High-throughput Transcriptome Research Articles

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.

Biological Diversity of Genes Encoding Wheat Defensin Homologues

Antimicrobial peptides (AMPs) are major components of innate immunity in plants and animals. AMP genes have significant intra- and interspecific polymorphism, the role of which is poorly understood. Previously, by high throughput transcriptome sequencing of wheat plants, we identified defensin genes up-regulated upon infection with the pathogenic fungus Fusarium oxysporum and/or treatment with resistance inducers. In the present work, a bioinformatic search in NCBI databases for peptide homologues of these defensins was carried out using the sequences of their γ-cores, the sites of the molecules responsible for antimicrobial activity. DEFL1-16 homologues were identified in 95 species of angiosperms belonging to 48 families and 30 orders of monocotyledonous and dicotyledonous plants. The ubiquitous distribution of this defensin in angiosperms suggests its involvement not only in defense, but also in other processes in flowering plants. Homologues of other defensins induced by infection were found only in plants of the Poaceae family, which suggests the existence of a Poaceae-specific defense mechanism associated with the expression of these defensins. Among the γ-core variants of wild plant defensins identified in the study, the peptides with better antimicrobial activity compared to wheat, might be present, which are of considerable interest for the development of new antibiotics for medicine and agriculture.

4-Octyl itaconate inhibits poly(I:C)-induced interferon-β secretion in mouse bone marrow-derived macrophages partially by activating Nrf2

Viruses have become a major threat to human health. Interferon-β (IFN-β) has a key role in the antivirus process, as it can increase the expression of antivirus-associated genes. Itaconate and its derivatives can regulate the immune response, secretion of inflammatory factors, and pyroptosis of macrophages. The effect of itaconate on IFN-β secretion of double-stranded RNA-induced macrophages are not well known. A derivative of itaconate, 4-octoyl itaconate (4-OI), was used to treat mouse bone marrow-derived macrophages (BMDM) induced with 100 μg/mL poly(I:C). The IFN-β concentration was detected through ELISA, and IFN-β mRNA expression was detected through quantitative PCR. High-throughput transcriptome sequencing was used to analyze changes in the BMDM transcriptome after 4-OI treatment. The Nrf2 expression was knocked down with siRNA.4-OI inhibited poly(I:C)-induced IFN-β secretion and mRNA expression in BMDM. Results of transcriptome sequencing revealed that 4-OI downregulated 1047 genes and upregulated 822 genes. GO and KEGG enrichment of differently expressed genes revealed that many downregulated genes were related to the anti-virus process, whereas many upregulated genes were related to metabolism. The Nrf2 inhibitor ML385 and Nrf2 siRNA could partially reverse the inhibitory effect of 4-OI. In conclusion, 4-octyl itaconate could inhibit the poly(I:C)-induced interferon-β secretion in BMDM partially by regulating Nrf2.

A review on gene regulatory network reconstruction algorithms based on single cell RNA sequencing.

Understanding gene regulatory networks (GRNs) is essential for unraveling the molecular mechanisms governing cellular behavior. With the advent of high-throughput transcriptome measurement technology, researchers have aimed to reverse engineer the biological systems, extracting gene regulatory rules from their outputs, which represented by gene expression data. Bulk RNA sequencing, a widely used method for measuring gene expression, has been employed for GRN reconstruction. However, it falls short in capturing dynamic changes in gene expression at the level of individual cells since it averages gene expression across mixed cell populations. In this review, we provide an overview of 15 GRN reconstruction tools and discuss their respective strengths and limitations, particularly in the context of single cell RNA sequencing (scRNA-seq). Recent advancements in scRNA-seq break new ground of GRN reconstruction. They offer snapshots of the individual cell transcriptomes and capturing dynamic changes. We emphasize how these technological breakthroughs have enhanced GRN reconstruction. GRN reconstructors can be classified based on their requirement for cellular trajectory, which represents a dynamical cellular process including differentiation, aging, or disease progression. Benchmarking studies support the superiority of GRN reconstructors that do not require trajectory analysis in identifying regulator-target relationships. However, methods equipped with trajectory analysis demonstrate better performance in identifying key regulatory factors. In conclusion, researchers should select a suitable GRN reconstructor based on their specific research objectives.

Transcriptome analysis reveals core lncRNA-mRNA networks regulating melanization and biomineralization in Patinopecten yessoensis shell-infested by Polydora

BackgroundPatinopecten yessoensis, a large and old molluscan group, has been one of the most important aquaculture shellfish in Asian countries because of its high economic value. However, the aquaculture of the species has recently been seriously affected by the frequent outbreaks of Polydora disease, causing great economic losses. Long non-coding RNAs (lncRNAs) exhibit exhibit crucial effects on diverse biological processes, but still remain poorly studied in scallops, limiting our understanding of the molecular regulatory mechanism of P. yessoensis in response to Polydora infestation.ResultsIn this study, a high-throughput transcriptome analysis was conducted in the mantles of healthy and Polydora-infected P. yessoensis by RNA sequencing. A total of 19,133 lncRNAs with 2,203 known and 16,930 novel were identified. The genomic characterizations of lncRNAs showed shorter sequence and open reading frame (ORF) length, fewer number of exons and lower expression levels in comparison with mRNAs. There were separately 2280 and 1636 differentially expressed mRNAs and lncRNAs (DEGs and DELs) detected in diseased individuals. The target genes of DELs were determined by both co-location and co-expression analyses. Functional enrichment analysis revealed that DEGs involved in melanization and biomineralization were significantly upregulated; further, obviously increased melanin granules were observed in epithelial cells of the edge mantle in diseased scallops by histological and TEM study, indicating the crucial role of melanizaiton and biomineralization in P. yessoensis to resist against Polydora infestation. Moreover, many key genes, such as Tyrs, Frizzled, Wnts, calmodulins, Pifs, perlucin, laccase, shell matrix protein, mucins and chitins, were targeted by DELs. Finally, a core lncRNA-mRNA interactive network involved in melanization and biomineralization was constructed and validated by qRT-PCR.ConclusionsThis work provides valuable resources for studies of lncRNAs in scallops, and adds a new insight into the molecular regulatory mechanisms of P. yessoensis defending against Polydora infestation, which will contribute to Polydora disease control and breeding of disease-resistant varieties in molluscs.

Exploring the potential mechanism of Heng-Gu-Gu-Shang-Yu-He-Ji therapy for osteoporosis based on network pharmacology and transcriptomics

Ethnopharmacological relevanceHeng-Gu-Gu-Shang-Yu-He-Ji (Osteoking, OK) is a well-known formula for fracture therapy. In clinic, OK is effective in treating fractures while alleviating osteoporosis (OP) symptoms. However, active components of OK and the associated molecular mechanisms remain not fully elucidated. Aim of the studyThis study aims to systematically evaluate the anti-osteoporosis efficacy of OK and for the first time combine network pharmacology with high-throughput whole gene transcriptome sequencing to study its underlying mechanism. Materials and methodsIn this study, the osteoporosis model was established by the castration of both ovaries. The level of serum bone turnover factor was detected by enzyme-linked immunosorbent assay. Micro-CT and HE staining were used to observe the changes of bone histopathology, and nano-indentation technique was used to detect the biomechanical properties of rat bone. The main active Chemical components of OK were identified using UPLC-DAD. Efficacy verification and mechanism exploration were conducted by network pharmacology, molecular docking, whole gene transcriptomics and in vivo experiments. ResultsIn our study, OK significantly improved bone microarchitecture and bone biomechanical parameters in OVX rats, reduced osteoclast indexes such as C-telopeptide of type I collage (CTX-I) and increased Osteoprotegerin (OPG)/Receptor activator of NF-κB ligand (RANKL) levels. Mechanistically, PI3K/AKT pathway was a common pathway for genome enrichment analysis (KEGG) of both network pharmacology and RNA-seq studies. G protein-β-like protein (GβL), Ribosomal-protein S6 kinase homolog 2 (S6K2), and Phosphoinositide 3-kinase (PI3K) appeared differentially expression in the PI3K-AKT signaling pathway. These results were also confirmed by qRT-PCR and immunohistochemistry. ConclusionsOK may be used to treat osteoporosis, at least partly by activating PI3K/AKT/mTORC1 signaling pathway.

FOXO3-Activated HOTTIP Sequesters miR-615-3p away from COL2A1 to Mitigate Intervertebral Disc Degeneration

In this study, knockout of FOXO3 was found to impair intervertebral disc maturation and homeostasis in postnatal mice as well as facilitating extracellular matrix degradation. RNA sequencing can uncover disease-related gene expression and investigate disease pathophysiology. High-throughput transcriptome sequencing and experimental validations were used to identify the essential gene and mechanism involved in intervertebral disc degeneration (IDD). Nucleus pulposus (NP) tissue samples were collected from the mice with conditional knockout of FOXO3 (FOXO3 KO) for high-throughput sequencing, followed by screening of differentially expressed lncRNAs and mRNAs. The mRNAs were subjected to GO and KEGG enrichment analyses. Interactions among FOXO3, HOTTIP, miR-615-3p, and COL2A1 were analyzed. NP cells were subjected to a series of mimics, inhibitors, overexpression plasmids, and shRNAs to validate the mechanisms of FOXO3 in controlling HOTTIP/miR-615-3p/COL2A1 in IDD. Mechanistically, FOXO3 transcriptionally activated HOTTIP, facilitated the competitive HOTTIP binding to miR-615-3p, and increased the expression of the miR-615-3p target gene COL2A1. Thus, NP cell proliferation was induced, cell apoptosis was diminished, resulting in delayed development of IDD. Based on these data, the transcription factor FOXO3 may decrease miR-615-3p binding to COL2A1 and up-regulate COL2A1 expression by activating HOTTIP transcription, which in turn inhibits NP cell apoptosis and promotes its proliferation, to prevent the degradation of intervertebral disc matrix and maintain the normal physiological function of intervertebral disc, thereby preventing the occurrence and development of IDD.

Quercus petraea (Matt.) Liebl. from the Thayatal National Park in Austria: Selection of Potentially Drought-Tolerant Phenotypes

The increasing demand for climate-adapted seeds and planting material poses a challenge due to the limited availability, particularly for tree species such as oaks. National parks, known for their large-standing diversity and a wide range of habitats, can serve as valuable sources for identifying trees suitable for both the initiation of tree breeding and conservation strategies. This study aimed to identify valuable forest genetic resources of the Thayatal National Park in Austria by selecting potentially drought-tolerant phenotypes. For this purpose, we selected 404 mature trees of Quercus petraea (Matt.) Liebl. from eight populations growing on medium to dry sites in eight populations. Further, we characterized them for autochthony, genetic structure, genetic diversity using genetic markers (plastid- and nuclear-SSRs) and estimated their age. Finally, we applied wood core analysis to estimate tree response to historical drought events to identify the possible drought-tolerant phenotypes. The age of the trees ranged from 29 to 245 years (as of the year 2023). All Q. petraea trees were inhabiting a plastid haplotype 17a, autochthonous for this area. Nevertheless, the genetic structure estimated by ten nuSSRs revealed a pronounced structure in the dataset, largely caused by young trees exhibiting lower genetic diversity. A total of 85 elite potentially drought-tolerant trees were finally selected based on their morphological response (resistance, recovery ability, resilience, and relative resilience) to three historical drought events (1992–1994, 1947, 1917). The intrinsic water use efficiency and its difference (iWUE and DWiWUE), estimated by isotope analysis of δ13C of latewood in wet (1987) and dry (1994) years, did not correlate with any of the drought response traits (Rt, Rc, Rs, rRs). We discuss the further use of the selected oak trees for the establishment of seed stands and orchards to enhance seed production and the integration of other omics approaches, such as large-scale high-throughput plant phenotyping (HTPP) and transcriptomics, for in-depth analyses of drought tolerance of selected phenotypes.

Transcriptomic and metabolomic analyses reveal the essential nature of Rab1B in Toxoplasma gondii

BackgroundThe protozoan parasite Toxoplasma gondii encodes a dozen Rab proteins, which are parts of the small GTPase superfamily and regulate intracellular membrane trafficking. Our previous study showed that depletion of Rab1B caused severe defects regarding parasite growth and morphological structure, yet early defects of endocytic trafficking and vesicle sorting to the rhoptry in T. gondii are not expected to have a strong effect. To understand this discrepancy, we performed an integrated analysis at the level of transcriptomics and metabolomics.MethodsIn the study, tetracycline-inducible TATi/Ty-Rab1B parasite line treated with ATc at three different time points (0, 18 and 24 h) was used. We first observed the morphological changes caused by Rab1B depletion via transmission electron technology. Then, high-throughput transcriptome along with non-targeted metabolomics were performed to analyze the RNA expression and metabolite changes in the Rab1B-depleted parasite. The essential nature of Rab1B in the parasite was revealed by the integrated omics approach.ResultsTransmission electron micrographs showed a strong disorganization of endo-membranes in the Rab1B-depleted parasites. Our deep analysis of transcriptome and metabolome identified 2181 and 2374 differentially expressed genes (DEGs) and 30 and 83 differentially expressed metabolites (DEMs) at 18 and 24 h of induction in the tetracycline-inducible parasite line, respectively. These DEGs included key genes associated with crucial organelles that contain the rhoptry, microneme, endoplasmic reticulum and Golgi apparatus. The analysis of qRT-PCR verified some of the key DEGs identified by RNA-Seq, supporting that the key vesicular regulator Rab1B was involved in biogenesis of multiple parasite organelles. Functional enrichment analyses revealed pathways related to central carbon metabolisms and lipid metabolisms, such as the TCA cycle, glycerophospholipid metabolism and fatty acid biosynthesis and elongation. Further correlation analysis of the major DEMs and DEGs supported the role of Rab1B in biogenesis of fatty acids (e.g. myrisoleic acid and oleic acid) (R > 0.95 and P < 0.05), which was consistent with the scavenging role in biotin via the endocytic process.ConclusionsRab1B played an important role in parasite growth and morphology, which was supported by the replication assay and transmission electron microscopy observation. Our multi-omics analyses provided detailed insights into the overall impact on the parasite upon depletion of the protein. These analyses reinforced the role of Rab1B in the endocytic process, which has an impact on fatty acid biogenesis and the TCA cycle. Taken together, these findings contribute to our understanding of a key vesicular regulator, Rab1B, on parasite metabolism and morphological formation in T. gondii.Graphical

A high-throughput single-cell RNA expression profiling method identifies human pericyte markers.

We sought to identify and optimise a universally available histological marker for pericytes in the human brain. Such a marker could be a useful tool for researchers. Further, identifying a gene expressed relatively specifically in human pericytes could provide new insights into the biological functions of this fascinating cell type. We analysed single-cell RNA expression profiles derived from different human and mouse brain regions using a high-throughput and low-cost single-cell transcriptome sequencing method called EasySci. Through this analysis, we were able to identify specific gene markers for pericytes, some of which had not been previously characterised. We then used commercially (and therefore universally) available antibodies to immunolabel the pericyte-specific gene products in formalin-fixed paraffin-embedded (FFPE) human brains and also performed immunoblots to determine whether appropriately sized proteins were recognised. In the EasySci data sets, highly pericyte-enriched expression was notable for SLC6A12 and SLC19A1. Antibodies against these proteins recognised bands of approximately the correct size in immunoblots of human brain extracts. Following optimisation of the immunohistochemical technique, staining for both antibodies was strongly positive in small blood vessels and was far more effective than a PDGFRB antibody at staining pericyte-like cells in FFPE human brain sections. In an exploratory sample of other human organs (kidney, lung, liver, muscle), immunohistochemistry did not show the same pericyte-like pattern of staining. The SLC6A12 antibody was well suited for labelling pericytes in human FFPE brain sections, based on the combined results of single-cell RNA-seq analyses, immunoblots and immunohistochemical studies.

Toxicological Mechanisms and Potencies of Organophosphate Esters in KGN Human Ovarian Granulosa Cells as Revealed by High-throughput Transcriptomics.

Despite the growing number of studies reporting potential risks associated with exposure to organophosphate esters (OPEs), their molecular mechanisms of action remain poorly defined. We used the high-throughput TempO-Seq™ platform to investigate the effects of frequently detected OPEs on the expression of ∼3000 environmentally responsive genes in KGN human ovarian granulosa cells. Cells were exposed for 48 h to one of five OPEs (0.1 to 50 μM): tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), triphenyl phosphate (TPHP), or tris(2-butoxyethyl) phosphate (TBOEP). The sequencing data indicate that four OPEs induced transcriptional changes, whereas TBOEP had no effect within the concentration range tested. Multiple pathway databases were used to predict alterations in biological processes based on differentially expressed genes. At lower concentrations, inhibition of the cholesterol biosynthetic pathway was the predominant effect of OPEs; this was likely a consequence of intracellular cholesterol accumulation. At higher concentrations, BPDP and TPHP had distinct effects, primarily affecting pathways involved in cell cycle progression and other stress responses. Benchmark concentration (BMC) modelling revealed that BPDP had the lowest transcriptomic point of departure. However, in vitro to in vivo extrapolation modeling indicated that TMPP was bioactive at lower concentrations than the other OPEs. We conclude that these new approach methodologies provide information on the mechanism(s) underlying the effects of data-poor compounds and assist in the derivation of protective points of departure for use in chemical read-across and decision-making.

Transcriptional regulation mechanism of differential accumulation of flavonoids in leaves and roots of Sarcandra glabra based on metabonomics and transcriptomics

This study aims to explore the molecular regulation mechanism of the differential accumulation of flavonoids in the leaves and roots of Sarcandra glabra. Liquid chromatography-mass spectrometry(LC-MS) and high-throughput transcriptome sequencing(RNA-seq) were employed to screen out the flavonoid-related differential metabolites and differentially expressed genes(DEGs) encoding key metabolic enzymes. Eight DEGs were randomly selected for qRT-PCR verification. The results showed that a total of 37 flavonoid-related differential metabolites between the leaves and roots of S. glabra were obtained, including pinocembrin, phlorizin, na-ringenin, kaempferol, leucocyanidin, and 5-O-caffeoylshikimic acid. The transcriptome analysis predicted 36 DEGs associated with flavonoids in the leaves and roots of S. glabra, including 2 genes in the PAL pathway, 3 genes in the 4CL pathway, 2 genes in the CHS pathway, 4 genes in the CHI pathway, 2 genes in the FLS pathway, 1 gene in the DFR pathway, 1 gene in the CYP73A pathway, 1 gene in the CYP75B1 pathway, 3 genes in the PGT1 pathway, 6 genes in the HCT pathway, 2 genes in the C3'H pathway, 1 gene in the CCOAOMT pathway, 1 gene in the ANR pathway, 1 gene in the LAR pathway, 2 genes in the 3AT pathway, 1 gene in the BZ1 pathway, 2 genes in the IFTM7 pathway, and 1 gene in the CYP81E9 pathway. Six transcription factors, including C2H2, bHLH, and bZIP, were involved in regulating the differential accumulation of flavonoids in the leaves and roots of S. glabra. The qRT-PCR results showed that the up-or down-regulated expression of the 8 randomly selected enzyme genes involved in flavonoid synthesis in the leaves and roots of S. glabra was consistent with the transcriptome sequencing results. This study preliminarily analyzed the transcriptional regulation mechanism of differential accumulation of flavonoids in the leaves and roots of S. glabra, laying a foundation for further elucidating the regulatory effects of key enzyme genes and corresponding transcription factors on the accumulation of flavonoids in S. glabra.

SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.

In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms uncovering interesting biological insights.

Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum

Environmental stresses significantly affect plant growth, development, and productivity. Therefore, a deeper understanding of the underlying stress responses at the molecular level is needed. In this study, to identify critical genetic factors associated with environmental stress responses, the entire 737.3 Gb clean RNA-seq dataset across abiotic, biotic stress, and phytohormone conditions in Capsicum annuum was used to perform individual differentially expressed gene analysis and to construct gene co-expression networks for each stress condition. Subsequently, gene networks were reconstructed around transcription factors to identify critical factors involved in the stress responses, including the NLR gene family, previously implicated in resistance. The abiotic and biotic stress networks comprise 233 and 597 hubs respectively, with 10 and 89 NLRs. Each gene within the NLR groups in the network exhibited substantial expression to particular stresses. The integrated analysis strategy of the transcriptome network revealed potential key genes for complex environmental conditions. Together, this could provide important clues to uncover novel key factors using high-throughput transcriptome data in other species as well as plants.

Big Data Analysis in Computational Biology and Bioinformatics.

Advancements in high-throughput technologies, genomics, transcriptomics, and metabolomics play an important role in obtaining biological information about living organisms. The field of computational biology and bioinformatics has experienced significant growth with the advent of high-throughput sequencing technologies and other high-throughput techniques. The resulting large amounts of data present both opportunities and challenges for data analysis. Big data analysis has become essential for extracting meaningful insights from the massive amount of data. In this chapter, we provide an overview of the current status of big data analysis in computational biology and bioinformatics. We discuss the various aspects of big data analysis, including data acquisition, storage, processing, and analysis. We also highlight some of the challenges and opportunities of big data analysis in this area of research. Despite the challenges, big data analysis presents significant opportunities like development of efficient and fast computing algorithms for advancing our understanding of biological processes, identifying novel biomarkers for breeding research and developments, predicting disease, and identifying potential drug targets for drug development programs.

Resveratrol and 3,3'-Diindolylmethane Differentially Regulate Aryl Hydrocarbon Receptor and Estrogen Receptor Alpha Activity through Multiple Transcriptomic Targets in MCF-7 Human Breast Cancer Cells.

Inhibitory crosstalk between estrogen receptor alpha (ERα) and aryl hydrocarbon receptor (AHR) regulates 17β-estradiol (E2)-dependent breast cancer cell signaling. ERα and AHR are transcription factors activated by E2 and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), respectively. Dietary ligands resveratrol (RES) and 3,3'diindolylmethane (DIM) also activate ERα while only DIM activates AHR and RES represses it. DIM and RES are reported to have anti-cancer and anti-inflammatory properties. Studies with genome-wide targets and AHR- and ERα-regulated genes after DIM and RES are unknown. We used chromatin immunoprecipitation with high-throughput sequencing and transcriptomics to study ERα as well as AHR coregulation in MCF-7 human breast cancer cells treated with DIM, RES, E2, or TCDD alone or E2+TCDD for 1 and 6 h, respectively. ERα bound sites after being DIM enriched for the AHR motif but not after E2 or RES while AHR bound sites after being DIM and E2+TCDD enriched for the ERE motif but not after TCDD. More than 90% of the differentially expressed genes closest to an AHR binding site after DIM or E2+TCDD also had an ERα site, and 60% of the coregulated genes between DIM and E2+TCDD were common. Collectively, our data show that RES and DIM differentially regulate multiple transcriptomic targets via ERα and ERα/AHR coactivity, respectively, which need to be considered to properly interpret their cellular and biological responses. These novel data also suggest that, when both receptors are activated, ERα dominates with preferential recruitment of AHR to ERα target genes.

Upregulated HAVCR2: A Prognostic and Immune-Related Marker in Testicular Germ Cell Tumors

Testicular germ cell tumors (TGCTs) are the most common solid malignant tumor in young men aged 20–34 years. Currently, the diagnosis and differentiation of TGCTs depend on immunohistochemical analysis, and the treatment methods are mainly surgery and chemoradiotherapy. Although immunotherapy has been applied in clinic, the response rate is not high, and also there is a lack of effective biomarkers. In this study, through high-throughput transcriptome sequencing and public data mining, the expression of hepatitis A virus cellular receptor 2 (HAVCR2) was found to be significantly upregulated in TGCT tissue and correlated with poor prognosis. Additionally, the expression level of HAVCR2 was negatively correlated with its DNA methylation but positively correlated with its copy number level. The HAVCR2 expression level was significantly positively correlated with the infiltration of six types of immune cells, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and myeloid dendritic cells. Also, the higher its expression level, the higher the immune cell abundance. Tumor immune dysfunction and exclusion (TIDE) scoring analysis showed that HAVCR2 was related to the responsiveness to TGCT immunotherapy. Drug sensitivity analysis revealed that HAVCR2 was related to the sensitivity of multiple antitumor drugs. This study demonstrated that HAVCR2 has high potential as a biomarker for the diagnosis, prognosis, and treatment of TGCTs.

Protective effect of Cornuside on OGD/R injury in SH-SY5Y cells and its underlying mechanism

Apoptosis induced by oxygen-glucose deprivation/reperfusion (OGD/R) injury is the main cause of neuronal damage. Cornuside, a small-molecule cyclic enol ether terpene glycoside extracted from the dried fruit of mature Cornus officinalis Sieb. et Zucc., has vigorous anti-apoptotic and antioxidant effects. Previous studies have shown that Cornuside can reduce apoptosis and improve mitochondrial energy metabolism in cortical neurons of rats by inhibiting caspase-3 and calcium release. In this study, we treated SH-SY5Y cells with OGD/R to simulated ischemia/reperfusion (I/R) injury. Using high-throughput transcriptome sequencing, differentially expressed genes were analyzed in the OGD/R group versus the OGD/R + Cornuside (10 μmol/L) group to explore the neuroprotective mechanisms of Cornuside. The differentially expressed genes were mainly enriched in apoptosis signaling pathway, cell cycle, DNA damage and repair, and p38/JNK MAPK and p53 signaling pathways. The results showed that OGD/R significantly reduced the survival of SH-SY5Y cells, induced apoptosis, disrupted the nucleus, promoted the release of ROS, and led to cell cycle arrest. Cornuside reversed OGD/R-induced damage. By upregulating MAPK8IP1 and downregulating MAPK14, TP53INP1, and signaling pathway-related proteins (p-p38, p-JNK, and p-p53), Cornuside ameliorated cell damage induced by p38/JNK MAPK and p53 signaling pathways. Cornuside also downregulated apoptosis regulatory proteins (Bax, Bcl-2, caspase-3, caspase-9, and cytochrome c) and cell cycle regulatory proteins (cyclin B1, cyclin E, and p21).

Physiological and immune profiling of tilapia Oreochromis niloticus gills by high-throughput single-cell transcriptome sequencing

The physiological and immune functions of fish gills are largely recognized, but their following functional heterogeneity at the single cell scale has been rarely reported. Here, we performed single cell RNA sequencing (scRNA-seq) on the gills of tilapia fish Oreochromis niloticus. We identified a total of 12 cell populations and analyzed their functional heterogeneity. To investigate the physiological function of O. niloticus gills, expression patterns of genes encoding ion transporters were selected from the identified H+-ATPase-rich cells (HR cells), Na+/K+-ATPase-rich cells (NaR cells), and pavement cells. Specific enrichment of ca4a, slc9a1a, and LOC100692482 in the HR cells of O. niloticus gills explained their functions in acid-base regulation. Genes encoding Ca2+ transporters, including atp2b1, LOC100696627, and LOC 100706765, were specifically expressed in the NaR cells. Pavement cells were presumably the main sites responsible for ammonia and urea transports in O. niloticus gills with specific enrichment of Rhbg and LOC100693008, respectively. The expression patterns of the four immune cell subtypes varied greatly, with B cells being enriched with the most immune-related GO terms. KEGG enrichment analysis showed that MAPK signaling pathway was the most enriched pathway among the four types of immune cells in O. niloticus gills. Our results are important in understanding the physiological and immune responses of fish gills at the cellular resolution.

High-throughput transcriptome analyses from ASPIRO, a phase 1/2/3 study of gene replacement therapy for X-linked myotubular myopathy

X-linked myotubular myopathy (XLMTM) is a severe congenital disease characterized by profound muscle weakness, respiratory failure, and early death. No approved therapy for XLMTM is currently available. Adeno-associated virus (AAV)-mediated gene replacement therapy has shown promise as an investigational therapeutic strategy. We aimed to characterize the transcriptomic changes in muscle biopsies of individuals with XLMTM who received resamirigene bilparvovec (AT132; rAAV8-Des-hMTM1) in the ASPIRO clinical trial and to identify potential biomarkers that correlate with therapeutic outcome. We leveraged RNA-sequencing data from the muscle biopsies of 15 study participants and applied differential expression analysis, gene co-expression analysis, and machine learning to characterize the transcriptomic changes at baseline (pre-dose) and at 24 and 48weeks after resamirigene bilparvovec dosing. As expected, MTM1 expression levels were significantly increased after dosing (p<0.0001). Differential expression analysis identified upregulated genes after dosing that were enriched in several pathways, including lipid metabolism and inflammatory response pathways, and downregulated genes were enriched in cell-cell adhesion and muscle development pathways. Genes involved in inflammatory and immune pathways were differentially expressed between participants exhibiting ventilator support reduction of either greater or less than 6 h/day after gene therapy compared to pre-dosing. Co-expression analysis identified similarly regulated genes, which were grouped into modules. Finally, the machine learning model identified five genes, including MTM1, as potential RNA biomarkers to monitor the progress of AAV gene replacement therapy. These findings further extend our understanding of AAV-mediated gene therapy in individuals with XLMTM at the transcriptomic level.