The distinctive features of plant organs are primarily determined by organ-specific gene expression. We analyzed the expression specificity of 8809 genes in 7 organs of Arabidopsis using a cDNA macroarray system. Using relative expression (RE) values between organs, many known and unknown genes specifically expressed in each organ were identified. We also analyzed the organ specificity of various gene groups using the GRE (group relative expression) value, the average of the REs of all genes in a group. Consequently, we found that many gene groups even ribosomal protein genes, have strong organ-specific expression. Clustering of the expression profiles revealed that the 8809 genes were classified into 9 major categories. Although 3451 genes were clustered into the largest category, which showed constitutive gene expression, 266 and 1005 genes were found to be root- and silique-specific genes, respectively. By this clustering, particular gene groups which showed multi-organ-specific expression profiles, such as bud-flower-specific, stem-silique-specific or bud-flower-root-specific profiles, could be effectively identified. From these results, major features of plant organs could be characterized by their distinct profiles of global gene expression. These data of organ-specific gene expression are available at our web site: Arabidopsis thaliana Tissue-Specific Expression Database, ATTED (http://www.atted.bio.titech.ac.jp/).

Download full-text PDF

Source
http://dx.doi.org/10.1093/dnares/11.1.11DOI Listing

Publication Analysis

Top Keywords

gene expression
20
features plant
12
plant organs
12
expression
12
gene groups
12
distinctive features
8
organs characterized
8
gene
8
organ-specific gene
8
genes
8

Similar Publications

Background: Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.

Aim: In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).

Methods And Results: Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes.

View Article and Find Full Text PDF

Effects of miRNAs in inborn error of metabolism and treatment strategies.

Postgrad Med J

January 2025

Department of Pediatric Metabolic Diseases, University of Health Sciences, Ankara Etlik City Hospital, Ankara 06170, Turkey.

Metabolism is the name given to all of the chemical reactions in the cell involving thousands of proteins, including enzymes, receptors, and transporters. Inborn errors of metabolism (IEM) are caused by defects in the production and breakdown of proteins, fats, and carbohydrates. Micro ribonucleic acids (miRNAs) are short non-coding RNA molecules, ⁓19-25 nucleotides long, hairpin-shaped, produced from DNA.

View Article and Find Full Text PDF

Impact of LITAF on Mitophagy and Neuronal Damage in Epilepsy via MCL-1 Ubiquitination.

CNS Neurosci Ther

January 2025

Department of Neurology, School of Medicine, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, China.

Objective: This study aims to investigate how the E3 ubiquitin ligase LITAF influences mitochondrial autophagy by modulating MCL-1 ubiquitination, and its role in the development of epilepsy.

Methods: Employing single-cell RNA sequencing (scRNA-seq) to analyze brain tissue from epilepsy patients, along with high-throughput transcriptomics, we identified changes in gene expression. This was complemented by in vivo and in vitro experiments, including protein-protein interaction (PPI) network analysis, western blotting, and behavioral assessments in mouse models.

View Article and Find Full Text PDF

STMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model.

Brief Bioinform

November 2024

Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.

Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction.

View Article and Find Full Text PDF

Knockout of a testis-specific gene cluster impairs male fertility in the fall armyworm, Spodoptera frugiperda.

Pest Manag Sci

January 2025

Key Laboratory of Plant Protection Resources and Pest Management of the Ministry of Education, Key Laboratory of Integrated Pest Management on the Loess Plateau of Ministry of Agriculture and Rural Affairs, College of Plant Protection, Northwest A&F University, Yangling, China.

Background: The function of some testis-specific genes (TSGs) in model insects have been studied, but their function in non-model insects remains largely unexplored. In the present study, we identified several TSGs in the fall armyworm (FAW), a significant agricultural pest, through comparative transcriptomic analysis. A testis-specific gene cluster (TSGC) comprising multiple functional genes and long non-coding RNAs was found.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!