scholarly journals Dual species dynamic transcripts reveal the interaction mechanisms between Chrysanthemum morifolium and Alternaria alternata

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lina Liu ◽  
Fadi Chen ◽  
Sumei Chen ◽  
Weimin Fang ◽  
Ye Liu ◽  
...  
Keyword(s):  
Alternaria Alternata ◽  
Interaction Mechanism ◽  
Black Spot ◽  
Chrysanthemum Morifolium ◽  
Potential Interaction ◽  
Late Infection ◽  
Rna Seq ◽  
Key Genes ◽  
Highly Correlated ◽  
Infection Stage

Abstract Background Chrysanthemum (Chrysanthemum morifolium) black spot disease caused by Alternaria alternata is one of the plant’s most destructive diseases. Dual RNA-seq was performed to simultaneously assess their transcriptomes to analyze the potential interaction mechanism between the two species, i.e., host and pathogen. Results C. morifolium and A. alternata were subjected to dual RNA-seq at 1, 12, and 24 h after inoculation, and differential expression genes (DEGs) in both species were identified. This analysis confirmed 153,532 DEGs in chrysanthemum and 14,932 DEGs in A. alternata, which were involved in plant-fungal interactions and phytohormone signaling. Fungal DEGs such as toxin synthesis related enzyme and cell wall degrading enzyme genes played important roles during chrysanthemum infection. Moreover, a series of key genes highly correlated with the early, middle, or late infection stage were identified, together with the regulatory network of key genes annotated in the Plant Resistance Genes database (PRGdb) or Pathogen-Host Interactions database (PHI-base). Highly correlated genes were identified at the late infection stage, expanding our understanding of the interplay between C. morifolium and A. alternata. Additionally, six DEGs each from chrysanthemum and A. alternata were selected for quantitative real-time PCR (qRT-PCR) assays to validate the RNA-seq output. Conclusions Collectively, data obtained in this study enriches the resources available for research into the interactions that exist between chrysanthemum and A. alternata, thereby providing a theoretical basis for the development of new chrysanthemum cultivars with resistance to pathogen.

scholarly journals Dual species dynamic transcripts reveal the interaction mechanisms between Chrysanthemum morifolium and Alternaria alternata

2020 ◽  
Author(s):  
Lina Liu ◽  
Fadi Chen ◽  
Sumei Chen ◽  
Weimin Fang ◽  
Ye Liu ◽  
...  
Keyword(s):  
Alternaria Alternata ◽  
Interaction Mechanism ◽  
Black Spot ◽  
Chrysanthemum Morifolium ◽  
Potential Interaction ◽  
Late Infection ◽  
Rna Seq ◽  
Key Genes ◽  
Highly Correlated ◽  
Infection Stage

Abstract Background: Chrysanthemum (C. morifolium) black spot disease caused by Alternaria alternata is one of the plant’s most destructive diseases. Dual RNA-seq was performed to simultaneously assess their transcriptomes to analyze the potential interaction mechanism between the two species, i.e., host and pathogen. Results: C. morifolium and A. alternata were subjected to dual RNA-seq at 1, 12, and 24 hours after inoculation, and differential expression genes (DEGs) in both species were identified. This analysis confirmed 153,532 DEGs in chrysanthemum and 14,932 DEGs in A. alternata, that were involved in plant-fungal interactions and phytohormone signaling. Fungal DEGs such as toxin synthesis related enzyme and cell wall degrading enzyme genes played important roles during chrysanthemum infecton. Moreover, a series of key genes highly correlated with the early, middle, or late infection stage was identified, together with the regulatory network of key genes annotated in PRG or PPI databases. Highly correlated genes were identified at the late infection stage, expanding our understanding of the interplay between C. morifolium and A. alternata. Additionally, six DEGs each from chrysanthemum and A. alternata were selected for qRT-PCR assays to validate the RNA-seq output. Conclusions: Collectively, data obtained in this study enriches the resources available for research into the interactions that exist between chrysanthemum and A. alternata, thereby providing a theoretical basis for the development of new chrysanthemum cultivars with resistance to pathogen.

scholarly journals Dual species dynamic transcripts reveal the interaction mechanisms between Chrysanthemum morifolium and Alternaria alternata

2020 ◽  
Author(s):  
Lina Liu ◽  
Fadi Chen ◽  
Sumei Chen ◽  
Weimin Fang ◽  
Ye Liu ◽  
...  
Keyword(s):  
Alternaria Alternata ◽  
Interaction Mechanism ◽  
Black Spot ◽  
Chrysanthemum Morifolium ◽  
Potential Interaction ◽  
Late Infection ◽  
Rna Seq ◽  
Key Genes ◽  
Highly Correlated ◽  
Infection Stage

Abstract Background Chrysanthemum (C. morifolium) black spot disease caused by Alternaria alternata is one of the plant’s most destructive diseases. Dual RNA-seq was performed to simultaneously assess their transcriptomes to analyze the potential interaction mechanism between the two species, i.e., host and pathogen. Results C. morifolium and A. alternata were subjected to dual RNA-seq at 1, 12, and 24 hours after inoculation, and differential expression genes (DEGs) in both species were identified. This analysis confirmed 153,532 DEGs in chrysanthemum and 14,932 DEGs in A. alternata, that were involved in plant-fungal interactions and phytohormone signaling. Fungal DEGs such as toxin synthesis related enzyme and cell wall degrading enzyme genes played important roles during chrysanthemum infecton. Moreover, a series of key genes highly correlated with the early, middle, or late infection stage was identified, together with the regulatory network of key genes annotated in PRG or PPI databases. Highly correlated genes were identified at the late infection stage, expanding our understanding of the interplay between C. morifolium and A. alternata. Additionally, six DEGs each from chrysanthemum and A. alternata were selected for qRT-PCR assays to validate the RNA-seq output. Conclusions Collectively, data obtained in this study enriches the resources available for research into the interactions that exist between chrysanthemum and A. alternata, thereby providing a theoretical basis for the development of new chrysanthemum varieties with resistance to pathogen.

scholarly journals Transcriptome Analysis of Responses to Dengue Virus 2 Infection in Aedes albopictus (Skuse) C6/36 Cells

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 343
Author(s):  
Manjin Li ◽  
Dan Xing ◽  
Duo Su ◽  
Di Wang ◽  
Heting Gao ◽  
...  
Keyword(s):  
Dengue Virus ◽  
Aedes Albopictus ◽  
Bioinformatics Analysis ◽  
Interaction Mechanism ◽  
Transcriptional Analysis ◽  
Functional Verification ◽  
Mosquito Vector ◽  
Rna Seq ◽  
Sequencing Data ◽  
Qrt Pcr

Dengue virus (DENV), a member of the Flavivirus genus of the Flaviviridae family, can cause dengue fever (DF) and more serious diseases and thus imposes a heavy burden worldwide. As the main vector of DENV, mosquitoes are a serious hazard. After infection, they induce a complex host–pathogen interaction mechanism. Our goal is to further study the interaction mechanism of viruses in homologous, sensitive, and repeatable C6/36 cell vectors. Transcriptome sequencing (RNA-Seq) technology was applied to the host transcript profiles of C6/36 cells infected with DENV2. Then, bioinformatics analysis was used to identify significant differentially expressed genes and the associated biological processes. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to verify the sequencing data. A total of 1239 DEGs were found by transcriptional analysis of Aedes albopictus C6/36 cells that were infected and uninfected with dengue virus, among which 1133 were upregulated and 106 were downregulated. Further bioinformatics analysis showed that the upregulated DEGs were significantly enriched in signaling pathways such as the MAPK, Hippo, FoxO, Wnt, mTOR, and Notch; metabolic pathways and cellular physiological processes such as autophagy, endocytosis, and apoptosis. Downregulated DEGs were mainly enriched in DNA replication, pyrimidine metabolism, and repair pathways, including BER, NER, and MMR. The qRT-PCR results showed that the concordance between the RNA-Seq and RT-qPCR data was very high (92.3%). The results of this study provide more information about DENV2 infection of C6/36 cells at the transcriptome level, laying a foundation for further research on mosquito vector–virus interactions. These data provide candidate antiviral genes that can be used for further functional verification in the future.

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

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.

scholarly journals Identification of Key Genes Affecting Porcine Fat Deposition Based on Co-Expression Network Analysis of Weighted Genes

2021 ◽  
Author(s):  
Kai Xing ◽  
Huatao Liu ◽  
Fengxia Zhang ◽  
Yibing Liu ◽  
Yong Shi ◽  
...  
Keyword(s):  
Network Analysis ◽  
Production Efficiency ◽  
Fat Deposition ◽  
Rna Seq ◽  
Genetic Studies ◽  
Gene Expression Matrix ◽  
Differential Gene ◽  
Key Genes ◽  
Strong Candidate ◽  
Molecular Regulatory Mechanisms

Abstract Background: Fat deposition is an important economic consideration for pig production. The amount of fat deposition in pigs seriously affects production efficiency, quality, and reproductive performance, while also affecting consumers' choice of pork. Weighted gene co-expression network analysis (WGCNA) has been shown to be effective in pig genetic studies. Therefore, this study aimed to identify modules that co-express genes associated with fat deposition in pigs (Songliao black and Landrace breeds) with extreme levels of backfat (high and low), and to identify the central genes in each of these modules. Results: We used RNA-seq of different pig tissues to construct a gene expression matrix consisting of 12 862 genes from 36 samples. Eleven co-expression modules were identified using WGCNA; the number of genes in these modules ranged from 39 to 3363. We found four co-expression modules were significantly correlated with backfat thickness. A total of 14 genes ( RAD9A , IGF2R , SCAP , TCAP , DGAT1 , GPS2 , IGF1 , MAPK8 , FABP , FABP5 , LEPR , UCP3 , APOF , and FASN ) were found to be related to fat deposition. Conclusions: RAD9A , TCAP , GPS2 , and APOF were found to be the key genes in the four modules according to the degree of gene connectivity. Combining the results of differential gene analysis, APOF was proposed as a strong candidate gene for body size traits. This study explores the key genes that regulate porcine fat deposition and lays the foundation for further research into the molecular regulatory mechanisms behind porcine fat deposition.

scholarly journals Transcriptome Analysis Reveals Key Seed-Development Genes in Common Buckwheat (Fagopyrum esculentum)

2019 ◽  
Vol 20 (17) ◽  
pp. 4303 ◽  
Author(s):  
Hongyou Li ◽  
Qiuyu Lv ◽  
Jiao Deng ◽  
Juan Huang ◽  
Fang Cai ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Seed Development ◽  
Seed Size ◽  
Molecular Mechanisms ◽  
Signal Transduction Pathway ◽  
Fagopyrum Esculentum ◽  
Rna Seq ◽  
Common Buckwheat ◽  
Size Change ◽  
Key Genes

Seed development is an essential and complex process, which is involved in seed size change and various nutrients accumulation, and determines crop yield and quality. Common buckwheat (Fagopyrum esculentum Moench) is a widely cultivated minor crop with excellent economic and nutritional value in temperate zones. However, little is known about the molecular mechanisms of seed development in common buckwheat (Fagopyrum esculentum). In this study, we performed RNA-Seq to investigate the transcriptional dynamics and identify the key genes involved in common buckwheat seed development at three different developmental stages. A total of 4619 differentially expressed genes (DEGs) were identified. Based on the results of Gene Ontology (GO) and KEGG analysis of DEGs, many key genes involved in the seed development, including the Ca2+ signal transduction pathway, the hormone signal transduction pathways, transcription factors (TFs), and starch biosynthesis-related genes, were identified. More importantly, 18 DEGs were identified as the key candidate genes for seed size through homologous query using the known seed size-related genes from different seed plants. Furthermore, 15 DEGs from these identified as the key genes of seed development were selected to confirm the validity of the data by using quantitative real-time PCR (qRT-PCR), and the results show high consistency with the RNA-Seq results. Taken together, our results revealed the underlying molecular mechanisms of common buckwheat seed development and could provide valuable information for further studies, especially for common buckwheat seed improvement.

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