Transcription group sequencing experiment service

First, transcription group sequencing experimental service introduction Transcriptome, a species or specific cells in some The sum of RNA generated in functional state is an important means of studying cell phenotypes and functions. Unlike the genome, the definition of the transcription group contains the limitations of time and space. The same cells are different in different growth periods and growth environments. Transcription group sequencing (RNA-SEQ) refers to the use of second generation high-throughput sequencing techniques for cDNA sequencing, quickly acquires a certain species specific organ or tissue in a certain state. Compared to traditional chips, RNA-SEQ does not require pre-design probes, which can be detected, which can detect the transcription group of the cell type of the species, and provide a more digital signal, higher detection flux, and a broader detection range. At present, the powerful tools for studying the complexity of transcription groups.

Second, transcription group sequencing experimental service operation flow

1. Full transcript Total RNA extraction; 2. MRNA separation and library construct;

3. High-throughput sequencing; 4. Data processing and biological information analysis;

[123 ] 5. Sequencing Report Generation

Third, Biological Information Analysis

(1) No reference gase sequence transcription group 1. Standard information analysis

1) Remove the joint sequence and low quality reads for raw data;

2) Component and quality assessment of data output statistics and sequencing data; 3) Performance quantitative analysis

4) Analysis of assembly results; [

5) UniGene function notes and COG analysis; GO classification; Pathway analysis; NR analysis; SwissProt analysis

6) UNIGENE expression difference analysis;

7) Expression mode clustering analysis of differential genes

[ 123] 8) GO function enrichment analysis and Pathway enrichment analysis of differentially expressing genes;

9) Protein interaction network analysis of differentially expressed genes; 10) SNP analysis

[ 123] 2. Analysis

Transcription regulatory network analysis, and network diagram construction and important TF analysis;

[ 123] Circular interactive network analysis, important path analysis.

Differentially expression gene co-expression analysis, constructing a network map

Transcription factor activity analysis , Predict important transcription factors; Gene common upstream regulation element prediction

miRNA Predict, predicting important miRNA

(two ) Reference group

1. Standard information analysis

1 Remove joint pollution sequence and low quality READS for raw data 2) Reference genomic ratio

[123 3) Performance of gene expression quantitative analysis

4) variable shearing analysis (eukaryotic)

[ 123] 5) New Transcription This prediction: new mRNA and new lNCRNA prediction

6) Differential expression gene analysis (2 Or 2 or more samples)

7) Expression mode clustering analysis of differential genes

8) GO function enrichment analysis and Kegg Pathway enrichment analysis of different genes

9) Protein interaction network analysis of differential genes 10) SNP analysis

2. Analysis

LNCRNA-mRNA expression association analysis, and network map construction;

[ 123] Transcriptional regulatory network analysis, and network diagram construction and important TF analysis;

Channel interactive network analysis , Important path analysis.

Differentially expression gene co-expression analysis, constructing a network map

Transcription factor activity analysis , Predict important transcription factors;

Gene common upstream regulation element prediction

miRNA It is predicted that the important miRNA

drug is small Molecular prediction analysis (suitable for humans), resulting in pharmaceutical small molecules.

4, sample requirements 1) Sample type: cell, fresh tissue or RNA sample.

2) The amount of sample: Cell sample provides at least 1 u0026 Times; 107 cells, tissue samples, provide at least 300 mg tissue block or slice, RNA sample please Total RNA above G or more. 3) Sample quality: RNA has no obvious degradation, the extraction total RNA OD260 / 280 value is between 1.8 to 2.2, concentration u0026 ge; 500 ng / u0026 mu ; L, 28S: 18S u0026 GE; 1.5, RIN u0026 GE; 8.

4) Sample preservation: cell sample or fresh groupThe fabric block (cut into a small piece) can be treated with Trizol or RNA protective agent or liquid nitrogen survival, -80 ° C.RNA samples are soluble in ultrapure water of ethanol or RNA-Free, and -80 ° C is stored.During the storage period, avoid repeated freeze-thaw. 5) Sample Transport: Samples are placed in 1.5 ml tubes, sealed membranes are sealed, dry ice transport.