Joint efficacy of the three biomarkers SNCA,GYPB and HBG1 for atrial fibrillation and stroke: Analysis via the support vector machine neural network

Atrial fibrillation (AF) is the most common type of persistent arrhythmia. Although its incidence has been increasing, the pathogenesis of AF in stroke remains unclear. In this study, a total of 30 participants were recruited, including 10 controls, 10 patients with AF and 10 patients with AF and stroke (AF + STROKE). Differentially expressed genes (DEGs) were identified, and functional annotation of DEGs, comparative toxicogenomic database analysis associated with cardiovascular diseases, and predictions of miRNAs of hub genes were performed. Using RT‐qPCR, biological process and support vector machine neural networks, numerous DEGs were found to be related to AF. HBG1, SNCA and GYPB were found to be upregulated in the AF group. Higher expression of hub genes in AF and AF + STROKE groups was detected via RT‐PCR. Upon training the biological process neural network of SNCA and GYPB for HBG1, only small differences were detected. Based on the support vector machine, the predicted value of SNCA and GYPB for HBG1 was 0.9893. Expression of the hub genes of HBG1, SNCA and GYPB might therefore be significantly correlated to AF. These genes are involved in the incidence of AF complicated by stroke, and may serve as targets for early diagnosis and treatment.     

Genome‐wide selective detection of Mile red‐bone goat using next‐generation sequencing technology

The ecotype population of goats (Capra hircus) was created by long‐term artificial selection and natural adaptation. Mile red‐bone goat is an indigenous breed with visible red bones, and its special bone structure has received extensive attention. This study aimed to identify genetic variants and candidate genes associated with specific bone phenotypes using next‐generation sequencing technology (NGS). The results revealed that 31,828,206 single nucleotide polymorphisms (SNPs) were obtained from 72 goats (20 Mile red‐bone goats and 52 common goats) by NGS. A total of 100 candidate genes were identified on the basis top 1% window interaction from nucleotide diversity (π), π ratio (π _A/π _B), and pairwise fixation index (F _ST). Exactly 77 known signaling pathways were enriched. Specifically, three coding genes (NMNAT2, LOC102172983, and PNLIP) were annotated in the vitamin metabolism signaling pathways, and NCF2 was annotated to the osteoclast (OC) differentiation pathway. Furthermore, 5862 reliable copy number variations (CNVs) were obtained, and 14 and 24 genes were annotated with the top 1‰ CNV based on F _ST (>0.490) and V _ST (>0.527), respectively. Several pathways related to bone development and metabolism of exogenous substances in vivo, including calcium signaling pathway, OC differentiation, and glycerophospholipid metabolism, were annotated. Specifically, six genes from 19 candidate CNVs, which were obtained by interaction of the top 1‰ CNVs with F _ST and V _ST, were annotated to mucin‐type O‐glycan biosynthesis and metabolic pathways. Briefly, the results implied that pseudopurpurin and specific genetic variants work together to contribute to the red‐bone color and specific bone structure of Mile red‐bone goat. This study is helpful to understanding the genetic basis of the unique bone phenotype of Mile red‐bone goats.     

Multi‐omics of the expression and clinical outcomes of TMPRSS2 in human various cancers: A potential therapeutic target for COVID‐19

Growing evidence has shown that Transmembrane Serine Protease 2 (TMPRSS2) not only contributes to the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, but is also closely associated with the incidence and progression of tumours. However, the correlation of coronavirus disease (COVID‐19) and cancers, and the prognostic value and molecular function of TMPRSS2 in various cancers have not been fully understood. In this study, the expression, genetic variations, correlated genes, immune infiltration and prognostic value of TMPRSS2 were analysed in many cancers using different bioinformatics platforms. The observed findings revealed that the expression of TMPRSS2 was considerably decreased in many tumour tissues. In the prognostic analysis, the expression of TMPRSS2 was considerably linked with the clinical consequences of the brain, blood, colorectal, breast, ovarian, lung and soft tissue cancer. In protein network analysis, we determined 27 proteins as protein partners of TMPRSS2, which can regulate the progression and prognosis of cancer mediated by TMPRSS2. Besides, a high level of TMPRSS2 was linked with immune cell infiltration in various cancers. Furthermore, according to the pathway analysis of differently expressed genes (DEGs) with TMPRSS2 in lung, breast, ovarian and colorectal cancer, 160 DEGs genes were found and were significantly enriched in respiratory system infection and tumour progression pathways. In conclusion, the findings of this study demonstrate that TMPRSS2 may be an effective biomarker and therapeutic target in various cancers in humans, and may also provide new directions for specific tumour patients to prevent SARS‐CoV‐2 infection during the COVID‐19 outbreak.     

Genome‐scale screening in a rat haploid system identifies Thop1 as a modulator of pluripotency exit

ObjectivesThe rats are crucial animal models for the basic medical researches. Rat embryonic stem cells (ESCs), which are widely studied, can self‐renew and exhibit pluripotency in long‐term culture, but the mechanism underlying how they exit pluripotency remains obscure. To investigate the key modulators on pluripotency exiting in rat ESCs, we perform genome‐wide screening using a unique rat haploid system.Materials and MethodsRat haploid ESCs (haESCs) enable advances in the discovery of unknown functional genes owing to their homozygous and pluripotent characteristics. REX1 is a sensitive marker for the naïve pluripotency that is often utilized to monitor pluripotency exit, thus rat haESCs carrying a Rex1‐GFP reporter are used for genetic screening. Genome‐wide mutations are introduced into the genomes of rat Rex1‐GFP haESCs via piggyBac transposon, and differentiation‐retarded mutants are obtained after random differentiation selection. The exact mutations are elucidated by high‐throughput sequencing and bioinformatic analysis. The role of candidate mutation is validated in rat ESCs by knockout and overexpression experiments, and the phosphorylation of ERK1/2 (p‐ERK1/2) is determined by western blotting.ResultsHigh‐throughput sequencing analysis reveals numerous insertions related to various pathways affecting random differentiation. Thereafter, deletion of Thop1 (one candidate gene in the screened list) arrests the differentiation of rat ESCs by inhibiting the p‐ERK1/2, whereas overexpression of Thop1 promotes rat ESCs to exit from pluripotency.ConclusionsOur findings provide an ideal tool to study functional genomics in rats: a homozygous haploid system carrying a pluripotency reporter that facilitates robust discovery of the mechanisms involved in the self‐renewal or pluripotency of rat ESCs.

Differentiation of pluripotent rat embryonic stem cells (ESCs) in vitro is difficult to achieve for unknown mechanisms. Rat haploid ESCs (haESCs) have been validated as a powerful tool to target unknown functional genes and pathways based on homozygous genetic screening. Xu et al. utilized Rex1‐GFP labelled‐rat haESCs to conduct genome‐scale screening of genes modulating pluripotency exiting. Validation experiments showed that Thop1 (one of the screened out genes) played very important roles in the random differentiation of rat ESCs in vitro via modulating phosphorylation of ERK.     

Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data

Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are two major types of joint diseases. The present study aimed to identify hub genes involved in the pathogenesis and further explore the potential treatment targets of RA and OA.Methods: The gene expression profile of {"type":"entrez-geo","attrs":{"text":"GSE12021","term_id":"12021"}}GSE12021 was downloaded from Gene Expression Omnibus (GEO). Total 31 samples (12 RA, 10 OA and 9 NC samples) were used. The differentially expressed genes (DEGs) in RA versus NC, OA versus NC and RA versus OA groups were screened using limma package. We also verified the DEGs in {"type":"entrez-geo","attrs":{"text":"GSE55235","term_id":"55235"}}GSE55235 and {"type":"entrez-geo","attrs":{"text":"GSE100786","term_id":"100786"}}GSE100786. Functional annotation and protein–protein interaction (PPI) network construction of OA‐ and RA‐specific DEGs were performed. Finally, the candidate small molecules as potential drugs to treat RA and OA were predicted in CMap database.Results: 165 up-regulated and 163 down-regulated DEGs between RA and NC samples, 73 up-regulated and 293 down-regulated DEGs between OA and NC samples, 92 up-regulated and 98 down-regulated DEGs between RA and OA samples were identified. Immune response and TNF signaling pathway were significantly enriched pathways for RA‐ and OA‐specific DEGs, respectively. The hub genes were mainly associated with ‘Primary immunodeficiency’ (RA vs. NC group), ‘Ribosome’ (OA vs. NC group), and ‘Chemokine signaling pathway’ (RA vs. OA group). Arecoline and Cefamandole were the most promising small molecule to reverse the RA and OA gene expression.Conclusion: Our findings suggest new insights into the underlying pathogenesis of RA and OA, which may improve the diagnosis and treatment of these intractable chronic diseases.