We identify novel interferon stimulated transcripts and genes. We also found elongation of poly(A) tails of genes encoding ribosomal proteins in response to interferon stimulation (but not influenza infection), indicating this may be an important part of the innate immune response.

As well as enriching for target host transcripts, we also show that it can be used to enrich for viral transcripts in infected cells, in this case SARS-Cov2

And can be used investigate differential isoform usage

The method provides ~10 fold enrichment across a range of different expression levels

Even though we had a relatively small sample size (12), we also looked to find potential polyadenylation biomarkers of bacterial vs viral infection. Left panel shows normal gene expression count based biomarkers (reflecting what we saw with larger cDNA-seq study), right panel shows polyA biomarkers

After filtering likely artefacts, we found a modest number (594) of new transcript isoforms, including 9 new isoforms for IGLL5. We also looked for differential transcript usage, and found 4 genes with statistically significant differential transcript usage between bacterial and viral infection

We asked whether polyadenylation varied by pathway/function. This plot shows polyA tails of transcripts in significant GO molecular functions in a gene set enrichment analysis for median tail length (excluding mitochondrial genes)

Firstly we wanted to see if dRNA sequencing based gene counts were similar to cDNA based gene counts. The answer depends a lot on which analysis pipeline you use. Algorithms which use expectation maximisation seem to be better correlated (e.g. nanocount with kallisto)

Was inspiring to attend the TBunion conference in Bali last week and learn about the great TB research happening all over the world. Probably one of the most international conferences I have been to (in terms of number of countries represented)