Comparative transcriptome analysis identifies jasmonic pathway genes related to anther dehiscence in Solanum melongena L.

2020 ◽  
Author(s):  
Zhimin Wang ◽  
Shaowei Zhang ◽  
Chao Yuan ◽  
Yi Niu ◽  
Qinglin Tang ◽  
...  
Keyword(s):  
Male Sterility ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Molecular Mechanisms ◽  
Solanum Melongena ◽  
Direct Interaction ◽  
Differentially Expressed ◽  
Anther Dehiscence ◽  
Interaction Studies ◽  
Pathway Analyses

Abstract Background: Anther indehiscence is an important form of functional male sterility that can facilitate the production of hybrid seeds. However, the molecular mechanisms of anther indehiscence-based male sterility in eggplant (Solanum melongena L.) have not been thoroughly explored. Therefore, we performed RNA-seq analysis to investigate the molecular mechanisms of anther dehiscence in eggplant. Results: We used transcriptome sequencing and qRT-PCR assays to compare the anthers of normally developing (F142) and anther indehiscent (S12) eggplant. We identified 2670 differentially expressed genes between lines. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identified 31 differentially expressed genes related to hormone biosynthesis. We therefore measured the contents of the phytohormones jasmonic acid (JA), IAA, GA3 and ABA in S12 and F142. There were no significant differences in IAA, GA3 or ABA levels between S12 and F142. However, JA levels were significantly lower in S12 than in F142. Five key genes in the JA signaling pathway were differentially expressed in S12 vs. F142. Of these, SmJAZ and SmJAR-like were significantly up-regulated and SmDAD1, SmLOX and SmCOI1 were down-regulated in S12 vs. F142. In DNA-protein interaction studies, SmLOX, SmAOC, SmOPR3, SmCOI1 and SmJAZ1 failed to be enriched on the chromatin of SmDAD1. Protein–protein interaction studies identified a direct interaction between SmDAD1 and SmLOX, but SmDAD1 failed to interact with SmAOC, SmOPR3, SmCOI1 and SmJAZ1. Conclusion: JA is an essential factor affecting anther dehiscence in eggplant. SmDAD1 interacts with SmLOX to alter JA levels, thereby regulating anther dehiscence. Our data represent a valuable resource for further exploring the regulatory mechanisms underlying anther dehiscence in eggplant.

scholarly journals Screening and Interaction Analysis Identify Genes Related to Anther Dehiscence in Solanum melongena L.

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhimin Wang ◽  
Chao Yuan ◽  
Shaowei Zhang ◽  
Shibing Tian ◽  
Qinglin Tang ◽  
...  
Keyword(s):  
Male Sterility ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Solanum Melongena ◽  
Direct Interaction ◽  
Differentially Expressed ◽  
Anther Dehiscence ◽  
Male Sterile ◽  
Reverse Transcription Pcr ◽  
Pathway Analyses

Anther indehiscence is an important form of functional male sterility that can facilitate the production of hybrid seeds. However, the molecular mechanisms of anther indehiscence-based male sterility in eggplant (Solanum melongena L.) have not been thoroughly explored. We performed transcriptome sequencing and real-time quantitative reverse transcription-PCR (qRT-PCR) assays to compare the fertile line (F142) and male sterile line (S12) eggplant. We identified 2,670 differentially expressed genes (DEGs) between lines. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identified 31 DEGs related to hormone biosynthesis. We, therefore, measured phytohormone contents, such as jasmonic acid (JA), auxin (IAA), gibberellin (GA), and abscisic acid (ABA) in S12 and F142. There were differences in IAA, GA3, and ABA levels between S12 and F142, while JA levels were significantly lower in S12 than in F142. Five key genes in the JA signaling pathway were differentially expressed in S12 vs. F142. Of these, SmJAZ1 and SmJAR1 were significantly upregulated and SmDAD1, SmLOX, and SmCOI1 were downregulated in S12 vs. F142. Protein–protein interaction studies identified a direct interaction between SmDAD1 and SmLOX, while SmDAD1 failed to interact with SmJAR1, SmCOI1, and SmJAZ1. The data represent a valuable resource for further exploration of regulatory mechanisms underlying anther dehiscence in eggplant.

scholarly journals Transcriptome Profiling Reveals Potential Genes Involved in Browning of Fresh-cut Eggplant (Solanum Melongena L.)

2020 ◽  
Author(s):  
Xiaohui Liu ◽  
Jing Shang ◽  
Aidong Zhang ◽  
Zongwen Zhu ◽  
Dingshi Zha ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Fruits And Vegetables ◽  
Molecular Mechanisms ◽  
Solanum Melongena ◽  
Transcriptome Profiling ◽  
Differentially Expressed ◽  
Enzymatic Browning ◽  
Fruit Samples ◽  
Phenylpropanoid Biosynthesis ◽  
Fresh Cut

Abstract Background: Fresh-cut processing promotes enzymatic browning of fresh fruits and vegetables, which negatively affects the appearance of products and impacts their nutrition. We used the RNA-Seq technique to analyze the transcriptomic changes occurring during the browning of fresh-cut eggplant (Solanum melongena L.) fruit samples from a browning-sensitive cultivar and a browning-resistant cultivar to investigate the genes and molecular mechanisms involved in browning. Results: A total of 111.55 GB of high-quality reads were generated, the genomes of each sample were compared, and 83.50%–95.14% of the data was mapped to the eggplant reference genome. Furthermore, a total of 19631 differentially expressed genes were identified, among which 12 genes and two WRKY transcription factors were identified as potentially involved in enzymatic browning in fresh-cut eggplant fruit. Moreover, the 14 differentially expressed genes associated with browning were verified using qRT-PCR. Conclusions: Several genes associated with phenolic oxidation, phenylpropanoid biosynthesis, and flavonoid biosynthesis were found to be differentially regulated between the eggplant cultivars with different browning sensitivities. This work is of great theoretical significance, as it provides a basis for future molecular studies and improvement of eggplants, and lays a theoretical foundation for the development of browning-resistant fresh-cut fruits and vegetables.

Identification of Differentially Expressed Genes Associated with Papillary Thyroid Carcinoma

2020 ◽  
Vol 23 (6) ◽  
pp. 546-553
Author(s):  
Hongyuan Cui ◽  
Mingwei Zhu ◽  
Junhua Zhang ◽  
Wenqin Li ◽  
Lihui Zou ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Cellular Proliferation ◽  
Mrna Level ◽  
Thyroid Tissue ◽  
Differentially Expressed ◽  
Thyroid Tumors ◽  
Papillary Thyroid

Objective: Next-generation sequencing (NGS) was performed to identify genes that were differentially expressed between normal thyroid tissue and papillary thyroid carcinoma (PTC). Materials & Methods: Six candidate genes were selected and further confirmed with quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry in samples from 24 fresh thyroid tumors and adjacent normal tissues. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to investigate signal transduction pathways of the differentially expressed genes. Results: In total, 1690 genes were differentially expressed between samples from patients with PTC and the adjacent normal tissue. Among these, SFRP4, ZNF90, and DCN were the top three upregulated genes, whereas KIRREL3, TRIM36, and GABBR2 were downregulated with the smallest p values. Several pathways were associated with the differentially expressed genes and involved in cellular proliferation, cell migration, and endocrine system tumor progression, which may contribute to the pathogenesis of PTC. Upregulation of SFRP4, ZNF90, and DCN at the mRNA level was further validated with RT-PCR, and DCN expression was further confirmed with immunostaining of PTC samples. Conclusion: These results provide new insights into the molecular mechanisms of PTC. Identification of differentially expressed genes should not only improve the tumor signature for thyroid tumors as a diagnostic biomarker but also reveal potential targets for thyroid tumor treatment.

scholarly journals Key Genes and Prognostic Analysis in HER2+ Breast Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382098329
Author(s):  
Yujie Weng ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Zhongxian Li ◽  
Rong Jia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Differentially Expressed ◽  
Protein Kinase Activity ◽  
Protein Protein Interaction ◽  
Risk Of Death ◽  
Her2 Breast Cancer ◽  
Key Genes

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

scholarly journals Identification of Differentially Expressed Genes in Porcine Ovaries at Proestrus and Estrus Stages Using RNA-Seq Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Songbai Yang ◽  
Xiaolong Zhou ◽  
Yue Pei ◽  
Han Wang ◽  
Ke He ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Hormone Secretion ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
The Novel ◽  
Kegg Pathways ◽  
Go Enrichment ◽  
Single Organism

Estrus is an important factor for the fecundity of sows, and it is involved in ovulation and hormone secretion in ovaries. To better understand the molecular mechanisms of porcine estrus, the expression patterns of ovarian mRNA at proestrus and estrus stages were analyzed using RNA sequencing technology. A total of 2,167 differentially expressed genes (DEGs) were identified (P≤0.05, log2  Ratio≥1), of which 784 were upregulated and 1,383 were downregulated in the estrus compared with the proestrus group. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in the cellular process, single-organism process, cell and cell part, and binding and metabolic process. In addition, a pathway analysis showed that these DEGs were significantly enriched in 33 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cell adhesion molecules, ECM-receptor interaction, and cytokine-cytokine receptor interaction. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) confirmed the differential expression of 10 selected DEGs. Many of the novel candidate genes identified in this study will be valuable for understanding the molecular mechanisms of the sow estrous cycle.

scholarly journals Comparative Transcriptomic Analysis of Embryo Implantation in Mice and Rats

2018 ◽  
Vol 50 (2) ◽  
pp. 668-678 ◽  
Author(s):  
Wen-Qian Zhang ◽  
Miao Zhao ◽  
Ming-Yu Huang ◽  
Ji-Long Liu
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Embryo Implantation ◽  
Differentially Expressed ◽  
Rat Uterus ◽  
Mouse Uterus ◽  
Pathway Network ◽  
Implantation Sites ◽  
High Selection ◽  
Transcriptomic Changes

Background/Aims: Embryo implantation is an essential process for eutherian pregnancy, but this process varies across eutherians. The genomic mechanisms that led to the emergence and diversification of embryo implantation are largely unknown. Methods: In this study, we analyzed transcriptomic changes during embryo implantation in mice and rats by using RNA-seq. Bioinformatics and evolutionary analyses were performed to characterize implantation-associated genes in these two species. Results: We identified a total of 518 differentially expressed genes in mouse uterus during implantation, of which 253 genes were up-regulated and 265 genes were down-regulated at the implantation sites compared with the inter-implantation sites. In rat uterus, there were 374 differentially expressed genes, of which 284 genes were up-regulated and 90 genes were down-regulated. A cross-species comparison revealed that 92 up-regulated genes and 20 down-regulated genes were shared. The differences and similarities between mice and rats were investigated further at the gene ontology, pathway, network, and causal transcription factor levels. Additionally, we found that embryo implantation might have evolved through the recruitment of ancient genes into uterine expression. The evolutionary rates of the differentially expressed genes in mouse and rat uterus were significantly lower than those of the non-changed genes, indicating that implantation-related genes are evolutionary conserved due to high selection pressure. Conclusion: Our study provides insights into the molecular mechanisms involved in the evolution of embryo implantation.

scholarly journals Bioinformatics analysis of differentially expressed genes and identification of an miRNA–mRNA network associated with entorhinal cortex and hippocampus in Alzheimer’s disease

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Haoming Li ◽  
Linqing Zou ◽  
Jinhong Shi ◽  
Xiao Han
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Differentially Expressed Genes ◽  
Entorhinal Cortex ◽  
Molecular Mechanisms ◽  
Kegg Pathway ◽  
Neurodegenerative Disorder ◽  
Early Stage ◽  
Differentially Expressed ◽  
Hub Genes

Abstract Background Alzheimer’s disease (AD) is a fatal neurodegenerative disorder, and the lesions originate in the entorhinal cortex (EC) and hippocampus (HIP) at the early stage of AD progression. Gaining insight into the molecular mechanisms underlying AD is critical for the diagnosis and treatment of this disorder. Recent discoveries have uncovered the essential roles of microRNAs (miRNAs) in aging and have identified the potential of miRNAs serving as biomarkers in AD diagnosis. Methods We sought to apply bioinformatics tools to investigate microarray profiles and characterize differentially expressed genes (DEGs) in both EC and HIP and identify specific candidate genes and pathways that might be implicated in AD for further analysis. Furthermore, we considered that DEGs might be dysregulated by miRNAs. Therefore, we investigated patients with AD and healthy controls by studying the gene profiling of their brain and blood samples to identify AD-related DEGs, differentially expressed miRNAs (DEmiRNAs), along with gene ontology (GO) analysis, KEGG pathway analysis, and construction of an AD-specific miRNA–mRNA interaction network. Results Our analysis identified 10 key hub genes in the EC and HIP of patients with AD, and these hub genes were focused on energy metabolism, suggesting that metabolic dyshomeostasis contributed to the progression of the early AD pathology. Moreover, after the construction of an miRNA–mRNA network, we identified 9 blood-related DEmiRNAs, which regulated 10 target genes in the KEGG pathway. Conclusions Our findings indicated these DEmiRNAs having the potential to act as diagnostic biomarkers at an early stage of AD.

scholarly journals Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8096 ◽  
Author(s):  
Haiping Zhang ◽  
Jian Zou ◽  
Ying Yin ◽  
Bo Zhang ◽  
Yaling Hu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Clinical Stage ◽  
Stage I ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

scholarly journals Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Healing Process ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Wound Age ◽  
Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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