Faculty Opinions recommendation of Identification of regulatory networks and hub genes controlling soybean seed set and size using RNA sequencing analysis.

Abstract Background: To understand the gene expression networks controlling flower color formation in alfalfa, flowers anthocyanins were identified using two materials with contrasting flower colors, namely Defu and Zhongtian No. 3, and transcriptome analyses of PacBio full-length sequencing combined with RNA sequencing were performed, across four flower developmental stages. Results: Malvidin and petunidin glycoside derivatives were the major anthocyanins in the flowers of Defu, which were lacking in the flowers of Zhongtian No. 3. The two transcriptomic datasets provided a comprehensive and systems-level view on the dynamic gene expression networks underpinning alfalfa flower color formation. By weighted gene coexpression network analyses, we identified candidate genes and hub genes from the modules closely related to floral developmental stages. PAL , 4CL , CHS , CHR , F3’H , DFR , and UFGT were enriched in the important modules. Additionally, PAL6 , PAL9 , 4CL18 , CHS2 , 4 and 8 were identified as hub genes. Thus, a hypothesis explaining the lack of purple color in the flower of Zhongtian No. 3 was proposed. Conclusions: These analyses identified a large number of potential key regulators controlling flower color pigmentation, thereby providing new insights into the molecular networks underlying alfalfa flower development.

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Identification of the regulatory networks and hub genes controlling alfalfa floral pigmentation variation using RNA-sequencing analysis

10.21203/rs.2.17797/v1 ◽

2019 ◽

Author(s):

Hui-Rong Duan ◽

Li-Rong Wang ◽

Guang-Xin Cui ◽

Xue-Hui Zhou ◽

Xiao-Rong Duan ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Regulatory Networks ◽

Developmental Stages ◽

Flower Color ◽

Molecular Networks ◽

Sequencing Analysis ◽

Hub Genes ◽

Color Formation ◽

Network Analyses

Abstract Background: To understand the gene expression networks controlling flower color formation in alfalfa, transcriptome analyses of PacBio full-length sequencing combined with RNA sequencing were performed using two materials with contrasting flower colors, namely Defu and Zhongtian No. 3, across four flower developmental stages. Results: The two datasets provided a comprehensive and systems-level view on the dynamic gene expression networks underpinning alfalfa flower color formation. By weighted gene coexpression network analyses, we identified candidate genes and hub genes from the modules closely related to floral developmental stages. PAL, 4CL, CHS, CHR, F3’H, DFR, and UFGT were enriched in the important modules. Additionally, PAL6, PAL9, 4CL18, CHS2, 4 and 8 were identified as hub genes. Thus, a hypothesis explaining the lack of purple color in the flower of Zhongtian No. 3 was proposed. Conclusions: These analyses identified a large number of potential key regulators controlling flower color pigmentation, thereby providing new insights into the molecular networks underlying alfalfa flower development.

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Identification of the regulatory networks and hub genes controlling alfalfa floral pigmentation variation using RNA-sequencing analysis

10.21203/rs.2.17797/v2 ◽

2020 ◽

Author(s):

Hui-Rong Duan ◽

Li-Rong Wang ◽

Guang-Xin Cui ◽

Xue-Hui Zhou ◽

Xiao-Rong Duan ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Regulatory Networks ◽

Developmental Stages ◽

Flower Color ◽

Molecular Networks ◽

Sequencing Analysis ◽

Hub Genes ◽

Color Formation ◽

Network Analyses

Abstract Background: To understand the gene expression networks controlling flower color formation in alfalfa, flowers anthocyanins were identified using two materials with contrasting flower colors, namely Defu and Zhongtian No. 3, and transcriptome analyses of PacBio full-length sequencing combined with RNA sequencing were performed, across four flower developmental stages. Results: Malvidin and petunidin glycoside derivatives were the major anthocyanins in the flowers of Defu, which were lacking in the flowers of Zhongtian No. 3. The two transcriptomic datasets provided a comprehensive and systems-level view on the dynamic gene expression networks underpinning alfalfa flower color formation. By weighted gene coexpression network analyses, we identified candidate genes and hub genes from the modules closely related to floral developmental stages. PAL, 4CL, CHS, CHR, F3’H, DFR, and UFGT were enriched in the important modules. Additionally, PAL6, PAL9, 4CL18, CHS2, 4 and 8 were identified as hub genes. Thus, a hypothesis explaining the lack of purple color in the flower of Zhongtian No. 3 was proposed. Conclusions: These analyses identified a large number of potential key regulators controlling flower color pigmentation, thereby providing new insights into the molecular networks underlying alfalfa flower development.

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Identification of the regulatory networks and hub genes controlling alfalfa floral pigmentation variation using RNA-sequencing analysis

10.21203/rs.2.17797/v3 ◽

2020 ◽

Author(s):

Hui-Rong Duan ◽

Li-Rong Wang ◽

Guang-Xin Cui ◽

Xue-Hui Zhou ◽

Xiao-Rong Duan ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Regulatory Networks ◽

Developmental Stages ◽

Flower Color ◽

Molecular Networks ◽

Sequencing Analysis ◽

Hub Genes ◽

Color Formation ◽

Network Analyses

Abstract Background: To understand the gene expression networks controlling flower color formation in alfalfa, flowers anthocyanins were identified using two materials with contrasting flower colors, namely Defu and Zhongtian No. 3, and transcriptome analyses of PacBio full-length sequencing combined with RNA sequencing were performed, across four flower developmental stages. Results: Malvidin and petunidin glycoside derivatives were the major anthocyanins in the flowers of Defu, which were lacking in the flowers of Zhongtian No. 3. The two transcriptomic datasets provided a comprehensive and systems-level view on the dynamic gene expression networks underpinning alfalfa flower color formation. By weighted gene coexpression network analyses, we identified candidate genes and hub genes from the modules closely related to floral developmental stages. PAL , 4CL , CHS , CHR , F3’H , DFR , and UFGT were enriched in the important modules. Additionally, PAL6 , PAL9 , 4CL18 , CHS2 , 4 and 8 were identified as hub genes. Thus, a hypothesis explaining the lack of purple color in the flower of Zhongtian No. 3 was proposed. Conclusions: These analyses identified a large number of potential key regulators controlling flower color pigmentation, thereby providing new insights into the molecular networks underlying alfalfa flower development.

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Network Pharmacology and Experiment Verification to Explore the Potential Mechanism of Yin-Huo-Tang for Lung Adenocarcinoma Recurrence

10.21203/rs.3.rs-956330/v1 ◽

2021 ◽

Author(s):

Dianna Liu ◽

Shicheng Lin ◽

Yuan Li ◽

Tian Zhou ◽

Kaiwen Hu ◽

...

Keyword(s):

Lung Cancer ◽

Molecular Docking ◽

Lung Adenocarcinoma ◽

Signaling Pathway ◽

Rna Sequencing ◽

Network Pharmacology ◽

Phytochemical Analysis ◽

Sequencing Analysis ◽

Lewis Lung ◽

Hub Genes

Abstract BackgroundLung adenocarcinoma (LUAD) is one of the most common malignancies with a rise in new cases worldwide each year. Recurrence significantly influences the survival in patients with LUAD. Yin-Huo-Tang (YHT) is a classic traditional Chinese prescription, used to prevent lung cancer relapse by “nourishing yin and clearing heat”. MethodsIn this study, the mechanism of YHT in LUAD recurrence was investigated. Firstly, the bioactive compounds-targets network and the protein–protein interaction network were constructed, and functional annotation and pathway enrichment analyses were performed. Pivotal compounds and hub genes were selected from the networks. Subsequently, the effectiveness of YHT was confirmed in lewis lung carcinoma mice. RNA sequencing was used to explore the mRNA expression differences between tumor tissues in the model mouses and YHT-treated mouses. The pathways screened by network pharmacology and RNA sequencing analysis at the same time were considered the most important pathways. At last, qualitative phytochemical analysis, molecular docking technology, PCR and WB analysis were used to validate the pivotal active ingredients, hub genes and main pathways.ResultsThere were 128 active compounds, 419 targets interacting with LUAD recurrence. Network analysis identified 4 pivotal compounds, 28 hub genes and 30 main pathways. Target genes mainly focused on inflammation, metabolism, immune responses and apoptosis. We confirmed that YHT could inhibit the recurrence of lung adenocarcinoma through animal experimental study. Sphingolipid signaling pathway was the common main pathway in network pharmacology and RNA sequencing results. The hub genes related with the sphingolipid signaling pathway was S1PR5. Qualitative phytochemical analysis of the water extract of YHT confirmed the presence of 3 pivotal compounds, namely stigmasterol, nootkatone and ergotamine. The results of molecular docking verified the pivotal compounds of YHT could good affinity with the S1PR5. The PCR and WB analysis verified YHT suppressed lewis lung cancer cells proliferation by inhibiting S1P/S1PR5/Gi/Ras/Raf/MEK/ERK pathway, and inhibited migration through S1P/S1PR5/Gi/PI3K/RAC pathway.ConclusionThe results confirmed the therapeutic effect of YHT on the recurrence of LUAD by multi-component-multi-target mode, the sphingolipid signaling pathway was one of the most relevant potential signaling pathways.

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Single-Cell RNA Sequencing Analysis of the Heterogeneity in Gene Regulatory Networks in Colorectal Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.765578 ◽

2021 ◽

Vol 9 ◽

Author(s):

Rui-Qi Wang ◽

Wei Zhao ◽

Hai-Kui Yang ◽

Jia-Mei Dong ◽

Wei-Jie Lin ◽

...

Keyword(s):

Colorectal Cancer ◽

Single Cell ◽

Rna Sequencing ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Sequencing Analysis ◽

Sequencing Data ◽

Communication Analysis ◽

Single Cell Rna Sequencing ◽

Gene Regulatory

Colorectal cancer (CRC) manifests as gastrointestinal tumors with high intratumoral heterogeneity. Recent studies have demonstrated that CRC may consist of tumor cells with different consensus molecular subtypes (CMS). The advancements in single-cell RNA sequencing have facilitated the development of gene regulatory networks to decode key regulators for specific cell types. Herein, we comprehensively analyzed the CMS of CRC patients by using single-cell RNA-sequencing data. CMS for all malignant cells were assigned using CMScaller. Gene set variation analysis showed pathway activity differences consistent with those reported in previous studies. Cell–cell communication analysis confirmed that CMS1 was more closely related to immune cells, and that monocytes and macrophages play dominant roles in the CRC tumor microenvironment. On the basis of the constructed gene regulation networks (GRNs) for each subtype, we identified that the critical transcription factor ERG is universally activated and upregulated in all CMS in comparison with normal cells, and that it performed diverse roles by regulating the expression of different downstream genes. In summary, molecular subtyping of single-cell RNA-sequencing data for colorectal cancer could elucidate the heterogeneity in gene regulatory networks and identify critical regulators of CRC.

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