1. NGS Transcriptomic Workflows Hugh Shanahan & Jamie al-Nasir Royal Holloway, University of London

2.  Transcriptome – total sequence and abundance of RNA generated by a cell  RNA is transcribed from DNA  Genome is fixed for a organism  Transcriptome is dynamic  Variation between tissues  Variation over time  RNA transcripts are 1,000’s-10,000 bases in length Setting the scene

3.  Interested in  How many copies of a particular transcript are there  What is the sequence  - sequence comes from genome but alternative splicing means a transcript may not just be a contiguous block of DNA

4. Size of transcriptome will vary between species

5.  Fragment transcripts into shorter pieces (reads)  100-300 bases longs  Have many overlapping reads  Amplify (make lots of copies of) the short reads  Can sequence these short reads and then assemble them to reconstruct transcripts.  Size of data set depends on size of transcriptome but also amount of fragmentation (sequencing depth)  Can either assemble with a reference genome or de novo (very hard) Sequencing steps

6. NGS Workflow

8.  File formats have been updated to binary – used to use flat text so sizes were huge (Reference Genome – 39 Gbyte -> 0.8 Gybte)  Raw image data is actually discarded  Discussions focusses on assembly and down-stream analysis  Much of this data is deposited in the Sequence Read Archive (SRA)  We’ve papered over everything that happens before sequencing – i.e. the biochemical steps carried out  This is highly variable  These steps are not properly annotated Final points