Selection and Validation of Reference Genes for RT-qPCR Normalization in Bradysia odoriphaga (Diptera: Sciaridae) Under Insecticides Stress

Bradysia odoriphaga (Diptera: Sciaridae) is the most serious root maggot pest which causes substantial damage to the Chinese chive. Organophosphate (OP) and neonicotinoid insecticides are widely used chemical pesticides and play important roles in controlling B. odoriphaga. However, a strong selection pressure following repeated pesticide applications has led to the development of resistant populations of this insect. To understand the insecticide resistance mechanism in B. odoriphaga, gene expression analysis might be required. Appropriate reference gene selection is a critical prerequisite for gene expression studies, as the expression stability of reference genes can be affected by experimental conditions, resulting in biased or erroneous results. The present study shows the expression profile of nine commonly used reference genes [elongation factor 1α (EF-1α), actin2 (ACT), elongation factor 2α (EF-2α), glucose-6-phosphate dehydrogenase (G6PDH), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein L10 (RPL10), ribosomal protein S3 (RPS3), ubiquitin-conjugating enzyme (UBC), and α-tubulin (TUB)] was systematically analyzed under insecticide stress. Moreover, we also evaluated their expression stability in other experimental conditions, including developmental stages, sexes, and tissues. Five programs (NormFinder, geNorm, BestKeeper, RefFinder, and ΔCt) were used to validate the suitability of candidate reference genes. The results revealed that the most appropriate sets of reference genes were RPL10 and ACT across phoxim; ACT and TUB across chlorpyrifos and chlorfluazuron; EF1α and TUB across imidacloprid; EF1α and EF2α across developmental stages; RPL10 and TUB across larvae; EF1α and ACT across tissues, and ACT and G6PDH across sex. These results will facilitate the standardization of RT-qPCR and contribute to further research on B. odoriphaga gene function under insecticides stress.

Transcriptomics and network analysis highlight potential pathways in the pathogenesis of pterygium

Pterygium is a common ocular surface condition frequently associated with irritative symptoms. The precise identity of its critical triggers as well as the hierarchical relationship between all the elements involved in the pathogenesis of this disease are not yet elucidated. Meta-analysis of gene expression studies represents a novel strategy capable of identifying key pathogenic mediators and therapeutic targets in complex diseases. Samples from nine patients were collected during surgery after photo documentation and clinical characterization of pterygia. Gene expression experiments were performed using Human Clariom D Assay gene chip. Differential gene expression analysis between active and atrophic pterygia was performed using limma package after adjusting variables by age. In addition, a meta-analysis was performed including recent gene expression studies available at the Gene Expression Omnibus public repository. Two databases including samples from adults with pterygium and controls fulfilled our inclusion criteria. Meta-analysis was performed using the Rank Production algorithm of the RankProd package. Gene set analysis was performed using ClueGO and the transcription factor regulatory network prediction was performed using appropriate bioinformatics tools. Finally, miRNA-mRNA regulatory network was reconstructed using up-regulated genes identified in the gene set analysis from the meta-analysis and their interacting miRNAs from the Brazilian cohort expression data. The meta-analysis identified 154 up-regulated and 58 down-regulated genes. A gene set analysis with the top up-regulated genes evidenced an overrepresentation of pathways associated with remodeling of extracellular matrix. Other pathways represented in the network included formation of cornified envelopes and unsaturated fatty acid metabolic processes. The miRNA-mRNA target prediction network, also reconstructed based on the set of up-regulated genes presented in the gene ontology and biological pathways network, showed that 17 target genes were negatively correlated with their interacting miRNAs from the Brazilian cohort expression data. Once again, the main identified cluster involved extracellular matrix remodeling mechanisms, while the second cluster involved formation of cornified envelope, establishment of skin barrier and unsaturated fatty acid metabolic process. Differential expression comparing active pterygium with atrophic pterygium using data generated from the Brazilian cohort identified differentially expressed genes between the two forms of presentation of this condition. Our results reveal differentially expressed genes not only in pterygium, but also in active pterygium when compared to the atrophic ones. New insights in relation to pterygium’s pathophysiology are suggested.

Optimized splitting of mixed-species RNA sequencing data

Gene expression studies using xenograft transplants or co-culture systems, usually with mixed human and mouse cells, have proven to be valuable to uncover cellular dynamics during development or in disease models. However, the mRNA sequence similarities among species presents a challenge for accurate transcript quantification. To identify optimal strategies for analyzing mixed-species RNA sequencing data, we evaluate both alignment-dependent and alignment-independent methods. Alignment of reads to a pooled reference index is effective, particularly if optimal alignments are used to classify sequencing reads by species, which are re-aligned with individual genomes, generating [Formula: see text] accuracy across a range of species ratios. Alignment-independent methods, such as convolutional neural networks, which extract the conserved patterns of sequences from two species, classify RNA sequencing reads with over 85% accuracy. Importantly, both methods perform well with different ratios of human and mouse reads. While non-alignment strategies successfully partitioned reads by species, a more traditional approach of mixed-genome alignment followed by optimized separation of reads proved to be the more successful with lower error rates.

PPIA and YWHAZ Constitute a Stable Pair of Reference Genes during Electrical Stimulation in Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) are multipotent adult stem cells with great potential in regenerative medicine. One method for stimulating proliferation and differentiation of MSCs is via electrical stimulation (ES). A valuable approach for evaluating the response of MSCs to ES is to assess changes in gene expression, relative to one or more reference genes. In a survey of 25 publications that used ES on cells, 70% selected GAPDH as the reference gene. We conducted a study to assess the suitability of six potential reference genes on an immortalized human MSC line following direct current ES at seeding densities of 5000 and 10,000 cells/cm2. We employed three methods to validate the most stable reference genes from qRT-PCR data. Our findings show that GAPDH and ACTB exhibit reduced stability when seeded at 5000 cell/cm2. In contrast, we found that the most stable genes across both plating densities and stimulation regimes were PPIA and YWHAZ. Thus, in ES gene expression studies in MSCs, we support the use of PPIA and YWHAZ as an optimal reference gene pair, and discourage the use of ACTB and GAPDH at lower seeding densities. However, it is strongly recommended that similar verification studies are carried out based on cell type and different ES conditions.

Understanding Gene Expression and Transcriptome Profiling of COVID-19: An Initiative Towards the Mapping of Protective Immunity Genes Against SARS-CoV-2 Infection

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease’s potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.

A success targeted nano delivery to lung cancer cells with multi-walled carbon nanotubes conjugated to bromocriptine

In this research, a new nano drug-based multi-walled carbon nanotubes (MWCNTs) was prepared and evaluated qualitatively. Bromocriptine (BRC) was conjugated to functionalized carbon nanotubes. Then, the CHNS, FT-IR, SEM, and RAMAN tests for characterization of the conjugated drug were done. The nanofluid-containing nano-drug was evaluated on lung cancer cells (A549 & QU-DB) and MRC5 by MTT and flow cytometry tests. Then, the gene expression studies of dopamine receptor genes were done before and after nano-drug treatment. After that, a western blotting test was carried out for further investigation of dopamine receptors protein production. Finally, Bax and Bcl-2 secretion were measured by the ELISA method in cells affected by MWCNTs-BRC Nf compared to untreated cells. The results showed that the nano-drug had a significant lethal effect on cancer cells, while it had no toxicity on MRC5. Also, the nano-drug could significantly induce apoptosis in lung cancer cells at a lower dose compared to the drug alone. In this study, a targeted nano-drug delivery system was designed, and its performance was evaluated based on neurotransmitter pathways, and the results showed that it may be useful in the treatment of lung cancer. However, additional studies on animal models are underway.

Validation of reference genes for quantitative PCR in the forest pest, Ips calligraphus

The six-spined ips, Ips calligraphus, is a North American bark beetle that can exploit most eastern North American Pinus species and can cause mortality. Biotic and abiotic disturbances weaken trees, creating breeding substrate that promotes rapid population growth. Management historically relied on silvicultural practices, but as forests become increasingly stressed, innovative management is needed. Manipulation of the cellular RNA interference (RNAi) pathway to induce gene silencing is an emerging means of insect suppression, and is effective for some bark beetles. Quantitative PCR (qPCR) is a powerful tool for analysis of gene expression, and is essential for examining RNAi. To compare gene expression among individuals, stably expressed reference genes must be validated for qPCR. We evaluated six candidate reference genes (18s, 16s, 28s, ef1a, cad, coi) for stability under biotic (beetle sex, developmental stage, and host plant), and abiotic (temperature, photoperiod, and dsRNA exposure) conditions. We used the comprehensive RefFinder tool to compare stability rankings across four algorithms. These algorithms identified 18s, 16s, and 28s as the most stably expressed. Overall, 16s and 28s were selected as reference genes due to their stability and moderate expression levels, and can be used for I. calligraphus gene expression studies using qPCR, including those evaluating RNAi.

Gene Expression Studies in Formalin-Fixed Paraffin-Embedded Samples of Cutaneous Cancer: The Need for Reference Genes

Formalin-fixed paraffin-embedded (FFPE) tumour samples may provide crucial data regarding biomarkers for neoplasm progression. Analysis of gene expression is frequently used for this purpose. Therefore, mRNA expression needs to be normalized through comparison to reference genes. In this study, we establish which of the usually reported reference genes is the most reliable one in cutaneous malignant melanoma (MM) and cutaneous squamous cell carcinoma (CSCC). ACTB, TFRC, HPRT1 and TBP expression was quantified in 123 FFPE samples (74 MM and 49 CSCC biopsies) using qPCR. Expression stability was analysed by NormFinder and Bestkeeper softwares, and the direct comparison method between means and SD. The in-silico analysis with BestKeeper indicated that HPRT1 was more stable than ACTB and TFRC in MM (1.85 vs. 2.15) and CSCC tissues (2.09 vs. 2.33). The best option to NormFinder was ACTB gene (0.56) in MM and TFRC (0.26) in CSCC. The direct comparison method showed lower SD means of ACTB expression in MM (1.17) and TFRC expression in CSCC samples (1.00). When analysing the combination of two reference genes for improving stability, NormFinder indicated HPRT1 and ACTB to be the best for MM samples, and HPRT1 and TFRC genes for CSCC. In conclusion, HPRT1 and ACTB genes in combination are the most appropriate choice for normalization in gene expression studies in MM FFPE tissue, while the combination of HPRT1 and TFRC genes are the best option in analysing CSCC FFPE samples. These may be used consistently in forthcoming studies on gene expression in both tumours.

The Evolution of Hox Genes in Spiralia

The decoding of genomes of a larger number of animal species have provided further insights into the genomic Hox gene organization and with this indicated the evolutionary changes during the radiation of several clades. The expansion of gene expression studies during development and life history stages of more species, complete the picture of the relationship between cluster organisation and temporal and spatial correlation of the Hox activity. Now these results open the opportunity to look deeper into the regulatory pathways that form these patterns and identify what exact changes caused the evolution of the application of this iconical gene set for the evolution of new larval forms and new structures. Here we review recent progress of Hox gene related research in the large clade Spiralia, that comprises Annelida, Mollusca, Lophophorata, Platyhelminthes, Nemertea and others. Albeit their relationship to each other is not resolved yet, there are emerging patterns that indicate that Hox genes are mainly used for patterning late, adult body parts and that Hox genes are often not expressed on the larval stages. Hox genes seem also often recruited for the formation of morphological novelties. Together with the emerging genomic information Hox genes show a much more dynamic evolutionary history than previously assumed.