term enrichment
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Author(s):  
Junhong Wang ◽  
Xiaoxu Li ◽  
Yiyuan Lu ◽  
Quntao Huang ◽  
Yu Sun ◽  
...  

In previous experiments, we identified the effect of deletion of the Zbtb1 gene on circRNAs and microRNAs. In this study, we examined the expression profiles of lncRNAs and mRNAs using the RNA-seq method for Zbtb1-deficient EL4 cells and performed a clustering analysis of differentially expressed lncRNAs and mRNAs. GO term histograms and KEGG scatter plots were drawn. For the experimental results, a joint analysis was performed, which predicted the regulatory relationships among lncRNAs, mRNAs, microRNAs and circRNAs. For the regulatory relationship between lncRNAs and target genes, the chromatin structure and the degree of openness were verified for the possible target gene locations regulated by lncRNA using experimental methods such as Hi-C and ATAC-seq. Ultimately, the possible differential regulation of the Brcal and Dennd5d genes by lncRNAs and the differential changes in transcription factor binding sites in the promoter region were identified. For neRNA-regulated target genes with significantly differentially expressed mRNAs, a combined screen was performed, and the final obtained candidate target genes were subjected to GO and KEGG term enrichment analyses. Our results illustrate that the Zbtb1 gene can not only function as a regulatory factor but also regulate EL4 cells from multiple perspectives based on ceRNA theory.


2021 ◽  
Author(s):  
Yongsen Shi ◽  
Chunli Xu ◽  
Jingyi Li ◽  
Yilin Yao ◽  
Qigui Niu

The expanded granular sludge blanket reactor (EGSB) was operated for 198 days to study the long-term effects of phenanthrene (PHE) enrichment on system performance and microbial community. The results showed that the PHE was significantly enriched in the reactor. The final PHE concentration in effluent and sludge reached to 1.764±0.05 mg/L and 12.52±0.42 mg/gTS, respectively. While the average daily methane production was decreased by 5.0%-9.8% under long-term PHE exposure. The 3D-EEM of effluent indicated that PHE stimulated the microbial metabolism with the higher intensity of soluble microbial byproduct-like materials (SMP) and proteins. Moreover, the removal efficiency of soluble chemical oxygen demand (SCOD) and NH4+-N gradually diminished with the enrichment of PHE. PHE shaped the microbial community, and the predominant fermentative bacteria (Mesotoga) was severely inhibited. Contrarily, the bacteria (Syntrophorhabdus, Acinetobacter, Desulfovibrio, Desulfomicrobium) involved in PHE-degradation was enriched at end of Phase V. In addition, the relative abundance (RA) of hydrotrophic methanogens (Methanofastidiosum, Methanolinea, Methanobacterium, Methanomassiliicoccus) increased by 0.96-fold with the long-term enrichment of PHE, while the RA of acetoclastic Methanosaeta obviously decreased.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rasmus Magnusson ◽  
Zelmina Lubovac-Pilav

Abstract Background Transcription factors (TFs) are the upstream regulators that orchestrate gene expression, and therefore a centrepiece in bioinformatics studies. While a core strategy to understand the biological context of genes and proteins includes annotation enrichment analysis, such as Gene Ontology term enrichment, these methods are not well suited for analysing groups of TFs. This is particularly true since such methods do not aim to include downstream processes, and given a set of TFs, the expected top ontologies would revolve around transcription processes. Results We present the TFTenricher, a Python toolbox that focuses specifically at identifying gene ontology terms, cellular pathways, and diseases that are over-represented among genes downstream of user-defined sets of human TFs. We evaluated the inference of downstream gene targets with respect to false positive annotations, and found an inference based on co-expression to best predict downstream processes. Based on these downstream genes, the TFTenricher uses some of the most common databases for gene functionalities, including GO, KEGG and Reactome, to calculate functional enrichments. By applying the TFTenricher to differential expression of TFs in 21 diseases, we found significant terms associated with disease mechanism, while the gene set enrichment analysis on the same dataset predominantly identified processes related to transcription. Conclusions and availability The TFTenricher package enables users to search for biological context in any set of TFs and their downstream genes. The TFTenricher is available as a Python 3 toolbox at https://github.com/rasma774/Tftenricher, under a GNU GPL license and with minimal dependencies.


2021 ◽  
Author(s):  
Xiangling Wang ◽  
Zhenzhen Wu ◽  
Baiquan Song ◽  
Xiaoyu Zhao ◽  
Xin Song

Abstract (Aims) Sugar beet is one of the most sensitive crops to boron and boron deficiency inhibits the root growth and causes hollow symptoms in beets. However, how the roots of boron efficient sugar beet variety adapt to the morphology, physiological, and transcriptome mechanisms of boron deficiency are rarely reported. (Method) Thus, the present study was carried out with B efficient sugar beet variety (H, KWS1197) and B inefficient variety (L, KWS0143), and two B levels i.e., B0.1 (0.1 μM H3BO3, deficiency) and B50 (50 μM H3BO3, control) were designed for hydroponic experiment. (Result) Boron deficiency reduced the total root length, root forks, and root biomass of sugar beet. Compared with L variety, H variety have higher boron transport coefficient, boron distribution ratio above ground, peroxidase and catalase activities, lower malondialdehyde content and reactive oxygen species accumulation. Transcriptome data showed that the two comparison groups, HB0.1 vs HB50 and LB0.1 vs LB50, were enriched for 537 and 257 differentially expressed genes, respectively. The H variety mainly induced and regulated the GO term enrichment associated with antioxidant and stress resistance. On the contrary, the L variety induced cell death and negative regulation of biological and metabolic processes. (Conclusion) B efficient variety specifically up-regulated boron deficiency response genes to activate the antioxidant enzyme system, promoted rational root configuration, and enhance plant growth anti-oxidation and resistance to boron deficiency. The results of this study serve as a theoretical basis of screening candidate genes that respond to boron deficiency and adaptation mechanism of boron deficiency.


2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Jia ◽  
Hui Feng ◽  
Yanhua Bu ◽  
Naizhe Ji ◽  
Yingmin Lyu ◽  
...  

Rose is one of the most fundamental ornamental crops, but its yield and quality are highly limited by drought. The key transcription factors (TFs) and co-expression networks during rose’s response to drought stress and recovery after drought stress are still limited. In this study, the transcriptomes of leaves of 2-year-old cutting seedlings of Rosa chinensis ‘Old Blush’ from three continuous droughted stages (30, 60, 90 days after full watering) and rewatering were analyzed using RNA sequencing. Weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression network, which was associated with the physiological traits of drought response to discovering the hub TFs involved in drought response. More than 45 million high-quality clean reads were generated from the sample and used for comparison with the rose reference genome. A total of 46433 differentially expressed genes (DEGs) were identified. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that drought stress caused significant changes in signal transduction, plant hormones including ABA, auxin, brassinosteroid (BR), cytokinin, ethylene (ET), jasmonic acid (JA) and salicylic acid (SA), primary and secondary metabolism, and a certain degree of recovery after rewatering. Gene co-expression analysis identified 18 modules, in which four modules showed a high degree of correlation with physiological traits. In addition, 42 TFs including members of NACs, WRKYs, MYBs, AP2/ERFs, ARFs, and bHLHs with high connectivity in navajowhite1 and blue modules were screened. This study provides the transcriptome sequencing report of R. chinensis ‘Old Blush’ during drought stress and rewatering process. The study also identifies the response of candidate TFs to drought stress, providing guidelines for improving the drought tolerance of the rose through molecular breeding in the future.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Giulio Testone ◽  
Anatoly Petrovich Sobolev ◽  
Giovanni Mele ◽  
Chiara Nicolodi ◽  
Maria Gonnella ◽  
...  

AbstractEndive (Cichorium endivia L.), a vegetable consumed as fresh or packaged salads, is mostly cultivated outdoors and known to be sensitive to waterlogging in terms of yield and quality. Phenotypic, metabolic and transcriptomic analyses were used to study variations in curly- (‘Domari’, ‘Myrna’) and smooth-leafed (‘Flester’, ‘Confiance’) cultivars grown in short-term waterlog due to rainfall excess before harvest. After recording loss of head weights in all cultivars (6-35%), which was minimal in ‘Flester’, NMR untargeted profiling revealed variations as influenced by genotype, environment and interactions, and included drop of total carbohydrates (6–50%) and polyols (3–37%), gain of organic acids (2–30%) and phenylpropanoids (98–560%), and cultivar-specific fluctuations of amino acids (−37 to +15%). The analysis of differentially expressed genes showed GO term enrichment consistent with waterlog stress and included the carbohydrate metabolic process. The loss of sucrose, kestose and inulin recurred in all cultivars and the sucrose-inulin route was investigated by covering over 50 genes of sucrose branch and key inulin synthesis (fructosyltransferases) and catabolism (fructan exohydrolases) genes. The lowered expression of a sucrose gene subset together with that of SUCROSE:SUCROSE-1-FRUCTOSYLTRANSFERASE (1-SST) may have accounted for sucrose and kestose contents drop in the leaves of waterlogged plants. Two anti-correlated modules harbouring candidate hub-genes, including 1-SST, were identified by weighted gene correlation network analysis, and proposed to control positively and negatively kestose levels. In silico analysis further pointed at transcription factors of GATA, DOF, WRKY types as putative regulators of 1-SST.


2021 ◽  
Vol 9 (4) ◽  
pp. 44
Author(s):  
Taichi Ishikawa ◽  
Daisuke Sasaki ◽  
Ryo Aizawa ◽  
Yu Shimoyama ◽  
Matsuo Yamamoto ◽  
...  

Purpose: To elucidate the effects of butyric acid (BA), a metabolite of bacteria involved in periodontitis, and a possible enhancer of the junctional epithelial cells. Methods: A murine junctional epithelial cell line, JE-1, was used to assess the effects of sodium butyrate (NaB) as BA. Cell proliferation, migration and attachment were analyzed. Additionally, gene and promoter expression analysis was performed, i.e., cap analysis of gene expression (CAGE) and gene ontology (GO) term enrichment analysis. Results: NaB affected junctional epithelial cell proliferation, migration and attachment. A high concentration of NaB caused cell death and a low concentration tended to promote migration and adhesion. CAGE analysis revealed 75 upregulated and 96 downregulated genes in the cells after 0.2 mM NaB stimulation for 3 h. Regarding GO term enrichment, the genes upregulated >4-fold participated predominantly in cell migration and proliferation. The results of this study suggest that BA produced from periodontopathic bacteria is involved in periodontal tissue destruction at high concentrations. Furthermore, at low concentrations, BA potentially participates in periodontal disease progression by increasing proliferation, migration and attachment of the junctional epithelium and thereby increasing epithelial down-growth.


2021 ◽  
Vol 1 ◽  
Author(s):  
Maarten J. M. F. Reijnders ◽  
Robert M. Waterhouse

The Gene Ontology (GO) is a cornerstone of functional genomics research that drives discoveries through knowledge-informed computational analysis of biological data from large-scale assays. Key to this success is how the GO can be used to support hypotheses or conclusions about the biology or evolution of a study system by identifying annotated functions that are overrepresented in subsets of genes of interest. Graphical visualizations of such GO term enrichment results are critical to aid interpretation and avoid biases by presenting researchers with intuitive visual data summaries. Amongst current visualization tools and resources there is a lack of standalone open-source software solutions that facilitate explorations of key features of multiple lists of GO terms. To address this we developed GO-Figure!, an open-source Python software for producing user-customisable semantic similarity scatterplots of redundancy-reduced GO term lists. The lists are simplified by grouping together terms with similar functions using their quantified information contents and semantic similarities, with user-control over grouping thresholds. Representatives are then selected for plotting in two-dimensional semantic space where similar terms are placed closer to each other on the scatterplot, with an array of user-customisable graphical attributes. GO-Figure! offers a simple solution for command-line plotting of informative summary visualizations of lists of GO terms, designed to support exploratory data analyses and dataset comparisons.


2021 ◽  
Author(s):  
Xiaopeng Xu ◽  
Bingqing Wang ◽  
Zhuoyuan Jiang ◽  
Qi Chen ◽  
Ke Mao ◽  
...  

Abstract Craniofacial microsomia (CFM, OMIM%164 210) is one of the most common congenital facial abnormalities worldwide, but it’s genetic risk factors and environmental threats are poorly investigated, as well as their interaction, making the diagnosis and prenatal screening of CFM impossible. We perform a comprehensive association study on the largest CFM cohort of 6074 samples. We identify 15 significant (P < 5 × 10−8) associated genomic loci (including eight previously reported) and decipher 107 candidates based on multi-omics data. Gene Ontology term enrichment found that these candidates are mainly enriched in neural crest cell (NCC) development and hypoxic environment. Single-cell RNA-seq data of mouse embryo demonstrate that nine of them show dramatic expression change during early cranial NCC development whose dysplasia is involved in pathogeny of CFM. Furthermore, we construct a well-performed CFM risk-predicting model based on polygenic risk score (PRS) method and estimate seven environmental risk factors that interacting with PRS. Single-nucleotide polymorphism-based PRS is significantly associated with CFM [P = 7.22 × 10−58, odds ratio = 3.15, 95% confidence interval (CI) 2.74–3.63], and the top fifth percentile has a 6.8-fold CFM risk comparing with the 10th percentile. Father’s smoking increases CFM risk as evidenced by interaction parameter of −0.324 (95% CI −0.578 to −0.070, P = 0.011) with PRS. In conclusion, the newly identified risk loci will significantly improve our understandings of genetics contribution to CFM. The risk prediction model is promising for CFM prediction, and father’s smoking is a key environmental risk factor for CFM through interacting with genetic factors.


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