1-L Transcription in Prion Diseases.

Understanding the pathogenesis and mechanisms of prion diseases can significantly expand our knowledge in the field of neurodegenerative diseases. Prion biology is increasingly recognized as being relevant to the pathophysiology of Alzheimer's disease and Parkinson's disease, both of which affect millions of people each year. This bioinformatics study used a theoretical protein-RNA recognition code (1-L transcription) to reveal the post-transcriptional regulation of the prion protein (PrPC). The principle for this method is directly elucidated on PrPC, in which an octa-repeat can be 1-L transcribed into a GGA triplet repeat RNA aptamer known to reduce the misfolding of normal PrPC into abnormal PrPSc. The identified genes/proteins are associated with mitochondria, cancer, COVID-19 and ER-stress, and approximately half are directly or indirectly associated with prion diseases. For example, the octa-repeat supports CD44, and regions of the brain with astrocytic prion accumulation also display high levels of CD44.

Identification of the Genetic Influence of SARS-CoV-2 Infections on IgA Nephropathy Based on Bioinformatics Method.

INTRODUCTION: Coronavirus disease-2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. It was initially detected in Wuhan, China, in December 2019. In March 2020, the World Health Organization (WHO) declared COVID-19 a global pandemic. Compared to healthy individuals, patients with IgA nephropathy (IgAN) are at a higher risk of SARS-CoV-2 infection. However, the potential mechanisms remain unclear. This study explores the underlying molecular mechanisms and therapeutic agents for the management of IgAN and COVID-19 using the bioinformatics and system biology way. METHODS: We first downloaded GSE73953 and GSE164805 from the Gene Expression Omnibus (GEO) database to obtain common differentially expressed genes (DEGs). Then, we performed the functional enrichment analysis, pathway analysis, protein-protein interaction (PPI) analysis, gene regulatory networks analysis, and potential drug analysis on these common DEGs. RESULTS: We acquired 312 common DEGs from the IgAN and COVID-19 datasets and used various bioinformatics tools and statistical analyses to construct the PPI network to extract hub genes. Besides, we performed gene ontology (GO) and pathway analyses to reveal the common correlation between IgAN and COVID-19. Finally, on the basis of common DEGs, we determined the interactions between DEGs-miRNAs, the transcription factor-genes (TFs-genes), protein-drug, and gene-disease networks. CONCLUSION: We successfully identified hub genes that may act as biomarkers of COVID-19 and IgAN and also screened out some potential drugs to provide new ideas for COVID-19 and IgAN treatment.

A new method for determining ribosomal DNA copy number shows differences between Saccharomyces cerevisiae populations.

Ribosomal DNA genes (rDNA) encode the major ribosomal RNAs and in eukaryotes typically form tandem repeat arrays. Species have characteristic rDNA copy numbers, but there is substantial intra-species variation in copy number that results from frequent rDNA recombination. Copy number differences can have phenotypic consequences, however difficulties in quantifying copy number mean we lack a comprehensive understanding of how copy number evolves and the consequences. Here we present a genomic sequence read approach to estimate rDNA copy number based on modal coverage to help overcome limitations with existing mean coverage-based approaches. We validated our method using Saccharomyces cerevisiae strains with known rDNA copy numbers. Application of our pipeline to a global sample of S. cerevisiae isolates showed that different populations have different rDNA copy numbers. Our results demonstrate the utility of the modal coverage method, and highlight the high level of rDNA copy number variation within and between populations.

1-L Transcription in Alzheimer's Disease.

Alzheimer's disease is a very complex disease and better explanations and models are needed to understand how neurons are affected and microglia are activated. A new model of Alzheimer's disease is presented here, the ß-amyloid peptide is considered an important RNA recognition/binding peptide. 1-L transcription revealed compatible sequences with AAUAAA (PAS signal) and UUUC (class III ARE rich in U) in the Aß peptide, supporting the peptide-RNA regulatory model. When a hypothetical model of fibril selection with the prionic character of amyloid assemblies is added to the peptide-RNA regulatory model, the downregulation of the PI3K-Akt pathway and the upregulation of the PLC-IP3 pathway are well explained. The model explains why neurons are less protected from inflammation and why microglia are activated; why mitochondria are destabilized; why the autophagic flux is destabilized; and why the post-transcriptional attenuation of the axonal signal "noise" is interrupted. For example, the model suggests that Aß peptide may post-transcriptionally control ELAVL2 (ELAV-like RNA binding protein 2) and DCP2 (decapping mRNA protein 2), which are known to regulate RNA processing, transport, and stability.

Transcription of the Envelope Protein by 1-L Protein-RNA Recognition Code Leads to Genes/Proteins That Are Relevant to the SARS-CoV-2 Life Cycle and Pathogenesis.

The theoretical protein-RNA recognition code was used in this study to research the compatibility of the SARS-CoV-2 envelope protein (E) with mRNAs in the human transcriptome. According to a review of the literature, the spectrum of identified genes showed that the virus post-transcriptionally promotes or represses the genes involved in the SARS-CoV-2 life cycle. The identified genes/proteins are also involved in adaptive immunity, in the function of the cilia and wound healing (EMT and MET) in the pulmonary epithelial tissue, in Alzheimer's and Parkinson's disease and in type 2 diabetes. For example, the E-protein promotes BHLHE40, which switches off the IL-10 inflammatory "brake" and inhibits antiviral THαß cells. In the viral cycle, E supports the COPII-SCAP-SREBP-HSP90α transport complex by the lowering of cholesterol in the ER and by the repression of insulin signaling, which explains the positive effect of HSP90 inhibitors in COVID-19 (geldanamycin), and E also supports importin α/ß-mediated transport to the nucleus, which explains the positive effect of ivermectin, a blocker of importins α/ß. In summary, transcription of the envelope protein by the 1-L protein-RNA recognition code leads to genes/proteins that are relevant to the SARS-CoV-2 life cycle and pathogenesis.

The expression and clinical significance of an Epithelial-Mesenchymal Transition inducer, SNAI1, in head and neck carcinoma.

BACKGROUND: SNAI1 is an epithelial-mesenchymal transition (EMT) inducer, which has been indicated to play a role in the progression of cancers. We aimed to evaluate the expression and prognostic roles of SNAI1 in head and neck carcinoma (HNC). METHODS: The study involved two major phases. In the in silico phase, the SNAI1 expression and its association with clinical features as well as its prognostic values were assessed; then, the target genes of SNAI1 were predicted and the relationship between SNAI1 expression and immune cell infiltration was evaluated. In the validation phase, a cohort of a tissue microarray (47 cases) and a cohort of HNC patients (68 cases) were enrolled. SNAI1 was detected by using an immunochemistry assay. RESULTS: The in silico analysis showed that overexpression of SNAI1 in HNC tissues may be correlated with metastatic lymph node numbers and may predict poor outcomes. Six genes, including CREB3L1, MITF, KLF9, RARA, KLF7, and ETV1, were predicted to be the target genes of SNAI1. The expression of SNAI1 was negatively correlated with tumor purity of HNC, while it was positively correlated with the infiltration of diverse immune cells, such as B cells and macrophages. In the validation phase, the relationships of SNAI1 expression with lymph node metastasis and poor prognosis were verified. CONCLUSION: Overexpression of SNAI1 might promote lymph node metastasis through complex molecular mechanisms and act as a prognostic indicator in HNC. SNAI1 expression may have a correlation with immune cell infiltrates. Future studies are needed to address these points.

1-L Transcription in Parkinson's Disease.

BACKGROUND: As a chronic degenerative disorder of the central nervous system that affects both motor and non-motor systems, Parkinson's disease (PD) is very complex, and explanations and models are needed to better understand how dopaminergic neurons are affected and microglia are activated. METHODS: A theoretical protein-RNA recognition code that assumes that the second letter in codons is compatible with specific amino acids involved in protein-RNA recognition was used to search for compatibility of human α-synuclein (α-syn) with mRNAs in the human transcriptome (1-L transcription). RESULTS: The 1-L transcription revealed compatible amino acid sequences with the ATTTA ARE (class I), PAS and polyA in α-syn, supporting a protein-RNA regulatory model. In PD, inflammatory microglia reactions, cognitive decline and motor circuit disturbances are observed. The model theoretically explains why α-syn producing neurons are less protected from inflammation and why microglia are activated. Consistent with knowledge of PD, the identified genes showed how the PI3K-AKT pathway is downregulated, how reactive oxygen species (ROS) production and sensitivity are increased, how mitochondria are destabilized, why autophagy is impaired, and why neuronal depigmentation is observed. CONCLUSIONS: 1-L transcription of α-syn leads to genes/proteins relevant to PD. When α-syn is accepted as a small RNA recognition protein involved in the post-transcriptional regulations, some identified genes indicate that its function is an important regulatory factor associated with intracellular and extracellular transport of RNA vesicles. These vesicles are extremely important in cellular communication. In addition, the spectrum of identified genes strongly indicates that α-syn produced by neuronal cells is required for proper regulation of inflammatory and immune responses.

Prediction of target genes in community-acquired pneumonia based on the bioinformatics method.

Background: To screen the related genes of community-acquired pneumonia (CAP) by bioinformatics technology, and to analyze the clinical value of key genes. Methods: Gene chip data sets containing CAP patients and normal controls were screened from the Gene Expression Omnibus (GEO) database. The downregulated differentially expressed genes (DEGs) were screened using a gene expression analysis tool (GEO2R). Simultaneously, gene set enrichment analysis (GSEA) was used to explore the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and core genes related to CAP. The candidate genes were then intersected with the genes reported in Online Mendelian Inheritance in Man (OMIM), and the clinical value of these candidate genes was examined based on a literature search. Finally, the clinical data of the CAP patients were retrospectively analyzed. Detect the type of pathogenic bacteria in bronchial-alveolar lavage fluid (BALF) using metagenomics next-generation sequencing (mNGS) high throughput sequencing technology, and detect the expression of key genes through liquid based cell immunohistochemistry to analyze the correlation between pathogenic bacteria and key genes. Results: Through the intersection of Venn diagrams, 175 co-expressed downregulated DEGs related to CAP were identified. A total of 4 candidate genes, including ICOS, IL7R, ITK, and ZAP70, were obtained by constructing the protein mutual aid network and conducting a module analysis of the common differentially expressed genes. The core genes in the GSEA enrichment pathways were intersected with the CAP-related genes reported in the relevant literature retrieved from the OMIM database. In the Venn diagram, two genes that coexist with OMIM include IL7R and PIK3R1. After considering our findings and the relevant literature, we determined that the key gene related to the occurrence and development of CAP was IL7R. The mNGS detected 13 kinds of bacteria, 4 kinds of fungi, and 2 kinds of viruses. Based on immunohistochemical results, it was found that there were relatively more bacteria detected in the IL7R high expression group. Conclusions: The identification of the key gene IL7R and the related signaling pathways extend understanding of the pathogenesis of CAP and provide a theoretical basis for clinical targeted therapy research.

HMGB1 promotes the development of castration­resistant prostate cancer by regulating androgen receptor activation.

AR signalling pathway reactivation plays a key role in the development of castration­resistant prostate cancer (CRPC). High­mobility group protein B1 (HMGB1) is an important factor involved in the occurrence and development of a variety of tumours by regulating gene transcription. In the present study, the association between HMGB1 and prostate cancer (PCa) and the effects of HMGB1 on androgen receptor (AR) transcription and signalling pathway reactivation in PCa cells in vitro and in vivo were evaluated. A bioinformatics method was used to determine the mRNA expression level of HMGB1 in PCa specimens and its correlation with the mRNA expression of AR. Immunohistochemical staining was used to detect the expression of these proteins in clinical PCa samples. Reporter gene and ChIP assays were performed to determine the activity of AR and the effect of HMGB1 on the ability of AR to bind to the promoters of prostate specific antigen and transmembrane protease, serine 2. A bioluminescence resonance energy transfer assay was employed to observe the direct interaction between HMGB1 and AR protein. Additionally, a castrated nude mouse xenograft tumour model was established to verify the effect of HMGB1 on PCa. The results revealed that HMGB1 expression was significantly increased in PCa specimens, which may have a strong correlation with AR expression. Moreover, HMGB1 could reactivate the AR signalling pathway, directly interact with AR, and promote the development of CRPC in an androgen­independent manner. The results of the present study indicated that HMGB1 promoted the development of CRPC by interacting with AR, which inferred that decreasing the expression of HMGB1 may be a potential effective method for CRPC prevention and treatment.

W-Test for Genetic Epistasis Testing.

The genetic epistasis effect has been widely acknowledged as an essential contributor to genetic variation in complex diseases. In this chapter, we introduce a powerful and efficient statistical method, called W-test, for genetic epistasis testing. A wtest R package is developed for the implementation of the W-test method, which provides various functions to measure the main effect, pairwise interaction, higher-order interaction, and cis-regulation of SNP-CpG pairs in genetic and epigenetic data. It allows flexible stagewise and exhaustive association testing as well as diagnostic checking on the probability distributions in a user-friendly interface. The wtest package is available in CRAN at https://CRAN.R-project.org/package=wtest .

IGFBP3 as an indicator of lymph node metastasis and unfavorable prognosis for papillary thyroid carcinoma.

Lymph node metastasis (LNM) is a usual event in papillary thyroid carcinoma (PTC) patients, which usually leads to poor prognosis. However, the molecular mechanisms of LNM remain unclear. Thus, we aimed to screen the possible key genes in the progression of LNM in PTC patients and further validate their roles. The study involved two phases: a discovery phase and a validation one. In the former phase, the candidate genes were screened by using bioinformatics methods. In the latter one, the genes were firstly assessed in a cohort from the cancer genome atlas (TCGA) to evaluate the associations of their expressions with clinical features and the prognostic values, and then, they were assessed at protein levels by using an immunohistochemical assay. Consequently, IGHBP3 was selected as the candidate gene, which might be enriched in several metabolism-related pathways and cancer progression-related pathways. High expressions of IGHBP3 have an association with gender, advanced clinical stages, high T stages, and the presence of LNM. Survival analysis indicated that IGHBP3 may affect the prognosis of PTC patients. The use of a tissue chip confirmed the view that IGHBP3 might play a crucial role in the LNM of PTC. In conclusion, IGHBP3 might be involved in the development of LNM in PTC patients. IGHBP3 over-expression might be a novel indicator and a potential target for PTC therapy.

Immune-related key gene CLDN10 correlates with lymph node metastasis but predicts favorable prognosis in papillary thyroid carcinoma.

The functions of immune cells in lymph node metastasis (LNM) have attracted considerable attention. This study aimed to screen the key immune-related and LNM-related genes in PTC. In the discovery phase, the immune-related genes in LNM were screened by using bioinformatics methods. In the validation phases, the association of the genes with LNM was first confirmed in a cohort from The Cancer Genome Atlas and a cohort based on a tissue chip. Then, the relationship of the genes with immune cell infiltration was further explored. Consequently, CLDN10 was identified, and its high expression was correlated with the presence of LNM in PTC but predicted a favorable prognosis. High CLDN10 expression was positively correlated with the infiltration of several immune cells, such as B cells, CD8+T cells, and macrophages. High CLDN10 expression may improve the outcomes of patients with PTC by increasing immune cell infiltration, although it might be associated with LNM. In conclusion, although CLDN1 might be correlated with LNM, it may also increase the infiltration of immune cells, including CD8+T cells and macrophages, and improve the clinical outcomes of patients with PTC. The effects of tumor purity and immune cell infiltration need to be considered in prognosis evaluation.

Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.

Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles derived from The Cancer Genome Atlas. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In the present study, the KEGG pathway enrichment analysis revealed that 5,962 upregulated DEGs were significantly enriched in the 'p53 signaling pathway' and involved in 'lysine degradation'. In addition, 3,709 downregulated DEGs were enriched in 'pathways in cancer', as well as 'tight junction regulation', the 'cell cycle' and the 'Wnt signaling pathway'. The 13 top hub genes MAPK1, PHLPP1, ESR1, MDM2, CDKN2A, CDKN1A, AURKA, BCL2L1, POLQ, PIK3R3, RHOQ, EIF4E and LATS2 were identified via the protein-protein interaction network. Furthermore, the OncoPrint algorithm from cBioPortal declared that 25% of EC cases carried genetic alterations. The altered DEGs (MAPK1, MDM2, AURKA, EIF4E and LATS2) may be involved in tumor differentiation and may be valuable diagnostic biomarkers. In conclusion, a number of principal genes were identified in the present study that may be determinants of poorly differentiated type II EC carcinogenesis, which may contribute to future research into potential molecular mechanisms. In addition, these genes may help identify candidate biomarkers and novel therapeutic targets for type II EC.