Eukaryotic mRNA-Seq

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Transcriptome sequencing makes use of high-throughput sequencing technology to comprehensively and rapidly obtain the sequence information of all messenger RNAs within a specific tissue or organ in a species under a certain condition. This approach is widely used across biological disciplines and has many applications.

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Technology Introduction Applications Case Study Project Workflow Information Analysis Content Technical parameters

Technology Introduction

The term transcriptome refers, in a broad sense, to the complete set of all transcription products present in a cell or a group of cells. These include mRNAs, rRNAs, tRNAs, and other non-coding RNAs. In a more narrow sense, the word refers only to the collection of all mRNAs. Eukaryotic transcriptome sequencing leverages advanced next-generation high-throughput sequencing technologies to sequence messenger RNAs from animal and plant samples. In addition to providing valuable insights into the quantitative expression of genes, this approach also enables gene annotation, differential analysis between subgroups, and enrichment analysis. Moreover, it greatly facilitates the analysis of complex mRNA processes, such as variable splicing, and allows for de novo gene prediction.

Applications of Eukaryotic mRNA-Seq

Research on growth and developmental mechanisms of animals and plants
Research on stress resistance in flora and fauna and potential applications
Research on gene expression patterns in different organs

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Case Study

Study Case

Journal: Journal of Agricultural and Food Chemistry

IF: 5.279

Time: 2021.09

Case Study

Research conclusions：

To our knowledge, this is the first study to examine the changes in GABA content, GABA-related metabolite content and enzyme activities of six quinoa varieties at different germination stages (seed, G24, G48 and G72). The molecular mechanism of GABA accumulation during germination in quinoa was explored by transcriptome sequencing. The findings enhance our understanding of the changes in bioactive compounds, particularly GABA, during quinoa germination. Moreover, it provides a solid basis for the development of novel functional foods enriched with GABA.

References：

Zhang Derui,Wei Xiaonan,Liu Ze et al. Chenopodium quinoaTranscriptome Analysis Reveals the Molecular Mechanism of GABA Accumulation during Quinoa ( Willd.) Germination.[J] .J Agric Food Chem, 2021, 69: 12171-12186.

SERVICES

Global Metabolite Profiling

Untargeted Metabolomics

TM Widely-Targeted Metabolomics

Widely-Targeted Metabolomics for Plants

Flavonoids Metabolomics

Targeted Metabolomics

Bile Acid

Energy Metabolism

Tryptophan Targeted Metabolomics

Amino Acid Targeted Metabolomics

Short-Chain Fatty Acids

Plant Hormone Assay

Carotenoid Targeted Metabolomics

Anthocyanin Assay

Gibberellin Assay

Lipidomics

Quantitative Lipidomics

Quantitative Lipidomics for Plants

Proteomics

DIA Quantitative Proteomics

DDA Quantitative Proteomics

Serum/Plasma Quantitative Proteomics

Phosphoproteomics

Multi-Omics

Proteomics + Metabolomics

Microbiome+Metabolome

Transcriptome+Metabolome

Resequencing+Metabolome

Transcriptomics + Proteomics + Metabolomics

Eukaryotic mRNA-Seq

16S rRNA gene Sequencing

Metagenomic Sequencing

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Project Workflow of Eukaryotic mRNA-Seq

Sample Preparation

RNA Library Preparation

Sequencing

Bioinformatics Analysis

Information Analysis Content

	Reference-based transcriptome	Transcriptome with no reference
Expression analysis	Overall gene expression distribution in samples	Overall gene expression distribution in samples
	Inter-sample correlation analysis	Inter-sample correlation analysis
	Differential gene expression analysis	Differential gene expression analysis
	Functional enrichment analysis of differentially expressed genes	Functional enrichment analysis of differentially expressed genes
	GESA enrichment analysis	Weighted correlation network analysis (WGCNA)
	Enrichment analysis (for human, rat, and mouse) based on the DO, DisGeNET, and Reactome databases	Weighted correlation network analysis (WGCNA)
	Protein interaction network analysis
	Weighted correlation network analysis (WGCNA)
Structural analysis	Comparison with the reference genome	Transcriptome data splicing
	Novel transcript prediction	Gene functional annotation (using 7 major databases)
	Alternative splicing analysis	CDS prediction
	Transcription factor annotation	SSR analysis
	Analysis of SNP and InDel variation	Transcription factor annotation
	Gene fusion analysis (human, rat, and mouse

Technical parameters of Eukaryotic mRNA-Seq

Eukaryotic mRNA-Seq
Amount	Plant:≥500mg; Animals; ≥300mg; Cells; ≥5X106; Fungus:≥300mg or5X106
Total RNA	Amount:≥1ug; Volume:≥50ng/ul; RIN:≥6.5
RNA Library	polyA enrichment
Read Length	Paired-end 150 bp
Data Output	6G bases

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WHAT'S NEXT IN OMICS: THE METABOLOME

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