The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life

Objective To identify dysregulated miRNAs in testicular tissues from animal models and patients with cryptorchidism. Methods Databases were systematically searched for studies published before 10 May 2020 that had investigated miRNAs in cryptorchidism. Predicted targets of the identified miRNA biomarkers were obtained by searching TargetScan and Starbase. Gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently conducted. Results Five publications met the eligibility criteria for the review. 21 differentially expressed miRNAs were the most abundantly reported in 185 animal and human tissue samples. Three miRNAs (miR-210, miR-449a and miR-34c) were dysregulated in both animal and human testicular tissues. The top five relevant lncRNAs associated with the miRNAs were NEAT1, KCNQ1OT1, XIST, AC005154.1, and TUG1. Conclusions Further research is warranted to explore the potential of these dysregulated miRNAs as biomarkers or therapeutic targets for male infertility associated with cryptorchidism.

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Transcriptome Analysis Reveals Dynamic Cultivar-Dependent Patterns of Gene Expression in Potato Spindle Tuber Viroid-Infected Pepper

Plants ◽

10.3390/plants10122687 ◽

2021 ◽

Vol 10 (12) ◽

pp. 2687

Author(s):

Nikol Hadjieva ◽

Elena Apostolova ◽

Vesselin Baev ◽

Galina Yahubyan ◽

Mariyana Gozmanova

Keyword(s):

Gene Expression ◽

Gene Ontology ◽

Differentially Expressed Genes ◽

Transcriptome Analysis ◽

Quantitative Polymerase Chain Reaction ◽

Potato Spindle Tuber Viroid ◽

Fine Tuning ◽

Differentially Expressed ◽

Gene Ontology Term ◽

Ontology Term

Potato spindle tuber viroid (PSTVd) infects various plants. PSTVd pathogenesis is associated with interference with the cellular metabolism and defense signaling pathways via direct interaction with host factors or via the transcriptional or post-transcriptional modulation of gene expression. To better understand host defense mechanisms to PSTVd infection, we analyzed the gene expression in two pepper cultivars, Capsicum annuum Kurtovska kapia (KK) and Djulunska shipka (DS), which exhibit mild symptoms of PSTVd infection. Deep sequencing-based transcriptome analysis revealed differential gene expression upon infection, with some genes displaying contrasting expression patterns in KK and DS plants. More genes were downregulated in DS plants upon infection than in KK plants, which could underlie the more severe symptoms seen in DS plants. Gene ontology enrichment analysis revealed that most of the downregulated differentially expressed genes in both cultivars were enriched in the gene ontology term photosynthesis. The genes upregulated in DS plants fell in the biological process of gene ontology term defense response. We validated the expression of six overlapping differentially expressed genes that are involved in photosynthesis, plant hormone signaling, and defense pathways by quantitative polymerase chain reaction. The observed differences in the responses of the two cultivars to PSTVd infection expand the understanding of the fine-tuning of plant gene expression that is needed to overcome the infection.

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The influence of metabolic network structures and energy metabolic pattern on E. coli K12 exposed to acoustic field: based on Gene Ontology and KEGG pathway enrichment analysis

10.7287/peerj.preprints.2821 ◽

2017 ◽

Author(s):

Shaobin Gu ◽

Suyu Qiao ◽

Ying Wu

Keyword(s):

Gene Ontology ◽

Energy Metabolism ◽

Stationary Phase ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Living Environment ◽

Pathway Enrichment Analysis ◽

E Coli ◽

Pathway Enrichment ◽

Sound Exposure

Microorganism is an important part of ecosystems; it is very sensitive to environmental change. In order to study the effects of sound on organisms, it’s meaningful to study mechanism of microbial exposure to sound. In our previous experiments, the effects of different sound intensity and frequency on the growth of E. coli K12 were studied. It was found that in stationary phase the bacteria concentration of sound expose group was higher than control. In this study, we aimed to understand the mechanisms of E. coli underlying sound expose by using Gene Ontology and KEGG Pathway Enrichment Analysis, and established a systematic pathway for the E. coli response to sound expose. At 6 hour, the chemotaxis pathway was significantly up-regulated which responses to the changes of the external environment and leads bacteria to favorable environment. At 12 hour, the glycerophospholipid pathway was significant up-regulated, it is related to the energy metabolism and cell division. At 24 hours, the energy metabolism, nucleotide synthesis and transcriptional translation pathways were significant differences. When bacteria entered the stationary phase (36 hour), in sound exposure group the pathways related to reduce the harmful substances were down-regulated and the pathways about degrade aromatic compounds provides energy were up-regulated, so that the E. coli K12 in sound exposure have a better ability to adapt poor living environment. Comparative transcriptome analysis of sound exposed E. coli K12 can not only reveal the behavior of E. coli K12 response to sound expose, but also lay a foundation for further study the mechanism of prokaryotes response to physical stimulus.

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PFP-WGAN: Protein function prediction by discovering Gene Ontology term correlations with generative adversarial networks

PLoS ONE ◽

10.1371/journal.pone.0244430 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0244430

Author(s):

Seyyede Fatemeh Seyyedsalehi ◽

Mahdieh Soleymani ◽

Hamid R. Rabiee ◽

Mohammad R. K. Mofrad

Keyword(s):

Gene Ontology ◽

Computational Methods ◽

Protein Function ◽

Protein Function Prediction ◽

Function Prediction ◽

Protein Sequencing ◽

Generative Adversarial Networks ◽

Gene Ontology Term ◽

Generative Adversarial Network ◽

Ontology Term

Understanding the functionality of proteins has emerged as a critical problem in recent years due to significant roles of these macro-molecules in biological mechanisms. However, in-laboratory techniques for protein function prediction are not as efficient as methods developed and processed for protein sequencing. While more than 70 million protein sequences are available today, only the functionality of around one percent of them are known. These facts have encouraged researchers to develop computational methods to infer protein functionalities from their sequences. Gene Ontology is the most well-known database for protein functions which has a hierarchical structure, where deeper terms are more determinative and specific. However, the lack of experimentally approved annotations for these specific terms limits the performance of computational methods applied on them. In this work, we propose a method to improve protein function prediction using their sequences by deeply extracting relationships between Gene Ontology terms. To this end, we construct a conditional generative adversarial network which helps to effectively discover and incorporate term correlations in the annotation process. In addition to the baseline algorithms, we compare our method with two recently proposed deep techniques that attempt to utilize Gene Ontology term correlations. Our results confirm the superiority of the proposed method compared to the previous works. Moreover, we demonstrate how our model can effectively help to assign more specific terms to sequences.

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Gene Ontology term enrichment analysis of gene expression changes observed in the TRAMP mouse model of prostate cancer upon treatement with green tea catechins

The FASEB Journal ◽

10.1096/fasebj.24.1_supplement.669.3 ◽

2010 ◽

Vol 24 (S1) ◽

Author(s):

Stephen Vincent Speicher ◽

Kam D Dahlquist

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Gene Ontology ◽

Mouse Model ◽

Enrichment Analysis ◽

Gene Ontology Term ◽

Ontology Term ◽

Tramp Mouse ◽

Term Enrichment Analysis ◽

Term Enrichment

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The influence of metabolic network structures and energy metabolic pattern on E. coli K12 exposed to acoustic field: based on Gene Ontology and KEGG pathway enrichment analysis

10.7287/peerj.preprints.2821v1 ◽

2017 ◽

Cited By ~ 1

Author(s):

Shaobin Gu ◽

Suyu Qiao ◽

Ying Wu

Keyword(s):

Gene Ontology ◽

Energy Metabolism ◽

Stationary Phase ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Living Environment ◽

Pathway Enrichment Analysis ◽

E Coli ◽

Pathway Enrichment ◽

Sound Exposure

Microorganism is an important part of ecosystems; it is very sensitive to environmental change. In order to study the effects of sound on organisms, it’s meaningful to study mechanism of microbial exposure to sound. In our previous experiments, the effects of different sound intensity and frequency on the growth of E. coli K12 were studied. It was found that in stationary phase the bacteria concentration of sound expose group was higher than control. In this study, we aimed to understand the mechanisms of E. coli underlying sound expose by using Gene Ontology and KEGG Pathway Enrichment Analysis, and established a systematic pathway for the E. coli response to sound expose. At 6 hour, the chemotaxis pathway was significantly up-regulated which responses to the changes of the external environment and leads bacteria to favorable environment. At 12 hour, the glycerophospholipid pathway was significant up-regulated, it is related to the energy metabolism and cell division. At 24 hours, the energy metabolism, nucleotide synthesis and transcriptional translation pathways were significant differences. When bacteria entered the stationary phase (36 hour), in sound exposure group the pathways related to reduce the harmful substances were down-regulated and the pathways about degrade aromatic compounds provides energy were up-regulated, so that the E. coli K12 in sound exposure have a better ability to adapt poor living environment. Comparative transcriptome analysis of sound exposed E. coli K12 can not only reveal the behavior of E. coli K12 response to sound expose, but also lay a foundation for further study the mechanism of prokaryotes response to physical stimulus.

Download Full-text