Ali, A.

We developed plant (Parallel Annotation of Transcriptomes), a de novo method that can potentially compare RNA-seq data of any two species without a reference genome. plant is conceptually similar to chromatography. In the same way a complex mixture is filtered to isolate its individual components, we applied a computational method to identify, annotate, and quantify components across transcriptomes. The comparison points are universal protein domain annotations rather than species-specific genes, as would be the case for a differential gene expression analysis. We looked at several Selaginella species via the 1000 Plant transcriptomes initiative (1KP) where RNA-seq data for various plant species have been made publicly available. The raw reads were assembled via Trinity. The assembled transcripts were then searched against the Pfam protein domain database via InterProScan. The assembled transcripts were also quantified via kallisto. By merging these two aspects, we were able to see how often a predicted protein structure is expressed. These quantified annotations of protein domains are comparable across species, assuming a relatively short evolutionary distance. We were also able to identify the presence of species-specific protein domains and trace each annotation back to the gene. A bubble plot was created to visualize the distributions of Pfam annotations across species as well as GO terms.