Comparative and Functional Genomics最新文献

Somatic embryogenesis (SE), which occurs naturally in many plant species, serves as a model to elucidate cellular and molecular mechanisms of embryo patterning in plants. Decoding the regulatory landscape of SE is essential for its further application. Hence, the present study was aimed at employing Weighted Gene Correlation Network Analysis (WGCNA) to construct a gene coexpression network (GCN) for Arabidopsis SE and then identifying highly correlated gene modules to uncover the hub genes associated with SE that may serve as potential molecular targets. A total of 17,059 genes were filtered from a microarray dataset comprising four stages of SE, i.e., stage I (zygotic embryos), stage II (proliferating tissues at 7 days of induction), stage III (proliferating tissues at 14 days of induction), and stage IV (mature somatic embryos). This included 1,711 transcription factors and 445 EMBRYO DEFECTIVE genes. GCN analysis identified a total of 26 gene modules with the module size ranging from 35 to 3,418 genes using a dynamic cut tree algorithm. The module-trait analysis revealed that four, four, seven, and four modules were associated with stages I, II, III, and IV, respectively. Further, we identified a total of 260 hub genes based on the degree of intramodular connectivity. Validation of the hub genes using publicly available expression datasets demonstrated that at least 78 hub genes are potentially associated with embryogenesis; of these, many genes remain functionally uncharacterized thus far. In silico promoter analysis of these genes revealed the presence of cis-acting regulatory elements, “soybean embryo factor 4 (SEF4) binding site,” and “E-box” of the napA storage-protein gene of Brassica napus; this suggests that these genes may play important roles in plant embryo development. The present study successfully applied WGCNA to construct a GCN for SE in Arabidopsis and identified hub genes involved in the development of somatic embryos. These hub genes could be used as molecular targets to further elucidate the molecular mechanisms underlying SE in plants.

Hepatocellular carcinoma (HCC) represents a common malignancy, and mechanisms of acquired sorafenib resistance during the treatment of HCC patients remain elusive. The present study performed integrated bioinformatics analysis and explored the potential action of heme oxygenase 1 (HMOX1) in sorafenib-resistant HCC cells. Differentially expressed genes (DEGs) of the sorafenib-resistant group as compared to the sorafenib-sensitive group from GSE140202 and GSE143233 were extracted. Fifty common DEGs between GSE140202 and GSE143233 were extracted. Ten hub genes were identified from the protein-protein interaction network based on common DEGs. Experimental results revealed the upregulation of HMOX1 in sorafenib-resistant HCC cells. HMOX1 silence promoted the sensitivity to sorafenib in sorafenib-resistant HCC cells; overexpression of HMOX1 attenuated the sensitivity. In addition, HMOX1 silence downregulated the mRNA expression of ABC transporters in sorafenib-resistant HCC cells, while HMOX1 overexpression upregulated mRNA expression of ABC transporter expression in HCC cells. Further analysis also revealed that high expression of HMOX1 was associated with shorter OS and DSS in HCC patients. In conclusion, our analysis identified ten hub genes associated with sorafenib resistance in HCC. Further validation studies demonstrated that HMOX1 promoted sorafenib resistance of HCC cells via modulating ABC transporter expression.

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease with a high mortality rate. The tumor microenvironment (TME) is composed of numerous noncancerous cells that contribute to tumorigenesis and prediction of therapeutic effects. In this study, we aimed to develop a cell component-related prognostic model based on TME. We screened cell component enrichments from samples in The Cancer Genome Atlas (TCGA) HNSCC cohort using the xCell algorithm. Univariate Cox and multivariate Cox regression analyses were performed to establish an optimal independent risk model. The prognostic value of the model was further validated using Gene Expression Omnibus datasets. We found that patients in the low-risk group had a better outcome and activated immunity and may benefit more from the immune checkpoint inhibitor therapy. We also explored microRNAs (miRNAs) that may regulate these identified cell components, and 11 miRNA expression levels influenced the overall survival time. Moreover, their target mRNAs were differentially expressed in TCGA cohort and enriched in pathways of cell cycle pathways, extracellular matrix receptor interaction, human papillomavirus infection, and cancer. In summary, our cell component-related signature was a promising prognostic biomarker that provides new insights into the predictive value of nontumor components in the TME.

Plants being sessile are always exposed to various environmental stresses, and to overcome these stresses, modifications at the epigenetic level can prove vital for their long-term survival. Epigenomics refers to the large-scale study of epigenetic marks on the genome, which include covalent modifications of histone tails (acetylation, methylation, phosphorylation, ubiquitination, and the small RNA machinery). Studies based on epigenetics have evolved over the years especially in understanding the mechanisms at transcriptional and posttranscriptional levels in plants against various environmental stimuli. Epigenomic changes in plants through induced methylation of specific genes that lead to changes in their expression can help to overcome various stress conditions. Recent studies suggested that epigenomics has a significant potential for crop improvement in plants. By the induction and modulation of various cellular processes like DNA methylation, histone modification, and biogenesis of noncoding RNAs, the plant genome can be activated which can help in achieving a quicker response against various plant stresses. Epigenetic modifications in plants allow them to adjust under varied environmental stresses by modulating their phenotypic plasticity and at the same time ensure the quality and yield of crops. The plasticity of the epigenome helps to adapt the plants during pre- and postdevelopmental processes. The variation in DNA methylation in different organisms exhibits variable phenotypic responses. The epigenetic changes also occur sequentially in the genome. Various studies indicated that environmentally stimulated epimutations produce variable responses especially in differentially methylated regions (DMR) that play a major role in the management of stress conditions in plants. Besides, it has been observed that environmental stresses cause specific changes in the epigenome that are closely associated with phenotypic modifications. However, the relationship between epigenetic modifications and phenotypic plasticity is still debatable. In this review, we will be discussing the role of various factors that allow epigenetic changes to modulate phenotypic plasticity against various abiotic stress in plants.

Gastric cancer (GC) is a common digestive tumor which ranks the fourth most common malignancy worldwide. Immunotherapy is a promising treatment for GC, especially for advanced gastric cancer (AGC). However, in clinical practice, not all patients are sensitive to immunotherapy. Recent studies showed that tumor mutation burden (TMB) is closely correlated with the response of immunotherapy. The current study identified a TMB-related genes’ signature to predict the prognosis and immune feature of GC patients. Firstly, we acquired the TMB data and expression data from The Cancer Genome Atlas (TCGA) and the National Center for Biotechnology Information (NCBI) GEO databases. Then, we extracted TMB-related genes from the expression data of TCGA and two GEO cohorts. By using univariate Cox analysis, we identified that the 429 genes were correlated to GC patients’ overall survival. Subsequently, an immune prognostic signature was constructed by using the least absolute shrinkage and selection operator analysis (LASSO) and multivariate Cox regression analysis. The signature could be utilized to predict the prognosis of GC patients. In addition, the signature showed a closed correlation with immune feature of GC patients. In conclusion, our risk signature could offer hints for the prognosis of GC patients and might provide insights to formulate new immunotherapy strategies for GC patients.

Objective. Evidence increasingly shows that circular RNAs (circRNAs) are closely associated with tumorigenesis and cancer progression. However, the roles of circRNAs and the underlying mechanism behind these circRNAs in gastric cancer (GC) remain to be elucidated. This study is aimed at conferring a better understanding of GC pathogenesis with a specific focus on circRNA-based ceRNA action. Methods. circRNA expression profiles were downloaded from two Gene Expression Omnibus (GEO) microarray datasets, GSE152309 and GSE121445. Expression profiles of miRNAs and mRNAs were collected from The Cancer Genome Atlas (TCGA) database. The ceRNA network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Functional and pathway enrichment analyses were performed to evaluate functional pathways of differentially expressed mRNAs (DEmRNAs). The PPI network was constructed by mapping DEmRNAs into the STRING database to identify hub genes, and then the DEcircRNA-DEmiRNA-hub gene subnetwork was constructed. The expression levels of candidate differentially expressed circRNAs (DEcircRNAs) in cancerous and matched noncancerous gastric tissues surgically resected from 52 GC patients were determined by the RT-qPCR analysis. Results. Differential expression analysis with Venn diagram analysis showed 11 overlapped DEcircRNAs (7 upregulated circRNAs and 4 downregulated ones) between cancerous tissues and noncancerous gastric tissues. The DEcircRNA-DEmiRNA-DEmRNA network was constructed, consisting of 2 DEcircRNAs, 7 DEmiRNAs, and 104 DEmRNAs. GO and KEGG pathway analyses revealed that 104 DEmRNAs might be associated with GC development and progression. The PPI network was constructed, yielding 16 hub genes, TFDP1, KRAS, LMNB1, MET, MYBL2, CDC25A, E2F5, HMGA1, HMGA2, CBFB, CBX3, CDC7, IGF2BP3, KIF11, PDGFB, and SMC1A, which were all upregulated in GC tissues compared with adjacent tumor-free gastric tissues. Based on the above hub genes in GC, the DEcircRNA-DEmiRNA-hub gene subnetwork was reconstructed based on hsa_circ_0000384 and hsa_circ_0000043, including 22 pairs of the upcircRNA-downmiRNA-upmRNA network. The expression levels of hsa_circ_0000384 and hsa_circ_0000043 were remarkably higher in GC tissues than those in matched adjacent tumor-free gastric tissues (p < 0.001), concurring with the bioinformatics results. Conclusion. Our study offers a better understanding of circRNA-related ceRNA regulatory mechanism in the pathogenesis of GC, highlighting two ceRNA networks based on hsa_circ_0000384 and hsa_circ_0000043.

Aim. We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA). Methods. Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA. Results. Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database. Conclusions. Three genes could predict prognosis and evaluate the response to ICB in BLCA.

Tomato (Solanum lycopersicum) gray leaf spot disease is a predominant foliar disease of tomato in China that is caused mainly by the necrotrophic fungal pathogen Stemphylium lycopersici. Little is known regarding the pathogenic mechanisms of this broad-host-range pathogen. In this study, a comparative transcriptomic analysis was performed and more genetic information on the pathogenicity determinants of S. lycopersici during the infection process in tomato were obtained. Through an RNA sequencing (RNA-seq) analysis, 1,642 and 1,875 genes upregulated during the early infection and necrotrophic phases, respectively, were identified and significantly enriched in 44 and 24 pathways, respectively. The induction of genes associated with pectin degradation, adhesion, and colonization was notable during the early infection phase, whereas during the necrotrophic phase, some structural molecule activity-related genes were prominently induced. Additionally, some genes involved in signal regulation or encoding hemicellulose- and cellulose-degrading enzymes and extracellular proteases were commonly upregulated during pathogenesis. Overall, we present some putative key genes and processes that may be crucial for S. lycopersici pathogenesis. The abilities to adhere and colonize a host surface, effectively damage host cell walls, regulate signal transduction to manage infection, and survive in a hostile plant environment are proposed as important factors for the pathogenesis of S. lycopersici in tomato. The functional characterization of these genes provides an invaluable resource for analyses of this important pathosystem between S. lycopersici and tomato, and it may facilitate the generation of control strategies against this devastating disease.

As essential components of the circadian clock, the pseudo-response regulator (PRR) gene family plays critical roles in plant photoperiod pathway. In this study, we performed a genome-wide identification and a systematic analysis of the PRR gene family in maize. Nine ZmPRRs were identified, and the gene structure, conserved motif, evolution relationship, and expression pattern of ZmPRRs were analyzed comprehensively. Phylogenetic analysis indicated that the nine ZmPRR genes were divided into three groups, except for ZmPRR73, two of which were highly homologous to each of the AtPRR or OsPRR quintet members. Promoter cis-element analysis of ZmPRRs demonstrated that they might be involved in multiple signaling transduction pathways, such as light response, biological or abiotic stress response, and hormone response. qRT-PCR analysis revealed that the levels of ZmPRRs transcripts varied considerably and exhibited a diurnal rhythmic oscillation expression pattern in the given 24-h period under both SD and LD conditions, which indicated that the level of transcription of ZmPRRs expression is subjected to a circadian rhythm and modulated by light and the circadian clock. The present study will provide an insight into further exploring the biological function and regulatory mechanism of ZmPRR genes in circadian rhythm and response to photoperiod in maize.