RNA-Seq analysis identifies key genes associated with haustorial development in the root hemiparasite Santalum album

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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Comparative Transcriptome Profiling of High and Low oil yielding Santalum album L.

10.1101/2021.05.12.443750 ◽

2021 ◽

Author(s):

Tanzeem Fatima ◽

Rangachari Krishnan ◽

Ashutosh Srivastava ◽

Vageeshbabu S. Hanur ◽

M. Srinivasa Rao

Keyword(s):

Transcriptome Profiling ◽

Santalum Album ◽

Rna Seq ◽

Improvement Program ◽

East Indian ◽

Kegg Pathways ◽

Oil Biosynthesis ◽

Genome Wide ◽

A Genome ◽

Santalum Album L

East Indian Sandalwood (Santalum album L.) is highly valued for its heartwood and its oil. There have been no efforts to comparative study of high and low oil yielding genetically identical sandalwood trees grown in similar climatic condition. Thus we intend to study a genome wide transcriptome analysis to identify the corresponding genes involved in high oil biosynthesis in S. album. In this study, 15 years old S. album (SaSHc and SaSLc) genotypes were targeted for analysis to understand the contribution of genetic background on high oil biosynthesis in S. album. A total of 28,959187 and 25,598869 raw PE reads were generated by the Illumina sequencing. 2.12 million and 1.811 million coding sequences were obtained in respective accessions. Based on the GO terms, functional classification of the CDS 21262, & 18113 were assigned into 26 functional groups of three GO categories; (4,168; 3,641) for biological process (5,758;4,971) cellular component and (5,108;4,441) for molecular functions. Total 41,900 and 36,571 genes were functionally annotated and KEGG pathways of the DEGs resulted 213 metabolic pathways. In this, 14 pathways were involved in secondary metabolites biosynthesis pathway in S. album. Among 237 cytochrome families, nine groups of cytochromes were participated in high oil biosynthesis. 16,665 differentially expressed genes were commonly detected in both the accessions (SaHc and SaSLc). The results showed that 784 genes were upregulated and 339 genes were downregulated in SaHc whilst 635 upregulated 299 downregulated in SaSLc S. album. RNA-Seq results were further validated by quantitative RT-PCR. Maximum Blast hits were found to be against Vitis vinifera. From this study we have identified additional number of cytochrome family in SaHc. The accessibility of a RNA-Seq for high oil yielding sandalwood accessions will have broader associations for the conservation and selection of superior elite samples/populations for further genetic improvement program.

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

10.21203/rs.3.rs-148726/v1 ◽

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.

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RNA-seq analysis revealed key genes associated with salt tolerance in rapeseed germination through carbohydrate metabolism, hormone, and MAPK signaling pathways

Industrial Crops and Products ◽

10.1016/j.indcrop.2021.114262 ◽

2022 ◽

Vol 176 ◽

pp. 114262

Author(s):

Ibrahim A.A. Mohamed ◽

Nesma Shalby ◽

Ali Mahmoud El-Badri ◽

Maria Batool ◽

Chunyun Wang ◽

...

Keyword(s):

Salt Tolerance ◽

Signaling Pathways ◽

Carbohydrate Metabolism ◽

Mapk Signaling ◽

Rna Seq ◽

Key Genes ◽

Mapk Signaling Pathways

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

International Journal of Molecular Sciences ◽

10.3390/ijms20174303 ◽

2019 ◽

Vol 20 (17) ◽

pp. 4303 ◽

Cited By ~ 3

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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Differential regulatory network-based quantification and prioritization of key genes underlying cancer drug resistance based on time-course RNA-seq data

PLoS Computational Biology ◽

10.1371/journal.pcbi.1007435 ◽

2019 ◽

Vol 15 (11) ◽

pp. e1007435 ◽

Cited By ~ 2

Author(s):

Jiajun Zhang ◽

Wenbo Zhu ◽

Qianliang Wang ◽

Jiayu Gu ◽

L. Frank Huang ◽

...

Keyword(s):

Drug Resistance ◽

Regulatory Network ◽

Time Course ◽

Cancer Drug ◽

Rna Seq ◽

Cancer Drug Resistance ◽

Key Genes

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Exploring differentially expressed key genes related to development of follicle by RNA-seq in Peking ducks (Anas Platyrhynchos)

PLoS ONE ◽

10.1371/journal.pone.0209061 ◽

2019 ◽

Vol 14 (6) ◽

pp. e0209061 ◽

Cited By ~ 2

Author(s):

Jindong Ren ◽

Changsen Sun ◽

Li Chen ◽

Jianhong Hu ◽

Xuetao Huang ◽

...

Keyword(s):

Anas Platyrhynchos ◽

Differentially Expressed ◽

Rna Seq ◽

Key Genes

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Characterization and Duodenal Transcriptome Analysis of Chinese Beef Cattle With Divergent Feed Efficiency Using RNA-Seq

Frontiers in Genetics ◽

10.3389/fgene.2021.741878 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chaoyun Yang ◽

Liyun Han ◽

Peng Li ◽

Yanling Ding ◽

Yun Zhu ◽

...

Keyword(s):

Beef Cattle ◽

Differentially Expressed Genes ◽

Feed Intake ◽

Feed Efficiency ◽

Muscle Development ◽

Dietary Factors ◽

Differentially Expressed ◽

Rna Seq ◽

Biological Regulation ◽

Key Genes

Residual feed intake (RFI) is an important measure of feed efficiency for agricultural animals. Factors associated with cattle RFI include physiology, dietary factors, and the environment. However, a precise genetic mechanism underlying cattle RFI variations in duodenal tissue is currently unavailable. The present study aimed to identify the key genes and functional pathways contributing to variance in cattle RFI phenotypes using RNA sequencing (RNA-seq). Six bulls with extremely high or low RFIs were selected for detecting differentially expressed genes (DEGs) by RNA-seq, followed by conducting GO, KEGG enrichment, protein-protein interaction (PPI), and co-expression network (WGCNA, n = 10) analysis. A total of 380 differentially expressed genes was obtained from high and low RFI groups, including genes related to energy metabolism (ALDOA, HADHB, INPPL1), mitochondrial function (NDUFS1, RFN4, CUL1), and feed intake behavior (CCK). Two key sub-networks and 26 key genes were detected using GO analysis of DEGs and PPI analysis, such as TPM1 and TPM2, which are involved in mitochondrial pathways and protein synthesis. Through WGCNA, a gene network was built, and genes were sorted into 27 modules, among which the blue (r = 0.72, p = 0.03) and salmon modules (r = −0.87, p = 0.002) were most closely related with RFI. DEGs and genes from the main sub-networks and closely related modules were largely involved in metabolism; oxidative phosphorylation; glucagon, ribosome, and N-glycan biosynthesis, and the MAPK and PI3K-Akt signaling pathways. Through WGCNA, five key genes, including FN1 and TPM2, associated with the biological regulation of oxidative processes and skeletal muscle development were identified. Taken together, our data suggest that the duodenum has specific biological functions in regulating feed intake. Our findings provide broad-scale perspectives for identifying potential pathways and key genes involved in the regulation of feed efficiency in beef cattle.

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Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.723477 ◽

2022 ◽

Vol 12 ◽

Author(s):

Yan Zhang ◽

Gui-hui Tong ◽

Xu-Xuan Wei ◽

Hai-yang Chen ◽

Tian Liang ◽

...

Keyword(s):

Breast Cancer ◽

T Cell ◽

Signaling Pathway ◽

Therapeutic Efficacy ◽

Normal Tissue ◽

R Package ◽

Rna Seq ◽

Matched Normal Tissue ◽

M1 Macrophage ◽

Key Genes

Background: Breast cancer is one of the deadly tumors in women, and its incidence continues to increase. This study aimed to identify novel therapeutic molecules using RNA sequencing (RNA-seq) data of breast cancer from our hospital.Methods: 30 pairs of human breast cancer tissue and matched normal tissue were collected and RNA sequenced in our hospital. Differentially expressed genes (DEGs) were calculated with raw data by the R package “edgeR”, and functionally annotated using R package “clusterProfiler”. Tumor-infiltrating immune cells (TIICs) were estimated using a website tool TIMER 2.0. Effects of key genes on therapeutic efficacy were analyzed using RNA-seq data and drug sensitivity data from two databases: the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP).Results: There were 2,953 DEGs between cancerous and matched normal tissue, as well as 975 DEGs between primary breast cancer and metastatic breast cancer. These genes were primarily enriched in PI3K-Akt signaling pathway, calcium signaling pathway, cAMP signaling pathway, and cell cycle. Notably, CD8+ T cell, M0 macrophage, M1 macrophage, regulatory T cell and follicular helper T cell were significantly elevated in cancerous tissue as compared with matched normal tissue. Eventually, we found five genes (GALNTL5, MLIP, HMCN2, LRRN4CL, and DUOX2) were markedly corelated with CD8+ T cell infiltration and cytotoxicity, and associated with therapeutic response.Conclusion: We found five key genes associated with tumor progression, CD8+ T cell and therapeutic efficacy. The findings would provide potential molecular targets for the treatment of breast cancer.

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