Physiological and Growth Response of Pepper (Capsicum annum L.) Seedlings to Supplementary Red/Blue Light Revealed through Transcriptomic Analysis

Red and blue light have great effects on physiological processes and growth of plants. In this experiment, we investigated the physiological and growth response of pepper (Capsicum annuum L.) to supplementary red:blue (4:1) light for 1 h (T1), 3 h (T2), and 5 h (T3), and the full-spectrum light-emitting diodes, LEDs, as control (CK). Thirty-day-old seedlings were grown under these treatments for 20 days in a climate-controlled room before data measurement. The results showed that the light treatments significantly (p < 0.05) affected the photosynthesis and growth indexes as well as gene expression in the pepper seedlings. Plants under T2 generally had better performance in terms of seedling growth. A total of 124, 1283, and 1091 differentially expressed genes were found in CK vs. T1, CK vs. T2, and CK vs. T3, respectively. Among the treatments, T2 in comparison with CK had 705 upregulated and 578 downregulated differentially expressed genes (DEGs). We also found that CPRF2, Paggis, HLIPS, GIGANTEA, LSH1, and FTSH genes were expressed differently under the various light treatments. Based on GeneOntology (GO) enrichment analysis, DEGs were significantly enriched on 15 GO terms of which xyloglucan:xyloglucosyl transferase activity and apoplastic, cellular polysaccharide metabolic, and cellular carbohydrate metabolic processes were closely related to light responses. A total of 96 genes that are related to plant–pathogen interaction, zeatin biosynthesis, plant hormone signal transduction, and wax/cutin/suberine biosynthesis which are involved in the pathway of light reaction in plants were significantly enriched in T2 plants compared with plants under CK. The application of red:blue light at 4:1 for 3 h improved the growth of pepper seedlings better than the other treatments and this can be tested under the Chinese Solar Greenhouse condition.

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Transcriptional identification of differentially expressed genes during the prepupal–pupal transition in the oriental armyworm, Mythimna separata (Walker) (Lepidoptera: Noctuidae)

Bulletin of Entomological Research ◽

10.1017/s0007485321000171 ◽

2021 ◽

pp. 1-14

Author(s):

Peirong Li ◽

Xinru Li ◽

Wei Wang ◽

Xiaoling Tan ◽

Xiaoqi Wang ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Metabolic Pathways ◽

Developmental Stages ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Mythimna Separata ◽

Kegg Pathway Analysis ◽

Oriental Armyworm ◽

Lepidoptera Noctuidae

Abstract The oriental armyworm, Mythimna separata (Walker) is a serious pest of agriculture that does particular damage to Gramineae crops in Asia, Europe, and Oceania. Metamorphosis is a key developmental stage in insects, although the genes underlying the metamorphic transition in M. separata remain largely unknown. Here, we sequenced the transcriptomes of five stages; mature larvae (ML), wandering (W), and pupation (1, 5, and 10 days after pupation, designated P1, P5, and P10) to identify transition-associated genes. Four libraries were generated, with 22,884, 23,534, 26,643, and 33,238 differentially expressed genes (DEGs) for the ML-vs-W, W-vs-P1, P1-vs-P5, and P5-vs-P10, respectively. Gene ontology enrichment analysis of DEGs showed that genes regulating the biosynthesis of the membrane and integral components of the membrane, which includes the cuticular protein (CP), 20-hydroxyecdysone (20E), and juvenile hormone (JH) biosynthesis, were enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that DEGs were enriched in the metabolic pathways. Of these DEGs, thirty CP, seventeen 20E, and seven JH genes were differentially expressed across the developmental stages. For transcriptome validation, ten CP, 20E, and JH-related genes were selected and verified by real-time PCR quantitative. Collectively, our results provided a basis for further studies of the molecular mechanism of metamorphosis in M. separata.

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Lipidomics profiling of goose granulosa cell model of stearoyl-CoA desaturase function identifies a pattern of lipid droplets associated with follicle development

Cell & Bioscience ◽

10.1186/s13578-021-00604-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Xin Yuan ◽

Shenqiang Hu ◽

Liang Li ◽

Chunchun Han ◽

Hehe Liu ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Lipid Droplets ◽

Cell Model ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Follicle Development ◽

Microscopy Analysis ◽

Stearoyl Coa Desaturase ◽

Underlying Mechanisms

Abstract Background Despite their important functions and nearly ubiquitous presence in cells, an understanding of the biology of intracellular lipid droplets (LDs) in goose follicle development remains limited. An integrated study of lipidomic and transcriptomic analyses was performed in a cellular model of stearoyl-CoA desaturase (SCD) function, to determine the effects of intracellular LDs on follicle development in geese. Results Numerous internalized LDs, which were generally spherical in shape, were dispersed throughout the cytoplasm of granulosa cells (GCs), as determined using confocal microscopy analysis, with altered SCD expression affecting LD content. GC lipidomic profiling showed that the majority of the differentially abundant lipid classes were glycerophospholipids, including PA, PC, PE, PG, PI, and PS, and glycerolipids, including DG and TG, which enriched glycerophospholipid, sphingolipid, and glycerolipid metabolisms. Furthermore, transcriptomics identified differentially expressed genes (DEGs), some of which were assigned to lipid-related Gene Ontology slim terms. More DEGs were assigned in the SCD-knockdown group than in the SCD-overexpression group. Integration of the significant differentially expressed genes and lipids based on pathway enrichment analysis identified potentially targetable pathways related to glycerolipid/glycerophospholipid metabolism. Conclusions This study demonstrated the importance of lipids in understanding follicle development, thus providing a potential foundation to decipher the underlying mechanisms of lipid-mediated follicle development.

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AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.1773 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1037.2-1038

Author(s):

X. Sun ◽

S. X. Zhang ◽

S. Song ◽

T. Kong ◽

C. Zheng ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathways ◽

Differentially Expressed Genes ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Shanxi Province ◽

Receptor Interaction ◽

Term Therapy ◽

Pathway Enrichment Analysis ◽

Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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Analysis of Transcriptional Changes in Different Brassica napus Synthetic Allopolyploids

Genes ◽

10.3390/genes12010082 ◽

2021 ◽

Vol 12 (1) ◽

pp. 82

Author(s):

Yunxiao Wei ◽

Guoliang Li ◽

Shujiang Zhang ◽

Shifan Zhang ◽

Hui Zhang ◽

...

Keyword(s):

Gene Expression ◽

Brassica Napus ◽

Differentially Expressed Genes ◽

Expression Patterns ◽

Female Parent ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Transcriptional Changes ◽

Aa Genome ◽

High Degree

Allopolyploidy is an evolutionary and mechanistically intriguing process involving the reconciliation of two or more sets of diverged genomes and regulatory interactions, resulting in new phenotypes. In this study, we explored the gene expression patterns of eight F2 synthetic Brassica napus using RNA sequencing. We found that B. napus allopolyploid formation was accompanied by extensive changes in gene expression. A comparison between F2 and the parent shows a certain proportion of differentially expressed genes (DEG) and activation\silent gene, and the two genomes (female parent (AA)\male parent (CC) genomes) showed significant differences in response to whole-genome duplication (WGD); non-additively expressed genes represented a small portion, while Gene Ontology (GO) enrichment analysis showed that it played an important role in responding to WGD. Besides, genome-wide expression level dominance (ELD) was biased toward the AA genome, and the parental expression pattern of most genes showed a high degree of conservation. Moreover, gene expression showed differences among eight individuals and was consistent with the results of a cluster analysis of traits. Furthermore, the differential expression of waxy synthetic pathways and flowering pathway genes could explain the performance of traits. Collectively, gene expression of the newly formed allopolyploid changed dramatically, and this was different among the selfing offspring, which could be a prominent cause of the trait separation. Our data provide novel insights into the relationship between the expression of differentially expressed genes and trait segregation and provide clues into the evolution of allopolyploids.

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Bioinformatics-based Screening of Key Genes for Saponin Metabolism in Quinoa

10.21203/rs.3.rs-139481/v1 ◽

2021 ◽

Author(s):

Chengang Guo ◽

Zhimin wei ◽

Wei Lyu ◽

Yanlou Geng

Keyword(s):

Differentially Expressed Genes ◽

Principal Component ◽

Enrichment Analysis ◽

Hierarchical Cluster ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Differential Analysis ◽

Rna Seq ◽

Protein Coding ◽

Key Genes

Abstract Quinoa saponins have complex, diverse and evident physiologic activities. However, the key regulatory genes for quinoa saponin metabolism are not yet well studied. The purpose of this study was to explore genes closely related to quinoa saponin metabolism. In this study, the significantly differentially expressed genes in yellow quinoa were firstly screened based on RNA-seq technology. Then, the key genes for saponin metabolism were selected by gene set enrichment analysis (GSEA) and principal component analysis (PCA) statistical methods. Finally, the specificity of the key genes was verified by hierarchical clustering. The results of differential analysis showed that 1654 differentially expressed genes were achieved after pseudogenes deletion. Therein, there were 142 long non-coding genes and 1512 protein-coding genes. Based on GSEA analysis, 116 key candidate genes were found to be significantly correlated with quinoa saponin metabolism. Through PCA dimension reduction analysis, 57 key genes were finally obtained. Hierarchical cluster analysis further demonstrated that these key genes can clearly separate the four groups of samples. The present results could provide references for the breeding of sweet quinoa and would be helpful for the rational utilization of quinoa saponins.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma

PeerJ ◽

10.7717/peerj.8831 ◽

2020 ◽

Vol 8 ◽

pp. e8831 ◽

Cited By ~ 1

Author(s):

Xiaojiao Guan ◽

Yao Yao ◽

Guangyao Bao ◽

Yue Wang ◽

Aimeng Zhang ◽

...

Keyword(s):

Gene Expression ◽

Esophageal Cancer ◽

Esophageal Carcinoma ◽

Differentially Expressed Genes ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Diagnostic Model ◽

Link Type ◽

Key Genes

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.

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Screening the Hub Genes and Analyzing the Mechanisms in Discharged COVID-19 Patients Retesting Positive through Bioinformatics Analysis

10.21203/rs.3.rs-991635/v1 ◽

2021 ◽

Author(s):

Ke-Ying Fang ◽

Gui-Ning Liang ◽

Zhuo-Qing Zhuang ◽

Yong-Xin Fang ◽

Yu-Qian Dong ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Social Order ◽

Expression System ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Virus Reactivation ◽

Hub Genes ◽

Messenger Ribonucleic Acid ◽

Ppi Networks ◽

Significant Enrichment

Abstract Background: With the worldwide spread of COVID-19, people’s health and social order have been exposed to enormous risks. After encountering patients who test positive again after discharge, our study analyzed the pathogenesis to further assess the risk and possibility of virus reactivation.Methods: A separate microarray was acquired from the Integrated Gene Expression System (GEO), and its samples were divided into two groups: a “convalescent-RTP” group consisting of recovery and “retesting-positive” (RTP) patients (group CR) and a “health-RTP” group consisting of healthy control and RTP patients (group HR). The enrichment analysis was performed with R software, obtaining the gene ontology (GO) and Kyoto pluripotent stem cells (KEGG) of the genes and genomes. Subsequently, the protein–protein interaction (PPI) networks of each group were established and the hub genes were discovered using the cytoHubba plug-in.Results: In this study, 20 differentially expressed genes were identified, and 6622 genes were identified in the group CR, consisting of 5003 up-regulated and 1619 down-regulated genes. Meanwhile, 7335 genes were screened in the group HR, including 4323 up-regulated and 3012 down-regulated ones. The GO and KEGG analysis of the two groups revealed significant enrichment of these differentially expressed genes in pathways associated with immune response and apoptosis. In the PPI network constructed, 10 hub genes in group CR were identified, including TP53BP1, SNRPD1, SNRPD2, SF3B1, SNRNP200, MRPS16, MRPS9, CALM1, PPP2R1A, YWHAZ. Similarly, TP53BP1, RPS15, EFTUD2, MRPL16, MRPL17, MRPS14, RPL35A, MRPL32, MRPS6, POLR2G were selected as hub genes.Conclusions: Using the messenger ribonucleic acid (mRNA) expression data from GSE166253, we explore the pathogenesis of retesting positive in COVID-19 from the immune mechanism and molecular level. We found TP53BP1, SNRPD1 and SNRPD2 as hub genes in RTP patients. Hence, their regulatory pathway is vital to the management and prognostic prediction of RTP patients, rendering the further study of these hub genes necessary.

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Comprehensive Analysis of Differentially Expressed Genes and Key Pathways in Neuropathic Pain by Spinal Nerve Ligation

10.21203/rs.3.rs-74125/v1 ◽

2020 ◽

Author(s):

Chao Xu ◽

HuiFang Li ◽

YunPeng Zhang ◽

TianYu Liu ◽

Yi Feng

Keyword(s):

Functional Analysis ◽

Neuropathic Pain ◽

Differentially Expressed Genes ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Spinal Nerve ◽

Spinal Nerve Ligation ◽

Differentially Expressed ◽

Hub Genes ◽

Long Term Treatment

Abstract Background: Neuropathic pain can cause significant physical and economic burden to people, and there are no effective long-term treatment methods for this condition. We conducted a bioinformatics analysis of microarray data to identify related mechanisms to determine strategies for more effective treatments of neuropathic pain.Methods: GSE24982 and GSE63442 microarray datasets were extracted from the Gene Expression Omnibus (GEO) database to analyze transcriptome differences of neuropathic pain in the dorsal root ganglions caused by spinal nerve ligation. We filtered the differentially expressed genes (DEGs) in the two datasets and Webgestalt was applied to conduct GeneOntology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the shared DEGs. String Database and Cytoscape software were used to construct the Protein-Protein Interaction (PPI) network to determine the hub genes, which were subsequently verified in the GSE30691 dataset. Finally, miRDB and miRWalk Databases were used to predict potential miRNA of the selected DEGs.Results: A total of 182 overlapped DEGs were found between GSE24982 and GSE63442 datasets. The GO functional analysis and KEGG enrichment analysis showed that the selected DEGs were mainly enriched in infection, transmembrane transport of ion channels, and synaptic transmission. Combining the results of PPI analysis and the verification of the GSE30691 dataset, we identified seven hub genes related to neuropathic pain (Atf3, Aif1, Ctss, Gfap, Scg2, Jun, and Vgf). Predicted miRNA targeting each selected hub genes were identified.Conclusion: Seven hub genes related to the pathogenesis of neuropathic pain and potential targeting miRNA were identified, expanding understanding of the mechanism of neuropathic pain and facilitating treatment development.

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Regulatory Crosstalk of Doxorubicin, Estradiol and TNFα Combined Treatment in Breast Cancer-derived Cell Lines

Scientific Reports ◽

10.1038/s41598-019-51349-9 ◽

2019 ◽

Vol 9 (1) ◽

Author(s):

Isar Nassiri ◽

Alberto Inga ◽

Erna Marija Meškytė ◽

Federica Alessandrini ◽

Yari Ciribilli ◽

...

Keyword(s):

Breast Cancer ◽

Cell Lines ◽

Differentially Expressed Genes ◽

Combination Treatment ◽

Combined Treatment ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Transcriptional Responses ◽

Predisposing Factor ◽

Inflammatory Microenvironment

Abstract We present a new model of ESR1 network regulation based on analysis of Doxorubicin, Estradiol, and TNFα combination treatment in MCF-7. We used Doxorubicin as a therapeutic agent, TNFα as marker and mediator of an inflammatory microenvironment and 17β-Estradiol (E2) as an agonist of Estrogen Receptors, known predisposing factor for hormone-driven breast cancer, whose pharmacological inhibition reduces the risk of breast cancer recurrence. Based on the results of transcriptomics analysis, we found 71 differentially expressed genes that are specific for the combination treatment with Doxorubicin + Estradiol + TNFα in comparison with single or double treatments. The responsiveness to the triple treatment was examined for seven genes by qPCR, of which six were validated, and then extended to four additional cell lines differing for p53 and/or ER status. The results of differential regulation enrichment analysis highlight the role of the ESR1 network that included 36 of 71 specific differentially expressed genes. We propose that the combined activation of p53 and NF-kB transcription factors significantly influences ligand-dependent, ER-driven transcriptional responses, also of the ESR1 gene itself. These results provide a model of coordinated interaction of TFs to explain the Doxorubicin, E2 and TNFα induced repression mechanisms.

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