ArticleGenes & genomics2018
Transcriptome analysis for identifying possible gene regulations during maize root emergence and formation at the initial growth stage.
Article in Genes & genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 22 citations in OpenAlex.
- Transcriptome analysis reveals key regulatory genes for root growth related to potassium utilization efficiency in rapeseed (Frontiers in plant science · 2023Article
- Network-based inference of master regulators in epithelial membrane protein 2-treated human RPE cells.BMC genomic data · 2022Article
- GWAS and WGCNA uncover hub genes controlling salt tolerance in maize (Zea mays L.) seedlings.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed.Biotechnology for biofuels · 2021Article
- Glyceroglycolipid Metabolism Regulations under Phosphate Starvation Revealed by Transcriptome Analysis inMarine drugs · 2020Article
- Effect of X-rays on transcript expression of rat brain microvascular endothelial cells: role of calcium signaling in X-ray-induced endothelium damage.Bioscience reports · 2020Article
- Effect of oxLDL on transcriptional expression of human lens epithelial cells.International journal of clinical and experimental pathology · 2020Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The root plays an important role during plant development and growth, i.e., the plant body maintenance, nutrient storage, absorption of water, oxygen and nutrient from the soil, and storage of water and carbohydrates, etc. The objective of this study was attempted to determine root-specific genes at the initial developmental stages of maize by using network-based transcriptome analysis. The raw data obtained using RNA-seq were filtered for quality control of the reads with the FASTQC tool, and the filtered reads were pre-proceed using the TRIMMOMATIC tool. The enriched BINs of the DEGs were detected using PageMan analysis with the ORA_FISHER statistical test, and genes were assigned to metabolic pathways by using the MapMan tool, which was also used for detecting transcription factors (TFs). For reconstruction of the co-expression network, we used the algorithm for the reconstruction of accurate cellular networks (ARACNE) in the R package, and then the reconstructed co-expression network was visualized using the Cytoscape tool. RNA-seq. was performed using maize shoots and roots at different developmental stages of root emergence (6-10 days after planting, VE) and 1 week after plant emergence (V2). A total of 1286 differentially expressed genes (DEGs) were detected in both tissues. Many DEGs involved in metabolic pathways exhibited altered mRNA levels between VE and V2. In addition, we observed gene expression changes for 113 transcription factors and found five enriched cis-regulatory elements in the 1-kb upstream regions of both DEGs. The network-based transcriptome analysis showed two modules as co-expressed gene clusters differentially expressed between the shoots and roots during plant development. The DEGs of one module exhibited gene expressional coherence in the maize root tips, suggesting that their functional relationships are associated with the initial developmental stage of the maize root. Finally, we confirmed reliable mRNA levels of the hub genes in the potential sub-network related to initial root development at the different developmental stages of VE, V2, and 2 weeks after plant emergence.
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