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... Radioresistant sublines de strated seven common up-regulated genes (ATRNL1, CA2, CNR1, FAM189A1, GF RASGRP1, RGL3); however, no statistically significant enrichment was found (Figur The nine down-regulated genes that were common between A549IR and H1299IR included ADGRF1, EPHA7, LOX, LY6G5C, NSUN7, SLC22A31, SNAI2, TNFRSF11B Within the obtained gene sets, Gene Ontology (GO)-based functional analysis vides statistically enriched GO terms that show gene relationships according to ontology categories and described gene products. These categories are biological pr molecular function and cellular component [11]. We then identified significantl riched GO terms and characterized radioresistant vs. parental A549 and H1299 ce total, enriched GO terms were found in 80 subcategories under biological process, subcategories under cellular component, and seven subcategories under molecular tion. ...
... Within the obtained gene sets, Gene Ontology (GO)-based functional analysis provides statistically enriched GO terms that show gene relationships according to three ontology categories and described gene products. These categories are biological process, molecular function and cellular component [11]. We then identified significantly enriched GO terms and characterized radioresistant vs. parental A549 and H1299 cells. ...
... The GO analysis is a commonly applied method for functional studies of large-scale genomic or transcriptomic data [11]. Function enrichGO from the clusterProfiler package was used to identify significantly enriched GO terms among the given list of genes that are differentially expressed in radioresistant and parental cells [PMID: 22455463]. ...
Radioresistance is a major obstacle for the successful therapy of many cancers, including non-small cell lung cancer (NSCLC). To elucidate the mechanism of radioresistance of NSCLC cells and to identify key molecules conferring radioresistance, the radioresistant subclones of p53 wild-type A549 and p53-deficient H1299 cell cultures were established. The transcriptional changes between parental and radioresistant NSCLC cells were investigated by RNA-seq. In total, expression levels of 36,596 genes were measured. Changes in the activation of intracellular molecular pathways of cells surviving irradiation relative to parental cells were quantified using the Oncobox bioinformatics platform. Following 30 rounds of 2 Gy irradiation, a total of 322 genes were differentially expressed between p53 wild-type radioresistant A549IR and parental A549 cells. For the p53-deficient (H1299) NSCLC cells, the parental and irradiated populations differed in the expression of 1628 genes and 1616 pathways. The expression of genes associated with radioresistance reflects the complex biological processes involved in clinical cancer cell eradication and might serve as a potential biomarker and therapeutic target for NSCLC treatment.
... Enrichment analysis of different function was referred to the GO enrichment ( 52 ). Take DBP enrichment as example, where A is the count of DBPs in clusterX, B is total number of proteins in clusterX, C is the count of DBPs outside of clusterX, and D is total number of proteins outside of clusterX. ...
... The odds ratio was calculated as (A / B) / (C / D) for a specific function annotation. Subsequently, the log 2 odds ratio (LR) was determined to represent the enrichment score of a particular function for each cluster ( 52 ). A larger LR indicates a higher level of enrichment of the function within the cluster compared to the overall sample, and vice versa. ...
Tandem repeat proteins (TRPs) are widely distributed and bind to a wide variety of ligands. DNA-binding TRPs such as zinc finger (ZNF) and transcription activator-like effector (TALE) play important roles in biology and biotechnology. In this study, we first conducted an extensive analysis of TRPs in public databases, and found that the enormous diversity of TRPs is largely unexplored. We then focused our efforts on identifying novel TRPs possessing DNA-binding capabilities. We established a protein language model for DNA-binding protein prediction (PLM-DBPPred), and predicted a large number of DNA-binding TRPs. A subset was then selected for experimental screening, leading to the identification of 11 novel DNA-binding TRPs, with six showing sequence specificity. Notably, members of the STAR (Short TALE-like Repeat proteins) family can be programmed to target specific 9 bp DNA sequences with high affinity. Leveraging this property, we generated artificial transcription factors using reprogrammed STAR proteins and achieved targeted activation of endogenous gene sets. Furthermore, the members of novel families such as MOON (Marine Organism-Originated DNA binding protein) and pTERF (prokaryotic mTERF-like protein) exhibit unique features and distinct DNA-binding characteristics, revealing interesting biological clues. Our study expands the diversity of DNA-binding TRPs, and demonstrates that a systematic approach greatly enhances the discovery of new biological insights and tools.
... Bonferroni is the most stringent one among these multiple hypothesis correction methods. Benjamini-Hochberg has been widely applied in enrichment tools such as BinGO [15], DAVID [4], GOEAST [21], Gorilla [3], and Babelomics [8], to name a few. The Benjamini-Yekutieli method is included in the GOEAST package [21]. ...
... Benjamini-Hochberg has been widely applied in enrichment tools such as BinGO [15], DAVID [4], GOEAST [21], Gorilla [3], and Babelomics [8], to name a few. The Benjamini-Yekutieli method is included in the GOEAST package [21]. GOssip provides a direct analytical estimation of false positives that compares well with resampling [22]. ...
Background
A central question in bioinformatics is how to minimize arbitrariness and bias in analysis of patterns of enrichment in data. A prime example of such a question is enrichment of gene ontology (GO) classes in lists of genes. Our paper deals with two issues within this larger question. One is how to calculate the false discovery rate (FDR) within a set of apparently enriched ontologies, and the second how to set that FDR within the context of assessing significance for addressing biological questions, to answer these questions we compare a random resampling method with a commonly used method for assessing FDR, the Benjamini-Hochberg (BH) method. We further develop a heuristic method for evaluating Type II (false negative) errors to enable utilization of F-Measure binary classification theory for distinguishing “significant” from “non-significant” degrees of enrichment.
Results
The results show the preferability and feasibility of random resampling assessment of FDR over the analytical methods with which we compare it. They also show that the reasonableness of any arbitrary threshold depends strongly on the structure of the dataset being tested, suggesting that the less arbitrary method of F-measure optimization to determine significance threshold is preferable.
Conclusion
Therefore, we suggest using F-measure optimization instead of placing an arbitrary threshold to evaluate the significance of Gene Ontology Enrichment results, and using resampling to replace analytical methods
... Finally, DEGs were determined using TBtools [113] with P < 0.01 and fold change ≥1.5. GO and KEGG were conducted as enrichment analyses [108,119]. ...
Black wolfberry (Lycium ruthenicum Murr.) is an important plant for ecological preservation. In addition, its fruits are rich in anthocyanins and have important edible and medicinal value. However, a high quality chromosome-level genome for this species is not yet available, and the regulatory mechanisms involved in the biosynthesis of anthocyanins are unclear. In this study, haploid material was used to assemble a high-quality chromosome-level reference genome of Lycium ruthenicum, resulting in a genome size of 2,272 Mb with contig N50 of 92.64 Mb, and 38,993 annotated gene models. In addition, the evolution of this genome and large-scale variations compared with the Ningxia wolfberry Lycium barbarum were determined. Importantly, homology annotation identified 86 genes involved in the regulatory pathway of anthocyanin biosynthesis, five of which [LrCHS1 (evm.TU.Chr05.295), LrCHS2 (evm.TU.Chr09.488), LrAOMT (evm.TU.Chr09.809), LrF3'5'H (evm.TU.Chr06.177) and LrAN2.1 (evm.TU.Chr05.2618)] were screened by differential expression analysis and correlation analysis using a combination of transcriptome and metabolome testing. Overexpression of these genes could significantly up- or downregulate anthocyanin-related metabolites. These results will help accelerate the functional genomic research of L. ruthenicum, and the elucidation of the genes involved in anthocyanin synthesis will be beneficial for breeding new varieties and further exploring its ecological conservation potential.
... In such a case, we say that the study set is enriched in that term [19]. But this test is not meaningful/applicable to our pseudo-cliques/DQCs directly, due to their small sizes and high overlaps among them [27,42,52]. So, we combine pseudo-cliques/DQCs in the following way. ...
Pseudo-cliques (subgraphs with almost all possible edges) have many applications. But they do not satisfy the convertible antimonotone constraint (as we prove here). So, it is hard to reduce the search space of pseudo-cliques and list them efficiently. To our knowledge, only two exact algorithms, namely, ODES and PCE, were proposed for this purpose, but both have high execution times. Here, we present an exact algorithm named Fast Pseudo-Clique Enumerator (FPCE). It employs some pruning techniques we derived to reduce the search space. Our experiment on 15 real and 16 synthetic graphs shows that (i) on real graphs, FPCE is, on average, 38.6 and 6.5 times faster than ODES and PCE, respectively, whereas (ii) on synthetic graphs, FPCE is, on average, 39.7 and 3.1 times faster than ODES and PCE, respectively. We apply FPCE and a popular heuristic method on a PPI network to identify pseudo-cliques. FPCE outputs match with more known protein complexes, are more accurate, and are biologically more significant - suggesting that the exact computation of pseudo-cliques may give better insights. For its speed, FPCE is a suitable choice in such cases.
... Differential expression analysis was realized using the Bioconductor package edgeR [77] with parameters (minimum fold change = 4, p-value cutoff = 0.01 after FDR correction). The differentially expressed transcripts were then subjected to enrichment analyses, using GOeast [78] for GO enrichment and clusterProfile [79] for KEGG enrichment. We used the entire transcript annotation as the background set when conducting the DEG functional enrichment analysis, which resulted from intraspecies comparisons. ...
Many Viola plants growing in mining areas exhibit high levels of cadmium (Cd) tolerance and accumulation, and thus are ideal organisms for comparative studies on molecular mechanisms of Cd hyperaccumulation. However, transcriptomic studies of hyperaccumulative plants in Violaceae are rare. Viola baoshanensis is an amazing Cd hyperaccumulator in metalliferous areas of China, whereas its relative V. inconspicua is a non-tolerant accumulator that resides at non-metalliferous sites. Here, comparative studies by transcriptome sequencing were performed to investigate the key pathways that are potentially responsible for the differential levels of Cd tolerance between these two Viola species. A cascade of genes involved in the ubiquitin proteosome system (UPS) pathway were observed to have constitutively higher transcription levels and more activation in response to Cd exposure in V. baoshanensis, implying that the enhanced degradation of misfolded proteins may lead to high resistance against Cd in this hyperaccumulator. Many genes related to sucrose metabolism, especially those involved in callose and trehalose biosynthesis, are among the most differentially expressed genes between the two Viola species, suggesting a crucial role of sucrose metabolism not only in cell wall modification through carbon supply but also in the antioxidant system as signaling molecules or antioxidants. A comparison among transcriptional patterns of some known transporters revealed that several tonoplast transporters are up-regulated in V. baoshanensis under Cd stress, suggesting more efficient compartmentalization of Cd in the vacuoles. Taken together, our findings provide valuable insight into Cd hypertolerance in V. baoshanensis, and the corresponding molecular mechanisms will be useful for future genetic engineering in phytoremediation.
... Throughout this analysis, the Benjamini-Hochberg method 44 was employed for the correction of P values (P < 0.05). We further selected these DEGs for GO enrichment and KEGG analysis 46 to gain in-depth undeírstanding of their functions and metabolic pathways involved. We then selected genes related to the synthesis of flavonoids and terpenoids from these DEG-related genes. ...
Gynostemma pentaphyllum (Thunb.) Makino (G. pentaphyllum) is a medicinal and edible plant with multiple functions of liver protection, anti-tumor, anti-inflammation, balancing blood sugar and blood lipids. The nutritional value of the G. pentaphyllum plant is mainly due to its rich variety of biologically active substances, such as flavonoids, terpenes and polysaccharides. In this study, we performed a comprehensive analysis combining metabolomics and root, stem and leaf transcriptomic data of G. pentaphyllum. We used transcriptomics and metabolomics data to construct a dynamic regulatory network diagram of G. pentaphyllum flavonoids and terpenoids, and screened the transcription factors involved in flavonoids and terpenoids, including basic helix-loop-helix (bHLH), myb-related, WRKY, AP2/ERF. Transcriptome analysis results showed that among the DEGs related to the synthesis of flavonoids and terpenoids, dihydroflavonol 4-reductase (DFR) and geranylgeranyl diphosphate synthases (GGPPS) were core genes. This study presents a dynamic image of gene expression in different tissues of G. pentaphyllum, elucidating the key genes and metabolites of flavonoids and terpenoids. This study is beneficial to a deeper understanding of the medicinal plants of G. pentaphyllum, and also provides a scientific basis for further regulatory mechanisms of plant natural product synthesis pathways and drug development.
... Upregulated DEGs showed significant enrichment in response to biotic stimulus, integral component of plasma membrane, and molecular transducer activity. Downregulated DEGs were enriched in cell-cell signaling, Synapse, and calcium ion transmembrane transporter activity [29], Figs. 6 and 7 illustrate the GO enrichment analysis. ...
Abstract
Background: Ataxia Telangiectasia (AT) is a genetic disorder characterized by compromised DNA repair, cerebellar degeneration, and immune dysfunction. Understanding the molecular mechanisms driving AT pathology is crucial for developing targeted therapies.
Methods: In this study, we conducted a comprehensive analysis to elucidate the molecular mechanisms underlying AT pathology. Using publicly available RNA-seq datasets comparing control and AT samples, we employed in silico transcriptomics to identify potential genes and pathways. We performed differential gene expression analysis with DESeq2 to reveal dysregulated genes associated with AT. Additionally, we constructed a Protein-Protein Interaction (PPI) network to explore the interactions between proteins implicated in AT.
Results: The network analysis identified hub genes, including TYROBP and PCP2, crucial in immune regulation and cerebellar function, respectively. Furthermore, pathway enrichment analysis unveiled dysregulated pathways linked to AT pathology, providing insights into disease progression.
Conclusion: Our integrated approach offers a holistic understanding of the complex molecular landscape of AT and identifies potential targets for therapeutic intervention. By combining transcriptomic analysis with network-based methods, we provide valuable insights into the underlying mechanisms of AT pathogenesis.
Keywords: Ataxia Telangiectasia; DESeq2; PCP2; RNA-Seq; TYROBP.
... Introduction functions in genes' clusters [22]. These statistically enriched functions are then used to characterize the cell's functional organization from a molecular network captured by the gene clusters produced by embeddings of genes [23]. ...
Common approaches for deciphering biological networks involve network embedding algorithms. These approaches strictly focus on clustering the genes' embedding vectors and interpreting such clusters to reveal the hidden information of the networks. However, the difficulty in interpreting the genes' clusters and the limitations of the functional annotations' resources hinder the identification of the currently unknown cell's functioning mechanisms. Thus, we propose a new approach that shifts this functional exploration from the embedding vectors of genes in space to the axes of the space itself. Our methodology better disentangles biological information from the embedding space than the classic gene-centric approach. Moreover, it uncovers new data-driven functional interactions that are unregistered in the functional ontologies, but biologically coherent. Furthermore, we exploit these interactions to define new higher-level annotations that we term Axes-Specific Functional Annotations and validate them through literature curation. Finally, we leverage our methodology to discover evolutionary connections between cellular functions and the evolution of species.
... It offers a variety of statistical tools and techniques for data analysis, including descriptive statistics, inferential statistics, correlation analysis, regression analysis, design of experiments, and more. These are a few applications for Minitab in biological research: Minitab offers tools for designing experiments and evaluating the collected data [37]. This is crucial for a variety of biological research projects, including animal experiments and clinical trials. ...
When asked to examine your data, never forget the dreadful sensation you receive! Your hypothesis has to be statistically supported now that you have all the necessary raw data. To dispel the myth that biology students are incapable of arithmetic, you should offer your numerical data as part of statistics in your research. Research in science must use statistical techniques. As a matter of fact, statistical procedures predominate in scientific research since they include thoughtful planning, data collection, analysis, and reporting. Planning, designing, gathering data, analysing it, developing relevant interpretation, and publishing the research findings are all statistical processes that go into conducting a study. The statistical analysis adds sense to the meaningless data, bringing life to the dead data. Only when appropriate statistical tests are employed can the results and conclusions be made with accuracy. The goal of this essay is to familiarise the reader with the fundamental research instruments used while carrying out various investigations. An overview of the factors, knowledge of quantitative and qualitative variables, and measurements of central tendency are all covered in this paper. In addition, without statistical analysis, the study project's findings are only worthless raw data. In order to support study findings, it is therefore imperative to determine statistics. In this paper, we'll see about the benefits of utilising statistical techniques to examine biological research and how these techniques may lead to more insightful conclusions
... Whether heat stress-induced phenotypic variations or physiological response changes, are both fundamentally and primarily due to the differential alterations of thermo-sensitive genes' expressions (De Montaigu et al., 2015). Hence, RNA-seq analysis was conducted to screen the crucially differentiated genes and corresponding biological processes that drive bay scallop responses to heat stress (Zheng and Wang, 2008). Up-regulated DEGs at the acute phase (6 h, 12 h, 24 h) were similarly enriched in protein-related activity via GO analysis (Fig. 2C), demonstrating that the misfolding of polypeptides or proteins induced by heat stress would produce harmful aggregates in the body; therefore, more chaperone genes need to be transcribed to facilitate correct protein folding/refolding (Morimoto, 1993). ...
The increased frequency of marine heat waves (MHWs) caused by global climate change is predicted to threaten the survival of economic bivalves, therefore having severely adverse effects on local ecological communities and aquaculture production. However, the study of scallops facing MHWs is still scarce, particularly in the scallop Argopecten irradians irradians, which has a significant share of "blue foods" in northern China. In the present study, bay scallop heart was selected to detect its cardiac performance, oxidative impairment and dynamic molecular responses, accompanied by assessing survival variations of individuals in the simulated scenario of MWHs (32 °C) with different time points (0 h, 6 h, 12 h, 24 h, 3 d, 6 d and 10 d). Notably, cardiac indices heart rate (HR), heart amplitude (HA), rate-amplitude product (RAP) and antioxidant enzyme activities superoxide dismutase (SOD) and catalase (CAT) all peaked at 24 h but sharply dropped on 3 d, coinciding with mortality. Transcriptome analysis revealed that the heart actively defended against heat stress at the acute stage (<24 h) via energy supply, misfolded proteins correction and enhanced signal transduction, whereas regulation of the defense response and apoptotic process combined with twice transcription initiation were the dominant responses at the chronic stage (3- 10 d). In particular, HSP70 (heat shock protein 70), HSP90 and CALR (calreticulin) in the endoplasmic reticulum were identified as the hub genes (top 5 %) in the HR-associated module via WGCNA (weighted gene co-expression network analysis) trait-module analysis, followed by characterization of their family members and diverse expression patterns under heat exposure. Furthermore, RNAi-mediated knockdown of CALR expression (after 24 h) significantly weakened the thermotolerance of scallops, as evidenced by a drop of 1.31 °C in ABT (Arrhenius break temperature) between the siRNA-injected group and the control group. Our findings elucidated the dynamic molecular responses at the transcriptome level and verified the cardiac functions of CALR in bay scallops confronted with stimulated MHWs.
... Gene expression pattern clusters were evaluated via R version 3.6.1. Gene Ontology (GO) enrichment was analyzed by GOEAST tools [78]. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation clustering was performed by using DAVID [79]. ...
Flowering and bud dormancy are crucial stages in the life cycle of perennial angiosperms in temperate climates. MADS-box family genes are involved in many plant growth and development processes. Here, we identified three MADS-box genes in tea plant belonging to the FLOWERING LOCUS C (CsFLC) family. We monitored CsFLC1 transcription throughout the year and found that CsFLC1 was expressed at a higher level during the winter bud dormancy and flowering phases. To clarify the function of CsFLC1, we developed transgenic Arabidopsis thaliana plants heterologously expressing 35S::CsFLC1. These lines bolted and bloomed earlier than the WT (Col-0), and the seed germination rate was inversely proportional to the increased CsFLC1 expression level. The RNA-seq of 35S::CsFLC1 transgenic Arabidopsis showed that many genes responding to ageing, flower development and leaf senescence were affected, and phytohormone-related pathways were especially enriched. According to the results of hormone content detection and RNA transcript level analysis, CsFLC1 controls flowering time possibly by regulating SOC1, AGL42, SEP3 and AP3 and hormone signaling, accumulation and metabolism. This is the first time a study has identified FLC-like genes and characterized CsFLC1 in tea plant. Our results suggest that CsFLC1 might play dual roles in flowering and winter bud dormancy and provide new insight into the molecular mechanisms of FLC in tea plants as well as other plant species.
... and visualized by ggplot2 (version 3.3.3). GO analysis can provide scientists with the better understanding of the functional annotations of the gene products [12]. KEGG Pathway is a tool to help biologists understand the systemic functions of the cell and even the organism [13]. ...
Background
Diabetic nephropathy (DN) is the major cause of end-stage renal disease worldwide. The mechanism of tubulointerstitial lesions in DN is not fully elucidated. This article aims to identify novel genes and clarify the molecular mechanisms for the progression of DN through integrated bioinformatics approaches.
Method
We downloaded microarray datasets from Gene Expression Omnibus (GEO) database and identified the differentially expressed genes (DEGs). Enrichment analyses, construction of Protein–protein interaction (PPI) network, and visualization of the co-expressed network between mRNAs and microRNAs (miRNAs) were performed. Additionally, we validated the expression of hub genes and analyzed the Receiver Operating Characteristic (ROC) curve in another GEO dataset. Clinical analysis and ceRNA networks were further analyzed.
Results
Totally 463 DEGs were identified, and enrichment analyses demonstrated that extracellular matrix structural constituents, regulation of immune effector process, positive regulation of cytokine production, phagosome, and complement and coagulation cascades were the major enriched pathways in DN. Three hub genes (CD53, CSF2RB, and LAPTM5) were obtained, and their expression levels were validated by GEO datasets. Pearson analysis showed that these genes were negatively correlated with the glomerular filtration rate (GFR). After literature searching, the ceRNA networks among circRNAs/IncRNAs, miRNAs, and mRNAs were constructed. The predicted RNA pathway of NEAT1/XIST-hsa-miR-155-5p/hsa-miR-486-5p-CSF2RB provides an important perspective and insights into the molecular mechanism of DN.
Conclusion
In conclusion, we identified three genes, namely CD53, CSF2RB, and LAPTM5, as hub genes of tubulointerstitial lesions in DN. They may be closely related to the pathogenesis of DN and the predicted RNA regulatory pathway of NEAT1/XIST-hsa-miR-155-5p/hsa-miR-486-5p-CSF2RB presents a biomarker axis to the occurrence and development of DN.
... Gene Ontology (GO) enrichment was carried out to identify the putative functions of differential expression genes (DEGs) in each group [63], and the results were presented in Fig. 15b and c & Fig. S7 (in Support Information). Proteins encoded by these DEGs were associated with porin activity, glucosidase activity and colicin transmembrane transporter activity using SCB-hydrolysates as carbon sources (Fig. 15b, red bars). ...
Adipic acid is an important precursor for manufacturing Nylon-66, and various efficient renewable routes for adipic acid from lignocellulosic biomass are being explored. To effectively valorize biomass into adipic acid, a novel aqueous solution NaOH/ChCl:TH/water (6:24:160, wt/wt/wt) was firstly applied to pretreat sugarcane bagasse (SCB) at a room temperature (25 oC) for a short pretreatment time (1 min) for improving its saccharification efficiency. A deep eutectic solvent ChCl:TH was synthesized by mixing choline chloride (ChCl) and thiourea (TH). The cellulose structure changes of SCB were characterized by FTIR, XRD, SEM, TEM and LSCM. Composition analysis and reducing sugar yield were used to evaluate pretreatment efficiency. Hydrolysis for 72 h, the yields of reducing sugars and glucose from 40 g/L NaOH/ChCl:TH-SCB with complexed cellulases were obtained at 90.2% and 94.1%, respectively. Finally, the obtained SCB-hydrolysate was used for adipic acid production by E. coli MG1655 K12. Glucose in SCB-hydrolysate was consumed within 72 h, with a productivity of 0.39 g adipic acid/g glucose, accounting for 72.2% of the theoretical yield. Further discovery, xylose in SCB-hydrolysate was also consumed for adipic acid fermentation, which contributed to an increase in adipic acid production. In view of transcriptome data, most of the genes involved in carbohydrate metabolism were most significantly up-regulated, which was conductive to improve the yield of adipic acid using biomass-hydrolysate as carbon source. Therefore, the NaOH/ChCl:TH-SCB hydrolysates were a better carbon source for adipic acid fermentation compared to commercial glucose. Obviously, this established rapid room temperature pretreatment with NaOH/ChCl:TH was proven to be effective for enhancing saccharification efficiency of SCB, and the hydrolysates had excellent adipic acid fermentability.
... The copyright holder for this preprint this version posted September 4, 2022. ; https://doi.org/10.1101/2022.09.02.506372 doi: bioRxiv preprint was analysed by GOEAST tools (Zheng and Wang, 2008). Kyoto Encyclopedia of Genes and Genomes 2 0 3 (KEGG) functional annotation clustering was performed by using DAVID (Dennis et al., 2003). 2 0 4 2 0 5 ...
Flowering and bud dormancy are crucial stages in the life cycle of perennial angiosperms in temperate climates. MADS-box family genes are involved in many plant growth and development processes. Here, we identified 3 MADS-box genes in tea plant belonging to the FLOWERING LOCUS C ( CsFLC ) family. We monitored CsFLC1 transcription throughout the year and found that CsFLC1 was expressed at a higher level during the winter bud dormancy and flowering phases. To clarify the function of CsFLC1 , we developed transgenic Arabidopsis thaliana plants heterologously expressing 35S::CsFLC1 . These lines bolted and bloomed earlier than the WT (Col-0), and the seed germination rate was inversely proportional to the increased CsFLC1 expression level. RNA-seq of 35S::CsFLC1 transgenic Arabidopsis showed that many genes responding to ageing, flower development and leaf senescence were affected, and phytohormone-related pathways were especially enriched. According to the results of hormone content detection and RNA transcript level analysis, CsFLC1 controls flowering time possibly by regulating SOC1, AGL42, SEP3 and AP3 and hormone signalling, accumulation and metabolism. Our results suggest that CsFLC1 might play dual roles in flowering and winter bud dormancy and provide new insight into the molecular mechanisms of FLC in tea plants as well as other plant species.
Highlight
Three FLOWERING LOCUS C-like genes were identified in tea plants, among them CsFLC1 played dual roles in flowering and winter bud dormancy.
... Gene ontology (GO) enrichment analysis was performed using the functions of the hypergeometric distribution test for the calculation of GO terms described by Zheng and Wang et al. [70]. All DEGs were mapped to GO terms in the Gene Ontology database (www.geneontology.org, ...
Panicle degeneration, sometimes known as abortion, causes heavy losses in grain yield. However, the mechanism of naturally occurring panicle abortion is still elusive. In a previous study, we characterized a mutant, apical panicle abortion1331 (apa1331), exhibiting abortion in apical spikelets starting from the 6 cm stage of panicle development. In this study, we have quantified the five phytohormones, gibberellins (GA), auxins (IAA), abscisic acid (ABA), cytokinins (CTK), and brassinosteroids (BR), in the lower, middle, and upper parts of apa1331 and compared these with those exhibited in its wild type (WT). In apa331, the lower and middle parts of the panicle showed contrasting concentrations of all studied phytohormones, but highly significant changes in IAA and ABA, compared to the upper part of the panicle. A comparative transcriptome of apa1331 and WT apical spikelets was performed to explore genes causing the physiological basis of spikelet abortion. The differential expression analysis revealed a significant downregulation and upregulation of 1587 and 978 genes, respectively. Hierarchical clustering of differentially expressed genes (DEGs) revealed the correlation of gene ontology (GO) terms associated with antioxidant activity, peroxidase activity, and oxidoreductase activity. KEGG pathway analysis using parametric gene set enrichment analysis (PGSEA) revealed the downregulation of the biological processes, including cell wall polysaccharides and fatty acids derivatives, in apa1331 compared to its WT. Based on fold change (FC) value and high variation in expression during late inflorescence, early inflorescence, and antherdevelopment, we predicted a list of novel genes, which presumably can be the potential targets of inflorescence development. Our study not only provides novel insights into the role of the physiological dynamics involved in panicle abortion, but also highlights the potential targets involved in reproductive development.
... It mainly classifies genes on the basis of their essential functions to define and describe the functions of genes and proteins. The GO database divides the functions into three types: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) [49][50][51]. The KEGG database integrates genomic, chemical, and system functional information [52,53]. ...
A new Populus variety with a strong salt tolerance was obtained from cross breeding P. talassica as the female parent and P. euphratica as the male parent. In order to elucidate the molecular mechanism and find out the major differentially expressed genes of salt tolerance of P. talassica × P. euphratica, after being subjected to salt stress, at 0, 200, and 400 mmol/L NaCl, the root, stem, and leaf transcriptomes (denoted as R0, S0, and L0; R200, S200, and L200; and R400, S400, and L400, respectively) of P. talassica × P. euphratica were sequenced. In total, 41,617 differentially expressed genes (DEGs) were identified in all the comparison groups with 21,603 differentially upregulated genes and 20,014 differentially downregulated genes. Gene Ontology analysis showed that DEGs were significantly enriched in biological processes that may be involved in salt stress, such as ‘cell communication’, ‘ion transport’, ‘signaling’, and signal ‘transmission’. Kyoto Encyclopedia of Genes and Genomes analysis showed that DEGs were mainly enriched in pathways of ‘plant–pathogen interaction’, ‘carbon metabolism’, and ‘plant hormone signal transmission’. The pathways and related gene information formed a basis for future research on the mechanisms of salt stress, the development of molecular markers, and the cloning of key genes in P. talassica × P. euphratica.
... and visualized by ggplot2 (version 3.3.3). GO analysis can provide scientists with the better understanding of the functional annotations of the gene products [12]. KEGG Pathway is a tool to help biologists understand the systemic functions of the cell and even the organism [13]. ...
Background: Diabetic nephropathy (DN) is the major cause of end-stage renal disease worldwide. The mechanism of tubulointerstitial lesions in DN is not fully elucidated. This article aims to identify novel genes and clarify the molecular mechanisms for the progression of DN through integrated bioinformatics approaches.
Method: We downloaded microarray datasets from Gene Expression Omnibus (GEO) database and identified the differentially expressed genes (DEGs). Enrichment analyses, construction of Protein-protein interaction (PPI) network, and visualization of the co-expressed network between mRNAs and microRNAs (miRNAs) were performed. Additionally, we validated the expression of hub genes and analyzed the Receiver Operating Characteristic (ROC) curve in another GEO dataset. Clinical analysis and ceRNA networks were further analyzed.
Results: Totally 463 DEGs were identified, and enrichment analyses demonstrated that extracellular matrix structural constituents, regulation of immune effector process, positive regulation of cytokine production, phagosome, and complement and coagulation cascades were the major enriched pathways in DN. Three hub genes (CD53, CSF2RB, and LAPTM5) were obtained, and their expression levels were validated by GEO datasets. Pearson analysis showed that these genes were negatively correlated with the glomerular filtration rate (GFR). After literature searching, the ceRNA networks among circRNAs/IncRNAs, miRNAs, and mRNAs were constructed. The predicted RNA pathway of NEAT1/XIST-hsa-miR-155-5p/hsa-miR-486-5p-CSF2RB provides an important perspective and insights into the molecular mechanism of DN.
Conclusion: In conclusion, we identified three genes, namely CD53, CSF2RB, and LAPTM5, as hub genes of tubulointerstitial lesions in DN. They may be closely related to the pathogenesis of DN and the predicted RNA regulatory pathway of NEAT1/XIST-hsa-miR-155-5p/hsa-miR-486-5p-CSF2RB presents a biomarker axis to the occurrence and development of DN.
... Both tests are available from the Bioconductor repository and are implemented in the packages "limma" and "siggenes", respectively. According to the three methods, genes that turned out to be significant were also compared by exploiting their functional roles with a Gene Ontology (GO) enrichment analysis 16 . We obtained three separate lists of significant GO-terms from the three sets of differentially expressed genes. ...
Statistical tests of differential expression usually suffer from two problems. Firstly, their statistical power is often limited when applied to small and skewed data sets. Secondly, gene expression data are usually discretized by applying arbitrary criteria to limit the number of false positives. In this work, a new statistical test obtained from a convolution of multivariate hypergeometric distributions, the Hy-test, is proposed to address these issues. Hy-test has been carried out on transcriptomic data from breast and kidney cancer tissues, and it has been compared with other differential expression analysis methods. Hy-test allows implicit discretization of the expression profiles and is more selective in retrieving both differential expressed genes and terms of Gene Ontology. Hy-test can be adopted together with other tests to retrieve information that would remain hidden otherwise, e.g., terms of (1) cell cycle deregulation for breast cancer and (2) “programmed cell death” for kidney cancer.
... Gene ontology enrichment analysis software tools (GOEAST) [43] were used to analyze the Gene Ontology (GO) functions. Biological process, molecular function, and cellular component were used to annotate the main function of DEGs in GO enrichment analysis. ...
Background
Egg production is one of the most important economic traits in the poultry industry. The hypothalamic-pituitary–gonadal (HPG) axis plays an essential role in regulating reproductive activities. However, the key genes and regulatory pathways within the HPG axis dominating egg production performance remain largely unknown in ducks.
Results
In this study, we compared the transcriptomic profiles of the HPG-related tissues between ducks with high egg production (HEP) and low egg production (LEP) to reveal candidate genes and regulatory pathways dominating egg production. We identified 543, 759, 670, and 181 differentially expressed genes (DEGs) in the hypothalamus, pituitary, ovary stroma, and F5 follicle membrane, respectively. Gene Ontology (GO) analysis revealed that DEGs from four HPG axis-related tissues were enriched in the "cellular component" category. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the neuroactive ligand-receptor interaction pathway was significantly enriched based on DEGs commonly identified in all four HPG axis-related tissues. Gene expression profiles and Protein–Protein Interaction (PPI) network were performed to show the regulatory relationships of the DEGs identified. Five DEGs encoding secreted proteins in the hypothalamus and pituitary have interaction with DEGs encoding targeted proteins in the ovary stroma and F5 follicle membrane, implying that they were these DEGs might play similar roles in the regulation of egg production.
Conclusions
Our results revealed that neuroactive ligand-receptor interaction pathway and five key genes( VEGFC , SPARC , BMP2 , THBS1 , and ADAMTS15 ) were identified as the key signaling pathways and candidate genes within the HPG axis responsible for different egg production performance between HEP and LEP. This is the first study comparing the transcriptomic profiles of all HPG axis-related tissues in HEP and LEP using RNA-seq in ducks to the best of our knowledge. These data are helpful to enrich our understanding of the classical HPG axis regulating the egg production performance and identify candidate genes that can be used for genetic selection in ducks.
... Node-link diagrams are widely used (e.g. Biological Networks Gene Ontology (BiNGO) [20], Gene Ontology Enrichment Aanalysis Software Toolkit (GOEAST) [21], Gorilla [17], and WebGestalt [18]) when it comes to showing relationships between GO terms. However, the GO hierarchy or term-term relationships are not easily shown in such an approach. ...
Background
Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking.
Results
Monash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options.
Conclusion
MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.
... High-level analysis was performed using Ingenuity Pathway Analysis (IPA, QIAGEN Redwood City, www.qiagen.com/ingen uity) and gene ontology enrichment analysis software toolkit (GOEAST) (Zheng & Wang, 2008). The dataset was compared with in-common differentially expressed genes from a previous comparison of six models of AKI ). ...
Acute kidney injury (AKI) is a common perioperative complication that is associated with increased mortality. This study investigates the renal gene expression in male Long–Evans rats after prolonged anesthesia and surgery to detect molecular mechanisms that could predispose the kidneys to injury upon further insults. Healthy and streptozotocin diabetic rats that underwent autoregulatory investigation in an earlier study were compared to rats that were sacrificed quickly for mRNA quantification in the same study. Prolonged surgery caused massive changes in renal mRNA expression by microarray analysis, which was validated by quantitative real‐time PCR with good correlation. Furthermore, bioinformatics analysis using gene ontology and pathway analysis identified biological processes involved in immune system activation, such as immune system processes (p = 1.3 × 10−80), immune response (p = 1.3 × 10−60), and regulation of cytokine production (p = 1.7 × 10−52). PCR analysis of specific cell type markers indicated that the gene activation in kidneys was most probably macrophages, while granulocytes and T cell appeared less activated. Immunohistochemistry was used to quantify immune cell infiltration and showed no difference between groups indicating that the genetic activation depends on the activation of resident cells, or infiltration of a relatively small number of highly activated cells. In follow‐up experiments, surgery was performed on healthy rats under standard and sterile condition showing similar expression of immune cell markers, which suggests that the inflammation was indeed caused by the surgical trauma rather than by bacterial infection. In conclusion, surgical trauma is associated with rapid activation of immune cells, most likely macrophages in rat kidneys. Network of genes activated by surgery that may predispose the kidney to further damage.
... AgriGO [41], GenMAPP [42], Onto-Express [5], GoMiner [6], DAVID [8], GOstat [43], FuncAssociate [11], GOToolBox [44], FatiGO [45], GOEAST [46], ClueGO [25], FunSpec [10], GeneMerge [9], GARBAN [47], GO: TermFinder [48], WebGestalt [26], GOFFA [49], WEGO [50], GOTM [51], GSAQ [52], Pathview [53], Wholepathwayscope [54], and ShinnyGO [55] Functional class scoring Wilcoxon signed-rank test, median, sum, or mean, of the gene-level statistic(s), and max-mean statistic • No requirement of threshold/ cutoff value to divide gene space into different nonselected and selected part. ...
Over the past 10 years, gene set analysis has been the first option for studying gene expression and gene interaction for gaining insights into the fundamental dynamic biology of disease/traits. It, therefore, reduces the complexity of traditional statistical research and increases the illustrating strength of the outcomes achieved. Although approaches to gene set analysis are commonly utilized in gene expression analytics, the statistical framework and steps generally employed in these methods have not yet been thoroughly explored, restricting their usefulness. Thus, in this chapter, the authors include an outlined statistical framework and steps for the analysis of gene set used for various genome studies, ranging from microarrays, RNA sequencing, and the analysis of genomic widespread association results. The drawbacks of these approaches and strengths have also been addressed depending on their separate components such as their gene score, null hypotheses, and essential evaluation methods. The authors believe that a standardized approach for testing the methods of gene set analysis can also be used for correcting the lack of agreement on the method of preference for a specific experiment. The benchmark expression data sets will reflect actual expression data characteristics and prevent oversimplifying conclusions, such as naturally distributed data with zero or constant gene-gene correlations. In the near future, information present in this chapter will be highly useful for underlying process with any disease or trait in more comprehensive way.
... Omics analysis platforms such as Perseus (Tyanova and Cox, 2018) and Qlucore (Qlucore, 2021) offer thorough analytical and explorative features, but require users to download and install their software and is not open source. While there are many existing webbased omics tools which are able to perform individual parts of an analysis workflow (Efstathiou et al., 2017;Kuleshov et al., 2016;Luo et al., 2017;Merico et al., 2010;Perlasca et al., 2019;Schweppe et al., 2017;Zheng and Wang, 2008), many lack the ability to perform complete pipelines in fast, interactive web-environments. Reimand et al. lists the protocols and time consumption for popular enrichment software, with the time expense ranging from minutes to several hours (Reimand et al., 2019). ...
Functional analysis has become a common approach to incorporate biological knowledge into the analysis of omics data, and to explore molecular events that govern a disease state. It is though only one step in a wider analytical pipeline that typically requires use of multiple individual analysis software. There is currently a need for a well-integrated omics analysis tool that performs all the steps. The ProteoMill portal is developed as an R Shiny application and integrates all necessary steps from data-upload, converting identifiers, to quality control, differential expression and network-based functional analysis into a single fast, interactive easy to use workflow. Further, it maintains annotation data sources up to date, overcoming a common problem with use of outdated information, and seamlessly integrates multiple R-packages for an improved user-experience. The functionality provided in this software can benefit researchers by facilitating the exploratory analysis of proteomics data.
Availability:
ProteoMill is available at https://proteomill.com.
... For example, for a Gene Ontologyterm complex analysis, some visualization tools can be used: ProfCOM [29] is a unique tool with the ability to profile enrichment of not only available Gene Ontology (GO) terms but also of complex functions. GOEAST [30] is a toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. CARMAweb [31] is a tool that performs data preprocessing (background correction, quality control and normalization), detection of differentially expressed genes, cluster analysis, dimension reduction and visualization, classification, and Gene Ontology-term analysis. ...
The study of Deoxyribonucleic Acid (DNA) methylation has allowed important advances in the understanding of genetic diseases related to abnormal cell behavior. DNA methylation analysis tools have become especially relevant in recent years. However, these tools have a high computational cost and some of them require the configuration of specific hardware and software, extending the time for research and diagnosis. In previous works, we proposed some tools for DNA methylation analysis and a new tool, called HPG-DHunter, for the detection and visualization of Differentially Methylated Regions (DMRs). Even though this tool offers a user-friendly interface, its installation and maintenance requires the information technology knowledge specified above. In this paper, we propose our tool as a web-based application, which allows biomedical researchers the use of a powerful tool for methylation analysis, even for those not specialized in the management of Graphics Processing Units (GPUs) and their related software. The performance evaluation results show that this web-based version of HPG-DHunter tool improves the response time offered to the user, also offering an improved interface and higher visualization quality, while showing the same efficiency in DMR identification than the standalone version.
... Hierarchical cluster analysis of differentially expressed genes (dEGs) was performed to explore gene expression patterns. GO enrichment (30) and KEGG (31) pathway enrichment analysis of DEGs were performed respectively using R based (R 3.6.2; https://cran.r-project.org/bin/windows/base/old/3.6.2/) on the hypergeometric distribution. ...
Radiation is one of the main methods for the treatment of colorectal cancer (CRC) before or after surgery. However, radiotherapy tolerance of patients with CRC is often a major concern. Interferon regulatory factor 1 (IRF1) is a member of the IRF family and is involved in the development of multiple diseases, including tumors. The present study investigated the role of IRF1 in the development and radiation sensitivity of CRC. Immunohistochemistry was performed to examine the expression levels of IRF1 in tissue samples from patients with CRC, as well as in nude mice. MTT, 5‑ethynyl‑20‑deoxyuridine, colony formation, cell cycle alteration and apoptosis assays were performed in CRC cell lines. Western blotting and immunofluorescence were used to detect the expression levels of a series of proteins. RNA sequencing was applied to identify genes whose expression was upregulated by IRF1 overexpression. Xenograft nude mouse models and hematoxylin and eosin staining were used to validate the present findings in vivo. It was revealed that the expression levels of IRF1 were significantly lower in CRC tissues than in adjacent tissues. IRF1 upregulation inhibited cell proliferation and colony formation, caused G1 cell arrest, promoted cell apoptosis, and enhanced the sensitivity of CRC cells to X‑ray irradiation. The role of IRF1 in promoting the radiosensitivity of CRC was further demonstrated in nude mice with CRC xenografts. In addition, RNA sequencing revealed that overexpression of IRF1 in CRC cells significantly increased the expression levels of interferon‑induced protein family members interferon α inducible protein 6, interferon induced transmembrane protein 1 and interferon induced protein 35 (fold change >2.0). In summary, the present study demonstrated that the upregulation of IRF1 inhibited the progression and promoted the radiosensitivity of CRC, likely by regulating interferon‑induced proteins.
... The determination of NPs induced biologically relevant pathways, the KEGG database [27] (Kyoto Encyclopedia of Genes and Genomes) search was performed using the whole protein sequence, which was retrieved using the in-house prepared python script. Further, the GOEAST [28] (Gene Ontology Enrichment Analysis Software Toolkit) was used to calculate the over/under enrichment of Gene Ontology (GO) category. The program used the binomial based probability scoring statistics for the calculation of p-values and e-values. ...
Background
The cellular response to nanoparticles (NPs) for the mechanical clue and biochemical changes are unexplored. Here, we provide the comprehensive analysis of the Chinese Hamster Ovary (CHO-K1) cell line to study cell behaviour following the exposure of mesoporous silica nanoparticle (MSN), multiwall carbon nanotubes (MWCNTs), and zinc oxide (ZnO) NPs.
Results
Through the high-throughput proteomic study, we observed that the effect of NPs is alone not restricted to cell viability but also on cell polarisation. In the case of MSN, no drastic changes were observed in cellular morphology, but it upregulated chaperons that might prevent protein aggregation. However, MWCNT showed elongated cell appearance with numerous cytoplasmic vacuoles, and induce lamellipodia formation through actin polymerisation. The cytoskeleton remodelling was accompanied by the increased expression of Dlc-1, cofilin and Rac1 proteins. While ZnO NPs resulted in the rounded cell morphology along with nuclear abnormalities. The proteome analysis revealed that UBXN11 control cell roundness and DOCK3 leads to actin stress fibre formation and finally, loss of cell adhesion. It enhances the expression of catastrophic DNA damage and apoptotic proteins, which was unrecoverable even after 72 h, as confirmed by the colony formation assay. All three NPs trigger over-expression of the endocytic pathway, ubiquitination, and proteasomal complex proteins. The data indicate that ZnO and MSN entered into the cells through clathrin-mediated pathways; whereas, MWCNT invades through ER-mediated phagocytosis.
Conclusions
Based on the incubation and concentration of NPs, our work provides evidence for the activation of Rac-Rho signalling pathway to alter cytoskeleton dynamics. Our results assist as a sensitive early molecular readout for nanosafety assessment.
... form biological roles related to fruit drop. Therefore, we performed Gene Ontology (GO) enrichment analysis to investigate the functions of the differentially induced/repressed genes using agriGO, GOEAST and ggplot2 [38][39][40] . Given the amount of stage-specific DEGs expressed at 17 DAF, we performed GO enrichment analysis of normal-abnormal differentially regulated genes at 17 DAF. ...
Almond is one of the most featured nut crops owing to its high nutritional value. However, due to three different waves of flower and fruitlet drop, fruit drop is a major concern for growers. In this study, we carried out a time-course transcriptome analysis to investigate gene expression differences between normal and abnormal fruitlet development. By de novo assembly analysis, we identified 33,577 unigenes and provided their functional annotations. In total, we identified 7,469 differentially expressed genes and observed the most apparent difference between normal and abnormal fruits at 12 and 17 days after flowering. Their biological functions were enriched in carbon metabolism, carbon fixation in photosynthetic organisms and plant hormone signal transduction. RT-qPCR validated the expression pattern of 14 representative genes, including glycosyltransferase like family 2 , MYB39 , IAA13 , gibberellin-regulated protein 11-like and POD44 , which confirmed the reliability of our transcriptome data. This study provides an insight into the association between abnormal fruit development and carbohydrate signaling from the early developmental stages and could be served as useful information for understanding the regulatory mechanisms related to almond fruit drop.
... 2.6. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses GO enrichment analysis was performed using agriGO, GOEAST and ggplot2 based on the hyper geometric test [31][32][33]. KEGG pathway analysis was conducted using clusterProfiler [34]. ...
The diploid wild goat grass Aegilops tauschii (Ae. tauschii, 2n = 14; DD), as the D-sub genome of common wheat, provides rich germplasm resources for many aspects of wheat breeding. Abscisic acid (ABA) is an essential phytohormone that plays a pivotal role in plant adaptation to abiotic stresses. However, the gene regulation network of Ae. tauschii in response to ABA stress remains unclear. Here, we conducted a time-course strand-specific RNA-sequencing study to globally profile the transcriptome that responded to ABA treatment in Ae. tauschii. We identified 4818 differentially expressed transcription units/genes with time-point-specific induction/repression patterns. Using functional annotation, one-to-one ortholog and comparative transcriptome profiling analyses, we identified 319 ABA-responsive Ae. tauschii orthologs that were also induced/repressed under ABA treatment in hexaploid wheat. On the quantitative trait loci (QTL) used in wheat marker-assisted breeding, we found that the ABA-responsive expression patterns of eight Ae. tauschii orthologs were associated with drought stress tolerance, flowering process and/or grain quality. Of them, the ABA-responsive gene encoding sucrose:sucrose 1-fructosyltransferase in fructan and glucose metabolism pathways showed the most significant association with wheat drought tolerance. The characterization of ABA early-responsive genes in this study provides valuable information for exploring the molecular functions of the regulatory genes and will assist in wheat breeding.
... We refer to this issue as gene set selection bias. While there was a tremendous amount of research into making evermore advanced methods and accessible web-based tools (Subramanian et al., 2005;Backes et al., 2007;Zheng and Wang, 2008;Eden et al., 2009;Wu et al., 2010), there is always an implicit assumption that end-users use a large gene expression profiling platform in experiments. In light of this, there is a need to develop a GST methodology which can produce interpretable gene set enrichment analysis results in the presence of gene set selection bias. ...
Motivation: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are important tools in Gene Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene set selection bias induced during the construction of these platforms.
Results: We propose bcGST, a bias-corrected Gene Set Test by introducing bias correction terms in the contingency table needed for calculating the Fisher’s Exact Test (FET). The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and TCGA cancer studies.
Availability: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/
Contact: kevin.wang@sydney.edu.au
... Lastly, we applied gene-set enrichment analysis to identify overrepresented gene ontology (GO) terms in the two sets of RNA-Seq genes in Tables V and VI. Specifically, we used the gene-batch tool in GOEAST (Gene Ontology Enrichment Analysis Software Toolkit) [35] to identify significantly overrepresented Biological Processes GO terms for the two sets of RNA-Seq genes. We also used the Multi-GOEAST tool to compare the results of the enrichment analysis of these two sets. ...
Recent technological advances in high-throughput omics technologies and their applications in genomic medicine have opened up outstanding opportunities for individualized medicine. However, several challenges arise in the integrative analysis of such data including heterogeneity and high dimensionality of the omics data. In this study, we present a novel multi-view feature selection algorithm based on the well-known canonical correlation analysis (CCA) statistical method for jointly selecting discriminative features from multi-omics data sources (multi-views). Our results demonstrate that models for predicting kidney renal clear cell carcinoma (KIRC) survival using our proposed method for jointly selecting discriminative features from copy number alteration (CNA), gene expression RNA-Seq, and reverse-phase protein arrays (RPPA) views outperform models trained using single-view data as well as three integrated models developed using data fusion approaches including CCA-based feature fusion.
... In order to obtain complete and effective annotation of functional genetic information, different annotation databases were used to analyze the RNA-seq data Zheng and Wang, 2008;Ma et al., 2020). Different annotation databases revealed clear differences between the enrichment and annotation information, and GO is the most widely and commonly used among them (Bauer et al., 2008;Eden et al., 2009;Zheng et al., 2019). ...
The great northern snakehead (Channa argus) is one of the most important economic and conservational fish in China. In this study, the melanocytes in the skin of two distinct color morphs C. argus were investigated and compared through employment of the microscopic analysis, hematoxylin and eosin (H&E) and Masson Fontana staining. Our results demonstrated the uneven distribution of melanocytes with extremely low density and most of them were in the state of aging or death. Meanwhile, there was no obvious pigment layer and melanocytes distribution pattern found in the albino-type (AT), while the melanocytes were evenly distributed with abundance in the bicolor-type (BT). The transcriptome analysis through Illumina HiSeq sequencing showed that a total of 34.93 Gb Clean Data was obtained, and Q30 base percentage reached 92.66%. The BT and AT northern snakeheads transcriptome data included a total of 56,039,701 and 60,410,063 clean reads (n = 3), respectively. In gene expression analyses, the sample correlation coefficients (r) were ranged between 0.92 and 1.00; the contribution of PC1 and PC2 were 50.25 and 13.73% by using PCA cluster analysis, the total number of DEGs were 1024 (559 up-regulated and 465 down-regulated), and the number of annotated DEGs was 767 (COG 172, KEGG 262, GO 288, SwissProt 548, Pfam 579 and NR 765). Additionally, 46,363 ± 873 and 44,947 ± 392 single nucleotide polymorphisms (SNPs) were compiled via genetic structure analysis, respectively. Ten key pigment-related genes were screened using qRT-PCR. And all of them revealed extremely higher expression levels in the skin of BT than those of AT. This is the first study to analyze the mechanism of albino characteristics of Channa via histology and transcriptomics, and also provide the oretical and practical support for the protection and development of germplasm resources for C. argus.
... The GO annotations were functionally classified by GOEAST web-based software (http://omicslab.genetics.ac.cn/GOEAST/index.php) (Zheng and Wang, 2008) for gene function distributions and the GO terms with a corrected P -value < 0.05 were considered significantly enriched by the differentially expressed genes. KOBAS 3.0 software was used to screen out the differentially expressed immune genes statistically enriched (P < 0.05) in KEGG immune pathways (Xie et al., 2011). ...
The bivalve mollusk, Pinctada fucata is renowned worldwide for its ability of producing high quality spherical pearl and accounts for more than 90% of seawater pearl production. Pearls are the result of mollusk’s capability to produce calcified shell materials in response to an injury to the mantle tissue. Mollusk shell is mainly composed of calcium carbonate (CaCO3) crystals (>90% w/w) surrounded by an organic matrix (0.01% to 5% w/w) of proteins, lipids and polysaccharides. As in shell biomineralization, pearl formation is also regulated by the extracellular organic matrix secreted by the mantle tissue of mollusk.
Mantle grafting is the commonly practiced method for producing spherical pearls. The process involves a surgical implantation where a small piece (3 × 3 mm) of mantle tissue is excised from a suitable donor oyster and then implanted into the gonad of a host oyster along with an inorganic nucleus. Once transplanted, the outer epithelial cells of the graft start to proliferate and differentiate to give rise a monolayer of the secretory epithelium around the nucleus termed as ‘pearl sac’. The newly formed pearl sac gradually secretes various matrix proteins onto the nucleus in order to produce a lustrous pearl. Therefore, it is very reasonable to claim that pearl sac formation is the critical step of pearl culture which eventually determines the success of culture.
Under normal condition, outer epithelium of the mantle is a stable and mitotically inactive tissue, whereas the inner epithelial cells, contrarily, proliferate intermittently for the renewal of the tissue. Upon a mantle injury, the outer epithelial cells multiply actively to regenerate the injured site. The pearl sac formation simply resembles the wound healing process that occurs after a mantle injury. During mantle grafting, the external epithelial cells of the graft become active soon after surgical implantation and start to proliferate into a pearl sac. Other components of the graft, such as inner epithelial cells, muscle fibres and connective tissues eventually disappear. It is assumed that the outer epithelium contains proliferating stem cells, but the feature of those cells is unclear. So, identification of genes involved in epithelial cell proliferation and differentiation is of utmost important to understand the mechanisms of pearl formation.
Shell or pearl biomineralization is a highly controlled biological process regulated by the cascades of a substantial number of genes. Though the mechanism of pearl formation has been studied largely, but the complex physiological process by which pearl sac and pearl is formed has not been properly understood yet. Using an RNAseq approach, here, we aimed to reveal the genes involved in the development of pearl sac and pearl, and the sequential expression patterns of different shell matrix proteins (SMPs) secreted from the pearl sac during different stages of pearl formation. We also examined the pearl layers to scrutinize the microstructural characterization of the surface depositions on pearls. In the last part of the study, we tried to establish a suitable method of gene editing in P. fucata using CRISPR/Cas9 system.
1. Genes expressed during the proliferation of mantle epithelial cells into pearl sac
To describe the genes engaged in pearl sac formation, we performed RNA sequencing of mantle graft and the later pearl sac at different stages of pearl formation. During grafting experiments for three months, we collected nine samples: donor mantle epithelial cells, donor mantle pallium, donor mantle pallium on grafting, and mantle pallium each from the host at 24 hours, 48 hours, 1 week, 2 weeks, 1 months and 3 months post grafting. In the wound healing process, pearl sac was developed by two weeks of culture as indicated by the up-regulated Gene Ontology (GO) terms relevant to epithelial cell proliferation and differentiation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that immune genes were highly expressed (P < 0.05) between 0 h – 24 h in a donor dependent-manner and 48 h – 1 w in a host dependent-manner.
We screened out a number of genes including JAG1, RFX3, STRC, FGFR2, SAV1, RAC1, DMD, RGMA, PTK7, MAF, MEF2A, SFRP5, TGM1, FZD1, GRHL2, TEAD1, PRKDC, LAMC1, EGFR, CASP8, CDC42, RSPO2, MTSS1, MATN1, SULF1, SPG20 and LRP6 that may be involved in the proliferation and differentiation of mantle epithelial cells into pearl sac. Furthermore, it is the first time that we identified some stem cell marker genes including ABCG2, SOX2, MEF2A, HES1, MET, NRP1, ESR1, STAT6, PAX2, FZD1 and PROM1 that were expressed differentially during pearl sac development. RT-PCR data showed ubiquitous expression of these stem cell marker genes in P. fucata, which further proposed their cell proliferation-related functions in different tissues. Additionally, qPCR results demonstrated that all these genes were highly expressed in mantle tissue, suggesting their potential role in the proliferation of the mantle epithelium into pearl sac. Furthermore, PAX2 and FZD1 were expressed higher in mantle compared to other tissues such as gonad and muscle.
2. Gene expression profiles at different stages of pearl formation during 3 months pearl culture
More than 200 molluscan biomineralization-related genes that contribute to the formation of shell and pearl have been identified till date. In this study, we screened out 192 genes likely involved in pearl biomineralization by blast search against a list of reference biomineralization genes prepared beforehand. It has been clearly defined that, the biomineralization genes are being secreted by the pearl sac developed from donor mantle graft, not by the host gonad tissue. So, the identified biomineralization-related genes in our study were expressed in the pearl sac, i.e., in the donor mantle epithelium.
Though the mantle tissue is primarily responsible for shell/pearl biomineralization, recent studies have also been reported that oyster hemocytes can mediate shell biomineralization by secreting and transporting CaCO3 crystals to the site of mineralization. Therefore, the interaction observed between donor mantle graft and surrounding host hemocytes immediately after grafting is very essential for the proper development of pearl sac and pearl.
Principal component analysis (PCA) precisely elucidates that the mineralization process during the first 3 months of culture is regulated differently. Further hierarchical clustering of 192 biomineralization-related genes showed clearly different expression profiles between the earlier (before 1 week) and later stages (1 week to 3 months) of pearl grafting. Detailed expression analysis of the major SMPs demonstrated that most of the prismatic layer forming SMPs were first up-regulated and then gradually down-regulated, indicating their involvement in the development of pearl sac and the onset of pearl mineralization. Most of the nacreous layer forming SMPs were up-regulated after the formation of pearl sac with the highest expression at 1 month, suggesting the completion of the nacreous layer formation. Nacrein, MSI7 and shematrin involved in both layer formation were highly expressed during 0 h – 24 h, down-regulated up to 1 week and then up-regulated again after maturation of pearl sac. Actually, these SMPs control and mediate the CaCO3 crystal formation. However, the genes highly expressed in the pearl sac may not be highly expressed in the mantle pallium. Therefore, the expression profiling of the SMPs can be used as a marker of the shell and pearl formation.
3. Microstructural characterization of pearl layers recapitulates the mineralization sequence of pearl
Clear morphological differences were observed among the pearls obtained at 1 month and 3 months of culture. Surface examination of 1 month pearls revealed the variation in the initial mineralization among the pearls. Moreover, the nacre deposition at the early stage of pearl formation was not uniform throughout the surroundings of a given pearl. But at 3 months, the pearl surface became smoother and more regular with a pearl luster.
Scanning electron microscopy (SEM) demonstrated that an initial organic layer was deposited onto the nucleus surface before the secretion of prismatic and nacreous layers. But, the thickness of the organic material layer was variable among different pearls and even in different parts of the same pearl. Thus the initial mineralization of pearl is not simply the reappearance of the nacreous structures, rather it is more complex. The metabolic changes that occur in the mantle epithelial cells during its differentiation into a pearl sac may result in the formation of a new mineralizing sequence that is comparable to the structure of the shell. However, the prismatic layer of pearl is more diversified compared to the regular brick-wall like structures of nacre that develops later on it. Unlike the canonical mollusk shell, prismatic layer in pearl was composed of both aragonite and calcite prisms, organic materials and some unknown compounds.
The study recapitulates the mineralization sequence of pearl, where a heterogeneous prismatic layer is secreted first and followed by nacreous layer. Additionally, SEM imaging confirmed the deposition of nacreous layer around the nucleus by 1 month that we predicted from our gene expression study.
4. CRISPR/Cas9 mediated gene editing in P. fucata
We tried to establish a suitable method of gene editing in pearl oyster using high-throughput CRISPR/Cas9 system. Here, we showed that direct injection of Cas9 protein and appropriate sgRNA into the adductor muscle of adult oyster can induce noticeable mutation in desired gene. DNA sequencing results from two representative mutants indicated a large deletion (45 bp) on the targeted gene, nacrein. We got 3 mutant oysters among 4 injected with sgRNA-Cas9 complex. The notable success rate suggests that, this tool can function in pearl oyster in vivo through a simple but efficient approach of direct injection.
This is the first and a preliminary trial of CRISPR-mediated gene alteration in bivalve mollusk. Therefore, further study is needed to make the method more appropriate.
Conclusion
The findings of the present study conclude two consecutive stages during the 3 months pearl culture. One is the initiation of pearl sac formation as part of the wound healing process in response to the oyster defense mechanism (before 1 week post grafting). Another is the maturation of pearl sac and deposition of organic matrices on the bare nucleus (2 week to 3 months). We figured out the key genes including some stem cell marker genes engaged in proliferation and differentiation of mantle epithelial cells into pearl sac. We also described the notable immune genes and pathways that provide insight into the increased understanding of the host immune reaction in response to accepting a graft.
The expression pattern of the key genes involved in the development of pearl sac and pearl elucidated that immune and cell proliferation related-genes were mostly enriched during earlier stages (before 2 weeks), whereas biomineralization genes were expressed in later stages (2 weeks to 3 months) of pearl grafting. The expression profiling of 192 biomineralization genes indicates that first 3 months of pearl biogenesis are very crucial when the pearl sac forms and secretes significant amount of nacre for making a lustrous pearl. Microstructural characterization of pearls explains the order of mineralization where a periostracum-like layer is secreted first before the deposition of the heterogeneous prismatic layer and the outermost nacreous layer onto the nucleus. CRISPR/Cas9 mediated gene editing suggests that it can be a simple but efficient tool for gene editing in pearl oyster towards improving the quality of cultured pearl.
The improved understanding of the molecular mechanisms underlying the formation of pearl sac and pearl obtained from this study will provide a basis for future research towards upgrading the pearl culture practice and pearl quality. The study also gives some valuable information for identifying the functional genes implicated for pearl sac formation. However, further functional analyses are needed to verify the functions of the identified stem cell marker genes in pearl sac development.
... Then they determine significance of the overlaps via statistical tests such as Fisher's exact test. Many tools are based on this method including Onto-Express (Draghici et al., 2003;Khatri et al., 2002), Fisher (Khatri, Sirota & Butte, 2012), and the Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) (Zheng & Wang, 2008). However, ORA-based methods only take into account large changes in individual genes that significantly affect pathways and they do not account for smaller changes in sets of functionally-related genes (i.e., pathways) capable of significant effects. ...
Background
Signaling pathway analysis methods are commonly used to explain biological behaviors of disease cells. Effector genes typically decide functional attributes (associated with biological behaviors of disease cells) by abnormal signals they received. The signals that the effector genes receive can be quite different in normal vs. disease conditions. However, most of current signaling pathway analysis methods do not take these signal variations into consideration.
Methods
In this study, we developed a novel signaling pathway analysis method called signaling pathway functional attributes analysis (SPFA) method. This method analyzes the signal variations that effector genes received between two conditions (normal and disease) in different signaling pathways.
Results
We compared the SPFA method to seven other methods across 33 Gene Expression Omnibus datasets using three measurements: the median rank of target pathways, the median p -value of target pathways, and the percentages of significant pathways. The results confirmed that SPFA was the top-ranking method in terms of median rank of target pathways and the fourth best method in terms of median p -value of target pathways. SPFA’s percentage of significant pathways was modest, indicating a good false positive rate and false negative rate. Overall, SPFA was comparable to the other methods. Our results also suggested that the signal variations calculated by SPFA could help identify abnormal functional attributes and parts of pathways. The SPFA R code and functions can be accessed at https://github.com/ZhenshenBao/SPFA .
... Initial methods include technologies based on overexpression analysis (ORA) and functional class scoring (FCS) [4]. ORA methods focus on the fraction of genes in signaling pathways found in the set of genes showing changes in expression, such as Onto-Express [5], Fisher [4], and GOEAST [6]. ORA methods are always based on the principles of statistics. ...
Signaling pathway analysis has become a routine task after differentially expressed gene (DEG) studies across disease conditions, drug treatments, or developmental stages. A signaling pathway can be represented by a graph that consists of Genes and interactions (the genetic regulation) between them. However, existing signaling pathway analysis methods ignore the strength variations of interactions in signaling pathways under different conditions. Here, we developed a novel method named SPACI (Signaling Pathway Analysis Combined with the strength variations of Interactions between genes in signaling pathways under different conditions) to improve signaling pathway analysis after DEG studies. To further evaluate the performance of SPACI, we compared SPACI with nine other methods by using a benchmark of 28 gene expression datasets in two standard measures: sensitivity and prioritization. The False positive rate (FPR) of SPACI was also compared with five methods. The results show that SPACI is the second-ranked method in terms of prioritization and the third-ranked method in terms of sensitivity. SPACI is the top method when compared in terms of the sum value of the two ranks. Also, the FPR of SPACI is modest compared with the classic methods. Furthermore, the strength variation of the interaction is demonstrated as coherent with the biological problem. The interactions with high strength variations under different conditions can help improve the discovery of the underlying biological information. The R package of SPACI can be accessed at https://github.com/ZhenshenBao/SPACI.
... The functional analysis usually refers to GO enrichment, KEGG pathway, function association to diseases, etc. DIANA-miRPath [10] is such a tool for functional analysis. The available tools for GO term enrichment include GoMiner [11], FatiGO [12], BiNGO [13], GOAT [14], DAVID [15], CytoScape plug-in BiNGO [13], GOLEM [16], GOEAST [17], and GOTM [18], GSEA [19], FatiScan [20], GO-stat [21], GeneTrail [22], and iGA [23]. ...
Background:
Although there are many studies on the characteristics of miRNA-mRNA interactions using miRNA and mRNA sequencing data, the complexity of the change of the correlation coefficients and expression values of the miRNA-mRNA pairs between tumor and normal samples is still not resolved, and this hinders the potential clinical applications. There is an urgent need to develop innovative methodologies and tools that can characterize and visualize functional consequences of cancer risk gene and miRNA pairs while analyzing the tumor and normal samples simultaneously.
Results:
We developed an innovative bioinformatics tool for visualizing functional annotation of miRNA-mRNA pairs in a network, known as MMiRNA-Viewer2. The tool takes mRNA and miRNA interaction pairs and visualizes mRNA and miRNA regulation network. Moreover, our MMiRNA-Viewer2 web server integrates and displays the mRNA and miRNA gene annotation information, signaling cascade pathways and direct cancer association between miRNAs and mRNAs. Functional annotation and gene regulatory information can be directly retrieved from our web server, which can help users quickly identify significant interaction sub-network and report possible disease or cancer association. The tool can identify pivotal miRNAs or mRNAs that contribute to the complexity of cancer, while engaging modern next-generation sequencing technology to analyze the tumor and normal samples concurrently. We compared our tools with other visualization tools.
Conclusion:
Our MMiRNA-Viewer2 serves as a multitasking platform in which users can identify significant interaction clusters and retrieve functional and cancer-associated information for miRNA-mRNA pairs between tumor and normal samples. Our tool is applicable across a range of diseases and cancers and has advantages over existing tools.
... The draft genome sequence of P. thermoglucosidasius DSM 6285 was annotated using gene ontology (GO) and KEGG orthologues obtained from UniProt [28] and using BlastKOALA [29]. GOEAST [71] and Pathview Web [72] were used to predict the functions of overexpressed transcripts. MDS plots and heat maps were generated using edgeR [69] and PAST [73], respectively. ...
Parageobacillus thermoglucosidasius is a metabolically versatile, facultatively anaerobic thermophile belonging to the family Bacillaceae. Previous studies have shown that this bacterium harbours co-localised genes coding for a carbon monoxide (CO) dehydrogenase (CODH) and Ni-Fe hydrogenase (Phc) complex and oxidises CO and produces hydrogen (H2) gas via the water-gas shift (WGS) reaction. To elucidate the genetic events culminating in the WGS reaction, P. thermoglucosidasius DSM 6285 was cultivated under an initial gas atmosphere of 50% CO and 50% air and total RNA was extracted at ~8 (aerobic phase), 20 (anaerobic phase), 27 and 44 (early and late hydrogenogenic phases) hours post inoculation. The rRNA-depleted fraction was sequenced using Illumina NextSeq, v2.5, 1x75bp chemistry. Differential expression revealed that at 8 vs.. 20, 20 vs.. 27 and 27 vs.. 44 h post inoculation, 2190, 2118 and 231 transcripts were differentially (FDR < 0.05) expressed. Cluster analysis revealed 26 distinct gene expression trajectories across the four time points. Of these, two similar clusters, showing overexpression at 20 relative to 8 h and depletion at 27 and 44 h, harboured the CODH and Phc transcripts, suggesting possible regulation by O2. The transition between aerobic respiration and anaerobic growth was marked by initial metabolic deterioration, as reflected by up-regulation of transcripts linked to sporulation and down-regulation of transcripts linked to flagellar assembly and metabolism. However, the transcriptome and growth profiles revealed the reversal of this trend during the hydrogenogenic phase.
هدفت الدراسة إلى التعرف علي أثر تفاعل مهام الويب القائمة على سقالات التعلم والتوجهات الدافعية على التفكير التفاعلي والتحصيل في مقرر الاحصاء لدى طلاب الجامعة، ولتحقيق الهدف استخدمت الباحثة المنهج شبه التجريبي وتكونت من (299) طالباً من طلاب كلية التربية جامعة قناة السويس، اعتمدت الباحثة منهم (171) لحساب الخصائص السيكومترية لمقياس التفكير التفاعلي، (128) لحساب الخصائص السيكومترية للاختبار التحصيلي، تكونت عينة الدراسة الأساسية من (72) طالب وطالبة وهي التي تم تطبيق البرنامج عليها، وتم تطبيق عليهم مقياس التوجهات الدافعية وتقسيمهم إلى (داخلية، خارجية)، وقد استخدمت الباحثة الأدوات التالية اختبار تحصيلي في ماده الإحصاء الاستدلالي، اختبار تحصيلي في ماده الإحصاء الاستدلالي (مكافئ)، ومهام الويب القائمة على سقالات التعلم (فيديو وصورة)، ومهام الويب القائمة على سقالات التعلم (نص)، ومقاييس للتفكير التفاعلي، وجميعهم من إعداد الباحثة أما مقياس التوجهات الدافعية (إعداد Cain (2008) تعريب السيد أبو هاشم(2010)، وقد أسفرت الدراسة عن النتائج التالية:
1- يوجد فروق ذات دلاله إحصائية بين متوسطي درجات التفكير التفاعلي ترجع للاختلاف في نمط مهام الويب القائمة على سقالات التعلم لصالح المجموعة التي استخدمت الفيديو.
2- يوجد فروق ذات دلاله إحصائيا بين متوسطي درجات التحصيل ترجع للاختلاف في نمط مهام الويب القائمة على سقالات التعلم لصالح المجموعة التي استخدمت الفيديو.
3- لا يوجد فروق ذات دلاله إحصائية بين متوسطي درجات التفكير التفاعلي ترجع للاختلاف في التوجهات الدافعية (داخلية-خارجية).
4- لا يوجد فروق ذات دلاله إحصائية بين متوسطي درجات التحصيل ترجع للاختلاف في التوجهات الدافعية(داخلية-خارجية).
5- يوجد فروق ذات دلاله احصائية بين متوسطي درجات التفكير التفاعلي ترجع تفاعل مهام الويب القائمة على سقالات التعلم والتوجهات الدافعية التعلم لصالح المجموعات التي استخدمت الفيديو.
6- يوجد فروق ذات دلاله احصائية بين متوسطي درجات التحصيل ترجع تفاعل مهام الويب القائمة على سقالات التعلم والتوجهات الدافعية التعلم لصالح المجموعات التي استخدمت الفيديو.
7- يوجد فروق ذات دلاله إحصائية بين متوسطي درجات التفكير التفاعلي والتحصيل ترجع للتفاعل بين مهام الويب والتوجهات الدافعية التعلم لصالح المجموعة التي استخدمت الفيديو.
بناء على النتائج التي خلصت الدراسة إليها، تقدم الدراسة عدة توصيات منها تدريب القائمين بتدريس مقررات الإحصاء على توظيف مهام الويب لتدريس المهارات الإحصائية لسنوات دراسية مختلفة، التوعية بأهمية استخدام الاساليب التكنولوجية .
الكلمات المفتاحية : مهام الويب- سقالات التعلم – التوجهات الدافعية – التحصيل في الاحصاء- التفكير التفاعلي – طلاب الجامعة.
The current study aimed at identifying the impact of the interaction of web quest based on learning scaffolds and motivational Orientations on the interactive thinking and achievement in the Statistical course for university students. For achieving this aim, the researcher used the quasi-experimental design. The sample consisted of (299) students from the Faculty of Education of Suez Canal University, the researcher adopted (n=171) to measure the psychometric characteristics of the Interactive Thinking Scale, and (n=128) to measure the psychometric characteristics of the Achievement Test. an experimental group (n=72 students) which took the intervention.Then, the motivational orientations scale was applied on them as well as divided into (internal, external). Moreover, the researcher used these instruments: Achievement test in Interference Statistics course, and equivalent Achievement test in Interference Statistics course, Web Quest Based on Learning Scaffolds (video, picture), Web Quest Based on Learning Scaffolds (text), and Interactive Thinking Scales, all of them were developed by the researcher except Motivational Orientations scale which was developed by Can (2008) and is translated by Elsayed Abo-Hashem (2010). This study revealed the following results:
1. There are statistically significant differences between the mean score of interactive thinking because of the difference in the pattern of the web quest based on learning scaffolds for the benefit of the group that used the video.
2. There are statistically significant differences between the mean achievement scores because of the difference in the pattern of the web quest based on learning scaffolds for the benefit of the group that used the video.
3. There are not statistically significant differences between the mean score of interactive thinking because of the differences in motivational orientations (internal, external).
4. There are not statistically significant differences between the mean score of achievement because of differences in motivational orientations (internal, external).
5. There are statistically significant differences between the mean score of interactive thinking because of the interaction of web quest based on learning scaffolds and motivational orientations for the benefit of the group that used the video.
6. There are statistically significant differences between the mean score of achievement as a result of the interaction of web quest based on learning scaffolds and motivational orientations For the benefit of the group that used the video.
7. There are statistically significant differences between the average degrees of interactive thinking and achievement as a result of the interaction of web quest based on learning scaffolds and motivational orientations For the benefit of the group that used the video.
Key Words: Web Quest , Learning Scaffolds , Motivational Orientations , Interactive Thinking , Achievement in the Statistics Course, University Students
Population transcriptomics aims at capturing variations in genome-wide expression that may reflect differences in selective pressures applying to the transcriptomes of different populations or sexes, and may therefore underlie ecological adaptation. To better understand the mechanisms of local adaptation, I re-analyzed previously published whole transcriptome sequencing data (RNA-seq) from brains and Malpighian tubules of an ancestral (African) and a derived (European) population of Drosophila melanogaster. I identified genes that differed in expression between populations or sexes as good candidates for adaptive regulatory evolution and related them to relevant eco-physiological functions. I analyzed the chromosomal distribution of these genes, showing a possible involvement of X-linked processes in shaping transcriptome evolution. Combined with further functional studies and analyses of DNA sequence data, these results will help to unravel the molecular mechanisms of regulatory adaptation.
In the era of next-generation sequencing, high-throughput sequencing technologies are being continuously exploited to produce a massive amount of uncharacterized and novel sequencing data. Manual annotation of such data is a complex, time-consuming, and laborious task that can only be performed by experienced biocurators. Thus computational methods are evolving from time to time to act as the best alternative approach without any substantial drop in the quality of annotation. Based on this, some software has been developed for automatic Gene Ontology (GO) term assignment. In this chapter, we will discuss the GO-based annotation, their types, software developed for the annotation purpose, and their application in establishing the structural–functional relationship.
The pathogenesis of Cystic Fibrosis (CF) airway disease is not well understood. CF is an autosomal recessive monogenic genetic disease. It affects the exocrine glands, which normally produce thin secretions such as mucus, sweat and tears. In CF, the mucus is thick and sticky which interferes with certain normal organs. A broad knowledge of the genes which are involved in the regulation or co-regulation of affected organs in the CF is required to get a better understanding of its pathophysiological mechanisms. DNA microarray approaches have made it possible to get an insight on gene expression across the genome. In the current study, microarray data related to CF and CF-associated affected organs were retrieved from the NCBS Gene Expression Omnibus database and were subjected to gene regulatory network analysis. We constructed two separated networks of up and down regulated genes from six microarray datasets. The power-law obeying topological properties showed scale-free hierarchical nature of the both networks. Density and compactness of both networks at each level was calculated by modularity and Hamiltonian energy. From all the leading hubs we found four key genes namely GSTT1, ANKRD7, PBX1, and TGFB2 deeply rooted in up and down regulated networks respectively. Conclusively these genes may have prognostic significance.
The acclimation mechanism of Chlamydomonas reinhardtii to nitric oxide (NO) was studied by exposure to S -nitroso- N -acetylpenicillamine (SNAP), a NO donor. Treatment with 0.1 or 0.3 mM SNAP transiently inhibited photosynthesis within 1 h, followed by a recovery without growth impairment, while 1.0 mM SNAP treatment caused irreversible photosynthesis inhibition and mortality. The SNAP effects are avoided in the presence of the NO scavenger, 2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-l-oxyl-3-oxide (cPTIO). RNA-seq, qPCR, and biochemical analyses were conducted to decode the metabolic shifts under sub-lethal NO stress by exposure to 0.3 mM SNAP in the presence or absence of 0.4 mM cPTIO. These findings revealed that the acclimation to NO stress comprises a temporally orchestrated implementation of metabolic processes: 1. trigger of NO scavenging elements to reduce NO level; 2. prevention of photo-oxidative risk through photosynthesis inhibition and antioxidant defense system induction; 3. acclimation to nitrogen and sulfur shortage; 4. degradation of damaged proteins through protein trafficking machinery (ubiquitin, SNARE, and autophagy) and molecular chaperone system for dynamic regulation of protein homeostasis. NO increased NADPH oxidase activity and respiratory burst oxidase-like 2 (RBOL2) transcript abundance, which were not observed in the rbol2 insertion mutant. Changes in gene expression in the rbol2 mutant and increased mortality under NO stress demonstrate that NADPH oxidase (RBOL2) is involved in the modulation of some acclimation processes (NO scavenging, antioxidant defense system, autophagy, and heat shock proteins) for Chlamydomonas to cope with NO stress. Our findings provide insight into the molecular events underlying acclimation mechanisms in Chlamydomonas to sub-lethal NO stress.
One-sentence Summary
Acclimation machinery is triggered in Chlamydomonas reinhardtii cells against sub-lethal nitric oxide stress.
The fruit trichomes of Cucurbitaceae are considered the market preference among many Asian countries and have been a key determinant of cucumber cultivar selection for commercial production and breeding. However, our understanding of the initiation and development processes of cucumber trichomes is still limited. Here, we found that the cucumber TINY BRANCHED HAIR (TBH) gene was preferentially expressed in multicellular trichomes. Overexpressing CsTBH in tbh mutants restored the trichome phenotype and increased the percentage of female flowers, whereas silencing CsTBH in wild-type plants resulted in stunted trichomes with a lower rate of female flowers. Furthermore, we provided evidence that CsTBH can directly bind to the promoters of cucumber 1-Aminocyclopropane-1-Carboxylate Synthase (CsACS) genes and regulate their expression, which affects multicellular trichome development, ethylene accumulation and sex expression. Two cucumber acs mutants with different trichome morphology and sex morphs compared with their near-isogenic line further supports our findings. Collectively, our study provides new information on the molecular mechanism of CsTBH in regulating multicellular trichome development and sex expression through an ethylene pathway.
Toxicogenomics is an emerging field defined by the adaptation and application of functional genomics techniques to toxicology. Recent advances in generating and analyzing multi-omics data have facilitated the development of toxicogenomics to provide novel answers to many toxicology-related questions. In this chapter, we discuss five recent toxicogenomics studies presenting complementary strategies for mining genome-wide molecular profiling data after exposure of cells to chemicals in vitro. The case studies cover various areas of systems toxicology and pharmacogenomics and illustrate the rapid evolution of toxicogenomics, including computational methods for the analysis, integration, and interpretation of omics data.
Colletotrichum infects diverse hosts, including tea plants, and can lead to crop failure. Numerous studies have reported that biological processes are involved in the resistance of tea plants to Colletotrichum spp. However, the molecular and biochemical responses in the host during this interaction are unclear. Cuttings of the tea cultivar Longjing 43 (LJ43) were inoculated with a conidial suspension of Colletotrichum camelliae, and water-sprayed cuttings were used as controls. In total, 10,592 differentially expressed genes (DEGs) were identified from the transcriptomic data of the tea plants and were significantly enriched in callose deposition and the biosynthesis of various phytohormones. Subsequently, 3,555 mass spectra peaks were obtained by LC–MS detection in the negative ion mode, and 27, 18 and 81 differentially expressed metabolites (DEMs) were identified in the tea leaves at 12 hpi, 24 hpi and 72 hpi, respectively. The metabolomic analysis also revealed that the levels of the precursors and intermediate products of jasmonic acid (JA) and indole-3-acetate (IAA) biosynthesis were significantly increased during the interaction, especially when the symptoms became apparent. In conclusion, we suggest that callose deposition and various phytohormone signaling systems play important roles in the tea plant-C. camelliae interaction.
We demonstrate a selection of network and machine learning techniques useful in the analysis of complex datasets, including 2-way similarity networks, Markov clustering, enrichment statistical networks, FCROS differential analysis, and random forests. We demonstrate each of these techniques on the Populus trichocarpa gene expression atlas.
Graphical Abstract Highlights d The deSUMOylase SENP7 contributes to IBD pathophysiology d SENP7 function and interactome modulate epithelial-immune crosstalk d SIAH2 negatively regulates SENP7 by ubiquitination in healthy, but not inflamed, cells d Epithelial SENP7 upregulation triggers proinflammatory mechanisms via gd T cells
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