H > ¼ºñ½º > Next-Generation Sequencing (NGS) > RNA-Seq(Transcriptome)
RNA-Seq(Transcriptome)
Prokaryotes RNA-Seq (Transcriptome)
Àû¿ëºÐ¾ß
- Transcriptome ½ÃÄö½Ì (>95% coverage)
- novel coding / non-coding RNA ¹ß±¼
- gene structural analysis (alternative splicing, fusion genes)
- transcriptome ³»ÀÇ SNP ºÐ¼®
- differential gene expression analysis
½ÇÇè Workflow
Bioinformatics ºÐ¼® Workflow
RNA-Seq(Transcriptome)-½ÇÇè ÁøÇà °úÁ¤
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 | |
---|---|
1Â÷ ºÐ¼® | 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 |
2Â÷ ºÐ¼® | 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) |
3Â÷ ºÐ¼® | º°µµ ³íÀÇ |