RNA-Seq methods for transcriptome analysis

Gene expression in the dorsal root ganglion and the cerebrospinal fluid metabolome in polyneuropathy and opioid tolerance in rats

First-line pharmacotherapy for peripheral neuropathic pain (NP) of diverse pathophysiology consists of antidepressants and gabapentinoids, but only a minority achieve sufficient analgesia with these drugs. Opioids are considered third-line analgesics in NP due to potential severe and unpredictable adverse effects in long-term use. Also, opioid tolerance and NP may have shared mechanisms, raising further concerns about opioid use in NP. We set out to further elucidate possible shared and separate mechanisms after chronic morphine treatment and oxaliplatin-induced and diabetic polyneuropathies, and to identify potential diagnostic markers and therapeutic targets. We analysed thermal nociceptive behaviour, the transcriptome of dorsal root ganglia (DRG) and the metabolome of cerebrospinal fluid (CSF) in these three conditions, in rats. Several genes were differentially expressed, most following oxaliplatin and least after chronic morphine treatment, compared with saline-treated rats. A few genes were differentially expressed in the DRGs in all three models (e.g. Csf3r and Fkbp5). Some, e.g. Alox15 and Slc12a5, were differentially expressed in both diabetic and oxaliplatin models. Other differentially expressed genes were associated with nociception, inflammation, and glial cells. The CSF metabolome was most significantly affected in the diabetic rats. Interestingly, we saw changes in nicotinamide metabolism, which has been associated with opioid addiction and withdrawal, in the CSF of morphine-tolerant rats. Our results offer new hypotheses for the pathophysiology and treatment of NP and opioid tolerance. In particular, the role of nicotinamide metabolism in opioid addiction deserves further study.

Transcriptomic analysis of Chaetoceros muelleri in response to different nitrogen concentrations reveals the activation of pathways to enable efficient nitrogen uptake

Nitrogen is the principal nutrient deficiency that increases lipids and carbohydrate content in diatoms but negatively affects biomass production. Marine diatom Chaetoceros muelleri is characterized by lipid and carbohydrate accumulation under low nitrogen concentration without affecting biomass. To elucidate the molecular effects of nitrogen concentrations, we performed an RNA-seq analysis of C. muelleri grown under four nitrogen concentrations (3.53 mM, 1.76 mM, 0.44 mM, and 0.18 mM of NaNO3). This research revealed that changes in global transcription in C. muelleri are differentially expressed by nitrogen concentration. "Energetic metabolism", "Carbohydrate metabolism" and "Lipid metabolism" pathways were identified as the most upregulated by N deficiency. Due to N limitation, alternative pathways to self-supply nitrogen employed by microalgal cells were identified. Additionally, nitrogen limitation decreased chlorophyll content and caused a greater response at the transcriptional level with a higher number of unigenes differentially expressed. By contrast, the highest N concentration (3.53 mM) recorded the lowest number of differentially expressed genes. Amt1, Nrt2, Fad2, Skn7, Wrky19, and Dgat2 genes were evaluated by RT-qPCR. In conclusion, C. muelleri modify their metabolic pathways to optimize nitrogen utilization and minimize nitrogen losses. On the other hand, the assembled transcriptome serves as the basis for metabolic engineering focused on improving the quantity and quality of the diatom for biotechnological applications. However, proteomic and metabolomic analysis is also required to compare gene expression, protein, and metabolite accumulation.

Molecular biomarkers identification and applications in CHO bioprocessing

Biomarkers are valuable tools in clinical research where they allow to predict susceptibility to diseases, or response to specific treatments. Likewise, biomarkers can be extremely useful in the biomanufacturing of therapeutic proteins. Indeed, constraints such as short timelines and the need to find hyper-productive cells could benefit from a data-driven approach during cell line and process development. Many companies still rely on large screening capacities to develop productive cell lines, but as they reach a limit of production, there is a need to go from empirical to rationale procedures. Similarly, during bioprocessing runs, substrate consumption and metabolism wastes are commonly monitored. None of them possess the ability to predict the culture behavior in the bioreactor. Big data driven approaches are being adapted to the study of industrial mammalian cell lines, enabled by the publication of Chinese hamster and CHO genome assemblies which allowed the use of next-generation sequencing with these cells, as well as continuous proteome and metabolome annotation. However, if these different -omics technologies contributed to the characterization of CHO cells, there is a significant effort remaining to apply this knowledge to biomanufacturing methods. The correlation of a complex phenotype such as high productivity or rapid growth to the presence or expression level of a specific biomarker could save time and effort in the screening of manufacturing cell lines or culture conditions. In this review we will first discuss the different biological molecules that can be identified and quantified in cells, their detection techniques, and associated challenges. We will then review how these markers are used during the different steps of cell line and bioprocess development, and the inherent limitations of this strategy.

Engineering a Microfluidic Platform to Cryopreserve Stem Cells: A DMSO-Free Sustainable Approach

Human adipose-derived stem cells (hASCs) are cryopreserved traditionally using dimethyl sulfoxide (DMSO) as the cryoprotectant agent. DMSO penetrates cell membranes and prevents cellular damage during cryopreservation. However, DMSO is not inert to cells, inducing cytotoxic effects by causing mitochondrial dysfunction, reduced cell proliferation, and impaired hASCs transplantation. Additionally, large-scale production of DMSO and contamination can adversely impact the environment. A sustainable, green alternative to DMSO is trehalose, a natural disaccharide cryoprotectant agent that does not pose any risk of cytotoxicity. However, the cellular permeability of trehalose is less compared to DMSO. Here, a microfluidic chip is developed for the intracellular delivery of trehalose in hASCs. The chip is designed for mechanoporation, which creates transient pores in cell membranes by mechanical deformation. Mechanoporation allows the sparingly permeable trehalose to be internalized within the cell cytosol. The amount of trehalose delivered intracellularly is quantified and optimized based on cellular compatibility and functionality. Furthermore, whole-transcriptome sequencing confirms that less than 1% of all target genes display at least a twofold change in expression when cells are passed through the chip compared to untreated cells. Overall, the results confirm the feasibility and effectiveness of using this microfluidic chip for DMSO-free cryopreservation of hASCs.

Assessing inorganic nanoparticle toxicity through omics approaches

In the last two decades, the development of nanotechnology has resulted in inorganic nanoparticles playing crucial roles in key industries, ranging from healthcare to energy technologies. For instance, gold and silver nanoparticles are widely used in rapid COVID-19 and flu tests, titania and zinc oxide nanoparticles are commonly found in cosmetic products, and superparamagnetic iron oxide nanoparticles have been clinically exploited as contrast agents and anti-anemia medicines. As a result, human exposure to nanomaterials is continuously increasing, raising concerns about their potential adverse health effects. Historically, the study of nanoparticle toxicity has largely relied on macroscopic observations obtained in different in vitro and in vivo models, resulting in readouts such as median lethal dose, biodistribution profile, and/or histopathological assessment. In recent years, omics methodologies, including transcriptomics, epigenomics, proteomics, metabolomics, and lipidomics, are increasingly used to characterize the biological interactions of nanomaterials, providing a better and broader understanding of their impact and mechanisms of toxicity. These approaches have been able to identify important genes and gene products that mediate toxicological effects, as well as endogenous functions and pathways dysregulated by nanoparticles. Omics methods improve our understanding of nanoparticle biology, and unravel mechanistic insights into nanomedicine-based therapies. This review aims to provide a deeper understanding and new perspectives of omics approaches to characterize the toxicity and biological interactions of inorganic nanoparticles, and improve the safety of nanoparticle applications.

Advances in the molecular biology of the solitary fibrous tumor and potential impact on clinical applications

Solitary fibrous tumor (SFT) is a rare fibroblastic mesenchymal neoplasm. The current classification has merged SFT and hemangiopericytoma (HPC) into the same tumor entity, while the risk stratification models have been developed to compensate for clinical prediction. Typically, slow-growing and asymptomatic, SFT can occur in various anatomical sites, most commonly in the pleura. Histologically, SFT consists of spindle to oval cells with minimal patterned growth, surrounded by stromal collagen and unique vascular patterns. Molecularly, SFT is defined by the fusion of NGFI-A-binding protein 2 (NAB2) and signal transducer and activator of transcription 6 (STAT6) genes as NAB2-STAT6. This fusion transforms NAB2 into a transcriptional activator, activating early growth response 1 (EGR1) and contributing to SFT pathogenesis and development. There are several fusion variants of NAB2-STAT6 in tumor tissues, with the most frequent ones being NAB2ex4-STAT6ex2 and NAB2ex6-STAT6ex16/ex17. Diagnostic methods play a crucial role in SFT clinical practice and basic research, including RT-PCR, next-generation sequencing (NGS), FISH, immunohistochemistry (IHC), and Western blot analysis, each with distinct capabilities and limitations. Traditional treatment strategies of SFT encompass surgical resection, radiation therapy, and chemotherapy, while emerging management regimes include antiangiogenic agents, immunotherapy, RNA-targeting technologies, and potential targeted drugs. This review provides an update on SFT's clinical and molecular aspects, diagnostic methods, and potential therapies.

A ligation-independent sequencing method reveals tRNA-derived RNAs with blocked 3' termini

Despite the numerous sequencing methods available, the diversity in RNA size and chemical modification makes it difficult to capture all RNAs in a cell. We developed a method that combines quasi-random priming with template switching to construct sequencing libraries from RNA molecules of any length and with any type of 3' modifications, allowing for the sequencing of virtually all RNA species. Our ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to identify and quantify all classes of coding and non-coding RNAs. With LIDAR, we comprehensively characterized the transcriptomes of mouse embryonic stem cells, neural progenitor cells, mouse tissues, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared with traditional ligation-dependent sequencing methods and uncovered tDRs with blocked 3' ends that had previously escaped detection. Therefore, LIDAR can capture all RNAs in a sample and uncover RNA species with potential regulatory functions.

Genomic Considerations in the Treatment of Thyroid Carcinoma

Highlighting genomically driven targeted therapies to improve outcomes in advanced thyroid carcinoma.

An improved bacterial mRNA enrichment strategy in dual RNA sequencing to unveil the dynamics of plant-bacterial interactions

BACKGROUND

Dual RNA sequencing is a powerful tool that enables a comprehensive understanding of the molecular dynamics underlying plant-microbe interactions. RNA sequencing (RNA-seq) poses technical hurdles in the transcriptional analysis of plant-bacterial interactions, especially in bacterial transcriptomics, owing to the presence of abundant ribosomal RNA (rRNA), which potentially limits the coverage of essential transcripts. Therefore, to achieve cost-effective and comprehensive sequencing of the bacterial transcriptome, it is imperative to devise efficient methods for eliminating rRNA and enhancing the proportion of bacterial mRNA. In this study, we modified a strand-specific dual RNA-seq method with the goal of enriching the proportion of bacterial mRNA in the bacteria-infected plant samples. The enriched method involved the sequential separation of plant mRNA by poly A selection and rRNA removal for bacterial mRNA enrichment followed by strand specific RNA-seq library preparation steps. We assessed the efficiency of the enriched method in comparison to the conventional method by employing various plant-bacterial interactions, including both host and non-host resistance interactions with pathogenic bacteria, as well as an interaction with a beneficial rhizosphere associated bacteria using pepper and tomato plants respectively.

RESULTS

In all cases of plant-bacterial interactions examined, an increase in mapping efficiency was observed with the enriched method although it produced a lower read count. Especially in the compatible interaction with Xanthmonas campestris pv. Vesicatoria race 3 (Xcv3), the enriched method enhanced the mapping ratio of Xcv3-infected pepper samples to its own genome (15.09%; 1.45-fold increase) and the CDS (8.92%; 1.49-fold increase). The enriched method consistently displayed a greater number of differentially expressed genes (DEGs) than the conventional RNA-seq method at all fold change threshold levels investigated, notably during the early stages of Xcv3 infection in peppers. The Gene Ontology (GO) enrichment analysis revealed that the DEGs were predominantly enriched in proteolysis, kinase, serine type endopeptidase and heme binding activities.

CONCLUSION

The enriched method demonstrated in this study will serve as a suitable alternative to the existing RNA-seq method to enrich bacterial mRNA and provide novel insights into the intricate transcriptomic alterations within the plant-bacterial interplay.

LINCATRA: Two-cycle method to amplify RNA for transcriptome analysis from formalin-fixed paraffin-embedded tissue

Whole transcriptome analysis (WTA) using RNA extracted from Formalin Fixed Paraffin Embedded (FFPE) tissue is an invaluable tool to understand the molecular pathology of disease. RNA extracted from FFPE tissue is either degraded and/or in very low quantities hampering gene expression analysis. Earlier studies described protocols applied for cellular RNA using poly-A primer-based linear amplification. The current study describes a method, LINCATRA (LINear amplifiCAtion of RNA for whole TRAnscriptome analysis). It employs random nonamer primer based method which can amplify short, fragmented RNA with high fidelity from as low as 5 ng to obtain enough material for WTA. The two-cycle method significantly amplified RNA at ∼1000 folds (p < 0.0001) improving the mean read lengths (p < 0.05) in WTA. Overall, increased mean read length positively correlated with on-target reads (Pearson's r = 0.71, p < 0.0001) in both amplified and unamplified RNA-seq analysis. Gene expression analysis compared between unamplified and amplified group displayed substantial overlap of the differentially expressed genes (DEGs) (log2 fold change cut-off < -2 and >2, p < 0.05) identified between lung cancer and asthma cohorts validating the method developed. This method is applicable in clinical molecular pathology field for both diagnostics and elucidation of disease mechanisms.

Landscape analysis of alternative splicing in kidney renal clear cell carcinoma and their clinical significance

A growing number of studies reveal that alternative splicing (AS) is associated with tumorigenesis, progression, and metastasis. Systematic analysis of alternative splicing signatures in renal cancer is lacking. In our study, we investigated the AS landscape of kidney renal clear cell carcinoma (KIRC) and identified AS predictive model to improve the prognostic prediction of KIRC. We obtained clinical data and gene expression profiles of KIRC patients from the TCGA database to evaluate AS events. The calculation results for seven types of AS events indicated that 46276 AS events from 10577 genes were identified. Next, we applied Cox regression analysis to identify 5864 prognostic-associated AS events. We used the Metascape database to verify the potential pathways of prognostic-associated AS. Moreover, we constructed KIRC prediction systems with prognostic-associated AS events by the LASSO Cox regression model. AUCs demonstrated that these prediction systems had excellent prognostic accuracy simultaneously. We identified 34 prognostic associated splicing factors (SFs) and constructed homologous regulatory networks. Furthermore, in vitro experiments were performed to validate the favorable effect of SFs FMR1 in KIRC. In conclusion, we overviewed AS events in KIRC and identified AS-based prognostic models to assist the survival prediction of KIRC patients. Our study may provide a novel predictive signature to improve the prognostic prediction of KIRC, which might facilitate KIRC patient counseling and individualized management.

RNA Sequencing Analyses Reveal the Potential Anti-Inflammatory Mechanisms of Acacetin Against ODG/R Injuries in Microglia

Background

Acacetin is a natural flavonoid known for its anti-tumor, antioxidant, and anti-inflammatory properties. Our previous studies have shown its protective effects against cerebral ischemia-reperfusion injury (IRI), but the underlying molecular mechanisms remain unclear.

Purpose

The study delves into acacetin's mechanism in mitigating cerebral IRI, with a focus on transcriptomic insights.

Methods

We established the oxygen-glucose deprivation/re-oxygenation (OGD/R) model in BV2 microglia, treating them with 10μM acacetin. Then we assessed cell proliferation using CCK-8 and measured Lactate Dehydrogenase (LDH) release. High-throughput RNA sequencing (RNA-seq) underpinned the analysis of differentially expressed genes (DEGs) and long non-coding RNAs (lncRNAs), functional enrichment, and alternative splicing events (ASEs), validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).

Results

OGD/R injury significantly impaired cell proliferation and increased LDH release, effects mitigated by acacetin. RNA-seq identified 2148 upregulated and 2135 downregulated DEGs post-OGD/R. In contrast, the acacetin-treated group showed 248 upregulated and 240 downregulated DEGs compared to the OGD/R group. All DEGs were enriched in both Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Overlapping analysis indicated that acacetin treatment reversed the expression of 203 genes affected by OGD/R, including inflammation-related genes such as Isg15, Fcgr1, Il1b, and Parp12. Moreover, the oxidative stress-related gene, Mt2, was downregulated post-OGD/R but upregulated following acacetin treatment. We further found that OGD/R and acacetin treatment could modulate gene splicing events, impacting cell apoptosis or inflammatory responses, such as the A3SS splicing event in the Trim47 gene. RNA-seq also highlighted differential expression of numerous lncRNAs, particularly the upregulation of lncRNA Rmrp and Terc post-OGD/R and their subsequent downregulation post-acacetin treatment. These lncRNAs might regulate cell proliferation through mediating target gene expressions. RT-qPCR validation confirmed these findings.

Conclusion

Significant upregulation of genes and ASEs linked to oxidative stress and inflammatory response is observed in cerebral IRI. Acacetin intervention reverses these effects, highlighting its mechanism in alleviating the injury by modulating gene expression and splicing events.

Fine mapping of leaf delayed virescence gene dv4 in Triticum aestivum

Wheat (Triticum aestivum L.) is one of the most important crops worldwide, and its yield affects national food security. Wheat leaves are key photosynthetic organs where carbohydrates are synthesized for grain yield. Leaf colour mutants are ideal germplasm resources for molecular genetic studies of wheat chloroplast development, chlorophyll synthesis and photosynthesis. We obtained a wheat mutant delayed virescence 4 (dv4) from cultivar Guomai 301. The leaves of mutant dv4 were pale yellow at the seedling stage, golden yellow at the turning green stage, and they started to turn green at the jointing stage. Genetic analysis demonstrated that the yellow-leaf phenotype was controlled by a single recessive gene named as dv4. Gene dv4 was fine mapped in a 1.46 Mb region on chromosome 7DS by SSR and dCAPS marker assays. Three putative candidate genes were identified in this region. Because no leaf colour genes have been reported on wheat chromosome arm 7DS previously, dv4 is a novel leaf colour gene. The result facilitates map-based cloning of dv4 and provides information for the construction of a high-photosynthetic efficiency ideotype for improving wheat yield.

[Identification of potential pathogenic genes of intestinal metaplasia based on transcriptomic sequencing and bioinformatics analysis]

OBJECTIVE

To explore the potential pathogenic genes of intestinal metaplasia.

METHODS

Twenty-one patients with intestinal metaplasia admitted to the Department of Gastroenterology at the Second Affiliated Hospital of Anhui University of Chinese Medicine from January, 2022 to June, 2022, and 21 healthy subjects undergoing gastroscopic examination during the same period were enrolled in this study. All the participants underwent gastroscopy and pathological examination, and gastric tissue samples were collected for transcriptome sequencing to screen for differentially expressed genes (DEGs). The biological functions of the DEGs were analyzed using bioinformatics analysis, and qRT-PCR was used to validate the results.

RESULTS

Transcriptomic sequencing identified a total of 1373 DEGs, including 827 upregulated and 546 downregulated ones. The top 6 upregulated genes (AGMAT, CCL25, FABP1, CDX1, SPINK4, and MUC2), ranked based on their significance and average expression level, were selected for validation, and qRT-PCR showed significant upregulation of their mRNAs in the gastric tissues of patients with intestinal metaplasia (P < 0.05).

CONCLUSION

AGMAT, CCL25, FABP1, CDX1, SPINK4, and MUC2 participate in the occurrence and development of intestinal metaplasia, and may serve as potential biomarkers for diagnosing intestinal metaplasia.

Dual RNA-seq in filarial nematodes and Wolbachia endosymbionts using RNase H based ribosomal RNA depletion

Lymphatic filariasis is caused by parasitic nematodes and is a leading cause of disability worldwide. Many filarial worms contain the bacterium Wolbachia as an obligate endosymbiont. RNA sequencing is a common technique used to study their molecular relationships and to identify potential drug targets against the nematode and bacteria. Ribosomal RNA (rRNA) is the most abundant RNA species, accounting for 80-90% of the RNA in a sample. To reduce sequencing costs, it is necessary to remove ribosomal reads through poly-A enrichment or ribosomal depletion. Bacterial RNA does not contain a poly-A tail, making it difficult to sequence both the nematode and Wolbachia from the same library preparation using standard poly-A selection. Ribosomal depletion can utilize species-specific oligonucleotide probes to remove rRNA through pull-down or degradation methods. While species-specific probes are commercially available for many commonly studied model organisms, there are currently limited depletion options for filarial parasites. Here, we performed total RNA sequencing from Brugia malayi containing the Wolbachia symbiont (wBm) and designed ssDNA depletion probes against their rRNA sequences. We compared the total RNA library to poly-A enriched, Terminator 5'-Phosphate-Dependent Exonuclease treated, NEBNext Human/Bacteria rRNA depleted and our custom nematode probe depleted libraries. The custom nematode depletion library had the lowest percentage of ribosomal reads across all methods, with a 300-fold decrease in rRNA when compared to the total RNA library. The nematode depletion libraries also contained the highest percentage of Wolbachia mRNA reads, resulting in a 16-1,000-fold increase in bacterial reads compared to the other enrichment and depletion methods. Finally, we found that the Brugia malayi depletion probes can remove rRNA from the filarial worm Dirofilaria immitis and the majority of rRNA from the more distantly related free living nematode Caenorhabditis elegans. These custom filarial probes will allow for future dual RNA-seq experiments between nematodes and their bacterial symbionts from a single sequencing library.

Enhancement of vitamin B6 production driven by omics analysis combined with fermentation optimization

BACKGROUND

Microbial engineering aims to enhance the ability of bacteria to produce valuable products, including vitamin B6 for various applications. Numerous microorganisms naturally produce vitamin B6, yet the metabolic pathways involved are rigorously controlled. This regulation by the accumulation of vitamin B6 poses a challenge in constructing an efficient cell factory.

RESULTS

In this study, we conducted transcriptome and metabolome analyses to investigate the effects of the accumulation of pyridoxine, which is the major commercial form of vitamin B6, on cellular processes in Escherichia coli. Our omics analysis revealed associations between pyridoxine and amino acids, as well as the tricarboxylic acid (TCA) cycle. Based on these findings, we identified potential targets for fermentation optimization, including succinate, amino acids, and the carbon-to-nitrogen (C/N) ratio. Through targeted modifications, we achieved pyridoxine titers of approximately 514 mg/L in shake flasks and 1.95 g/L in fed-batch fermentation.

CONCLUSION

Our results provide insights into pyridoxine biosynthesis within the cellular metabolic network for the first time. Our comprehensive analysis revealed that the fermentation process resulted in a remarkable final yield of 1.95 g/L pyridoxine, the highest reported yield to date. This work lays a foundation for the green industrial production of vitamin B6 in the future.

Anthocyanin of Black Highland Barley Alleviates H2O2-Induced Cardiomyocyte Injury and Myocardial Infarction via Activating the Phosphatase and Tensin Homolog/Phosphatidylinositol 3-Kinase/Protein Kinase B Pathway

Cardiovascular disease (CVD) represents a substantial global health challenge, with its impact on mortality and morbidity rates surpassing that of cancer. The present study was designed to explore the cardioprotective properties of anthocyanin (ACN), a compound derived from black barley, against oxidative stress-induced damage in myocardial cells and to uncover the molecular mechanisms at play. Utilizing both in vitro and in vivo experimental models, our findings indicate that ACN notably reduced cell damage caused by oxidative stress and effectively prevented apoptosis. High-throughput RNA sequencing analysis has shed light on the mechanism by which ACN achieves its antioxidative stress effects, implicating the PTEN-Akt signaling pathway. ACN was found to modulate PTEN expression levels, which in turn influences the Akt pathway, leading to a reduction in apoptotic processes. This novel insight lays the groundwork for the potential clinical utilization of ACN in the management of CVD. While this study has shed light on some of the functions of ACN, it is important to recognize that natural compounds often interact with multiple molecular targets and engage in intricate signaling cascades. Future research endeavors will concentrate on further elucidating the regulatory mechanisms by which ACN influences PTEN expression, with the goal of enhancing our comprehension and expanding the therapeutic potential of ACN in the treatment of cardiovascular conditions.

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

Integrative analysis of metabolomics and transcriptomics to uncover biomarkers in sepsis

To utilize metabolomics in conjunction with RNA sequencing to identify biomarkers in the blood of sepsis patients and discover novel targets for diagnosing and treating sepsis. In January 2019 and December 2020, blood samples were collected from a cohort of 16 patients diagnosed with sepsis and 11 patients diagnosed with systemic inflammatory response syndrome (SIRS). Non-targeted metabolomics analysis was conducted using liquid chromatography coupled with mass spectrometry (LC-MS/MS technology), while gene sequencing was performed using RNA sequencing. Afterward, the metabolite data and sequencing data underwent quality control and difference analysis, with a fold change (FC) greater than or equal to 2 and a false discovery rate (FDR) less than 0.05.Co-analysis was then performed to identify differential factors with consistent expression trends based on the metabolic pathway context; KEGG enrichment analysis was performed on the crossover factors, and Meta-analysis of the targets was performed at the transcriptome level using the public dataset. In the end, a total of five samples of single nucleated cells from peripheral blood (two normal controls, one with systemic inflammatory response syndrome, and two with sepsis) were collected and examined to determine the cellular location of the essential genes using 10× single cell RNA sequencing (scRNA-seq). A total of 485 genes and 1083 metabolites were found to be differentially expressed in the sepsis group compared to the SIRS group. Among these, 40 genes were found to be differentially expressed in both the metabolome and transcriptome. Functional enrichment analysis revealed that these genes were primarily involved in biological processes related to inflammatory response, immune regulation, and amino acid metabolism. Furthermore, a meta-analysis identified four genes, namely ITGAM, CD44, C3AR1, and IL2RG, which were highly expressed in the sepsis group compared to the normal group (P < 0.05). Additionally, scRNA-seq analysis revealed that the core genes ITGAM and C3AR1 were predominantly localized within the macrophage lineage. The primary genes ITGAM and C3AR1 exhibit predominant expression in macrophages, which play a significant role in inflammatory and immune responses. Moreover, these genes show elevated expression levels in the plasma of individuals with sepsis, indicating their potential as valuable subjects for further research in sepsis.

Transcriptomics of Human Brain Tissue in Parkinson's Disease: a Comparison of Bulk and Single-cell RNA Sequencing

Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease leading to motor dysfunction and, in some cases, dementia. Transcriptome analysis is one promising approach for characterizing PD and other neurodegenerative disorders by informing how specific disease events influence gene expression and contribute to pathogenesis. With the emergence of single-cell and single-nucleus RNA sequencing (scnRNA-seq) technologies, the transcriptional landscape of neurodegenerative diseases can now be described at the cellular level. As the application of scnRNA-seq is becoming routine, it calls to question how results at a single-cell resolution compare to those obtained from RNA sequencing of whole tissues (bulk RNA-seq), whether the findings are compatible, and how the assays are complimentary for unraveling the elusive transcriptional changes that drive neurodegenerative disease. Herein, we review the studies that have leveraged RNA-seq technologies to investigate PD. Through the integration of bulk and scnRNA-seq findings from human, post-mortem brain tissue, we use the PD literature as a case study to evaluate the compatibility of the results generated from each assay and demonstrate the complementarity of the sequencing technologies. Finally, through the lens of the PD transcriptomic literature, we evaluate the current feasibility of bulk and scnRNA-seq technologies to illustrate the necessity of both technologies for achieving a comprehensive insight into the mechanism by which gene expression promotes neurodegenerative disease. We conclude that the continued application of both assays will provide the greatest insight into neurodegenerative disease pathology, providing both cell-specific and whole-tissue level information.

Transcriptional patterns of human retinal pigment epithelial cells under protracted high glucose

BACKGROUND

The retinal pigment epithelium (RPE) is essential for retinal homeostasis. Comprehensively exploring the transcriptional patterns of diabetic human RPE promotes the understanding of diabetic retinopathy (DR).

METHODS AND RESULTS

A total of 4125 differentially expressed genes (DEGs) were screened out from the human primary RPE cells subjected to prolonged high glucose (HG). The subsequent bioinformatics analysis is divided into 3 steps. In Step 1, 21 genes were revealed by intersecting the enriched genes from the KEGG, WIKI, and Reactome databases. In Step 2, WGCNA was applied and intersected with the DEGs. Further intersection based on the enrichments with the GO biological processes, GO cellular components, and GO molecular functions databases screened out 12 candidate genes. In Step 3, 13 genes were found to be simultaneously up-regulated in the DEGs and a GEO dataset involving human diabetic retinal tissues. VEGFA and ERN1 were the 2 starred genes finally screened out by overlapping the 3 Steps.

CONCLUSION

In this study, multiple genes were identified as crucial in the pathological process of RPE under protracted HG, providing potential candidates for future researches on DR. The current study highlights the importance of RPE in DR pathogenesis.

Curare and GenExVis: a versatile toolkit for analyzing and visualizing RNA-Seq data

Even though high-throughput transcriptome sequencing is routinely performed in many laboratories, computational analysis of such data remains a cumbersome process often executed manually, hence error-prone and lacking reproducibility. For corresponding data processing, we introduce Curare, an easy-to-use yet versatile workflow builder for analyzing high-throughput RNA-Seq data focusing on differential gene expression experiments. Data analysis with Curare is customizable and subdivided into preprocessing, quality control, mapping, and downstream analysis stages, providing multiple options for each step while ensuring the reproducibility of the workflow. For a fast and straightforward exploration and visualization of differential gene expression results, we provide the gene expression visualizer software GenExVis. GenExVis can create various charts and tables from simple gene expression tables and DESeq2 results without the requirement to upload data or install software packages. In combination, Curare and GenExVis provide a comprehensive software environment that supports the entire data analysis process, from the initial handling of raw RNA-Seq data to the final DGE analyses and result visualizations, thereby significantly easing data processing and subsequent interpretation.

RNAvigate: efficient exploration of RNA chemical probing datasets

Chemical probing technologies enable high-throughput examination of diverse structural features of RNA, including local nucleotide flexibility, RNA secondary structure, protein and ligand binding, through-space interaction networks, and multistate structural ensembles. Deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multilayered relationships. Current platforms lack the broad accessibility, flexibility and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library that automatically parses 21 standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs 18 plot types. RNAvigate enables efficient exploration of nuanced relationships between multiple layers of RNA structure information and across multiple experimental conditions. Compatibility with Jupyter notebooks enables nonburdensome, reproducible, transparent and organized sharing of multistep analyses and data visualization strategies. RNAvigate simplifies and accelerates discovery and characterization of RNA-centric functions in biology.

Translation variation across genetic backgrounds reveals a post-transcriptional buffering signature in yeast

Gene expression is known to vary among individuals, and this variability can impact the phenotypic diversity observed in natural populations. While the transcriptome and proteome have been extensively studied, little is known about the translation process itself. Here, we therefore performed ribosome and transcriptomic profiling on a genetically and ecologically diverse set of natural isolates of the Saccharomyces cerevisiae yeast. Interestingly, we found that the Euclidean distances between each profile and the expression fold changes in each pairwise isolate comparison were higher at the transcriptomic level. This observation clearly indicates that the transcriptional variation observed in the different isolates is buffered through a phenomenon known as post-transcriptional buffering at the translation level. Furthermore, this phenomenon seemed to have a specific signature by preferentially affecting essential genes as well as genes involved in complex-forming proteins, and low transcribed genes. We also explored the translation of the S. cerevisiae pangenome and found that the accessory genes related to introgression events displayed similar transcription and translation levels as the core genome. By contrast, genes acquired through horizontal gene transfer events tended to be less efficiently translated. Together, our results highlight both the extent and signature of the post-transcriptional buffering.

Noxa inhibits oncogenesis through ZNF519 in gastric cancer and is suppressed by hsa-miR-200b-3p

While Phorbol-12-myristate-13-acetate-induced protein 1 (Noxa/PMAIP1) assumes a pivotal role in numerous tumors, its clinical implications and underlying mechanisms of gastric cancer (GC) are yet enigmatic. In this investigation, our primary objective was to scrutinize the clinical relevance and potential mechanisms of Noxa in gastric cancer. Immunohistochemical analysis was conducted on tissue microarrays comprising samples from a meticulously characterized cohort of 84 gastric cancer patients, accompanied by follow-up data, to assess the expression of Noxa. Additionally, Noxa expression levels in gastric cancer clinical samples and cell lines were measured through quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis. The effect of Noxa expression on the prognosis of patients with gastric cancer was evaluated using Kaplan-Meier survival. Further insight into the role of Noxa in driving gastric cancer progression was gained through an array of experimental techniques, including cell viability assays (CCK8), plate cloning assays, transwell assays, scratch assays, and real-time cell analysis (RTCA). Potential upstream microRNAs (miRNAs) that might modulate Noxa were identified through rigorous bioinformatics analysis, substantiated by luciferase reporter assays and Western blot experiments. Additionally, we utilized RNA sequencing, qRT-PCR, and Western blot to identify proteins binding to Noxa and potential downstream target. Finally, we utilized BALB/c nude mice to explore the role of Noxa in vivo. Our investigation unveiled a marked downregulation of Noxa expression in gastric cancer and underscored its significance as a pivotal prognostic factor influencing overall survival (OS). Noxa overexpression exerted a substantial inhibitory effect on the proliferation, migration and invasion of GC cells. Bioinformatic analysis and dual luciferase reporter assays unveiled the capacity of hsa-miR-200b-3p to interact with the 3'-UTR of Noxa mRNA, thereby orchestrating a downregulation of Noxa expression in vitro, consequently promoting tumor progression in GC. Our transcriptome analysis, coupled with mechanistic validation, elucidated a role for Noxa in modulating the expression of ZNF519 in the Mitophagy-animal pathway. The depletion of ZNF519 effectively reversed the oncogenic attributes induced by Noxa. Upregulation of Noxa expression suppressed the tumorigenesis of GC in vivo. The current investigation sheds light on the pivotal role of the hsa-miR-200b-3p/Noxa/ZNF519 axis in elucidating the pathogenesis of gastric cancer, offering a promising avenue for targeted therapeutic interventions in the management of this challenging malignancy.

Differentially expressed genes of RNA-seq data are suggested on the intersections of normalization techniques

Data normalization is the critical step for the RNA-seq data analysis. Several techniques are suggested for the normalization of transcript reads in the samples. In this study, the differentially expressed genes (DEGs) are generated from the TCGA normalized laryngeal cancer data obtained using the TPM, FPKM, and DESeq2 techniques. The results showed that the reports of DEGs were different based on the normalization techniques. We suggested that the DEG intersections obtain the top transcripts from the normalized data in support of the pathway enrichment process.

Genome and transcriptome sequencing of Trichoderma harzianum T4, an important biocontrol fungus of Rhizoctonia solani, reveals genes related to mycoparasitism

Trichoderma harzianum is a well-known biological control strain and a mycoparasite of Rhizoctonia solani. To explore the mechanisms of mycoparasitism, the genome and transcriptome of T. harzianum T4 were both assembled and analyzed in this study. The genome of T. harzianum T4 was assembled into 106 scaffolds, sized 41.25 Mb, and annotated with a total of 8118 predicted genes. We analyzed the transcriptome of T. harzianum T4 against R. solani in a dual culture in three culture periods: before contact (BC), during contact (C), and after contact (AC). Transcriptome sequencing identified 1092, 1222, and 2046 differentially expressed genes (DEGs), respectively. These DEGs, which are involved in pathogen recognition and signal transduction, hydrolase, transporters, antibiosis, and defense-related functional genes, are significantly upregulated in the mycoparasitism process. The results of genome and transcriptome analysis indicated that the mycoparasitism process of T. harzianum T4 was very complex. T. harzianum successfully recognizes and invades host cells and kills plant pathogens by regulating various DEGs at different culture periods. The relative expression levels of the 26 upregulated DEGs were confirmed by RT-qPCR to validate the reliability of the transcriptome data. The results provide insight into the molecular mechanisms underlying T. harzianum T4's mycoparasitic processes, and they provide a potential molecular target for the biological control mechanism of T. harzianum T4.

Investigation of the General Molecular Mechanisms of Gallic Acid via Analyses of Its Transcriptome Profile

Gallic acid (GA), a phenolic compound naturally found in many plants, exhibits potential preventive and therapeutic roles. However, the underlying molecular mechanisms of its diverse biological activities remain unclear. Here, we investigated possible mechanisms of GA function through a transcriptome-based analysis using LINCS L1000, a publicly available data resource. We compared the changes in the gene expression profiles induced by GA with those induced by FDA-approved drugs in three cancer cell lines (A549, PC3, and MCF7). The top 10 drugs exhibiting high similarity with GA in their expression patterns were identified by calculating the connectivity score in the three cell lines. We specified the known target proteins of these drugs, which could be potential targets of GA, and identified 19 potential targets. Next, we retrieved evidence in the literature that GA likely binds directly to DNA polymerase β and ribonucleoside-diphosphate reductase. Although our results align with previous studies suggesting a direct and/or indirect connection between GA and the target proteins, further experimental investigations are required to fully understand the exact molecular mechanisms of GA. Our study provides insights into the therapeutic mechanisms of GA, introducing a new approach to characterizing therapeutic natural compounds using transcriptome-based analyses.

Anciently duplicated genes continuously recruited to heart expression in vertebrate evolution are associated with heart chamber increase

Although gene/genome duplications in the early stage of vertebrates have been thought to provide major resources of raw genetic materials for evolutionary innovations, it is unclear whether they continuously contribute to the evolution of morphological complexity during the course of vertebrate evolution, such as the evolution from two heart chambers (fishes) to four heart chambers (mammals and birds). We addressed this issue by our heart RNA-Seq experiments combined with published data, using 13 vertebrates and one invertebrate (sea squirt, as an outgroup). Our evolutionary transcriptome analysis showed that number of ancient paralogous genes expressed in heart tends to increase with the increase of heart chamber number along the vertebrate phylogeny, in spite that most of them were duplicated at the time near to the origin of vertebrates or even more ancient. Moreover, those paralogs expressed in heart exert considerably different functions from heart-expressed singletons: the former are functionally enriched in cardiac muscle and muscle contraction-related categories, whereas the latter play more basic functions of energy generation like aerobic respiration. These findings together support the notion that recruiting anciently paralogous genes that are expressed in heart is associated with the increase of chamber number in vertebrate evolution.

Circulating Nucleic Acids in Colorectal Cancer: Diagnostic and Prognostic Value

Colorectal cancer (CRC) is the third most prevalent cancer in the world and the fourth leading cause of cancer-related mortality. DNA (cfDNA/ctDNA) and RNA (cfRNA/ctRNA) in the blood are promising noninvasive biomarkers for molecular profiling, screening, diagnosis, treatment management, and prognosis of CRC. Technological advancements that enable precise detection of both genetic and epigenetic abnormalities, even in minute quantities in circulation, can overcome some of these challenges. This review focuses on testing for circulating nucleic acids in the circulation as a noninvasive method for CRC detection, monitoring, detection of minimal residual disease, and patient management. In addition, the benefits and drawbacks of various diagnostic techniques and associated bioinformatics tools have been detailed.

Transcriptome and lipidome integration unveils mechanisms of fatty liver formation in Shitou geese

Geese evolved from migratory birds, and when they consume excessive high-energy feed, glucose is converted into triglycerides. A large amount of triglyceride deposition can induce incomplete oxidation of fatty acids, leading to lipid accumulation in the liver and the subsequent formation of fatty liver. In the Chaoshan region of Guangdong, China, Shitou geese develop a unique form of fatty liver through 24 h overfeeding of brown rice. To investigate the mechanisms underlying the formation of fatty liver in Shitou geese, we collected liver samples from normally fed and overfed geese. The results showed that the liver size in the treatment group was significantly larger, weighing 3.5 times more than that in the control group. Extensive infiltration of lipid droplets was observed in the liver upon staining of tissue sections. Biochemical analysis revealed that compared to the control group, the treatment group showed significantly elevated levels of total cholesterol (T-CHO), triglycerides (TG), and glycogen in the liver. However, no significant differences were observed in the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), which are common indicators of liver damage. Furthermore, we performed a combined transcriptomic and lipidomic analysis of the liver samples and identified 1,510 differentially expressed genes (DEGs) and 1,559 significantly differentially abundant metabolites (SDMs). The enrichment analysis of the DEGs revealed their enrichment in metabolic pathways, cellular process-related signaling pathways, and specific lipid metabolism pathways. We also conducted KEGG enrichment analysis of the SDMs and compared them with the enriched signaling pathways obtained from the DEGs. In this study, we identified 3 key signaling pathways involved in the formation of fatty liver in Shitou geese, namely, the biosynthesis of unsaturated fatty acids, glycerol lipid metabolism, and glycerophospholipid metabolism. In these pathways, genes such as glycerol-3-phosphate acyltransferase, mitochondrial (GPAM), 1-acylglycerol-3-phosphate O-acyltransferase 2 (AGPAT2), diacylglycerol O-acyltransferase 2 (DGAT2), lipase, endothelial (LIPG), lipoprotein lipase (LPL), phospholipase D family member 4 (PLD4), and phospholipase A2 group IVF (PLA2G4F) may regulate the synthesis of metabolites, including triacylglycerol (TG), phosphatidate (PA), 1,2-diglyceride (DG), phosphatidylethanolamine (PE), and phosphatidylcholine (PC). These genes and metabolites may play a predominant role in the development of fatty liver, ultimately promoting the accumulation of TG in the liver and leading to the progression of fatty liver.

scCensus: Off-target scRNA-seq reads reveal meaningful biology

Single-cell RNA-sequencing (scRNA-seq) provides unprecedented insights into cellular heterogeneity. Although scRNA-seq reads from most prevalent and popular tagged-end protocols are expected to arise from the 3' end of polyadenylated RNAs, recent studies have shown that "off-target" reads can constitute a substantial portion of the read population. In this work, we introduced scCensus, a comprehensive analysis workflow for systematically evaluating and categorizing off-target reads in scRNA-seq. We applied scCensus to seven scRNA-seq datasets. Our analysis of intergenic reads shows that these off-target reads contain information about chromatin structure and can be used to identify similar cells across modalities. Our analysis of antisense reads suggests that these reads can be used to improve gene detection and capture interesting transcriptional activities like antisense transcription. Furthermore, using splice-aware quantification, we find that spliced and unspliced reads provide distinct information about cell clusters and biomarkers, suggesting the utility of integrating signals from reads with different splicing statuses. Overall, our results suggest that off-target scRNA-seq reads contain underappreciated information about various transcriptional activities. These observations about yet-unexploited information in existing scRNA-seq data will help guide and motivate the community to improve current algorithms and analysis methods, and to develop novel approaches that utilize off-target reads to extend the reach and accuracy of single-cell data analysis pipelines.

Clamping-mediated incorporation of single-stranded DNA with concomitant DNA synthesis by Taq polymerase involves nick-translation

The development and characterization of a new enzyme reaction contribute to advancements in modern biotechnology. Here, we report a novel CIS (clamping-mediated incorporation of single-stranded DNA with concomitant DNA synthesis) reaction catalyzed by Taq polymerase. In the reaction, a single-stranded DNA (ssDNA) with 3' Cs is attached with a preformed 3' G-tail of double-stranded DNA (dsDNA); DNA syntheses starting from both 3' ends result in the incorporation of ssDNA. A 3' G-tail length of 3 nucleotides adequately supports this reaction, indicating that Taq polymerase can clump short Watson-Crick base pairs as short as three pairs and use them to initiate DNA polymerization. The reverse transcriptase from Molony murine leukemia virus catalyzes strand displacement synthesis and produces flapped-end DNA, whereas the reaction by Taq polymerase involves the nick translation. These new reaction properties may be beneficial for the development of new molecular tools applicable in various fields. Apart from its CIS reaction activity, we also report that Taq polymerase has the undesirable characteristic of removing 5' fluorescent labels from dsDNA. This characteristic may have compromised various experiments involving the preparation of fluorescently-labeled dsDNA by PCR for a long time.

Effects of silybin supplementation on growth performance, serum indexes and liver transcriptome of Peking ducks

As an emerging feed additive extracted from the traditional herb milk thistle, silybin has few applications and studies in Peking ducks. The aim of this study was to explore the practical significance of silymarin application in Peking ducks and to provide more theoretical support for the application of silymarin in livestock and poultry production. A total of 156 1-day-old healthy Peking ducks were randomly divided into four groups and supplemented with 0 mg/kg (control group), 400 mg/kg (S400), 800 mg/kg (S800) and 1,600 mg/kg (S1600) of silybin in the diets at day 14, to investigate the effects of silymarin on the growth, serum indexes and liver transcriptome of Peking ducks. The whole experiment lasted until day 42, and the sample collection was scheduled to take place in the morning. A substantial inprovement in average daily gain (ADG) and a decrease in feed conversion ratio (FCR) occurred in the S1600 group on days 14-28 compared to the control group (p < 0.05). The FCRs of other additive groups in the same period showed the same results. Supplementation of diets with silybin significantly increased serum IgA levels and when 1,600 mg/kg of silybin was given, levels of TNF-α and IL-6 were also significantly decreased (p < 0.05). In addition, we observed that the S1600 group had a significantly lower (p < 0.05) glutamine transaminase and an increased (p < 0.05) T-SOD level in the S400 group (p < 0.05). Liver transcriptome sequencing showed that 71 and 258 differentially expressed genes (DEGs) were identified in the S400 and S1600 groups, respectively, compared with the control group. DEGs related to cell composition and function, antigen processing and presentation were up-regulated, while DEGs related to insulin resistance and JAK-STAT were down-regulated. Conclusively, silybin can be used as a feed additive to improve the growth performance and health status of Peking ducks.

Transcriptome profiling reveals SLC5A5 regulates chicken ovarian follicle granulosa cell proliferation, apoptosis, and steroid hormone synthesis

The egg-laying performance of hens holds significant economic importance within the poultry industry. Broody inheritance of the parent stock of chickens can result in poor options for the improvement of egg production, and is a phenomenon influenced by multiple genetic factors. However, few studies have been conducted to delineate the molecular mechanism of ovarian regression in brooding chickens. Here, we explored the pivotal genes responsible for the regulation of ovarian follicles in laying hens, using RNA-sequencing analysis on the small ovarian follicles from broody and laying chickens. Sequencing data analysis revealed the differential expression of 200 genes, with a predominant enrichment in biological processes related to cell activation and metabolism. Among these genes, we focused on solute carrier family 5 member 5 (SLC5A5), which exhibited markedly higher RNA expression levels in follicles from laying compared with broody chickens. Subsequent cellular function studies with knockdown of SLC5A5 in chicken ovarian follicle granulosa cells (GCs) led to the down-regulation of genes associated with cell proliferation and steroid hormone synthesis, and concurrent promotion of gene expression linked to apoptosis. These findings indicated that SLC5A5 deficiency led to the inhibition of proliferation, steroid hormone synthesis and secretion, and promotion of apoptosis in chicken GCs. Our study demonstrated a pivotal role for SLC5A5 in the development and function of chicken GCs, shedding light on its potential significance in the broader context of chicken ovarian follicle development, and providing a prospective target to improve the egg-laying performance of chickens via molecular marker-assisted breeding technology.

Transcriptomic sequencing analysis of key long noncoding RNAs and mRNAs expression profiles in postoperative recurrence of hepatocellular carcinoma

BACKGROUND

Recurrence is the main cause of death in hepatocellular carcinoma (HCC) patients after liver resection.

OBJECTIVE

The long non-coding RNAs (lncRNAs) have been reported participated in progression and prognosis of HCC, however, the vital role of lncRNA in postoperative recurrence of HCC has rarely been systematically identified.

METHODS

RNA-sequencing (RNA-seq) was performed between orthotopic model of HCC and hepatoma postoperative recurrent model to comprehensively analyze the integrated transcriptome expression profiles of lncRNA and mRNA. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) was then conducted to quantify the expression levels of DElncRNAs and their target mRNAs.

RESULTS

In our study, 211 lncRNAs (P-value < 0.05) and 1125 mRNAs (P-adjust < 0.05) were significantly differentially expressed (DE) between two groups. Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DElncRNAs and DEmRNAs were mainly enriched in lipid metabolism, including Arachidonic acid metabolism, PPAR signaling pathway, Steroid hormone biosynthesis, Linoleic acid metabolism, Inflammatory mediator regulation of TRP channels, and Fatty acid degradation. Furthermore, we constructed lncRNA-mRNA interaction networks and protein-protein interaction (PPI) network, and verified by qRT-PCR, suggesting that increased DEIncRNAs (XLOC_063499 and XLOC_042016) may prevent HCC recurrence after surgery by upregulating on targeted cytochrome P450 (CYP) family genes in the lipid metabolism pathway, such as cyp3a16, cyp3a44, cyp2c39, cyp2c40 and cyp2c68.

CONCLUSION

Overall, Our findings provided new insights for further investigation of biological function in lncRNA related HCC recurrence.

Integration of ATAC-Seq and RNA-Seq Analysis to Identify Key Genes in the Longissimus Dorsi Muscle Development of the Tianzhu White Yak

During the postnatal stages, skeletal muscle development undergoes a series of meticulously regulated alterations in gene expression. However, limited studies have employed chromatin accessibility to unravel the underlying molecular mechanisms governing muscle development in yak species. Therefore, we conducted an analysis of both gene expression levels and chromatin accessibility to comprehensively characterize the dynamic genome-wide chromatin accessibility during muscle growth and development in the Tianzhu white yak, thereby elucidating the features of accessible chromatin regions throughout this process. Initially, we compared the differences in chromatin accessibility between two groups and observed that calves exhibited higher levels of chromatin accessibility compared to adult cattle, particularly within ±2 kb of the transcription start site (TSS). In order to investigate the correlation between alterations in chromatin accessible regions and variations in gene expression levels, we employed a combination of ATAC-seq and RNA-seq techniques, leading to the identification of 18 central transcriptional factors (TFs) and 110 key genes with significant effects. Through further analysis, we successfully identified several TFs, including Sp1, YY1, MyoG, MEF2A and MEF2C, as well as a number of candidate genes (ANKRD2, ANKRD1, BTG2 and LMOD3) which may be closely associated with muscle growth and development. Moreover, we constructed an interactive network program encompassing hub TFs and key genes related to muscle growth and development. This innovative approach provided valuable insights into the molecular mechanism underlying skeletal muscle development in the postnatal stages of Tianzhu white yaks while also establishing a solid theoretical foundation for future research on yak muscle development.

Detection of NTRK gene fusions in solid tumors: recommendations from a Latin American group of oncologists and pathologists

NTRK gene fusions have been detected in more than 25 types of tumors and their prevalence is approximately 0.3% in solid tumors. This low prevalence makes identifying patients who could benefit from TRK inhibitors a considerable challenge. Furthermore, while numerous papers on the evaluation of NTRK fusion genes are available, not all countries have guidelines that are suitable for their setting, as is the case with Latin America. Therefore, a group of oncologists and pathologists from several countries in Latin America (Argentina, Chile, Ecuador, Mexico, Peru and Uruguay) met to discuss and reach consensus on how to identify patients with NTRK gene fusions in solid tumors. To do so, they developed a practical algorithm, considering their specific situation and limitations.

Differentially expressed transcripts study during pregnancy and postpartum anestrus of yak (Bos grunniens)

Background: Yak is the main livestock species in the plateau area, and its reproductive performance is low, usually two years or three years. A very few of yaks recover within a certain period of time after delivery and smoothly enter the next estrous cycle, while most of them enter the postpartum anestrus and show no estrus performance. However, the key biological factors and influencing mechanisms that cause postpartum anestrus in yaks are not clear. Objective: To study the expression of differential transcripts in ovaries of yak during pregnancy and postpartum anestrus. Methods: Each three yaks in pregnancy and anestrus under natural grazing conditions in Haiyan County, Qinghai Province were selected and slaughtered, and their ovaries were collected and sent to Biomarker Technologies. Oxford Nanopore Technologies single-molecule real-time electrical signal sequencing technology was used to perform full-length transcriptome sequencing. Astalavista software was used to identify the types of alternative splicing events in yak estrus and pregnancy, and TAPIS pipeline was used to identify alternative polyadenylation. Results: The results showed that there were 1751 differentially expressed transcripts (DETs) between pregnancy and anestrus in yak, of which 808 were upregulated and 943 were downregulated. GO analysis showed that the biological processes of DETs were mainly reproductive, reproductive and rhythmic processes. KEGG analysis showed that the DET cell junction-related adhesion junction protein (β-catenin) and amino terminal kinase (JNK) were involved in FAs (local adhesion). Phosphatidylinositol-3-kinase (PI3K) is involved in the PI3K/AKT/mTOR signaling pathway. Circadian rhythm output cycle failure (Clock) and brain and muscle tissue aromatic hydrocarbon receptor nuclear transporter-like protein 1 (Bmal1) are involved in circadian rhythm signaling pathway. Conclusion: This study found that β-catenin, JNK, PI3K, Clock and Bmal1 were closely related to postpartum anestrus in yak.

Gastric protective effect of Alpinia officinarum flavonoids: mediating TLR4/NF-κB and TRPV1 signalling pathways and gastric mucosal healing

CONTEXT

Our previous studies have found that total flavonoid of Alpinia officinarum Hance (Zingiberaceae) (F.AOH) had protective effects on gastric ulcer (GU).

OBJECTIVE

To investigate the protective mechanism of F.AOH on acetic acid-induced chronic GUs in rats and ethanol-induced GES-1 cells damage.

MATERIALS AND METHODS

In vivo: Gastric damage was induced in SD rats by administering acetic acid after oral treatment with F-AOH at 54, 27 and 13.5 mg/kg (2 weeks of continuous gavage). After a comprehensive evaluation of rats' serum and gastric tissue-related indicators, gene transcriptome sequencing, qPCR and Western blotting were used to investigate the mechanism further. In vivo: GES-1 cells were incubated with F-AOH (8, 4 and 2 μg/mL) for 16 h and treated with 7% ethanol for 4 h. Transwell and flow cytometry were employed to detect migration and apoptosis of cells.

RESULTS

F.AOH effectively reduced the area of GUs in rats (from 11.2 ± 1.89 to 2.19 ± 0.95), reversing ethanol-induced cells apoptosis (from 23 ± 1.3 to 8.11 ± 0.93%). It also inhibited the expression of endothelin-1 (ET-1) and iNOS proteins, decreasing the levels of TNF-α IL-6 in serum, improving oxidative stress levels and increasing the expression of Bcl-2/Bax dimer genes. In addition, 4005 differentially expressed genes between the acetic acid model and the drug groups. Through experimental verification, F.AOH can inhibit the activation of TLR4/NF-κB signalling pathway and TRPV1 receptor.

CONCLUSIONS

F.AOH, as an effective gastric protective plant component, had potential therapeutic value in anti-inflammatory pain and antioxidative stress gastrointestinal diseases.

Astragalus polysaccharide promotes autophagy and alleviates diabetic nephropathy by targeting the lncRNA Gm41268/PRLR pathway

BACKGROUND

Astragalus polysaccharide (APS) is a major bioactive component of the Chinese herb astragalus, with well-established protective effects on the kidney. However, the effect of APS on diabetic nephropathy (DN) is unclear.

METHODS

Long non-coding RNA (lncRNA) expression profiles in kidney samples from control, db/db, and APS-treated db/db mice were evaluated using RNA high-throughput sequencing techniques. Additionally, rat renal tubular epithelial (NRK-52E) cells were cultured in high glucose (HG) media. We inhibited the expression of Gm41268 and prolactin receptor (PRLR) by transfecting NRK-52E cells with Gm41268-targeting antisense oligonucleotides and PRLR siRNA.

RESULTS

We found that APS treatment reduced 24-h urinary protein levels and fasting blood glucose and improved glucose intolerance and pathological renal damage in db/db mice. Furthermore, APS treatment enhanced autophagy and alleviated fibrosis in the db/db mice. We identified a novel lncRNA, Gm41268, which was differentially expressed in the three groups, and the cis-regulatory target gene PRLR. APS treatment induced autophagy by reducing p62 and p-mammalian target of rapamycin (mTOR) protein levels and increasing the LC3 II/I ratio. Furthermore, APS alleviated fibrosis by downregulating fibronectin (FN), transforming growth factor-β (TGF-β), and collagen IV levels. In addition, APS reversed the HG-induced overexpression of Gm41268 and PRLR. Reduction of Gm41268 decreased PRLR expression, restored autophagy, and ameliorated renal fibrosis in vitro. Inhibition of PRLR could enhance the protective effect of APS.

CONCLUSIONS

In summary, we demonstrated that the therapeutic effect of APS on DN is mediated via the Gm41268/PRLR pathway. This information contributes to the exploration of bioactive constituents in Chinese herbs as potential treatments for DN.

Transcriptome software results show significant variation among different commercial pipelines

BACKGROUND

We have been documenting the biological responses to low levels of radiation (natural background) and very low level radiation (below background), and thus these studies are testing mild external stimuli to which we would expect relatively mild biological responses. We recently published a transcriptome software comparison study based on RNA-Seqs from a below background radiation treatment of two model organisms, E. coli and C. elegans (Thawng and Smith, BMC Genomics 23:452, 2022). We reported DNAstar-D (Deseq2 in the DNAstar software pipeline) to be the more conservative, realistic tool for differential gene expression compared to other transcriptome software packages (CLC, Partek and DNAstar-E (using edgeR). Here we report two follow-up studies (one with a new model organism, Aedes aegypti and another software package (Azenta) on transcriptome responses from varying dose rates using three different sources of natural radiation.

RESULTS

When E. coli was exposed to varying levels of K40, we again found that the DNAstar-D pipeline yielded a more conservative number of DEGs and a lower fold-difference than the CLC pipeline and DNAstar-E run in parallel. After a 30 read minimum cutoff criterion was applied to the data, the number of significant DEGs ranged from 0 to 81 with DNAstar-D, while the number of significant DEGs ranged from 4 to 117 and 14 to 139 using DNAstar-E and the CLC pipelines, respectively. In terms of the extent of expression, the highest foldchange DEG was observed in DNAstar-E with 19.7-fold followed by 12.5-fold in CLC and 4.3-fold in DNAstar-D. In a recently completed study with Ae. Aegypti and using another software package (Azenta), we analyzed the RNA-Seq response to similar sources of low-level radiation and again found the DNAstar-D pipeline to give the more conservative number and fold-expression of DEGs compared to other softwares. The number of significant DEGs ranged 31-221 in Azenta and 31 to 237 in CLC, 19-252 in DNAstar-E and 0-67 in DNAStar-D. The highest fold-change of DEGs were found in CLC (1,350.9-fold), with DNAstar-E (5.9 -fold) and Azenta (5.5-fold) intermediate, and the lowest levels of expression (4-fold) found in DNAstar-D.

CONCLUSIONS

This study once again highlights the importance of choosing appropriate software for transcriptome analysis. Using three different biological models (bacteria, nematode and mosquito) in four different studies testing very low levels of radiation (Van Voorhies et al., Front Public Health 8:581796, 2020; Thawng and Smith, BMC Genomics 23:452, 2022; current study), the CLC software package resulted in what appears to be an exaggerated gene expression response in terms of numbers of DEGs and extent of expression. Setting a 30-read cutoff diminishes this exaggerated response in most of the software tested. We have further affirmed that DNAstar-Deseq2 gives a more conservative transcriptome expression pattern which appears more suitable for studies expecting subtle gene expression patterns.

Praeruptorin A inhibits the activation of NF-κB pathway and the expressions of inflammatory factors in poly (I:C)-induced RAW264.7 cells

Praeruptorin A (PA), a natural coumarin compound, has significant anti-inflammatory effects. In this study, we evaluate the anti-inflammatory effect of PA on RAW 264.7 mouse macrophages induced by Polyinosinic acid-polycytidylic acid (poly (I:C)). RAW 264.7 mouse macrophages induced by poly (I:C) were treated with or without PA, the viability of which was determined to screen working solution of PA. RNA-sequencing was applied to analyze the differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were carried out. The expressions of interleukin (IL)-1β, heme oxygenase 1 (HMOX1), prostaglandin-endoperoxide synthase 2 (PTGS2), ATP binding cassette subfamily A member 1 (Abca1) and NF-κB-related proteins were measured by enzyme-linked immunosorbent assay (ELISA), quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot. As a result, PA at 1, 2, 3, 4 and 5 μM slightly affected cell viability, while PA at 6 and 7 μM significantly inhibited cell viability. GO and KEGG analysis results revealed that DEGs were mainly enriched in the pathways related to inflammatory signaling. Through further analysis, we obtained five possible targets of PA, and verified that PA inhibited the expressions of IL-1β, HMOX1, PTGS2 and Abca1 as well as the activation of NF-κB pathway in poly (I:C)-induced RAW264.7 cells. To summarize, PA may inhibit expressions of the inflammation-related genes in poly (I:C)-induced RAW264.7 cells, which demonstrates its potential as a drug against virus related diseases.

Carotenoids in Health as Studied by Omics-Related Endpoints

Carotenoids have been associated with risk reduction for several chronic diseases, including the association of their dietary intake/circulating levels with reduced incidence of obesity, type 2 diabetes, certain types of cancer, and even lower total mortality. In addition to some carotenoids constituting vitamin A precursors, they are implicated in potential antioxidant effects and pathways related to inflammation and oxidative stress, including transcription factors such as nuclear factor κB and nuclear factor erythroid 2-related factor 2. Carotenoids and metabolites may also interact with nuclear receptors, mainly retinoic acid receptor/retinoid X receptor and peroxisome proliferator-activated receptors, which play a role in the immune system and cellular differentiation. Therefore, a large number of downstream targets are likely influenced by carotenoids, including but not limited to genes and proteins implicated in oxidative stress and inflammation, antioxidation, and cellular differentiation processes. Furthermore, recent studies also propose an association between carotenoid intake and gut microbiota. While all these endpoints could be individually assessed, a more complete/integrative way to determine a multitude of health-related aspects of carotenoids includes (multi)omics-related techniques, especially transcriptomics, proteomics, lipidomics, and metabolomics, as well as metagenomics, measured in a variety of biospecimens including plasma, urine, stool, white blood cells, or other tissue cellular extracts. In this review, we highlight the use of omics technologies to assess health-related effects of carotenoids in mammalian organisms and models.

HArmonized single-cell RNA-seq Cell type Assisted Deconvolution (HASCAD)

BACKGROUND

Cell composition deconvolution (CCD) is a type of bioinformatic task to estimate the cell fractions from bulk gene expression profiles, such as RNA-seq. Many CCD models were developed to perform linear regression analysis using reference gene expression signatures of distinct cell types. Reference gene expression signatures could be generated from cell-specific gene expression profiles, such as scRNA-seq. However, the batch effects and dropout events frequently observed across scRNA-seq datasets have limited the performances of CCD methods.

METHODS

We developed a deep neural network (DNN) model, HASCAD, to predict the cell fractions of up to 15 immune cell types. HASCAD was trained using the bulk RNA-seq simulated from three scRNA-seq datasets that have been normalized by using a Harmony-Symphony based strategy. Mean square error and Pearson correlation coefficient were used to compare the performance of HASCAD with those of other widely used CCD methods. Two types of datasets, including a set of simulated bulk RNA-seq, and three human PBMC RNA-seq datasets, were arranged to conduct the benchmarks.

RESULTS

HASCAD is useful for the investigation of the impacts of immune cell heterogeneity on the therapeutic effects of immune checkpoint inhibitors, since the target cell types include the ones known to play a role in anti-tumor immunity, such as three subtypes of CD8 T cells and three subtypes of CD4 T cells. We found that the removal of batch effects in the reference scRNA-seq datasets could benefit the task of CCD. Our benchmarks showed that HASCAD is more suitable for analyzing bulk RNA-seq data, compared with the two widely used CCD methods, CIBERSORTx and quanTIseq. We applied HASCAD to analyze the liver cancer samples of TCGA-LIHC, and found that there were significant associations of the predicted abundance of Treg and effector CD8 T cell with patients' overall survival.

CONCLUSION

HASCAD could predict the cell composition of the PBMC bulk RNA-seq and classify the cell type from pure bulk RNA-seq. The model of HASCAD is available at https://github.com/holiday01/HASCAD .

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

BACKGROUND

Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay.

RESULTS

We generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method.

CONCLUSIONS

Previous benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.

Rational probe design for efficient rRNA depletion and improved metatranscriptomic analysis of human microbiomes

The microbiota that colonize the human gut and other tissues are dynamic, varying both in composition and functional state between individuals and over time. Gene expression measurements can provide insights into microbiome composition and function. However, efficient and unbiased removal of microbial ribosomal RNA (rRNA) presents a barrier to acquiring metatranscriptomic data. Here we describe a probe set that achieves efficient enzymatic rRNA removal of complex human-associated microbial communities. We demonstrate that the custom probe set can be further refined through an iterative design process to efficiently deplete rRNA from a range of human microbiome samples. Using synthetic nucleic acid spike-ins, we show that the rRNA depletion process does not introduce substantial quantitative error in gene expression profiles. Successful rRNA depletion allows for efficient characterization of taxonomic and functional profiles, including during the development of the human gut microbiome. The pan-human microbiome enzymatic rRNA depletion probes described here provide a powerful tool for studying the transcriptional dynamics and function of the human microbiome.

Epigenetic alternations and targeted therapy in intrauterine adhesion: A comparative study

Although intrauterine adhesion (IUA) has been well recognized as a critical factor in infertility, little information is available regarding the molecular mechanisms. We performed a high-throughput RNA sequencing in the endometrium of three IUA patients and three normal controls. And another two gene expression profiles (PMID34968168 and GSE160365) were analyzed together. A total of 252 DEGs were identified. Cell cycle, E2F target, G2M checkpoint, integrin3 pathway and H1F1 signaling were aberrantly regulated in the IUA endometrium. 10 hub genes (CCL2, TFRC, THY1, IGF1, CTGF, SELL, SERPINE1, HBB, HBA1, LYZ) were exhibited in PPI analysis. FOXM1, IKBKB and MYC were three common transcription factors of DEGs. Five chemicals (MK-1775, PAC-1, TW-37, BIX-01294, 3-matida) were identified as putative therapeutic agents for IUA. Collectively, a series of DEGs associated with IUA were disclosed. Five chemicals and ten hub genes may be further explored as potential drugs and targets for IUA treatment.

Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics

BACKGROUND

To investigate the correlation between computed tomography (CT) radiomic characteristics and key genes for cervical lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC).

METHODS

The region of interest was annotated at the edge of the primary tumor on enhanced CT images from 140 patients with OSCC and obtained radiomic features. Ribonucleic acid (RNA) sequencing was performed on pathological sections from 20 patients. the DESeq software package was used to compare differential gene expression between groups. Weighted gene co-expression network analysis was used to construct co-expressed gene modules, and the KEGG and GO databases were used for pathway enrichment analysis of key gene modules. Finally, Pearson correlation coefficients were calculated between key genes of enriched pathways and radiomic features.

RESULTS

Four hundred and eighty radiomic features were extracted from enhanced CT images of 140 patients; seven of these correlated significantly with cervical LNM in OSCC (p < 0.01). A total of 3527 differentially expressed RNAs were screened from RNA sequencing data of 20 cases. original_glrlm_RunVariance showed significant positive correlation with most long noncoding RNAs.

CONCLUSIONS

OSCC cervical LNM is related to the salivary hair bump signaling pathway and biological process. Original_glrlm_RunVariance correlated with LNM and most differentially expressed long noncoding RNAs.