expressed NOX5 in mammalian cells. Furthermore, we could also detect NOX5 protein in the human spleen, testis, and ovary. Immunohistochemical studies on human testis revealed that NOX5 localized to spermatogenic cells. This expression pattern was also supported by the result of in silico analysis of single-cell RNA sequencing data that indicated that NOX5 protein is present in developing spermatids and spermatocytes. Mature spermatozoa, however, did not contain detectable NOX5. In the human ovary, both immunostaining and single-cell RNA sequencing suggest that NOX5 is expressed in interstitial fibroblasts and theca cells. We also analyzed vascular cells for the presence of NOX5 and we found that NOX5 expression is a fairly specific feature of splenic endothelial cells. [ABSTRACT FROM AUTHOR]

Differential gene expression (DGE) analysis has been widely employed to identify genes expressed differentially with respect to a trait of interest using RNA sequencing (RNA-Seq) data. Recent RNA-Seq data with large samples pose challenges to existing DGE methods, which were mainly developed for dichotomous traits and small sample sizes. Especially, existing DGE methods are likely to result in inflated false positive rates. To address this gap, we employed a linear mixed model (LMM) that has been widely used in genetic association studies for DGE analysis of quantitative traits. We first applied the LMM method to the discovery RNA-Seq data of dorsolateral prefrontal cortex (DLPFC) tissue (n = 632) with four continuous measures of Alzheimer's Disease (AD) cognitive and neuropathologic traits. The quantile–quantile plots of p-values showed that false positive rates were well calibrated by LMM, whereas other methods not accounting for sample-specific mixed effects led to serious inflation. LMM identified 37 potentially significant genes with differential expression in DLPFC for at least one of the AD traits, 17 of which were replicated in the additional RNA-Seq data of DLPFC, supplemental motor area, spinal cord, and muscle tissues. This application study showed not only well calibrated DGE results by LMM, but also possibly shared gene regulatory mechanisms of AD traits across different relevant tissues. [ABSTRACT FROM AUTHOR]

Although the effects of paternal exposure to insults on the offspring received limited attention in the past, it is currently gaining interest especially after understanding the mechanisms which may mediate such exposure effects. In the current study, the well-controlled avian model (Fayoumi) was utilized to investigate the effects of paternal exposure to the developmental insult, chlorpyrifos on the offspring's gene expression via mRNA and small RNA sequencing. Numerous mRNA gene expression changes were detected in the offspring after paternal exposure to the developmental insult, especially in genes related to neurogenesis, learning and memory. qPCR analysis of several genes, that were significantly changed in mRNA sequencing, confirmed the results obtained in mRNA sequencing. On the other hand, small RNA sequencing did not identify significant microRNA genes expression changes in the offspring after paternal exposure to the developmental insult. The effects of the paternal exposure were more pronounced in the female offspring compared to the male offspring. The results identified expression alterations in major genes (some of which were pertinent to the functional changes observed in other forms of early developmental exposure) after paternal insult exposure and provided a direction for future studies involving the most affected genes. [ABSTRACT FROM AUTHOR]

Prostate cancer is the most common cancer in men and a major cause of cancer related deaths worldwide. Nearly all affected men develop resistance to current therapies and there is an urgent need to develop new treatments for advanced disease. Aberrant glycosylation is a common feature of cancer cells implicated in all of the hallmarks of cancer. A major driver of aberrant glycosylation in cancer is the altered expression of glycosylation enzymes. Here, we show that GCNT1, an enzyme that plays an essential role in the formation of core 2 branched O-glycans and is crucial to the final definition of O-glycan structure, is upregulated in aggressive prostate cancer. Using in vitro and in vivo models, we show GCNT1 promotes the growth of prostate tumours and can modify the glycome of prostate cancer cells, including upregulation of core 2 O-glycans and modifying the O-glycosylation of secreted glycoproteins. Furthermore, using RNA sequencing, we find upregulation of GCNT1 in prostate cancer cells can alter oncogenic gene expression pathways important in tumour growth and metastasis. Our study highlights the important role of aberrant O-glycosylation in prostate cancer progression and provides novel insights regarding the mechanisms involved. [ABSTRACT FROM AUTHOR]

Mechanisms of sex-dependent orofacial pain are widely understudied. A significant gap in knowledge exists about comprehensive regulation of tissue-specific trigeminal sensory neurons in diseased state of both sexes. Using RNA sequencing of FACS sorted retro-labeled sensory neurons innervating tongue tissue, we determined changes in transcriptomic profiles in males and female mice under naïve as well as tongue-tumor bearing conditions Our data revealed the following interesting findings: (1) FACS sorting obtained higher number of neurons from female trigeminal ganglia (TG) compared to males; (2) Naïve female neurons innervating the tongue expressed immune cell markers such as Csf1R, C1qa and others, that weren't expressed in males. This was validated by Immunohistochemistry. (3) Accordingly, immune cell markers such as Csf1 exclusively sensitized TRPV1 responses in female TG neurons. (4) Male neurons were more tightly regulated than female neurons upon tumor growth and very few differentially expressed genes (DEGs) overlapped between the sexes, (5) Male DEGs contained higher number of transcription factors whereas female DEGs contained higher number of enzymes, cytokines and chemokines. Collectively, this is the first study to characterize the effect of sex as well as of tongue-tumor on global gene expression, pathways and molecular function of tongue-innervating sensory neurons. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNA) are known to function as competing endogenous RNA (ceRNA) in various cancers by regulating microRNAs (miRNA). However, in colorectal cancer (CRC), the precise pathological role of circ000240/miRNA/mRNA remains indeterminate. The expression level of hsa_circ_000240 was evaluated using qRT-PCR in matching pairs of CRC tumor and adjacent normal tissue samples in our laboratory. Then, to determine whether hsa_circ_000240 acted as a ceRNA in CRC, the linked miRNAs and gene targets were retrieved. Topological analysis of candidate genes using a network approach identified the most critical hub genes and subnetworks related to CRC disease. Microarray and bulk RNA sequencing analyses were utilized to comprehensively evaluate the expression levels of both miRNA and mRNA in CRC. Single-cell RNA-seq analysis was also used to evaluate the significant overall survival (OS) genes at the cellular level. ATAC-seq data provided insights into candidate genes' accessible chromatin regions. The research uncovered a considerable upregulation of hsa_circ_000240 in CRC tissues. Three miRNAs interacted with the target circRNA. One thousand six hundred eighty intersected genes regulated by three miRNAs were further identified, and the relevant functionality of identified neighbor genes highlighted their relevance to cancer. The topological analysis of the constructed network has identified 33 hub genes with notably high expression in CRC. Among these genes, eight, including CHEK1, CDC6, FANCI, GINS2, MAD2L1, ORC1, RACGAP1, and SMC4, have demonstrated a significant impact on overall survival. The utilization of single-cell RNA sequencing unequivocally corroborated the augmented expression levels of CDC6 and ORC1 in individuals with CRC, alongside their noteworthy connection with the infiltration of immune cells. ATAC-seq analyses revealed altered accessibility regions in Chr2, 4, and 12 for CDC6 and ORC1 high-expression. Correlation analysis of CDC6 and ORC1 further highlighted the association of candidate gene expression with exhaustion markers such as CTLA4, CD247, TIGIT, and CD244. The candidate genes exhibit a positive correlation with chromatin remodeling and histone acetylation. These epigenetic modifications play a significant role in influencing the cancer progression following expression of CDC6 and ORC1 in CRC. Additionally, results showed that the methylation rate of the promoter region of CDC6 was elevated in CRC disease, confirming the functional importance of CDC6 and their interaction with hsa_circ_000240 and associated ceRNA in CRC. In conclusion, this study highlights hsa_circ_000240's role as a ceRNA in CRC. It opens new avenues for further dissection of CDC6, ORC1, and underlying novel epigenetics and immunotherapy targets for CRC therapy. [ABSTRACT FROM AUTHOR]

Enhancer RNAs (eRNAs) are non-coding RNAs produced by transcriptional enhancers that are highly correlated with their activity. Using a capped nascent RNA sequencing (PRO-cap) dataset in human lymphoblastoid cell lines across 67 individuals, we identified inter-individual variation in the expression of over 80 thousand transcribed transcriptional regulatory elements (tTREs), in both enhancers and promoters. Co-expression analysis of eRNAs from tTREs across individuals revealed how enhancers are associated with each other and with promoters. Mid- to long-range co-expression showed a distance-dependent decay that was modified by TF occupancy. In particular, we found a class of "bivalent" TFs, including Cohesin, that both facilitate and isolate the interaction between enhancers and/or promoters, depending on their topology. At short distances, we observed strand-specific correlations between nearby eRNAs in both convergent and divergent orientations. Our results support a cooperative model of convergent eRNAs, consistent with eRNAs facilitating adjacent enhancers rather than interfering with each other. Therefore, our approach to infer functional interactions from co-expression analyses provided novel insights into the principles of enhancer interactions as a function of distance, orientation, and binding landscapes of TFs. [ABSTRACT FROM AUTHOR]

Differential diagnosis of inflammatory bowel disease (IBD) to Crohn's disease (CD) or ulcerative colitis (UC) is crucial for treatment decision making. With the aim of generating a clinically applicable molecular-based tool to classify IBD patients, we assessed whole transcriptome analysis on endoscopy samples. A total of 408 patient samples were included covering both internal and external samples cohorts. Whole transcriptome analysis was performed on an internal cohort of FFPE IBD samples (CD, n = 16 and UC, n = 17). The 100 most significantly differentially expressed genes (DEG) were tested in two external cohorts. Ten of the DEG were further processed by functional enrichment analysis from which seven were found to show consistent significant performance in discriminating CD from UC: PI3, ANXA1, VDR, MTCL1, SH3PXD2A-AS1, CLCF1, and CD180. Differential expression of PI3, ANXA1, and VDR was reproduced by RT-qPCR, which was performed on an independent sample cohort of 97 patient samples (CD, n = 44 and UC, n = 53). Gene expression levels of the three-gene profile, resulted in an area under the curve of 0.84 (P = 0.02) in discriminating CD from UC, and therefore appear as an attractive molecular-based diagnostic tool for clinicians to distinguish CD from UC. [ABSTRACT FROM AUTHOR]

The apicomplexan parasite Theileria annulata is transmitted by Hyalomma ticks and causes an acute lymphoproliferative disease that is invariably lethal in exotic cattle breeds. The unique ability of the schizont stage of T. annulata to transform infected leukocytes to a cancer-like phenotype and the simplicity of culturing and passaging T. annulata-transformed cells in vitro have been explored for live vaccine development by attenuating the transformed cells using lengthy serial propagation in vitro. The empirical in vivo evaluation of attenuation required for each batch of long-term cultured cells is a major constraint since it is resource intensive and raises ethical issues regarding animal welfare. As yet, the molecular mechanisms underlying attenuation are not well understood. Characteristic changes in gene expression brought about by attenuation are likely to aid in the identification of novel biomarkers for attenuation. We set out to undertake a comparative transcriptome analysis of attenuated (passage 296) and virulent (passage 26) bovine leukocytes infected with a Tunisian strain of T. annulata termed Beja. RNA-seq was used to analyse gene expression profiles and the relative expression levels of selected genes were verified by real-time quantitative PCR (RT-qPCR) analysis. Among the 3538 T. annulata genes analysed, 214 were significantly differentially expressed, of which 149 genes were up-regulated and 65 down-regulated. Functional annotation of differentially expressed T. annulata genes revealed four broad categories of metabolic pathways: carbon metabolism, oxidative phosphorylation, protein processing in the endoplasmic reticulum and biosynthesis of secondary metabolites. It is interesting to note that of the top 40 genes that showed altered expression, 13 were predicted to contain a signal peptide and/or at least one transmembrane domain, suggesting possible involvement in host-parasite interaction. Of the 16,514 bovine transcripts, 284 and 277 showed up-regulated and down-regulated expression, respectively. These were assigned to functional categories relevant to cell surface, tissue morphogenesis and regulation of cell adhesion, regulation of leucocyte, lymphocyte and cell activation. The genetic alterations acquired during attenuation that we have catalogued herein, as well as the accompanying in silico functional characterization, do not only improve understanding of the attenuation process, but can also be exploited by studies aimed at identifying attenuation biomarkers across different cell lines focusing on some host and parasite genes that have been highlighted in this study, such as bovine genes (CD69, ZNF618, LPAR3, and APOL3) and parasite genes such as TA03875. [ABSTRACT FROM AUTHOR]

Prostate cancer is the most common cancer in men and a major cause of cancer related deaths worldwide. Nearly all affected men develop resistance to current therapies and there is an urgent need to develop new treatments for advanced disease. Aberrant glycosylation is a common feature of cancer cells implicated in all of the hallmarks of cancer. A major driver of aberrant glycosylation in cancer is the altered expression of glycosylation enzymes. Here, we show that GCNT1, an enzyme that plays an essential role in the formation of core 2 branched O-glycans and is crucial to the final definition of O-glycan structure, is upregulated in aggressive prostate cancer. Using in vitro and in vivo models, we show GCNT1 promotes the growth of prostate tumours and can modify the glycome of prostate cancer cells, including upregulation of core 2 O-glycans and modifying the O-glycosylation of secreted glycoproteins. Furthermore, using RNA sequencing, we find upregulation of GCNT1 in prostate cancer cells can alter oncogenic gene expression pathways important in tumour growth and metastasis. Our study highlights the important role of aberrant O-glycosylation in prostate cancer progression and provides novel insights regarding the mechanisms involved. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan–Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein–protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC. [ABSTRACT FROM AUTHOR]

Differential gene expression (DGE) analysis has been widely employed to identify genes expressed differentially with respect to a trait of interest using RNA sequencing (RNA-Seq) data. Recent RNA-Seq data with large samples pose challenges to existing DGE methods, which were mainly developed for dichotomous traits and small sample sizes. Especially, existing DGE methods are likely to result in inflated false positive rates. To address this gap, we employed a linear mixed model (LMM) that has been widely used in genetic association studies for DGE analysis of quantitative traits. We first applied the LMM method to the discovery RNA-Seq data of dorsolateral prefrontal cortex (DLPFC) tissue (n = 632) with four continuous measures of Alzheimer's Disease (AD) cognitive and neuropathologic traits. The quantile–quantile plots of p-values showed that false positive rates were well calibrated by LMM, whereas other methods not accounting for sample-specific mixed effects led to serious inflation. LMM identified 37 potentially significant genes with differential expression in DLPFC for at least one of the AD traits, 17 of which were replicated in the additional RNA-Seq data of DLPFC, supplemental motor area, spinal cord, and muscle tissues. This application study showed not only well calibrated DGE results by LMM, but also possibly shared gene regulatory mechanisms of AD traits across different relevant tissues. [ABSTRACT FROM AUTHOR]

Although the effects of paternal exposure to insults on the offspring received limited attention in the past, it is currently gaining interest especially after understanding the mechanisms which may mediate such exposure effects. In the current study, the well-controlled avian model (Fayoumi) was utilized to investigate the effects of paternal exposure to the developmental insult, chlorpyrifos on the offspring's gene expression via mRNA and small RNA sequencing. Numerous mRNA gene expression changes were detected in the offspring after paternal exposure to the developmental insult, especially in genes related to neurogenesis, learning and memory. qPCR analysis of several genes, that were significantly changed in mRNA sequencing, confirmed the results obtained in mRNA sequencing. On the other hand, small RNA sequencing did not identify significant microRNA genes expression changes in the offspring after paternal exposure to the developmental insult. The effects of the paternal exposure were more pronounced in the female offspring compared to the male offspring. The results identified expression alterations in major genes (some of which were pertinent to the functional changes observed in other forms of early developmental exposure) after paternal insult exposure and provided a direction for future studies involving the most affected genes. [ABSTRACT FROM AUTHOR]

Reduction in visceral adipose tissue (VAT) mass reduces body weight and metabolic disease risk in obese patients. However surgical removal of VAT is highly invasive and thus not clinically feasible. We developed an injectable ice slurry for selective reduction of adipose tissue through cryolipolysis. The aim of this study was to investigate safety, feasibility and mechanism of ice slurry-induced cryolipolysis of VAT. Perigonadal VAT in diet-induced obese mice and rats was subjected to slurry or sham treatment. Body weight and blood chemistry were monitored for 56 days post-treatment. Histological analysis and molecular studies were performed to elucidate mechanisms of fat reduction. Treatment of VAT was well tolerated in all animals. Slurry induced adipocyte cell death via selective cryolipolysis; significant weight loss was noted at day 21 post-treatment. RNA sequencing from treated VAT samples showed increased expression of genes involved in inflammation, immune response, collagen biosynthesis and wound healing, and decreased expression of adipokines. This study demonstrates that slurry treatment is safe and effective in inducing cryolipolysis of VAT and subsequent weight loss in mice. Ice slurry is promising as a minimally-invasive treatment to reduce visceral adipose tissue. [ABSTRACT FROM AUTHOR]

Gene expression data generated from whole blood via next generation sequencing is frequently used in studies aimed at identifying mRNA-based biomarker panels with utility for diagnosis or monitoring of human disease. These investigations often employ data normalization techniques more typically used for analysis of data originating from solid tissues, which largely operate under the general assumption that specimens have similar transcriptome composition. However, this assumption may be violated when working with data generated from whole blood, which is more cellularly dynamic, leading to potential confounds. In this study, we used next generation sequencing in combination with flow cytometry to assess the influence of donor leukocyte counts on the transcriptional composition of whole blood specimens sampled from a cohort of 138 human subjects, and then subsequently examined the effect of four frequently used data normalization approaches on our ability to detect inter-specimen biological variance, using the flow cytometry data to benchmark each specimens true cellular and molecular identity. Whole blood samples originating from donors with differing leukocyte counts exhibited dramatic differences in both genome-wide distributions of transcript abundance and gene-level expression patterns. Consequently, three of the normalization strategies we tested, including median ratio (MRN), trimmed mean of m-values (TMM), and quantile normalization, noticeably masked the true biological structure of the data and impaired our ability to detect true interspecimen differences in mRNA levels. The only strategy that improved our ability to detect true biological variance was simple scaling of read counts by sequencing depth, which unlike the aforementioned approaches, makes no assumptions regarding transcriptome composition. [ABSTRACT FROM AUTHOR]

Senescent cells are predicted to occur and increase in animal tissues with aging. However, senescent cells in the tissues of aged animals remain to be identified. We refer to the marker genes to identify senescent cells in tissues as "age-associated genes". In this study, we searched for age-associated genes to identify senescent cells in the livers of aged animals. We performed single-cell RNA sequencing (scRNA-seq) to screen candidates for age-associated genes using young and aged rat primary hepatocytes. To remove animal species specificity, gene expression analyses in mouse livers were performed, confirming age-associated increases in the mRNA expression levels of Glipr1, Clec12a, and Phlda3. Moreover, the mRNA expression levels of Glipr1 and Phlda3 were increased by stress-induced premature senescence using doxorubicin in primary hepatocytes and livers of young mice. Transcriptome data of aged rat hepatocytes suggested that Glipr1, Clec12a, and Phlda3 were expressed in almost identical cells. Fluorescence in situ hybridization (FISH) confirmed the presence of cells with abundant Glipr1, Clec12a, and Phlda3 mRNA in 27-month-old mouse primary hepatocytes, which are considered to be senescent cells. This study is the first to identify Glipr1, Clec12a, and Phlda3 as age-associated genes in the mouse liver. [ABSTRACT FROM AUTHOR]

Cancer treatment is still challenging because the disease is often caused by multiple mutations. Although genomic studies have identified many oncogenes and tumor suppressor genes, gene sets involved in tumorigenesis remain poorly understood. Xenopus, a genus of aquatic frogs, is a useful model to identify gene sets because it can be genetically and experimentally analyzed. Here, we analyzed gene expression in tumor tissues of three individuals in Xenopus tropicalis and identified 55 differentially expressed genes (DEGs). Gene ontology (GO) analysis showed that the upregulated genes in the tumor tissues were enriched in GO terms related to the extracellular matrix and collagen fibril organization. Hierarchical clustering showed that the gene expression patterns of tumor tissues in X. tropicalis were comparable to those of human connective, soft, and subcutaneous tissue-derived cancers. Additionally, pathway analysis revealed that these DEGs were associated with multiple pathways, including the extracellular matrix, collagen fibril organization, MET signaling, and keratan sulfate. We also found that the expression tendency of some DEGs that have not been well analyzed in the cancer field clearly determines the prognosis of human cancer patients. This study provides a remarkable reference for future experimental work on X. tropicalis to identify gene sets involved in human cancer. [ABSTRACT FROM AUTHOR]

Mechanisms of sex-dependent orofacial pain are widely understudied. A significant gap in knowledge exists about comprehensive regulation of tissue-specific trigeminal sensory neurons in diseased state of both sexes. Using RNA sequencing of FACS sorted retro-labeled sensory neurons innervating tongue tissue, we determined changes in transcriptomic profiles in males and female mice under naïve as well as tongue-tumor bearing conditions Our data revealed the following interesting findings: (1) FACS sorting obtained higher number of neurons from female trigeminal ganglia (TG) compared to males; (2) Naïve female neurons innervating the tongue expressed immune cell markers such as Csf1R, C1qa and others, that weren't expressed in males. This was validated by Immunohistochemistry. (3) Accordingly, immune cell markers such as Csf1 exclusively sensitized TRPV1 responses in female TG neurons. (4) Male neurons were more tightly regulated than female neurons upon tumor growth and very few differentially expressed genes (DEGs) overlapped between the sexes, (5) Male DEGs contained higher number of transcription factors whereas female DEGs contained higher number of enzymes, cytokines and chemokines. Collectively, this is the first study to characterize the effect of sex as well as of tongue-tumor on global gene expression, pathways and molecular function of tongue-innervating sensory neurons. [ABSTRACT FROM AUTHOR]

Brain disorders are leading causes of disability worldwide. Gene expression studies provide promising opportunities to better understand their etiology but it is critical that expression is studied on a cell-type level. Cell-type specific association studies can be performed with bulk expression data using statistical methods that capitalize on cell-type proportions estimated with the help of a reference panel. To create a fine-grained reference panel for the human prefrontal cortex, we performed an integrated analysis of the seven largest single nucleus RNA-seq studies. Our panel included 17 cell-types that were robustly detected across all studies, subregions of the prefrontal cortex, and sex and age groups. To estimate the cell-type proportions, we used an empirical Bayes estimator that substantially outperformed three estimators recommended previously after a comprehensive evaluation of methods to estimate cell-type proportions from brain transcriptome data. This is important as being able to precisely estimate the cell-type proportions may avoid unreliable results in downstream analyses particularly for the multiple cell-types that had low abundances. Transcriptome-wide association studies performed with permuted bulk expression data showed that it is possible to perform transcriptome-wide association studies for even the rarest cell-types without an increased risk of false positives. [ABSTRACT FROM AUTHOR]

Single cell RNA sequencing has a central role in immune profiling, identifying specific immune cells as disease markers and suggesting therapeutic target genes of immune cells. Immune cell-type annotation from single cell transcriptomics is in high demand for dissecting complex immune signatures from multicellular blood and organ samples. However, accurate cell type assignment from single-cell RNA sequencing data alone is complicated by a high level of gene expression heterogeneity. Many computational methods have been developed to respond to this challenge, but immune cell annotation accuracy is not highly desirable. We present ImmunIC, a simple and robust tool for immune cell identification and classification by combining marker genes with a machine learning method. With over two million immune cells and half-million non-immune cells from 66 single cell RNA sequencing studies, ImmunIC shows 98% accuracy in the identification of immune cells. ImmunIC outperforms existing immune cell classifiers, categorizing into ten immune cell types with 92% accuracy. We determine peripheral blood mononuclear cell compositions of severe COVID-19 cases and healthy controls using previously published single cell transcriptomic data, permitting the identification of immune cell-type specific differential pathways. Our publicly available tool can maximize the utility of single cell RNA profiling by functioning as a stand-alone bioinformatic cell sorter, advancing cell-type specific immune profiling for the discovery of disease-specific immune signatures and therapeutic targets. [ABSTRACT FROM AUTHOR]

With the advent of multiplex fluorescence in situ hybridization (FISH) and in situ RNA sequencing technologies, spatial transcriptomics analysis is advancing rapidly, providing spatial location and gene expression information about cells in tissue sections at single cell resolution. Cell type classification of these spatially-resolved cells can be inferred by matching the spatial transcriptomics data to reference atlases derived from single cell RNA-sequencing (scRNA-seq) in which cell types are defined by differences in their gene expression profiles. However, robust cell type matching of the spatially-resolved cells to reference scRNA-seq atlases is challenging due to the intrinsic differences in resolution between the spatial and scRNA-seq data. In this study, we systematically evaluated six computational algorithms for cell type matching across four image-based spatial transcriptomics experimental protocols (MERFISH, smFISH, BaristaSeq, and ExSeq) conducted on the same mouse primary visual cortex (VISp) brain region. We find that many cells are assigned as the same type by multiple cell type matching algorithms and are present in spatial patterns previously reported from scRNA-seq studies in VISp. Furthermore, by combining the results of individual matching strategies into consensus cell type assignments, we see even greater alignment with biological expectations. We present two ensemble meta-analysis strategies used in this study and share the consensus cell type matching results in the Cytosplore Viewer (https://viewer.cytosplore.org) for interactive visualization and data exploration. The consensus matching can also guide spatial data analysis using SSAM, allowing segmentation-free cell type assignment. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) increases tuberculosis (TB) severity. We compared blood gene expression in adults with pulmonary TB, with or without diabetes mellitus (DM) from sites in Brazil and India. RNA sequencing (RNAseq) performed at baseline and during TB treatment. Publicly available baseline RNAseq data from South Africa and Romania reported by the TANDEM Consortium were also analyzed. Across the sites, differentially expressed genes varied for each condition (DM, TB, and TBDM) and no pattern classified any one group across all sites. A concise signature of TB disease was identified but this was expressed equally in TB and TBDM. Pathway enrichment analysis failed to distinguish TB from TBDM, although there was a trend for greater neutrophil and innate immune pathway activation in TBDM participants. Pathways associated with insulin resistance, metabolic dysfunction, diabetic complications, and chromosomal instability were positively correlated with glycohemoglobin. The immune response to pulmonary TB as reflected by whole blood gene expression is substantially similar with or without comorbid DM. Gene expression pathways associated with the microvascular and macrovascular complications of DM are upregulated during TB, supporting a syndemic interaction between these coprevalent diseases. [ABSTRACT FROM AUTHOR]

Cell-cycle control is accomplished by cyclin-dependent kinases (CDKs), motivating extensive research into CDK targeting small-molecule drugs as cancer therapeutics. Here we use combinatorial CRISPR/Cas9 perturbations to uncover an extensive network of functional interdependencies among CDKs and related factors, identifying 43 synthetic-lethal and 12 synergistic interactions. We dissect CDK perturbations using single-cell RNAseq, for which we develop a novel computational framework to precisely quantify cell-cycle effects and diverse cell states orchestrated by specific CDKs. While pairwise disruption of CDK4/6 is synthetic-lethal, only CDK6 is required for normal cell-cycle progression and transcriptional activation. Multiple CDKs (CDK1/7/9/12) are synthetic-lethal in combination with PRMT5, independent of cell-cycle control. In-depth analysis of mRNA expression and splicing patterns provides multiple lines of evidence that the CDK-PRMT5 dependency is due to aberrant transcriptional regulation resulting in premature termination. These inter-dependencies translate to drug–drug synergies, with therapeutic implications in cancer and other diseases. [ABSTRACT FROM AUTHOR]

Avicennia marina (Forsk.) Vierh. is a typical mangrove plant. Its epidermis contains salt glands, which can secrete excess salts onto the leaf surfaces, improving the salt tolerance of the plants. However, knowledge on the epidermis-specific transcriptional responses of A. marina to salinity treatment is lacking. Thus, physiological and transcriptomic techniques were applied to unravel the salt tolerance mechanism of A. marina. Our results showed that 400 mM NaCl significantly reduced the plant height, leaf area, leaf biomass and photosynthesis of A. marina. In addition, 1565 differentially expressed genes were identified, of which 634 and 931 were up- and down-regulated. Based on Kyoto Encyclopedia of Genes and Genomes metabolic pathway enrichment analysis, we demonstrated that decreased gene expression, especially that of OEE1, PQL2, FDX3, ATPC, GAPDH, PRK, FBP and RPE, could explain the inhibited photosynthesis caused by salt treatment. Furthermore, the ability of A. marina to cope with 400 mM NaCl treatment was dependent on appropriate hormone signalling and potential sulfur-containing metabolites, such as hydrogen sulfide and cysteine biosynthesis. Overall, the present study provides a theoretical basis for the adaption of A. marina to saline habitats and a reference for studying the salt tolerance mechanism of other mangrove plants. [ABSTRACT FROM AUTHOR]

miRNA and other forms of small RNAs are known to regulate many biological processes. Single-cell small RNA sequencing can be used to profile small RNAs of individual cells; however, limitations of efficiency and scale prevent its widespread application. Here, we developed parallel single-cell small RNA sequencing (PSCSR-seq), which can overcome the limitations of existing methods and enable high-throughput small RNA expression profiling of individual cells. Analysis of PSCSR-seq data indicated that diverse cell types could be identified based on patterns of miRNA expression, and showed that miRNA content in nuclei is informative (for example, cell type marker miRNAs can be detected in isolated nuclei). PSCSR-seq is very sensitive: analysis of only 732 peripheral blood mononuclear cells (PBMCs) detected 774 miRNAs, whereas bulk small RNA analysis would require input RNA from approximately 106 cells to detect as many miRNAs. We identified 42 miRNAs as markers for PBMC subpopulations. Moreover, we analyzed the miRNA profiles of 9,533 cells from lung cancer biopsies, and by dissecting cell subpopulations, we identified potentially diagnostic and therapeutic miRNAs for lung cancers. Our study demonstrates that PSCSR-seq is highly sensitive and reproducible, thus making it an advanced tool for miRNA analysis in cancer and life science research. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNAseq) enables researchers to identify and characterize populations and subpopulations of different cell types in hearts recovering from myocardial infarction (MI) by characterizing the transcriptomes in thousands of individual cells. However, the effectiveness of the currently available tools for processing and interpreting these immense datasets is limited. We incorporated three Artificial Intelligence (AI) techniques into a toolkit for evaluating scRNAseq data: AI Autoencoding separates data from different cell types and subpopulations of cell types (cluster analysis); AI Sparse Modeling identifies genes and signaling mechanisms that are differentially activated between subpopulations (pathway/gene set enrichment analysis), and AI Semisupervised Learning tracks the transformation of cells from one subpopulation into another (trajectory analysis). Autoencoding was often used in data denoising; yet, in our pipeline, Autoencoding was exclusively used for cell embedding and clustering. The performance of our AI scRNAseq toolkit and other highly cited non-AI tools was evaluated with three scRNAseq datasets obtained from the Gene Expression Omnibus database. Autoencoder was the only tool to identify differences between the cardiomyocyte subpopulations found in mice that underwent MI or sham-MI surgery on postnatal day (P) 1. Statistically significant differences between cardiomyocytes from P1-MI mice and mice that underwent MI on P8 were identified for six cell-cycle phases and five signaling pathways when the data were analyzed via Sparse Modeling, compared to just one cell-cycle phase and one pathway when the data were analyzed with non-AI techniques. Only Semisupervised Learning detected trajectories between the predominant cardiomyocyte clusters in hearts collected on P28 from pigs that underwent apical resection (AR) on P1, and on P30 from pigs that underwent AR on P1 and MI on P28. In another dataset, the pig scRNAseq data were collected after the injection of CCND2-overexpression Human-induced Pluripotent Stem Cell-derived cardiomyocytes (CCND2hiPSC) into injured P28 pig heart; only the AI-based technique could demonstrate that the host cardiomyocytes increase proliferating by through the HIPPO/YAP and MAPK signaling pathways. For the cluster, pathway/gene set enrichment, and trajectory analysis of scRNAseq datasets generated from studies of myocardial regeneration in mice and pigs, our AI-based toolkit identified results that non-AI techniques did not discover. These different results were validated and were important in explaining myocardial regeneration. [ABSTRACT FROM AUTHOR]

In order to better understand the relationship between normal and neoplastic brain, we combined five publicly available large-scale datasets, correcting for batch effects and applying Uniform Manifold Approximation and Projection (UMAP) to RNA-Seq data. We assembled a reference Brain-UMAP including 702 adult gliomas, 802 pediatric tumors and 1409 healthy normal brain samples, which can be utilized to investigate the wealth of information obtained from combining several publicly available datasets to study a single organ site. Normal brain regions and tumor types create distinct clusters and because the landscape is generated by RNA-Seq, comparative gene expression profiles and gene ontology patterns are readily evident. To our knowledge, this is the first meta-analysis that allows for comparison of gene expression and pathways of interest across adult gliomas, pediatric brain tumors, and normal brain regions. We provide access to this resource via the open source, interactive online tool Oncoscape, where the scientific community can readily visualize clinical metadata, gene expression patterns, gene fusions, mutations, and copy number patterns for individual genes and pathway over this reference landscape. [ABSTRACT FROM AUTHOR]

Epithelial-to-mesenchymal transition (EMT) is associated with tumor initiation, metastasis, and drug resistance. However, the mechanisms underlying these associations are largely unknown. We studied several tumor types to identify the source of EMT gene expression signals and a potential mechanism of resistance to immuno-oncology treatment. Across tumor types, EMT-related gene expression was strongly associated with expression of stroma-related genes. Based on RNA sequencing of multiple patient-derived xenograft models, EMT-related gene expression was enriched in the stroma versus parenchyma. EMT-related markers were predominantly expressed by cancer-associated fibroblasts (CAFs), cells of mesenchymal origin which produce a variety of matrix proteins and growth factors. Scores derived from a 3-gene CAF transcriptional signature (COL1A1, COL1A2, COL3A1) were sufficient to reproduce association between EMT-related markers and disease prognosis. Our results suggest that CAFs are the primary source of EMT signaling and have potential roles as biomarkers and targets for immuno-oncology therapies. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the most common and fatal tumor in the gastrointestinal system. Its incidence and mortality rate have increased in recent years. Hypoxia, a persistent physiological tumor feature, plays a vital role in CRC tumorigenesis, metastasis, and tumor microenvironment (TME). Therefore, we constructed a hypoxia-related gene (HRG) nomogram to predict overall survival (OS) and explored the role of HRGs in the CRC TME. The Cancer Genome Atlas (TCGA) dataset was used as the training set, and two Gene Expression Omnibus datasets (GSE39582 and GSE103479) were used as the testing sets. HRGs were identified using the Gene Set Enrichment Analysis (GSEA) database. An HRG prognostic model was constructed in the training set using the least absolute shrinkage and selection operator regression algorithm and validated in the testing sets. Then, we analyzed tumor-infiltrating cells (TICs) using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Furthermore, single-cell next-generation RNA sequencing (RNA-seq) was used to investigate HRG expression in different TICs in the GSE139555 dataset. Finally, reverse transcription polymerase chain reactions (RT-PCR) were used to validate HRG mRNA expression in ten pairs of CRC normal and cancer tissue samples. A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780). GSEA enrichment analysis identified six pathways enriched in the high-risk group. The TIC analysis indicated that the high-risk group had lower T-cell expression and higher neutrophil expression than the low-risk group. Furthermore, immune-related genes had an inseparable relationship with the HRG prognostic signature. Based on single-cell RNA-seq data, we found elevated hexokinase 1 (HK1) and glucose-6-phosphate isomerase (GPI) gene expression in natural killer (NK) and CD8+ T cells. RT-PCR in ten CRC normal-tumor tissue pairs showed that expression of the signature's six HRGs varied differently in cancerous and paracancerous tissues. The constructed HRG signature successfully predicted the OS of whole-stage CRC patients. In addition, we showed that the signature's six HRGs were closely associated with the TME in CRC, where hypoxia inhibits the antitumor function of T cells. [ABSTRACT FROM AUTHOR]

Transcriptome profiling is a mainstay of translational cancer research and is increasingly finding its way into precision oncology. While bulk RNA sequencing (RNA-seq) is widely available, high investment costs and long data return time are limiting factors for clinical applications. We investigated a portable nanopore long-read sequencing device (MinION, Oxford Nanopore Technologies) for transcriptome profiling of tumors. In particular, we investigated the impact of lower coverage than that of larger sequencing devices by comparing shallow nanopore RNA-seq data with short-read RNA-seq data generated using reversible dye terminator technology (Illumina) for ten samples representing four cancer types. Coupled with ShaNTi (Shallow Nanopore sequencing for Transcriptomics), a newly developed data processing pipeline, a turnaround time of five days was achieved. The correlation of normalized gene-level counts between nanopore and Illumina RNA-seq was high for MinION but not for very low-throughput Flongle flow cells (r = 0.89 and r = 0.24, respectively). A cost-saving approach based on multiplexing of four samples per MinION flow cell maintained a high correlation with Illumina data (r = 0.56–0.86). In addition, we compared the utility of nanopore and Illumina RNA-seq data for analysis tools commonly applied in translational oncology: (1) Shallow nanopore and Illumina RNA-seq were equally useful for inferring signaling pathway activities with PROGENy. (2) Highly expressed genes encoding kinases targeted by clinically approved small-molecule inhibitors were reliably identified by shallow nanopore RNA-seq. (3) In tumor microenvironment composition analysis, quanTIseq performed better than CIBERSORT, likely due to higher average expression of the gene set used for deconvolution. (4) Shallow nanopore RNA-seq was successfully applied to detect fusion genes using the JAFFAL pipeline. These findings suggest that shallow nanopore RNA-seq enables rapid and biologically meaningful transcriptome profiling of tumors, and warrants further exploration in precision cancer medicine studies. [ABSTRACT FROM AUTHOR]

Transportation stress causes significant changes in physiological responses in goats; however, studies exploring the transcriptome of stress are very limited. The objective of this study was to determine the differential gene expressions and related pathways in the blood samples using RNA-seq procedure in Spanish goats subjected to different durations of transportation stress. Fifty-four male Spanish goats (8-mo old; BW = 29.7 ± 2.03 kg) were randomly subjected to one of three treatments (TRT; n = 18 goats/treatment): (1) transported for 180 min, (2) transported for 30 min, or (3) held in pens (control). Blood samples were collected before and after treatment for stress hormone, metabolite, and transcriptomic analysis. RNA-seq technology was used to obtain the transcriptome profiles of blood. Analysis of physiological data using SAS showed that plasma cortisol concentrations were higher (P < 0.01) in 180 min and 30 min groups compared to the control group. Enrichment analysis of DEGs related to transportation stress through Gene Ontology and KEGG databases revealed that the differentially expressed genes related to inflammatory pathways, caspases, and apoptosis such as IL1R2, CASP14, CD14, TLR4, and MAPK14 were highly enriched in the transported group of goats compared to non-transported goats. Stress in goats leads to a sequence of events at cellular and molecular levels that causes inflammation and apoptosis. [ABSTRACT FROM AUTHOR]

Transportation stress causes significant changes in physiological responses in goats; however, studies exploring the transcriptome of stress are very limited. The objective of this study was to determine the differential gene expressions and related pathways in the blood samples using RNA-seq procedure in Spanish goats subjected to different durations of transportation stress. Fifty-four male Spanish goats (8-mo old; BW = 29.7 ± 2.03 kg) were randomly subjected to one of three treatments (TRT; n = 18 goats/treatment): (1) transported for 180 min, (2) transported for 30 min, or (3) held in pens (control). Blood samples were collected before and after treatment for stress hormone, metabolite, and transcriptomic analysis. RNA-seq technology was used to obtain the transcriptome profiles of blood. Analysis of physiological data using SAS showed that plasma cortisol concentrations were higher (P < 0.01) in 180 min and 30 min groups compared to the control group. Enrichment analysis of DEGs related to transportation stress through Gene Ontology and KEGG databases revealed that the differentially expressed genes related to inflammatory pathways, caspases, and apoptosis such as IL1R2, CASP14, CD14, TLR4, and MAPK14 were highly enriched in the transported group of goats compared to non-transported goats. Stress in goats leads to a sequence of events at cellular and molecular levels that causes inflammation and apoptosis. [ABSTRACT FROM AUTHOR]

When profiling blood samples by RNA-sequencing (RNA-seq), RNA from haemoglobin (Hgb) can account for up to 70% of the transcriptome. Due to considerations of sequencing depth and power to detect biological variation, Hgb RNA is typically depleted prior to sequencing by hybridisation-based methods; an alternative approach is to deplete reads arising from Hgb RNA bioinformatically. In the present study, we compared the impact of these two approaches on the outcome of differential gene expression analysis performed using RNA-seq data from 58 human tuberculosis (TB) patient or contact whole blood samples–29 globin kit-depleted and 29 matched non-depleted—a subset of which were taken at TB diagnosis and at six months post-TB treatment from the same patient. Bioinformatic depletion of Hgb genes from the non-depleted samples (bioinformatic-depleted) substantially reduced library sizes (median = 57.24%) and fewer long non-coding, micro, small nuclear and small nucleolar RNAs were captured in these libraries. Profiling published TB gene signatures across all samples revealed inferior correlation between kit-depleted and bioinformatic-depleted pairs when the proportion of reads mapping to Hgb genes was higher in the non-depleted sample, particularly at the TB diagnosis time point. A set of putative "globin-fingerprint" genes were identified by directly comparing kit-depleted and bioinformatic-depleted samples at each timepoint. Two TB treatment response signatures were also shown to have decreased differential performance when comparing samples at TB diagnosis to six months post-TB treatment when profiled on the bioinformatic-depleted samples compared with their kit-depleted counterparts. These results demonstrate that failure to deplete Hgb RNA prior to sequencing has a negative impact on the sensitivity to detect disease-relevant gene expression changes even when bioinformatic removal is performed. [ABSTRACT FROM AUTHOR]