Ontology highlight
ABSTRACT:
PROVIDER: PRJNA682850 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13205453_1.fastq.gz | Fastqsanger.gz | |||
| SRR13205453_2.fastq.gz | Fastqsanger.gz | |||
| SRR13205454_1.fastq.gz | Fastqsanger.gz | |||
| SRR13205454_2.fastq.gz | Fastqsanger.gz | |||
| SRR13205455_1.fastq.gz | Fastqsanger.gz |
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Project description:Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently have moderately significant number of ESTs has been released into the public domain. Utilization of these ESTs for the oligonucleotide microarrays provides a means to investigate large-scale transcript responses to a variety of developmental and environmental signals, ultimately improving our understanding of plant biology. We have developed a high-density oligonucleotide microarray for peanut using approximately 47,767 publicly available ESTs and tested the utility of this array for expression profiling in a variety of peanut tissues. To identify putatively tissue-specific genes and investigate the utility of this array, we compared transcript levels in pod to peg, leaf, stem, and root tissues. Results from this experiment showed a number of putatively pod-specific/abundant genes, as well as transcripts whose expression was low or undetected in pod compared to either peg, leaf, or stem. Keywords: Peanut tissue-specific gene expression We used Agilent peanut gene chips (017430) to identify putative tissue-specific genes and investigate the utility of the array for expression profiling of various peanut tissues. Pod, leaf, stem, peg and root tissues of the peanut genotype Flavrunner 458 were used in the study. Field grown plants under normal irrigation were used for sample collection. Three replications of microarray experiments were carried out by hybridizing the cRNA from pod tissue and cRNA from leaf, stem, peg and root tissues on the same dual color oligonucleotide arrays.
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Project description:<p>Sophora flavescens (Kushen) is a traditional medicinal plant widely used in East Asia for its anti-inflammatory, antimicrobial, and antitumor properties. Its pharmacological activities are mainly attributed to diverse secondary metabolites, including alkaloids, flavonoids, and phenolic compounds. However, the metabolic differences between distinct tissues remain incompletely characterized.</p><p>In this study, an untargeted metabolomics approach based on liquid chromatography–mass spectrometry (LC–MS) was employed to comprehensively profile the metabolic composition of Sophora flavescens. Root and stem tissues were collected and analyzed to investigate tissue-specific metabolic variations. Metabolite extraction was performed using organic solvent-based protocols, followed by high-resolution LC–MS analysis in both positive and negative ionization modes.</p><p>Multivariate statistical analyses, including principal component analysis (PCA) and differential abundance analysis, were applied to evaluate metabolic differences between tissues. Differentially accumulated metabolites were further annotated and mapped to KEGG pathways to elucidate the biological processes and metabolic pathways underlying tissue-specific metabolite distribution.</p><p>This dataset provides a valuable resource for understanding the metabolic basis of bioactive compound accumulation in Sophora flavescens and supports further studies on medicinal plant metabolomics, functional metabolism, and natural product discovery.</p>
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