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RNA-Seq(quantification)
RNA-Seq (Quantification)?
RNA-Seq(Quantification)은 실험 생물체내에서 발현되는 유전자의 발현 변화를 가장 손쉽고 부담없이 분석할 수 있는 방법입니다.
이미 알려져 있는 reference sequence와 비교하여, 실제 샘플로 부터 추출된 total RNA를 직접 sequencing한 결과를 이용하므로,
실험 재현성과 반복성이 매우 높은 방법입니다.
적용분야
- differential gene expression analysis
실험 Workflow
Bioinformatics 분석 Workflow
RNA-Seq(Transcriptome)-실험 진행 과정
Sample requirements
| concentration | Concentration (ng/㎕) | Quality | |
|---|---|---|---|
| Total RNA | > 2㎍ (human, mouse, rat) > 5㎍ (other animals) |
> 80 (human, mouse, rat) > 200 (other animals) |
OD(260/230) > 2.0, OD(260/280)>1.8 is highly recommended |
Sequencing Strategy
| 50 SE sequencing |
Bioinformatic analysis - contents
| RNA-Seq(Transcriptome)-resequencing | |
|---|---|
| 1차 분석 | 1. Data filtering includes removing adaptors, contamination and low-quality reads from raw reads
2. Assessment of sequencing（Statistics of raw reads, Sequencing saturation analysis, Analysis of the distribution of reads on reference gene） 3. Gene expression annotation |
| 2차 분석 | 4. Differential gene expression analysis (Screening of differentially expressed genes(DEGs), Experimental repeatability analysis of DEGs. 5. Expression pattern analysis of DEGs (Client to determine what conditions to meet to perform cluster analysis, for example, "hormone treatment in 2 hours, 4 hours, 8 hours showed a significant difference of gene expression") 6. Gene ontology analysis of DEGs 7. Pathway enrichment analysis of DEGs 8. Protein-protein interaction network analysis (protein-protein interaction database of the target species needed) |
| 3차 분석 | 별도 논의 |
