Transcription Elongation Factor A (SII) -Like (TCEAL) Gene Family Member-TCEAL2: A Novel Prognostic Marker in Pan-Cancer

Background: Cancer is the leading cause of death in the world. The mechanism is not fully elucidated and the therapeutic effect is also unsatisfactory. In our study, we aim to find new target gene in pan-cancer.Methods: Differentially expressed genes (DEGs) was screened out in various types of cancers from GEO database. The expression of DEG (TCEAL2) in tumor cell lines, normal tissues and tumor tissues was calculated. Then the clinical characteristics, DNA methylation, tumor infiltration and gene enrichment of TCEAL2 was studied. Results: TCEAL2 expressions were down-regulated in most cancers. Its expression and methylation were positively or negatively associated with prognosis in different cancers. The tumor infiltration results revealed that TCEAL2 was significantly related with many immune cells especially NK cells and immune-related genes in majority cancers. Furthermore, tau protein and tubulin binding were involved in the molecular function mechanisms of TCEAL2. Conclusion: TCEAL2 may be a novel prognostic marker in different cancers and may affect tumor through immune infiltration.

Altered neurogenic pathways in experimental rat models of ischemic cerebral stroke: A transcriptome based meta-analysis

Objectives: Promoting neurogenesis mediated recovery is one of the most sought after strategies in recovery after cerebral stroke. In this paper we elucidate how neurogenesis related genes are altered in the early stroke environment, to hint at potential pathways for therapeutic recovery. Materials and Methods: Around 97 microarray datasets derived from stroke affected rat brains were collected from NCBI-GEO. Datasets were normalized and subjected to a meta-analysis in Network Analyst to identify differentially expressed genes. Gene enrichment analyses were carried out using GSEA, and WebGestalt and results were visualized using Cytoscape Enrichment mapping. Results: Nearly 939 differentially expressing genes were identified in the cerebral stroke group. Among them, 30 neurogenesis related genes were identified through enrichment mapping analysis, and 35 genes through Protein-Protein Interaction analysis. Highest upregulated neurogenesis genes were found to be TSPO, GFAP, VIM, and TGFB1. The Highest Downregulated neurogenesis genes were found to be THY1, NR1D1, CDK5, STX1B, and NOG. Conclusions: Through this study, we have identified that during the acute time frame after stroke, the majority of the neurogenesis genes related to neural proliferation and neural differentiation are downregulated, while the majority of the genes related to neuronal migration were upregulated. A single or combined therapeutic approach against the identified dysregulated genes could greatly aid neural restoration and functional recovery during the postischemic stage.

WebSeq: A Genomic Data Analytics Platform for Monogenic Disease Discovery

Whole exome sequencing (WES) is commonly used to study monogenic diseases. The application of this sequencing technology has gained in popularity amongst clinicians and researchers as WES pricing has declined. The accumulation of WES data creates a need for a robust, flexible, scalable and easy-to-use analytics platform to allow researchers to gain biological insight from this genomic data. We present WebSeq, a self-contained server and web interface to facilitate intuitive analysis of WES data. WebSeq provides access to sophisticated tools and pipelines through a user-friendly and modern web interface. WebSeq has modules that support i) FASTQ to VCF conversion, ii) VCF to ANNOVAR CSV conversion, iii) family-based analyses for Mendelian disease gene discovery, iv) cohort-wide gene enrichment analyses, (v) an automated IGV browser, and (vi) a 'virtual gene panel' analysis module. WebSeq Pro, our expanded pipeline, also supports SNP genotype analyses such as ancestry inference and kinship testing. WebSeq Lite, our minimal pipeline, supports family-based analyses, cohort-wide gene enrichment analyses, and a virtual gene panel along with the IGV browser module. We anticipate that the rigorous use of our web application will allow researchers to expedite discoveries from human genomic data. WebSeq Lite, WebSeq, and WebSeq Pro are fully containerized using Docker, run on all major operating systems, and are freely available for personal, academic, and non-profit use at http://bitly.ws/g6cn .

Combination Breeding and Marker-Assisted Selection to Develop Late Blight Resistant Potato Cultivars

(1) Background: Although resistance to pathogens and pests has been researched in many potato cultivars and breeding lines with DNA markers, there is scarce evidence as to the efficiency of the marker-assisted selection (MAS) for these traits when applied at the early stages of breeding. A goal of this study was to estimate the potential of affordable DNA markers to track resistance genes that are effective against the pathogen Phytophthora infestans (Rpi genes), as a practical breeding tool on a progeny of 68 clones derived from a cross between the cultivar Sudarynya and the hybrid 13/11-09. (2) Methods: this population was studied for four years to elucidate the distribution of late blight (LB) resistance and other agronomical desirable or simple to phenotype traits such as tuber and flower pigmentation, yield capacity and structure. LB resistance was phenotypically evaluated following natural and artificial infection and the presence/absence of nine Rpi genes was assessed with 11 sequence-characterized amplified region (SCAR) markers. To validate this analysis, the profile of Rpi genes in the 13/11-09 parent was established using diagnostic resistance gene enrichment sequencing (dRenSeq) as a gold standard. (3) Results: at the early stages of a breeding program, when screening the segregation of F1 offspring, MAS can halve the workload and selected SCAR markers for Rpi-genes provide useful tools.

Derivation and Comprehensive Analysis of Aging Patterns in Patients with Bladder Cancer

Background. Aging is an essential risk factor for cancer. However, aging-related genes (ARGs) have not been comprehensively analyzed in bladder cancer (BC). Therefore, the study is aimed at derivating a risk stratification system for BC patients based on ARGs. Methods. Public databases were used to acquire ARGs sets, transcriptome files, and clinical data. The “limma” package was then used to screen for differential ARGs while also using univariate Cox regression analysis to explore for prognostic ARGs. The “ConsensusClusterPlus” package was used to perform aging patterns in BC patients based on the above prognostic ARGs. Subsequently, aging patterns were investigated in survival prediction, mutation landscape, immunotherapy, immunological checkpoints, and immune microenvironment. We likewise utilized gene enrichment analysis to explore the biological functions that were behind the findings. To construct a risk signature and nonogram for prognostic prediction, we used LASSO and Cox regression analysis based on differential genes in aging patterns. In addition, we plotted a nomogram and validate the accuracy of the risk signature in GEO and TCGA cohorts. We explored the possible biological mechanism using GSEA analysis and preliminarily identified a hub gene using PPI network. Finally, we validated the expression of hub gene in BC cell lines. Results. We screened 84 downregulated ARGs, 74 upregulated ARGs, and 32 prognostic ARGs in the human aging genome resource. The aging patterns based on prognostic genes had excellent survival prediction ( p < 0.001 ) and discriminatory ability in 405 BC patients. In addition, we found no significant differences in aging patterns in mutation analysis, which were all characterized by TP53, TTN, and KMT2D mutations. It is worth noting that cluster B in the aging patterns has a better response to immunotherapy and a more active immune microenvironment ( p < 0.05 ). In addition, gene enrichment analysis showed that aging patterns may be related to biological processes such as Staphylococcus aureus infection, phagosome, and cytokine-cytokine receptor interaction. Subsequently, we constructed a risk signature based on 16 differential genes from different aging patterns and had good survival prediction ability in both GEO and TCGA cohort. Specifically, survival analysis revealed a significantly shorter survival time in the high-risk group than in the low-risk group (TCGA and GEO, p < 0.001 ). In addition, AUC values in the ROC analysis predicted 1, 3, and 5 years in TCGA cohort that are 0.713, 0.714, and 0.738, respectively. AUC values predicted 1, 3, and 5 years in GEO cohort that are 0.606, 0.663, and 0.718, respectively. There is no doubt that risk score was an independent prognostic factor from results of multivariate Cox regression analysis in BC patients ( p < 0.001 ). There were also significant differences in immune cell infiltration, immune checkpoint, and immune score between the two groups ( p < 0.05 ), but it should not be ignored that the correlation with the HLA expression was weak. Finally, we identified and validated CLIC3 as a hub gene that may be involved in the Wnt signaling pathway, etc. Conclusion. We provided robust evidences that aging patterns based on ARGs can guide targeted therapy and survival prediction in BC patients.

Combination Breeding and Marker-Assisted Selection to Develop Late Blight Resistant Potato Cultivars

(1) Background: Although resistance to pathogens and pests has been researched in many potato cultivars and breeding lines with DNA markers, there is scarce evidence as to the efficiency of the marker-assisted selection (MAS) for these traits when applied at the early stages of breeding. A goal of this study was to estimate the potential of affordable DNA markers to track Rpi disease resistance genes, that are effective against the pathogen Phytophthora infestans, as a practical breeding tool on a progeny of 68 clones derived from a cross between the cultivar Sudarynya and 13/11-09. (2) Methods: this population was studied for four years to elucidate the distribution of LB resistance and other agronomical desirable or simple to phenotype traits such as tuber and flower pigmentation, capacity and structure of yield. LB resistance was phenotypically determined through natural and artificial infection and the presence/absence of nine Rpi genes was assessed via 11 sequence-characterized amplified region (SCAR) markers. To aid this analysis, the profile of Rpi genes in the 13/11-09 parent was established using diagnostic resistance gene enrichment sequencing (dRenSeq) as a gold standard. (3) Results: at the early stages of a breeding program, MAS can halve the workload when screening the segregation of F1 offspring and selected SCAR markers for Rpi-genes provide useful tools.

Assessing the relationships between neurological and psychiatric diseases with astrocyte subtypes and psychotropic medications

Astrocytes have many important functions in the brain, but their roles in CNS disorders and their responses to psychotropic medications are still being elucidated. In this study, we used gene enrichment analysis to assess the relationships between different astrocyte subtypes, neurological and psychiatric diseases, and psychotropic medications. We also carried out qPCR analyses and "look-up" studies to further assess the chronic effects of these drugs on astrocyte marker gene expression. Our bioinformatic analysis identified differential gene enrichment of different astrocyte subtypes in CNS disorders. The "common" astrocyte subtype was the most frequently enriched across disorders, but the highest level of enrichment was found in depression, supporting a role for astrocytes in this disorder. We also identified common enrichment of metabolic and signal transduction-related biological processes in astrocyte subtypes and CNS disorders. However, enrichment of different psychotropic medications, including antipsychotics, antidepressants, and mood stabilizers, was limited in astrocyte subtypes. These results were confirmed by "look-up" studies and qPCR analysis, which also reported little effect of common psychotropic medications on astrocyte marker gene expression, suggesting that astrocytes are not a primary target of these medications. Overall, this study provides a unique view of astrocyte subtypes and the effect of medications on astrocytes in disease, which will contribute to our understanding of their role in CNS disorders and offers insights into targeting astrocytes therapeutically.

Bioinformatics Analysis Predicts ceRNA Regulatory Axes Related to Melanoma Pathogenesis

Background Melanoma is a highly malignant skin tumour, with an incidence and mortality rates accounting for approximately 5% and >75% of all tumours, respectively. In the present study, we aimed to screen mRNAs, microRNAs, and circRNAs related to the pathogenesis of melanoma via bioinformatics methods. Materials and methods The microarray data correlating with melanoma were obtained from the GEO database, and the differentially expressed genes between melanomatissues and non-melanoma tissues were screened using GEO2R. Moreover, the Hub genes were screened using the STRING database, Cytoscape software, and GEPIA database. The DAVID database was used for gene enrichment analysis. Thereafter, the ceRNA network diagram was constructed using the starBase database and was analysed for survival in order to predict the molecular markers for diagnosis and treatment of skin cutaneous melanoma; the most probable ceRNA mechanism was screened via pan-cancer analysis. Furthermore, the ceRNA network was verified using the GEPIA and UALCAN databases. Results In total, 266, 20, and 10 differentially expressed mRNAs, microRNAs, and circRNA10 were screened. Using Cytoscape software, 59 Hub and 31 key genes were screened, followed by construction of the ceRNA and ceRNA-gene enrichment analysis networks. Conclusion Clinical verification revealed that SIPA1L1 could regulate the expression of DSC3 by sponge adsorption of has-miR-106b and has-miR-20b, and thereby affect the pathogenesis and progression of skin cutaneous melanoma.

Genome-wide association study reveals susceptibility loci for self-reported headache in a large community-based Asian population

Background The genetic substrate for headache in the general population has not been identified in Asians. We investigated susceptible genetic variants for self-reported headache in a large community-based Asian population. Methods We conducted a genome-wide association study in participants recruited from a community-based cohort to identify the genetic variants associated with headache in Taiwanese. All participants received a structured questionnaire for self-reported headache. A total of 2084 patients with “self-reported headache” and 11,822 age- and sex-matched controls were enrolled. Gene enrichment analysis using the Genotype-Tissue Expression version 6 database was performed to explore the potential function of the identified variants. Results We identified two novel loci, rs10493859 in TGFBR3 and rs13312779 in FGF23, that are functionally relevant to vascular function and migraine to be significantly associated with self-reported headache after adjusting age, sex and top 10 principal components ( p = 8.53 × 10−11 and p = 1.07 × 10−8, respectively). Gene enrichment analysis for genes with GWAS suggestive significance ( p < 10−6) demonstrated that the expression of these genes was significantly enriched in the artery ( p = 8.18 × 10−4) and adipose tissue ( p = 8.95 × 10−4). Conclusion Our results suggest that vascular dysfunction might play important roles in the pathogenesis of self-reported headache in Asian populations.

A Comparison Analysis for Protein-Protein Interaction Network-Based Methods in Prioritizing Arabidopsis Functional Genes

Background: Connecting genes to phenotypes is still a great challenge in genetics. Research related to gene-phenotype associations has made remarkable progress recently due to high-throughput sequencing technology and genome-wide association study (GWAS). However, these genes, which are considered to be significantly associated with a target phenotype according to traditional GWAS, are less precise or subject to greater confounding. Objective: The present study is an attempt to prioritize functional genes for complex phenotypes employing protein-protein interaction (PPI) network-based systems genetics methods on available GWAS results. Method: In this paper, we calculated the functional gene enrichment ratios of the trait ontology of A. thaliana for three common systems genetics methods (i.e. GeneRank, K-shell and HotNet2). Then, comparison of gene enrichment ratios obtained by PPI network-based methods was performed. Finally, a hybrid model was proposed, integrating GeneRank, comprehensive score algorithm and HotNet diffusion-oriented subnetworks (HotNet2) to prioritize functional genes. Results: These PPI network-based systems genetics methods were indeed useful for prioritizing phenotype-associated genes. And functional gene enrichment ratios calculated from the top 20% of GeneRank-identified genes were higher than these ratios of K-shell and these ratios of HotNet2 for most phenotypes. However, the hybrid model can improve the efficiency of functional gene enrichment for A. thaliana (up to 40%). Conclusion: The present study provides a hybrid method integrating GeneRank, comprehensive score algorithm and HotNet2 to prioritize functional genes. The method will contribute to functional genomics in plants. The source data and codes are freely available at http://47.242.161.60/Plant/.