
High-throughput RNA sequencing permits the analysis of complete eukaryotic and prokaryotic transcriptoms without prior sequence information. Various library preparation and sequencing protocols can be used and combined for different applications, like e.g., detection of novel and rare transcripts, SNP discovery or quantitative expression analyses. Take advantage of GATCs expertise and state-of-the-art sequencing technologies to specifically answer your scientific question.
= Roche GS FLX+ or Pacific Biosciences PacBio RS | long reads for the de novo assembly and analysis of full length transcripts
+ optional: cDNA normalization to reduce complexity and enhance gene discovery rate
+ made-to-measure bioinformatics for every budget: From raw data via the assembly or clustering right through to the gene identification by BLAST
= Illumina HiSeq 2000 | single or paired end reads for SNP discovery and expression analyses
+ optional: preparation of 3’- or 5’-UTR libraries to specifically focus on the information-rich untranslated regions and to increase the depth of sequencing
+ made-to-measure bioinformatics for every budget: From raw data via the mapping right through to SNP analysis or expression profiling
Identification and quantification of transcripts which are not detectable with commercial arrays through combination of different library preparation methods and sequencing technologies
1. Pooling of poly(A)+ RNA from four samples and generation of one normalized cDNA library
2. Sequencing using the GS FLX Titanium protocol
3. Clustering of resulting sequences
4. Blast of cluster representatives against known ESTs for gene identification
5. Generation of four non-normalized cDNA libraries with four different barcodes
6. Sequencing of the four tagged and pooled samples with Illumina technology (36bp single end)
7. Mapping of the Illumina reads to the GS FLX sequence data for quantitative expression analyses
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Genomics & Transcriptomes
Analyses & Visualisation
On the path to a deep understanding of the organism, two parameters are important to the interpretation of the Next Gen sequencing data: The use of various Next Gen systems to take advantage of each technology and the combination of different bioinformatic tools and their stepwise application.
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