Identification of key genes underlying clinical features of hepatocellular carcinoma based on weighted gene co‑expression network analysis and bioinformatics analysis

Objective: To identify module genes that are closely related to clinical features of hepatocellular carcinoma (HCC) by weighted gene co‑expression network analysis, and to provide a reference for early clinical diagnosis and treatment. Methods: GSE84598 chip data were downloaded from the GEO database, and module genes closely related to the clinical features of HCC were extracted by comprehensive weighted gene co‑expression network analysis. Hub genes were identified through protein interaction network analysis by the maximum clique centrality (MCC) algorithm;Finally, the expression of hub genes was validated by TCGA database and the Kaplan Meier plotter online database was used to evaluate the prognostic relationship between hub genes and HCC patients. Results: By comparing the gene expression data between HCC tissue samples and normal liver tissue samples, a total of 6 262 differentially expressed genes were obtained, of which 2 207 were upregulated and 4 055 were downregulated. Weighted gene co‑expression network analysis was applied to identify 120 genes of key modules. By intersecting with the differentially expressed genes, 115 candidate hub genes were obtained. The results of enrichment analysis showed that the candidate hub genes were closely related to cell mitosis, p53 signaling pathway and so on. Further application of the MCC algorithm to the protein interaction network of 115 candidate hub genes identified five hub genes, namely NUF2, RRM2, UBE2C, CDC20 and MAD2L1. Validation of hub genes by TCGA database revealed that all five hub genes were significantly upregulated in HCC tissues compared to normal liver tissues;Moreover, survival analysis revealed that high expression of hub genes was closely associated with poor prognosis in HCC patients. Conclusions: This study identifies five hub genes by combining multiple databases, which may provide directions for the clinical diagnosis and treatment of HCC.

Heterogeneity of mature oligodendrocytes in the central nervous system

Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.

Peripheral blood RNA biomarkers can predict lesion severity in degenerative cervical myelopathy

Degenerative cervical myelopathy is a common cause of spinal cord injury,with longer symptom duration and higher myelopathy severity indicating a worse prognosis.While numerous studies have investigated serological biomarkers for acute spinal cord injury,few studies have explored such biomarkers for diagnosing degenerative cervical myelopathy.This study involved 30 patients with degenerative cervical myelopathy(51.3±7.3 years old,12 women and 18 men),seven healthy controls(25.7±1.7 years old,one woman and six men),and nine patients with cervical spondylotic radiculopathy(51.9±8.6 years old,three women and six men).Analysis of blood samples from the three groups showed clear differences in transcriptomic characteristics.Enrichment analysis identified 128 differentially expressed genes that were enriched in patients with neurological disabilities.Using least absolute shrinkage and selection operator analysis,we constructed a five-gene model(TBCD,TPM2,PNKD,EIF4G2,and AP5Z1)to diagnose degenerative cervical myelopathy with an accuracy of 93.5%.One-gene models(TCAP and SDHA)identified mild and severe degenerative cervical myelopathy with accuracies of 83.3%and 76.7%,respectively.Signatures of two immune cell types(memory B cells and memory-activated CD4^(+)T cells)predicted levels of lesions in degenerative cervical myelopathy with 80%accuracy.Our results suggest that peripheral blood RNA biomarkers could be used to predict lesion severity in degenerative cervical myelopathy.

Transcriptome analysis shows nicotinamide seed treatment alters expression of genes involved in defense and epigenetic processes in roots of seedlings of Picea abies

Nicotinamide treatment of plants and plant cell cultures has been shown to promote defense and decrease levels of DNA methylation.In the present study,we used RNA-seq technology to study overall changes in gene expression induced in roots of 3-month-old spruce(Picea abies)seedlings grown from nicotinamide-treated seeds to examine the molecular mechanisms underlying the defense promotion.Approximately 350 genes were identified as differentially expressed in roots after the seed treatment.Stress response genes,including transcription factors MYB77 and LHY and two chitinase enzymes,were generally upregulated,whereas genes thought to be involved in epigenetic regulation such as DDM1,known to promote DNA methylation,were present at high frequency among the downregulated genes.Across all samples,the expression of downregulated epigenetic-related genes was highly correlated with the nicotinamide treatment,indicating a common regulation.Our results support an earlier hypothesis regarding a potential role of nicotinamide as a defense-signal mediator.

Inhibition of citral nanoemulsion to growth,spoilage ability and Al-2/luxS quorum sensing system of Shewanella putrefaciens CN-32:a study on bacteriostasis from in vitro culture and gene expression analysis

Objectives:The bacteriostatic effects of a citral nanoemulsion against Shewanella putrefaciens CN-32(SHP CN-32)were investigated using in vitro culture and gene expression analysis,forbuilding a potential application in spoilage microorganism control and aquatic products quality maintenance.Materials and Methods:SHP CN-32 was treated by prepared citral nanoemulsion when the minimal inhibitory concentration(MIC)was verified.The growth curve,membrane integrity,scanning electron microscope(SEM)observation,biofilm formation and quorum sensing(QS)signaling molecule Al-2 content were evaluated in different MIC treatment groups(0 to 1.00 MIC).The gene expression status of SHP CN-32 in O and 0.50 MIC groups were compared using transcriptome sequencing and quantitative polymerase chain reaction(PCR).Results:The in vitro culture revealed that the citral nanoemulsion could inhibit the growth of SHP CN-32 with MIC of approximately 200μg/mL.Images of membrane integrity.SEM and biofilm formation suggested significant biological structure damage in bacteria after treatment.Meanwhile,the Qs signaling molecule Al-2 content showed a decline with increasing treatment concentration.Transcriptome sequencing and quantitative PCR revealed that the majority genes related diversified functional metabolic pathways of SHP CN-32 were downregulated at varying degree.Conclusion:A significant bacteriostasis of citral nanoemulsion against SHP CN-32 was verified via the results of growth inhibition,structural destruction,signal molecular decrease and gene expression downregulation of strains.These synergies significantly affect the characteristic expression of SHP CN-32,revealing the application potential as bacteriostat,QS inhibitor and preservative in aquatic products.

Identification of potential immune-related prognostic biomarkers of lung cancer using gene co-expression network analysis

Objective The objective of this study was to identify new carcinogenetic hub genes and develop the integration of differentially expressed genes to predict the prognosis of lung cancer.Methods GSE139032 microarray data packages were downloaded from the Gene Expression Omnibus for planning,testing,and review of data.We identified KRT6C,LAMC2,LAMB3,KRT6A,and MYEOV from a key module for validation.Results We found that the five genes were related to a poor prognosis,and the expression levels of these genes were associated with tumor stage.Furthermore,Kaplan-Meier plotter showed that the five hub genes had better prognostic values.The mean levels of methylation in lung adenocarcinoma(LUAD)were significantly lower than those in healthy lung tissues for the hub genes.However,gene set enrichment analysis(GSEA)for single hub genes showed that all of them were immune-related.Conclusion Our findings demonstrated that KRT6C,LAMC2,LAMB3,KRT6A,and MYEOV are all candidate diagnostic and prognostic biomarkers for LUAD.They may have clinical implications in LUAD patients not only for the improvement of risk stratification but also for therapeutic decisions and prognosis prediction.

Characterization and expression analysis of genes encoding Taxol biosynthetic enzymes in Taxus spp.

Taxol(Paclitaxel),an important anticancer drug,is derived at very low yields from Taxus(yew)species that grow very slowly.In the present study,thirteen genes that encode enzymes involved in Taxol biosynthesis in Taxus spp.were analyzed with bioinformatics methods,and their expression levels in different tissues and after cold and hormone treatments were also analyzed.The results indicated that many cis-elements related to abiotic stresses and hormones were found in the promoter sequences of the 8 genes involved in Taxol biosynthesis.Moreover,the 13 enzymes encoded by the target genes were located in different organelles and had many phosphorylation sites in the response proteins.The 13 genes were expressed highly either in roots or in stems,with lower transcripts in needles,and they were highly expressed after treatment with cold,gibberellin,methyl jasmonate or coronatine,consistent with predictions based on the bioinformatics analysis.These results suggest that the factors such as hormones and abiotic stresses stimulate taxane biosynthesis in yews,providing an important way to sustainably generate taxanes from yew trees or their cell cultures to improve Taxol yields.

Characterization and Expression Analysis of Peroxiredoxin Genes in NNK-induced V79 Cells

4-（Methylnitrosamino）-1-（3-pyridyl）-1-butanone （NNK） is a potent and prevalent nitrosamine procarcinogen found in cigarette smoke. The aim of this work is to study alterations in peroxiredoxin （Prx） expression induced by NNK during carcinogenesis. Characterization of Prx genes from hamster was performed using bioinformatics.

FEATURE-EXTRACT ANALYSIS OF SERIAL ANALYSIS OF GENE EXPRESSION DATA

Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feature to improve the accuracy and efficiency when they are used for pattern recognition and clustering analysis. A Poisson Model-based Kernel (PMK) was proposed based on the Poisson distribution of the SAGE data. Kernel Principle Component Analysis (KPCA) with PMK was proposed and used in feature-extract analysis of mouse retinal SAGE data. The computa-tional results show that this algorithm can extract feature effectively and reduce dimensions of SAGE data.

Expression Profile Analysis of Genes Involved in Brassinosteroid Biosynthesis Pathway in Cotton Fiber Development

Cotton(Gossypium hirsutum L.) is the leading fiber crop and one of the mainstays of the economy in the world.Cotton fibers,as the main product of cotton plants,are unicellular,linear

Transcriptome and Functional Analysis of Fiber-related Gene Expression in Cotton

Fiber cell initiation is a complex process involving many pathways,including phytohormones and components for transcriptional and posttranscriptional regulation.Here we report expression

Identification and expression of the CEP gene family in apple (Malus×domestica)

Plant peptide hormones play important roles in plant growth and development. Among these hormones, the C-TERMINALLYENCODED PEPTIDE（CEP） belongs to a newly found peptide family that regulates root development in Arabidopsis as well as in other species. However, nothing is known about the CEP genes in apple（Malus×domestica, MdCEP）. In this study, a total of 27 apple CEP genes were identified through a genome-wide analysis and were phylogenetically divided into three classes（Ⅰ, Ⅱ and Ⅲ）. The predicted MdCEP genes were distributed across 10 of 17 chromosomes with different densities. Next, the gene structures and motif compositions of the MdCEP genes were analyzed. Subsequently, the expression analysis suggested that the MdCEP genes were highly activated in roots and that MdCEP23 may play an important role in regulating the growth and development of roots. Moreover, all of the MdCEP genes were responsive to multiple abiotic stresses, indicating that MdCEP genes may be involved with various aspects of physiological processes in apple. Nearly one-third of MdCEP genes had a significant response to low nitrogen treatment. Most of the MdCEP genes were up-regulated under stress, including mannitol, polyethylene glycol（PEG） and abscisic acid（ABA）, suggesting that MdCEP genes may be involved in the drought stress response. This study provides insight into the putative functions of the MdCEP genes using a genome-wide analysis of the CEP gene family.

Transcriptome analysis of adherens junction pathway-related genes after peripheral nerve injury

The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically characterized the transcript changes in the adherens junction pathway following injury. In this study, a rat model of sciatic nerve crush injury was established by forceps. Deep sequencing data were analyzed using comprehensive transcriptome analysis at 0, 1, 4, 7, and 14 days after injury. Results showed that most individual molecules in the adherens junctions were either upregulated or downregulated after nerve injury. The m RNA expression of ARPC1 B, ARPC3, TUBA8, TUBA1 C, CTNNA2, ACTN3, MET, HGF, NME1 and ARF6, which are involved in the adherens junction pathway and in remodeling of adherens junctions, was analyzed using quantitative real-time polymerase chain reaction. Most of these genes were upregulated in the sciatic nerve stump following peripheral nerve injury, except for CTNNA2, which was downregulated. Our findings reveal the dynamic changes of key molecules in adherens junctions and in remodeling of adherens junctions. These key genes provide a reference for the selection of clinical therapeutic targets for peripheral nerve injury.

Identification and analysis of differentially expressed genes involved in dark-induced photoperiod response and senescence of soybean leaves by suppression subtractive hybridization

A cDNA subtractive library enriched for dark-induced up-regulated ESTs was constructed by suppression subtractive hybridization(SSH) from leaf tissues of soybean cultivar DongNong L13 treated with short-day(8-h light/16-h dark) and long-day(16-h light/8-h dark) conditions.A total of 148 clones were sequenced,representing 76 unique ESTs which corresponded to about 20% of 738 clones from the cDNA library and showed a significant up-regulation of at least three fold verified by dot blot hybridization.The putative functions of ESTs were predicted by Blastn and Blastx.The 43 differentially expressed genes identified by subtractions were classified according to their putative functions generated by Blast analysis.Genetic functional analysis indicated that putative proteins encoded by these genes were related to diverse functions during organism development,which include biological regulation pathways such as transcription,signal transduction and programmed cell death,protein,nucleic acid and carbohydrate macromolecule degradation,the cell wall modification,primary and secondary metabolism and stress response.Two soybean transcription factors enhanced in SD conditions,GAMYB-binding protein and DNA binding protein RAV cDNAs that may be involved in SD soybean photoperiod response,had been isolated using 5'-and 3'-rapid amplification of cDNA ends(RACE)(Genbank Accession numbers DQ112540 and DQ147914).

Data Mining Based on Principal Component Analysis Application to the Nitric Oxide Response in Escherichia coli

This work evaluates a recently developed multivariate statistical method based on the creation of pseudo or latent variables using principal component analysis （PCA）. The application is the data mining of gene expression data to find a small subset of the most important genes in a set of thousand or tens of thousands of genes from a relatively small number of experimental runs. The method was previously developed and evaluated on artificially generated data and real data sets. Its evaluations consisted of its ability to rank the genes against known truth in simulated data studies and to identify known important genes in real data studies. The purpose of the work described here is to identify a ranked set of genes in an experimental study and then for a few of the most highly ranked unverified genes, experimentally verify their importance.This method was evaluated using the transcriptional response of Escherichia coli to treatment with four distinct inhibitory compounds： nitric oxide, S-nitrosoglutathione, serine hydroxamate and potassium cyanide. Our analysis identified genes previously recognized in the response to these compounds and also identified new genes.Three of these new genes, ycbR, yJhA and yahN, were found to significantly （p-values〈0.002） affect the sensitivityofE, coli to nitric oxide-mediated growth inhibition. Given that the three genes were not highly ranked in the selected ranked set （RS）, these results support strong sensitivity in the ability of the method to successfully identify genes related to challenge by NO and GSNO. This ability to identify genes related to the response to an inhibitory compound is important for engineering tolerance to inhibitory metabolic products, such as biofuels, and utilization of cheap sugar streams, such as biomass-derived sugars or hydrolysate.

Serial analysis of gene expression in mice with lipopoly-saccharide-induced acute lung injury

Objective: To monitor the systemic gene expression profile in a murine model of lipopolysaccharide-induced acute lung injury. Methods: Acute lung injury was induced by intratracheal injection of lipopolysaccharide in 3 mice. Another 3 normal mice receiving same volume of normal saline were taken as the controls. The comprehensive gene expression profile was monitored by the recently modified long serial analysis of gene expression. Results: A total of 24 670 tags representing 12 168 transcripts in the control mice and 26 378 tags representing 13 397 transcripts in the mice with lung injury were identified respectively. There were 11 transcripts increasing and 7 transcripts decreasing more than 10 folds in the lipopolysaccharide-treated mice. The most overexpressed genes in the mice with lung injury included serum amyloid A3, metallothionein 2, lipocalin 2, cyclin-dependent kinase inhibitor 1A, lactate dehydrogenase 1, melatonin receptor, S100 calcium-binding protein A9, natriuretic peptide precursor, etc. Mitogen activated protein kinase 3, serum albumin, complement component 1 inhibitor, and ATP synthase were underexpressed in the lung injury mice. Conclusions: Serial analysis of gene expression provides a molecular characteristic of acute lung injury.

Genome-Wide Analysis and Expression Patterns of the YUCCA Genes in Maize

Auxin plays important roles in various aspects of plant growth and development （Zhao, 2010）. In Arabidopsis, a number of YUCCA （YUC） genes, which are involved in auxin biosyn- thesis, have been identified （Zhao et al., 2001; Woodward et al., 2005; Cheng et al., 2006, 2007; Kim et al., 2007; Chen et al., 2014）. YUC genes encode flavin monooxygenases （FMOs） that convert indole-3-pyruvate （IPA） to indole-3-acetic acid （IAA） （Zhao, 2012）. The Arabidopsis YUC family is comprised of 11 members （Zhao et al., 2001;

Expression Analysis of Proline Metabolism-related Genes From Halophyte Arabis stelleri under Osmotic Stress Conditions

Arabis stelleri var. japonica evidenced stronger osmotic stress tolerance than Arabidopsis thaliana. Using an A. thaliana microarray chip, we determined changes in the expression of approximately 2 800 genes between A. stelleri plants treated with 0.2 M mannitol versus mock-treated plants. The most significant changes in the gene expression patterns were in genes defining cellular components or in genes associated with the endomembrane system, stimulus response, stress response, chemical stimulus response, and defense response. The expression patterns of three de novo proline biosynthesis enzymes were evaluated in A. stelleri var. japonica seedlings treated with 0.2 M mannitol, 0.2 M sorbitol, and 0.2 M NaCI. The expression of At-pyrroline-5-carboxylate synthetase was not affected by NaCI stress but was similarly induced by mannitol and sorbitol. The proline dehydrogenase gene, which is known to be repressed by dehydration stress and induced by free L-proline, was induced at an early stage by mannitol treatment, but the level of proline dehydrogenase was increased later by treatment with both mannitol and NaCI. The level of free L-proline accumulation increased progressively in response to treatments with mannitol, sorbitol, and NaCI. Mannitol induced L-proline accumulation more rapidly than NaCI or sorbitol. These findings demonstrate that the osmotic tolerance of the novel halophyte, Arabis stelleri, is associated with the accumulation of L-proline.

AN IMPROVED BICLUSTERING ALGORITHM AND ITS APPLICATION TO GENE EXPRESSION SPECTRUM ANALYSIS

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly.

Genome-Wide Analysis of Gene Expression in Stationary Phase and Genetic Characterization of Stationary-Phase-Dependent Halocin Gene Expression in the Haloarchaeon Haloferax mediterranei

The stationary phase of microbial growth is a very complex state regulated by various environmental and physiological factors. An intensive study of stationary phase could promote a comprehensive understanding of the complete life cycle of microorganisms, and may provide important insights into their adaptation to harsh and nutrient-depleted conditions. Although the underlying mechanisms have been weU-studied in bacteria and yeasts （Herman, 2002; Navarro Llorens et al., 2010）, less is known about this growth phase in archaea yet. The haloarchaeon Haloferax mediterranei has served as a good model for studying haloarchaeal physiology and metabolism for several decades because of its accelerated growth, remarkable metabolic ability and genomic stability （Han et al., 2012）. During stationary phase, H. mediterranei can produce halocin H4 （Cheung et al.,