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Eukaryotic mRNA-Seq

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eukaryotic mrna seq

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.

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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Project Workflow

1

Sample Preparation


2

RNA Library Preparation


3

Sequencing


4

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



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Technical parameters

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


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.


WHAT'S NEXT IN OMICS: THE METABOLOME
WHAT'S NEXT IN OMICS: THE METABOLOME

Please submit a detailed description of your project. We will provide you with a customized project plan metabolomics services to meet your research requests. You can also send emails directly to support-global@metwarebio.com for inquiries.