Shanghai RNA-SEQ experiment

Shanghai RNA-SEQ experiment high-throughput sequencing technology, that is, the next generation of sequencing technology has become a more conventional experimental means of modern biology research. The development of this technology promotes the study of genomics, apparent genomics, and translation. RNA-SEQ is studied by measuring the sequence of RNA samples in a stable state, thereby avoiding many of the lack of research methods prior to research, such as genetics, or PCRs require background knowledge. Moreover, RNA-SEQ can also touch the area where you can't study, such as complex structures. Shanghai RNA-SEQ experiments can be applied to the following aspects, 1. SNPS; 2. Novel Transcripts; 3. Alternative splicing; 4. RNA Editing. In any case, the use of RNA-SEQ is more than comparing the difference in expression of the two groups of sample genes, such as wild-type and mutation type, pharmaceutical group and control group, different tissues, cancer cells and normal cells, and so on. We have different levels of genetically horizontal, referred to as DE (DiffERENTIAL Expression, Note, not ED ah ???).

Common Shanghai RNA-SEQ experiment operation platform has Illumina Ga / Hiseq, Solid and Roche 454. They are all after extracting RNA, purify, break, reverse into cDNA, and then sequen. The results of the sequencing are called Short Reads, short sequences. Typically a short range of 25-300 bp. If the sequencing only one end may bring a comparative compassion, these operational platforms provide both ends of the measures, such results are pairs, intermediate intervals, but because the sequencing length is doubled Therefore, there is a lot of comparisons. This sequencing results are called u0026 rsquo; paired-end u0026 rsquo; reads, pair of short prices. In general, sequencing results are directly converted into a row of short sequences, which may be FASTA, FASTQ, and so on.

Generally, the workflow of DE after RNA-SEQ experiment is such (Fig. 1), first, the short range is mapped to the genome corresponding position, secondly, the genetically level of the mapping , The level of exon level, and the stitching of transcriptional levels, and then generate statistics on the results, after normalization, the expression level report document is generated, and the data results are analyzed by biologists according to system biological knowledge.

RNA-SEQ analysis workflow

service content: big data analysis, overall decomposition, real experimental data, complete Experimental report and analysis.